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Kang JG, Park JH, Park MS, Han K, Lee HS, Yang HK. Differentiation of intrapancreatic accessory spleen from pancreatic neuroendocrine tumor using MRI R2. Abdom Radiol (NY) 2025:10.1007/s00261-024-04758-y. [PMID: 39841231 DOI: 10.1007/s00261-024-04758-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2024] [Revised: 12/09/2024] [Accepted: 12/10/2024] [Indexed: 01/23/2025]
Abstract
PURPOSE To evaluate the performance of R2* in distinguishing intrapancreatic accessory spleens (IPASs) from pancreatic neuroendocrine tumors (PNETs). METHODS Two radiologists (R1 and R2) retrospectively reviewed the MRIs of 20 IPAS and 20 PNET patients. IPASs were diagnosed with uptake on 99mTc labeled heat-damaged red blood cell scintigraphy or characteristic findings on CT/MRI and ≥ 12 month-long-stability. PNETs were histopathologically diagnosed with resection. Using McNemar test, sensitivities and specificities of the diagnostic criterion based on R2* mass-to-spleen ratio (MSR) were compared with those of the other criteria using contrast-enhanced (CE) MRI and apparent diffusion coefficient (ADC) MSR. RESULTS The study included 40 patients (median age, 54; interquartile range, 43-65; 24 men, 16 women). IPASs exhibited spleen-isointensity on T2WI, late arterial and portal phases, and diffusion-weighted images more frequently than PNETs (p <.05). ADC MSRs were lower (p <.001) and R2* MSRs were higher (p <.001) in IPASs compared to PNETs. For R1, sensitivity and specificity were 45.0% and 100.0% for criterion 1 (spleen-isointensity on CE-MRI); 45.0% and 85.0% for criterion 2 (ADC MSR ≤ 1.08); 90.0% and 95.0% for criterion 3 (0.9 ≤ R2* MSR ≤ 1.7). For R2, 75.0% and 100.0%; 45.0% and 90.0%; 90.0% and 100.0%. Criterion 3 showed higher sensitivity than criterion 1 for R1 (p =.004), and criterion 2 for R1 and R2 (p =.012). There was no difference in specificity. CONCLUSION For differentiating IPAS from PNET, R2* showed higher sensitivity than, and similar specificity to CE-MRI and ADC.
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Affiliation(s)
- Jun Gu Kang
- Severance Hospital, Seoul, Republic of Korea
| | | | - Mi-Suk Park
- Severance Hospital, Seoul, Republic of Korea
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Chen R, Su Q, Li Y, Shen P, Zhang J, Tan Y. Multi-sequence MRI-based radiomics model to preoperatively predict the WHO/ISUP grade of clear Cell Renal Cell Carcinoma: a two-center study. BMC Cancer 2024; 24:1176. [PMID: 39333970 PMCID: PMC11438199 DOI: 10.1186/s12885-024-12930-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2024] [Accepted: 09/10/2024] [Indexed: 09/30/2024] Open
Abstract
OBJECTIVES To develop radiomics models based on multi-sequence MRI from two centers for the preoperative prediction of the WHO/ISUP grade of Clear Cell Renal Cell Carcinoma (ccRCC). METHODS This retrospective study included 334 ccRCC patients from two centers. Significant clinical factors were identified through univariate and multivariate analyses. MRI sequences included Dynamic contrast-enhanced MRI, axial fat-suppressed T2-weighted imaging, diffusion-weighted imaging, and in-phase/out-of-phase images. Feature selection methods and logistic regression (LR) were used to construct clinical and radiomics models, and a combined model was developed using the Rad-score and significant clinical factors. Additionally, seven classifiers were used to construct the combined model and different folds LR was used to construct the combined model to evaluate its performance. Models were evaluated using receiver operating characteristic (ROC) curves, area under the curve (AUC), and decision curve analysis (DCA). The Delong test compared ROC performance, with p < 0.050 considered significant. RESULTS Multivariate analysis identified intra-tumoral vessels as an independent predictor of high-grade ccRCC. In the external validation set, the radiomics model (AUC = 0.834) outperformed the clinical model (AUC = 0.762), with the combined model achieving the highest AUC (0.855) and significantly outperforming the clinical model (p = 0.003). DCA showed that the combined model had a higher net benefit within the 0.04-0.54 risk threshold range than clinical model. Additionally, the combined model constructed using logistic regression has a higher priority compared to other classifiers. Additionally, 10-fold cross-validation with LR for the combined model showed consistent AUC values (0.849-0.856) across different folds. CONCLUSION The radiomics models based on multi-sequence MRI might be a noninvasive and effective tool, demonstrating good efficacy in preoperatively predicting the WHO/ISUP grade of ccRCC.
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Affiliation(s)
- Ruihong Chen
- Department of Radiology, First Hospital of Shanxi Medical University, No. 85 Jiefang South Road, Taiyuan, Shanxi Province, 030001, P.R. China
- Department of College of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi Province, 030001, P.R. China
| | - Qiaona Su
- Department of Radiology, Shanxi Province Cancer Hospital/ Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/ Cancer Hospital Affiliated to Shanxi Medical University, No. 3 Workers' New Street, Taiyuan, Shanxi Province, 030013, P.R. China
- Department of College of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi Province, 030001, P.R. China
| | - Yangyang Li
- Department of Radiology, First Hospital of Shanxi Medical University, No. 85 Jiefang South Road, Taiyuan, Shanxi Province, 030001, P.R. China
- Department of College of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi Province, 030001, P.R. China
| | - Pengxin Shen
- Department of Radiology, First Hospital of Shanxi Medical University, No. 85 Jiefang South Road, Taiyuan, Shanxi Province, 030001, P.R. China
- Department of College of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi Province, 030001, P.R. China
| | - Jianxin Zhang
- Department of Radiology, Shanxi Province Cancer Hospital/ Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences/ Cancer Hospital Affiliated to Shanxi Medical University, No. 3 Workers' New Street, Taiyuan, Shanxi Province, 030013, P.R. China.
| | - Yan Tan
- Department of Radiology, First Hospital of Shanxi Medical University, No. 85 Jiefang South Road, Taiyuan, Shanxi Province, 030001, P.R. China.
- Department of Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province, 030001, P.R. China.
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Zhu Q, Sun J, Ye J, Zhu W, Chen W. Comparison of conventional diffusion-weighted imaging and intravoxel incoherent motion in differentiating between chromophobe renal cell carcinoma and renal oncocytoma: a preliminary study. Br J Radiol 2024; 97:1146-1152. [PMID: 38688580 PMCID: PMC11135799 DOI: 10.1093/bjr/tqae088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 03/06/2024] [Accepted: 04/27/2024] [Indexed: 05/02/2024] Open
Abstract
OBJECTIVE Quantitative comparison of the diagnostic efficacy of conventional diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) in differentiating between chromophobe renal cell carcinoma (ChRCC) from renal oncocytoma (RO). METHODS A total of 48 patients with renal tumours who had undergone DWI and IVIM were divided into two groups-ChRCC (n = 28) and RO (n = 20) groups, and the apparent diffusion coefficient (ADC), true diffusivity (D), pseudo-diffusion coefficient (D*), perfusion fraction (f) and their diagnostic efficacy were compared between the two groups. RESULTS The D* values were higher in the ChRCCs group compared to the RO groups (0.019 ± 0.003 mm2/s vs 0.008 ± 0.002 mm2/s, P < .05). Moreover, the ADC, D and f values were higher in ROs compared to ChRCCs (0.61 ± 0.08 × 10-3 mm2/s vs 0.51 ± 0.06 × 10-3 mm2/s, 1.02 ± 0.15 × 10-3 mm2/s vs 0.86 ± 0.07 × 10-3 mm2/s, 0.41 ± 0.05 vs 0.28 ± 0.02, P < .05). The areas of the ADC, D, D* and f values under the ROC curves in differentiating ChRCCs from ROs were 0.713, 0.839, 0.856 and 0.906, respectively. The cut-off values of ADC, D, D* and f were 0.54, 0.91, 0.013 and 0.31, respectively. The AUC, sensitivity, specificity and accuracy of the f values were 0.906, 89.3%, 80.0% and 89.6%, respectively. For pairwise comparisons of ROC curves and diagnostic efficacy, IVIM parameters, that is, D, D* and f offered better diagnostic accuracy than ADC in differentiating ChRCCs from ROs (P = .013, .016, and .008) with f having the highest diagnostic accuracy. CONCLUSION IVIM parameters presented better performance than ADC in differentiating ChRCCs from ROs. ADVANCES IN KNOWLEDGE (1) D* values of ChRCCs were higher, while ADC, D and f values were lower than those of RO tumours. (2) f values had the highest diagnostic efficacy in differentiating ChRCC from RO. (3) IVIM parameters, that is, D, D* and f offered better diagnostic accuracy than ADC in differentiating ChRCC from RO (P=.013, .016, and .008).
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Affiliation(s)
- Qingqiang Zhu
- Northern Jiangsu People's Hospital Affiliated to Yangzhou University, Yangzhou 225001, China
| | - Jun Sun
- Northern Jiangsu People's Hospital Affiliated to Yangzhou University, Yangzhou 225001, China
| | - Jing Ye
- Northern Jiangsu People's Hospital Affiliated to Yangzhou University, Yangzhou 225001, China
| | - Wenrong Zhu
- Northern Jiangsu People's Hospital Affiliated to Yangzhou University, Yangzhou 225001, China
| | - Wenxin Chen
- Northern Jiangsu People's Hospital Affiliated to Yangzhou University, Yangzhou 225001, China
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He K, Wan D, Li S, Yuan G, Gao M, Han Y, Li Z, Hu D, Meng X, Niu Y. Non-contrast-enhanced magnetic resonance urography for measuring split kidney function in pediatric patients with hydronephrosis: comparison with renal scintigraphy. Pediatr Nephrol 2024; 39:1447-1457. [PMID: 38041747 DOI: 10.1007/s00467-023-06224-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 11/01/2023] [Accepted: 11/02/2023] [Indexed: 12/03/2023]
Abstract
BACKGROUND Split kidney function (SKF) is critical for treatment decision in pediatric patients with hydronephrosis and is commonly measured using renal scintigraphy (RS). Non-contrast-enhanced magnetic resonance urography (NCE-MRU) is increasingly used in clinical practice. This study aimed to investigate the feasibility of using NCE-MRU as an alternative to estimate SKF in pediatric patients with hydronephrosis, compared to RS. METHODS Seventy-five pediatric patients with hydronephrosis were included in this retrospective study. All patients underwent NCE-MRU and RS within 2 weeks. Kidney parenchyma volume (KPV) and texture analysis parameters were obtained from T2-weighted (T2WI) in NCE-MRU. The calculated split KPV (SKPV) percent and texture analysis parameters percent of left kidney were compared with the RS-determined SKF. RESULTS SKPV showed a significant positive correlation with SKF (r = 0.88, p < 0.001), while inhomogeneity was negatively correlated with SKF (r = - 0.68, p < 0.001). The uncorrected and corrected prediction models of SKF were established using simple and multiple linear regression. Bland-Altman plots demonstrated good agreement of both predictive models. The residual sum of squares of the corrected prediction model was lower than that of the uncorrected model (0.283 vs. 0.314) but not statistically significant (p = 0.662). Subgroup analysis based on different MR machines showed correlation coefficients of 0.85, 0.95, and 0.94 between SKF and SKPV for three different scanners, respectively (p < 0.05 for all). CONCLUSIONS NCE-MRU can be used as an alternative method for estimating SKF in pediatric patients with hydronephrosis when comparing with RS. Specifically, SKPV proves to be a simple and universally applicable indicator for predicting SKF.
