Predictive value of flexible proctosigmoidoscopy and laboratory findings for complete clinical responses after neoadjuvant chemoradiotherapy in patients with locally advanced primary rectal cancer: a retrospective cohort study.

PURPOSE: Colorectal cancer is the second leading cause of cancer death worldwide. Standard treatments for locally advanced rectal cancer include neoadjuvant chemoradiotherapy and total mesorectal excision (TME), which are associated with significant morbidity. After neoadjuvant therapy, one-third of patients achieve a pathological complete response (pCR) and are eligible for a watch-and-wait approach without TME. The purpose of this study was to determine the potential predictors of pCR before surgery. METHODS: The demographic, clinical, and endoscopic data of 119 patients with primary locally advanced rectal cancer without distant metastasis who underwent restaging endoscopy and TME 6-8 weeks after the end of neoadjuvant therapy were collected. The absence of tumor cells in the histological examination of the TME specimen after neoadjuvant therapy was considered pCR. Binary logistic regression and receiver operating characteristic curves were utilized for analysis. RESULTS: According to the multivariate logistic regression analysis, flattening of marginal tumor swelling (p value < 0.001, odds ratio = 100.605) emerged as an independent predictor of pCR in rectal cancer patients. Additionally, receiver operating characteristic curve analysis revealed that lower preoperative carcinoembryonic antigen and erythrocyte sedimentation rate levels predict pCR, with cutoffs of 2.15 ng/ml and 19.0 mm/h, respectively. CONCLUSION: Carcinoembryonic antigen and erythrocyte sedimentation rate, along with the presence of flattening of marginal tumor swelling, can predict pCR after neoadjuvant chemoradiotherapy in patients with primary rectal cancer. These factors offer a potential method for selecting candidates for conservative treatment based on endoscopic and laboratory findings.

Rectal adenocarcinoma: Ex vivo 9.4T MRI-correlation with histopathologic treatment response to neoadjuvant chemoradiotherapy.

OBJECTIVES: To determine the imaging details and diagnostic information of the treatment response to neoadjuvant chemoradiotherapy (nCRT) of rectal adenocarcinoma at 9.4T magnetic resonance imaging (MRI) by ex vivo. METHODS: Fifteen cases with locally advanced rectal cancer (LARC) followed by radical surgery after nCRT between September 2022 and February 2023 were recruited. Resected specimens were fixed in a perfluoropolyether-filled test tube and scanned with a 3.0T and 9.4T MRI system ex vivo. The residual tumor depth and MRI-based tumor regression grade (TRG) were subjectively assessed and then compared with the pathological findings. RESULTS: The ex vivo 9.4T T2WI without fat suppression clearly differentiated tumor tissue, fibrosis and normal rectal wall, which clearly corresponded to the pathologic tissues of the rectal specimens. The TRG could be accurately assessed on ex vivo 9.4T images in 13/15 specimens (86.7%), while in 11/15 specimens (73.3%) on ex vivo 3.0T images. CONCLUSION: Ex vivo 9.4T MR imaging clearly displayed the components of rectal wall and proved excellent diagnostic performance for evaluating the treatment response to nCRT, which allow radiologists to understand and then assess more accurately the TRG of LARC after nCRT.

Preliminary study of indocyanine green-guided laparoscopic lateral lymph node dissection for rectal cancer.

BACKGROUND: LLNM can occur in mid-low rectal cancer, but LLND in patients with rectal cancer presents certain challenges. Recent years have seen the progressive application of ICG fluorescence imaging technology in colorectal surgery. This study aimed to explore the effectiveness of ICG-guided laparoscopic LLND for rectal cancer. METHODS: We applied ICG-guided laparoscopic lateral lymph node dissection in 11 patients diagnosed as rectal cancer with lateral lymph node metastasis. RESULTS: All 11 patients in this group successfully completed ICG-guided laparoscopic LLND for rectal cancer with good lateral lymph node imaging. CONCLUSIONS: ICG-guided laparoscopic LLND for rectal cancer is safe and represents a feasible solution, thereby providing valuable guidance for intraoperative lymph node dissection.

Synthetic CT generation for pelvic cases based on deep learning in multi-center datasets.

