{"title":"计算机断层显像衍生心肌放射组学检测严重主动脉瓣狭窄患者甲状腺素淀粉样变性。","authors":"Alexios S Antonopoulos, Ioannis Panagiotopoulos, Konstantinos Karampinos, Konstantinos Spargias, Charalampos Papastamos, Theodoros Tsampras, Nikolaos Axypolitos, Spyridon Simantiris, Georgios Benetos, Nikolaos Ktenopoulos, Panagiotis Kanatas, Maria Koutelou, Konstantinos Toutouzas, Marios Ioannides, Christos Eftychiou, Christos Mourmouris, Thomas Vrachliotis, Charalambos Antoniades, Konstantinos Tsioufis, Charalambos Vlachopoulos","doi":"10.1080/13506129.2025.2486072","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>We explored the value of myocardial radiomics by computed tomography angiography (CTA) for detection of transthyretin amyloidosis cardiomyopathy (ATTR-CM).</p><p><strong>Methods: </strong>The study included 589 patients with aortic stenosis and CTA datasets. Radiomics were extracted from LV myocardium. Arm 1 (<i>n</i> = 400) served for method optimisation and removal of redundant features. In Arm 2 (<i>n</i> = 30), we identified radiomics associated with extracellular volume by CT (ECV<sub>CT</sub>); in Arm 3 (<i>n</i> = 159), radiomics were compared in patients with/without positive bone scintigraphy scan (training cohort, <i>n</i> = 84; validation cohort, <i>n</i> = 75) to build a radiomic signature for ATTR-CM.</p><p><strong>Results: </strong>In Arm 1, unsupervised clustering of patients based on radiomics was associated with significant differences in patients' clinical profile among clusters. In Arm 2, we constructed a radiomic-based ECV (correlation with ECV<sub>CT</sub>: rho = .78, <i>p</i> = 1.2 x 10<sup>-6</sup>) with excellent diagnostic accuracy for high ECV<sub>CT</sub> (AUC = .925, 95%CI: .825-1.000, <i>p</i> = .0002). In Arm 3, a radiomic score (AmyloidRS) had good performance for ATTR-CM detection in the training (c-index .88, 95%CI: .80-.95) and validation cohort (c-index .84, 95%CI: .69-.98). When combined with clinical features, AmyloidRS maximised diagnostic accuracy for ATTR (kappa: .894, balanced accuracy .984).</p><p><strong>Conclusions: </strong>We present a radiomic method for myocardial tissue characterisation in patients with severe aortic stenosis which enables ATTR-CM detection from standard CTA scans.</p>","PeriodicalId":50964,"journal":{"name":"Amyloid-Journal of Protein Folding Disorders","volume":" ","pages":"1-12"},"PeriodicalIF":5.2000,"publicationDate":"2025-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Computed tomography-derived myocardial radiomics for detection of transthyretin amyloidosis in patients with severe aortic stenosis.\",\"authors\":\"Alexios S Antonopoulos, Ioannis Panagiotopoulos, Konstantinos Karampinos, Konstantinos Spargias, Charalampos Papastamos, Theodoros Tsampras, Nikolaos Axypolitos, Spyridon Simantiris, Georgios Benetos, Nikolaos Ktenopoulos, Panagiotis Kanatas, Maria Koutelou, Konstantinos Toutouzas, Marios Ioannides, Christos Eftychiou, Christos Mourmouris, Thomas Vrachliotis, Charalambos Antoniades, Konstantinos Tsioufis, Charalambos Vlachopoulos\",\"doi\":\"10.1080/13506129.2025.2486072\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>We explored the value of myocardial radiomics by computed tomography angiography (CTA) for detection of transthyretin amyloidosis cardiomyopathy (ATTR-CM).</p><p><strong>Methods: </strong>The study included 589 patients with aortic stenosis and CTA datasets. Radiomics were extracted from LV myocardium. Arm 1 (<i>n</i> = 400) served for method optimisation and removal of redundant features. In Arm 2 (<i>n</i> = 30), we identified radiomics associated with extracellular volume by CT (ECV<sub>CT</sub>); in Arm 3 (<i>n</i> = 159), radiomics were compared in patients with/without positive bone scintigraphy scan (training cohort, <i>n</i> = 84; validation cohort, <i>n</i> = 75) to build a radiomic signature for ATTR-CM.