open access

Vol 26, No 1 (2021)
Research paper
Published online: 2021-01-22
Submitted: 2021-01-07
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Pretreatment CT and PET Radiomics Predicting Rectal Cancer Patients in Response to Neoadjuvant Chemoradiotherapy

Zhigang Yuan, Marissa Frazer, Anupam Rishi, Kujtim Latifi, Michal R. Tomaszewski, Eduardo G. Moros, Vladimir Feygelman, Seth Felder, Julian Sanchez, Sophie Dessureault, Iman Imanirad, Richard D. Kim, Louis B. Harrison, Sarah E. Hoffe, Geoffrey G. Zhang, Jessica M. Frakes
DOI: 10.5603/RPOR.a2021.0004
·
Rep Pract Oncol Radiother 2021;26(1):29-34.

open access

Vol 26, No 1 (2021)
Original research articles
Published online: 2021-01-22
Submitted: 2021-01-07

Abstract

Background: The purpose of this study was to characterize pre-treatment non-contrast computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (PET) based radiomics signatures predictive of pathological response and clinical outcomes in rectal cancer patients treated with neoadjuvant chemoradiotherapy (NACRT).

Material and methods: An exploratory analysis was performed using pre-treatment non-contrast CT and PET imaging dataset. The association of tumor regression grade (TRG) and neoadjuvant rectal (NAR) score with pre-treatment CT and PET features was assessed using machine learning algorithms. Three separate predictive models were built for composite features from CT + PET.

Results: The patterns of pathological response were TRG 0 (n = 13; 19.7%), 1 (n = 34; 51.5%), 2 (n = 16; 24.2%), and 3 (n = 3; 4.5%). There were 20 (30.3%) patients with low, 22 (33.3%) with intermediate and 24 (36.4%) with high NAR scores. Three separate predictive models were built for composite features from CT + PET and analyzed separately for clinical endpoints. Composite features with α = 0.2 resulted in the best predictive power using logistic regression. For pathological response prediction, the signature resulted in 88.1% accuracy in predicting TRG 0 vs. TRG 1–3; 91% accuracy in predicting TRG 0–1 vs. TRG 2–3. For the surrogate of DFS and OS, it resulted in 67.7% accuracy in predicting low vs. intermediate vs. high NAR scores.

Conclusion: The pre-treatment composite radiomics signatures were highly predictive of pathological response in rectal cancer treated with NACRT. A larger cohort is warranted for further validation.

Abstract

Background: The purpose of this study was to characterize pre-treatment non-contrast computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (PET) based radiomics signatures predictive of pathological response and clinical outcomes in rectal cancer patients treated with neoadjuvant chemoradiotherapy (NACRT).

Material and methods: An exploratory analysis was performed using pre-treatment non-contrast CT and PET imaging dataset. The association of tumor regression grade (TRG) and neoadjuvant rectal (NAR) score with pre-treatment CT and PET features was assessed using machine learning algorithms. Three separate predictive models were built for composite features from CT + PET.

Results: The patterns of pathological response were TRG 0 (n = 13; 19.7%), 1 (n = 34; 51.5%), 2 (n = 16; 24.2%), and 3 (n = 3; 4.5%). There were 20 (30.3%) patients with low, 22 (33.3%) with intermediate and 24 (36.4%) with high NAR scores. Three separate predictive models were built for composite features from CT + PET and analyzed separately for clinical endpoints. Composite features with α = 0.2 resulted in the best predictive power using logistic regression. For pathological response prediction, the signature resulted in 88.1% accuracy in predicting TRG 0 vs. TRG 1–3; 91% accuracy in predicting TRG 0–1 vs. TRG 2–3. For the surrogate of DFS and OS, it resulted in 67.7% accuracy in predicting low vs. intermediate vs. high NAR scores.

Conclusion: The pre-treatment composite radiomics signatures were highly predictive of pathological response in rectal cancer treated with NACRT. A larger cohort is warranted for further validation.

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Keywords

rectal cancer; CT; PET; radiomics; neoadjuvant chemoradiation therapy; pathologic response

About this article
Title

Pretreatment CT and PET Radiomics Predicting Rectal Cancer Patients in Response to Neoadjuvant Chemoradiotherapy

Journal

Reports of Practical Oncology and Radiotherapy

Issue

Vol 26, No 1 (2021)

Article type

Research paper

Pages

29-34

Published online

2021-01-22

DOI

10.5603/RPOR.a2021.0004

Bibliographic record

Rep Pract Oncol Radiother 2021;26(1):29-34.

Keywords

rectal cancer
CT
PET
radiomics
neoadjuvant chemoradiation therapy
pathologic response

Authors

Zhigang Yuan
Marissa Frazer
Anupam Rishi
Kujtim Latifi
Michal R. Tomaszewski
Eduardo G. Moros
Vladimir Feygelman
Seth Felder
Julian Sanchez
Sophie Dessureault
Iman Imanirad
Richard D. Kim
Louis B. Harrison
Sarah E. Hoffe
Geoffrey G. Zhang
Jessica M. Frakes

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