Photon-counting cine-cardiac CT in the mouse.
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2019-01
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Abstract
The maturation of photon-counting detector (PCD) technology promises to enhance routine CT imaging applications with high-fidelity spectral information. In this paper, we demonstrate the power of this synergy and our complementary reconstruction techniques, performing 4D, cardiac PCD-CT data acquisition and reconstruction in a mouse model of atherosclerosis, including calcified plaque. Specifically, in vivo cardiac micro-CT scans were performed in four ApoE knockout mice, following their development of calcified plaques. The scans were performed with a prototype PCD (DECTRIS, Ltd.) with 4 energy thresholds. Projections were sampled every 10 ms with a 10 ms exposure, allowing the reconstruction of 10 cardiac phases at each of 4 energies (40 total 3D volumes per mouse scan). Reconstruction was performed iteratively using the split Bregman method with constraints on spectral rank and spatio-temporal gradient sparsity. The reconstructed images represent the first in vivo, 4D PCD-CT data in a mouse model of atherosclerosis. Robust regularization during iterative reconstruction yields high-fidelity results: an 8-fold reduction in noise standard deviation for the highest energy threshold (relative to unregularized algebraic reconstruction), while absolute spectral bias measurements remain below 13 Hounsfield units across all energy thresholds and scans. Qualitatively, image domain material decomposition results show clear separation of iodinated contrast and soft tissue from calcified plaque in the in vivo data. Quantitatively, spatial, spectral, and temporal fidelity are verified through a water phantom scan and a realistic MOBY phantom simulation experiment: spatial resolution is robustly preserved by iterative reconstruction (10% MTF: 2.8-3.0 lp/mm), left-ventricle, cardiac functional metrics can be measured from iodine map segmentations with ~1% error, and small calcifications (615 μm) can be detected during slow moving phases of the cardiac cycle. Given these preliminary results, we believe that PCD technology will enhance dynamic CT imaging applications with high-fidelity spectral and material information.
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Clark, Darin P, Matthew Holbrook, Chang-Lung Lee and Cristian T Badea (2019). Photon-counting cine-cardiac CT in the mouse. PloS one, 14(9). p. e0218417. 10.1371/journal.pone.0218417 Retrieved from https://hdl.handle.net/10161/21142.
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Scholars@Duke
Darin Clark
Chang Lung Lee
The overall goal of the Lee lab is to improve the therapeutic window of radiation therapy and the survivorship of cancer patients by minimizing the acute and late effects of radiation. The lab studies mechanisms underlying radiation-induced tissue injury and regeneration to develop novel medical countermeasures and predictive biomarkers. The Lee lab is supported by active NIH grants studying radiation-induced oral mucositis (R01DE033404), gastrointestinal acute radiation syndrome (U01AI186969 and R21AI193496), radiation-induced intestinal fibrosis (U01AI183940), and radiation-induced heart disease (U01AI189426).
Cristian Tudorel Badea
- Our QIAL lab advances quantitative imaging by designing novel CT systems, reconstruction algorithms, image analysis and applications, with a core strength in preclinical CT.
- Current efforts center on spectral CT (dual-energy and photon-counting) with nanoparticle contrast agents for theranostics, multidimensional CT for challenging applications such as intracranial aneurysm, cardiac, and perfusion imaging, and modern reconstruction and image processing ( including deep learning).
- In parallel, we lead co-clinical cancer imaging work; I served as PI of the U24 Duke Preclinical Research Resources for Quantitative Imaging Biomarkers within the NCI Co-Clinical Imaging Research Program (CIRP).
- We are also building a virtual preclinical photon-counting CT platform for cancer studies to accelerate method development and translation.
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