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Wen X, Qiu H, Ying L, Huang M, Xiao Y, Fan C. Diagnostic efficacy of combining diffusion-weighted magnetic resonance imaging with serum Mucin 1, Mucin 13, and Mucin 16 in distinguishing borderline from malignant epithelial ovarian tumors. Asia Pac J Clin Oncol 2025; 21:115-122. [PMID: 38221766 PMCID: PMC11733834 DOI: 10.1111/ajco.14045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 09/20/2023] [Accepted: 12/28/2023] [Indexed: 01/16/2024]
Abstract
AIMS To enhance ovarian tumor diagnosis beyond conventional methods, this study explored combining diffusion-weighted magnetic resonance imaging (DWI-MRI) and serum biomarkers (Mucin 1 [MUC1], MUC13, and MUC16) for distinguishing borderline from malignant epithelial ovarian tumors. METHODS A total of 126 patients, including 71 diagnosed with borderline (BEOTs) and 55 with malignant epithelial ovarian tumors (MEOTs), underwent preoperative DWI-MRI. Region of interest (ROI) was manually drawn along the solid component's boundary of the largest tumor, focusing on areas with potentially the lowest apparent diffusion coefficient (ADC). For entirely cystic tumors, a free-form ROI enclosed the maximum number of septa while targeting the lowest ADC. Serum biomarkers were determined using enzyme-linked immunosorbent assay. RESULTS Basic morphological traits proved inadequate for malignancy diagnosis, warranting this investigation. BEOTs had an ADC mean of (1.670 ± 0.250) × 103 mm2/s, while MEOTs had a lower ADC mean of (1.332 ± 0.481) × 103 mm2/s, with a sensitivity of 63.6% and specificity of 90.1%. Median MUC1 (167.0 U/mL vs. 87.3 U/mL), MUC13 (12.44 ng/mL vs. 7.77 ng/mL), and MUC16 (180.6 U/mL vs. 36.1 U/mL) levels were higher in MEOTs patients. The biomarker performance was: MUC1, sensitivity 50.9%, specificity 100%; MUC13, sensitivity 56.4%, specificity 78.9%; MUC16, sensitivity 83.64%, specificity 100%. Combining serum biomarkers and ADC mean resulted in a sensitivity of 96.4% and specificity of 100%. CONCLUSION The integration of DWI-MRI with serum biomarkers (MUC1, MUC13, and MUC16) achieves exceptional diagnostic accuracy, offering a powerful tool for the precise differentiation between borderline and malignant epithelial ovarian tumors.
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Affiliation(s)
- Xiao‐Ting Wen
- Department of ObstetricsThe People's Hospital of PingYangWenzhouChina
| | - Hai‐Feng Qiu
- Department of RadiologyNingbo Yinzhou NO.2 HospitalNingboChina
| | - Ling‐Ling Ying
- Department of RadiologyNingbo Yinzhou NO.2 HospitalNingboChina
| | - Min Huang
- Department of ObstetricsThe People's Hospital of PingYangWenzhouChina
| | - Yun‐Zhou Xiao
- Department of RadiologyThe People's Hospital of PingYangWenzhouChina
| | - Chen‐Chen Fan
- Department of RadiologyNingbo Yinzhou NO.2 HospitalNingboChina
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Zhang M, Zhang Y, Liu G, Ge L. A new risk algorithm combining D-dimer and HE4 differentiates borderline tumor from patients with ovarian tumor. Transl Cancer Res 2025; 14:93-101. [PMID: 39974418 PMCID: PMC11833360 DOI: 10.21037/tcr-24-1276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2024] [Accepted: 12/04/2024] [Indexed: 02/21/2025]
Abstract
Background Timely diagnosis of borderline ovarian tumors (BOTs) is crucial for preserving fertility and ovarian function. However, current markers for detecting BOTs lack effectiveness. This research aims to identify and validate the role of small molecular markers in diagnosing BOTs. Six small molecule markers-human epididymis protein 4 (HE4), carbohydrate antigen 125 (CA125), fibrinogen (FIB), D-dimer (DD), platelet (PLT), and homocysteine (HCY)-were identified as candidate markers. Methods Candidate markers were evaluated using the receiver operating characteristic (ROC) curve to assess their diagnostic efficacy for BOTs. Suitable markers were chosen through statistical methods to develop a risk prediction model. The model's diagnostic performance was assessed using parameters such as the area under the ROC curve (AUC), Youden index, sensitivity, and specificity. Results There were significant differences in the levels of HE4, CA125, FIB, and DD between the group of BOTs and benign ovarian tumors. while PLT and HCY levels did not show significant variation. Notably, DD, with an AUC of 0.818, demonstrated utility in diagnosing BOTs. Building on this, a risk prediction model was created based on the diagnostic value of DD and HE4, resulting in an AUC of 0.852, particularly effective in diagnosing serous BOTs (AUC: 0.941). Significant diagnostic value was also observed in ovarian tumors with a diameter less than 4 cm (AUC: 0.772). Conclusions Changes in DD levels in BOTs patients can be utilized for disease diagnosis, especially when combined with HE4, resulting in improved diagnostic efficiency.
