Development of Imaging Complexity Biomarkers for Prediction of Symptomatic Radiation Pneumonitis in Patients with Non-Small Cell Lung Cancer, Focusing on Underlying Lung Disease
<b>Objectives:</b> We aimed to develop imaging biomarkers to predict radiation pneumonitis (RP) in non-small cell lung cancer (NSCLC) patients undergoing thoracic radiotherapy. We hypothesized that measuring morphometric complexity in the lung using simulation computed tomography may pro...
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2024-11-01
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| author | Jeongeun Hwang Hakyoung Kim Joon-Young Moon Sun Myung Kim Dae Sik Yang |
| author_facet | Jeongeun Hwang Hakyoung Kim Joon-Young Moon Sun Myung Kim Dae Sik Yang |
| author_sort | Jeongeun Hwang |
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| description | <b>Objectives:</b> We aimed to develop imaging biomarkers to predict radiation pneumonitis (RP) in non-small cell lung cancer (NSCLC) patients undergoing thoracic radiotherapy. We hypothesized that measuring morphometric complexity in the lung using simulation computed tomography may provide objective imaging biomarkers for lung parenchyma integrity, potentially forecasting the risk of RP. <b>Materials and Methods:</b> A retrospective study was performed on medical records of 175 patients diagnosed with NSCLC who had received thoracic radiotherapy. Three indices were utilized to measure the morphometric complexity of the lung parenchyma: box-counting fractal dimension, lacunarity, and minimum spanning tree (MST) fractal dimension. Patients were dichotomized into two groups at median values. Cox proportional hazard models were constructed to estimate the hazard ratios for grade ≥ 2 or grade ≥ 3 RP. <b>Results and Conclusions:</b> We found significant associations between lung parenchymal morphometric complexity and RP incidence. In univariate Cox-proportional hazard analysis, patients with a lower MST fractal dimension had a significantly higher hazard ratio of 2.296 (95% CI: 1.348–3.910) for grade ≥ 2 RP. When adjusted for age, sex, smoking status, category of the underlying lung disease, category of radiotherapy technique, clinical stage, histology, and DLCO, patients with a lower MST fractal dimension showed a significantly higher hazard ratio of 3.292 (95% CI: 1.722–6.294) for grade ≥ 2 RP and 7.952 (95% CI: 1.722 36.733) for grade ≥ 3 RP than those with a higher MST fractal dimension. Patients with lower lacunarity exhibited a significantly lower hazard ratio of 0.091 (95% CI: 0.015–0.573) for grade ≥ 3 RP in the adjusted model. We speculated that the lung tissue integrity is captured by morphometric complexity measures, particularly by the MST fractal dimension. We suggest the MST fractal dimension as an imaging biomarker for predicting the occurrence of symptomatic RP after thoracic radiotherapy. |
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| institution | Kabale University |
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| language | English |
| publishDate | 2024-11-01 |
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| spelling | doaj-art-a78bb9ed17dc4ad89b0718bd7c38f2bb2024-11-26T18:10:39ZengMDPI AGLife2075-17292024-11-011411149710.3390/life14111497Development of Imaging Complexity Biomarkers for Prediction of Symptomatic Radiation Pneumonitis in Patients with Non-Small Cell Lung Cancer, Focusing on Underlying Lung DiseaseJeongeun Hwang0Hakyoung Kim1Joon-Young Moon2Sun Myung Kim3Dae Sik Yang4Department of Medical IT Engineering, College of Medical Sciences, Soonchunhyang University, Asan-si 31538, Republic of KoreaDepartments of Radiation Oncology, Korea University Guro Hospital, Korea University College of Medicine, Seoul 08308, Republic of KoreaCenter for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon-si 16419, Republic of KoreaDepartments of Radiation Oncology, Korea University Guro Hospital, Korea University College of Medicine, Seoul 08308, Republic