{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T07:00:40Z","timestamp":1767164440811,"version":"build-2238731810"},"reference-count":41,"publisher":"Wiley","issue":"36","license":[{"start":{"date-parts":[[2023,11,12]],"date-time":"2023-11-12T00:00:00Z","timestamp":1699747200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Thoracic Cancer"],"published-print":{"date-parts":[[2023,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>We sought to quantify diffuse parenchymal lung disease (DPLD) extent using quantitative computed tomography (CT) analysis and to investigate its association with radiation pneumonitis (RP) development in non\u2010small cell lung cancer (NSCLC) patients receiving definitive concurrent chemoradiation therapy (CCRT).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A total of 82 NSCLC patients undergoing definitive CCRT were included in this prospective cohort study. Pretreatment CT scans were analyzed using quantitative CT analysis software. Low\u2010attenuation area (LAA) features based on lung density and texture features reflecting interstitial lung disease (ILD) were extracted from the whole lung. Clinical and dosimetric factors were also evaluated. RP development was assessed using the Common Terminology Criteria for Adverse Events version 5.0. Univariable and multivariable logistic regression analyses were performed to identify independent risk factors for grade\u2009\u22653 (\u2265GR3) RP.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>RP was identified in 68 patients (73.9%), with nine patients (10.9%) experiencing \u2265GR3 RP. Univariable logistic regression analysis identified excess kurtosis and high\u2010attenuation area (HAA)_volume (cc) as significantly associated with \u2265GR3 RP. Multivariable logistic regression analysis showed that the combined use of imaging features and clinical factors (forced expiratory volume in 1\u2009second [FEV1], forced vital capacity [FVC], and CHEMO regimen) demonstrated the best performance (area under the receiver operating characteristic curve\u2009=\u20090.924) in predicting \u2265GR3 RP.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Quantified imaging features of DPLD obtained from pretreatment CT scans would predict the occurrence of RP in NSCLC patients undergoing definitive CCRT. Combining imaging features with clinical factors could improve the accuracy of the predictive model for severe RP.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/1759-7714.15156","type":"journal-article","created":{"date-parts":[[2023,11,12]],"date-time":"2023-11-12T20:54:38Z","timestamp":1699822478000},"page":"3530-3539","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Quantification of diffuse parenchymal lung disease in non\u2010small cell lung cancer patients with definitive concurrent chemoradiation therapy for predicting radiation pneumonitis"],"prefix":"10.1111","volume":"14","author":[{"given":"Ye Chan","family":"An","sequence":"first","affiliation":[{"name":"Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology Sungkyunkwan University  Seoul South Korea"},{"name":"Department of Radiation Oncology Samsung Medical Center, Sungkyunkwan 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