Background: As guidelines endorse the use of computed tomography (CT) for examining coronary artery disease (CAD), it is important to compare the advantages and disadvantages of the novel photon counting detector CT (PCD-CT) technology with the established energy integrating detector CT (EID-CT). Purpose: To compare the image quality of coronary computed tomography angiography (CCTA) and the Agatston scores (AS) derived from EID-CT and PCD-CT. Material and Methods: In this prospective observational study, 28 patients underwent clinical calcium score and CCTA scans on an EID-CTand a PCD-CT scanner. CCTA images were qualitatively analyzed by five observers using visual grading characteristics. The correlation and agreement of the AS were assessed using Spearmans rank correlation and Bland-Altman plots. Results: This qualitative analyses demonstrated a high fraction of " good" or "excellent" ratings for the image criteria in both CT systems. The sharpness of the distal lumen and image quality regarding motion artifacts were rated significantly higher for EID-CT (P < 0.05). However, the sharpness of coronary calcification was rated significantly higher for PCD-CT (P < 0.05). Spearmans rank correlation and Bland-Altman plots showed good correlation (P = 0.95) and agreement regarding the AS between EID-CT and PCD-CT. Conclusion: Both CT systems exhibited high CCTA image quality. The sharpness of calcifications was rated significantly higher for PCD-CT. A good correlation was observed between the AS derived from the two systems.

Plain language summaryAssessing the blood flow inside the heart is important in diagnosis and treatment of various cardiovascular diseases, such as atrial fibrillation or heart failure. We developed a method to accurately track the motion of the heart walls over the course of a heartbeat in three-dimensional Computed Tomography (CT) images. Based on the motion, we calculated the amount of blood passing through the mitral valve and the left atrial appendage orifice, which are markers used in the diagnostic of heart failure and assessment of stroke risk in atrial fibrillation. The results agreed well with measurements from 4D flow MRI, an imaging technique that measures blood velocities. Our method could broaden the use of CT and make additional exams redundant. It can even be used to calculate the blood flow inside the heart. BackgroundCardiac time-resolved CT (4D-CT) acquisitions provide high quality anatomical images of the heart. However, some cardiac diseases require assessment of blood flow in the heart. Diastolic dysfunction, for instance, is diagnosed by measuring the flow through the mitral valve (MV), while in atrial fibrillation, the flow through the left atrial appendage (LAA) indicates the risk for thrombus formation. Accurate validated techniques to extract this information from 4D-CT have been lacking, however.MethodsTo measure the flow rate though the MV and the LAA from 4D-CT, we developed a motion tracking algorithm that performs a nonrigid deformation of the surface separating the blood pool from the myocardium. To improve the tracking of the LAA, this region was deformed separately from the left atrium and left ventricle. We compared the CT based flow with 4D flow and short axis MRI data from the same individual in 9 patients.ResultsFor the mitral valve flow, good agreement was found for the time span between the early and late diastolic peak flow (bias: &lt;0.1 s). The ventricular stroke volume is similar compared to short-axis MRI (bias 3 ml). There are larger differences in the diastolic peak flow rates, with a larger bias for the early flow rate than the late flow rate. The peak LAA outflow rate measured with both modalities matches well (bias: -6 ml/s).ConclusionsOverall, the developed algorithm provides accurate tracking of dynamic cardiac geometries resulting in similar flow rates at the MV and LAA compared to 4D flow MRI. Back et al. describe a motion tracking algorithm to measure the flow rate through the mitral valve (MV) and the left atrial appendage (LAA) from 4D-CT data. The developed algorithm provided accurate tracking of dynamic cardiac geometries resulting in similar flow rates at the MV and LAA to those measured by 4D flow MRI.