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Affiliation(s)
- Mi Zhang
- Department of Obstetrics and Gynecology, Women's Hospital of Nanjing Medical University (Nanjing Maternity and Child Health Care Hospital), Nanjing, China
| | - Ya Zhang
- Department of Obstetrics and Gynecology, Women's Hospital of Nanjing Medical University (Nanjing Maternity and Child Health Care Hospital), Nanjing, China
| | - Guangquan Liu
- Department of Obstetrics and Gynecology, Women's Hospital of Nanjing Medical University (Nanjing Maternity and Child Health Care Hospital), Nanjing, China
| | - Lili Ge
- Department of Obstetrics and Gynecology, Women's Hospital of Nanjing Medical University (Nanjing Maternity and Child Health Care Hospital), Nanjing, China
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Cao Y, Lu Y, Shao W, Zhai W, Song J, Zhang A, Huang S, Zhao X, Cheng W, Wu F, Chen T. Time-dependent diffusion MRI-based microstructural mapping for differentiating high-grade serous ovarian cancer from serous borderline ovarian tumor. Eur J Radiol 2024; 178:111622. [PMID: 39018648 DOI: 10.1016/j.ejrad.2024.111622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 06/24/2024] [Accepted: 07/11/2024] [Indexed: 07/19/2024]
Abstract
PURPOSE To investigate the value of microstructural characteristics derived from time-dependent diffusion MRI in distinguishing high-grade serous ovarian cancer (HGSOC) from serous borderline ovarian tumor (SBOT) and the associations of immunohistochemical markers with microstructural features. METHODS Totally 34 HGSOC and 12 SBOT cases who received preoperative pelvic MRI were retrospectively included in this study. Two radiologists delineated the tumors to obtain the regions of interest (ROIs). Time-dependent diffusion MRI signals were fitted by the IMPULSED (imaging microstructural parameters using limited spectrally edited diffusion) model, to extract microstructural parameters, including fraction of the intracellular component (fin), cell diameter (d), cellularity and extracellular diffusivity (Dex). Apparent diffusion coefficient (ADC) values were obtained from standard diffusion-weighted imaging (DWI). The parameters of HGSOCs and SBOTs were compared, and the diagnostic performance was evaluated. The associations of microstructural indexes with immunopathological parameters were assessed, including Ki-67, P53, Pax-8, ER and PR. RESULTS In this study, fin, cellularity, Dex and ADC had good diagnostic performance levels in differentiating HGSOC from SBOT, with AUCs of 0.936, 0.909, 0.902 and 0.914, respectively. There were no significant differences in diagnostic performance among these parameters. Spearman analysis revealed in the HGSOC group, cellularity had a significant positive correlation with P53 expression (P = 0.028, r = 0.389) and Dex had a significant positive correlation with Pax-8 expression (P = 0.018, r = 0.415). ICC showed excellent agreement for all parameters. CONCLUSION Time-dependent diffusion MRI had value in evaluating the microstructures of HGSOC and SBOT and could discriminate between these tumors.
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Affiliation(s)
- Yuwei Cao
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, China
| | - Yao Lu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, China
| | - Wenhui Shao
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, China
| | - Weiling Zhai
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, China
| | - Jiacheng Song
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, China
| | - Aining Zhang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, China
| | - Shan Huang
- Philips (China) Investment Co. Ltd Building A1, No 718, Ling Shi Road, Jing'an District, Shanghai, China
| | - Xiance Zhao
- Philips (China) Investment Co. Ltd Building A1, No 718, Ling Shi Road, Jing'an District, Shanghai, China
| | - Wenjun Cheng
- Department of Obstetrics & Gynecology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, China
| | - Feiyun Wu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, China.
| | - Ting Chen
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, China.
