{"title":"基于磁共振成像的放射特征来确定肾上腺库欣综合征。","authors":"Ferhat Can Piskin, Gamze Akkus, Sevinc Puren Yucel, Bisar Akbas, Fulya Odabası","doi":"10.5114/pjr.2023.124435","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>The aim of this study was to develop radiomics signature-based magnetic resonance imaging (MRI) to determine adrenal Cushing's syndrome (ACS) in adrenal incidentalomas (AI).</p><p><strong>Material and methods: </strong>A total of 50 patients with AI were included in this study. The patients were grouped as nonfunctional adrenal incidentaloma (NFAI) and ACS. The lesions were segmented on unenhanced T1-weighted (T1W) in-phase (IP) and opposed-phase (OP) as well as on T2-weighted (T2-W) 3-Tesla MRIs. The LASSO regression model was used for the selection of potential predictors from 111 texture features for each sequence. The radiomics scores were compared between the groups.</p><p><strong>Results: </strong>The median radiomics score in T1W-Op for the NFAI and ACS were -1.17 and -0.17, respectively (<i>p</i> < 0.001). Patients with ACS had significantly higher radiomics scores than NFAI patients in all phases (<i>p</i> < 0.001 for all). The AUCs for radiomics scores in T1W-Op, T1W-Ip, and T2W were 0.862 (95% CI: 0.742-0.983), 0.892 (95% CI: 0.774-0.999), and 0.994 (95% CI: 0.982-0.999), respectively.</p><p><strong>Conclusion: </strong>The developed MRI-based radiomic scores can yield high AUCs for prediction of ACS.</p>","PeriodicalId":47128,"journal":{"name":"Polish Journal of Radiology","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/2f/12/PJR-88-50002.PMC9907166.pdf","citationCount":"0","resultStr":"{\"title\":\"A radiomic signature based on magnetic resonance imaging to determine adrenal Cushing's syndrome.\",\"authors\":\"Ferhat Can Piskin, Gamze Akkus, Sevinc Puren Yucel, Bisar Akbas, Fulya Odabası\",\"doi\":\"10.5114/pjr.2023.124435\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>The aim of this study was to develop radiomics signature-based magnetic resonance imaging (MRI) to determine adrenal Cushing's syndrome (ACS) in adrenal incidentalomas (AI).</p><p><strong>Material and methods: </strong>A total of 50 patients with AI were included in this study. The patients were grouped as nonfunctional adrenal incidentaloma (NFAI) and ACS. The lesions were segmented on unenhanced T1-weighted (T1W) in-phase (IP) and opposed-phase (OP) as well as on T2-weighted (T2-W) 3-Tesla MRIs. The LASSO regression model was used for the selection of potential predictors from 111 texture features for each sequence. The radiomics scores were compared between the groups.</p><p><strong>Results: </strong>The median radiomics score in T1W-Op for the NFAI and ACS were -1.17 and -0.17, respectively (<i>p</i> < 0.001). Patients with ACS had significantly higher radiomics scores than NFAI patients in all phases (<i>p</i> < 0.001 for all). The AUCs for radiomics scores in T1W-Op, T1W-Ip, and T2W were 0.862 (95% CI: 0.742-0.983), 0.892 (95% CI: 0.774-0.999), and 0.994 (95% CI: 0.982-0.999), respectively.</p><p><strong>Conclusion: </strong>The developed MRI-based radiomic scores can yield high AUCs for prediction of ACS.</p>\",\"PeriodicalId\":47128,\"journal\":{\"name\":\"Polish Journal of Radiology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/2f/12/PJR-88-50002.PMC9907166.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Polish Journal of Radiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5114/pjr.2023.124435\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Polish Journal of Radiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5114/pjr.2023.124435","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
A radiomic signature based on magnetic resonance imaging to determine adrenal Cushing's syndrome.
Purpose: The aim of this study was to develop radiomics signature-based magnetic resonance imaging (MRI) to determine adrenal Cushing's syndrome (ACS) in adrenal incidentalomas (AI).
Material and methods: A total of 50 patients with AI were included in this study. The patients were grouped as nonfunctional adrenal incidentaloma (NFAI) and ACS. The lesions were segmented on unenhanced T1-weighted (T1W) in-phase (IP) and opposed-phase (OP) as well as on T2-weighted (T2-W) 3-Tesla MRIs. The LASSO regression model was used for the selection of potential predictors from 111 texture features for each sequence. The radiomics scores were compared between the groups.
Results: The median radiomics score in T1W-Op for the NFAI and ACS were -1.17 and -0.17, respectively (p < 0.001). Patients with ACS had significantly higher radiomics scores than NFAI patients in all phases (p < 0.001 for all). The AUCs for radiomics scores in T1W-Op, T1W-Ip, and T2W were 0.862 (95% CI: 0.742-0.983), 0.892 (95% CI: 0.774-0.999), and 0.994 (95% CI: 0.982-0.999), respectively.
Conclusion: The developed MRI-based radiomic scores can yield high AUCs for prediction of ACS.
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