</p><p><strong>Results: </strong>In Arm 1, unsupervised clustering of patients based on radiomics was associated with significant differences in patients' clinical profile among clusters. In Arm 2, we constructed a radiomic-based ECV (correlation with ECV<sub>CT</sub>: rho = .78, <i>p</i> = 1.2 x 10<sup>-6</sup>) with excellent diagnostic accuracy for high ECV<sub>CT</sub> (AUC = .925, 95%CI: .825-1.000, <i>p</i> = .0002). In Arm 3, a radiomic score (AmyloidRS) had good performance for ATTR-CM detection in the training (c-index .88, 95%CI: .80-.95) and validation cohort (c-index .84, 95%CI: .69-.98). When combined with clinical features, AmyloidRS maximised diagnostic accuracy for ATTR (kappa: .894, balanced accuracy .984).</p><p><strong>Conclusions: </strong>We present a radiomic method for myocardial tissue characterisation in patients with severe aortic stenosis which enables ATTR-CM detection from standard CTA scans.</p>\",\"PeriodicalId\":50964,\"journal\":{\"name\":\"Amyloid-Journal of Protein Folding Disorders\",\"volume\":\" \",\"pages\":\"1-12\"},\"PeriodicalIF\":5.2000,\"publicationDate\":\"2025-04-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Amyloid-Journal of Protein Folding Disorders\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/13506129.2025.2486072\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Amyloid-Journal of Protein Folding Disorders","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/13506129.2025.2486072","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Computed tomography-derived myocardial radiomics for detection of transthyretin amyloidosis in patients with severe aortic stenosis.
Background: We explored the value of myocardial radiomics by computed tomography angiography (CTA) for detection of transthyretin amyloidosis cardiomyopathy (ATTR-CM).
Methods: The study included 589 patients with aortic stenosis and CTA datasets. Radiomics were extracted from LV myocardium. Arm 1 (n = 400) served for method optimisation and removal of redundant features. In Arm 2 (n = 30), we identified radiomics associated with extracellular volume by CT (ECVCT); in Arm 3 (n = 159), radiomics were compared in patients with/without positive bone scintigraphy scan (training cohort, n = 84; validation cohort, n = 75) to build a radiomic signature for ATTR-CM.
Results: In Arm 1, unsupervised clustering of patients based on radiomics was associated with significant differences in patients' clinical profile among clusters. In Arm 2, we constructed a radiomic-based ECV (correlation with ECVCT: rho = .78, p = 1.2 x 10-6) with excellent diagnostic accuracy for high ECVCT (AUC = .925, 95%CI: .825-1.000, p = .0002). In Arm 3, a radiomic score (AmyloidRS) had good performance for ATTR-CM detection in the training (c-index .88, 95%CI: .80-.95) and validation cohort (c-index .84, 95%CI: .69-.98). When combined with clinical features, AmyloidRS maximised diagnostic accuracy for ATTR (kappa: .894, balanced accuracy .984).
Conclusions: We present a radiomic method for myocardial tissue characterisation in patients with severe aortic stenosis which enables ATTR-CM detection from standard CTA scans.
期刊介绍：
Amyloid: the Journal of Protein Folding Disorders is dedicated to the study of all aspects of the protein groups and associated disorders that are classified as the amyloidoses as well as other disorders associated with abnormal protein folding. The journals major focus points are:
etiology,
pathogenesis,
histopathology,
chemical structure,
nature of fibrillogenesis;
whilst also publishing papers on the basic and chemical genetic aspects of many of these disorders.
Amyloid is recognised as one of the leading publications on amyloid protein classifications and the associated disorders, as well as clinical studies on all aspects of amyloid related neurodegenerative diseases and major clinical studies on inherited amyloidosis, especially those related to transthyretin. The Journal also publishes book reviews, meeting reports, editorials, thesis abstracts, review articles and symposia in the various areas listed above.
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