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Non-Contrast Cine Cardiac Magnetic Resonance Derived-Radiomics for the Prediction of Left Ventricular Adverse Remodeling in Patients With ST-Segment Elevation Myocardial Infarction.
A, Xin; Liu, Mingliang; Chen, Tong; Chen, Feng; Qian, Geng; Zhang, Ying; Chen, Yundai.
Afiliação
  • A X; Chinese People's Liberation Army General Hospital, Chinese People's Liberation Army Medical School, Beijing, China.
  • Liu M; The Senior Department of Cardiology, the Sixth Medical Center, Chinese People's Liberation Army General Hospital, Beijing, China.
  • Chen T; Nankai University, School of Medicine, Tianjin, Nankai, China.
  • Chen F; Chinese People's Liberation Army General Hospital, Chinese People's Liberation Army Medical School, Beijing, China.
  • Qian G; The Senior Department of Cardiology, the Sixth Medical Center, Chinese People's Liberation Army General Hospital, Beijing, China.
  • Zhang Y; Department of Computer Science, the University of Adelaide, Adelaide, Australia.
  • Chen Y; Chinese People's Liberation Army General Hospital, Chinese People's Liberation Army Medical School, Beijing, China.
Korean J Radiol ; 24(9): 827-837, 2023 09.
Article em En | MEDLINE | ID: mdl-37634638
ABSTRACT

OBJECTIVE:

To investigate the predictive value of radiomics features based on cardiac magnetic resonance (CMR) cine images for left ventricular adverse remodeling (LVAR) after acute ST-segment elevation myocardial infarction (STEMI). MATERIALS AND

METHODS:

We conducted a retrospective, single-center, cohort study involving 244 patients (random-split into 170 and 74 for training and testing, respectively) having an acute STEMI (88.5% males, 57.0 ± 10.3 years of age) who underwent CMR examination at one week and six months after percutaneous coronary intervention. LVAR was defined as a 20% increase in left ventricular end-diastolic volume 6 months after acute STEMI. Radiomics features were extracted from the one-week CMR cine images using the least absolute shrinkage and selection operator regression (LASSO) analysis. The predictive performance of the selected features was evaluated using receiver operating characteristic curve analysis and the area under the curve (AUC).

RESULTS:

Nine radiomics features with non-zero coefficients were included in the LASSO regression of the radiomics score (RAD score). Infarct size (odds ratio [OR] 1.04 (1.00-1.07); P = 0.031) and RAD score (OR 3.43 (2.34-5.28); P < 0.001) were independent predictors of LVAR. The RAD score predicted LVAR, with an AUC (95% confidence interval [CI]) of 0.82 (0.75-0.89) in the training set and 0.75 (0.62-0.89) in the testing set. Combining the RAD score with infarct size yielded favorable performance in predicting LVAR, with an AUC of 0.84 (0.72-0.95). Moreover, the addition of the RAD score to the left ventricular ejection fraction (LVEF) significantly increased the AUC from 0.68 (0.52-0.84) to 0.82 (0.70-0.93) (P = 0.018), which was also comparable to the prediction provided by the combined microvascular obstruction, infarct size, and LVEF with an AUC of 0.79 (0.65-0.94) (P = 0.727).

CONCLUSION:

Radiomics analysis using non-contrast cine CMR can predict LVAR after STEMI independently and incrementally to LVEF and may provide an alternative to traditional CMR parameters.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Infarto do Miocárdio com Supradesnível do Segmento ST Tipo de estudo: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Male / Newborn Idioma: En Revista: Korean J Radiol Assunto da revista: RADIOLOGIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Infarto do Miocárdio com Supradesnível do Segmento ST Tipo de estudo: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Male / Newborn Idioma: En Revista: Korean J Radiol Assunto da revista: RADIOLOGIA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China