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Yu X, Zou Y, Wang L, Yang H, Jiao J, Yu H, Zhang S. Radiomics nomogram for preoperative differentiation of early-stage serous borderline ovarian tumors and serous malignant ovarian tumors. Front Oncol 2024; 13:1269589. [PMID: 38288103 PMCID: PMC10822955 DOI: 10.3389/fonc.2023.1269589] [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: 07/30/2023] [Accepted: 12/18/2023] [Indexed: 01/31/2024] Open
Abstract
Objectives This study aimed to construct a radiomics nomogram and validate its performance in the preoperative differentiation between early-stage (I and II) serous borderline ovarian tumors (SBOTs) and serous malignant ovarian tumors (SMOTs). Methods Data were collected from 80 patients with early-stage SBOTs and 102 with early-stage SMOTs (training set: n = 127; validation set: n = 55). Univariate and multivariate analyses were performed to identify the independent clinicoradiological factors. A radiomics signature model was constructed using radiomics features extracted from multidetector computed tomography images of the venous phase, in which the least absolute shrinkage and selection operator regression was employed to lessen the dimensionality of the data and choose the radiomics features. A nomogram model was established by combining independent clinicoradiological factors with the radiomics signature. The performance of nomogram calibration, discrimination, and clinical usefulness was evaluated using training and validation sets. Results In terms of clinicoradiological characteristics, age (p = 0.001), the diameter of the solid component (p = 0.009), and human epididymis protein 4 level (p < 0.001) were identified as the independent risk factors of SMOT, for which the area under the curves (AUCs) were calculated to be 0.850 and 0.836 in the training and validation sets, respectively. Nine features were finally selected to construct the radiomics signature model, which exhibited AUCs of 0.879 and 0.826 for the training and validation sets, respectively. The nomogram model demonstrated considerable calibration and discrimination with AUCs of 0.940 and 0.909 for the training and validation sets, respectively. The nomogram model displayed more prominent clinical usefulness than the clinicoradiological and radiomics signature models according to the decision curve analysis. Conclusions The nomogram model can be employed as an individualized preoperative non-invasive tool for differentiating early-stage SBOTs from SMOTs.
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Affiliation(s)
- Xinping Yu
- Department of Gynecology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Yuwei Zou
- Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Lei Wang
- Department of Gynecology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Hongjuan Yang
- Department of Gynecology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Jinwen Jiao
- Department of Gynecology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Haiyang Yu
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Shuai Zhang
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China
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Shin KH, Kim HH, Yoon HJ, Kim ET, Suh DS, Kim KH. The Discrepancy between Preoperative Tumor Markers and Imaging Outcomes in Predicting Ovarian Malignancy. Cancers (Basel) 2022; 14:cancers14235821. [PMID: 36497302 PMCID: PMC9737674 DOI: 10.3390/cancers14235821] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 11/18/2022] [Accepted: 11/22/2022] [Indexed: 11/29/2022] Open
Abstract
Preoperative tumor markers and imaging often differ in predicting whether an ovarian tumor is malignant. Therefore, we evaluated the correlation between the predictive values of imaging and tumor markers for diagnosing ovarian tumors, especially when there were discrepancies between the two. We enrolled 1047 patients with ovarian tumors. The predictive values and concordance rates between the preoperative risk of ovarian malignancy algorithm (ROMA) and imaging, including CT and MRI, were evaluated. Diagnoses of 561 CT (77.9%) and 322 MRI group (69.2%) participants were consistent with the ROMA. Among them, 96.4% of the CT (541/561) and 92.5% of the MRI (298/322) group predicted an accurate diagnosis. In contrast, 67.3% (101/150) of CT and 75.2% (100/133) of MRI cases accurately predicted the diagnosis in cases with discrepancies between ROMA and CT or MRI; a total of 32% (48/150) of the CT and 25.5% (34/133) of the MRI group showed an accurate ROMA diagnosis in cases with discrepancies between ROMA and imaging. In the event of a discrepancy between ROMA and imaging when ovarian tumor malignancy prediction, the question is which method should take precedence. This study demonstrates that MRI has the greatest diagnostic accuracy, followed by CT and ROMA. It is also important to understand underlying diseases and benign conditions and rare histopathologies of malignant tumors.
