{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T16:40:08Z","timestamp":1755880808867,"version":"3.44.0"},"reference-count":54,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2024,5,31]],"date-time":"2024-05-31T00:00:00Z","timestamp":1717113600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01 CA 202761"],"award-info":[{"award-number":["R01 CA 202761"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2024,9]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Investigations on radiation\u2010induced lung injury (RILI) have predominantly focused on local effects, primarily those associated with radiation damage to lung parenchyma. However, recent studies from our group and others have revealed that radiation\u2010induced damage to branching serial structures such as airways and vessels may also have a substantial impact on post\u2010radiotherapy (RT) lung function. Furthermore, recent results from multiple functional lung avoidance RT trials, although promising, have demonstrated only modest toxicity reduction, likely because they were primarily focused on dose avoidance to lung parenchyma. These observations emphasize the critical need for predictive dose\u2010response models that effectively incorporate both local and distant RILI effects.<\/jats:p><\/jats:sec><jats:sec><jats:title>Purpose<\/jats:title><jats:p>We develop and validate a predictive model for ventilation loss after lung RT. This model, referred to as P+A, integrates local (parenchyma [P]) and distant (central and peripheral airways [A]) radiation\u2010induced damage, modeling partial (narrowing) and complete (collapse) obstruction of airways.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>In an IRB\u2010approved prospective study, pre\u2010RT breath\u2010hold CTs (BHCTs) and pre\u2010 and one\u2010year post\u2010RT 4DCTs were acquired from lung cancer patients treated with definitive RT. Up to 13 generations of airways were automatically segmented on the BHCTs using a research virtual bronchoscopy software. Ventilation maps derived from the 4DCT scans were utilized to quantify pre\u2010 and post\u2010RT ventilation, serving, respectively, as input data and reference standard (RS) in model validation. To predict ventilation loss solely due to parenchymal damage (referred to as P model), we used a normal tissue complication probability (NTCP) model. Our model used this NTCP\u2010based estimate and predicted additional loss due radiation\u2010induced partial or complete occlusion of individual airways, applying fluid dynamics principles and a refined version of our previously developed airway radiosensitivity model. Predictions of post\u2010RT ventilation were estimated in the sublobar volumes (SLVs) connected to the terminal airways. To validate the model, we conducted a k\u2010fold cross\u2010validation. Model parameters were optimized as the values that provided the lowest root mean square error (RMSE) between predicted post\u2010RT ventilation and the RS for all SLVs in the training data. The performance of the P+A and the P models was evaluated by comparing their respective post\u2010RT ventilation values with the RS predictions. Additional evaluation using various receiver operating characteristic (ROC) metrics was also performed.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We extracted a dataset of 560 SLVs from four enrolled patients. Our results demonstrated that the P+A model consistently outperformed the P model, exhibiting RMSEs that were nearly half as low across all patients (13\u00a0\u00b1\u00a03 percentile for the P+A model vs. 24\u00a0\u00b1\u00a03 percentile for the P model on average). Notably, the P+A model aligned closely with the RS in ventilation loss distributions per lobe, particularly in regions exposed to doses \u226513.5\u00a0Gy. The ROC analysis further supported the superior performance of the P+A model compared to the P model in sensitivity (0.98\u00a0vs. 0.07), accuracy (0.87\u00a0vs. 0.25), and balanced predictions.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>These early findings indicate that airway damage is a crucial factor in RILI that should be included in dose\u2010response modeling to enhance predictions of post\u2010RT lung function.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mp.17187","type":"journal-article","created":{"date-parts":[[2024,5,31]],"date-time":"2024-05-31T15:29:06Z","timestamp":1717169346000},"page":"6259-6275","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Integrating local and distant radiation\u2010induced lung injury: Development and validation of a predictive model for ventilation loss"],"prefix":"10.1002","volume":"51","author":[{"given":"Esther 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