Marili Niglas, Nicoleta Baxan, Ali Ashek, Lin Zhao, Jinming Duan, Declan O'Regan, Timothy J. W. Dawes, Chen Nien‐Chen, Chongyang Xie, Wenjia Bai and Lan Zhao 2025. Automated Bi‐Ventricular Segmentation and Regional Cardiac Wall Motion Analysis for Rat Models of Pulmonary Hypertension. Pulmonary Circulation. 15 (2) e70092. https://doi.org/10.1002/pul2.70092
| Title | Automated Bi‐Ventricular Segmentation and Regional Cardiac Wall Motion Analysis for Rat Models of Pulmonary Hypertension |
|---|---|
| Type | Journal article |
| Authors | Marili Niglas, Nicoleta Baxan, Ali Ashek, Lin Zhao, Jinming Duan, Declan O'Regan, Timothy J. W. Dawes, Chen Nien‐Chen, Chongyang Xie, Wenjia Bai and Lan Zhao |
| Abstract | Artificial intelligence‐based cardiac motion mapping offers predictive insights into pulmonary hypertension (PH) disease progression and its impact on the heart. We proposed an automated deep learning pipeline for bi‐ventricular segmentation and 3D wall motion analysis in PH rodent models for bridging the clinical developments. A data set of 163 short‐axis cine cardiac magnetic resonance scans were collected longitudinally from monocrotaline (MCT) and Sugen‐hypoxia (SuHx) PH rats and used for training a fully convolutional network for automated segmentation. The model produced an accurate annotation in < 1 s for each scan (Dice metric > 0.92). High‐resolution atlas fitting was performed to produce 3D cardiac mesh models and calculate the regional wall motion between end‐diastole and end‐systole. Prominent right ventricular hypokinesia was observed in PH rats (−37.7% ± 12.2 MCT; −38.6% ± 6.9 SuHx) compared to healthy controls, attributed primarily to the loss in basal longitudinal and apical radial motion. This automated bi‐ventricular rat‐specific pipeline provided an efficient and novel translational tool for rodent studies in alignment with clinical cardiac imaging AI developments. |
| Article number | e70092 |
| Journal | Pulmonary Circulation |
| Journal citation | 15 (2) |
| ISSN | 2045-8940 |
| 2045-8940 | |
| Year | 2025 |
| Publisher | Wiley |
| Publisher's version | License CC BY 4.0 File Access Level Open (open metadata and files) |
| Digital Object Identifier (DOI) | https://doi.org/10.1002/pul2.70092 |
| Web address (URL) | http://dx.doi.org/10.1002/pul2.70092 |
| Publication dates | |
| Published online | 12 May 2025 |