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Affiliation(s)
- Kangwen He
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Dongyi Wan
- Department of Nuclear Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Shichao Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Guanjie Yuan
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Mengmeng Gao
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yunfeng Han
- Department of Nuclear Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zhen Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Daoyu Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiaoyan Meng
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
| | - Yonghua Niu
- Department of Pediatric Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
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Zhou M, Huang H, Fan Y, Chen M, Li M, Wang Y. The application of quantitative perfusion analysis of golden-angle radial sparse parallel MRI and R2∗ value for predicting pathological prognostic factors in rectal cancer. Clin Radiol 2024; 79:124-132. [PMID: 38030505 DOI: 10.1016/j.crad.2023.10.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 10/25/2023] [Accepted: 10/27/2023] [Indexed: 12/01/2023]
Abstract
AIM To investigate the diagnostic value of golden-angle radial sparse parallel magnetic resonance imaging (MRI) (GRASP) and R2∗ in predicting the prognostic factors of resectable rectal cancer. MATERIALS AND METHODS A total of 108 patients with rectal adenocarcinoma were included in this retrospective study. The volume transfer constant (Ktrans), rate constant (Kep), plasma volume fraction (Ve), and R2∗ were obtained. Univariate and multivariate logistic regression were conducted. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of the imaging parameters. RESULTS The Ktrans was found to be significantly higher in rectal cancers with positive lymph node metastasis (LNM), higher tumour grade, positive lymphovascular invasion (LVI), and higher ki-67 (all p<0.05). The Kep was also significantly higher in the LNM-positive group (p<0.001), while the R2∗ was higher in rectal cancers with LNM-positive, higher tumour grade, LVI-positive, and higher ki-67 (all p<0.05). Combining the Ktrans and R2∗ provided the highest area under the ROC curve (AUC) for LNM-positive and higher ki-67 tumours differentiation (0.790 and 0.823, respectively). DISCUSSION Combining quantitative parameters of the Ktrans and R2∗ could be used to non-invasively predict pathological prognostic factors preoperatively.
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Affiliation(s)
- M Zhou
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - H Huang
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - Y Fan
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - M Chen
- Department of MR Scientific Marketing, Siemens Healthineers, Shanghai, 200135, China
| | - M Li
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - Y Wang
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China.
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Pan L, Chen M, Sun J, Jin P, Ding J, Cai P, Chen J, Xing W. Prediction of Fuhrman grade of renal clear cell carcinoma by multimodal MRI radiomics: a retrospective study. Clin Radiol 2024; 79:e273-e281. [PMID: 38065776 DOI: 10.1016/j.crad.2023.11.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 10/16/2023] [Accepted: 11/05/2023] [Indexed: 01/02/2024]
Abstract
AIM To explore the value of multimodal magnetic resonance imaging (MRI) radiomics combined with traditional radiologist-defined semantic characteristics and conventional (cMRI) and functional MRI (fMRI) texture features in predicting Fuhrman grade of clear cell renal cell carcinoma (ccRCC). MATERIALS AND METHODS The data of 89 patients with histopathologically proven ccRCC (low-grade, 54; high-grade, 35) were collected. Texture features were extracted from cMRI (T1- and T2-weighted imaging) and fMRI (Dixon-MRI; blood-oxygen-level dependent [BOLD]-MRI; and susceptibility-weighted imaging [SWI]) images, and the traditional characteristics (TC) were evaluated. Logistic regression analysis was performed to develop models based on TC, cMRI, and fMRI texture features for grading. Receiver operating characteristic (ROC) curve analysis and leave-group-out cross-validation (LGOCV) were performed to test the reliability of combined models. RESULTS Two T2-weighted imaging-based, two Dixon_W-based, one Dixon_F-based, one BOLD-based, and three SWI-based texture features, and three TC were extracted for feature selection. TC, cMRI, fMRI, cMRI+fMRI, cMRI+TC, fMRI+TC, and cMRI+fMRI+TC models were constructed. The AUC of the cMRI+fMRI+TC model for differentiating high- from low-grade ccRCC was 0.74, with 81.42% accuracy, 75.93% sensitivity, and 91.43% specificity. The fMRI+TC model exhibited a performance similar to that of the cMRI+fMRI+TC model (p>0.05). The areas under the curve (AUCs) of the fMRI+TC and cMRI+fMRI+TC models were significantly higher than those of the other five models (all p<0.05). For the cMRI+fMRI+TC model, the mean accuracy was 85.40% after 100 LGOCV for the test sets. CONCLUSION Multimodal MRI radiomics combined with TC, cMRI, and fMRI texture features may be a reliable quantitative approach for differentiating high-grade ccRCC from low-grade ccRCC.
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Affiliation(s)
- L Pan
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou 213003, Jiangsu, China
| | - M Chen
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou 213003, Jiangsu, China
| | - J Sun
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou 213003, Jiangsu, China
| | - P Jin
- Department of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China
| | - J Ding
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou 213003, Jiangsu, China
| | - P Cai
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou 213003, Jiangsu, China
| | - J Chen
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou 213003, Jiangsu, China.
| | - W Xing
- Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou 213003, Jiangsu, China.
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Cheng Q, Ren A, Xu X, Meng Z, Feng X, Pylypenko D, Dou W, Yu D. Application of DKI and IVIM imaging in evaluating histologic grades and clinical stages of clear cell renal cell carcinoma. Front Oncol 2023; 13:1203922. [PMID: 37954085 PMCID: PMC10637387 DOI: 10.3389/fonc.2023.1203922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 10/09/2023] [Indexed: 11/14/2023] Open
Abstract
Purpose To evaluate the value of quantitative parameters derived from diffusion kurtosis imaging (DKI) and intravoxel incoherent motion (IVIM) in differentiating histologic grades and clinical stages of clear cell renal cell carcinoma (ccRCC). Materials and methods A total of 65 patients who were surgically and pathologically diagnosed as ccRCC were recruited in this study. In addition to routine renal magnetic resonance imaging examination, all patients underwent preoperative IVIM and DKI. The corresponding diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), mean diffusivity (MD), kurtosis anisotropy (KA), and mean kurtosis (MK) values were obtained. Independent-samples t-test or Mann-Whitney U test was used for comparing the differences in IVIM and DKI parameters among different histologic grades and clinical stages. The diagnostic efficacy of IVIM and DKI parameters was evaluated using the receiver operating characteristic (ROC) curve. Spearman's correlation analysis was used to separately analyze the correlation of each parameter with histologic grades and stages of ccRCC. Results The D and MD values were significantly higher in low-grade ccRCC than high-grade ccRCC (all p < 0.001) and in low-stage than high-stage ccRCC (all p < 0.05), and the f value of high-stage ccRCC was lower than that of low-stage ccRCC (p = 0.007). The KA and MK values were significantly higher in low-grade than high-grade ccRCC (p = 0.000 and 0.000, respectively) and in low-stage than high-stage ccRCC (p = 0.000 and 0.000, respectively). The area under the curve (AUC) values of D, D*, f, MD, KA, MK, DKI, and IVIM+DKI values were 0.825, 0.598, 0.626, 0.792, 0.750, 0.754, 0.803, and 0.857, respectively, in grading ccRCC and 0.837, 0.719, 0.710, 0.787, 0.796, 0.784, 0.864, 0.823, and 0.916, respectively, in staging ccRCC. The AUC of IVIM was 0.913 in staging ccRCC. The D, D*, and MD values were negatively correlated with the histologic grades and clinical stages (all p < 0.05), and the KA and MK values showed a positive correlation with histologic grades and clinical stages (all p < 0.05). The f value was also negatively correlated with the ccRCC clinical stage (p = 0.008). Conclusion Both the IVIM and DKI values can be used preoperatively to predict the degree of histologic grades and stages in ccRCC, and the D and MD values have better diagnostic performance in the grading and staging. Also, further slightly enhanced diagnostic efficacy was observed in the model with combined IVIM and DKI parameters.
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Affiliation(s)
- QiChao Cheng
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
| | - AnLi Ren
- Department of Radiology, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, China
| | - XingHua Xu
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
| | - Zhao Meng
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
| | - Xue Feng
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
| | | | | | - DeXin Yu
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China
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Zou J, Ye J, Zhu W, Wu J, Chen W, Chen R, Zhu Q. Diffusion-weighted and diffusion kurtosis imaging analysis of microstructural differences in clear cell renal cell carcinoma: a comparative study. Br J Radiol 2023; 96:20230146. [PMID: 37393526 PMCID: PMC10546464 DOI: 10.1259/bjr.20230146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Revised: 06/12/2023] [Accepted: 06/13/2023] [Indexed: 07/03/2023] Open
Abstract
OBJECTIVE To quantitatively compare the diagnostic values of conventional diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) analysis of microstructural differences for clear cell renal cell carcinoma (CRCC). METHODS A total of 108 patients with pathologically confirmed CRCC, including 38 Grade I, 37 Grade II, 18 Grade III and 15 Grade IV, were enrolled and divided into groups according to tumor grade [low grade (Ⅰ+Ⅱ, n = 75) and high grade (Ⅲ+Ⅳ, n = 33)]. Apparent diffusion coefficient (ADC), mean diffusivity (MD), mean kurtosis (MK), kurtosis anisotropy (KA) and radial kurtosis (RK) were performed. RESULTS Both the ADC (r = -0.803) and MD (-0.867) values showed a negative correlation with tumor grading (p < 0.05) and MK (r = 0.812), KA (0.816) and RK (0.853) values a positive correlation with tumor grading (p < 0.05). Mean FA values showed no significant differences among CRCC grades (p > 0.05). ROC curve analyses showed that MD values had the highest diagnostic efficacy in differentiating low/high and Ⅱ/Ⅲ tumor grading. MD values gave AUC: 0.937 (0.896); sensitivity: 92.0% (86.5%); specificity: 78.8% (77.8%) and accuracy: 90.7% (87.3%). ADC performed worse than MD, MK, KA or RK (all p < 0.05) during pair-wise comparisons of ROC curves to show diagnostic efficacy. CONCLUSION DKI analysis performs better than ADC in differentiating CRCC grading. ADVANCES IN KNOWLEDGE Both the ADC and MD values correlated negatively with CRCC grading.The MK, KA and RK values correlated positively with CRCC grading.MD values had the highest diagnostic efficacy in differentiating low/high and Ⅱ/Ⅲ CRCC grading.
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Affiliation(s)
- Jinzhao Zou
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Jing Ye
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Wenrong Zhu
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Jingtao Wu
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Wenxin Chen
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Rui Chen
- Department of Kidney internal medicine, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Qingqiang Zhu
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
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Akıncı Ö, Türkoglu F, Nalbant MO, Öner Ö, İnci E. The Effectiveness of Volumetric MRI Histogram Analysis in Renal Cell Carcinoma. Acad Radiol 2023; 30 Suppl 1:S278-S285. [PMID: 37105802 DOI: 10.1016/j.acra.2023.03.029] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 03/19/2023] [Accepted: 03/20/2023] [Indexed: 04/29/2023]
Abstract
RATIONALE AND OBJECTIVES This study investigated the utility of histogram parameters derived from diffusion-weighted imaging (DWI) for evaluating renal cell carcinoma (RCC) grading prior to surgery. MATERIALS AND METHODS This retrospective study included 88 patients who were histopathologically diagnosed with RCC and underwent magnetic resonance imaging (MRI) examinations. The patients were divided into two groups as well-differentiated (Group 1) and poorly differentiated (Group 2). Demographic data, preoperative MRI findings, MRI apparent diffusion coefficient (ADC) histogram analyzes, operation types, postoperative histopathological data and cancer stages of the patients were recorded. The histogram parameters of ADC values, comprising the mean, minimum, maximum, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles, as well as skewness, kurtosis, and variance, were calculated. RESULTS The study included 59 males and 29 women with an average age of 56.21 ± 1.33 years. There were 52 patients in Group 1 and 36 patients in Group 2. The ADCmin, ADCmean, ADCmax, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ADC values of the poorly differentiated group were all lower than those of the well-differentiated group. ADCmin and the 5th percentile of ADC values, as well as ADCmean and the 10th, 25th, 50th, and 75th percentiles of ADC values, showed a statistically significant difference (p < 0.05). The AUC, sensitivity, and specificity of the ADCmin value were 0.703, 56.3%, and 75.7%, respectively. CONCLUSION The present study indicated that histogram parameters generated from DWI were capable of differentiating between high-grade and low-grade RCC.
