Pretreatment CT and 18 F-FDG PET-based radiomic model predicting pathological complete response and loco-regional control following neoadjuvant chemoradiation in oesophageal cancer

Anupam Rishi; Geoffrey G Zhang; Zhigang Yuan; Austin J Sim; Ethan Y Song; Eduardo G Moros; Michal R Tomaszewski; Kujtim Latifi; Jose M Pimiento; Jacques-Pierre Fontaine; Rutika Mehta; Louis B Harrison; Sarah E Hoffe; Jessica M Frakes

doi:10.1111/1754-9485.13128

Pretreatment CT and ¹⁸ F-FDG PET-based radiomic model predicting pathological complete response and loco-regional control following neoadjuvant chemoradiation in oesophageal cancer

J Med Imaging Radiat Oncol. 2021 Feb;65(1):102-111. doi: 10.1111/1754-9485.13128. Epub 2020 Dec 1.

Affiliations

¹ Department of Radiation Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, USA.
² Morsani College of Medicine, University of South Florida, Tampa, Florida, USA.
³ Department of Cancer Physiology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, USA.
⁴ Department of Gastrointestinal Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, USA.

PMID: 33258556
DOI: 10.1111/1754-9485.13128

Abstract

Introduction: To develop a radiomic-based model to predict pathological complete response (pCR) and outcome following neoadjuvant chemoradiotherapy (NACRT) in oesophageal cancer.

Methods: We analysed 68 patients with oesophageal cancer treated with NACRT followed by esophagectomy, who had staging 18F-fluorodeoxyglucose (¹⁸ F-FDG) positron emission tomography (PET) and computed tomography (CT) scans performed at our institution. An in-house data-chjmirocterization algorithm was used to extract 3D-radiomic features from the segmented primary disease. Prediction models were constructed and internally validated. Composite feature, F_c = α * F_PET + (1 - α) * F_CT , 0 ≤ α ≤ 1, was constructed for each corresponding CT and PET feature. Loco-regional control (LRC), recurrence-free survival (RFS), metastasis-free survival (MFS) and overall survival (OS) were estimated by Kaplan-Meier analysis, and compared using log-rank test.

Results: Median follow-up was 59 months. pCR was achieved in 34 (50%) patients. Five-year RFS, LRC, MFS and OS were 67.1%, 88.5%, 75.6% and 57.6%, respectively. Tumour Regression Grade (TRG) 0-1 indicative of complete response or minimal residual disease was significantly associated with improved 5-year LRC [93.7% vs 71.8%; P = 0.020; HR 0.19, 95% CI 0.04-0.85]. Four sepjmirote pCR predictive models were built for CT alone, PET alone, CT+PET and composite. CT, PET and CT+PET models had AUC 0.73 ± 0.08, 0.66 ± 0.08 and 0.77 ± 0.07, respectively. The composite model resulted in an improvement of pCR predicting power with AUC 0.87 ± 0.06. Stratifying patients with a low versus high radiomic score showed clinically relevant improvement in 5-year LRC favouring low-score group (91.1% vs. 80%, 95% CI 0.09-1.77, P = 0.2).

Conclusion: The composite CT/PET radiomics model was highly predictive of pCR following NACRT. Validation in larger data sets is warranted to determine whether the model can predict clinical outcomes.

Keywords: chemoradiation; oesophageal cancer; radiomics; response.

MeSH terms

Chemoradiotherapy
Esophageal Neoplasms* / diagnostic imaging
Esophageal Neoplasms* / therapy
Fluorodeoxyglucose F18
Humans
Neoadjuvant Therapy*
Positron Emission Tomography Computed Tomography
Radiopharmaceuticals
Retrospective Studies

Substances

Radiopharmaceuticals
Fluorodeoxyglucose F18