Rectal Cancer

Comparison of preoperative CT- and MRI-based multiparametric radiomics in the prediction of lymph node metastasis in rectal cancer

OBJECTIVE

To compare computed tomography (CT)- and magnetic resonance imaging (MRI)-based multiparametric radiomics models and validate a multi-modality, multiparametric clinical-radiomics nomogram for individual preoperative prediction of lymph node metastasis (LNM) in rectal cancer (RC) patients.

METHODS

234 rectal adenocarcinoma patients from our retrospective study cohort were randomly selected as the training (n = 164) and testing (n = 70) cohorts. The radiomics features of the primary tumor were extracted from the non-contrast enhanced computed tomography (NCE-CT), the enhanced computed tomography (CE-CT), the T2-weighted imaging (T2WI) and the gadolinium contrast-enhanced T1-weighted imaging (CE-TIWI) of each patient. Three kinds of models were constructed based on training cohort, including the Clinical model (based on the clinical features), the radiomics models (based on NCE-CT, CE-CT, T2WI, CE-T1WI, CT, MRI, CT combing with MRI) and the clinical-radiomics models (based on CT or MRI radiomics model combing with clinical data) and Clinical-IMG model (based on CT and MRI radiomics model combing with clinical data). The performances of the 11 models were evaluated via the area under the receiver operator characteristic curve (AUC), accuracy, sensitivity, and specificity in the training and validation cohort. Differences in the AUCs among the 11 models were compared using DeLong's test. Finally, the optimal model (Clinical-IMG model) was selected to create a radiomics nomogram. The performance of the nomogram to evaluate clinical efficacy was verified by ROC curves and decision curve analysis (DCA).

RESULTS

The MRI radiomics model in the validation cohort significantly outperformed than CT radiomics model (AUC, 0.785 vs. 0.721, p<0.05). The Clinical-IMG nomogram had the highest prediction efficiency than all other predictive models (p<0.05), of which the AUC was 0.947, the sensitivity was 0.870 and the specificity was 0.884.

CONCLUSION

MRI radiomics model performed better than both CT radiomics model and Clinical model in predicting LNM of RC. The clinical-radiomics nomogram that combines the radiomics features obtained from both CT and MRI along with preoperative clinical characteristics exhibits the best diagnostic performance.

Predictive value of modified MRI-based split scar sign (mrSSS) score for pathological complete response after neoadjuvant chemoradiotherapy for patients with rectal cancer

PURPOSE

To measure the diagnostic performance of modified MRI-based split scar sign (mrSSS) score for the prediction of pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) for patients with rectal cancer.

METHODS

The modified MRI-based split scar sign (mrSSS) score, which consists of T2-weighted images (T2WI)-based score and diffusion-weighted images (DWI)-based score. The sensitivity, specificity, and accuracy of modified mrSSS score, endoscopic gross type, and MRI-based tumor regression grading (mrTRG) score, in the prediction of pCR, were compared. The prognostic value of the modified mrSSS score was also studied.

RESULTS

A total of 189 patients were included in the study. The Kendall's coefficient of interobserver concordance of modified mrSSS score, T2WI -based score, and DWI-based score were 0.899, 0.890, and 0.789 respectively. And the maximum and minimum k value of the modified mrSSS score was 0.797 (0.742-0.853) and 0.562 (0.490-0.634). The sensitivity, specificity, and accuracy of prediction of pCR were 0.66, 0.97, and 0.90 for modified mrSSS score; 0.37, 0.89, and 0.78 for endoscopic gross type (scar); and 0.24, 0.92, and 0.77 for mrTRG score (mrTRG = 1). The modified mrSSS score had significantly higher sensitivity than the endoscopic gross type and the mrTRG score in predicting pCR. Patients with lower modified mrSSS scores had significantly longer disease-free survival (P < 0.05).

CONCLUSION

The modified mrSSS score showed satisfactory interobserver agreement and higher sensitivity in predicting pCR after nCRT in patients with rectal cancer. The modified mrSSS score is also a predictor of disease-free survival.

Rectal MRI Interpretation After Neoadjuvant Therapy

In recent years, several key advances in the management of locally advanced rectal cancer have been made, including the implementation of total mesorectal excision as the standard surgical approach; use of neoadjuvant chemoradiotherapy in selected patients with a high risk of local recurrence, and finally, adoption of organ preservation strategies, through either local excision or nonoperative management in selected patients with clinical complete response following neoadjuvant chemoradiotherapy. This review aims to shed light on the role of rectal MRI in the assessment of treatment response after neoadjuvant therapy, which is especially important given the growing feasibility of nonoperative management. First, an overview of current neoadjuvant therapies and response assessment based on digital rectal examination, endoscopy, and MRI will be provided. Second, the use of a high-quality restaging rectal MRI protocol will be presented. Third, a step-by-step approach to assessing treatment response on restaging rectal MRI following neoadjuvant treatment will be outlined, acknowledging challenges faced by radiologists during MRI interpretation. Finally, research related to response assessment will be discussed. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 3.

Preoperative Prediction of Perineural Invasion Status of Rectal Cancer Based on Radiomics Nomogram of Multiparametric Magnetic Resonance Imaging

Objectives

To compare the predictive performance of different radiomics signatures from multiparametric magnetic resonance imaging (mpMRI), including four sequences when used individually or combined, and to establish and validate an optimal nomogram for predicting perineural invasion (PNI) in rectal cancer (RC) patients.

