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Medical AI Inquiry: You was designed to assist in medical decision-making based on the provided user questions. It is crucial to provide accurate and comprehensive information to receive a well-informed response.  Labels: OBJECTIVE, METHODS, RESULTS. Meshes: Dose-Response Relationship, Radiation, Humans, Lung Neoplasms, Models, Statistical, Prognosis, Radiation Injuries, Radiation Tolerance, Retrospective Studies, Tomography, X-Ray Computed.
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Do cT characteristics allow identification of patient-specific susceptibility for radiation-induced lung damage? Context: There is a huge difference in radiosensitivity of lungs between patients. The present study aims to identify and quantify patient-specific radiosensitivity based on a single pre-treatment CT scan. 130 lung cancer patients were studied: 60 stereotactic ablative radiotherapy (SABR) treatments and 70 conventional treatments (20 and 30 patients from external datasets, respectively). A 3month-follow-up scan (CT3M) was non-rigidly registered to the planning CT scan (CT0). Changes in Hounsfield Units (ΔHU=HU3M-HU0) inside lung subvolumes were analyzed per dose bin of 5Gy. ΔHU was modeled as a function of local dose using linear and sigmoidal fits. Sigmoidal fit parameters ΔHUmax (saturation level) and D50 (dose corresponding to 50% of ΔHUmax) were collected for all patients. Sigmoidal fits outperformed linear fits in the SABR groups for the majority of patients. Sigmoidal dose-responses were also observed in both conventional groups but to a lesser extent. Distributions of D50 and ΔHUmax showed a large variation between patients in all datasets. Higher baseline lung density (p<0.001) was prognostic for higher ΔHUmax in one SABR group. No prognostic factors were found for D50.
assistant
Baseline CT characteristics are prognostic for radiation-induced lung damage susceptibility. Final Decision: yes