Modality-agnostic, patient-specific digital twins modeling temporally varying digestive motion.
Objective. Clinical implementation of deformable image registration (DIR) requires voxel-based spatial accuracy metrics such as manually identified landmarks, which are challenging to implement for highly mobile gastrointestinal (GI) organs. To address this, patient-specific digital twins (DTs) modeling temporally varying motion were created to assess the accuracy of DIR methods.Approach. A total of 21 motion phases simulating digestive GI motion as 4D image sequences were generated from static 3D patient scans using published analytical GI motion models through a multi-step semi-automated pipeline. Eleven datasets, including six T2-weighted FSE MRI (T2w MRI), two T1-weighted 4D golden-angle stack-of-stars, and three contrast-enhanced computed tomography scans were analyzed. The motion amplitudes of the DTs were assessed against real patient stomach motion amplitudes extracted from independent 4D MRI datasets using hierarchical motion reconstruction. The patient-specific DTs were then used to assess six different DIR methods using target registration error, Dice similarity coefficient (DSC), and the 95th percentile Hausdorff distance using summary metrics and voxel-level granular visualizations. Finally, for a subset of T2w MRI scans collected from patients treated with magnetic resonance-guided radiation therapy, dose distributions were warped and accumulated to assess dose warping errors (DWEs), including evaluations of DIR performance in both low- and high-dose regions for patient-specific error estimation.Main results. Our proposed pipeline synthesized patient-specific DTs modeling realistic GI motion, achieving mean and maximum motion amplitudes and a mean log Jacobian determinant within 0.8 mm and 0.01, respectively, similar to published real-patient gastric motion data. It also enables the extraction of detailed quantitative DIR performance metrics and supports rigorous validation of dose mapping accuracy prior to clinical implementation.Significance. The developed pipeline enables rigorously testing DIR tools for dynamic, anatomically complex regions facilitating granular spatial and dosimetric accuracies.
Duke Scholars
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Related Subject Headings
- Time Factors
- Patient-Specific Modeling
- Nuclear Medicine & Medical Imaging
- Movement
- Magnetic Resonance Imaging
- Image Processing, Computer-Assisted
- Humans
- Gastrointestinal Tract
- 5105 Medical and biological physics
- 1103 Clinical Sciences
Citation
Published In
DOI
EISSN
Publication Date
Volume
Issue
Location
Related Subject Headings
- Time Factors
- Patient-Specific Modeling
- Nuclear Medicine & Medical Imaging
- Movement
- Magnetic Resonance Imaging
- Image Processing, Computer-Assisted
- Humans
- Gastrointestinal Tract
- 5105 Medical and biological physics
- 1103 Clinical Sciences