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Affiliation(s)
- Özlem Akıncı
- Bakırköy Dr Sadi Konuk Training and Research Hospital, Department of Radiology, Istanbul, Turkey.
| | - Furkan Türkoglu
- Bakırköy Dr Sadi Konuk Training and Research Hospital, Department of Radiology, Istanbul, Turkey
| | - Mustafa Orhan Nalbant
- Bakırköy Dr Sadi Konuk Training and Research Hospital, Department of Radiology, Istanbul, Turkey
| | - Özkan Öner
- Bakırköy Dr Sadi Konuk Training and Research Hospital, Department of Radiology, Istanbul, Turkey
| | - Ercan İnci
- Bakırköy Dr Sadi Konuk Training and Research Hospital, Department of Radiology, Istanbul, Turkey
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10
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Laothamatas I, Al Mubarak H, Reddy A, Wax R, Badani K, Taouli B, Bane O, Lewis S. Multiparametric MRI of Solid Renal Masses: Principles and Applications of Advanced Quantitative and Functional Methods for Tumor Diagnosis and Characterization. J Magn Reson Imaging 2023. [PMID: 37052601 DOI: 10.1002/jmri.28718] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 03/23/2023] [Accepted: 03/23/2023] [Indexed: 04/14/2023] Open
Abstract
Solid renal masses (SRMs) are increasingly detected and encompass both benign and malignant masses, with renal cell carcinoma (RCC) being the most common malignant SRM. Most patients with SRMs will undergo management without a priori pathologic confirmation. There is an unmet need to noninvasively diagnose and characterize RCCs, as significant variability in clinical behavior is observed and a wide range of differing management options exist. Cross-sectional imaging modalities, including magnetic resonance imaging (MRI), are increasingly used for SRM characterization. Multiparametric (mp) MRI techniques can provide insight into tumor biology by probing different physiologic/pathophysiologic processes noninvasively. These include sequences that probe tissue microstructure, including intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and T1 relaxometry; oxygen metabolism (blood oxygen level dependent [BOLD-MRI]); as well as vascular flow and perfusion (dynamic contrast-enhanced MRI [DCE-MRI] and arterial spin labeling [ASL]). In this review, we will discuss each mpMRI method in terms of its principles, roles, and discuss the results of human studies for SRM assessment. Future validation of these methods may help to enable a personalized management approach for patients with SRM in the emerging era of precision medicine. EVIDENCE LEVEL: 5. TECHNICAL EFFICACY: 2.
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Affiliation(s)
- Indira Laothamatas
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Haitham Al Mubarak
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Arthi Reddy
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Rebecca Wax
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Ketan Badani
- Department of Urology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Bachir Taouli
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Octavia Bane
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Sara Lewis
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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11
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Lu J, Zhao S, Ma F, Li H, Li Y, Qiang J. Whole-tumor ADC histogram analysis for differentiating endometriosis-related tumors: seromucinous borderline tumor, clear cell carcinoma and endometrioid carcinoma. Abdom Radiol (NY) 2023; 48:724-732. [PMID: 36401131 DOI: 10.1007/s00261-022-03742-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 11/03/2022] [Accepted: 11/04/2022] [Indexed: 11/21/2022]
Abstract
PURPOSE To investigate the feasibility of whole-tumor apparent diffusion coefficient (ADC) histogram analysis for improving the differentiation of endometriosis-related tumors: seromucinous borderline tumor (SMBT), clear cell carcinoma (CCC) and endometrioid carcinoma (EC). METHODS Clinical features, solid component ADC (ADCSC) and whole-tumor ADC histogram-derived parameters (volume, the ADCmean, 10th, 50th and 90th percentile ADCs, inhomogeneity, skewness, kurtosis and entropy) were compared among 22 SMBTs, 42 CCCs and 21 ECs. Statistical analyses were performed using chi-square test, one-way ANOVA or Kruskal-Wallis test, and receiver operating characteristic curves. RESULTS A significantly higher ADCSC and smaller volume were associated with SMBT than with CCC/EC. The ADCmean was significantly higher in CCC than in EC. The 10th percentile ADC was significantly lower in EC than in SMBT/CCC. The 50th and 90th percentile ADCs were significantly higher in CCC than in SMBT/EC. For differentiating SMBT from CCC, AUCs of the ADCSC, volume, and 50th and 90th percentile ADCs were 0.97, 0.86, 0.72 and 0.81, respectively. For differentiating SMBT from EC, AUCs of the ADCSC, volume and 10th percentile ADC were 0.97, 0.71 and 0.72, respectively. For differentiating CCC from EC, AUCs of the ADCmean and 10th, 50th and 90th percentile ADCs were 0.79, 0.72, 0.81 and 0.85, respectively. CONCLUSION Whole-tumor ADC histogram analysis was valuable for differentiating endometriosis-related tumors, and the 90th percentile ADC was optimal in differentiating CCC from EC.
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Affiliation(s)
- Jing Lu
- Department of Radiology, Jinshan Hospital, Fudan University, 1508 Longhang Road, Shanghai, 201508, People's Republic of China
| | - Shuhui Zhao
- Department of Radiology, Jinshan Hospital, Fudan University, 1508 Longhang Road, Shanghai, 201508, People's Republic of China.,Department of Radiology, Xinhua Hospital, Medical College of Shanghai Jiao Tong University, Shanghai, 200092, People's Republic of China
| | - Fenghua Ma
- Department of Radiology, Jinshan Hospital, Fudan University, 1508 Longhang Road, Shanghai, 201508, People's Republic of China.,Department of Radiology, Obstetrics and Gynecology Hospital, Fudan University, 419 Fangxie Road, Shanghai, 200011, People's Republic of China
| | - Haiming Li
- Department of Radiology, Jinshan Hospital, Fudan University, 1508 Longhang Road, Shanghai, 201508, People's Republic of China.,Department of Radiology, Shanghai Cancer Center, Fudan University, 270 Dongan Road, Shanghai, 200032, People's Republic of China
| | - Yong'ai Li
- Department of Radiology, Jinshan Hospital, Fudan University, 1508 Longhang Road, Shanghai, 201508, People's Republic of China.
| | - Jinwei Qiang
- Department of Radiology, Jinshan Hospital, Fudan University, 1508 Longhang Road, Shanghai, 201508, People's Republic of China.
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12
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Li YZ, Liu P, Mao BH, Wang LL, Ren JL, Xu YS, Liu GY, Xin ZH, Lei JQ. Development of an improved diagnostic nomogram for preoperative prediction of small cell neuroendocrine cancer of the cervix. Br J Radiol 2022; 95:20220368. [PMID: 36169239 PMCID: PMC9733602 DOI: 10.1259/bjr.20220368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 09/09/2022] [Accepted: 09/24/2022] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVES Accurate preoperative diagnosis of small cell neuroendocrine cancer of the cervix (SCNECC) is crucial for establishing the best treatment plan. This study aimed to develop an improved, non-invasive method for the preoperative diagnosis of SCNECC by integrating clinical, MR morphological, and apparent diffusion coefficient (ADC) information. METHODS A total of 105 pathologically confirmed cervical cancer patients (35 SCNECC, 70 non-SCNECC) from multiple centres with complete clinical and MR records were included. Whole lesion histogram analysis of the ADC was performed. Multivariate logistic regression analysis was used to develop diagnostic models based on clinical, morphological, and histogram data. The predictive performance in terms of discrimination, calibration, and clinical usefulness of the different models was assessed. A nomogram for preoperatively discriminating SCNECC was developed from the combined model. RESULTS In preoperative SCNECC diagnosis, the combined model, which had a diagnostic AUC (area under the curve) of 0.937 (95% CI: 0.887-0.987), outperformed the clinical-morphological model, which had an AUC of 0.869 (CI: 0.788-0.949), and the histogram model, which had an AUC of 0.872 (CI: 0.792-0.951). The calibration curve and decision curve analyses suggest that the combined model achieved good fitting and clinical utility. CONCLUSIONS Non-invasive preoperative diagnosis of SCNECC can be achieved with high accuracy by integrating clinical, MR morphological, and ADC histogram features. The nomogram derived from the combined model can provide an easy-to-use clinical preoperative diagnostic tool for SCNECC. ADVANCES IN KNOWLEDGE It is clear that the therapeutic strategies for SCNECC are different from those for other pathological types of cervical cancer according to V 1.2021 of the NCCN clinical practice guidelines in oncology for cervical cancer. This research developed an improved, non-invasive method for the preoperative diagnosis of SCNECC by integrating clinical, MR morphological, and apparent diffusion coefficient (ADC) information.
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Affiliation(s)
| | - Peng Liu
- Department of Radiology, Gansu Provincial Cancer Hospital, Lanzhou, Gansu, China
| | - Bao-Hong Mao
- Department of Clinical Medical Research Centre, Gansu Provincial Maternity and Child-care Hospital, Lanzhou, Gansu, China
| | - Li-Li Wang
- Department of Radiology, Gansu Provincial Hospital, Lanzhou, Gansu, China
| | | | | | - Guang-Yao Liu
- Department of Magnetic Resonance, the Second Hospital of Lanzhou University, Lanzhou, Gansu, China
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13
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Zhu Q, Zou J, Ye J, Zhu W, Wu J, Chen W. Comparative study of conventional ROI-based and volumetric histogram analysis derived from CT enhancement in differentiating malignant and benign renal tumors. Br J Radiol 2022; 95:20210801. [PMID: 35333594 PMCID: PMC10996318 DOI: 10.1259/bjr.20210801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 02/12/2022] [Accepted: 03/17/2022] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVE To quantitatively compare the diagnostic values of conventional region of interest (ROI)-based and volumetric histogram analysis derived from CT enhancement in differentiating malignant and benign renal tumors. METHODS A total of 230 patients with pathologically confirmed renal tumors who had undergone CT enhancement were classified into clear cell renal cell carcinoma (ccRCC) (n = 133), non-ccRCC (n = 56), and benign renal tumor(n = 41) group. Parametric CT enhancement of each tumor from volumetric histogram were obtained using in-house software, including 10th percentile, 25th percentile, median, 75th percentile, 90th percentile, mean, standard deviation, as well as skewness, kurtosis and entropy, and histogram metrics among these groups were analyzed. ROI-based enhancement density was also analyzed. RESULTS The entropy and SD values of ccRCCs were higher than those of non-ccRCCs and benign renal tumors (p < 0.05). The 10th percentile, 25th percentile, median, 75th percentile, 90th percentile and mean values of ccRCCs were lower than those of benign renal tumors, however, higher than those of non-ccRCCs (p < 0.05). The ROI-based enhancement density of non-ccRCCs were lower than those of ccRCCs and benign renal tumors(p < 0.05). Receiver operating characteristic (ROC) curve analyses showed that entropy and mean values had the highest diagnostic efficacy in differentiating ccRCCs/non-ccRCCs and benign renal tumors. ROC curve analyses showed that mean values had the highest diagnostic efficacy in differentiating ccRCCs and non-ccRCCs. In terms of pairwise comparisons of ROC curves and diagnostic efficacy, ROI-based CT enhancement density was worse than volumetric histogram analysis (p < 0.05). CONCLUSION Volumetric histogram analysis parameters can effectively distinguish malignant and benign renal tumors. ADVANCES IN KNOWLEDGE 1. Entropy and mean values had the highest diagnostic efficacy in differentiating ccRCCs/ non-ccRCCs and benign renal tumors.2. Mean values had the highest diagnostic efficacy in differentiating ccRCCs and non-ccRCCs.3.Volumetric histogram analysis had better performance than ROI-based enhancement density.
