| |  Online-Ressource |
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| Verfasst von: | Mühlbauer, Julia [VerfasserIn]  |
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| | Egen, Luisa [VerfasserIn] |
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| | Kowalewski, Karl-Friedrich [VerfasserIn] |
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| | Grilli, Maurizio [VerfasserIn] |
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| | Walach, Margarete [VerfasserIn] |
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| | Westhoff, Niklas Christian [VerfasserIn] |
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| | Nuhn, Philipp [VerfasserIn] |
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| | Kriegmair, Maximilian [VerfasserIn] |
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| Titel: | Radiomics in renal cell carcinoma |
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| Titelzusatz: | a systematic review and meta-analysis |
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| Verf.angabe: | Julia Mühlbauer, Luisa Egen, Karl-Friedrich Kowalewski, Maurizio Grilli, Margarete T. Walach, Niklas Westhoff, Philipp Nuhn, Fabian C. Laqua, Bettina Baessler and Maximilian C. Kriegmair |
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| E-Jahr: | 2021 |
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| Jahr: | 17 March 2021 |
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| Umfang: | 15 S. |
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| Fussnoten: | Gesehen am 18.03.2021 |
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| Titel Quelle: | Enthalten in: Cancers |
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| Ort Quelle: | Basel : MDPI, 2009 |
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| Jahr Quelle: | 2021 |
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| Band/Heft Quelle: | 13(2021,6) Artikel-Nummer 1348, 15 Seiten |
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| ISSN Quelle: | 2072-6694 |
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| Abstract: | Radiomics may increase the diagnostic accuracy of medical imaging for localized and metastatic RCC (mRCC). A systematic review and meta-analysis was performed. Doing so, we comprehensively searched literature databases until May 2020. Studies investigating the diagnostic value of radiomics in differentiation of localized renal tumors and assessment of treatment response to ST in mRCC were included and assessed with respect to their quality using the radiomics quality score (RQS). A total of 113 out of 1098 identified studies met the criteria and were included in qualitative synthesis. Median RQS of all studies was 13.9% (5.0 points, IQR 0.25-7.0 points), and RQS increased over time. Thirty studies were included into the quantitative synthesis: For distinguishing angiomyolipoma, oncocytoma or unspecified benign tumors from RCC, the random effects model showed a log odds ratio (OR) of 2.89 (95%-CI 2.40-3.39, p < 0.001), 3.08 (95%-CI 2.09-4.06, p < 0.001) and 3.57 (95%-CI 2.69-4.45, p < 0.001), respectively. For the general discrimination of benign tumors from RCC log OR was 3.17 (95%-CI 2.73-3.62, p < 0.001). Inhomogeneity of the available studies assessing treatment response in mRCC prevented any meaningful meta-analysis. The application of radiomics seems promising for discrimination of renal tumor dignity. Shared data and open science may assist in improving reproducibility of future studies. |
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| DOI: | doi:10.3390/cancers13061348 |
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| URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.
Volltext: https://doi.org/10.3390/cancers13061348 |
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| | Volltext: https://www.mdpi.com/2072-6694/13/6/1348 |
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| | DOI: https://doi.org/10.3390/cancers13061348 |
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| Datenträger: | Online-Ressource |
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| Sprache: | eng |
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| Sach-SW: | computed tomography |
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| | machine learning |
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| | magnetic resonance imaging |
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| | radiomics |
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| | renal cell carcinoma |
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| K10plus-PPN: | 1751720594 |
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| Verknüpfungen: | → Zeitschrift |
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Radiomics in renal cell carcinoma / Mühlbauer, Julia [VerfasserIn]; 17 March 2021 (Online-Ressource)
