Mr. Kevin Jaeyoung Chung Profile

Kevin Jaeyoung Chung

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Proceedings Article | 4 April 2022 Presentation + Paper

Quality versus quantity of dynamic CT perfusion images at isodose

Kevin Chung, Ting-Yim Lee

Proceedings Volume 12036, 120360L (2022) https://doi.org/10.1117/12.2611249

KEYWORDS: Temporal resolution, Deconvolution, Brain, Computed tomography, Image segmentation, Signal to noise ratio, Neuroimaging

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Whole-brain high temporal resolution CT perfusion (CTP) is now feasible with wide-detector row CT scanners, but the optimal dose distribution of dynamic images remains unknown. In this study, we investigated the accuracy of perfusion parameters estimated in digital perfusion phantoms generated at various temporal resolutions with fixed scan dose. In accordance with CTP guidelines, simulated dose was set to a time-density curve (TDC) noise of 10 HU at a sampling interval of 2.0 s over 60 s, and higher temporal resolutions of 1.0 and 0.5 s intervals were investigated at 14 and 20 HU of noise, respectively. Monte Carlo simulations with known ground truth perfusion were conducted to test the performance of model-independent and model-dependent deconvolution algorithms as a function of temporal resolution at isodose. Tissue TDCs were simulated by convolving gamma-variate, linear or boxcar residue functions with a patient arterial TDC before adding Gaussian noise at the appropriate level then sampling at the investigated temporal resolutions. A digital brain perfusion phantom with physiological ground truth perfusion was similarly investigated. Only cerebral blood flow (CBF) estimates with the model-dependent algorithm marginally improved at higher temporal resolution as indicated by mean absolute error (MAE; 7.1±4.6 ml/min/100 g at 0.5 s, 9.6±6.0 ml/min/100 g at 2.0 s) but not with the modelindependent algorithm (MAE: 11.6±11.4 ml/min/100 g at 0.5 s, 11.3±11.7 ml/min/100 g at 2.0 s). Higher temporal resolution did not improve parameter estimation in the brain perfusion phantom. For the investigated temporal resolutions and simulated CTP dose, dose distribution appears negligible.

Proceedings Article | 28 February 2020 Presentation + Paper

Sparse-view CT perfusion with filtered back projection image reconstruction

Kevin Chung, Bijoy Menon, Ting-Yim Lee

Proceedings Volume 11317, 113170P (2020) https://doi.org/10.1117/12.2549121

KEYWORDS: X-ray computed tomography, Computed tomography, Computer simulations, Image restoration, Ischemic stroke, Cerebral blood flow, Tissues, Brain

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CT perfusion (CTP) efficiently provides valuable hemodynamic information for triage of acute ischemic stroke patients at the expense of additional radiation dose from consecutive CT acquisitions. Low-dose CTP is therefore highly desirable but is often attempted by iterative or deep learning reconstructions that are computationally intensive. We aimed to demonstrate that acquiring fewer x-ray projections in a CTP scan while reconstructing with filtered back projection (FBP) can reduce radiation dose without impacting clinical utility. Six CTP studies were selected from the PRove-IT clinical database. For each axial source CTP slice, a 984-view sinogram was synthesized using a Radon Transform and uniformly under-sampled to 492, 328, 246, and 164-views. An FBP was applied on each sparse-view sinogram to reconstruct source images that were used to generate perfusion maps using a delay-insensitive deconvolution algorithm. The resulting Tmax and cerebral blood flow perfusion maps were evaluated for their ability to identify penumbra and ischemic core volumes using the Pearson correlation (R) and Bland-Altman analysis. In addition, sparse-view perfusion maps were assessed for fidelity to original full-view maps using structural similarity, peak signal-to-noise ratio, and normalized root mean squared error. Ischemic penumbra and infarct core volumes were accurately estimated by all sparse-view configurations (R<0.95, p<0.001; mean difference <3 ml) and overall perfusion map fidelity was well-maintained up to 328-views. Our preliminary analysis reveals that radiation dose can potentially be reduced by a factor of 6 with further validation that the errors in ischemic volume measurement do not impact clinical decision-making.

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