ArticleMedical physics2022
Four-dimensional computed tomography of the left ventricle, Part II: Estimation of mechanical activation times.
Article in Medical physics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 11 citations in OpenAlex.
- 3D regional evaluation of right ventricular myocardial work from cineCT.medRxiv : the preprint server for health sciences · 2024Article
- Protocol optimization for functional cardiac CT imaging using noise emulation in the raw data domain.Medical physics · 2024Article
- Protocol Optimization for Functional Cardiac CT Imaging Using Noise Emulation in the Raw Data Domain.ArXiv · 2024Article
- A three-dimensional left atrial motion estimation from retrospective gated computed tomography: application in heart failure patients with atrial fibrillation.Frontiers in cardiovascular medicine · 2024Article
- Cardiac CT in CRT as a Singular Imaging Modality for Diagnosis and Patient-Tailored Management.Journal of clinical medicine · 2023Review
- Regional left ventricular endocardial strains estimated from low-dose 4DCT: Comparison with cardiac magnetic resonance feature tracking.Medical physics · 2022Article
- Prediction of Cardiac Resynchronization Therapy Response Using a Lead Placement Score Derived From 4-Dimensional Computed Tomography.Circulation. Cardiovascular imaging · 2022Article
- Four-dimensional computed tomography of the left ventricle, Part I: Motion artifact reduction.Medical physics · 2022Article
- Motion correction of wide-detector 4DCT images for cardiac resynchronization therapy planning.Journal of cardiovascular computed tomographyArticle
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
purposeWe demonstrate the viability of a four-dimensional X-ray computed tomography (4DCT) imaging system to accurately and precisely estimate mechanical activation times of left ventricular (LV) wall motion. Accurate and reproducible timing estimates of LV wall motion may be beneficial in the successful planning and management of cardiac resynchronization therapy (CRT).
methodsWe developed an anthropomorphically accurate in silico LV phantom based on human CT images with programmed septal-lateral wall dyssynchrony. Twenty-six temporal phases of the in silico phantom were used to sample the cardiac cycle of 1 s. For each of the 26 phases, 1 cm thick axial slabs emulating axial CT image volumes were extracted, 3D printed, and imaged using a commercially available CT scanner. A continuous dynamic sinogram was synthesized by blending sinograms from these static phases; the synthesized sinogram emulated the sinogram that would be acquired under true continuous phantom motion. Using the synthesized dynamic sinogram, images were reconstructed at 70 ms intervals spanning the full cardiac cycle; these images exhibited expected motion artifact characteristics seen in images reconstructed from real dynamic data. The motion corrupted images were then processed with a novel motion correction algorithm (ResyncCT) to yield motion corrected images. Five pairs of motion uncorrected and motion corrected images were generated, each corresponding to a different starting gantry angle (0 to 180 degrees in 45 degree increments). Two line profiles perpendicular to the endocardial surface were used to sample local myocardial motion trajectories at the septum and the lateral wall. The mechanical activation time of wall motion was defined as the time at which the endocardial boundary crossed a fixed position defined on either of the two line profiles while moving toward the center of the LV during systolic contraction. The mechanical activation times of these myocardial trajectories estimated from the motion uncorrected and the motion corrected images were then compared with those derived from the static images of the 3D printed phantoms (ground truth). The precision of the timing estimates was obtained from the five different starting gantry angle simulations.
resultsThe range of estimated mechanical activation times observed across all starting gantry angles was significantly larger for the motion uncorrected images than for the motion corrected images (lateral wall: 58 ± 15 ms vs 12 ± 4 ms, p < 0.005; septal wall: 61 ± 13 ms vs 13 ± 9 ms, p < 0.005).
conclusions4DCT images processed with the ResyncCT motion correction algorithm yield estimates of mechanical activation times of LV wall motion with significantly improved accuracy and precision. The promising results reported in this study highlight the potential utility of 4DCT in estimating the timing of mechanical events of interest for CRT guidance.
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