Purpose: To quantitatively and qualitatively assess the visibility of bone structures in the wrist on photon-counting detector computed tomography (PCD-CT) images compared to state-of-the-art energy-integrating de-tector CT (EID-CT).Method: Four human cadaveric wrist specimens were scanned with EID-CT and PCD-CT at identical CTDIvolof 12.2 mGy and with 6.1 mGy (half dose PCD-CT). Axial images were reconstructed using the thinnest possible slice thickness, i.e. 0.4 mm on EID-CT and 0.2 mm on PCD-CT, with the largest image matrix size possible using reconstruction kernels optimized for bone (EID-CT: Ur68, PCD-CT: Br92). Quantitative evaluation was performed to determine contrast-noise ratio (CNR) of bone/ fat, cortical and trabecular sharpness. An observer study using visual grading characteristics (VGC) analysis was performed by six observers to assess the visibility of nutrient canals, trabecular architecture, cortical bone and the general image quality.Results: At equal dose, images obtained with PCD-CT had 39 +/- 6 % lower CNR (p = 0.001), 71 +/- 57 % higher trabecular sharpness in the radius (p = 0.02) and 42 +/- 8 % (p &lt; 0.05) sharper cortical edges than those obtained with EID-CT. This was confirmed by VGC analysis showing a superior visibility of nutrient canals, trabeculae and cortical bone area under the curve (AUC) &gt; 0.89) for PCD-CT, even at half dose.Conclusions: Despite a lower CNR and increased noise, the trabecular and cortical sharpness were twofold higher with PCD-CT. Visual grading analysis demonstrated superior visibility of cortical bone, trabeculae, nutrient canals and an overall improved image quality with PCD-CT over EID-CT. At half dose, PCD-CT also yielded superior image quality, both in quantitative measures and as evaluated by radiologists.

Background and aims: Elevated body weight in adolescence is associated with early cardiovascular disease, but whether this association is traceable to weight in early adulthood, weight in midlife or to weight gain is not known. The aim of this study is to assess the risk of midlife coronary atherosclerosis being associated with body weight at age 20, body weight in midlife and body weight change.Methods: We used data from 25,181 participants with no previous myocardial infarction or cardiac procedure in the Swedish CArdioPulmonary bioImage Study (SCAPIS, mean age 57 years, 51% women). Data on coronary atherosclerosis, self-reported body weight at age 20 and measured midlife weight were recorded together with potential confounders and mediators. Coronary atherosclerosis was assessed using coronary computed tomog-raphy angiography (CCTA) and expressed as segment involvement score (SIS).Results: The probability of having coronary atherosclerosis was markedly higher with increasing weight at age 20 and with mid-life weight (p < 0.001 for both sexes). However, weight increase from age 20 until mid-life was only modestly associated with coronary atherosclerosis. The association between weight gain and coronary atherosclerosis was mainly seen in men. However, no significant sex difference could be detected when adjusting for the 10-year delay in disease development in women.Conclusions: Similar in men and women, weight at age 20 and weight in midlife are strongly related to coronary atherosclerosis while weight increase from age 20 until midlife is only modestly related to coronary atherosclerosis.

Introduction: Atrial fibrillation (AF) is associated with an increased risk of stroke, often caused by thrombi that form in the left atrium (LA), and especially in the left atrial appendage (LAA). The underlying mechanism is not fully understood but is thought to be related to stagnant blood flow, which might be present despite sinus rhythm. However, measuring blood flow and stasis in the LAA is challenging due to its small size and low velocities. We aimed to compare the blood flow and stasis in the left atrium of paroxysmal AF patients with controls using computational fluid dynamics (CFD) simulations.Methods : The CFD simulations were based on time-resolved computed tomography including the patient-specific cardiac motion. The pipeline allowed for analysis of 21 patients with paroxysmal AF and 8 controls. Stasis was estimated by computing the blood residence time.Results and Discussion: Residence time was elevated in the AF group (p &lt; 0.001). Linear regression analysis revealed that stasis was strongest associated with LA ejection ratio (p &lt; 0.001, R-2 = 0.68) and the ratio of LA volume and left ventricular stroke volume (p &lt; 0.001, R-2 = 0.81). Stroke risk due to LA thrombi could already be elevated in AF patients during sinus rhythm. In the future, patient specific CFD simulations may add to the assessment of this risk and support diagnosis and treatment.