BACKGROUND AND PURPOSE: To investigate the feasibility of synthesizing computed tomography (CT) images from magnetic resonance (MR) images in multi-center datasets using generative adversarial networks (GANs) for rectal cancer MR-only radiotherapy. MATERIALS AND METHODS: Conventional T2-weighted MR and CT images were acquired from 90 rectal cancer patients at Peking University People's Hospital and 19 patients in public datasets. This study proposed a new model combining contrastive learning loss and consistency regularization loss to enhance the generalization of model for multi-center pelvic MRI-to-CT synthesis. The CT-to-sCT image similarity was evaluated by computing the mean absolute error (MAE), peak signal-to-noise ratio (SNRpeak), structural similarity index (SSIM) and Generalization Performance (GP). The dosimetric accuracy of synthetic CT was verified against CT-based dose distributions for the photon plan. Relative dose differences in the planning target volume and organs at risk were computed. RESULTS: Our model presented excellent generalization with a GP of 0.911 on unseen datasets and outperformed the plain CycleGAN, where MAE decreased from 47.129 to 42.344, SNRpeak improved from 25.167 to 26.979, SSIM increased from 0.978 to 0.992. The dosimetric analysis demonstrated that most of the relative differences in dose and volume histogram (DVH) indicators between synthetic CT and real CT were less than 1%. CONCLUSION: The proposed model can generate accurate synthetic CT in multi-center datasets from T2w-MR images. Most dosimetric differences were within clinically acceptable criteria for photon radiotherapy, demonstrating the feasibility of an MRI-only workflow for patients with rectal cancer.

Response of various histological types of locally advanced rectal cancer to neoadjuvant multimodality therapy.

Objectives: To determine the response of various histological types of locally advanced rectal cancer to neoadjuvant multimodality therapy. METHODS: The non-randomised, quasi-experimental retrospective cohort study was conducted at the Combined Military Hospital, Rawalpindi, Pakistan, and comprised data of patients treated between January 1, 2020, to September 30, 2021. The data retrieved related to histologically proven and locally advanced rectal cancer patients aged 18-70 years receiving neoadjuvant chemoradiotherapy. Radiotherapy dose was 45 gray to pelvis with a boost to gross tumour of 5.4 gray in 3 fractions by using volumetric arc therapy concurrently with capecitabine 625mg/m² daily. A magnetic resonance imaging scan of pelvis with contrast was done at 5-10 weeks before surgery. Histological response to neoadjuvant treatment of various histological types was evaluated using the Rectal Cancer Regression Grade. Data was analysed using SPSS 22. RESULTS: Of the 182 patients evaluated, 108(59.34%) were included; 64(59.3%) males and 44(40.7%) females. The overall mean age was 45.4±5.2 years. Regression status was grade 1 in 24(22%) patients, grade 2 in 43(40%) and grade 3 in 41(38%) (p=0.074). There were 12(11.11%) patients with signet ring cell and 10(83.3%) showed pathological tumour regression. There were 17(15.74%) patients with mucinous variant, and 12(70.5%) had tumour regression. There were 79(73.15%) patients with adenocarcinoma, and 59(74.6%) of them showed tumour regression. . CONCLUSIONS: There was less tumour regression in mucinous and signet ring cell variants of adenocarcinoma. Modification and intensification of neoadjuvant therapy may be required in such histologies.

Magnetic resonance imaging radiomics-based prediction of severe inflammatory response in locally advanced rectal cancer patients after neoadjuvant radiochemotherapy.

PURPOSE: To predict severe inflammatory response after neoadjuvant radiochemotherapy in locally advanced rectal cancer (RC) patients using magnetic resonance imaging (MRI) radiomics models. METHODS: This retrospective study included patients who underwent radical surgery for RC cancer after neoadjuvant radiochemotherapy between July 2017 and December 2019 at XXX Hospital. MRI radiomics features were extracted from T2WI images before (pre-nRCT-RF) and after (post-nRCT-RF) neoadjuvant radiochemotherapy, and the variation of radiomics features before and after neoadjuvant radiochemotherapy (delta-RF) were calculated. Eight, eight, and five most relevant features were identified for pre-nRCT-RF, post-nRCT-RF, and delta-RF, respectively. RESULTS: Eighty-six patients were included and randomized 3:1 to the training and test set (n = 65 and n = 21, respectively). The prediction model based on delta-RF had areas under the curve (AUCs) of 0.80 and 0.85 in the training and test set, respectively. A higher rate of difficult operations was observed in patients with severe inflammation (65.5% vs. 42.9%, P = 0.045). CONCLUSION: The prediction model based on MRI delta-RF may be a useful tool for predicting severe inflammatory response after neoadjuvant radiochemotherapy in locally advanced RC patients.

