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Volume ratio factor: a novel CT-derived biomarker for pre-planning ipsilateral lung dose risk stratification in breast cancer radiotherapy.

July 10, 2026pubmed logopapers

Authors

Meng Q,Qi Z,Li Z,Hu B,Xue G,Zhong R

Affiliations (5)

  • Radiotherapy Physics and Technology Center, Cancer Center, West China Hospital, Sichuan University, Chengdu, China.
  • Department of Nuclear Medicine, West China Hospital, Sichuan University, Chengdu, China.
  • Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China.
  • West China School of Medicine, Sichuan University, Sichuan University Affiliated Chengdu Second People's Hospital, Chengdu Second People's Hospital, Chengdu, China.
  • Health Management Center, General Practice Medical Center, West China Hospital, Sichuan University, Chengdu, China.

Abstract

Ipsilateral lung dose in breast cancer radiotherapy is typically evaluated only after treatment planning, limiting early risk stratification and planning optimization. This study aimed to develop and validate a novel computed tomography (CT)-derived volumetric biomarker, the volume ratio factor (VRF), for pre-planning assessment of ipsilateral lung dose risk in breast cancer radiotherapy. In this retrospective single-center study, 58 breast cancer patients receiving volumetric modulated arc therapy (VMAT) with regional nodal irradiation (RNI) were analyzed. VRF was defined as the ratio of lung internal volume (LIV) to ipsilateral lung volume (ILV) using simulation CT. Correlation analyses were performed between VRF and lung dose metrics, and predictive performance was compared with conventional anatomical parameters using receiver operating characteristic (ROC) analysis and machine learning regression models. VRF demonstrated the strongest correlation with mean lung dose (MLD) among all evaluated anatomical parameters (r=0.582, P<0.01), with significant correlation also observed for V20 (r=0.485, P<0.01) and V10 (r=0.438, P<0.01). ROC analysis showed that VRF achieved the highest discriminative performance for identifying patients with MLD >13 Gy [area under the curve (AUC) =0.71]. Regression analyses further demonstrated stable predictive performance with low estimation error using repeated cross-validation [mean absolute error (MAE): 0.51±0.10 Gy; mean absolute percentage error (MAPE): 4.22%±0.90%]. Compared with seven conventional anatomical parameters, VRF reduced MAE and MAPE by 19.5% and 20.9%, respectively, across all regression frameworks and lung dose-volume endpoints. In the subgroup without internal mammary node (IMN) irradiation, the correlation between VRF and MLD further increased to r=0.637. VRF is a simple and interpretable CT-derived biomarker that captures three‑dimensional target‑lung spatial interaction. It enables pre‑planning risk stratification of ipsilateral lung dose and may support geometry‑informed, individualized radiotherapy planning.

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Journal Article

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