This study investigates the dose-response patterns associated with radiation pneumonitis (RP) in patients treated for thoracic malignancies with different radiation modalities. To this end, voxel-based analysis (VBA) empowered by a novel strategy for the characterization of spatial properties of dose maps was applied. Data from 382 lung cancer and mediastinal lymphoma patients from three institutions treated with different radiation therapy (RT) techniques were analyzed. Each planning CT and biologically effective dose map (?/? = 3 Gy) was spatially normalized on a com-mon anatomical reference. The VBA of local dose differences between patients with and without RP was performed and the clusters of voxels with dose differences that significantly correlated with RP at a p-level of 0.05 were generated accordingly. The robustness of VBA inference was evaluated by a novel characterization for spatial properties of dose maps based on probabilistic independent component analysis (PICA) and connectograms. This lays robust foundations to the obtained find-ings that the lower parts of the lungs and the heart play a prominent role in the development of RP. Connectograms showed that the dataset can support a radiobiological differentiation between the main heart and lung substructures.

Radiation pneumonitis in thoracic cancer patients: Multi-center voxel-based analysis

Palma Giuseppe;Monti Serena;Cella Laura
2021

Abstract

This study investigates the dose-response patterns associated with radiation pneumonitis (RP) in patients treated for thoracic malignancies with different radiation modalities. To this end, voxel-based analysis (VBA) empowered by a novel strategy for the characterization of spatial properties of dose maps was applied. Data from 382 lung cancer and mediastinal lymphoma patients from three institutions treated with different radiation therapy (RT) techniques were analyzed. Each planning CT and biologically effective dose map (?/? = 3 Gy) was spatially normalized on a com-mon anatomical reference. The VBA of local dose differences between patients with and without RP was performed and the clusters of voxels with dose differences that significantly correlated with RP at a p-level of 0.05 were generated accordingly. The robustness of VBA inference was evaluated by a novel characterization for spatial properties of dose maps based on probabilistic independent component analysis (PICA) and connectograms. This lays robust foundations to the obtained find-ings that the lower parts of the lungs and the heart play a prominent role in the development of RP. Connectograms showed that the dataset can support a radiobiological differentiation between the main heart and lung substructures.
2021
Istituto di Biostrutture e Bioimmagini - IBB - Sede Napoli
Connectograms
Probabilistic independent component analysis
Radiation pneumonitis
Thoracic cancer
Voxel-based analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/440858
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