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Rationale and Objectives: To investigate the impact of iterative reconstruction in image space (IRIS) on image noise, image quality (IQ), and postprocessing at coronary computed tomography angiography (cCTA) compared to traditional filtered back-projection (FBP). Materials and Methods: The cCTA results of 50 patients (26 men; 58 ± 15 years, body mass index 31.5 ± 6.7 kg/m²) were investigated using a second-generation dual-source computed tomography system. Scan data were reconstructed with the use of IRIS and FBP algorithms. Two radiologists independently evaluated the reconstructions using automated coronary tree analysis software. Image noise was measured and IQ was rated on a 5-point Likert scale. The number of manual corrections after automated vessel segmentation, the time required to complete segmentation, and the number of missed segments were assessed in both IRIS and FBP reconstructions. Results were compared using paired t-test. Results: IRIS significantly reduced image noise compared to FBP (23.3 ± 8.8 vs. 33.5 ± 13.5 Hounsfield units, P < .001). Subjective IQ improved with IRIS (IRIS 3.2 ± 1.0 vs. FBP 3.0 ± 1.0, P < .05). IRIS decreased the time needed for coronary segmentation from 111.9 ± 40.5 seconds to 95.2 ± 38.2 seconds with FBP (P < .01) and required fewer manual corrections (5.7 ± 3.0 vs. 6.8 ± 3.6, P < .01). The number of missed vessel segments was not significantly different (3.6 ± 1.8 vs. 3.8 ± 1.9, P > .05) between IRIS and FBP, respectively. Conclusions: During cCTA postprocessing, IRIS significantly decreases the time and the number of manual corrections for a complete coronary segmentation compared to FBP. This effect is likely attributable to suppression of image noise by IRIS, which improves the performance of automated vessel segmentation and positively impacts cCTA analysis. [Copyright &y& Elsevier]

Background: The performance of dual-energy CT (DECT) for the detection of myocardial blood volume deficits has not systematically been compared with single-energy CT (SCT) spectra. Objective: We evaluated the accuracy for detection of myocardial blood volume deficits in DECT and SCT compared with 99m-Tc-Sestamibi-SPECT (single-photon emission CT) during rest and stress. Methods: 47 patients underwent rest/stress SPECT myocardial perfusion imaging and cardiac DECT on a dual-source CT scanner. The A- and B-tubes were operated with 140 kV and 80 kV/100 kV, respectively. DECT raw data were reconstructed by (1) only using high-energy (140 kV) CT spectra, (2) only using low-energy (80 kV/100 kV) CT spectra, (3) merging data (30% low- and 70% high-energy CT spectra), and (4) DECT-based iodine maps. Two independent, blinded observers analyzed all CT data according to each of the 4 reconstruction strategies for myocardial blood volume deficits. Results: Specificity and positive predictive values were relatively similar between the 4 reconstruction strategies, with highest specificity (98%) of SCT datasets based on 140 kV for mixed perfusion deficits seen on SPECT. DECT iodine maps showed highest sensitivity, negative predictive value, and accuracy of 91%, 97%, and 93%, respectively, for mixed perfusion deficits. Analysis with receiver operating characteristics showed highest area under the curve values (0.84–0.93) with the use of DECT iodine maps in the detection of purely fixed and mixed perfusion deficits. Conclusion: DECT iodine maps show superior performance for the detection of fixed and mixed perfusion deficits compared with SCT spectra. [Copyright &y& Elsevier]