An MRI-based scoring system for pretreatment risk stratification in locally advanced rectal cancer

Enhancing the role of MRI in rectal cancer: advances from staging to prognosis prediction

Rectal cancer (RC) is one of the major health challenges worldwide. Accurate staging, restaging, invasiveness assessment, and treatment efficacy evaluation are crucial for its clinical management. Magnetic resonance imaging (MRI) plays a significant role in these processes. However, standard MRI techniques, including T2-weighted and diffusion-weighted imaging, have uncertainties in identifying early-stage tumors, high-risk nodules, extramural vascular invasion, and treatment efficacy, potentially leading to inappropriate treatment. Recent advances suggest that the integration of traditional MRI methods, including diffusion-weighted imaging, opposed-phase or contrast-enhanced T1-weighted imaging, as well as emerging synthetic MRI, could address these challenges. Additionally, improvements in imaging technology have spurred research into advanced functional MRI techniques such as diffusion kurtosis imaging and amide proton transfer weighted MRI, yielding promising results in RC assessment. Total neoadjuvant therapy has emerged as a new treatment paradigm for locally advanced RC, with neoadjuvant immunotherapy and chemotherapy offering viable alternatives to neoadjuvant chemoradiotherapy. However, the lack of standards for the early prediction of patient survival and tumor response to neoadjuvant therapy highlights a critical unmet need in matching therapies to suitable patients. Furthermore, organ preservation strategies after neoadjuvant therapy provide personalized options based on tumor response and patient preferences, yet traditional MRI assessments show significant variability. Radiomics and artificial intelligence hold promise for revealing complex patterns in MRI images associated with patient prognosis and treatment response. This review provides an overview of current MRI advancements in RC assessment and emphasizes how future research can refine tailored treatment strategies to improve patient outcomes. KEY POINTS: Question The accurate diagnosis of early-stage rectal tumors, high-risk nodules, treatment responses, and the early prediction of patient survival and therapeutic outcomes remain an unmet need. Findings Visual MRI has improved staging, restaging, and invasiveness evaluation. Advanced MRI, radiomics and artificial intelligence provide significant potential for tumor characterization and outcome prediction. Clinical relevance Advances in visual MRI are improving routine imaging protocols and radiomics and artificial intelligence show promise in enhancing treatment decisions through precise tumor characterization and outcome prediction.

Impact of MRI risk assessment on the survival benefits of neoadjuvant chemoradiotherapy in patients with stage II-III rectal cancer: A retrospective cohort study

PURPOSE

To investigate whether MRI risk factors can be used to predict clinical outcomes and whether MRI risk assessment can be used to select stage II-III rectal cancer patients who may benefit from neoadjuvant chemoradiotherapy (nCRT).

METHODS AND MATERIALS

A total of 947 rectal cancer patients who underwent total mesorectal excision (TME) were retrospectively recruited. An MRI scoring system was established using the cumulative score of three risk factors (mesorectal fascia involvement, extramural venous invasion, and tumour deposits). Patients with mrT3c-T4 stage, N2 stage, or any risk factors were considered MRI high-risk cases of rectal cancer. Cox regression analysis was used to identify independent risk factors for overall survival (OS) and disease-free survival (DFS). Kaplan-Meier curves were generated to show the benefits of nCRT after propensity score matching (PSM).

RESULTS

OS and DFS were more favourable in the MRI low-risk group than in the MRI high-risk group, and the MRI scoring system facilitated prognostic stratification in stage II-III rectal cancer patients. NCRT significantly improved 3-year OS (89.1 % versus 78.8 %, p = 0.001) and 3-year DFS (73.4 % versus 68.0 %, p = 0.030) in the MRI high-risk group. After PSM, OS and DFS were improved in the MRI high-risk group with an MRI score of 1 (OS: HR = 0.432 [95 % CI: 0.214-0.871], p = 0.019; DFS: HR = 0.477 [95 % CI: 0.275-0.825], p = 0.008) and an MRI score of 2 (OS: HR = 0.276 [95 % CI: 0.130-0.586], p = 0.001; DFS: HR = 0.358 [95 % CI: 0.182-0.705], p = 0.003), whereas MRI low-risk patients did not obtain any survival benefit from nCRT.

