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Title: | Radiomics analysis in characterization of salivary gland tumors on MRI : a systematic review | Authors: | Mao, KJ Wong, LM Zhang, RL So, TY Shan, ZY Hung, KF Ai, QYH |
Issue Date: | Oct-2023 | Source: | Cancers, Oct. 2023, v. 15, no. 20, 4918 | Abstract: | Simple Summary: This review systematically evaluated radiomics analysis procedures for characterizing salivary gland tumors (SGTs) on magnetic resonance imaging (MRI). Radiomics analysis showed potential for characterizing SGTs on MRI, but its clinical application is limited due to complex procedures and a lack of standardized methods. This review summarized radiomics analysis procedures, focusing on reported methodologies and performances, and proposed potential standards for the procedures for radiomics analysis, which may benefit further developments of radiomics analysis in characterizing SGTs on MRI. Abstract: Radiomics analysis can potentially characterize salivary gland tumors (SGTs) on magnetic resonance imaging (MRI). The procedures for radiomics analysis were various, and no consistent performances were reported. This review evaluated the methodologies and performances of studies using radiomics analysis to characterize SGTs on MRI. We systematically reviewed studies published until July 2023, which employed radiomics analysis to characterize SGTs on MRI. In total, 14 of 98 studies were eligible. Each study examined 23-334 benign and 8-56 malignant SGTs. Least absolute shrinkage and selection operator (LASSO) was the most common feature selection method (in eight studies). Eleven studies confirmed the stability of selected features using cross-validation or bootstrap. Nine classifiers were used to build models that achieved area under the curves (AUCs) of 0.74 to 1.00 for characterizing benign and malignant SGTs and 0.80 to 0.96 for characterizing pleomorphic adenomas and Warthin's tumors. Performances were validated using cross-validation, internal, and external datasets in four, six, and two studies, respectively. No single feature consistently appeared in the final models across the studies. No standardized procedure was used for radiomics analysis in characterizing SGTs on MRIs, and various models were proposed. The need for a standard procedure for radiomics analysis is emphasized. |
Keywords: | Radiomics Texture analysis Salivary glands tumor Magnetic resonance imaging Systematic review |
Publisher: | MDPI AG | Journal: | Cancers | EISSN: | 2072-6694 | DOI: | 10.3390/cancers15204918 | Rights: | © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). The following publication Mao K, Wong LM, Zhang R, So TY, Shan Z, Hung KF, Ai QYH. Radiomics Analysis in Characterization of Salivary Gland Tumors on MRI: A Systematic Review. Cancers. 2023; 15(20):4918 is available at https://dx.doi.org/10.3390/cancers15204918. |
Appears in Collections: | Journal/Magazine Article |
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cancers-15-04918-v2.pdf | 1.27 MB | Adobe PDF | View/Open |
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