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The original version of this article, published on 16 December 2019, unfortunately contained two mistakes.

To implement detailed EU cardiac computed tomography angiography (CCTA) quality criteria in the multicentre DISCHARGE trial (FP72007-2013, EC-GA 603266), we reviewed image quality and adherence to CCTA protocol and to the recommendations of invasive coronary angiography (ICA) in a pilot study.From every clinical centre, imaging datasets of three patients per arm were assessed for adherence to the inclusion/exclusion criteria of the pilot study, predefined standards for the CCTA protocol and ICA recommendations, image quality and non-diagnostic (NDX) rate. These parameters were compared via multinomial regression and ANOVA. If a site did not reach the minimum quality level, additional datasets had to be sent before entering into the final accepted database (FADB).We analysed 226 cases (150 CCTA/76 ICA). The inclusion/exclusion criteria were not met by 6 of the 226 (2.7%) datasets. The predefined standard was not met by 13 of 76 ICA datasets (17.1%). This percentage decreased between the initial CCTA database and the FADB (multinomial regression, 53 of 70 vs 17 of 75 [76%] vs [23%]). The signal-to-noise ratio and contrast-to-noise ratio of the FADB did not improve significantly (ANOVA, p = 0.20; p = 0.09). The CTA NDX rate was reduced, but not significantly (initial CCTA database 15 of 70 [21.4%]) and FADB 9 of 75 [12%]; p = 0.13).We were able to increase conformity to the inclusion/exclusion criteria and CCTA protocol, improve image quality and decrease the CCTA NDX rate by implementing EU CCTA quality criteria and ICA recommendations.• Failure to meet protocol adherence in cardiac CTA was high in the pilot study (77.6%). • Image quality varies between sites and can be improved by feedback given by the core lab. • Conformance with new EU cardiac CT quality criteria might render cardiac CTA findings more consistent and comparable.

Purpose: Low contrast sensitivity of CT scanners is regularly assessed by subjective scoring of low contrast detectability within phantom CT images. Since in these phantoms low contrast objects are arranged in known fixed patterns, subjective rating of low contrast visibility might be biased. The purpose of this study was to develop and validate a software for automated objective low contrast detectability based on a model observer. Methods: Images of the low contrast module of the Catphan 600 phantom were used for the evaluation of the software. This module contains two subregions: the supraslice region with three groups of low contrast objects (each consisting of nine circular objects with diameter 2-15 mm and contrast 0.3, 0.5, and 1.0%, respectively) and the subslice region with three groups of four circular objects each (diameter 3-9 mm; contrast 1.0%). The software method offered automated determination of low contrast detectability using a NPWE (nonprewhitening matched filter with an eye filter) model observer for the supraslice region. The model observer correlated templates of the low contrast objects with the acquired images of the Catphan phantom and a discrimination index d' was calculated. This index was transformed into a proportion correct (PC) value. In the two-alternative forced choice (2-AFC) experiments used in this study, a PC >= 75% was proposed as a threshold to decide whether objects were visible. As a proof of concept, influence of kVp (between 80 and 135 kV), mAs (25-200 mAs range) and reconstruction filter (four filters, two soft and two sharp) on low contrast detectability was investigated. To validate the outcome of the software in a qualitative way, a human observer study was performed. Results: The expected influence of kV, mAs and reconstruction filter on image quality are consistent with the results of the proposed automated model. Higher values for d' (or PC) are found with increasing mAs or kV values and for the soft reconstruction filters. For the highest contrast group (1%), PC values were fairly above 75% for all object diameters > 2 mm, for all conditions. For the 0.5% contrast group, the same behavior was observed for object diameters > 3 mm for all conditions. For the 0.3% contrast group, PC values were higher than 75% for object diameters > 6 mm except for the series acquired at the lowest dose (25 mAs), which gave lower PC values. In the human observer study similar trends were found. Conclusions: We have developed an automated method to objectively investigate image quality using the NPWE model in combination with images of the Catphan phantom low contrast module. As a first step, low contrast detectability as a function of both acquisition and reconstruction parameter settings was successfully investigated with the software. In future work, this method could play a role in image reconstruction algorithms evaluation, dose reduction strategies or novel CT technologies, and other model observers may be implemented as well. (c) 2011 American Association of Physicists in Medicine. [DOI: 10.1118/1.3577757]