CONCLUSIONS

MRI-defined high-risk patients with MRI scores of 1 or 2 may benefit from nCRT. Baseline MRI should be given more consideration in nCRT decision-making.

Predictive value of magnetic resonance imaging parameters combined with tumor markers for rectal cancer recurrence risk after surgery

BACKGROUND

An increasing number of studies to date have found preoperative magnetic resonance imaging (MRI) features valuable in predicting the prognosis of rectal cancer (RC). However, research is still lacking on the correlation between preoperative MRI features and the risk of recurrence after radical resection of RC, urgently necessitating further in-depth exploration.

AIM

To investigate the correlation between preoperative MRI parameters and the risk of recurrence after radical resection of RC to provide an effective tool for predicting postoperative recurrence.

METHODS

The data of 90 patients who were diagnosed with RC by surgical pathology and underwent radical surgical resection at the Second Affiliated Hospital of Bengbu Medical University between May 2020 and December 2023 were collected through retrospective analysis. General demographic data, MRI data, and tumor markers levels were collected. According to the reviewed data of patients six months after surgery, the clinicians comprehensively assessed the recurrence risk and divided the patients into high recurrence risk (37 cases) and low recurrence risk (53 cases) groups. Independent sample t-test and χ² test were used to analyze differences between the two groups. A logistic regression model was used to explore the risk factors of the high recurrence risk group, and a clinical prediction model was constructed. The clinical prediction model is presented in the form of a nomogram. The receiver operating characteristic curve, Hosmer-Lemeshow goodness of fit test, calibration curve, and decision curve analysis were used to evaluate the efficacy of the clinical prediction model.

RESULTS

The detection of positive extramural vascular invasion through preoperative MRI [odds ratio (OR) = 4.29, P = 0.045], along with elevated carcinoembryonic antigen (OR = 1.08, P = 0.041), carbohydrate antigen 125 (OR = 1.19, P = 0.034), and carbohydrate antigen 199 (OR = 1.27, P < 0.001) levels, are independent risk factors for increased postoperative recurrence risk in patients with RC. Furthermore, there was a correlation between magnetic resonance based T staging, magnetic resonance based N staging, and circumferential resection margin results determined by MRI and the postoperative recurrence risk. Additionally, when extramural vascular invasion was integrated with tumor markers, the resulting clinical prediction model more effectively identified patients at high risk for postoperative recurrence, thereby providing robust support for clinical decision-making.

CONCLUSION

The results of this study indicate that preoperative MRI detection is of great importance for predicting the risk of postoperative recurrence in patients with RC. Monitoring these markers helps clinicians identify patients at high risk, allowing for more aggressive treatment and monitoring strategies to improve patient outcomes.

Development and evaluation of the mrTE scoring system for MRI-detected tumor deposits and extramural venous invasion in rectal cancer

PURPOSE

Tumor deposits (TDs) and extramural venous invasion (EMVI) in locally advanced rectal cancer (LARC) are MRI-detectable markers that reflect the invasive and metastatic potential of tumors. However, both mrTDs and mrEMVI are closely associated with peritumoral vascular signals, and they show a high degree of statistical correlation. We developed a novel scoring system that integrates mrTDs and mrEMVI into a single parameter, simplifying the assessment process and capturing the prognostic value of both factors simultaneously.

METHODS

We retrospectively included LARC patients who received neoadjuvant chemoradiotherapy at five centers and proposed a novel MRI-based scoring system, mrTE (derived from mrTDs and mrEMVI), to integrate the prognostic significance of mrEMVI and mrTDs in rectal cancer. The prognostic value of different mrTE scores was evaluated using Kaplan-Meier curves and the Cox model. The predictive accuracy of the new scoring system was evaluated using the integrated area under the ROC curve (iAUC).

