Diagnostic value of CT radiomics and clinical features in differentiating focal organizing pneumonia from peripheral lung cancer
ObjectiveThis study aimed to evaluate the diagnostic value of computed tomography (CT) radiomics combined with clinical characteristics in differentiating focal organizing pneumonia (FOP) from peripheral lung cancer (PLC).MethodsA total of 60 FOP patients admitted between June 2023 and June 2024 wer...
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Frontiers Media S.A.
2025-06-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2025.1620217/full |
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| author | Weihua Tang Huadong Chen Peijun Liu Yunxuan Zhang Yunxuan Zhang |
| author_facet | Weihua Tang Huadong Chen Peijun Liu Yunxuan Zhang Yunxuan Zhang |
| author_sort | Weihua Tang |
| collection | DOAJ |
| description | ObjectiveThis study aimed to evaluate the diagnostic value of computed tomography (CT) radiomics combined with clinical characteristics in differentiating focal organizing pneumonia (FOP) from peripheral lung cancer (PLC).MethodsA total of 60 FOP patients admitted between June 2023 and June 2024 were included as the FOP group, while 60 PLC patients were assigned to the PLC group. General clinical and imaging data were collected for both groups. Logistic regression analysis was employed to identify independent risk factors for FOP. Radiomics features were extracted from CT images of FOP patients, and the Lasso method was used to select key radiomics features and calculate CT radiomics scores. The diagnostic performance of CT radiomics and clinical characteristics for FOP was assessed using receiver operating characteristic (ROC) curve analysis.ResultsThere were no statistically significant differences in age, gender, lung tissue boundary, pleural indentation sign, vascular convergence sign, pleural traction sign, or bronchial air sign between the FOP and PLC groups (P > 0.05). However, significant differences were observed in pleural adhesion, lesion location in the outer lung zone, liquefaction necrosis, cavity formation, and spiculation (P < 0.05). Logistic regression analysis identified pleural adhesion, lesion location in the outer lung zone, liquefaction necrosis, cavity formation, and long spiculation as independent risk factors for FOP (P < 0.05). ROC curve analysis demonstrated that the area under the curve (AUC) for clinical characteristics and CT radiomics in diagnosing FOP were 0.895 and 0.859, respectively. Notably, the AUC for the combined model integrating CT radiomics and clinical characteristics was 0.955, which was significantly higher than that of either approach alone (P < 0.05).ConclusionPleural adhesion, lesion location in the outer lung zone, liquefaction necrosis, cavity formation, and long spiculation are key risk factors for FOP. Both CT radiomics and clinical characteristics can aid in the differentiation of FOP from PLC, and their combination significantly enhances diagnostic accuracy. |
| format | Article |
| id | doaj-art-aee5dc1a91ee4bf39287ffe90ca25a2c |
| institution | Matheson Library |
| issn | 2234-943X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Oncology |
| spelling | doaj-art-aee5dc1a91ee4bf39287ffe90ca25a2c2025-06-25T04:10:20ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2025-06-011510.3389/fonc.2025.16202171620217Diagnostic value of CT radiomics and clinical features in differentiating focal organizing pneumonia from peripheral lung cancerWeihua Tang0Huadong Chen1Peijun Liu2Yunxuan Zhang3Yunxuan Zhang4Graduate Training Base, Jinzhou Medical University (Renmin Hospital of Wuhan University), Wuhan, Hubei, ChinaDepartment of Radiology, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi, ChinaDepartment of Radiology, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi, ChinaGraduate Training Base, Jinzhou Medical University (Renmin Hospital of Wuhan University), Wuhan, Hubei, ChinaDepartment of Radiology, The Second Hospital of Huangshi, Huangshi, ChinaObjectiveThis study aimed to evaluate the diagnostic value of computed tomography (CT) radiomics combined with clinical characteristics in differentiating focal organizing pneumonia (FOP) from peripheral lung cancer (PLC).MethodsA total of 60 FOP patients admitted between June 2023 and June 2024 were included as the FOP group, while 60 PLC patients were assigned to the PLC group. General clinical and imaging data were collected for both groups. Logistic regression analysis was employed to identify independent risk factors for FOP. Radiomics features were extracted from CT images of FOP patients, and the Lasso method was used to select key radiomics features and calculate CT radiomics scores. The diagnostic performance of CT radiomics and clinical characteristics for FOP was assessed using receiver operating characteristic (ROC) curve analysis.ResultsThere were no statistically significant differences in age, gender, lung tissue boundary, pleural indentation sign, vascular convergence sign, pleural traction sign, or bronchial air sign between the FOP and PLC groups (P > 0.05). However, significant differences were observed in pleural adhesion, lesion location in the outer lung zone, liquefaction necrosis, cavity formation, and spiculation (P < 0.05). Logistic regression analysis identified pleural adhesion, lesion location in the outer lung zone, liquefaction necrosis, cavity formation, and long spiculation as independent risk factors for FOP (P < 0.05). ROC curve analysis demonstrated that the area under the curve (AUC) for clinical characteristics and CT radiomics in diagnosing FOP were 0.895 and 0.859, respectively. Notably, the AUC for the combined model integrating CT radiomics and clinical characteristics was 0.955, which was significantly higher than that of either approach alone (P < 0.05).ConclusionPleural adhesion, lesion location in the outer lung zone, liquefaction necrosis, cavity formation, and long spiculation are key risk factors for FOP. Both CT radiomics and clinical characteristics can aid in the differentiation of FOP from PLC, and their combination significantly enhances diagnostic accuracy.https://www.frontiersin.org/articles/10.3389/fonc.2025.1620217/fullcomputed tomographyradiomicsfocal organizing pneumoniaperipheral lung cancerclinical features |
| spellingShingle | Weihua Tang Huadong Chen Peijun Liu Yunxuan Zhang Yunxuan Zhang Diagnostic value of CT radiomics and clinical features in differentiating focal organizing pneumonia from peripheral lung cancer Frontiers in Oncology computed tomography radiomics focal organizing pneumonia peripheral lung cancer clinical features |
| title | Diagnostic value of CT radiomics and clinical features in differentiating focal organizing pneumonia from peripheral lung cancer |
| title_full | Diagnostic value of CT radiomics and clinical features in differentiating focal organizing pneumonia from peripheral lung cancer |
| title_fullStr | Diagnostic value of CT radiomics and clinical features in differentiating focal organizing pneumonia from peripheral lung cancer |
| title_full_unstemmed | Diagnostic value of CT radiomics and clinical features in differentiating focal organizing pneumonia from peripheral lung cancer |
| title_short | Diagnostic value of CT radiomics and clinical features in differentiating focal organizing pneumonia from peripheral lung cancer |
| title_sort | diagnostic value of ct radiomics and clinical features in differentiating focal organizing pneumonia from peripheral lung cancer |
| topic | computed tomography radiomics focal organizing pneumonia peripheral lung cancer clinical features |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2025.1620217/full |
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