Radiation Pneumonitis in Thoracic Cancer Patients: Multi-Center Voxel-Based Analysis
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 dos...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-07-01
|
| Series: | Cancers |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-6694/13/14/3553 |
| _version_ | 1797527496320614400 |
|---|---|
| author | Giuseppe Palma Serena Monti Roberto Pacelli Zhongxing Liao Joseph O. Deasy Radhe Mohan Laura Cella |
| author_facet | Giuseppe Palma Serena Monti Roberto Pacelli Zhongxing Liao Joseph O. Deasy Radhe Mohan Laura Cella |
| author_sort | Giuseppe Palma |
| collection | DOAJ |
| description | 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 <i>p</i>-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. |
| first_indexed | 2024-03-10T09:44:33Z |
| format | Article |
| id | doaj.art-f0ed0b0cc3c24047987dc7194500285f |
| institution | Directory Open Access Journal |
| issn | 2072-6694 |
| language | English |
| last_indexed | 2024-03-10T09:44:33Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cancers |
| spelling | doaj.art-f0ed0b0cc3c24047987dc7194500285f2023-11-22T03:25:14ZengMDPI AGCancers2072-66942021-07-011314355310.3390/cancers13143553Radiation Pneumonitis in Thoracic Cancer Patients: Multi-Center Voxel-Based AnalysisGiuseppe Palma0Serena Monti1Roberto Pacelli2Zhongxing Liao3Joseph O. Deasy4Radhe Mohan5Laura Cella6Institute of Biostructures and Bioimaging, National Research Council, 80145 Napoli, ItalyInstitute of Biostructures and Bioimaging, National Research Council, 80145 Napoli, ItalyDepartment of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Napoli, ItalyDepartment of Radiation Oncology, MD Anderson Cancer Center, Houston, TX 77030, USADepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USADepartment of Radiation Physics, MD Anderson Cancer Center, Houston, TX 77030, USAInstitute of Biostructures and Bioimaging, National Research Council, 80145 Napoli, ItalyThis 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 <i>p</i>-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.https://www.mdpi.com/2072-6694/13/14/3553radiation pneumonitisthoracic cancervoxel-based analysisprobabilistic independent component analysisconnectograms |
| spellingShingle | Giuseppe Palma Serena Monti Roberto Pacelli Zhongxing Liao Joseph O. Deasy Radhe Mohan Laura Cella Radiation Pneumonitis in Thoracic Cancer Patients: Multi-Center Voxel-Based Analysis Cancers radiation pneumonitis thoracic cancer voxel-based analysis probabilistic independent component analysis connectograms |
| title | Radiation Pneumonitis in Thoracic Cancer Patients: Multi-Center Voxel-Based Analysis |
| title_full | Radiation Pneumonitis in Thoracic Cancer Patients: Multi-Center Voxel-Based Analysis |
| title_fullStr | Radiation Pneumonitis in Thoracic Cancer Patients: Multi-Center Voxel-Based Analysis |
| title_full_unstemmed | Radiation Pneumonitis in Thoracic Cancer Patients: Multi-Center Voxel-Based Analysis |
| title_short | Radiation Pneumonitis in Thoracic Cancer Patients: Multi-Center Voxel-Based Analysis |
| title_sort | radiation pneumonitis in thoracic cancer patients multi center voxel based analysis |
| topic | radiation pneumonitis thoracic cancer voxel-based analysis probabilistic independent component analysis connectograms |
| url | https://www.mdpi.com/2072-6694/13/14/3553 |
| work_keys_str_mv | AT giuseppepalma radiationpneumonitisinthoraciccancerpatientsmulticentervoxelbasedanalysis AT serenamonti radiationpneumonitisinthoraciccancerpatientsmulticentervoxelbasedanalysis AT robertopacelli radiationpneumonitisinthoraciccancerpatientsmulticentervoxelbasedanalysis AT zhongxingliao radiationpneumonitisinthoraciccancerpatientsmulticentervoxelbasedanalysis AT josephodeasy radiationpneumonitisinthoraciccancerpatientsmulticentervoxelbasedanalysis AT radhemohan radiationpneumonitisinthoraciccancerpatientsmulticentervoxelbasedanalysis AT lauracella radiationpneumonitisinthoraciccancerpatientsmulticentervoxelbasedanalysis |