Validation of an Automated Cardiothoracic Ratio Calculation for Hemodialysis Patients

Author:

Chou Hsin-Hsu12,Lin Jin-Yi3,Shen Guan-Ting3,Huang Chih-Yuan45ORCID

Affiliation:

1. Department of Pediatrics, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi 600566, Taiwan

2. Department of Bioinformatics and Medical Engineering, Asia University, Taichung 413305, Taiwan

3. Innovation and Incubation Center, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi 600566, Taiwan

4. Division of Nephrology, Department of Internal Medicine, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi 600566, Taiwan

5. Department of Sport Management, College of Recreation and Health Management, Chia Nan University of Pharmacy and Science, Tainan 717301, Taiwan

Abstract

Cardiomegaly is associated with poor clinical outcomes and is assessed by routine monitoring of the cardiothoracic ratio (CTR) from chest X-rays (CXRs). Judgment of the margins of the heart and lungs is subjective and may vary between different operators. Methods: Patients aged > 19 years in our hemodialysis unit from March 2021 to October 2021 were enrolled. The borders of the lungs and heart on CXRs were labeled by two nephrologists as the ground truth (nephrologist-defined mask). We implemented AlbuNet-34, a U-Net variant, to predict the heart and lung margins from CXR images and to automatically calculate the CTRs. Results: The coefficient of determination (R2) obtained using the neural network model was 0.96, compared with an R2 of 0.90 obtained by nurse practitioners. The mean difference between the CTRs calculated by the nurse practitioners and senior nephrologists was 1.52 ± 1.46%, and that between the neural network model and the nephrologists was 0.83 ± 0.87% (p < 0.001). The mean CTR calculation duration was 85 s using the manual method and less than 2 s using the automated method (p < 0.001). Conclusions: Our study confirmed the validity of automated CTR calculations. By achieving high accuracy and saving time, our model can be implemented in clinical practice.

Publisher

MDPI AG

Subject

Clinical Biochemistry

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