Difficulties in achieving knowledge about physiology and anatomy of the beating heart highlight the challenges with more traditional pedagogical methods. Recent research regarding anatomy education has mainly focused on digital three-dimensional models. However, these pedagogical improvements may not be entirely applicable to cardiac anatomy and physiology due to the multidimensional complexity with moving anatomy and complex blood flow. The aim of this study was therefore to evaluate whether high quality time-resolved anatomical images combined with realistic blood flow simulations improve the understanding of cardiac structures and function. Three time-resolved datasets were acquired using time-resolved computed tomography and blood flow was computed using Computational Fluid Dynamics. The anatomical and blood flow information was combined and interactively visualized using volume rendering on an advanced stereo projection system. The setup was tested in interactive lectures for medical students. Ninety-seven students participated. Summative assessment of examinations showed significantly improved mean score (18.1 +/- 4.5 vs 20.3 +/- 4.9, p = 0.002). This improvement was driven by knowledge regarding myocardial hypertrophy and pressure-velocity differences over a stenotic valve. Additionally, a supplementary formative assessment showed significantly more agreeing answers than disagreeing answers (p &lt; 0.001) when the participants subjectively evaluated the contribution of the visualizations to their education and knowledge. In conclusion, the use of simultaneous visualization of time-resolved anatomy data and simulated blood flow improved medical students results, with a particular effect on understanding of cardiac physiology and these simulations may be useful educational tools for teaching complex anatomical and physiological concepts.

Background: Patients with type 2 diabetes have an increased risk of death and cardiovascular events and people with diabetes or prediabetes have been found to have increased atherosclerotic burden in the coronary and carotid arteries. This study will estimate the cross-sectional prevalence of atherosclerosis in the coronary and carotid arteries in individuals with prediabetes and diabetes, compared with normoglycaemic individuals in a large population-based cohort.Methods: The 30,154 study participants, 50-64 years, were categorized according to their fasting glycaemic status or self-reported data as normoglycaemic, prediabetes, and previously undetected or known diabetes. Prevalence of affected coronary artery segments, severity of stenosis and coronary artery calcium score (CACS) were determined by coronary computed tomography angiography. Total atherosclerotic burden was assessed in the 11 clinically most relevant segments using the Segment Involvement Score and as the presence of any coronary atherosclerosis. The presence of atherosclerotic plaque in the carotid arteries was determined by ultrasound examination.Results: Study participants with prediabetes (n = 4804, 16.0%) or diabetes (n = 2282, 7.6%) had greater coronary artery plaque burden, more coronary stenosis and higher CACS than normoglycaemic participants (all, p &lt; 0.01). Among male participants with diabetes 35.3% had CACS &gt;= 100 compared to 16.1% among normoglycaemic participants. For women, the corresponding figures were 8.9% vs 6.1%. The prevalence of atherosclerosis in the coronary arteries was higher in participants with previously undetected diabetes than prediabetes, but lower than in patients with known diabetes. The prevalence of any plaque in the carotid arteries was higher in participants with prediabetes or diabetes than in normoglycaemic participants.Conclusions: In this large population-based cohort of currently asymptomatic people, the atherosclerotic burden in the coronary and carotid arteries increased with increasing degree of dysglycaemia. The finding that the atherosclerotic burden in the coronary arteries in the undetected diabetes category was midway between the prediabetes category and patients with known diabetes may have implications for screening strategies and tailored prevention interventions for people with dysglycaemia in the future.

Purpose: To find the optimal imaging parameters for a photon-counting detector CT (PCD-CT) and to compare it to an energy-integrating detector CT (EID-CT) in terms of image quality and metal artefact severity using a metal-containing bovine knee specimen. Methods: A bovine knee with a stainless-steel plate and screws was imaged in a whole-body research PCD-CT at 120 kV and 140 kV and in an EID dual-source CT (DSCT) at Sn150 kV and 80/Sn150 kV. PCD-CT virtual monoenergetic 72 and 150 keV images and EID-CT images processed with and without metal artefact reduction algorithms (iMAR) were compared. Four radiologists rated the visualisation of bony structures and metal artefact severity. The Friedman test and Wilcoxon signed-rank test with Bonferronis correction were used. P-values of &lt;= 0.0001 were considered statistically significant. Distributions of HU values of regions of interest (ROIs) in artefact-affected areas were analysed.Results: PCD-CT 140 kV 150 keV images received the highest scores and were significantly better than EID-CT Sn150 kV images. PCD-CT 72 keV images were rated significantly lower than all the others. HU-value variation was larger in the 120 kV and the 72 keV images. The ROI analysis revealed no large difference between scanners regarding artefact severity.Conclusion: PCD-CT 140 kV 150 keV images of a metal-containing bovine knee specimen provided the best image quality. They were superior to, or as good as, the best EID-CT images; even without the presumed advantage of tin filter and metal artefact reduction algorithms. PCD-CT is a promising method for reducing metal artefacts.

