Our primary objective in this study was to determine the preferred strength setting for the sinogram-affirmed iterative reconstruction algorithm (SAFIRE) in abdominal computed tomography (CT) imaging. Sixteen consecutive clinical CT scans of the abdomen were reconstructed by use of traditional filtered back projection (FBP) and 5 SAFIRE strengths: S1-S5. Six readers of differing experience were asked to rank the images on preference for overall diagnostic quality. The contrast-to-noise ratio was not significantly different between SAFIRE S1 and FBP, but increased with increasing SAFIRE strength. For pooled data, S2 and S3 were preferred equally but both were preferred over all other reconstructions. S5 was the least preferred, with FBP the next least preferred. This represents a marked disparity between the image quality based on quantitative parameters and qualitative preference. Care should be taken to factor in qualitative in addition to quantitative aspects of image quality when one is optimizing iterative reconstruction images.
Purpose: Realistic three‐dimensional mathematical models of subtle lesions are essential for many CT studies focused on performance evaluation and optimization. The purpose of this work was to develop and apply a generic framework for creating such models informed by clinical data. Methods: A contrast profile equation was developed to describe the attenuation of a modeled lesion as a function of distance from the center of the lesion in a given direction. This equation prescribes the overall size, shape, contrast, and edge profile characteristics of the lesion in 3D. By adjusting the parameters of the contrast profile equation, the characteristics of a simulated lesion could be manipulated to emulate a realistic lesion. The simulated lesions could further be voxelized at any arbitrary resolution for comparison with real CT data. Using this framework, a trust‐region iterative minimization fitting algorithm was developed to generate a library of simulated lesions based on clinical CT data with known lesions. We first identified and segmented liver lesions, lung nodules, and renal stones from clinical cases. The fitting algorithm was then applied to the segmented pathologies. The results were evaluated for realism using an observer study and ROC analysis. Results: Based on CT image data from 22 patients; 10 liver lesion, 13 lung nodule, and 20 renal stone models were created. These models were found to have size, shape, contrast, and edge profile characteristics similar to those of real lesions. The observers could not distinguish between real and modeled lesions (AUC = 0.49). Conclusions: It is possible to create realistic 3D mathematical models of anthropomorphic lesions in CT images. These models could be instrumental in performance evaluation and optimization of CT systems. GE Healthcare, A‐56:Optimization of Protocols Employing Advanced Reconstruction Algorithms
Purpose:
The objective of this study was two‐fold: (a) to test a new approach to approximating organ dose by using the effective energy of the combined 80kV/140kV beam in dual‐energy (DE) computed tomography (CT), and (b) to derive the effective dose (ED) in the abdomen‐pelvis protocol in DECT.
Methods:
A commercial dual energy CT scanner was employed using a fast‐kV switch abdomen/pelvis protocol alternating between 80 kV and 140 kV. MOSFET detectors were used for organ dose measurements. First, an experimental validation of the dose equivalency between MOSFET and ion chamber (as a gold standard) was performed using a CTDI phantom. Second, the ED of DECT scans was measured using MOSFET detectors and an anthropomorphic phantom. For ED calculations, an abdomen/pelvis scan was used using ICRP 103 tissue weighting factors; ED was also computed using the AAPM Dose Length Product (DLP) method and compared to the MOSFET value.
Results:
The effective energy was determined as 42.9 kV under the combined beam from half‐value layer (HVL) measurement. ED for the dual‐energy scan was calculated as 16.49 ± 0.04 mSv by the MOSFET method and 14.62 mSv by the DLP method.
Conclusion:
Tissue dose in the center of the CTDI body phantom was 1.71 ± 0.01 cGy (ion chamber) and 1.71 ± 0.06 (MOSFET) respectively; this validated the use of effective energy method for organ dose estimation. ED from the abdomen‐pelvis scan was calculated as 16.49 ± 0.04 mSv by MOSFET and 14.62 mSv by the DLP method; this suggests that the DLP method provides a reasonable approximation to the ED.
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