Quantification of diffuse parenchymal lung disease in non‐small cell lung cancer patients with definitive concurrent chemoradiation therapy for predicting radiation pneumonitis
Abstract Background 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‐small cell lung cancer (NSCLC) patients receiving definitive concurrent...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023-12-01
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| Series: | Thoracic Cancer |
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| Online Access: | https://doi.org/10.1111/1759-7714.15156 |
| _version_ | 1827577871676211200 |
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| author | Ye Chan An Jong Hoon Kim Jae Myung Noh Kyung Mi Yang You Jin Oh Sung Goo Park Hong Ryul Pyo Ho Yun Lee |
| author_facet | Ye Chan An Jong Hoon Kim Jae Myung Noh Kyung Mi Yang You Jin Oh Sung Goo Park Hong Ryul Pyo Ho Yun Lee |
| author_sort | Ye Chan An |
| collection | DOAJ |
| description | Abstract Background 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‐small cell lung cancer (NSCLC) patients receiving definitive concurrent chemoradiation therapy (CCRT). Methods 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‐attenuation 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 ≥3 (≥GR3) RP. Results RP was identified in 68 patients (73.9%), with nine patients (10.9%) experiencing ≥GR3 RP. Univariable logistic regression analysis identified excess kurtosis and high‐attenuation area (HAA)_volume (cc) as significantly associated with ≥GR3 RP. Multivariable logistic regression analysis showed that the combined use of imaging features and clinical factors (forced expiratory volume in 1 second [FEV1], forced vital capacity [FVC], and CHEMO regimen) demonstrated the best performance (area under the receiver operating characteristic curve = 0.924) in predicting ≥GR3 RP. Conclusion 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. |
| first_indexed | 2024-03-08T21:34:00Z |
| format | Article |
| id | doaj.art-4424bdda6339462f9ed8930b33baeb6a |
| institution | Directory Open Access Journal |
| issn | 1759-7706 1759-7714 |
| language | English |
| last_indexed | 2024-03-08T21:34:00Z |
| publishDate | 2023-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | Thoracic Cancer |
| spelling | doaj.art-4424bdda6339462f9ed8930b33baeb6a2023-12-21T03:47:14ZengWileyThoracic Cancer1759-77061759-77142023-12-0114363530353910.1111/1759-7714.15156Quantification of diffuse parenchymal lung disease in non‐small cell lung cancer patients with definitive concurrent chemoradiation therapy for predicting radiation pneumonitisYe Chan An0Jong Hoon Kim1Jae Myung Noh2Kyung Mi Yang3You Jin Oh4Sung Goo Park5Hong Ryul Pyo6Ho Yun Lee7Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology Sungkyunkwan University Seoul South KoreaDepartment of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology Sungkyunkwan University Seoul South KoreaDepartment of Radiation Oncology Samsung Medical Center, Sungkyunkwan University School of Medicine Seoul South KoreaDepartment of Radiation Oncology Samsung Medical Center, Sungkyunkwan University School of Medicine Seoul South KoreaDepartment of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology Sungkyunkwan University Seoul South KoreaDepartment of Radiology and Center for Imaging Science, Samsung Medical Center Sungkyunkwan University School of Medicine Seoul South KoreaDepartment of Radiation Oncology Samsung Medical Center, Sungkyunkwan University School of Medicine Seoul South KoreaDepartment of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology Sungkyunkwan University Seoul South KoreaAbstract Background 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‐small cell lung cancer (NSCLC) patients receiving definitive concurrent chemoradiation therapy (CCRT). Methods 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‐attenuation 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 ≥3 (≥GR3) RP. Results RP was identified in 68 patients (73.9%), with nine patients (10.9%) experiencing ≥GR3 RP. Univariable logistic regression analysis identified excess kurtosis and high‐attenuation area (HAA)_volume (cc) as significantly associated with ≥GR3 RP. Multivariable logistic regression analysis showed that the combined use of imaging features and clinical factors (forced expiratory volume in 1 second [FEV1], forced vital capacity [FVC], and CHEMO regimen) demonstrated the best performance (area under the receiver operating characteristic curve = 0.924) in predicting ≥GR3 RP. Conclusion 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.https://doi.org/10.1111/1759-7714.15156chronic obstructive pulmonary diseaseconcurrent chemoradiation therapyinterstitial lung diseasepredictive modelradiation pneumonitis |
| spellingShingle | Ye Chan An Jong Hoon Kim Jae Myung Noh Kyung Mi Yang You Jin Oh Sung Goo Park Hong Ryul Pyo Ho Yun Lee Quantification of diffuse parenchymal lung disease in non‐small cell lung cancer patients with definitive concurrent chemoradiation therapy for predicting radiation pneumonitis Thoracic Cancer chronic obstructive pulmonary disease concurrent chemoradiation therapy interstitial lung disease predictive model radiation pneumonitis |
| title | Quantification of diffuse parenchymal lung disease in non‐small cell lung cancer patients with definitive concurrent chemoradiation therapy for predicting radiation pneumonitis |
| title_full | Quantification of diffuse parenchymal lung disease in non‐small cell lung cancer patients with definitive concurrent chemoradiation therapy for predicting radiation pneumonitis |
| title_fullStr | Quantification of diffuse parenchymal lung disease in non‐small cell lung cancer patients with definitive concurrent chemoradiation therapy for predicting radiation pneumonitis |
| title_full_unstemmed | Quantification of diffuse parenchymal lung disease in non‐small cell lung cancer patients with definitive concurrent chemoradiation therapy for predicting radiation pneumonitis |
| title_short | Quantification of diffuse parenchymal lung disease in non‐small cell lung cancer patients with definitive concurrent chemoradiation therapy for predicting radiation pneumonitis |
| title_sort | quantification of diffuse parenchymal lung disease in non small cell lung cancer patients with definitive concurrent chemoradiation therapy for predicting radiation pneumonitis |
| topic | chronic obstructive pulmonary disease concurrent chemoradiation therapy interstitial lung disease predictive model radiation pneumonitis |
| url | https://doi.org/10.1111/1759-7714.15156 |
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