Anthropomorphic cardiac phantom for dynamic SPECT

Krakovich, A; Zaretsky, Uri; Gelbart, Elad; Moalem, I; Naimushin, Alexey; Rozen, Eli; Scheinowitz, Mickey; Goldkorn, Ronen

doi:10.1007/s12350-022-03024-2

Cited by 4 publications

(1 citation statement)

References 29 publications

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“…Physical phantoms are used to assess imaging device performance, geometric distortion, signal-to-noise ratio (SNR), etc., and provide important information for the development and validation of imaging and post-processing pipelines; few physical phantoms support the simulation of motion and blood flow [ 2 – 6 ] see Table 1 in Supplementary material. Most published physical phantoms focus on sub-parts of the cardiovascular anatomy, such as the ventricles [ 3 – 5 ].…”

Section: Introductionmentioning

confidence: 99%

A simulation-based phantom model for generating synthetic mitral valve image data–application to MRI acquisition planning

Manini,

Nemchyna,

Akansel

et al. 2023

Int J CARS

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Purpose Numerical phantom methods are widely used in the development of medical imaging methods. They enable quantitative evaluation and direct comparison with controlled and known ground truth information. Cardiac magnetic resonance has the potential for a comprehensive evaluation of the mitral valve (MV). The goal of this work is the development of a numerical simulation framework that supports the investigation of MRI imaging strategies for the mitral valve. Methods We present a pipeline for synthetic image generation based on the combination of individual anatomical 3D models with a position-based dynamics simulation of the mitral valve closure. The corresponding images are generated using modality-specific intensity models and spatiotemporal sampling concepts. We test the applicability in the context of MRI imaging strategies for the assessment of the mitral valve. Synthetic images are generated with different strategies regarding image orientation (SAX and rLAX) and spatial sampling density. Results The suitability of the imaging strategy is evaluated by comparing MV segmentations against ground truth annotations. The generated synthetic images were compared to ones acquired with similar parameters, and the result is promising. The quantitative analysis of annotation results suggests that the rLAX sampling strategy is preferable for MV assessment, reaching accuracy values that are comparable to or even outperform literature values. Conclusion The proposed approach provides a valuable tool for the evaluation and optimization of cardiac valve image acquisition. Its application to the use case identifies the radial image sampling strategy as the most suitable for MV assessment through MRI.

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