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Article

Radiation Pneumonitis in Thoracic Cancer Patients: Multi-Center Voxel-Based Analysis

1
Institute of Biostructures and Bioimaging, National Research Council, 80145 Napoli, Italy
2
Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Napoli, Italy
3
Department of Radiation Oncology, MD Anderson Cancer Center, Houston, TX 77030, USA
4
Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
5
Department of Radiation Physics, MD Anderson Cancer Center, Houston, TX 77030, USA
*
Authors to whom correspondence should be addressed.
Academic Editor: Charles B. Simone
Cancers 2021, 13(14), 3553; https://doi.org/10.3390/cancers13143553
Received: 31 May 2021 / Revised: 7 July 2021 / Accepted: 14 July 2021 / Published: 15 July 2021
The pathophysiology of radiation pneumonitis (RP) after thoracic cancer radiation treatments is still not completely understood although the identification of underlying RP mechanisms may improve the therapeutic window of thoracic cancer patients. The aim of our retrospective study was to explore the dose–response patterns associated with RP by a multi-center voxel-based analysis. In a heterogeneously treated population of 382 thoracic cancer patients, we confirmed the previously described heart–lung interaction in the development of RP. The empowerment of VBA with a novel description of dose map spatial properties based on probabilistic independent component analysis (PICA) and connectograms provided valuable additional and independent information on the radiobiology of RP.
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 (α/β = 3 Gy) was spatially normalized on a common 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 findings 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. View Full-Text
Keywords: radiation pneumonitis; thoracic cancer; voxel-based analysis; probabilistic independent component analysis; connectograms radiation pneumonitis; thoracic cancer; voxel-based analysis; probabilistic independent component analysis; connectograms
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MDPI and ACS Style

Palma, G.; Monti, S.; Pacelli, R.; Liao, Z.; Deasy, J.O.; Mohan, R.; Cella, L. Radiation Pneumonitis in Thoracic Cancer Patients: Multi-Center Voxel-Based Analysis. Cancers 2021, 13, 3553. https://doi.org/10.3390/cancers13143553

AMA Style

Palma G, Monti S, Pacelli R, Liao Z, Deasy JO, Mohan R, Cella L. Radiation Pneumonitis in Thoracic Cancer Patients: Multi-Center Voxel-Based Analysis. Cancers. 2021; 13(14):3553. https://doi.org/10.3390/cancers13143553

Chicago/Turabian Style

Palma, Giuseppe, Serena Monti, Roberto Pacelli, Zhongxing Liao, Joseph O. Deasy, Radhe Mohan, and Laura Cella. 2021. "Radiation Pneumonitis in Thoracic Cancer Patients: Multi-Center Voxel-Based Analysis" Cancers 13, no. 14: 3553. https://doi.org/10.3390/cancers13143553

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