Deep learning model based on endoscopic images predicting treatment response in locally advanced rectal cancer undergo neoadjuvant chemoradiotherapy: a multicenter study.

PURPOSE: Neoadjuvant chemoradiotherapy has been the standard practice for patients with locally advanced rectal cancer. However, the treatment response varies greatly among individuals, how to select the optimal candidates for neoadjuvant chemoradiotherapy is crucial. This study aimed to develop an endoscopic image-based deep learning model for predicting the response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. METHODS: In this multicenter observational study, pre-treatment endoscopic images of patients from two Chinese medical centers were retrospectively obtained and a deep learning-based tumor regression model was constructed. Treatment response was evaluated based on the tumor regression grade and was defined as good response and non-good response. The prediction performance of the deep learning model was evaluated in the internal and external test sets. The main outcome was the accuracy of the treatment prediction model, measured by the AUC and accuracy. RESULTS: This deep learning model achieved favorable prediction performance. In the internal test set, the AUC and accuracy were 0.867 (95% CI: 0.847-0.941) and 0.836 (95% CI: 0.818-0.896), respectively. The prediction performance was fully validated in the external test set, and the model had an AUC of 0.758 (95% CI: 0.724-0.834) and an accuracy of 0.807 (95% CI: 0.774-0.843). CONCLUSION: The deep learning model based on endoscopic images demonstrated exceptional predictive power for neoadjuvant treatment response, highlighting its potential for guiding personalized therapy.

Unraveling the role of computed tomography derived body composition metrics on anastomotic leakages rates in rectal cancer surgery: A protocol for a systematic review and meta-analysis.

INTRODUCTION: Anastomotic leakage is a major concern following total mesorectal excision for rectal cancer, affecting oncological outcomes, morbidity an treatment costs. Body composition has been suggested to influence anastomotic leakage rates. However, literature on how body composition impact anastomotic leakage rates is conflicting. This systematic review aims to evaluate the role of computed tomography derived body composition metrics on anastomotic leakage rates in rectal cancer patients. METHODS: Databases PubMed/MEDLINE, Cochrane Library, web of science, and EMBASE, will be systematically searched for papers from January 2010 onwards. Study selection, data collection and quality assessment will be independently performed by three research fellows. Outcomes described in three or more studies will be included in the meta-analysis. The Q-test and I2 statistic will be used to assess statistical heterogeneity between studies. Publication bias will be examined by visual inspection of funnel plots and quantified by Egger's test. Sensitivity analyses will be conducted to examine the robustness of the meta-analysis. Reporting of the findings will be in line with the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines. CONCLUSIONS: This systematic review will synthesize the current evidence and will identify knowledge gaps. Results of the systematic review will aid health care professional in pre-operative decision making and will be distributed through a peer-reviewed publication and presentation of results at international meetings. TRIAL REGISTRATION: PROSPERO protocol number: CRD42023471537.

Evaluation of Neoadjuvant Chemoradiotherapy Response in Rectal Cancer Using MR Images and Deep Learning Neural Networks.