Purpose: The aim of this study was to evaluate the effect of reconstruction parameters on image quality in wrist imaging using photon-counting detector CT (PCD-CT) and to compare the results with images from an energyintegrating detector CT (EID-CT). Methods: Twelve cadaveric wrist specimens were examined using a prototype PCD-CT and a clinical EID-CT using similar radiation dose. Reconstruction parameters were matched between scanners. Also, sharper reconstruction kernels, a larger matrix size, and smaller slice thicknesses were evaluated for PCD-CT. Image noise, contrast-tonoise ratio (CNR) and image sharpness in trabecular structures were quantitatively measured. Image quality with respect to the visibility of cortical and trabecular bone structures was assessed by six radiologists using visual grading methods.Results: Images obtained with PCD-CT had lower noise (42.6 +/- 3.9 HU vs 75.1 +/- 6.3 HU), higher CNR (38.9 +/- 4.5 vs 19.0 +/- 2.4) and higher trabecular sharpness (63.5 +/- 6.0 vs 53.7 +/- 8.5) than those obtained with EID-CT using similar scan and reconstruction parameters (p &lt; 0.001). The image sharpness in trabecular structures was further improved by using sharper kernels, despite higher noise levels. Radiologists had a strong preference for PCD-CT images both in terms of spatial resolution and suitability for bone imaging. Visual grading analysis showed an improved visibility of cortical bone, trabeculae and nutritive canals (p &lt; 0.005).Conclusion: PCD-CT offers improved image quality regarding bone structures in the wrist relative to EID-CT systems, particularly when sharper reconstruction kernels, smaller slice thickness and a larger image matrix size are used.

The purpose of this study was to compare the correlation and agreement between AS derived from either an energy-integrating detector CT (EID-CT) or a photon-counting detector CT (PCD-CT). Reproducibility was also compared. In total, 26 calcified coronary lesions (from five cadaveric hearts) were identified for inclusion. The hearts were positioned in a chest phantom and scanned in both an EID-CT and a prototype PCD-CT. The EID-CT and PCD-CT acquisition and reconstruction parameters were matched. To evaluate the reproducibility, the phantom was manually repositioned, and an additional scan was performed using both methods. The EID-CT reconstructions were performed using the dedicated calcium score kernel Sa36. The PCD-CT reconstructions were performed with a vendor-recommended kernel (Qr36). Several monoenergetic energy levels (50-150 keV) were evaluated to find the closest match with the EID-CT scans. A semi-automatic evaluation of calcium score was performed on a post-processing multimodality workplace. The best match with Sa36 was PCD-CT Qr36 images, at a monoenergetic level of 72 keV. Statistical analyses showed excellent correlation and agreement. The correlation and agreement with regards to the Agatston score (AS) between the two methods, for each position as well as between the two positions for each method, were assessed with the Spearman s rank correlation. The correlation coefficient, rho, was 0.98 and 0.97 respectively 0.99 and 0.98. The corresponding agreements were investigated by means of Bland-Altman plots. High correlation and agreement was observed between the AS derived from the EID-CT and a PCD-CT. Both methods also demonstrated excellent reproducibility.

Background and aims: Previous studies reported divergent results on whether metabolically healthy obesity is associated with increased coronary artery calcium and carotid plaques. We investigated this in a cross-sectional fashion in a large, well-defined, middle-aged population using coronary CT angiography (CCTA) and carotid ultrasound.Methods: In the SCAPIS study (50-65 years, 51% female), CCTA and carotid artery ultrasound were performed in 23,674 individuals without clinical atherosclerotic disease. These subjects were divided into six groups according to BMI (normal weight, overweight, obese) and the presence of metabolic syndrome (MetS) according to the NCEP consensus criteria.Results: The severity of coronary artery stenosis was increased in individuals with obesity without MetS compared to normal-weight individuals without MetS (OR 1.47, 95%CI 1.34-1.62; p &lt; 0.0001), even after adjusting for non-HDL-cholesterol and several lifestyle factors. Such difference was not observed for the presence of carotid artery plaques (OR 0.94, 95%CI 0.87-1.02; p = 0.11). Obese or overweight individuals without any MetS criteria (except the waist criterion) showed significantly more pronounced stenosis in the coronary arteries as compared to the normal-weight individuals, while one criterion was needed to show increased plaque prevalence in the carotid arteries. High blood pressure was the most important single criterion for increased atherosclerosis in this respect.Conclusions: Individuals with obesity without MetS showed increased severity of coronary artery stenosis, but no increased occurrence of carotid artery plaques compared to normal-weight individuals without MetS, further emphasizing that obesity is not a benign condition even in the absence of MetS.

