• Lateral lymph node dissection
• lateral lymph node metastasis
• locally advanced rectal cancer
• magnetic resonance imaging
• neoadjuvant therapy

• Computed tomography scan
• Diagnosis
• High-resolution anoscopy
• Imaging
• MRI
• PET computed tomography
• Staging
• Symptoms

• Humans
• Anus Neoplasms/diagnosis
• Anus Neoplasms/diagnostic imaging

• Lateral lymph node
• Pathological features
• Rectal cancer
• Survival

• No. 2022YFC2505003 the National Key Research and Development Program/Prevention and Treatment Research on Commonly Occurring and Prevalent Diseases
• No. 2017-12 M-1e006 the Medicine and Health Technology Innovation Project of the Chinese Academy of Medical Sciences

• Lateral lymph node dissection
• Lateral pelvic lymph nodes
• Radiotherapy
• Rectal tumors
• prognosis

• Humans
• Rectal Neoplasms/pathology
• Rectal Neoplasms/therapy
• Rectal Neoplasms/mortality
• Male
• Female
• Lymphatic Metastasis/pathology
• Middle Aged
• Aged
• Prognosis
• Neoadjuvant Therapy
• Magnetic Resonance Imaging
• Adult
• Lymph Nodes/pathology

• Adjuvant therapy
• Local advanced rectal cancer
• Long-term prognosis
• Neoadjuvant therapy
• Recurrence risk factors
• yStage Ⅰ
• yStage Ⅱ

• Artificial intelligence
• MRI
• Rectal cancer

• Humans
• Rectal Neoplasms/diagnostic imaging
• Rectal Neoplasms/pathology
• Magnetic Resonance Imaging/methods
• Artificial Intelligence
• Female
• Male
• Middle Aged
• Aged
• Sensitivity and Specificity
• Adult
• Algorithms
• Aged, 80 and over

• Fujifilm Holdings
• Osaka University

• Lateral pelvic lymph nodes
• Locally advanced rectal cancer
• Oligometastases
• Progression-free survival
• Propensity score matching
• Recurrence patterns

• Humans
• Rectal Neoplasms/pathology
• Rectal Neoplasms/therapy
• Rectal Neoplasms/mortality
• Male
• Female
• Propensity Score
• Middle Aged
• Retrospective Studies
• Chemoradiotherapy
• Lymphatic Metastasis
• Aged
• Lymph Nodes/pathology
• Pelvis
• Adult
• Neoplasm Recurrence, Local/pathology
• Neoplasm Recurrence, Local/therapy
• Survival Rate
• Prognosis

• No. 2020-2-1027 Capital's Funds for Health Improvement and Research
• Z181100001718192 Beijing Municipal Science & Technology Commission
• No. 82073333 National Natural Science Foundation
• DFL20220902 Beijing Hospitals Authority's Ascent Plan
• ZLRK202327 Beijing Municipal Administration of Hospitals Clinical Medical Development of special funding support, code

• chemoradiotherapy
• lateral pelvic node
• magnetic resonance imaging
• neoadjuvant chemotherapy
• rectal neoplasms

• DCE-MRI
• Metachronous metastases
• Predictive model
• Rectal cancer

• Humans
• Rectal Neoplasms/pathology
• Rectal Neoplasms/diagnostic imaging
• Male
• Female
• Middle Aged
• Retrospective Studies
• Magnetic Resonance Imaging/methods
• Contrast Media
• Aged
• Neoplasms, Second Primary/diagnostic imaging
• Neoplasms, Second Primary/pathology
• Predictive Value of Tests
• Adult
• Neoplasm Staging

• 81801662 National Natural Science Foundation of China

• lateral lymph nodes
• mri re-review
• rectal cancer

• Humans
• Cross-Sectional Studies
• Prognosis
• Retrospective Studies
• Radiology
• Rectal Neoplasms/diagnostic imaging
• Rectal Neoplasms/therapy
• Lymph Nodes/diagnostic imaging
• Neoplasm Staging

• artificial intelligence
• cancer diagnosis
• deep learning
• deep neural network
• medical image
• overfitting prevention technique