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Affiliation(s)
- Qingqiang Zhu
- Department of Medical Imaging, Clinical Medical College,
Yangzhou University, Yangzhou,
China
| | - Jinzhao Zou
- Department of Medical Imaging, Clinical Medical College,
Yangzhou University, Yangzhou,
China
| | - Jing Ye
- Department of Medical Imaging, Clinical Medical College,
Yangzhou University, Yangzhou,
China
| | - Wenrong Zhu
- Department of Medical Imaging, Clinical Medical College,
Yangzhou University, Yangzhou,
China
| | - Jingtao Wu
- Department of Medical Imaging, Clinical Medical College,
Yangzhou University, Yangzhou,
China
| | - Wenxin Chen
- Department of Medical Imaging, Clinical Medical College,
Yangzhou University, Yangzhou,
China
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14
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Ghosh A, Yekeler E, Dalal D, Holroyd A, States L. Whole-tumour apparent diffusion coefficient (ADC) histogram analysis to identify MYCN-amplification in neuroblastomas: preliminary results. Eur Radiol 2022; 32:8453-8462. [PMID: 35437614 DOI: 10.1007/s00330-022-08750-2] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 02/27/2022] [Accepted: 03/11/2022] [Indexed: 11/26/2022]
Abstract
OBJECTIVES To determine the role of apparent diffusion coefficient (ADC) histogram analysis in the identification of MYCN-amplification status in neuroblastomas. METHODS We retrospectively evaluated imaging records from 62 patients with neuroblastomas (median age: 15 months (interquartile range (IQR): 7-24 months); 38 females) who underwent magnetic resonance imaging at our institution before the initiation of any therapy or biopsy. Fourteen patients had MYCN-amplified (MYCNA) neuroblastoma. Histogram parameters of ADC maps from the entire tumour was obtained from the baseline images and the normalised images. The Mann-Whitney U test was used to compare the absolute and normalised histogram parameters amongst neuroblastomas with and without MYCN-amplification. Receiver operating characteristic (ROC) curves and area under the curves (AUC) were generated for the statistically significant histogram parameters. Cut-offs obtained from the ROC curves were evaluated on an external validation set (n-15, MYCNA-6, F-7, age 24 months (10-60)). A logistic regression model was trained to predict MYCNA by combining statistically significant histogram parameters and was evaluated on the validation set. RESULTS MYCN-amplified neuroblastomas had statistically significant higher maximum ADC and lower minimum ADC than non-amplified neuroblastomas. They also demonstrated higher entropy, variance, energy, and lower uniformity than non-amplified neoplasms (p > 0.05). Energy, entropy, and maximum ADC had AUC of 0.85, 0.79, and 0.82, respectively. CONCLUSIONS Whole tumour ADC histogram analysis of neuroblastomas can differentiate between tumours with and without MYCN-amplification. These parameters can help identify areas for targeted biopsies or can be used to predict subtypes of these high-risk tumours before biopsy results are available. KEY POINTS • MYCN-amplification significantly affects treatment decisions in neuroblastomas. • MYCN-amplified neuroblastomas had significantly different ADC histogram metrics as compared to tumours without amplification. • ADC histogram metrics can be used to predict MYCN-amplification status based on imaging.
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Affiliation(s)
- Adarsh Ghosh
- Department of Radiology, Children's Hospital of Philadelphia, Roberts Center for Pediatric Research, Office 3122, 3rd Floor, 2716 South Street, 3401 Civic Center Boulevard, Philadelphia, PA, 19104, USA.
| | - Ensar Yekeler
- Department of Radiology, Children's Hospital of Philadelphia, Roberts Center for Pediatric Research, Office 3122, 3rd Floor, 2716 South Street, 3401 Civic Center Boulevard, Philadelphia, PA, 19104, USA
| | - Deepa Dalal
- Department of Radiology, Children's Hospital of Philadelphia, Roberts Center for Pediatric Research, Office 3122, 3rd Floor, 2716 South Street, 3401 Civic Center Boulevard, Philadelphia, PA, 19104, USA
| | - Alexandria Holroyd
- Department of Radiology, Children's Hospital of Philadelphia, Roberts Center for Pediatric Research, Office 3122, 3rd Floor, 2716 South Street, 3401 Civic Center Boulevard, Philadelphia, PA, 19104, USA
| | - Lisa States
- Department of Radiology, Children's Hospital of Philadelphia, Roberts Center for Pediatric Research, Office 3122, 3rd Floor, 2716 South Street, 3401 Civic Center Boulevard, Philadelphia, PA, 19104, USA
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
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15
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Hu S, Peng Y, Wang Q, Liu B, Kamel I, Liu Z, Liang C. T2*-weighted imaging and diffusion kurtosis imaging (DKI) of rectal cancer: correlation with clinical histopathologic prognostic factors. Abdom Radiol (NY) 2022; 47:517-529. [PMID: 34958406 DOI: 10.1007/s00261-021-03369-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Revised: 11/26/2021] [Accepted: 11/27/2021] [Indexed: 10/19/2022]
Abstract
PURPOSE Histopathologic prognostic factors of rectal cancer are closely associated with local recurrence and distant metastasis. We aim to investigate the feasibility of T2*WI in assessment of clinical prognostic factors of rectal cancer, and compare with DKI. METHODS This retrospective study enrolled 50 out of 205 patients with rectal cancer according to the inclusion criteria. The following parameters were obtained: R2* from T2*WI, mean diffusivity (MDk), mean kurtosis (MK), and mean diffusivity (MDt) from DKI using tensor method. Above parameters were compared by Mann-Whitney U-test or students' t test. Spearman correlations between different parameters and histopathological prognostic factors were determined. The diagnostic performances of R2* and DKI-derived parameters were analyzed by receiver operating characteristic curves (ROC), separately and jointly. RESULTS There were positive correlations between R2* and multiple prognostic factors of rectal cancer such as T category, N category, tumor grade, CEA level, and LVI (P < 0.004). MDk and MDt showed negative correlations with almost all the histopathological prognostic factors except CRM and TIL involvement (P < 0.003). MK correlated positively with the prognostic factors except CA19-9 level and CRM involvement (P < 0.006). The AUC ranges were 0.724-0.950 for R2* and 0.755-0.913 for DKI-derived parameters for differentiation of prognostic factors. However, no significant differences of diagnostic performance were found between T2*WI, DKI, or the combined imaging methods in characterizing rectal cancer. CONCLUSION R2* and DKI-derived parameters were associated with different histopathological prognostic factors, and might act as noninvasive biomarkers for histopathological characterization of rectal cancer.
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16
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Peng Y, Luo Y, Hu X, Shen Y, Hu D, Li Z, Kamel I. Quantitative T2*-Weighted Imaging and Reduced Field-of-View Diffusion-Weighted Imaging of Rectal Cancer: Correlation of R2* and Apparent Diffusion Coefficient With Histopathological Prognostic Factors. Front Oncol 2021; 11:670156. [PMID: 34109120 PMCID: PMC8180870 DOI: 10.3389/fonc.2021.670156] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Accepted: 04/28/2021] [Indexed: 12/24/2022] Open
Abstract
Purpose To assess T2*-weighted imaging (T2*WI) and reduced field-of-view diffusion-weighted Imaging (rDWI) derived parameters and their relationships with histopathological factors in patients with rectal cancer. Methods Fifty-four patients with pathologically-proven rectal cancer underwent preoperative T2*-weighted imaging and rDWI in this retrospective study. R2* values from T2*-weighted imaging and apparent diffusion coefficient (ADC) values from rDWI were compared in terms of different histopathological prognostic factors using student’s t-test or Mann-Whitney U-test. The correlations of R2* and ADC with prognostic factors were assessed by Spearman correlation analysis. The diagnostic performances of R2* and ADC were analyzed by receiver operating characteristic curves (ROC) separately and jointly. Results Significant positive correlation was found between R2* values and T stage, lymph node involvement, histological grades, CEA level, the presence of EMVI and tumor deposit (r = 0.374 ~ 0.673, p = 0.000–0.006), with the exception of CA19-9 level, CRM status and tumor involvement in the circumference lumen (TIL). Meanwhile, ADC values negatively correlated with almost all the prognostic factors (r = −0.588 to −0.299, p = 0.000–0.030), except CA19-9 level. The AUC range was 0.724–0.907 for R2* and 0.674–0.887 for ADC in discrimination of different prognostic factors. While showing the highest AUC of 0.913 (0.803–1.000) in differentiation of T stage, combination of R2* and ADC with reference to different prognostic factors did not significantly improve the diagnostic performance in comparison with individual R2*/ADC parameter. Conclusions R2* and ADC were associated with important histopathological prognostic factors of rectal cancer. R2* might act as additional quantitative imaging marker for tumor characterization of rectal cancer.
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Affiliation(s)
- Yang Peng
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan Luo
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xuemei Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yaqi Shen
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Daoyu Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhen Li
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ihab Kamel
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, United States
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Zhu Q, Xu Q, Dou W, Zhu W, Wu J, Chen W, Ye J. Diffusion kurtosis imaging features of renal cell carcinoma: a preliminary study. Br J Radiol 2021; 94:20201374. [PMID: 33989037 DOI: 10.1259/bjr.20201374] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
OBJECTIVE To explore the feasibility of diffusion kurtosis imaging (DKI) in differentiating different types of renal cell carcinoma (RCC). METHODS 36 patients with clear cell RCC (CCRCC, low-grade,n = 20 and high-grade, n = 16), 19 with papillary RCC, 11 with chromophobe RCC, and 9 with collecting duct carcinoma (CDC) were examined with DKI technique. b values of 0, 500 and 1000 s/mm2 were adopted. The DKI parameters, i.e., mean diffusivity (MD), mean kurtosis (MK), kurtosis anisotropy (KA), radial kurtosis (RK) and signa-to-noise ration (SNR) of DKI images at different b values were used. RESULTS The mean SNRs of DKI images at b = 0, 500 and 1000 s/mm2 were 32.8, 14.2 and 9.18, respectively. For MD parameter, a significant higher value was shown in CCRCC than those of papillary RCC, chromophobe RCC and CDC (p < 0.05). In addition, both chromophobe RCC and CDC have larger MD values than papillary RCC (p < 0.05), however, there was no significant differences between chromophobe RCC and CDC (p > 0.05). For MK, KA and RK parameters, a significant higher value was shown in papillary RCC than those of CCRCC, chromophobe RCC and CDC (p < 0.05). Moreover, both chromophobe RCC and CDC have significantly larger values of MK, KA and RK than CCRCC (p < 0.05). CONCLUSION Our preliminary study demonstrated significant differences in the DKI parameters between the subtypes of RCCs, given an adequate SNR of DKI images. ADVANCES IN KNOWLEDGE 1.The MD value is the best parameter to distinguish CCRCC from other RCCs.2.The MK, KA and RK values are the best parameters to distinguish papillary RCC from other RCCs.3.DKI is able to provide images with sufficient SNRs in kidney disease.