Background: CT is often used for fracture evaluation following knee trauma and to diagnose ACL injuries would also be valuable. Purpose: To investigate the diagnostic accuracy of dual energy CT (DECT) for detection of ACL tears in acute and subacute knee injuries. Material and Methods: Patients with suspected ACL injury were imaged with DECT and MRI. Clinically blinded DECT images were independently read twice by two radiologists. ACL was classified as normal or abnormal. Arthroscopy served as reference method. Sensitivity and positive predictive value (PPV) were calculated, and diagnostic performance between DECT and MRI was assessed. Results: 48 patients (26 M, 22 F, mean age 23 years, range 15-37 years) were imaged with a mean of 25 days following trauma. Of these, 21 patients underwent arthroscopy with a mean of 195 days after trauma. Arthroscopy revealed 19 ACL tears and 2 ACLs with no tear. The combined sensitivity was 76.3% (95% CI 66.8-85.9) and 86.8 (95% CI 71.9-95.6) for DECT and MRI, respectively. There was no statistically significant difference between these two methods (p = .223). The positive predictive value (PPV) was 93.5 (95% CI 84.3-98.2) and 91.7 (95% CI 77.5-98.3) for DECT and MRI, respectively. Conclusion: DECT has lower sensitivity to detect an ACL rupture than MRI, but the difference is not statistically significant. The PPV is high in both methods.

Background Lesion/tissue segmentation on digital medical images enables biomarker extraction, image-guided therapy delivery, treatment response measurement, and training/validation for developing artificial intelligence algorithms and workflows. To ensure data reproducibility, criteria for standardised segmentation are critical but currently unavailable. Methods A modified Delphi process initiated by the European Imaging Biomarker Alliance (EIBALL) of the European Society of Radiology (ESR) and the European Organisation for Research and Treatment of Cancer (EORTC) Imaging Group was undertaken. Three multidisciplinary task forces addressed modality and image acquisition, segmentation methodology itself, and standards and logistics. Devised survey questions were fed via a facilitator to expert participants. The 58 respondents to Round 1 were invited to participate in Rounds 2-4. Subsequent rounds were informed by responses of previous rounds. Results/conclusions Items with &gt;= 75% consensus are considered a recommendation. These include system performance certification, thresholds for image signal-to-noise, contrast-to-noise and tumour-to-background ratios, spatial resolution, and artefact levels. Direct, iterative, and machine or deep learning reconstruction methods, use of a mixture of CE marked and verified research tools were agreed and use of specified reference standards and validation processes considered essential. Operator training and refreshment were considered mandatory for clinical trials and clinical research. Items with a 60-74% agreement require reporting (site-specific accreditation for clinical research, minimal pixel number within lesion segmented, use of post-reconstruction algorithms, operator training refreshment for clinical practice). Items with &lt;= 60% agreement are outside current recommendations for segmentation (frequency of system performance tests, use of only CE-marked tools, board certification of operators, frequency of operator refresher training). Recommendations by anatomical area are also specified.

A Correction to this paper has been published:

Traditional filtered back projection (FBP) reconstruction methods have served the computed tomography (CT) community wellfor over 40 years. With the increased use of CT during the last decades, efforts to minimise patient exposure, while maintainingsufficient or improved image quality, have led to the development of model-based iterative reconstruction (MBIR) algorithms fromseveral vendors. The usefulness of the advanced modeled iterative reconstruction (ADMIRE) (Siemens Healthineers) MBIR inabdominal CT is reviewed and its noise suppression and/or dose reduction possibilities explored. Quantitative and qualitativemethods with phantom and human subjects were used. Assessment of the quality of phantom images will not always correlatepositively with those of patient images, particularly at the higher strength of the ADMIRE algorithm. With few exceptions,ADMIRE Strength 3 typically allows for substantial noise reduction compared to FBP and hence to significant (≈30%) patientdose reductions. The size of the dose reductions depends on the diagnostic task.

