Radiomic Modeling of Bone Density and Rib Fracture Risk After Stereotactic Body Radiation Therapy for Early-Stage Non-Small Cell Lung Cancer

Nicholas R Rydzewski; Poonam Yadav; Hima Bindu Musunuru; Kevin M Condit; David Francis; Shuang G Zhao; Andrew M Baschnagel

doi:10.1016/j.adro.2021.100884

Radiomic Modeling of Bone Density and Rib Fracture Risk After Stereotactic Body Radiation Therapy for Early-Stage Non-Small Cell Lung Cancer

Adv Radiat Oncol. 2021 Dec 29;7(3):100884. doi: 10.1016/j.adro.2021.100884. eCollection 2022 May-Jun.

Authors

Nicholas R Rydzewski^{1

2}, Poonam Yadav³, Hima Bindu Musunuru⁴, Kevin M Condit^{1

2}, David Francis^{1

2}, Shuang G Zhao^{1

2

5}, Andrew M Baschnagel^{1

2}

Affiliations

¹ Department of Human Oncology, University of Wisconsin Hospital and Clinics, Madison, Wisconsin.
² Carbone Cancer Center, University of Wisconsin Hospital and Clinics, Madison, Wisconsin.
³ Department of Radiation Oncology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
⁴ Department of Radiation Oncology, UPMC Hillman Cancer Center, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
⁵ William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin.

Abstract

Purpose: Our purpose was to determine whether bone density and bone-derived radiomic metrics in combination with dosimetric variables could improve risk stratification of rib fractures after stereotactic body radiation therapy (SBRT) for early-stage non-small cell lung cancer (NSCLC).

Methods and materials: A retrospective analysis was conducted of patients with early-stage NSCLC treated with SBRT. Dosimetric data and rib radiomic data extracted using PyRadiomics were used for the analysis. A subset of patients had bone density scans that were used to create a predicted bone density score for all patients. A 10-fold cross validated approach with 10 resamples was used to find the top univariate logistic models and elastic net regression models that predicted for rib fracture.

Results: A total of 192 treatment plans were included in the study with a rib fracture rate of 16.1%. A predicted bone density score was created from a multivariate model with vertebral body Hounsfield units and patient weight, with an R-squared of 0.518 compared with patient dual-energy x-ray absorptiometry T-scores. When analyzing all patients, a low predicted bone density score approached significance for increased risk of rib fracture (P = .07). On competing risk analysis, when stratifying patients based on chest wall V30 Gy and bone density score, those with a V30 Gy ≥30 cc and a low bone density score had a significantly higher risk of rib fracture compared with all other patients (P < .001), with a predicted 2-year risk of rib fracture of 28.6% (95% confidence interval, 17.2%-41.1%) and 4.9% (95% confidence interval, 2.3%-9.0%), respectively. Dosimetric variables were the primary drivers of fracture risk. A multivariate elastic net regression model including all dosimetric variables was the best predictor of rib fracture (area under the curve [AUC], 0.864). Bone density variables (AUC, 0.618) and radiomic variables (AUC, 0.617) have better predictive power than clinical variables that exclude bone density (AUC, 0.538).

Conclusion: Radiomic features, including a bone density score that includes vertebral body Hounsfield units and radiomic signatures from the ribs, can be used to stratify risk of rib fracture after SBRT for NSCLC.