Rationale And Objectives: We compared the effect of iterative model reconstruction (IMR), filtered back projection (FBP), and hybrid iterative reconstruction (HIR) on coronary artery calcium (CAC) scoring.
Materials And Methods: CAC scans of 30 consecutive patients (18 men and 12 women, age 70.1 ± 12.2 years) were reconstructed with FBP, HIR, and IMR, and the image noise was measured on all images. Two radiologists independently measured the CAC scores using semiautomated software, and interobserver agreement was evaluated. Statistical analysis included the Spearman correlation coefficient and Bland-Altman analysis.
Results: The mean image noise on FBP, HIR, and IMR images was 48.0 ± 7.9, 29.6 ± 4.8, and 9.3 ± 1.3 Hounsfield units, respectively. The difference among all reconstruction combinations was significant (P < .01). The CAC score on HIR and IMR scans was 4.2% and 8.9% lower, respectively, than the CAC score on FBP images. There was no significant difference in the mean CAC score among the three reconstructions. The interobserver correlation was excellent for all three reconstructions (r = 0.96 FBP, 0.99 HIR, 0.99 IMR); the best Bland-Altman measure of agreement was with IMR, followed by HIR and FBP.
Conclusion: For CAC scoring, IMR can reduce the image noise and blooming artifacts, and consequently lowers the measured CAC score. IMR can lessen measurement variability and yield stable, reproducible measurements.
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http://dx.doi.org/10.1016/j.acra.2016.11.003 | DOI Listing |
Med Phys
December 2024
Department of Physics, Lakehead University, Thunder Bay, Ontario, Canada.
Background: This study investigates a multi-angle acquisition method aimed at improving image quality in organ-targeted PET detectors with planar detector heads. Organ-targeted PET technologies have emerged to address limitations of conventional whole-body PET/CT systems, such as restricted axial field-of-view (AFOV), limited spatial resolution, and high radiation exposure associated with PET procedures. The AFOV in organ-targeted PET can be adjusted to the organ of interest, minimizing unwanted signals from other parts of the body, thus improving signal collection efficiency and reducing the dose of administered radiotracer.
View Article and Find Full Text PDFPLoS One
December 2024
College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, Liaoning Province, China.
The iterative shrinkage-thresholding algorithm (ISTA) is a classic optimization algorithm for solving ill-posed linear inverse problems. Recently, this algorithm has continued to improve, and the iterative weighted shrinkage-thresholding algorithm (IWSTA) is one of the improved versions with a more evident advantage over the ISTA. It processes features with different weights, making different features have different contributions.
View Article and Find Full Text PDFTomography
December 2024
Department of Diagnostic Radiology, Kitasato University School of Medicine, Sagamihara 252-0374, Japan.
Objectives: We evaluated the noise reduction effects of deep learning reconstruction (DLR) and hybrid iterative reconstruction (HIR) in brain computed tomography (CT).
Methods: CT images of a 16 cm dosimetry phantom, a head phantom, and the brains of 11 patients were reconstructed using filtered backprojection (FBP) and various levels of DLR and HIR. The slice thickness was 5, 2.
Tomography
November 2024
Department of Diagnostic Radiology, Tokai University School of Medicine, 143 Shimokasuya, Isehara 259-1193, Japan.
Photon-counting detector computed tomography (PCD-CT) offers energy-resolved CT data with enhanced resolution, reduced electronic noise, and improved tissue contrast. This study aimed to evaluate the visibility of intracranial perforating arteries on ultra-high-resolution (UHR) CT angiography (CTA) on PCD-CT. A retrospective analysis of intracranial UHR PCD-CTA was performed for 30 patients.
View Article and Find Full Text PDFIEEE Access
November 2024
University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
The achievable spatial resolution of C metabolic images acquired with hyperpolarized C-pyruvate is worse than H images typically by an order of magnitude due to the rapidly decaying hyperpolarized signals and the low gyromagnetic ratio of C. This study is to develop and characterize a volumetric patch-based super-resolution reconstruction algorithm that enhances spatial resolution C cardiac MRI by utilizing structural information from H MRI. The reconstruction procedure comprises anatomical segmentation from high-resolution H MRI, calculation of a patch-based weight matrix, and iterative reconstruction of high-resolution multi-slice C MRI.
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