Multiparametric Evaluation of Radiomics Features and Dual-Energy CT Iodine Maps for Discrimination and Outcome Prediction of Thymic Masses
Copyright © 2023 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved..
RATIONALE AND OBJECTIVES: To investigate the diagnostic value of radiomics features and dual-source dual-energy CT (DECT) based material decomposition in differentiating low-risk thymomas, high-risk thymomas, and thymic carcinomas.
MATERIALS AND METHODS: This retrospective study included 32 patients (16 males, mean age 66 ± 14 years) with pathologically confirmed thymic masses who underwent contrast-enhanced DECT between 10/2014 and 01/2023. Two experienced readers evaluated all patients regarding conventional radiomics features, as well as DECT-based features, including attenuation (HU), iodine density (mg/mL), and fat fraction (%). Data comparisons were performed using analysis of variance and chi-square statistic tests. Receiver operating characteristic curve analysis and Cox-regression tests were used to discriminate between low-risk/high-risk thymomas and thymic carcinomas.
RESULTS: Of the 32 thymic tumors, 12 (38%) were low-risk thymomas, 11 (34%) were high-risk thymomas, and 9 (28%) were thymic carcinomas. Values differed significantly between low-risk thymoma, high-risk thymoma, and thymic carcinoma regarding DECT-based features (p ≤ 0.023) and 30 radiomics features (p ≤ 0.037). The area under the curve to differentiate between low-risk/high-risk thymomas and thymic cancer was 0.998 (95% CI, 0.915-1.000; p < 0.001) for the combination of DECT imaging parameters and radiomics features, yielding a sensitivity of 100% and specificity of 96%. During a follow-up of 60 months (IQR, 35-60 months), the multiparametric approach including radiomics features, DECT parameters, and clinical parameters showed an excellent prognostic power to predict all-cause mortality (c-index = 0.978 [95% CI, 0.958-0.998], p = 0.003).
CONCLUSION: A multiparametric approach including conventional radiomics features and DECT-based features facilitates accurate, non-invasive discrimination between low-risk/high-risk thymomas and thymic carcinomas.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:30 |
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| Enthalten in: |
Academic radiology - 30(2023), 12 vom: 30. Dez., Seite 3010-3021 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Mahmoudi, Scherwin [VerfasserIn] |
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| Links: |
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| Themen: |
9679TC07X4 |
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| Anmerkungen: |
Date Completed 01.12.2023 Date Revised 04.12.2023 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.acra.2023.03.034 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM356093816 |
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| 100 | 1 | |a Mahmoudi, Scherwin |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Multiparametric Evaluation of Radiomics Features and Dual-Energy CT Iodine Maps for Discrimination and Outcome Prediction of Thymic Masses |
| 264 | 1 | |c 2023 | |
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| 500 | |a Date Completed 01.12.2023 | ||
| 500 | |a Date Revised 04.12.2023 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2023 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved. | ||
| 520 | |a RATIONALE AND OBJECTIVES: To investigate the diagnostic value of radiomics features and dual-source dual-energy CT (DECT) based material decomposition in differentiating low-risk thymomas, high-risk thymomas, and thymic carcinomas | ||
| 520 | |a MATERIALS AND METHODS: This retrospective study included 32 patients (16 males, mean age 66 ± 14 years) with pathologically confirmed thymic masses who underwent contrast-enhanced DECT between 10/2014 and 01/2023. Two experienced readers evaluated all patients regarding conventional radiomics features, as well as DECT-based features, including attenuation (HU), iodine density (mg/mL), and fat fraction (%). Data comparisons were performed using analysis of variance and chi-square statistic tests. Receiver operating characteristic curve analysis and Cox-regression tests were used to discriminate between low-risk/high-risk thymomas and thymic carcinomas | ||
| 520 | |a RESULTS: Of the 32 thymic tumors, 12 (38%) were low-risk thymomas, 11 (34%) were high-risk thymomas, and 9 (28%) were thymic carcinomas. Values differed significantly between low-risk thymoma, high-risk thymoma, and thymic carcinoma regarding DECT-based features (p ≤ 0.023) and 30 radiomics features (p ≤ 0.037). The area under the curve to differentiate between low-risk/high-risk thymomas and thymic cancer was 0.998 (95% CI, 0.915-1.000; p < 0.001) for the combination of DECT imaging parameters and radiomics features, yielding a sensitivity of 100% and specificity of 96%. During a follow-up of 60 months (IQR, 35-60 months), the multiparametric approach including radiomics features, DECT parameters, and clinical parameters showed an excellent prognostic power to predict all-cause mortality (c-index = 0.978 [95% CI, 0.958-0.998], p = 0.003) | ||
| 520 | |a CONCLUSION: A multiparametric approach including conventional radiomics features and DECT-based features facilitates accurate, non-invasive discrimination between low-risk/high-risk thymomas and thymic carcinomas | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Artificial intelligence | |
| 650 | 4 | |a Iodine | |
| 650 | 4 | |a Mediastinal neoplasm | |
| 650 | 4 | |a Mediastinum | |
| 650 | 4 | |a Multidetector computed tomography | |
| 650 | 4 | |a Thymoma | |
| 650 | 7 | |a Iodine |2 NLM | |
| 650 | 7 | |a 9679TC07X4 |2 NLM | |
| 700 | 1 | |a Gruenewald, Leon D |e verfasserin |4 aut | |
| 700 | 1 | |a Eichler, Katrin |e verfasserin |4 aut | |
| 700 | 1 | |a Althoff, Friederike C |e verfasserin |4 aut | |
| 700 | 1 | |a Martin, Simon S |e verfasserin |4 aut | |
| 700 | 1 | |a Bernatz, Simon |e verfasserin |4 aut | |
| 700 | 1 | |a Booz, Christian |e verfasserin |4 aut | |
| 700 | 1 | |a Yel, Ibrahim |e verfasserin |4 aut | |
| 700 | 1 | |a Kinzler, Maximilian N |e verfasserin |4 aut | |
| 700 | 1 | |a Ziegengeist, Nicole Suarez |e verfasserin |4 aut | |
| 700 | 1 | |a Torgashov, Katerina |e verfasserin |4 aut | |
| 700 | 1 | |a Mohammed, Hanin |e verfasserin |4 aut | |
| 700 | 1 | |a Geyer, Tobias |e verfasserin |4 aut | |
| 700 | 1 | |a Scholtz, Jan-Erik |e verfasserin |4 aut | |
| 700 | 1 | |a Hammerstingl, Renate M |e verfasserin |4 aut | |
| 700 | 1 | |a Weber, Christophe |e verfasserin |4 aut | |
| 700 | 1 | |a Hardt, Stefan E |e verfasserin |4 aut | |
| 700 | 1 | |a Sommer, Christof M |e verfasserin |4 aut | |
| 700 | 1 | |a Gruber-Rouh, Tatjana |e verfasserin |4 aut | |
| 700 | 1 | |a Leistner, David M |e verfasserin |4 aut | |
| 700 | 1 | |a Vogl, Thomas J |e verfasserin |4 aut | |
| 700 | 1 | |a Koch, Vitali |e verfasserin |4 aut | |
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