of KoreaDepartments of Radiation Oncology, Korea University Guro Hospital, Korea University College of Medicine, Seoul 08308, Republic of Korea<b>Objectives:</b> We aimed to develop imaging biomarkers to predict radiation pneumonitis (RP) in non-small cell lung cancer (NSCLC) patients undergoing thoracic radiotherapy. We hypothesized that measuring morphometric complexity in the lung using simulation computed tomography may provide objective imaging biomarkers for lung parenchyma integrity, potentially forecasting the risk of RP. <b>Materials and Methods:</b> A retrospective study was performed on medical records of 175 patients diagnosed with NSCLC who had received thoracic radiotherapy. Three indices were utilized to measure the morphometric complexity of the lung parenchyma: box-counting fractal dimension, lacunarity, and minimum spanning tree (MST) fractal dimension. Patients were dichotomized into two groups at median values. Cox proportional hazard models were constructed to estimate the hazard ratios for grade ≥ 2 or grade ≥ 3 RP. <b>Results and Conclusions:</b> We found significant associations between lung parenchymal morphometric complexity and RP incidence. In univariate Cox-proportional hazard analysis, patients with a lower MST fractal dimension had a significantly higher hazard ratio of 2.296 (95% CI: 1.348–3.910) for grade ≥ 2 RP. When adjusted for age, sex, smoking status, category of the underlying lung disease, category of radiotherapy technique, clinical stage, histology, and DLCO, patients with a lower MST fractal dimension showed a significantly higher hazard ratio of 3.292 (95% CI: 1.722–6.294) for grade ≥ 2 RP and 7.952 (95% CI: 1.722 36.733) for grade ≥ 3 RP than those with a higher MST fractal dimension. Patients with lower lacunarity exhibited a significantly lower hazard ratio of 0.091 (95% CI: 0.015–0.573) for grade ≥ 3 RP in the adjusted model. We speculated that the lung tissue integrity is captured by morphometric complexity measures, particularly by the MST fractal dimension. We suggest the MST fractal dimension as an imaging biomarker for predicting the occurrence of symptomatic RP after thoracic radiotherapy.https://www.mdpi.com/2075-1729/14/11/1497lung cancerradiotherapyradiation pneumonitisbiomarkerlung disease |
| spellingShingle | Jeongeun Hwang Hakyoung Kim Joon-Young Moon Sun Myung Kim Dae Sik Yang Development of Imaging Complexity Biomarkers for Prediction of Symptomatic Radiation Pneumonitis in Patients with Non-Small Cell Lung Cancer, Focusing on Underlying Lung Disease Life lung cancer radiotherapy radiation pneumonitis biomarker lung disease |
| title | Development of Imaging Complexity Biomarkers for Prediction of Symptomatic Radiation Pneumonitis in Patients with Non-Small Cell Lung Cancer, Focusing on Underlying Lung Disease |
| title_full | Development of Imaging Complexity Biomarkers for Prediction of Symptomatic Radiation Pneumonitis in Patients with Non-Small Cell Lung Cancer, Focusing on Underlying Lung Disease |
| title_fullStr | Development of Imaging Complexity Biomarkers for Prediction of Symptomatic Radiation Pneumonitis in Patients with Non-Small Cell Lung Cancer, Focusing on Underlying Lung Disease |
| title_full_unstemmed | Development of Imaging Complexity Biomarkers for Prediction of Symptomatic Radiation Pneumonitis in Patients with Non-Small Cell Lung Cancer, Focusing on Underlying Lung Disease |
| title_short | Development of Imaging Complexity Biomarkers for Prediction of Symptomatic Radiation Pneumonitis in Patients with Non-Small Cell Lung Cancer, Focusing on Underlying Lung Disease |
| title_sort | development of imaging complexity biomarkers for prediction of symptomatic radiation pneumonitis in patients with non small cell lung cancer focusing on underlying lung disease |
| topic | lung cancer radiotherapy radiation pneumonitis biomarker lung disease |
| url | https://www.mdpi.com/2075-1729/14/11/1497 |
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