RESULTS

A total of 1188 patients with LARC were included in the evaluation cohort to assess the reliability of the novel imaging scoring system. Based on the mrTE scores ranging from 0 to 2, the patients were categorized into three groups. The 3-year disease-free survival rates for the groups were 88.1%, 78.1%, and 51.9% (score 1 vs 0: HR 2.00, 95% CI 1.36-2.93, p < 0.001; score 2 vs 0: HR 4.75, 95% CI 3.61-6.26, p < 0.001). The mrTE scoring system demonstrated superior performance in predicting DFS compared to other clinical and imaging markers, with a higher predictive accuracy (iAUC = 0.707).

CONCLUSIONS

The mrTE scoring system simplifies the clinical assessment of relevant MR markers and has proven to be an effective tool for predicting the prognosis of LARC patients.

Baseline MRI-based radiomics improving the recurrence risk stratification in rectal cancer patients with negative carcinoembryonic antigen: A multicenter cohort study

OBJECTIVES

Surveillance of rectal cancer recurrence in patients with negative pretreatment carcinoembryonic antigen (CEA) is challenging. This study aimed to develop the magnetic resonance imaging (MRI)-based radiomics models to predict rectal cancer recurrence in CEA-negative patients.

MATERIALS AND METHODS

This retrospective multicenter study consecutively enrolled rectal cancer patients with negative pretreatment CEA diagnosed between November 2012 and November 2018 from three medical centers. Radiomics features were extracted from the volume of interest on T2-weighted and diffusion-weighted images. Inter-class correlation coefficient (ICC) analysis, univariate Cox and least absolute shrinkage and selection operator (LASSO) Cox regression were then used to select features and construct a radiomics signature (RS). Multivariable Cox regression analysis was applied to develop two prediction models for disease-free survival (DFS) by incorporating the RS and independent clinicopathological predictors. The Kaplan-Meier method stratified tumor recurrence risk, and model performance was assessed using the Harrell concordance index (C-index).

RESULTS

A total of 600 rectal cancer patients were assigned to the development cohort (n = 358), internal test cohort (n = 120) and external test cohort (n = 122). The combination of ICC, univariate and LASSO Cox regression resulted in the selection of 25 radiomics features that comprise the RS. The RS can significantly stratify high-risk and low-risk patients (development: HR = 6.63, internal test: HR = 4.76, external test: HR = 4.62, all p < 0.05) and achieved good predictive performance (C-index = 0.720-0.758). The All-Clin+Rad model constructed by integrating RS and clinicopathological predictors showed superior performance with a C-index of 0.775 (95 % confidence interval [CI], 0.723-0.827), 0.739 (95 %CI, 0.654-0.823), and 0.822 (95 %CI, 0.720-0.924) in the development, internal test, and external test cohorts, respectively.

CONCLUSIONS

The radiomics signature notably enhanced the prediction of tumor recurrence in rectal cancer patients with negative pretreatment CEA, assisting clinicians in making personalized follow-up plans.

MRI-based radiomics for stratifying recurrence risk of early-onset rectal cancer: a multicenter study

BACKGROUND

Early-onset rectal cancer (EORC) is characterized by a unique disease process with different clinicopathological features compared with late-onset rectal cancer (LORC). Research on the risk of recurrence in EORC patients, however, is limited. We aim to develop a predictive model to accurately predict EORC recurrence risk.

MATERIALS AND METHODS

Rectal cancer patients who underwent radical surgery and T2-weighted imaging and diffusion-weighted imaging magnetic resonance imaging (MRI) were retrospectively enrolled from three medical institutions from November 2012 to November 2018. Differences in clinicopathological characteristics between EORC and LORC were compared. Five prediction models for disease-free survival were constructed based on clinicopathological variables and five radiomic features from pretreatment MRI of the EORC. A fixed cut-off value calculated in the training set was used to stratify EORC patients into high-risk and low-risk groups of post-operative recurrence. Model performance was evaluated by concordance index (C-index) and receiver operating characteristic curve.