Significant mitral valve regurgitation creates progressive adverse remodeling of the left ventricle (LV). Replacement of the failing valve with a prosthesis generally improves patient outcomes but leaves the patient with non-physiological intracardiac flow patterns that might contribute to their future risk of thrombus formation and embolism. It has been suggested that the angular orientation of the implanted valve might modify the postoperative distortion of the intraventricular flow field. In this study, we investigated the effect of prosthetic valve orientation on LV flow patterns by using heart geometry from a patient with LV dysfunction and a competent native mitral valve to calculate intracardiac flow fields with computational fluid dynamics (CFD). Results were validated using in vivo 4D Flow MRI. The computed flow fields were compared to calculations following virtual implantation of a mechanical heart valve oriented in four different angles to assess the effect of leaflet position. Flow patterns were visualized in longand short-axes and quantified with flow component analysis. In comparison to a native valve, valve implantation increased the proportion of the mitral inflow remaining in the basal region and further increased the residual volume in the apical area. Only slight changes due to valve orientation were observed. Using our numerical framework, we demonstrated quantitative changes in left ventricular blood flow due to prosthetic mitral replacement. This framework may be used to improve design of prosthetic heart valves and implantation procedures to minimize the potential for apical flow stasis, and potentially assist personalized treatment planning. (c) 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Objectives To compare the accuracy of coronary calcium quantification of cadaveric specimens imaged from a photon-counting detector (PCD)-CT and an energy-integrating detector (EID)-CT. Methods Excised coronary specimens were scanned on a PCD-CT scanner, using both the PCD and EID subsystems. The scanning and reconstruction parameters for EID-CT and PCD-CT were matched: 120 kV, 9.3-9.4 mGy CTDIvol, and a quantitative kernel (D50). PCD-CT images were also reconstructed using a sharper kernel (D60). Scanning the same specimens using micro-CT served as a reference standard for calcified volumes. Calcifications were segmented with a half-maximum thresholding technique. Segmented calcified volume differences were analyzed using the Friedman test and post hoc pairwise Wilcoxon signed rank test with the Bonferroni correction. Image noise measurements were compared between EID-CT and PCD-CT with a repeated-measures ANOVA test and post hoc pairwise comparison with the Bonferroni correction. A p &lt; 0.05 was considered statistically significant. Results The volume measurements in 12/13 calcifications followed a similar trend: EID-D50 &gt; PCD-D50 &gt; PCD-D60 &gt; micro-CT. The median calcified volumes in EID-D50, PCD-D50, PCD-D60, and micro-CT were 22.1 (IQR 10.2-64.8), 21.0 (IQR 9.0-56.5), 18.2 (IQR 8.3-49.3), and 14.6 (IQR 5.1-42.4) mm(3), respectively (p &lt; 0.05 for all pairwise comparisons). The average image noise in EID-D50, PCD-D50, and PCD-D60 was 60.4 (+/- 3.5), 56.0 (+/- 4.2), and 113.6 (+/- 8.5) HU, respectively (p &lt; 0.01 for all pairwise comparisons). Conclusion The PCT-CT system quantified coronary calcifications more accurately than EID-CT, and a sharp PCD-CT kernel further improved the accuracy. The PCD-CT images exhibited lower noise than the EID-CT images.

Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials.

Background: Compared with invasive fractional flow reserve (FFR), coronary CT angiography (cCTA) is limited in detecting hemodynamically relevant lesions. cCTA-based FFR (CT-FFR) is an approach to overcome this insufficiency by use of computational fluid dynamics. Applying recent innovations in computer science, a machine learning (ML) method for CT-FFR derivation was introduced and showed improved diagnostic performance compared to cCTA alone. We sought to investigate the influence of stenosis location in the coronary artery system on the performance of ML-CT-FFR in a large, multicenter cohort. Methods: Three hundred and thirty patients (75.2% male, median age 63 years) with 502 coronary artery stenoses were included in this substudy of the MACHINE (Machine Learning Based CT Angiography Derived FFR: A MultiCenter Registry) registry. Correlation of ML-CT-FFR with the invasive reference standard FFR was assessed and pooled diagnostic performance of ML-CT-FFR and cCTA was determined separately for the following stenosis locations: RCA, LAD, LCX, proximal, middle, and distal vessel segments. Results: ML-CT-FFR correlated well with invasive FFR across the different stenosis locations. Per-lesion analysis revealed improved diagnostic accuracy of ML-CT-FFR compared with conventional cCTA for stenoses in the RCA (71.8% [95% confidence interval, 63.0%-79.5%] vs. 54.8% [45.7%-63.8%]), LAD (79.3 [73.9-84.0] vs. 59.6 [53.5-65.6]), LCX (84.1 [76.0-90.3] vs. 63.7 [54.1-72.6]), proximal (81.5 [74.6-87.1] vs. 63.8 [55.9-71.2]), middle (81.2 [75.7-85.9] vs. 59.4 [53.0-65.6]) and distal stenosis location (67.4 [57.0-76.6] vs. 51.6 [41.1-62.0]). Conclusion: In a multicenter cohort with high disease prevalence, ML-CT-FFR offered improved diagnostic performance over cCTA for detecting hemodynamically relevant stenoses regardless of their location.

