Evaluation of a multiparametric MRI scoring system for histopathologic treatment response following preoperative chemoradiotherapy for rectal cancer

Radiomics for the Prediction of Pathological Complete Response to Neoadjuvant Chemoradiation in Locally Advanced Rectal Cancer: A Prospective Observational Trial

(1) Background: An increasing amount of research has supported the role of radiomics for predicting pathological complete response (pCR) to neoadjuvant chemoradiation treatment (nCRT) in order to provide better management of locally advanced rectal cancer (LARC) patients. However, the lack of validation from prospective trials has hindered the clinical adoption of such studies. The purpose of this study is to validate a radiomics model for pCR assessment in a prospective trial to provide informative insight into radiomics validation. (2) Methods: This study involved a retrospective cohort of 147 consecutive patients for the development/validation of a radiomics model, and a prospective cohort of 77 patients from two institutions to test its generalization. The model was constructed using T2-weighted, diffusion-weighted, and dynamic contrast-enhanced MRI to understand the associations with pCR. The consistency of physicians' evaluations and agreement on pathological complete response prediction were also evaluated, with and without the aid of the radiomics model. (3) Results: The radiomics model outperformed both physicians' visual assessments in the prospective test cohort, with an area under the curve (AUC) of 0.84 (95% confidence interval of 0.70-0.94). With the aid of the radiomics model, a junior physician could achieve comparable performance as a senior oncologist. (4) Conclusion: We have built and validated a radiomics model with pretreatment MRI for pCR prediction of LARC patients undergoing nCRT.

Utility of Circulating Free DNA Fragmentomics in the Prediction of Pathological Response after Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer

BACKGROUND

A "Watch and Wait" (W&W) approach has become an alternative to surgery for locally advanced rectal cancer (LARC) after neoadjuvant chemoradiotherapy (nCRT). Precise prediction of pathological complete response (pCR) will improve patient selection for W&W. We investigated the utility of cell-free DNA (cfDNA) fragmentomics in predicting pCR.

METHODS

We recruited 119 LARC patients and evaluated nCRT response by pCR status and pathological or MRI tumor regression grade (mrTRG). Plasma samples before, during, and after nCRT were applied to deep targeted-panel sequencing, with 103 patients having complete samples. cfDNA fragment and 5'-end motif profiles were used to construct elastic-net logistic regression models to predict non-pCR. Predictive performance was measured by area under the receiver operator characteristic curve (AUC), sensitivity, and specificity.

RESULTS

In the training cohort, the model based on 5'-end motif profile plus mrTRG achieved the highest cross-validation AUC (0.92, 95% CI, 0.91-0.93). The AUC in a testing cohort was 0.96 (95% CI, 0.90-1.00). The models based on 5'-end motif profile alone or in combination with mrTRG both maintained good predictive ability for patients without detectable circulating tumor DNA (AUC 0.94, 95% CI, 0.93-0.95; AUC 0.95, 95% CI, 0.94-0.96). In an external validation cohort, the model trained with a local 5'-end motif profile obtained an AUC of 0.878 (95% CI, 0.801-0.956) in discriminating colorectal cancer from healthy subjects.

CONCLUSIONS

The combination of a 5'-end motif profile with mrTRG has the potential to predict the response to nCRT, and therefore may improve the patient selection for a W&W approach.

MRI Evaluation of Complete and Near-Complete Response after Neoadjuvant Therapy in Patients with Locally Advanced Rectal Cancer

Purpose To evaluate MRI performance in restaging locally advanced rectal cancers (LARC) after neoadjuvant chemoradiotherapy (nCRT) and interobserver agreement in identifying complete response (CR) and near-complete response (nCR). Methods 40 patients with CR and nCR on restaging MRI, surgery and/or endoscopy were enrolled. Two radiologists independently scored the restaging MRI and reported the presence of split scar sign (SSS) and MRI tumor regression grade (mrTRG). Diagnostic accuracy and ROC curves were calculated for single and combined sequences, with inter-reader agreement. Results Diagnostic performance was good for detecting CR and weaker for nCR. T2WI had the highest AUCs among individual sequences. There was a significant positive correlation between SSS and CR, with high Sp (89.5%/73.7%) and PPV (90%/79.2%) for both Readers. Similar accuracy rates were observed for the combination of sequences, with AUCs of 0.828–0.847 for CR and 0.690–0.762 for nCR. Interobserver agreement was strong for SSS, moderate for T2WI, weak for the combination of sequences. Conclusions Restaging MRI had good diagnostic performance in identifying CR and nCR. SSS had high Sp and PPV in diagnosing CR, with a strong level of interobserver agreement. T2WI with DWI was the optimal combination of sequences for selecting good responders.