Exploring published and novel pre-treatment CT and PET radiomics to stratify risk of progression among early-stage non-small cell lung cancer patients treated with stereotactic radiation

Maria Thor ^1,4, Kelly Fitzgerald ^2,4, Aditya Apte ¹, Jung Hun Oh ¹, Aditi Iyer ¹, Otasowie Odiase ², Saad Nadeem ¹, Ellen D. Yorke ¹, Jamie Chaft ³, Abraham J. Wu ², Michael Offin ³, Charles B Simone II ², Isabel Preeshagul ³, Daphna Y. Gelblum ², Daniel Gomez ², Joseph O. Deasy ¹, Andreas Rimner ^2
1Department of Medical Physics, Memorial Sloan Kettering Cancer Center
²Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center
³Department of Medicine, Memorial Sloan Kettering Cancer Center

https://doi.org/10.1016/j.radonc.2023.109983

This paper examines the critical issue of identifying patients at risk of disease progression after SBRT treatment. The occurrence of disease progression in a significant percentage of cases highlights the necessity for improved predictive tools. In this context, the study utilizes an innovative approach by integrating spiculation as a crucial radiomics feature in the analysis. Spiculation, a visually apparent pattern in imaging, has gained recognition for its potential as a prognostic indicator. By utilizing spiculation alongside other radiomics features, this study seeks to improve the precision and dependability of forecasts related to progression-free survival among early-stage NSCLC patients after SBRT. Incorporating spiculation into the radiomics framework is a noteworthy advance toward more personalized and effective therapeutic approaches for this patient cohort.

Highlights

• Pre-treatment CT and PET features predict PFS to a larger extent than other non-image-based characteristics.
• A re-fitted model based on the two most published CT and PET features (SUVmax and tumor diameter) predicted PFS with high accuracy (AUC=0.78)
• The performance of a model built on novel CT and PET features did not supersede that of the re-fitted model based on SUVmax and diameter (AUC=0.75)