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Affiliation(s)
- Qingqiang Zhu
- Department of Medical Imaging, Subei People's Hospital, Medical School of Yangzhou University, Yangzhou, China
| | - Qing Xu
- Department of Medical Imaging, Subei People's Hospital, Medical School of Yangzhou University, Yangzhou, China
| | - Weiqiang Dou
- MR Research China, GE Healthcare, Beijing 100176, China., Beijing, China
| | - Wenrong Zhu
- Department of Medical Imaging, Subei People's Hospital, Medical School of Yangzhou University, Yangzhou, China
| | - Jingtao Wu
- Department of Medical Imaging, Subei People's Hospital, Medical School of Yangzhou University, Yangzhou, China
| | - Wenxin Chen
- Department of Medical Imaging, Subei People's Hospital, Medical School of Yangzhou University, Yangzhou, China
| | - Jing Ye
- Department of Medical Imaging, Subei People's Hospital, Medical School of Yangzhou University, Yangzhou, China
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Shi GZ, Chen H, Zeng WK, Gao M, Wang MZ, Zhang HT, Shen J. R2* value derived from multi-echo Dixon technique can aid discrimination between benign and malignant focal liver lesions. World J Gastroenterol 2021; 27:1182-1193. [PMID: 33828393 PMCID: PMC8006098 DOI: 10.3748/wjg.v27.i12.1182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 02/02/2021] [Accepted: 02/25/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND R2* estimation reflects the paramagnetism of the tumor tissue, which may be used to differentiate between benign and malignant liver lesions when contrast agents are contraindicated. AIM To investigate whether R2* derived from multi-echo Dixon imaging can aid differentiating benign from malignant focal liver lesions (FLLs) and the impact of 2D region of interest (2D-ROI) and volume of interest (VOI) on the outcomes. METHODS We retrospectively enrolled 73 patients with 108 benign or malignant FLLs. All patients underwent conventional abdominal magnetic resonance imaging and multi-echo Dixon imaging. Two radiologists independently measured the mean R2* values of lesions using 2D-ROI and VOI approaches. The Bland-Altman plot was used to determine the interobserver agreement between R2* measurements. Intraclass correlation coefficient (ICC) was used to determine the reliability between the two readers. Mean R2* values were compared between benign and malignant FFLs using the nonparametric Mann-Whitney test. Receiver operating characteristic curve analysis was used to determine the diagnostic performance of R2* in differentiation between benign and malignant FFLs. We compared the diagnostic performance of R2* measured by 2D-ROI and VOI approaches. RESULTS This study included 30 benign and 78 malignant FLLs. The interobserver reproducibility of R2* measurements was excellent for the 2D-ROI (ICC = 0.994) and VOI (ICC = 0.998) methods. Bland-Altman analysis also demonstrated excellent agreement. Mean R2* was significantly higher for malignant than benign FFLs as measured by 2D-ROI (P < 0.001) and VOI (P < 0.001). The area under the curve (AUC) of R2* measured by 2D-ROI was 0.884 at a cut-off of 25.2/s, with a sensitivity of 84.6% and specificity of 80.0% for differentiating benign from malignant FFLs. R2* measured by VOI yielded an AUC of 0.875 at a cut-off of 26.7/s in distinguishing benign from malignant FFLs, with a sensitivity of 85.9% and specificity of 76.7%. The AUCs of R2* were not significantly different between the 2D-ROI and VOI methods. CONCLUSION R2* derived from multi-echo Dixon imaging whether by 2D-ROI or VOI can aid in differentiation between benign and malignant FLLs.
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Affiliation(s)
- Guang-Zi Shi
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, Guangdong Province, China
| | - Hong Chen
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, Guangdong Province, China
| | - Wei-Ke Zeng
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, Guangdong Province, China
| | - Ming Gao
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, Guangdong Province, China
| | - Meng-Zhu Wang
- MR Scientific Marketing, Siemens Healthineers, Guangzhou 510120, Guangdong Province, China
| | - Hui-Ting Zhang
- MR Scientific Marketing, Siemens Healthineers, Guangzhou 510120, Guangdong Province, China
| | - Jun Shen
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, Guangdong Province, China
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Zhu J, Luo X, Gao J, Li S, Li C, Chen M. Application of diffusion kurtosis tensor MR imaging in characterization of renal cell carcinomas with different pathological types and grades. Cancer Imaging 2021; 21:30. [PMID: 33726862 PMCID: PMC7962255 DOI: 10.1186/s40644-021-00394-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Accepted: 02/19/2021] [Indexed: 12/13/2022] Open
Abstract
Background To probe the feasibility and reproducibility of diffusion kurtosis tensor imaging (DKTI) in renal cell carcinoma (RCC) and to apply DKTI in distinguishing the subtypes of RCC and the grades of clear cell RCC (CCRCC). Methods Thirty-eight patients with pathologically confirmed RCCs [CCRCC for 30 tumors, papillary RCC (PRCC) for 5 tumors and chromophobic RCC (CRCC) for 3 tumors] were involved in the study. Diffusion kurtosis tensor MR imaging were performed with 3 b-values (0, 500, 1000s/mm2) and 30 diffusion directions. The mean kurtosis (MK), axial kurtosis (Ka), radial kurtosis (Kr) values and mean diffusity (MD) for RCC and contralateral normal parenchyma were acquired. The inter-observer agreements of all DKTI metrics of contralateral renal cortex and medulla were evaluated using Bland-Altman plots. Statistical comparisons with DKTI metrics of 3 RCC subtypes and between low-grade (Furman grade I ~ II, 22 cases) and high-grade (Furman grade III ~ IV, 8 cases) CCRCC were performed with ANOVA test and Student t test separately. Receiver operating characteristic (ROC) curve analyses were used to compare the diagnostic efficacy of DKTI metrics for predicting nuclear grades of CCRCC. Correlations between DKTI metrics and nuclear grades were also evaluated with Spearman correlation analysis. Results Inter-observer measurements for each metric showed great reproducibility with excellent ICCs ranging from 0.81 to 0.87. There were significant differences between the DKTI metrics of RCCs and contralateral renal parenchyma, also among the subtypes of RCC. MK and Ka values of CRCC were significantly higher than those of CCRCC and PRCC. Statistical difference of the MK, Ka, Kr and MD values were also obtained between CCRCC with high- and low-grades. MK values were more effective for distinguishing between low- and high- grade CCRCC (area under the ROC curve: 0.949). A threshold value of 0.851 permitted distinction with high sensitivity (90.9%) and specificity (87.5%). Conclusion Our preliminary results suggest a possible role of DKTI in differentiating CRCC from CCRCC and PRCC. MK, the principle DKTI metric might be a surrogate biomarker to predict nuclear grades of CCRCC. Trial registration ChiCTC, ChiCTR-DOD-17010833, Registered 10 March, 2017, retrospectively registered, http://www.chictr.org.cn/showproj.aspx?proj=17559.
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Affiliation(s)
- Jie Zhu
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, P. R. China
| | - Xiaojie Luo
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, P. R. China
| | - Jiayin Gao
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, P. R. China
| | - Saying Li
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, P. R. China
| | - Chunmei Li
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, P. R. China
| | - Min Chen
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, P. R. China.
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Cao J, Luo X, Zhou Z, Duan Y, Xiao L, Sun X, Shang Q, Gong X, Hou Z, Kong D, He B. Comparison of diffusion-weighted imaging mono-exponential mode with diffusion kurtosis imaging for predicting pathological grades of clear cell renal cell carcinoma. Eur J Radiol 2020; 130:109195. [PMID: 32763475 DOI: 10.1016/j.ejrad.2020.109195] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 07/01/2020] [Accepted: 07/20/2020] [Indexed: 12/24/2022]
Abstract
PURPOSE To evaluate the role of diffusion kurtosis imaging (DKI1) in the characterization of clear cell renal cell carcinoma (ccRCC2) compared with standard diffusion-weighted imaging (DWI3). METHODS 89 patients with histologically proven ccRCC were evaluated by DKI and DWI on a 3-T scanner. All ccRCCs were classified as grade 1-4 according to the Fuhrman classification system. The apparent diffusion coefficient (ADC4), fractional anisotropy (FA5), mean diffusivity (MD6), mean kurtosis (MK7), axial kurtosis (Ka8) and radial kurtosis (Kr9) values were recorded. The differences in DWI and DKI parameters were evaluated by independent-sample t test and a receiver operating characteristic (ROC10) analysis was performed. The DeLong test was performed to compare the ROCs. RESULTS Compared to normal renal parenchyma, ADC and MD values of ccRCC decreased and MK, Ka, and Kr values increased (p < 0.05). ADC and MD values of ccRCC decreased with the increase in pathological grade, while MK, Ka, and Kr values were increased (p < 0.05). ADC could discriminate G1 vs G3, G1 vs G4, G2 vs G3, G2 vs G4, and G3 vs G4 (p < 0.05) except for G1 vs G2 (p > 0.05). Ka and Kr could discriminate G1 vs G2, G1 vs G3, G1 vs G4, G2 vs G4, and G3 vs G4 (p < 0.05) except for G2 vs G3 (p > 0.05). MD and MK could discriminate G1 vs G2, G1 vs G3, G1 vs G4, G2 vs G3, G2 vs G4, and G3 vs G4 (p < 0.05). The AUC of MK was the highest. The DeLong test showed that there were significant differences regarding ROCs between ADC/MK, ADC/Ka, ADC/Kr in grading G1/G2, and ADC/MK, MK/Ka in grading G3/G4 (p < 0.05). CONCLUSION DKI was superior compared to the mono-exponential mode of DWI in grading ccRCC.
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Affiliation(s)
- Jinfeng Cao
- Department of Radiology, Zibo Central Hospital, Zibo, Shandong, China; Zibo Key Laboratory of Precision Neuroimaging, China
| | - Xin Luo
- Department of Radiology, Zibo Central Hospital, Zibo, Shandong, China; Zibo Key Laboratory of Precision Neuroimaging, China
| | - Zhongmin Zhou
- Department of Nephrology, Zibo Central Hospital, Shandong, China
| | - Yanhua Duan
- Department of Radiology, Shandong Medical Imaging Research Institute, Shandong University, Jinan, Shandong, China
| | - Lianxiang Xiao
- Department of Radiology, Shandong Medical Imaging Research Institute, Shandong University, Jinan, Shandong, China
| | - Xinru Sun
- Department of Radiology, Zibo Central Hospital, Zibo, Shandong, China; Zibo Key Laboratory of Precision Neuroimaging, China
| | - Qun Shang
- Department of Radiology, Zibo Central Hospital, Zibo, Shandong, China; Zibo Key Laboratory of Precision Neuroimaging, China
| | - Xiao Gong
- Department of Radiology, Zibo Central Hospital, Zibo, Shandong, China; Zibo Key Laboratory of Precision Neuroimaging, China
| | - Zhenbo Hou
- Department of Pathology, Zibo Central Hospital, Zibo, Shandong, China
| | - Demin Kong
- Department of Radiology, Zibo Central Hospital, Zibo, Shandong, China; Zibo Key Laboratory of Precision Neuroimaging, China
| | - Bing He
- Department of Radiology, Zibo Central Hospital, Zibo, Shandong, China; Zibo Key Laboratory of Precision Neuroimaging, China.