• RM32G0178B8 BBSRC
• MC_PC_17171 MRC, UK
• RP202G0230 Royal Society, UK
• AA/18/3/34220 BHF, UK
• RM60G0680 Hope Foundation for Cancer Research, UK
• P202PF11 GCRF, UK
• RP202G0289 Sino-UK Industrial Fund, UK
• P202ED10, P202RE969 LIAS, UK
• P202RE237 Data Science Enhancement Fund, UK
• 24NN201 Fight for Sight, UK
• OP202006 Sino-UK Education Fund, UK
• RM32G0178B8 BBSRC, UK
• 2023SJZD125 Major project of philosophy and social science research in colleges and universities in Jiangsu Province, China

• deep lesion
• indocyanine green
• multimodal
• photoacoustic endoscopy
• spectroscopic imaging

• Humans
• Lymphatic Metastasis/diagnostic imaging
• Lymphatic Metastasis/pathology
• Fluorodeoxyglucose F18
• Positron Emission Tomography Computed Tomography/methods
• Radiopharmaceuticals
• Diagnostic Tests, Routine
• Sensitivity and Specificity
• Lymph Nodes/diagnostic imaging
• Lymph Nodes/pathology
• Positron-Emission Tomography/methods
• Rectal Neoplasms/diagnostic imaging
• Rectal Neoplasms/surgery
• Rectal Neoplasms/pathology

• aspect ratio
• lateral pelvic lymph node
• local recurrence
• pathological morphology
• rectal cancer

The aim of this study was to explore the feasibility of a high-resolution T2-weighted imaging (HR-T2WI)-based radiomics prediction model for diagnosing metastatic lymph nodes (LNs) within the mesorectum in rectal cancer.

A total of 604 LNs (306 metastatic and 298 non-metastatic) from 166 patients were obtained. All patients underwent HR-T2WI examination and total mesorectal excision (TME) surgery. Four kinds of segmentation methods were used to select region of interest (ROI), including method 1 along the border of LNs; method 2 along the expanded border of LNs with an additional 2–3 mm; method 3 covering the border of LNs only; and method 4, a circle region only within LNs. A total of 1,409 features were extracted for each method. Variance threshold method, Select K Best, and Lasso algorithm were used to reduce the dimension. All LNs were divided into training and test sets. Fivefold cross-validation was used to build the logistic model, which was evaluated by the receiver operating characteristic (ROC) with four indicators, including area under the curve (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). Three radiologists with different working experience in diagnosing rectal diseases assessed LN metastasis respectively. The diagnostic efficiencies with each of four segmentation methods and three radiologists were compared to each other.

For the test set, the AUCs of four segmentation methods were 0.820, 0.799, 0.764, and 0.741; the ACCs were 0.725, 0.704, 0.709, and 0.670; the SEs were 0.756, 0.634, 0.700, and 0.589; and the SPs were 0.696, 0.772, 0.717, and 0.750, respectively. There was no statistically significant difference in AUC between the four methods (p > 0.05). Method 1 had the highest values of AUC, ACC, and SE. For three radiologists, the overall diagnostic efficiency was moderate. The corresponding AUCs were 0.604, 0.634, and 0.671; the ACCs were 0.601, 0.632, and 0.667; the SEs were 0.366, 0.552, and 0.392; and the SPs were 0.842, 0.715, and 0.950, respectively.

The proposed HR-T2WI-based radiomic signature exhibited a robust performance on predicting mesorectal LN status and could potentially be used for clinicians in order to determine the status of metastatic LNs in rectal cancer patients.

• Acoustics
• Animals
• Endoscopy/methods
• Indocyanine Green/chemistry
• Molecular Imaging
• Photoacoustic Techniques/methods
• Rabbits

• MRI
• Mesorectal lymph nodes
• N-staging
• Neoadjuvant therapy
• Node by node
• Nomogram
• Rectal cancer
• Restaging

The preoperative prediction of lateral pelvic lymph node (LPLN) metastasis is crucial in determining further treatment strategies for advanced lower rectal cancer patients. In this study, we established a nomogram model to preoperatively predict LPLN metastasis and then externally validated the accuracy of this model.

A total of 287 rectal cancer patients who underwent LPLN dissection were included in this study. Among them, 200 patients from the Peking University First Hospital were included in the development set, and 87 patients from the First Affiliated Hospital of Xi’an Jiaotong University were included in the independent external validation set. Multivariate logistic regression analysis was used to develop the nomogram. The performance of the nomogram was assessed based on its calibration, discrimination, and clinical utility.