INTRODUCTION: The aim of the study was to develop deep-learning neural networks to guide treatment decisions and for the accurate evaluation of tumor response to neoadjuvant chemoradiotherapy (nCRT) in rectal cancer using magnetic resonance (MR) images. METHODS: Fifty-nine tumors with stage 2 or 3 rectal cancer that received nCRT were retrospectively evaluated. Pathological tumor regression grading was carried out using the Dworak (Dw-TRG) guidelines and served as the ground truth for response predictions. Imaging-based tumor regression grading was performed according to the MERCURY group guidelines from pre-treatment and post-treatment para-axial T2-weighted MR images (MR-TRG). Tumor signal intensity signatures were extracted by segmenting the tumors volumetrically on the images. Normalized histograms of the signatures were used as input to a deep neural network (DNN) housing long short-term memory (LSTM) units. The output of the network was the tumor regression grading prediction, DNN-TRG. RESULTS: In predicting complete or good response, DNN-TRG demonstrated modest agreement with Dw-TRG (Cohen's kappa= 0.79) and achieved 84.6% sensitivity, 93.9% specificity, and 89.8% accuracy. MR-TRG revealed 46.2% sensitivity, 100% specificity, and 76.3% accuracy. In predicting a complete response, DNN-TRG showed slight agreement with Dw-TRG (Cohen's kappa= 0.75) with 71.4% sensitivity, 97.8% specificity, and 91.5% accuracy. MR-TRG provided 42.9% sensitivity, 100% specificity, and 86.4% accuracy. DNN-TRG benefited from higher sensitivity but lower specificity, leading to higher accuracy than MR-TRG in predicting tumor response. CONCLUSION: The use of deep LSTM neural networks is a promising approach for evaluating the tumor response to nCRT in rectal cancer.

Mild hyperthermia with magnetic resonance- guided high intensity focused ultrasound combined with salvage chemoradiation for recurrent rectal cancer.

INTRODUCTION: Pelvic recurrences from rectal cancer present a challenging clinical scenario. Hyperthermia represents an innovative treatment option in combination with concurrent chemoradiation to enhance therapeutic effect. We provide the initial results of a prospective single center feasibility study (NCT02528175) for patients undergoing rectal cancer retreatment using concurrent chemoradiation and mild hyperthermia with MR-guided high intensity focused ultrasound (MR-HIFU). METHODS: All patients were deemed ineligible for salvage surgery and were evaluated in a multidisciplinary fashion with a surgical oncologist, radiation oncologist and medical oncologist. Radiation was delivered to a dose of 30.6 Gy in 1.8 Gy per fraction with concurrent capecitabine. MR-HIFU was delivered on days 1, 8 and 15 of concurrent chemoradiation. Our primary objective was feasibility and toxicity. RESULTS: Six patients (total 11 screened) were treated with concurrent chemoradiation and mild hyperthermia with MR-HIFU. Tumor size varied between 3.1-16.6 cm. Patients spent an average of 228 min in the MRI suite and sonication with the external transducer lasted an average of 35 min. There were no complications on the day of the MR-HIFU procedure and all acute toxicities (no grade >/=3 toxicities) resolved after completion of treatment. There were no late grade >/=3 toxicities. CONCLUSION: Mild hyperthermia with MR-HIFU, in combination with concurrent chemoradiation for appropriately selected patients, is safe for localized pelvic recurrences from rectal cancer. The potential for MR-HIFU to be applied in the recurrent setting in rectal cancer treatment requires further technical development and prospective evaluation.

Solitary fibrous tumor within the mesorectum: literature review based on a case report of resection by transanal minimally invasive surgery (TAMIS).

PURPOSE: Solitary fibrous tumors (SFT) are a rare entity of in majority benign neoplasms. Nevertheless, up to 20% of cases show a malignant tendency with local infiltration or metastasis. Commonly arising in the thoracic cavity, only few cases of SFT of the mesorectal tissue have been reported in the literature. Complete surgical resection, classically by posterior approach, is the treatment of choice. The purpose of this review is to demonstrate the safety and suitability of transanal minimally invasive surgery (TAMIS) as a surgical approach for the resection of benign pararectal solid tumors. METHODS: We report the case of a 52-year-old man who was diagnosed incidentally with SFT of the distal mesorectum. Resection by TAMIS was performed. Based on this case, we describe the steps and potential benefits of this procedure and provide a comprehensive review of the literature. RESULTS: Histopathology confirms the completely resected SFT. After uneventful postoperative course and discharge on day four, follow-up was recommended by a multidisciplinary board by clinical examination and MRI, which showed a well-healed scar and no recurrence up to 3 years after resection. CONCLUSION: SFT of the mesorectum is a very rare entity. To our knowledge, this is the first report on a TAMIS resection for SFT, demonstrated as a safe approach for complete resection of benign pararectal solid tumors.