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Goh V, Prezzi D. Predicting Growth Kinetics in Hereditary Renal Cancer with Diffusion-weighted MRI. Radiology 2020; 295:591-592. [PMID: 32267214 DOI: 10.1148/radiol.2020200700] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Vicky Goh
- From the Department of Cancer Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, King's Health Partners, London, England; and Department of Radiology, Guy's and St Thomas' NHS Foundation Trust, Level 1, Lambeth Wing, St Thomas' Hospital, Westminster Bridge Road, London SE1 7EH, England
| | - Davide Prezzi
- From the Department of Cancer Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, King's Health Partners, London, England; and Department of Radiology, Guy's and St Thomas' NHS Foundation Trust, Level 1, Lambeth Wing, St Thomas' Hospital, Westminster Bridge Road, London SE1 7EH, England
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Farhadi F, Nikpanah M, Paschall AK, Shafiei A, Tadayoni A, Ball MW, Linehan WM, Jones EC, Malayeri AA. Clear Cell Renal Cell Carcinoma Growth Correlates with Baseline Diffusion-weighted MRI in Von Hippel-Lindau Disease. Radiology 2020; 295:583-590. [PMID: 32255415 DOI: 10.1148/radiol.2020191016] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Background Identification of markers to aid in understanding the growth kinetics of Von Hippel-Lindau (VHL)-associated clear cell renal cell carcinoma (ccRCC) has the potential to allow individualization of patient care, thereby helping prevent unnecessary screening and optimizing intervention. Purpose To determine whether the degree of restricted diffusion at baseline MRI holds predictive potential for the growth rate of VHL-associated ccRCC. Materials and Methods Patients with VHL disease who underwent surgical resection of tumors between November 2014 and October 2017 were analyzed retrospectively in this HIPAA-compliant study. The change in ccRCC volume between two time points and apparent diffusion coefficient (ADC) at baseline was calculated by using segmentations by two readers at nephrographic-phase CT and diffusion-weighted MRI, respectively. Intraclass correlation coefficient was used to assess agreement between readers. Repeated-measures correlation was used to investigate relationships between ADC (histogram parameters) and tumor size at baseline with growth rate and volume doubling time (VDT). Predictive performance of the ADC parameter with highest correlation and tumor size at baseline was reviewed to differentiate tumors based on their VDT (≤1 year or >1 year). Results Forty-six patients (mean age, 46 years ± 7 [standard deviation]; 25 women) with 100 ccRCCs were evaluated. Interreader agreement resulted in mean κ scores of 0.89, 0.82, and 0.93 for mean ADC, baseline tumor volume, and follow-up tumor volume, respectively. ADC percentiles correlated negatively with tumor growth rate but correlated positively with VDT. Lower ADC values demonstrated stronger correlations. The 25th percentile ADC had the strongest correlation with growth rate (ρ = -0.52, P < .001) and VDT (ρ = 0.60, P < .001) and enabled prediction of VDT (≤1 year or >1 year) with an area under the receiver operating characteristic curve of 0.86 (sensitivity, 67%; specificity, 89%) (P < .001). Conclusion Apparent diffusion coefficient at baseline was negatively correlated with tumor growth rate. Diffusion-weighted MRI may be useful to identify clear cell renal cell carcinomas with higher growth rates. © RSNA, 2020See also the editorial by Goh and Prezzi in this issue.
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Affiliation(s)
- Faraz Farhadi
- From the Radiology and Imaging Sciences, NIH Clinical Center (F.F., M.N., A.K.P., A.S., A.T., E.C.J., A.A.M.), and Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute (M.W.B., W.M.L.), National Institutes of Health, 10 Center Dr, Bethesda, MD 20814
| | - Moozhan Nikpanah
- From the Radiology and Imaging Sciences, NIH Clinical Center (F.F., M.N., A.K.P., A.S., A.T., E.C.J., A.A.M.), and Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute (M.W.B., W.M.L.), National Institutes of Health, 10 Center Dr, Bethesda, MD 20814
| | - Anna K Paschall
- From the Radiology and Imaging Sciences, NIH Clinical Center (F.F., M.N., A.K.P., A.S., A.T., E.C.J., A.A.M.), and Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute (M.W.B., W.M.L.), National Institutes of Health, 10 Center Dr, Bethesda, MD 20814
| | - Ahmad Shafiei
- From the Radiology and Imaging Sciences, NIH Clinical Center (F.F., M.N., A.K.P., A.S., A.T., E.C.J., A.A.M.), and Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute (M.W.B., W.M.L.), National Institutes of Health, 10 Center Dr, Bethesda, MD 20814
| | - Ashkan Tadayoni
- From the Radiology and Imaging Sciences, NIH Clinical Center (F.F., M.N., A.K.P., A.S., A.T., E.C.J., A.A.M.), and Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute (M.W.B., W.M.L.), National Institutes of Health, 10 Center Dr, Bethesda, MD 20814
| | - Mark W Ball
- From the Radiology and Imaging Sciences, NIH Clinical Center (F.F., M.N., A.K.P., A.S., A.T., E.C.J., A.A.M.), and Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute (M.W.B., W.M.L.), National Institutes of Health, 10 Center Dr, Bethesda, MD 20814
| | - W Marston Linehan
- From the Radiology and Imaging Sciences, NIH Clinical Center (F.F., M.N., A.K.P., A.S., A.T., E.C.J., A.A.M.), and Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute (M.W.B., W.M.L.), National Institutes of Health, 10 Center Dr, Bethesda, MD 20814
| | - Elizabeth C Jones
- From the Radiology and Imaging Sciences, NIH Clinical Center (F.F., M.N., A.K.P., A.S., A.T., E.C.J., A.A.M.), and Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute (M.W.B., W.M.L.), National Institutes of Health, 10 Center Dr, Bethesda, MD 20814
| | - Ashkan A Malayeri
- From the Radiology and Imaging Sciences, NIH Clinical Center (F.F., M.N., A.K.P., A.S., A.T., E.C.J., A.A.M.), and Urologic Oncology Branch, Center for Cancer Research, National Cancer Institute (M.W.B., W.M.L.), National Institutes of Health, 10 Center Dr, Bethesda, MD 20814
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Diagnostic test accuracy of ADC values for identification of clear cell renal cell carcinoma: systematic review and meta-analysis. Eur Radiol 2020; 30:4023-4038. [PMID: 32144458 DOI: 10.1007/s00330-020-06740-w] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 01/14/2020] [Accepted: 02/11/2020] [Indexed: 12/11/2022]
Abstract
OBJECTIVES To perform a systematic review on apparent diffusion coefficient (ADC) values of renal tumor subtypes and meta-analysis on the diagnostic performance of ADC for differentiation of localized clear cell renal cell carcinoma (ccRCC) from other renal tumor types. METHODS Medline, Embase, and the Cochrane Library databases were searched for studies published until May 1, 2019, that reported ADC values of renal tumors. Methodological quality was evaluated. For the meta-analysis on diagnostic test accuracy of ADC for differentiation of ccRCC from other renal lesions, we applied a bivariate random-effects model and compared two subgroups of ADC measurement with vs. without cystic and necrotic areas. RESULTS We included 48 studies (2588 lesions) in the systematic review and 13 studies (1126 lesions) in the meta-analysis. There was no significant difference in ADC of renal parenchyma using b values of 0-800 vs. 0-1000 (p = 0.08). ADC measured on selected portions (sADC) excluding cystic and necrotic areas differed significantly from whole-lesion ADC (wADC) (p = 0.002). Compared to ccRCC, minimal-fat angiomyolipoma, papillary RCC, and chromophobe RCC showed significantly lower sADC while oncocytoma exhibited higher sADC. Summary estimates of sensitivity and specificity to differentiate ccRCC from other tumors were 80% (95% CI, 0.76-0.88) and 78% (95% CI, 0.64-0.89), respectively, for sADC and 77% (95% CI, 0.59-0.90) and 77% (95% CI, 0.69-0.86) for wADC. sADC offered a higher area under the receiver operating characteristic curve than wADC (0.852 vs. 0.785, p = 0.02). CONCLUSIONS ADC values of kidney tumors that exclude cystic or necrotic areas more accurately differentiate ccRCC from other renal tumor types than whole-lesion ADC values. KEY POINTS • Selective ADC of renal tumors, excluding cystic and necrotic areas, provides better discriminatory ability than whole-lesion ADC to differentiate clear cell RCC from other renal lesions, with area under the receiver operating characteristic curve (AUC) of 0.852 vs. 0.785, respectively (p = 0.02). • Selective ADC of renal masses provides moderate sensitivity and specificity of 80% and 78%, respectively, for differentiation of clear cell renal cell carcinoma (RCC) from papillary RCC, chromophobe RCC, oncocytoma, and minimal-fat angiomyolipoma. • Selective ADC excluding cystic and necrotic areas are preferable to whole-lesion ADC as an additional tool to multiphasic MRI to differentiate clear cell RCC from other renal lesions whether the highest b value is 800 or 1000.
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Application of R2* and Apparent Diffusion Coefficient in Estimating Tumor Grade and T Category of Bladder Cancer. AJR Am J Roentgenol 2019; 214:383-389. [PMID: 31670586 DOI: 10.2214/ajr.19.21668] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
OBJECTIVE. The objective of our study was to compare the feasibility of R2* and apparent diffusion coefficient (ADC) for differentiating tumor grade and T category of bladder cancer. SUBJECTS AND METHODS. In this prospective study, 58 patients with pathologically confirmed bladder cancers underwent pretreatment T2*-weighted imaging and DWI on a 3-T MRI unit. The apparent transverse relaxation rate R2*, which is derived from T2*-weighted imaging, and ADC, which is derived from DWI, were calculated and compared between low- and high-grade bladder cancers as well as between non-muscle-invasive bladder cancers (NMIBCs) and muscle-invasive bladder cancers (MIBCs) using the Mann-Whitney U test. The diagnostic performances of R2*, ADC, and the combination of R2* and ADC were evaluated through an ROC analysis. RESULTS. Significant differences were found in R2* (mean ± SD, 16.55 ± 5.54 vs 20.96 ± 7.75 s-1; p = 0.001) and ADC (1.62 ± 0.31 vs 1.33 ± 0.21 × 10-3 mm2/s; p < 0.001) between lowand high-grade bladder cancers. R2* was significantly higher (22.56 ± 8.41 vs 18.06 ± 6.46 s-1; p = 0.008) and ADC was considerably lower (1.21 ± 0.18 vs 1.53 ± 0.27 × 10-3 mm2/s; p < 0.001) in MIBCs than in NMIBCs. The AUCs for differentiating low-from high-grade groups were 0.714 using R2* and 0.779 using ADC. AUCs for distinguishing between NMIBC and MIBC groups using R2* and ADC were 0.682 and 0.850, respectively. CONCLUSION. In addition to ADC, R2* can be used as a quantitative imaging biomarker to provide additional information for tumor characterization of bladder cancer.
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Zha T, Ren X, Xing Z, Zhang J, Tian X, Du Y, Xing W, Chen J. Evaluating Renal Fibrosis with R2* Histogram Analysis of the Whole Cortex in a Unilateral Ureteral Obstruction Model. Acad Radiol 2019; 26:e202-e207. [PMID: 30111497 DOI: 10.1016/j.acra.2018.07.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2018] [Revised: 07/19/2018] [Accepted: 07/19/2018] [Indexed: 12/15/2022]
Abstract
RATIONALE AND OBJECTIVES The aim of this study was to use histogram analysis to assess the correlation between blood oxygen-level dependent magnetic resonance imaging (BOLD-MRI) and renal fibrosis induced by unilateral ureteral obstruction (UUO) in an animal model for a long experimental period. MATERIALS AND METHODS The rabbits were randomly divided into a control group (n = 6) and a UUO group (n = 30). The rabbits in the UUO group underwent left ureteral obstruction surgery. BOLD-MRI examinations were performed at 2, 4, 6, and 8 weeks after ligation. After the examinations, nephrectomy was performed for histologic evaluation. Histogram analysis of the left renal cortex (C) R2* values was performed to measure the mean, median, 10th percentile, 90th percentile, skewness, and kurtosis for all kidneys. Masson trichrome staining was used to assess the percentage of fibrotic area. RESULTS The histogram R2* values of the mean, median, 10th percentile, and 90th percentile at week 2 were all lower than those at baseline. Over the course of UUO progression, there were statistical differences between the histogram R2* values at any other two time points, except between weeks 4 and 6, and weeks 6 and 8. A close correlation was found between the percentage of fibrotic area and R2* values (mean: F = 21.49, p = 0.0001, R2 = 0.49, median: F = 30.07, p < 0.0001, R2 = 0.58, 10th percentile: F = 31.02, p < 0.0001, R2 = 0.59, 90th percentile: F = 24.13, p < 0.0001, R2 = 0.52). CONCLUSION BOLD-MRI could reflect the formation and progression of renal fibrosis in a rabbit UUO model; however, the value of BOLD-MRI in the long-term evaluation of fibrosis is limited.