Methods

Our retrospective study included 279 RC patients without preoperative antitumor therapy (194 in the training dataset and 85 in the test dataset) who underwent preoperative mpMRI scan between January 2017 and January 2021. Among them, 72 cases were PNI-positive. Then, clinical and radiological variables were collected, including carcinoembryonic antigen (CEA), radiological tumour stage (T_1-4), lymph node stage (N_0-2) and so on. Quantitative radiomics features were extracted and selected from oblique axial T₂-weighted imaging (T₂WI), T₁-weighted imaging (T₁WI), apparent diffusion coefficient (ADC), and enhanced T₁WI (T₁CE) sequences. The clinical model was constructed by integrating the final selected clinical and radiological variables. The radiomics signatures included four single-sequence signatures and one fusion signature were built using the respective remaining optimized features. And the nomogram was constructed based on the independent predictors by using multivariable logistic regression. The area under curve (AUC), DeLong test, calibration curve, and decision curve analysis (DCA) were used to evaluate the performance.

Results

Ultimately, 20 radiomics features were retained from the four sequences—T₁WI (n = 4), T₂WI (n = 5), ADC (n = 5), and T₁CE (n = 6)—to construct four single-sequence radiomics signatures and one fusion radiomics signature. The fusion radiomics signature performed better than four single-sequence radiomics signatures and clinical model (AUCs of 0.835 and 0.773 vs. 0.680-0.737 and 0.666-0.709 in the training and test datasets, respectively). The nomogram constructed by incorporating CEA, tumour stage and rad-score performed best, with AUCs of 0.869 and 0.864 in the training and test datasets, respectively. Delong test showed that the nomogram was significantly different from the clinical model and four single-sequence radiomics signatures (P < 0.05). Moreover, calibration curves demonstrated good agreement, and DCA highlighted benefits of the nomogram.

Conclusions

The comprehensive nomogram can preoperatively and noninvasively predict PNI status, provide a convenient and practical tool for treatment strategy, and help optimize individualized clinical decision-making in RC patients.

MRI Evaluation of Complete Response of Locally Advanced Rectal Cancer After Neoadjuvant Therapy: Current Status and Future Trends

Complete tumor response can be achieved in a certain proportion of patients with locally advanced rectal cancer, who achieve maximal response to neoadjuvant therapy (NAT). For these patients, a watch-and-wait (WW) or nonsurgical strategy has been proposed and is becoming widely practiced in order to avoid unnecessary surgical complications. Therefore, a non-invasive, reliable diagnostic tool for accurately evaluating complete tumor response is needed. Magnetic resonance imaging (MRI) plays a crucial role in both primary staging and restaging tumor response to NAT in rectal cancer without relying on resected specimen. In recent years, numerous efforts have been made to research the value of MRI in predicting and evaluating complete response in rectal cancer. Current MRI evaluation is mainly based on morphological and functional images. Morphologic MRI yields high soft tissue resolution, multiplanar images, and provides detailed depictions of rectal cancer and its surrounding structures. Functional MRI may help to distinguish residual tumor from fibrosis, therefore improving the diagnostic performance of morphologic MRI in identifying complete tumor response. Both morphologic and functional MRI have several promising parameters that may help accurately evaluate and/or predict complete response of rectal cancer. However, these parameters still have limitations and the results remain inconsistent. Recent development of new techniques, such as textural analysis, radiomics analysis and deep learning, demonstrate great potential based on MRI-derived parameters. This article aimed to review and help better understand the strengths, limitations, and future trends of these MRI-derived methods in evaluating complete response in rectal cancer.

MRI for Rectal Cancer Primary Staging and Restaging After Neoadjuvant Chemoradiation Therapy: How to Do It During Daily Clinical Practice

PURPOSE

To provide a practical overview regarding the state-of-the-art of the magnetic resonance imaging (MRI) protocol for rectal cancer imaging and interpretation during primary staging and restaging after neoadjuvant chemoradiation therapy (CRT), pointing out technical skills and findings that radiologists should consider for their reports during everyday clinical activity.

METHOD

Both 1.5T and 3.0T scanners can be used for rectal cancer evaluation, using pelvic phased array external coils. The standard MR protocol includes T2-weighted imaging of the pelvis, high-resolution T2-weighted sequences focused on the tumor and diffusion-weighted imaging (DWI). The mnemonic DISTANCE is helpful for the interpretation of MR images: DIS, for distance from the inferior part of the tumor to the anorectal-junction; T, for T staging; A, for anal sphincter complex status; N, for nodal staging; C, for circumferential resection margin status; and E, for extramural venous invasion.

RESULTS

Primary staging with MRI is a cornerstone in the preoperative workup of patients with rectal cancer, because it provides clue information for decisions on the administration of CRT and surgical treatment. Restaging after CRT is crucial for treatment planning, and findings on post-CRT MRI correlate with the patient's prognosis and survival. It may be useful to remember the mnemonic word "DISTANCE" to check and describe all the relevant MRI findings necessary for an accurate radiological definition of tumor stage and response to CRT.

CONCLUSIONS

"DISTANCE" assessment for rectal cancer staging and treatment response estimation after CRT may be helpful as a checklist for a structured reporting.