Five factors (differentiation grade, extramural vascular invasion, distance of the tumor from the anal verge, perirectal lymph node status, and largest short-axis diameter of LPLN) were identified and included in the nomogram. The nomogram developed based on the analysis showed robust discrimination with an area under the receiver operating characteristic curve (AUC) of 0.878 (95% CI, 0.824–0.932). The validation set showed good discrimination with an AUC of 0.863 (95% CI, 0.779–0.948). Decision curve analysis showed that the nomogram was clinically useful.

The present study proposed a clinical-imaging nomogram with a combination of clinicopathological risk factors and imaging features. After external verification, the predictive power of the nomogram model was satisfactory, and it is expected to be a convenient, visual, and personalized clinical tool for assessing the risk of LPLN metastasis in advanced lower rectal cancer patients.

• National Natural Science Foundation of China

Endoscopic and transanal local resection without lymph node dissection are treatment options for patients with a low risk of lymph node metastasis; however, some patients might have undiagnosed lymph node metastases before surgery. This retrospective study aimed to evaluate the efficacy of preoperative PET/CT for diagnosing regional lymph node metastasis.

Patients who underwent curative resection with lymph node dissection for colorectal cancer at Osaka University between January 2012 and December 2015 were included. The cut-off values appropriate for diagnosing lymph node metastasis were calculated by way of a receiver operating characteristic (ROC) curves from maximum standard unit value (SUVmax) of main tumour, and lymph node short axis, and SUVmax of lymph node. The cut-off values of primary tumour SUVmax: 7, short-axis diameter of the lymph node at 7 mm, and lymph node SUVmax at 1.5 were set.

A total of 541 patients were included. Regional lymph node metastases were confirmed in resected specimens from 187 patients (35 per cent). With a primary tumour SUVmax of 7 used as a cut-off value, the sensitivity and specificity of regional lymph node metastasis were 70.1 per cent and 45.5 per cent respectively. With a cut-off short-axis diameter of the regional lymph node of 7 mm, the sensitivity and specificity of regional lymph node metastasis were 75.2 per cent and 82.6 per cent respectively, and with a cut-off regional lymph node SUVmax of 1.5, the sensitivity and specificity of regional lymph node metastasis were 78.6 per cent and 96.8 per cent respectively. When the diagnostic criteria were defined by a lymph node short-axis diameter of 7 mm or SUVmax of 1.5, the sensitivity and specificity were 87.4 per cent and 81.8 per cent respectively.

Preoperative PET/CT is a useful modality for evaluating regional lymph node metastasis in patients with colorectal cancer.

Although MRI has a substantial role in directing treatment decisions for locally advanced rectal cancer, precise interpretation of the findings is not necessarily available at every institution. In this study, we aimed to develop artificial intelligence-based software for the segmentation of rectal cancer that can be used for staging to optimize treatment strategy and for preoperative surgical simulation.

Images from a total of 201 patients who underwent preoperative MRI were analyzed for training data. The resected specimen was processed in a circular shape in 103 cases. Using these datasets, ground-truth labels were prepared by annotating MR images with ground-truth segmentation labels of tumor area based on pathologically confirmed lesions. In addition, the areas of rectum and mesorectum were also labeled. An automatic segmentation algorithm was developed using a U-net deep neural network.

The developed algorithm could estimate the area of the tumor, rectum, and mesorectum. The Dice similarity coefficients between manual and automatic segmentation were 0.727, 0.930, and 0.917 for tumor, rectum, and mesorectum, respectively. The T2/T3 diagnostic sensitivity, specificity, and overall accuracy were 0.773, 0.768, and 0.771, respectively.

This algorithm can provide objective analysis of MR images at any institution, and aid risk stratification in rectal cancer and the tailoring of individual treatments. Moreover, it can be used for surgical simulations.