Surgeon assessment of significant rectal polyps using white light endoscopy alone and in comparison to fluorescence-augmented AI lesion classification.

PURPOSE: Perioperative decision making for large (> 2 cm) rectal polyps with ambiguous features is complex. The most common intraprocedural assessment is clinician judgement alone while radiological and endoscopic biopsy can provide periprocedural detail. Fluorescence-augmented machine learning (FA-ML) methods may optimise local treatment strategy. METHODS: Surgeons of varying grades, all performing colonoscopies independently, were asked to visually judge endoscopic videos of large benign and early-stage malignant (potentially suitable for local excision) rectal lesions on an interactive video platform (Mindstamp) with results compared with and between final pathology, radiology and a novel FA-ML classifier. Statistical analyses of data used Fleiss Multi-rater Kappa scoring, Spearman Coefficient and Frequency tables. RESULTS: Thirty-two surgeons judged 14 ambiguous polyp videos (7 benign, 7 malignant). In all cancers, initial endoscopic biopsy had yielded false-negative results. Five of each lesion type had had a pre-excision MRI with a 60% false-positive malignancy prediction in benign lesions and a 60% over-staging and 40% equivocal rate in cancers. Average clinical visual cancer judgement accuracy was 49% (with only 'fair' inter-rater agreement), many reporting uncertainty and higher reported decision confidence did not correspond to higher accuracy. This compared to 86% ML accuracy. Size was misjudged visually by a mean of 20% with polyp size underestimated in 4/6 and overestimated in 2/6. Subjective narratives regarding decision-making requested for 7/14 lesions revealed wide rationale variation between participants. CONCLUSION: Current available clinical means of ambiguous rectal lesion assessment is suboptimal with wide inter-observer variation. Fluorescence based AI augmentation may advance this field via objective, explainable ML methods.

Unusual Unique Renal Metastasis of Rectal Carcinoma.

Rectal cancer Is a Common malignant pathology; its usual spread in volves the liver and lungs. The occurrence of renal metastases is exceptional. CT scanning aims to evaluate extension and may incidentally reveal a renal mass, which can be better characterized through MRI and ultrasound. We describe a case of a solitary renal metastasis from rectal cancer and underscore the significant role of imaging in positively diagnosing this uncommon pathology.

Comparison of conventional MRI analysis versus MRI-based radiomics to predict the circumferential margin resection involvement of rectal cancer.

BACKGROUND: To compare the application of conventional MRI analysis and MRI-based radiomics to identify the circumferential resection margin (CRM) status of rectal cancer (RC). METHODS: A cohort of 301 RC patients with 66 CRM invloved status and 235 CRM non-involved status were enrolled in this retrospective study between September 2017 and August 2022. Conventional MRI characteristics included gender, age, diameter, distance to anus, MRI-based T/N phase, CEA, and CA 19 - 9, then the relevant logistic model (Logistic-cMRI) was built. MRI-based radiomics of rectal cancer and mesorectal fascia were calculated after volume of interest segmentation, and the logistic model of rectal cancer radiomics (Logistic-rcRadio) and mesorectal fascia radiomics (Logistic-mfRadio) were constructed. And the combined nomogram (nomo-cMRI/rcRadio/mfRadio) containing conventional MRI characteristics, radiomics of rectal cancer and mesorectal fascia was developed. The receiver operator characteristic curve (ROC) was delineated and the area under curve (AUC) was calculated the efficiency of models. RESULTS: The AUC of Logistic-cMRI was 0.864 (95%CI, 0.820 to 0.901). The AUC of Logistic-rcRadio was 0.883 (95%CI, 0.832 to 0.928) in the training set and 0.725 (95%CI, 0.616 to 0.826) in the testing set. The AUCs of Logistic-mfRadio was 0.891 (95%CI, 0.838 to 0.936) in the training set and 0.820 (95%CI, 0.725 to 0.905) in the testing set. The AUCs of nomo-cMRI/rcRadio/mfRadio were the highest in both the training set of 0.942 (95%CI, 0.901 to 0.969) and the testing set of 0.909 (95%CI, 0.830 to 0.959). CONCLUSION: MRI-based radiomics of rectal cancer and mesorectal fascia showed similar efficacy in predicting the CRM status of RC. The combined nomogram performed better in assessment.