RESULTS

A total of 264 EORC patients (median age, 43 years, 163 males) and 778 LORC patients (median age, 62 years, 520 males) were enrolled. Pretreatment positive carcinoembryonic antigen [hazard ratio (HR) = 2.84, P = 0.006], pathological positive lymph node status (pN positive) [HR = 2.86, P = 0.011] and MRI-based radiomics score [HR = 2.72, P < 0.001] are independent risk factors for disease-free survival in EORC patients. The EORC-ClinPathRadiom model, constructed by integrating the clinicopathological characteristics and MRI-based radiomics features of EORC, showed C-index of 0.82, 0.82, and 0.81 in the training, internal, and external test sets, respectively. This model effectively stratified EORC patients into high risk and low risk of recurrence (HRs for the training, internal, and external test sets were 8.96, 6.81, and 7.46, respectively).

CONCLUSION

The EORC-ClinPathRadiom model can effectively predict and stratify the risk of post-operative recurrence in EORC patients.

Arterial Mucosal Linear Enhancement at Contrast-enhanced MRI to Exclude Residual Tumor after Neoadjuvant Chemotherapy and Radiation Therapy for Rectal Cancer

Background A watch-and-wait regimen for locally advanced rectal cancer after neoadjuvant chemotherapy and radiation therapy (NCRT) relies on identifying complete tumor response. However, the concordance between a complete response at combined T2-weighted and diffusion-weighted MRI (T2DWI) and pathologic complete response (pCR; ie, ypT0N0) in the tumor is unsatisfactory. Purpose To assess whether identification of mucosal linear enhancement (MLE) at arterial-phase contrast-enhanced (CE) T1-weighted MRI is associated with ypT0 status in patients with locally advanced rectal cancer after NCRT and to evaluate whether combining MLE at CE T1-weighted MRI and negative lymph node metastasis (LNM) at T2DWI can improve identification of pCR. Materials and Methods This retrospective study included patients with locally advanced rectal cancer who underwent total mesorectal excision after NCRT between July 2020 and July 2023 at a tertiary referral academic center. Restaging MRI included T2DWI and arterial-phase CE T1-weighted MRI for primary tumor assessment and T2DWI for evaluation of LNM status. Imaging features associated with ypT0 status were identified at multivariable regression analysis. Results In total, 239 patients (mean age, 58 years ± 12 [SD]; 180 male patients) were assessed. MLE was more common in the ypT0 group than in the ypT1-4 group after NCRT (73% vs 4%, respectively; P < .001). MLE was associated with higher odds of ypT0 status in an adjusted analysis (odds ratio, 137; 95% CI: 25, 767; P < .001). The combination of MLE and negative LNM status achieved an area under the receiver operating characteristic curve of 0.84 (95% CI: 0.79, 0.88) for pCR. Conclusion MLE at CE MRI was associated with higher odds of complete tumor response. Combining MLE and negative LNM status showed good performance for identifying complete tumor response and may exclude residual tumors after NCRT in patients with locally advanced rectal cancer. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Schoellnast in this issue.

Prediction of pathologic complete response to neoadjuvant chemoradiation in locally advanced rectal cancer

Purpose

To investigate the predictive factors of pathologic complete response (pCR) in locally advanced rectal cancer (LARC) patients who had been treated with neoadjuvant chemoradiation (nCRT).

Methods and materials

For this retrospective study, 53 LARC patients (37 males and 16 females; age range 25 to 79 years) were selected. Clinical characteristics, baseline mrTNM staging, MR gross tumor volumes (GTV), and pCR were evaluated. The diagnostic accuracy of GTV for predicting pCR was calculated.

Results

Among 53 LARC patients, 15 patients achieved pCR (28.3%), while 38 patients achieved non-pCR. Only three (5.7%) out of 53 patients did not downstage after nCRT. GTV and tumor differentiation were the significant prognostic parameters for predicting pCR. A tumor volume threshold of 21.1 cm3 was determined as a predictor for pCR, with a sensitivity of 84% and specificity of 47%. In addition, GTV was associated with mrN stage, circumferential resection margin (CRM) status, extramural vascular invasion (EMVI) status, and pretreatment serum CEA level.

Conclusion

Tumor volume and tumor differentiation have significant predictive values in preoperative assessment of pCR among LARC patients. These findings aid clinicians to discriminate those patients who may likely benefit from preoperative regimens and to make optimal treatment plans.