Post-Neoadjuvant Treatment MRI Based AI System to Predict pCR for Rectal Cancer

  • STATUS
    Recruiting
  • participants needed
    322
  • sponsor
    Sixth Affiliated Hospital, Sun Yat-sen University
Updated on 16 February 2024
cancer
metastasis
adenocarcinoma
MRI
chemoradiotherapy
adjuvant therapy
rectal cancer
adenocarcinoma of rectum

Summary

In this study, investigators seek for a better way to identify the potential pathologic complete response (pCR) patients form non-pCR patients with locally advanced rectal cancer (LARC), based on their post-neoadjuvant treatment Magnetic Resonance Imaging (MRI) data.

Previously, a post neoadjuvant treatment MRI based radiomics AI model had been constructed and trained. The predictive power of this artificial intelligence system and expert radiologist to identify pCR patients from non-pCR LARC patients will be compared in this randomized controlled, prospective, multicenter, observational clinical study.

Description

This is a randomized controlled, multicenter, prospective, observational clinical study for seeking out a better way to predict the pathologic complete response (pCR) in patients with locally advanced rectal cancer (LARC) based on the post- neoadjuvant treatment Magnetic Resonance Imaging (MRI) data. Patients who have been pathologically diagnosed as rectal adenocarcinoma and defined as clinical II-III staging without distant metastasis will be enrolled from the Sixth Affiliated Hospital of Sun Yat-sen University, Sir Run Run Shaw Hospital and the Third Affiliated Hospital of Kunming Medical College. All participants should follow a standard treatment protocol, including neoadjuvant treatment, total mesorectum excision (TME) surgery and adjuvant chemotherapy. Patients with LARC who received neoadjuvant treatment will be randomly assigned into two arms, and their post-neoadjuvant treatment MRI images will be used to predict their pathologic response (pCR vs. non-pCR). Patients in arm A assign to the artificial intelligence prediction system. While in group B, the patients assign to the expert radiologist prediction. The pathologist will provide the final pathology report of TME surgery specimen (pCR or non-pCR) as a standard. The predictive efficacy of these two arms will be compared in this randomized controlled, multicenter clinical study among patients with locally advanced rectal cancer.

Details
Condition Colorectal Cancer, Colorectal Cancer, Rectal Cancer, Rectal Cancer
Age 18years - 75years
Treatment the artificial intelligence, the radiologists
Clinical Study IdentifierNCT04278274
SponsorSixth Affiliated Hospital, Sun Yat-sen University
Last Modified on16 February 2024

Eligibility

Yes No Not Sure

Inclusion Criteria

pathologically diagnosed as rectal adenocarcinoma
defined as clinical II-III staging (T3, and/or positive nodal status) without distant metastasis
receive neoadjuvant chemoradiotherapy or chemotherapy
pre- and post-neoadjuvant treatment MRI data obtained
receive total mesorectum excision (TME) surgery after neoadjuvant therapy and get the pathologic assessment of tumor response

Exclusion Criteria

with history of other cancer
insufficient imaging quality of MRI to delineate tumor volume or obtain measurements (e.g., lack of sequence, motion artifacts)
not completing neoadjuvant chemotherapy or chemoradiotherapy
tumor recurrence or distant metastasis during neoadjuvant treatment
not undergoing surgery resulting in lack of pathologic assessment of tumor response
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