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Objectives: To investigate the diagnostic accuracy of a modified three-material decomposition calcium subtraction (CS) algorithm for the detection of arterial stenosis in dual-energy CT angiography (DE-CTA) of the lower extremity runoff compared to standard image reconstruction, using digital subtraction angiography (DSA) as the reference standard., Methods: Eighty-eight patients (53 males; mean age, 65.9 ± 11 years) with suspected peripheral arterial disease (PAD) who had undergone a DE-CTA examination of the lower extremity runoff between May 2014 and May 2015 were included in this IRB-approved, HIPAA-compliant retrospective study. Standard linearly blended and CS images were reconstructed and vascular contrast-to-noise ratios (CNR) were calculated. Two independent observers assessed subjective image quality using a 5-point Likert scale. Diagnostic accuracy for ≥ 50% stenosis detection was analyzed in a subgroup of 45 patients who had undergone additional DSA. Diagnostic accuracy parameters were estimated with a random-effects logistic regression analysis and compared using generalized estimating equations., Results: CS datasets showed higher CNR (15.3 ± 7.3) compared to standard reconstructions (13.5 ± 6.5, p < 0.001). Both reconstructions showed comparable qualitative image quality scores (CS, 4.64; standard, 4.57; p = 0.220). Diagnostic accuracy (sensitivity, specificity, positive and negative predictive values) for CS reconstructions was 96.5% (97.5%, 95.6%, 90.9%, 98.1) and 93.1% (98.8%, 90.4%, 82.3%, 99.1%) for standard images., Conclusions: A modified three-material decomposition CS algorithm provides increased vascular CNR, equivalent qualitative image quality, and greater diagnostic accuracy for the detection of significant arterial stenosis of the lower extremity runoff on DE-CTA compared with standard image reconstruction., Key Points: • Calcified plaques may lead to overestimation of stenosis severity and false positive results, requiring additional invasive digital subtraction angiography (DSA). • A modified three-material decomposition algorithm for calcium subtraction provides greater diagnostic accuracy for the detection of significant arterial stenosis of the lower extremity runoff compared with standard image reconstruction. • The application of this algorithm in patients with heavily calcified vessels may be helpful to potentially reduce inconclusive CT angiography examinations and the need for subsequent invasive DSA.

Purpose To compare two technical approaches for determination of coronary computed tomography (CT) angiography-derived fractional flow reserve (FFR)-FFR derived from coronary CT angiography based on computational fluid dynamics (hereafter, FFR CFD ) and FFR derived from coronary CT angiography based on machine learning algorithm (hereafter, FFR ML )-against coronary CT angiography and quantitative coronary angiography (QCA). Materials and Methods A total of 85 patients (mean age, 62 years ± 11 [standard deviation]; 62% men) who had undergone coronary CT angiography followed by invasive FFR were included in this single-center retrospective study. FFR values were derived on-site from coronary CT angiography data sets by using both FFR CFD and FFR ML . The performance of both techniques for detecting lesion-specific ischemia was compared against visual stenosis grading at coronary CT angiography, QCA, and invasive FFR as the reference standard. Results On a per-lesion and per-patient level, FFR ML showed a sensitivity of 79% and 90% and a specificity of 94% and 95%, respectively, for detecting lesion-specific ischemia. Meanwhile, FFR CFD resulted in a sensitivity of 79% and 89% and a specificity of 93% and 93%, respectively, on a per-lesion and per-patient basis (P = .86 and P = .92). On a per-lesion level, the area under the receiver operating characteristics curve (AUC) of 0.89 for FFR ML and 0.89 for FFR CFD showed significantly higher discriminatory power for detecting lesion-specific ischemia compared with that of coronary CT angiography (AUC, 0.61) and QCA (AUC, 0.69) (all P < .0001). Also, on a per-patient level, FFR ML (AUC, 0.91) and FFR CFD (AUC, 0.91) performed significantly better than did coronary CT angiography (AUC, 0.65) and QCA (AUC, 0.68) (all P < .0001). Processing time for FFR ML was significantly shorter compared with that of FFR CFD (40.5 minutes ± 6.3 vs 43.4 minutes ± 7.1; P = .042). Conclusion The FFR ML algorithm performs equally in detecting lesion-specific ischemia when compared with the FFR CFD approach. Both methods outperform accuracy of coronary CT angiography and QCA in the detection of flow-limiting stenosis., (© RSNA, 2018.)

There is an urgent need to develop new protocols to reduce radiation dose of coronary computed tomography angiography (CTA). The aim of this pilot study was to demonstrate the feasibility of an ultra-low dose CTA scanning., (Copyright © 2017. Published by Elsevier B.V.)

Objectives: The aim of this study was to evaluate a prototype dual-energy computed tomography calcium subtraction algorithm and its impact on luminal visualization in patients with heavily calcified coronary arteries., Materials and Methods: Twenty-nine patients (62% male; mean age, 64 ± 7 years) who had undergone dual-energy coronary computed tomography angiography were retrospectively included in this institutional review board-approved, Health Insurance Portability and Accountability Act-compliant study. Linearly blended (M&#95;0.6) and calcium-subtracted images were reconstructed. Two independent observers assessed luminal visualization of the coronary arteries in a segment-based analysis, subjective image quality, and diagnostic confidence using 5-point Likert scales. Contrast-to-noise ratios for both data sets were calculated. Wilcoxon testing and Cohen's κ were used for statistical comparisons., Results: Calcium-subtracted image series showed improved lumen visualization of the coronary arteries (P = 0.008), with excellent interreader agreement (mean score, 3.3; κ = 0.82), compared with M&#95;0.6 series (mean score, 2.9; κ = 0.77). The calcium subtraction algorithm improved diagnostic confidence compared with the M&#95;0.6 reconstructions (mean scores, 4.0 and 3.1, respectively; all P ≤ 0.002). The image quality analysis showed no significant differences between calcium-subtracted and M&#95;0.6 data sets (subjectively: mean scores, 4.1 and 4.2, respectively, P = 0.442; objectively: mean contrast-to-noise ratio, 37.0 and 38.2, respectively, P = 0.733)., Conclusions: A prototype algorithm for calcium subtraction improves coronary lumen visualization and diagnostic confidence in patients with heavy coronary calcifications without differences in conventional subjective and objective measures of image quality.