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Affiliation(s)
- Kyung-Hwa Shin
- Department of Laboratory Medicine, Pusan National University School of Medicine, Busan 49241, Republic of Korea
- Biomedical Research Institute, Pusan National University Hospital, Busan 49241, Republic of Korea
| | - Hyung-Hoi Kim
- Department of Laboratory Medicine, Pusan National University School of Medicine, Busan 49241, Republic of Korea
- Biomedical Research Institute, Pusan National University Hospital, Busan 49241, Republic of Korea
| | - Hyung Joon Yoon
- Biomedical Research Institute, Pusan National University Hospital, Busan 49241, Republic of Korea
- Department of Obstetrics and Gynecology, Pusan National University School of Medicine, Busan 49241, Republic of Korea
| | - Eun Taeg Kim
- Biomedical Research Institute, Pusan National University Hospital, Busan 49241, Republic of Korea
- Department of Obstetrics and Gynecology, Pusan National University School of Medicine, Busan 49241, Republic of Korea
| | - Dong Soo Suh
- Biomedical Research Institute, Pusan National University Hospital, Busan 49241, Republic of Korea
- Department of Obstetrics and Gynecology, Pusan National University School of Medicine, Busan 49241, Republic of Korea
| | - Ki Hyung Kim
- Biomedical Research Institute, Pusan National University Hospital, Busan 49241, Republic of Korea
- Department of Obstetrics and Gynecology, Pusan National University School of Medicine, Busan 49241, Republic of Korea
- Correspondence:
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Li XL, Han PF, Wang W, Shao LW, Wang YW. Multi-slice spiral computed tomography in differential diagnosis of gastric stromal tumors and benign gastric polyps, and gastric stromal tumor risk stratification assessment. World J Gastrointest Oncol 2022; 14:2004-2013. [PMID: 36310702 PMCID: PMC9611439 DOI: 10.4251/wjgo.v14.i10.2004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 07/18/2022] [Accepted: 09/14/2022] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND The biological characteristics of gastric stromal tumors are complex, and their incidence has increased in recent years. Gastric stromal tumors (GST) have potential malignant tendencies, and the probability of transformation into malignant tumors is as high as 20%-30%.
AIM To investigate the value of multi-slice spiral computed tomography (MSCT) in the differential diagnosis of GST and benign gastric polyps, and GST risk stratification assessment.
METHODS We included 64 patients with GST (GST group) and 60 with benign gastric polyps (control group), confirmed by pathological examination after surgery in PLA General Hospital, from January 2016 to June 2021. The differences in the MSCT imaging characteristic parameters and enhanced CT values between the two groups before surgery were compared. According to the National Institutes of Health’s standard, GST is divided into low- and high-risk groups for MSCT imaging characteristic parameters and enhanced CT values.
RESULTS The incidences of extraluminal growth, blurred boundaries, and ulceration in the GST group were significantly higher than those in the control group (P < 0.05). The CT values and enhanced peak CT values in the arterial phase in the CST group were higher than those in the control group (P < 0.05). The MSCT differential diagnosis of GST and gastric polyp sensitivity, specificity, misdiagnosis rate, missed diagnosis rate, and areas under the curve (AUCs) were 73.44 %, 83.33%, 26.56%, 16.67%, 0.784, respectively. The receiver operating characteristic curves were plotted with the arterial CT value and enhanced peak CT value, with a statistical difference. The results showed that the sensitivity, specificity, misdiagnosis rate, missed diagnosis rate, and AUC value of arterial CT in the differential diagnosis of GST and gastric polyps were 80.18%, 62.20%, 19.82%, 37.80%, and 0.710, respectively. The sensitivity, specificity, misdiagnosis rate, missed diagnosis rate, and AUC value of the enhanced peak CT value in the differential diagnosis of GST and gastric polyps were 67.63%, 60.40%, 32.37%, 39.60%, and 0.710, respectively. The incidence of blurred lesion boundaries and ulceration in the high-risk group was significantly higher than that in the low-risk group (P < 0.05). The arterial phase and enhanced peak CT values in the high-risk group were significantly higher than those in the low-risk group (P < 0.05).
CONCLUSION Presurgical MSCT examination has important value in the differential diagnosis of GST and gastric benign polyps and can effectively evaluate the risk grade of GST patients.
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Affiliation(s)
- Xiao-Long Li
- Diagnostic Radiology Department, The First Medical Center of PLA General Hospital, Beijing 100853, China
| | - Peng-Fei Han
- Diagnostic Radiology Department, The First Medical Center of PLA General Hospital, Beijing 100853, China
| | - Wei Wang
- Diagnostic Radiology Department, The First Medical Center of PLA General Hospital, Beijing 100853, China
| | - Li-Wei Shao
- Pathology Department, The Seventh Medical Center of PLA General Hospital, Beijing 100700, China
| | - Ying-Wei Wang
- Diagnostic Radiology Department, The First Medical Center of PLA General Hospital, Beijing 100853, China
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