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CT-based machine learning model to predict the Fuhrman nuclear grade of clear cell renal cell carcinoma. Abdom Radiol (NY) 2019; 44:2528-2534. [PMID: 30919041 DOI: 10.1007/s00261-019-01992-7] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
PURPOSE To predict the Fuhrman grade of clear cell renal cell carcinoma (ccRCC) with a machine learning classifier based on single- or three-phase computed tomography (CT) images. MATERIALS AND METHODS Patients with pathologically proven ccRCC from February 1, 2009 to September 31, 2018 who were not treated were retrospectively collected for machine learning-based analysis. The texture features were extracted and ranked from precontrast phase (PCP), corticomedullary phase (CMP), nephrographic phase (NP) and three-phase CT images, and open-source gradient boosting from the decision tree library of CatBoost was used to establish a machine learning classifier to differentiate low- from high-grade ccRCC. The performances of machine learning classifiers based on features from single- and three-phase CT images were compared with each other. RESULTS A total of 231 patients with 232 pathologically proven ccRCC lesions were retrospectively collected. 35, 36, 41, and 22 Features were extracted and ranked from PCP, CMP, NP, and three-phase CT images, respectively. The machine learning model based on three-phase CT images [area under the ROC curve (AUC) = 0.87] achieved the best diagnostic performance for differentiating low- from high-grade ccRCC, followed by single-phase NP (AUC = 0.84), CMP (AUC = 0.80), and PCP images (AUC = 0.82). CONCLUSION Machine learning classifiers can be promising noninvasive techniques to differentiate low- and high-Fuhrman nuclear grade ccRCC, and classifiers based on three-phase CT images are superior to those based on features from each single phase.
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Wang K, Cheng J, Wang Y, Wu G. Renal cell carcinoma: preoperative evaluate the grade of histological malignancy using volumetric histogram analysis derived from magnetic resonance diffusion kurtosis imaging. Quant Imaging Med Surg 2019; 9:671-680. [PMID: 31143658 DOI: 10.21037/qims.2019.04.14] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Background To investigate the value of histogram analysis of magnetic resonance (MR) diffusion kurtosis imaging (DKI) in the assessment of renal cell carcinoma (RCC) grading before surgery. Methods A total of 73 RCC patients who had undergone preoperative MR imaging and DKI were classified into either a low- grade group or a high-grade group. Parametric DKI maps of each tumor were obtained using in-house software, and histogram metrics between the two groups were analyzed. Receiver operating characteristic (ROC) curve analysis was used for obtaining the optimum diagnostic thresholds, the area under the ROC curve (AUC), sensitivity, specificity and accuracy of the parameters. Results Significant differences were observed in 3 metrics of ADC histogram parameters and 8 metrics of DKI histogram parameters (P<0.05). ROC curve analyses showed that Kapp mean had the highest diagnostic efficacy in differentiating RCC grades. The AUC, sensitivity, and specificity of the Kapp mean were 0.889, 87.9% and 80%, respectively. Conclusions DKI histogram parameters can effectively distinguish high- and low- grade RCC. Kapp mean is the best parameter to distinguish RCC grades.
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Affiliation(s)
- Ke Wang
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan 437100, China
| | - Jingyun Cheng
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan 437100, China
| | - Yan Wang
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan 437100, China
| | - Guangyao Wu
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan 437100, China.,Radiology Department, Shenzhen University General Hospital and Shenzhen University Clinical Medical Academy, Shenzhen 518000, China
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Chen Y, Wu B, Liu H, Wang D, Gu Y. Feasibility study of dual parametric 2D histogram analysis of breast lesions with dynamic contrast-enhanced and diffusion-weighted MRI. J Transl Med 2018; 16:325. [PMID: 30470241 PMCID: PMC6260880 DOI: 10.1186/s12967-018-1698-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Accepted: 11/16/2018] [Indexed: 01/01/2023] Open
Abstract
Background This study aimed to investigate the diagnostic value of a dual-parametric 2D histogram classification method for breast lesions. Methods This study included 116 patients with 72 malignant and 44 benign breast lesions who underwent CAIPIRINHA-Dixon-TWIST-VIBE dynamic contrast-enhanced (CDT-VIBE DCE) and readout-segmented diffusion-weighted magnetic resonance examination. The volume of interest (VOI), which encompassed the entire lesion, was segmented from the last phase of DCE images. For each VOI, a 1D histogram analysis (mean, median, 10th percentile, 90th percentile, kurtosis and skewness) was performed on apparent diffusion coefficient (ADC) and volume transfer constant (Ktrans) maps; a 2D histogram image (Ktrans-ADC) was generated from the pixelwise aligned maps, and its kurtosis and skewness were calculated. Each parameter was correlated with pathological results using the Mann–Whitney test and receiver operating characteristic curve analysis. Results For the Ktrans histogram, the area under the curve (AUC) of the mean, median, 90th percentile and kurtosis had statistically diagnostic values (mean: 0.760; median: 0.661; 90th percentile: 0.781; and kurtosis: 0.620). For the ADC histogram, the AUC of the mean, median, 10th percentile, skewness and kurtosis had statistically diagnostic values (mean: 0.661; median: 0.677; 10th percentile: 0.656; skewness: 0.664; and kurtosis: 0.620). For the 2D Ktrans-ADC histogram, the skewness and kurtosis had statistically higher diagnostic values (skewness: 0.831, kurtosis: 0.828) than those of the 1D histogram (all P < 0.05). Conclusions The dual-parametric 2D histogram analysis revealed better diagnostic accuracy for breast lesions than single parametric histogram analysis of either Ktrans or ADC maps.
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Affiliation(s)
- Yanqiong Chen
- Fudan University Shanghai Cancer Center, No. 270, Dong'an Rd, Shanghai, 200032, China
| | - Bin Wu
- Fudan University Shanghai Cancer Center, No. 270, Dong'an Rd, Shanghai, 200032, China
| | - Hui Liu
- Imaging Technology (Shanghai), Shanghai, China
| | - Dan Wang
- Fudan University Shanghai Cancer Center, No. 270, Dong'an Rd, Shanghai, 200032, China
| | - Yajia Gu
- Fudan University Shanghai Cancer Center, No. 270, Dong'an Rd, Shanghai, 200032, China.
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The utility of ADC measurement techniques for differentiation of low- and high-grade clear cell RCC. Pol J Radiol 2018; 83:e446-e451. [PMID: 30655922 PMCID: PMC6334124 DOI: 10.5114/pjr.2018.80207] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2018] [Accepted: 06/20/2018] [Indexed: 01/29/2023] Open
Abstract
Purpose To evaluate the diffusion properties of clear cell renal cell carcinoma (ccRCC) on magnetic resonance imaging (MRI) concerning their Fuhrman nuclear grades and sizes, and to compare the diagnostic performance of two ROI placement techniques for apparent diffusion coefficient (ADC) measurement (entire mass vs. only the darkest region of the mass). Material and methods Fifty-one ccRCC were enrolled in the study and grouped into low-grade ccRCC (Fuhrman grade 1 and 2, n = 37) and high-grade ccRCC (Fuhrman grade 3 and 4, n = 14). Selective ADC (Sel-ADC) measurement was performed by placing a circular ROI that included the darkest region of the tumour on ADC map images. Extensive ADC (Ext-ADC) measurement was performed by drawing an ROI that covered the entire tumour. Results The Sel-ADC value was lower in high-grade ccRCC (p = 0.019), whereas the Ext-ADC value did not show a statistically significant difference (p = 0.42). Sel-ADC value of a ≤ 1.405 mm2/s has a sensitivity, specificity, positive predictive value, negative predictive value, and accuracy value of 78.6, 72.2, 73.87, 77.13, and 75.4, respectively, to differentiate high-grade from low-grade ccRCC. The size and Fuhrman grade of the ccRCC were inversely correlated with the Sel-ADC value; however, the correlations were weak (r = -0.322, p = 0.021 and r = -0.376, p = 0.006, respectively). There was no difference between ADC values of small (≤ 4 cm) and large (> 4 cm) ccRCCs. Conclusions The ADC value of the darkest region in solid part of the ccRCC may play a role in predicting the nuclear grade of ccRCC.
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Histogram analysis of apparent diffusion coefficient maps for differentiating malignant from benign parotid gland tumors. Eur Arch Otorhinolaryngol 2018; 275:2151-2157. [DOI: 10.1007/s00405-018-5052-y] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Accepted: 06/28/2018] [Indexed: 12/25/2022]
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Subtype Differentiation of Small (≤ 4 cm) Solid Renal Mass Using Volumetric Histogram Analysis of DWI at 3-T MRI. AJR Am J Roentgenol 2018; 211:614-623. [PMID: 29812980 DOI: 10.2214/ajr.17.19278] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
OBJECTIVE The purpose of this article is to evaluate the utility of volumetric histogram analysis of apparent diffusion coefficient (ADC) derived from reduced-FOV DWI for small (≤ 4 cm) solid renal mass subtypes at 3-T MRI. MATERIALS AND METHODS This retrospective study included 38 clear cell renal cell carcinomas (RCCs), 16 papillary RCCs, 18 chromophobe RCCs, 13 minimal fat angiomyolipomas (AMLs), and seven oncocytomas evaluated with preoperative MRI. Volumetric ADC maps were generated using all slices of the reduced-FOV DW images to obtain histogram parameters, including mean, median, 10th percentile, 25th percentile, 75th percentile, 90th percentile, and SD ADC values, as well as skewness, kurtosis, and entropy. Comparisons of these parameters were made by one-way ANOVA, t test, and ROC curves analysis. RESULTS ADC histogram parameters differentiated eight of 10 pairs of renal tumors. Three subtype pairs (clear cell RCC vs papillary RCC, clear cell RCC vs chromophobe RCC, and clear cell RCC vs minimal fat AML) were differentiated by mean ADC. However, five other subtype pairs (clear cell RCC vs oncocytoma, papillary RCC vs minimal fat AML, papillary RCC vs oncocytoma, chromophobe RCC vs minimal fat AML, and chromophobe RCC vs oncocytoma) were differentiated by histogram distribution parameters exclusively (all p < 0.05). Mean ADC, median ADC, 75th and 90th percentile ADC, SD ADC, and entropy of malignant tumors were significantly higher than those of benign tumors (all p < 0.05). Combination of mean ADC with histogram parameters yielded the highest AUC (0.851; sensitivity, 80.0%; specificity, 86.1%). CONCLUSION Quantitative volumetric ADC histogram analysis may help differentiate various subtypes of small solid renal tumors, including benign and malignant lesions.
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Abstract
PURPOSE OF REVIEW Renal cell carcinoma is a heterogeneous disease with a spectrum of subtypes and clinical behavior. Quantitative and qualitative imaging biomarkers are sought to correlate with genetic and histologic features and complement pathologic analysis. RECENT FINDINGS Texture analysis, radiogenomics, and modality-specific advancements have yielded an array of renal cell carcinoma imaging biomarkers in the research domain. Although many techniques are promising, standardization and validation of these procedures are needed prior to implementation into clinical practice. SUMMARY We introduce novel imaging techniques and analytic methods which have been shown to contribute to characterization of renal cell carcinoma and its subtypes, aggressiveness, and responsiveness to therapy, including associated advantages and limitations.
