MRI-based radiomic score increased mrTRG accuracy in predicting rectal cancer response to neoadjuvant therapy.

Autor: Miranda, Joao, Horvat, Natally, Assuncao Jr, Antonildes N., de M. Machado, Felipe Augusto, Chakraborty, Jayasree, Pandini, Rafael Vaz, Saraiva, Samya, Nahas, Caio Sergio Rizkallah, Nahas, Sergio Carlos, Nomura, Cesar Higa
Předmět:
Zdroj: Abdominal Radiology; Jun2023, Vol. 48 Issue 6, p1911-1920, 10p
Abstrakt: Purpose: To develop a magnetic resonance imaging (MRI)-based radiomics score, i.e., "rad-score," and to investigate the performance of rad-score alone and combined with mrTRG in predicting pathologic complete response (pCR) in patients with locally advanced rectal cancer following neoadjuvant chemoradiation therapy. Methods: This retrospective study included consecutive patients with LARC who underwent neoadjuvant chemoradiotherapy followed by surgery from between July 2011 to November 2015. Volumes of interest of the entire tumor on baseline rectal MRI and of the tumor bed on restaging rectal MRI were manually segmented on T2-weighted images. The radiologist also provided the ymrTRG score on the restaging MRI. Radiomic score (rad-score) was calculated and optimal cut-off points for both mrTRG and rad-score to predict pCR were selected using Youden's J statistic. Results: Of 180 patients (mean age = 63 years; 60% men), 33/180 (18%) achieved pCR. High rad-score (> − 1.49) yielded an area under the curve (AUC) of 0.758, comparable to ymrTRG 1–2 which yielded an AUC of 0.759. The combination of high rad-score and ymrTRG 1–2 yielded a significantly higher AUC of 0.836 compared with ymrTRG 1–2 and high rad-score alone (p < 0.001). A logistic regression model incorporating both high rad-score and mrTRG 1–2 was built to calculate adjusted odds ratios for pCR, which was 4.85 (p < 0.001). Conclusion: Our study demonstrates that a rectal restaging MRI-based rad-score had comparable diagnostic performance to ymrTRG. Moreover, the combined rad-score and ymrTRG model yielded a significant better diagnostic performance for predicting pCR. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index