OBJECTIVE. The purpose of this article is to evaluate to what extent Agatston scores may be derived from CT coronary angiography (CTA) examinations, compared with traditional unenhanced CT calcium scores. MATERIALS AND METHODS. Fifty patients with a CT calcium score-Agatston score of zero and 50 patients with a CT calcium score-Agatston score of 1 or greater whose CT calcium scores had been calculated and who had undergone CTA using volumetric 320-MDCT were included. Agatston scores were obtained at 3.0-mm slices for CT calcium score and CTA. Method agreement, interobserver agreement, and diagnostic performance of CTA for detecting coronary calcium were evaluated. RESULTS. Of 50 patients with a positive CT calcium score-Agatston score, coronary artery calcium was detected with CTA in 43 patients by observer 1 (mean CTA score, 102 +/- 202; mean CT calcium score, 254 +/- 501) and in 46 patients by observer 2 (mean CTA score, 94 +/- 147; mean CT calcium score, 272 +/- 531). Of the 50 patients with a CT calcium score-Agatston score of zero, 49 (98%, observer 1) and 50 (100%, observer 2) had a zero score with CTA as well. An intraclass correlation of 0.78 and 0.62 was found between CT calcium score and CTA (p < 0.01), whereas higher Agatston scores were underestimated with CTA. For observer 1, the sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy for detection of coronary calcium with CTA were 86%, 98%, 98%, 88%, and 92%, respectively, and the corresponding values for observer 2 were 92%, 100%, 100%, 93%, and 96%, respectively. Interobserver agreement was 0.996 for CT calcium score and 0.93 for CTA. CONCLUSION. Coronary artery calcium can be detected on CTA images with high accuracy. The Agatston calcium score derived from CTA images shows good correlation with unenhanced CT calcium score and is highly reproducible. However, higher Agatston scores are systematically underestimated when derived from CTA images.

Methods: The artifact suppression technique incorporates two steps: metal object segmentation in raw data and replacement of the segmented region by new values using an interpolation scheme, followed by addition of the scaled metal signal intensity. Segmentation of metal is performed directly in sinograms, making it efficient and different from current methods that perform segmentation in reconstructed images in combination with Radon transformations. Metal signal segmentation is achieved by using a Markov random field model (MRF). Three interpolation methods are applied and investigated. To provide a proof of concept, CT data of five patients with metal implants were included in the study, as well as CT data of a PMMA phantom with Teflon, PVC, and titanium inserts. Accuracy was determined quantitatively by comparing mean Hounsfield (HU) values and standard deviation (SD) as a measure of distortion in phantom images with titanium (original and suppressed) and without titanium insert. Qualitative improvement was assessed by comparing uncorrected clinical images with artifact suppressed images. Results: Artifacts in CT data of a phantom and five patients were automatically suppressed. The general visibility of structures clearly improved. In phantom images, the technique showed reduced SD close to the SD for the case where titanium was not inserted, indicating improved image quality. HU values in corrected images were different from expected values for all interpolation methods. Subtle differences between interpolation methods were found. Conclusions: The new artifact suppression design is efficient, for instance, in terms of preserving spatial resolution, as it is applied directly to original raw data. It successfully reduced artifacts in CT images of five patients and in phantom images. Sophisticated interpolation methods are needed to obtain reliable HU values close to the prosthesis.

Patient dosimetry and assessment of effective dose was implemented under the condition that measurements involve commonly available instrumentation. Four categories of examination were distinguished: radiographs with manual techniques, radiographs with automatic exposure control (AEC), examinations involving fluoroscopy, and computed tomography (CT). For projection radiography the dose-area product (DAP) and for CT the computed tomography dose index were measured. Databases of conversion factors were consulted for the calculation of effective dose. Effective doses varied from less than 0.001 to over 100 mSv. Only 5-7% of the total examinations consist of CT scans, the contribution of CT to the collective effective dose for the patient population, however, was 40-50%. Whereas simple radiographs constitute almost 84-89% of the number of examinations the contribution to the collective dose was only 2-11%.