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Sasaguri K, Takahashi N. CT and MR imaging for solid renal mass characterization. Eur J Radiol 2017; 99:40-54. [PMID: 29362150 DOI: 10.1016/j.ejrad.2017.12.008] [Citation(s) in RCA: 61] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Revised: 12/04/2017] [Accepted: 12/09/2017] [Indexed: 12/15/2022]
Abstract
As our understanding has expanded that relatively large fraction of incidentally discovered renal masses, especially in small size, are benign or indolent even if malignant, there is growing acceptance of more conservative management including active surveillance for small renal masses. As for advanced renal cell carcinomas (RCCs), nonsurgical and subtype specific treatment options such as immunotherapy and targeted therapy is developing. On these backgrounds, renal mass characterization including differentiation of benign from malignant tumors, RCC subtyping and prediction of RCC aggressiveness is receiving much attention and a variety of imaging techniques and analytic methods are being investigated. In addition to conventional imaging techniques, integration of texture analysis, functional imaging (i.e. diffusion weighted and perfusion imaging) and multivariate diagnostic methods including machine learning have provided promising results for these purposes in research fields, although standardization and external, multi-institutional validations are needed.
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Affiliation(s)
- Kohei Sasaguri
- Department of Radiology, Faculty of Medicine, Saga University, 5-1-1 Nabeshima, Saga, 849-8501, Japan.
| | - Naoki Takahashi
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, United States.
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Diagnostic Performance of DWI for Differentiating High- From Low-Grade Clear Cell Renal Cell Carcinoma: A Systematic Review and Meta-Analysis. AJR Am J Roentgenol 2017; 209:W374-W381. [PMID: 29023154 DOI: 10.2214/ajr.17.18283] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
OBJECTIVE The purpose of our study was to review the diagnostic performance of DWI for differentiating high- from low-grade clear cell renal cell carcinoma (RCC). MATERIALS AND METHODS MEDLINE, EMBASE, and Cochrane library databases were searched up to March 15, 2017. We included diagnostic accuracy studies that used DWI for differentiating high- from low-grade clear cell RCC compared with histopathologic results of Fuhrman grade based on nephrectomy or biopsy specimens in original research articles. Two independent reviewers assessed methodologic quality using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Sensitivity and specificity of the included studies were pooled and graphically presented using a hierarchic summary ROC plot. For heterogeneity exploration, we assessed the presence of a threshold effect and performed meta-regression analyses. RESULTS Eight retrospective studies (394 patients with 397 clear cell RCCs) were included. Pooled sensitivity was 0.78 (95% CI, 0.68-0.85) with a specificity of 0.86 (95% CI, 0.70-0.94). A considerable threshold effect was observed with a correlation coefficient of 0.811 (95% CI, 0.248-0.964) between the sensitivity and false-positive rate. At meta-regression analysis, apparent diffusion coefficient (× 10 mm2/s) cutoff value (< 1.57 vs ≥ 1.57; p = 0.03) and location of ROI (solid portion vs whole tumor; p = 0.04) were significant factors affecting heterogeneity. Other factors with regard to patients and tumors, study, and MRI characteristics were not significant (p = 0.17-0.91). CONCLUSION DWI shows moderate diagnostic performance for differentiating high-from low-grade clear cell RCC. Substantial heterogeneity was observed because of a threshold effect. Further prospective studies may be needed; all included studies were retrospective.
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PET-MRI of the Pancreas and Kidneys. CURRENT RADIOLOGY REPORTS 2017. [DOI: 10.1007/s40134-017-0229-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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Chen C, Kang Q, Xu B, Guo H, Wei Q, Wang T, Ye H, Wu X. Differentiation of low- and high-grade clear cell renal cell carcinoma: Tumor size versus CT perfusion parameters. Clin Imaging 2017; 46:14-19. [PMID: 28686936 DOI: 10.1016/j.clinimag.2017.06.010] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2017] [Revised: 06/11/2017] [Accepted: 06/28/2017] [Indexed: 01/20/2023]
Abstract
PURPOSE To compare the utility of tumor size and CT perfusion parameters for differentiation of low- and high-grade clear cell renal cell carcinoma (RCC). MATERIALS AND METHODS Tumor size, Equivalent blood volume (Equiv BV), permeability surface-area product (PS), blood flow (BF), and Fuhrman pathological grading of clear cell RCC were retrospectively analyzed. RESULTS High-grade clear cell RCC had significantly higher tumor size and lower PS than low grade. Tumor size positively correlated with Fuhrman grade, but PS negatively did. CONCLUSIONS Tumor size and PS were significantly independent indexes for differentiating high-grade from low-grade clear cell RCC.
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Affiliation(s)
- Chao Chen
- Department of Radiology, PLA Army General Hospital, Beijing 100700, China
| | - Qinqin Kang
- Department of Radiology, Changhai Hospital of Shanghai, The second Military Medical University, Shanghai 200433, China
| | - Bing Xu
- Department of Radiology, Changhai Hospital of Shanghai, The second Military Medical University, Shanghai 200433, China
| | - Hairuo Guo
- Affiliated Bayi Brain Hospital, PLA Army General Hospital, Beijing 100700, China
| | - Qiang Wei
- Department of Orthopaedics, Changhai Hospital of Shanghai, The second Military Medical University, Shanghai 200433, China
| | - Tiegong Wang
- Department of Radiology, Changhai Hospital of Shanghai, The second Military Medical University, Shanghai 200433, China
| | - Hui Ye
- Hunan Tumor Hospital, PET-CT Center, Changsha 410013, China
| | - Xinhuai Wu
- Department of Radiology, PLA Army General Hospital, Beijing 100700, China.
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Correlation between CT perfusion parameters and Fuhrman grade in pTlb renal cell carcinoma. Abdom Radiol (NY) 2017; 42:1464-1471. [PMID: 27999886 DOI: 10.1007/s00261-016-1009-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
PURPOSE To evaluate the correlation of CT perfusion parameters with the Fuhrman grade in pT1b (4-7 cm) renal cell carcinoma (RCC). METHODS CT perfusion imaging and Fuhrman pathological grading of pT1b RCC were performed in 48 patients (10 grade 1, 27 grade 2, 9 grade 3, and 2 grade 4). Equivalent blood volume (BV Equiv), permeability surface area product (PS), and blood flow (BF) of tumors were measured. Grade 1 and 2 were defined as low-grade group (n = 37), meanwhile high-grade group (n = 11) included grade 3 and 4. Comparisons of CT perfusion parameters and tumor size of the two different groups were performed. Correlations between CT perfusion parameters, Fuhrman grade (grade 1, 2, 3, and 4), and tumor size were assessed. RESULTS PS was significantly lower in high grade than in low-grade pT1b RCC (P = 0.004). However, no significant differences were found in BV Equiv and BF between the two groups (P > 0.05 for both). The optimal threshold value, sensitivity, specificity, and the area under the ROC curve for distinguishing the two groups using PS were 68.8 mL/100 g/min, 0.7, 0.8, and 0.8, respectively. Negative significant correlation was observed between PS and Fuhrman grade (r = -0.338, P = 0.019). CONCLUSIONS The PS of pT1b RCC had negative significant correlation with Fuhrman grade. CT perfusion appeared to be a non-invasive means to predict high Fuhrman grade of pT1b RCC preoperatively and guide the optimal treatment for the patient.
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Parada Villavicencio C, Mc Carthy RJ, Miller FH. Can diffusion-weighted magnetic resonance imaging of clear cell renal carcinoma predict low from high nuclear grade tumors. Abdom Radiol (NY) 2017; 42:1241-1249. [PMID: 27904923 DOI: 10.1007/s00261-016-0981-7] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVE To assess the diagnostic performance of the apparent diffusion coefficient (ADC) in predicting the Fuhrman nuclear grading of clear cell renal cell carcinomas (ccRCC). MATERIALS AND METHODS A total of 129 patients who underwent partial and radical nephrectomies with pathology-proven ccRCC were retrospectively evaluated. Histopathological characteristics and nuclear grades were analyzed. In addition, conventional magnetic resonance imaging (MRI) features were assessed in consensus by two radiologists to discriminate nuclear grading. ADC values were obtained from a region of interest (ROI) measurement in the ADC maps calculated from diffusion-weighted imaging (DWI) using b values of 50, 500, and 800 s/mm2. The threshold values for predicting and differentiating low-grade cancers (Fuhrman I-II) from high grade (Fuhrman III-IV) was obtained using binary logistic regression. The ADC cut-off value for differentiating low- and high-grade tumors was determined using classification analysis. RESULTS Significant associations (P < 0.001) were found between nuclear grading, conventional MR features, and DWI. Hemorrhage, necrosis, perirenal fat invasion, enhancement homogeneity, and cystic component were identified as independent predictors of tumor grade. High-grade ccRCC had significantly lower mean ADC values compared to low-grade tumors. An ADC cut-off value of 1.6 × 10-3 mm2/s had an optimal predictive percentage of 65.5% for low-grade tumors above this threshold and 81% for high-grade ccRCC below this threshold. Overall predictive accuracy was 70.5%. CONCLUSION The addition of ADC values to a model based on MRI conventional features demonstrates increased sensitivity and high specificity improving the distinguishing accuracy between both high-grade and low-grade ccRCC.
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Affiliation(s)
- Carolina Parada Villavicencio
- Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 North Saint Clair St. Suite 800, Chicago, IL, USA
| | - Robert J Mc Carthy
- Department of Anesthesiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 North Saint Clair St. Suite 1050, Chicago, IL, USA
| | - Frank H Miller
- Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 North Saint Clair St. Suite 800, Chicago, IL, USA.
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Differentiation grade for extrahepatic bile duct adenocarcinoma: Assessed by diffusion-weighted imaging at 3.0-T MR. Eur J Radiol 2016; 85:1980-1986. [PMID: 27776649 DOI: 10.1016/j.ejrad.2016.09.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2016] [Revised: 08/29/2016] [Accepted: 09/07/2016] [Indexed: 02/06/2023]
Abstract
PURPOSE- To assess the pathological differentiation grade in the patients with extrahepatic bile duct adenocarcinoma (EBDA) using diffusion-weighted imaging (DWI) at 3.0-T MR. METHODS- Sixty-eight patients who were clinically and histologically diagnosed with EBDA underwent abdominal DWI within 2 weeks before surgery. The lesion signal intensity, signal intensity ratio of the lesion and hepar (SIR-LH) value, and apparent diffusion coefficient (ADC) value in patients with EBDA were retrospectively analysed. RESULTS -In the 68 patients, 22 well-differentiated, 36 moderately-differentiated, and 10 poorly-differentiated EBDAs were histopathological confirmed. These EBDAs exhibited hyper-intensity on DWI in 95.59% of patients. Hyper-intensity lesions were found in 90.91% of patients with good-differentiation, in 97.22% with moderate-differentiation and in 100% with poor-differentiation. There showed no statistical difference for the lesion signal intensity (P=0.426) and SIR-LH value (P=0.766) on DWI among three groups. The median ADC value of the well-differentiated, moderately-differentiated and poorly-differentiated EBDAs were 1.506×10-3mm2/s, 1.275×10-3mm2/s and 1.154×10-3mm2/s, respectively. As the pathological differentiation grade decreased, the lesion ADC value of EBDA gradually declined (x2=51.220, P=0.000). The ADC value <1.184×10-3mm2/s can predict the poorly-differentiated EBDA with a sensitivity of 100% and a specificity of 94.83%. The ADC value >1.316×10-3mm2/s can forecast the well-differentiated EBDA with a sensitivity of 100% and a specificity of 84.78%. CONCLUSIONS- The histopathological differentiation grade of EBDA can be detected non-invasively using DWI at 3.0-T MR.
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