• Mesorectal fascia
• Neoadjuvant chemoradiotherapy
• Pathological circumferential margin
• Pretreatment assessment
• Rectal cancer

• Histogram
• LNM
• Multi-parametric magnetic resonance imaging
• Nomogram
• Rectal cancer

• Neoadjuvant treatment
• Overtreatment
• Pathologic stage I
• Radiochemotherapy
• Rectal cancer

• Diagnosis
• Lateral pelvic lymph node dissection
• Lateral pelvic lymph node metastasis
• Radiotherapy
• Rectal cancer
• Treatment

• collagen content
• multifrequency magnetic resonance elastography
• rectal cancer
• risk factors
• stiffness
• tomoelastography
• tumor aggressiveness

Magnetic resonance imaging (MRI)-based lymph node staging remains a significant challenge in the treatment of rectal cancer. Pretreatment evaluation of lymph node metastasis guides the formulation of treatment plans. This systematic review aimed to evaluate the diagnostic performance of MRI in lymph node staging using various morphological criteria.

A systematic search of the EMBASE, Medline, and Cochrane databases was performed. Original articles published between 2000 and January 2021 that used MRI for lymph node staging in rectal cancer were eligible. The included studies were assessed using the QUADAS-2 tool. A bivariate random-effects model was used to conduct a meta-analysis of diagnostic test accuracy.

Thirty-seven studies were eligible for this meta-analysis. The pooled sensitivity, specificity, and diagnostic odds ratio of preoperative MRI for the lymph node stage were 0.73 (95% confidence interval [CI], 0.68–0.77), 0.74 (95% CI, 0.68–0.80), and 7.85 (95% CI, 5.78–10.66), respectively. Criteria for positive mesorectal lymph node metastasis included (A) a short-axis diameter of 5 mm, (B) morphological standard, including an irregular border and mixed-signal intensity within the lymph node, (C) a short-axis diameter of 5 mm with the morphological standard, (D) a short-axis diameter of 8 mm with the morphological standard, and (E) a short-axis diameter of 10 mm with the morphological standard. The pooled sensitivity/specificity for these criteria were 75%/64%, 81%/67%, 74%/79%, 72%/66%, and 62%/91%, respectively. There was no significant difference among the criteria in sensitivity/specificity. The area under the receiver operating characteristic (ROC) curve values of the fitted summary ROC indicated a diagnostic accuracy rate of 0.75–0.81.

MRI scans have minimal accuracy as a reference index for pretreatment staging of various lymph node staging criteria in rectal cancer. Multiple types of evidence should be used in clinical decision-making.

• lymph node
• lymph node staging
• magnetic resonance imaging
• metastasis
• node-by-node
• rectal cancer

• Rectal cancer
• chemical shift effect (CSE)
• lymph nodes (LNs)
• magnetic resonance imaging (MRI)
• nomogram

• lymph node metastasis
• machine learning
• magnetic resonance imaging
• radiomics
• rectal cancer

• Lateral pelvic lymph node
• Maximum standardized uptake value; metastases
• Positron emission tomography
• Rectal cancer

• Adult
• Aged
• Aged, 80 and over
• Female
• Humans
• Lymphatic Metastasis/diagnostic imaging
• Male
• Middle Aged
• Positron Emission Tomography Computed Tomography/methods
• Predictive Value of Tests
• ROC Curve
• Rectal Neoplasms/pathology
• Retrospective Studies

• Rectal cancer
• diagnostic accuracy
• magnetic resonance imaging staging
• neoadjuvant chemoradiotherapy
• pathological staging
• treatment decision-making

This study investigated the predictive value of apparent diffusion coefficient (ADC) histogram parameters of the primary tumor for regional lymph node metastasis (LNM) in pathological T3 stage rectal cancer.

We retrospectively studied 175 patients with T3 stage rectal cancer who underwent preoperative MRI, including diffusion-weighted imaging, between January 2015 and October 2017. Based on pathological analysis of surgical specimens, 113 patients were classified into the LN− group and 62 in the LN+ group. We analyzed clinical data, radiological characteristics and histogram parameters derived from ADC maps. Then, receiver operating characteristic curve (ROC) analyses were generated to determine the best diagnostic performance.

The mean (p=0.002, cutoff=1.08×10^–3 s/mm²), coefficient of variation (CV) (p=0.040, cutoff=0.249) of the ADC map, carbohydrate antigen 199, and N stage with magnetic resonance (mrN stage) were independent factors for LNM. Combining these factors yielded the best diagnostic performance, with the area under the ROC curve of 0.838, 72.9% sensitivity, 79.1% specificity, 65.2% positive predictive value, and 84.5% negative predictive value.