Radiomic score for lung nodules as a prognostic biomarker in locally advanced rectal cancer patients: A bi-institutional study.

BACKGROUND: Undetermined lung nodules are common in locally advanced rectal cancer (LARC) and lack precise risk stratification. This study aimed to develop a radiomic-based score (Rad-score) to distinguish metastasis and predict overall survival (OS) in patients with LARC and lung nodules. METHODS: Retrospective data from two institutions (July 10, 2006-September 24, 2015) was used to develop and validate the Rad-score for distinguishing lung nodule malignancy. The prognostic value of the Rad-score was investigated in LARC cohorts, leading to the construction and validation of a clinical and radiomic score (Cli-Rad-score) that incorporates both clinical and radiomic information for the purpose of improving personalized clinical prognosis prediction. Descriptive statistics, survival analysis, and model comparison were performed to assess the results. RESULTS: The Rad-score demonstrated great performance in distinguishing malignancy, with C-index values of 0.793 [95% CI: 0.729-0.856] in the training set and 0.730 [95% CI: 0.666-0.874] in the validation set. In independent LARC cohorts, Rad-score validation achieved C-index values of 0.794 [95% CI: 0.737-0.851] and 0.747 [95% CI: 0.615-0.879]. Regarding prognostic prediction, Rad-score effectively stratified patients. Cli-Rad-score outperformed the clinicopathological information alone in risk stratification, as evidenced by significantly higher C-index values (0.735 vs. 0.695 in the internal set and 0.618 vs. 0.595 in the external set). CONCLUSIONS: CT-based radiomics could serve as a reliable and powerful tool for lung nodule malignancy distinction and prognostic prediction in LARC patients. Rad-score predicts prognosis independently. Incorporation of Cli-Rad-score significantly enhances the persionalized clinical prognostic capacity in LARC patients with lung nodules.

Anatomic Basis of Rectal Cancer Staging: Clarifying Controversies and Misconceptions.

Rectal MRI provides a detailed depiction of pelvic anatomy; specifically, the relationship of the tumor to key anatomic structures, including the mesorectal fascia, anterior peritoneal reflection, and sphincter complex. However, anatomic inconsistencies, pitfalls, and confusion exist, which can have a strong impact on interpretation and treatment. These areas of confusion include the definition of the rectum itself, specifically differentiation of the rectum from the anal canal and the sigmoid colon, and delineation of the high versus low rectum. Other areas of confusion include the relative locations of the mesorectal fascia and peritoneum and their significance in staging and treatment, the difference between the mesorectal fascia and circumferential resection margin, involvement of the sphincter complex, and evaluation of lateral pelvic lymph nodes. The impact of these anatomic inconsistencies and sources of confusion is significant, given the importance of MRI in depicting the anatomic relationship of the tumor to critical pelvic structures, to triage surgical resection and neoadjuvant chemoradiotherapy with the goal of minimizing local recurrence. Evolving treatment paradigms also place MRI central in management of rectal cancer. ©RSNA, 2024.

Correlation study of functional magnetic resonance index and clinicopathological features of rectal cancer.

PURPOSE: To investigate the correlation between DCE-MRI, R2*, IVIM, and clinicopathological features of rectal cancer. METHODS: This was a prospective study, enrolling 42 patients with rectal cancer, 20 of whom underwent rectal mesorectal excision. Dynamic contrast-enhanced magnetic resonance imaging scanning was performed preoperatively in all patients, and additional preoperative scanning of R2* imaging and intravoxel incoherent motion was performed in those who underwent surgery. Artificially delineate the ROI around the tumor. Functional magnetic resonance index parameters Ktrans, Ve, R2*, D, D*, and f were estimated by computer software to analyze postoperative pathological reports of patients undergoing total mesenteric resection. Correlation and significance analyses of imaging metrics and pathologic features were performed by GraphPad Prism 9 to assess statistical significance. RESULTS: DEC-MRI, R2*, and IVIM have certain application values in the distance from the lower margin of the tumor to the anorectal ring, imaging T stage and N stage, tumor markers CEA and CA199, immunohistochemical indexes Ki-76 and P53, lymph node cancer metastasis, and rectal fascia status (P < 0.05). CONCLUSION: DEC-MRI, R2*, and IVIM provide reliable quantitative parameters for preoperative clinicopathological evaluation of patients with rectal cancer.

