In Journal of imaging
AIMS : Increased left ventricular (LV) wall thickness is frequently encountered in transthoracic echocardiography (TTE). While accurate and early diagnosis is clinically important, given the differences in available therapeutic options and prognosis, an extensive workup is often required to establish the diagnosis. We propose the first echo-based, automated deep learning model with a fusion architecture to facilitate the evaluation and diagnosis of increased left ventricular (LV) wall thickness.
METHODS AND RESULTS : Patients with an established diagnosis of increased LV wall thickness (hypertrophic cardiomyopathy (HCM), cardiac amyloidosis (CA), and hypertensive heart disease (HTN)/others) between 1/2015 and 11/2019 at Mayo Clinic Arizona were identified. The cohort was divided into 80%/10%/10% for training, validation, and testing sets, respectively. Six baseline TTE views were used to optimize a pre-trained InceptionResnetV2 model. Each model output was used to train a meta-learner under a fusion architecture. Model performance was assessed by multiclass area under the receiver operating characteristic curve (AUROC). A total of 586 patients were used for the final analysis (194 HCM, 201 CA, and 191 HTN/others). The mean age was 55.0 years, and 57.8% were male. Among the individual view-dependent models, the apical 4-chamber model had the best performance (AUROC: HCM: 0.94, CA: 0.73, and HTN/other: 0.87). The final fusion model outperformed all the view-dependent models (AUROC: HCM: 0.93, CA: 0.90, and HTN/other: 0.92).
CONCLUSION : The echo-based InceptionResnetV2 fusion model can accurately classify the main etiologies of increased LV wall thickness and can facilitate the process of diagnosis and workup.
Li James, Chao Chieh-Ju, Jeong Jiwoong Jason, Farina Juan Maria, Seri Amith R, Barry Timothy, Newman Hana, Campany Megan, Abdou Merna, O’Shea Michael, Smith Sean, Abraham Bishoy, Hosseini Seyedeh Maryam, Wang Yuxiang, Lester Steven, Alsidawi Said, Wilansky Susan, Steidley Eric, Rosenthal Julie, Ayoub Chadi, Appleton Christopher P, Shen Win-Kuang, Grogan Martha, Kane Garvan C, Oh Jae K, Patel Bhavik N, Arsanjani Reza, Banerjee Imon
2023-Feb-18
LV wall thickness, deep learning, echocardiography