With the mean >1.08×10^–3 s/mm² and CV <0.249, the ADC improved the diagnostic performance of LNM in T3 stage rectal cancer, which could assist surgeons with neoadjuvant chemoradiotherapy.

• diffusion-weighted magnetic resonance imaging
• histogram analysis
• lymph node metastasis
• rectal cancer

• logistic regression
• lymph node
• magnetic resonance imaging
• metastasis
• rectal cancer

To determine the diagnostic accuracy of preoperative T/N stage with magnetic resonance imaging (MRI) in lower and middle rectal cancer patients and the impacts on clinical decision‐making.

A total of 211 patients were recruited from October 2015 to March 2017 in this retrospective study. High‐resolution MRI was performed within 2 weeks before surgery. Histopathologic results were evaluated for the postoperative T/N stage and the diagnostic accuracy of MRI was assessed according to the postoperative histopathologic results. The accuracy, sensitivity, specificity, positive predictive value and negative predictive value were evaluated for T/N staging and κ values were used to evaluate MRI consistent analysis compared with postoperative histopathologic staging.

The overall MRI diagnostic accuracy was 79.62% for T1‐4 staging and 54.50% for N0‐2 staging. The κ values were 0.619 and 0.255 for T1‐4 and N0‐2 staging, respectively. The diagnostic accuracy of MRI for treatment decision‐making was 80.57%.

MRI allows a highly accurate preoperative assessment of T stage but only a fairly accurate preoperative assessment of N stage for rectal cancer. The diagnostic accuracy of MRI for treatment decision‐making is promising, but additional studies are needed to validate these findings in a larger sample size from multiple centers.

• diagnostic accuracy
• histopathology
• magnetic resonance imaging staging
• rectal cancer

• Lateral pelvic lymph node dissection
• Low rectal cancer
• MRI
• Neoadjuvant chemotherapy

• Chemotherapy, Adjuvant
• Humans
• Induction Chemotherapy
• Lymph Nodes/pathology
• Lymphatic Metastasis/diagnostic imaging
• Lymphatic Metastasis/pathology
• Magnetic Resonance Imaging
• Neoadjuvant Therapy
• Oxaliplatin/administration & dosage
• Predictive Value of Tests
• Rectal Neoplasms/therapy
• Retrospective Studies

The pre-operative diagnostic value of detecting lateral pelvic lymph node (LPLN) metastasis with magnetic resonance imaging, multidirectory computed tomography, and positron emission tomography/computed tomography was investigated in lower rectal cancer patients.

We retrospectively evaluated, using the three different modalities, the metastatic status of LPLNs in four regions, including both the internal iliac and the obturator, in 46 patients affected by lower rectal cancer patients who underwent LPLN dissection. The size inclusion criterion for LPLN metastasis was set at 6 mm in the short axis diameter. Histological examination was performed for determining the false positive and negative rate of LPLNs metastasis detection.

Among 184 LPLNs regions, 17 (9%) were positive for metastasis. The region-based sensitivity, specificity, and accuracy rate did not differ among the three tested diagnostic modalities. Moreover, a significant increase in these rates could not be observed when the modalities were combined. Of 184 regions, 8 (4.4%) were false negative, whereas 2 (1.1%) were false positive. The histological pattern of metastatic regions did not differ in 8 false negative LPLNs.

Each modality had a similar detection power for LPLNs metastasis, with a cut-off value at 6 mm in the short axis diameter. However, the sensitivity of all the modalities was slightly low, along with the number of false negative LPLNs. Further reduction of the false negative rate with these modalities may be difficult because of an inherent limitation of current imaging technologies to accurately detect lymph node metastases.

• computed tomography
• lateral pelvic lymph node metastasis
• lower rectal cancer
• magnetic resonance imaging
• positron emission tomography

• multiplanar reformations
• multi-slice spiral computed tomography
• preoperative t staging
• rectal cancer
• tnm stage

• Adult
• Aged
• Aged, 80 and over
• Female
• Humans
• Male
• Middle Aged
• Neoplasm Staging
• Preoperative Care
• Rectal Neoplasms/diagnostic imaging
• Rectal Neoplasms/pathology
• Rectal Neoplasms/surgery
• Retrospective Studies
• Tomography, Spiral Computed/methods