Diagnostic performance of Node Reporting and Data System (Node-RADS) for assessing mesorectal lymph node in rectal cancer by CT.

BACKGROUND: To compare the diagnostic performance of the Node-RADS scoring system and lymph node (LN) size in preoperative LN assessment for rectal cancer (RC), and to investigate whether the selection of size as the primary criterion whereas morphology as the secondary criterion for LNs can be considered the preferred method for clinical assessment. METHODS: Preoperative CT data of 146 RC patients treated with radical resection surgery were retrospectively analyzed. The Node-RADS score and short-axis diameter of size-prioritized LNs and the morphology-prioritized LNs were obtained. The correlations of Node-RADS score to the pN stage, LNM number and lymph node ratio (LNR) were investigated. The performances on assessing pathological lymph node metastasis were compared between Node-RADS score and short-axis diameter. A nomogram combined the Node-RADS score and clinical features was also evaluated. RESULTS: Node-RADS score showed significant correlation with pN stage, LNM number and LNR (Node-RADS of size-prioritized LN: r = 0.600, 0.592, and 0.606; Node-RADS of morphology-prioritized LN: r = 0.547, 0.538, and 0.527; Node-RADSmax: r = 0.612, 0.604, and 0.610; all p < 0.001). For size-prioritized LN, Node-RADS achieved an AUC of 0.826, significantly superior to short-axis diameter (0.826 vs. 0.743, p = 0.009). For morphology-prioritized LN, Node-RADS exhibited an AUC of 0.758, slightly better than short-axis diameter (0.758 vs. 0.718, p = 0.098). The Node-RADS score of size-prioritized LN was significantly better than that of morphology-prioritized LN (0.826 vs. 0.758, p = 0.038). The nomogram achieved the best diagnostic performance (AUC = 0.861) than all the other assessment methods (p < 0.05). CONCLUSIONS: The Node-RADS scoring system outperforms the short-axis diameter in predicting lymph node metastasis in RC. Size-prioritized LN demonstrates superior predictive efficacy compared to morphology-prioritized LN. The nomogram combined the Node-RADS score of size-prioritized LN with clinical features exhibits the best diagnostic performance. Moreover, a clear relationship was demonstrated between the Node-RADS score and the quantity-dependent pathological characteristics of LNM.

The role of endoscopic ultrasonography for diagnosis of residual rectal neuroendocrine tumor.

BACKGROUND: Endoscopic ultrasonography (EUS) is useful for assessing the depth and regional lymph node involvement in rectal neuroendocrine tumors (NETs). However, evidence regarding the effectiveness of EUS in identifying residual lesions in patients with incompletely resected NET is limited. We aimed to evaluate the efficacy of EUS in identifying residual rectal NETs and the clinical outcomes of salvage endoscopic treatment. METHODS: We retrospectively reviewed the records of patients who were transferred to Chosun University Hospital and received salvage treatment for incompletely resected rectal NETs between January 2012 and October 2021. RESULTS: This study included 68 incompletely resected rectal NET, of which 59 were margin-positive and 9 were margin-indeterminate. EUS detection (odds ratio (OR), 8.44; 95% confidence interval (CI), 1.18-41.35) and visual detection (OR, 7.00; 95% CI, 1.50-47.48) were associated with residual lesion in patients with incompletely resected NET. EUS detection of residual lesions showed a sensitivity of 94%, specificity of 71%, positive predictive value of 88%, negative predictive value of 83%, and accuracy of 87%. All patients underwent salvage treatment with band-ligation endoscopic mucosal resection (58.8%) and endoscopic submucosal dissection (41.2%). Residual NETs were diagnosed in 47 of 68 patients (69.1%), and no recurrence was noted during the follow-up period of 51.8 ± 22.9 months. CONCLUSIONS: EUS is a more sensitive method than visual detection for evaluating residual rectal NETs. Salvage endoscopic treatment for incompletely resected NETs is safe and effective.