Three dimensional computed tomography texture analysis of pulmonary lesions : Does radiomics allow differentiation between carcinoma, neuroendocrine tumor and organizing pneumonia?
Copyright © 2023 Elsevier B.V. All rights reserved..
PURPOSE: To investigate whether CT texture analysis allows differentiation between adenocarcinomas, squamous cell carcinomas, carcinoids, small cell lung cancers and organizing pneumonia and between carcinomas and neuroendocrine tumors.
METHOD: This retrospective study included patients 133 patients (30 patients with organizing pneumonia, 30 patients with adenocarcinoma, 30 patients with squamous cell carcinoma, 23 patients with small cell lung cancer, 20 patients with carcinoid), who underwent CT-guided biopsy of the lung and had a corresponding histopathologic diagnosis. Pulmonary lesions were segmented in consensus by two radiologists with and without a threshold of -50HU in three dimensions. Groupwise comparisons were performed to assess for differences between all five above-listed entities and between carcinomas and neuroendocrine tumors.
RESULTS: Pairwise comparisons of the five entities revealed 53 statistically significant texture features when using no HU-threshold and 6 statistically significant features with a threshold of -50HU. The largest AUC (0.818 [95%CI 0.706-0.930]) was found for the feature wavelet-HHH_glszm_SmallAreaEmphasis for discrimination of carcinoid from the other entities when using no HU-threshold. In differentiating neuroendocrine tumors from carcinomas, 173 parameters proved statistically significant when using no HU threshold versus 52 parameters when using a -50HU-threshold. The largest AUC (0.810 [95%CI 0.728-0,893]) was found for the parameter original_glcm_Correlation for discrimination of neuroendocrine tumors from carcinomas when using no HU-threshold.
CONCLUSIONS: CT texture analysis revealed features that differed significantly between malignant pulmonary lesions and organizing pneumonia and between carcinomas and neuroendocrine tumors of the lung. Applying a HU-threshold for segmentation substantially influenced the results of texture analysis.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:165 |
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| Enthalten in: |
European journal of radiology - 165(2023) vom: 03. Aug., Seite 110931 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Adelsmayr, Gabriel [VerfasserIn] |
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| Links: |
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| Themen: |
Humans |
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| Anmerkungen: |
Date Completed 24.07.2023 Date Revised 24.07.2023 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.ejrad.2023.110931 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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NLM35900864X |
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| 100 | 1 | |a Adelsmayr, Gabriel |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Three dimensional computed tomography texture analysis of pulmonary lesions |b Does radiomics allow differentiation between carcinoma, neuroendocrine tumor and organizing pneumonia? |
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| 500 | |a Date Revised 24.07.2023 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2023 Elsevier B.V. All rights reserved. | ||
| 520 | |a PURPOSE: To investigate whether CT texture analysis allows differentiation between adenocarcinomas, squamous cell carcinomas, carcinoids, small cell lung cancers and organizing pneumonia and between carcinomas and neuroendocrine tumors | ||
| 520 | |a METHOD: This retrospective study included patients 133 patients (30 patients with organizing pneumonia, 30 patients with adenocarcinoma, 30 patients with squamous cell carcinoma, 23 patients with small cell lung cancer, 20 patients with carcinoid), who underwent CT-guided biopsy of the lung and had a corresponding histopathologic diagnosis. Pulmonary lesions were segmented in consensus by two radiologists with and without a threshold of -50HU in three dimensions. Groupwise comparisons were performed to assess for differences between all five above-listed entities and between carcinomas and neuroendocrine tumors | ||
| 520 | |a RESULTS: Pairwise comparisons of the five entities revealed 53 statistically significant texture features when using no HU-threshold and 6 statistically significant features with a threshold of -50HU. The largest AUC (0.818 [95%CI 0.706-0.930]) was found for the feature wavelet-HHH_glszm_SmallAreaEmphasis for discrimination of carcinoid from the other entities when using no HU-threshold. In differentiating neuroendocrine tumors from carcinomas, 173 parameters proved statistically significant when using no HU threshold versus 52 parameters when using a -50HU-threshold. The largest AUC (0.810 [95%CI 0.728-0,893]) was found for the parameter original_glcm_Correlation for discrimination of neuroendocrine tumors from carcinomas when using no HU-threshold | ||
| 520 | |a CONCLUSIONS: CT texture analysis revealed features that differed significantly between malignant pulmonary lesions and organizing pneumonia and between carcinomas and neuroendocrine tumors of the lung. Applying a HU-threshold for segmentation substantially influenced the results of texture analysis | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Humans | |
| 650 | 4 | |a Lung neoplasms | |
| 650 | 4 | |a Pneumonia | |
| 650 | 4 | |a Radiographic image interpretation | |
| 650 | 4 | |a Tomography | |
| 650 | 4 | |a X-ray computed | |
| 700 | 1 | |a Janisch, Michael |e verfasserin |4 aut | |
| 700 | 1 | |a Müller, Heimo |e verfasserin |4 aut | |
| 700 | 1 | |a Holzinger, Andreas |e verfasserin |4 aut | |
| 700 | 1 | |a Talakic, Emina |e verfasserin |4 aut | |
| 700 | 1 | |a Janek, Elmar |e verfasserin |4 aut | |
| 700 | 1 | |a Streit, Simon |e verfasserin |4 aut | |
| 700 | 1 | |a Fuchsjäger, Michael |e verfasserin |4 aut | |
| 700 | 1 | |a Schöllnast, Helmut |e verfasserin |4 aut | |
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