Novel radiomic signatures for treatment response to neoadjuvant therapy in rectal cancers - ABSTRACT: With nearly 45,000 rectal cancers to be diagnosed in 2023, the major clinical question of interest is the identification of those patients who will achieve sustained clinical complete response (cCR, no detectable macroscopic tumor) or true pCR (pathologic complete response, with very few/no tumor cells). With the recent incorporation of options such as total neoadjuvant therapy (neoadjuvant chemotherapy and chemoradiation), these complete responder patients can comprise up to ~50% of the population. If these “true” complete response patients could be reliably identified, they could avoid the major complications of rectal resection (anastomotic leakage, pelvic sepsis, ureteric injury) and quality-of-life issues (permanent ostomy, fecal incontinence), with no impact on their overall survival. However, there are no validated objective diagnostic criteria (using endoscopy, MRI, and digital rectal exams) or serum/blood-based markers (e.g., carcinoembryonic antigen, CEA) that can definitively identify true complete responders for organ-preserving strategies and non-operative management in rectal cancers. Quantitative non-invasive imaging markers that accurately characterize pathologic tumor regression in rectal cancers after neoadjuvant therapy could be hugely impactful in selecting complete response patients who can be safely recommended organ-preservation vs partial/non-responders who require surgery. To specifically capture subtle pathologic cues on MRI resulting from the desmoplastic fibrosis and tumor response after chemoradiation/TNT, we have identified unique computer-extracted image features of gradient response and morphological disruptions within the lesion (wall, tumor) and peri-lesion environment (lumen, peritumoral fat). This R01 will build on these exciting findings to develop and validate a Radiomic Tumor Response (RadTR) classifier to accurately identify complete responders after neoadjuvant therapy in rectal cancers, via routine MRI. The RadTR classifier will additionally incorporate a novel “spatial diversity” descriptor that captures macro-scale tissue organization and stromal composition that are biological hallmarks of complete response. Using a multi-institutional cohort of ~900 patients, our validation of the RadTR classifier will focus on three key criteria. (i) To enable clinical interpretability, we will conduct detailed histomorphological evaluation of RadTR features via spatially mapped MRI and whole-mount rectal pathology specimens. (ii) For confirming diagnostic reliability, the RadTR classifier will be comprehensively compared against clinical evaluation criteria (endoscopy, MRI, digital rectal exam) as well as within a multi-reader study; to confirm performance improvements in identifying CR via MRI. (iii) Towards ensuring equity in population performance for future clinical deployment, the RadTR classifier will be validated across multiple institutions and populations using a national clinical trial cohort of TNT in rectal cancers (NRG GI-002). To be clinically actionable for recommending organ- preserving treatment in rectal cancers, RadTR model will target a 50% improvement in sensitivity for identifying complete response as well as ensuring 95% specificity in identifying partial/non-pCR patients needing surgery.