While the usefulness of 3D visualizations has been shown for a range of clinical applications such as treatment planning it still had difficulties in being adopted in widespread clinical practice. This chapter describes how multi-touch surfaces with patient-specific data have contributed to breaking this barrier, paving the way for adoption into clinical practice and, at the same time, also found widespread use in educational settings and in communication of science to the general public. The key element identified for this adoption is the string of steps found in the full imaging chain, which will be described as an introduction to the topic in this chapter. Emphasis in the chapter is, however, visualization aspects, e.g., intuitive interaction with patient-specific data captured with the latest high speed and high-quality imaging modalities. A necessary starting point for this discussion is the foundations of and state-of-the-art in volumetric rendering, which form the basis for the underlying theory part of the chapter. The chapter presents two use cases. One case is focusing on the use of multi-touch in medical education and the other is focusing on the use of touch surfaces at public venues, such as science centers and museums. 

Background: Early detection of coronary atherosclerosis using coronary computed tomography angiography (CCTA), in addition to coronary artery calcification (CAC) scoring, may help inform prevention strategies. We used CCTA to determine the prevalence, severity, and characteristics of coronary atherosclerosis and its association with CAC scores in a general population. Methods: We recruited 30 154 randomly invited individuals age 50 to 64 years to SCAPIS (the Swedish Cardiopulmonary Bioimage Study). The study includes individuals without known coronary heart disease (ie, no previous myocardial infarctions or cardiac procedures) and with high-quality results from CCTA and CAC imaging performed using dedicated dual-source CT scanners. Noncontrast images were scored for CAC. CCTA images were visually read and scored for coronary atherosclerosis per segment (defined as no atherosclerosis, 1% to 49% stenosis, or &gt;= 50% stenosis). External validity of prevalence estimates was evaluated using inverse probability for participation weighting and Swedish register data. Results: In total, 25 182 individuals without known coronary heart disease were included (50.6% women). Any CCTA-detected atherosclerosis was found in 42.1%; any significant stenosis (&gt;= 50%) in 5.2%; left main, proximal left anterior descending artery, or 3-vessel disease in 1.9%; and any noncalcified plaques in 8.3% of this population. Onset of atherosclerosis was delayed on average by 10 years in women. Atherosclerosis was more prevalent in older individuals and predominantly found in the proximal left anterior descending artery. Prevalence of CCTA-detected atherosclerosis increased with increasing CAC scores. Among those with a CAC score &gt;400, all had atherosclerosis and 45.7% had significant stenosis. In those with 0 CAC, 5.5% had atherosclerosis and 0.4% had significant stenosis. In participants with 0 CAC and intermediate 10-year risk of atherosclerotic cardiovascular disease according to the pooled cohort equation, 9.2% had CCTA-verified atherosclerosis. Prevalence estimates had excellent external validity and changed marginally when adjusted to the age-matched Swedish background population. Conclusions: Using CCTA in a large, random sample of the general population without established disease, we showed that silent coronary atherosclerosis is common in this population. High CAC scores convey a significant probability of substantial stenosis, and 0 CAC does not exclude atherosclerosis, particularly in those at higher baseline risk.

Background It is not clear if the European Systematic Coronary Risk Evaluation algorithm is useful for identifying prevalent subclinical atherosclerosis in a population of apparently healthy individuals. Our aim was to explore the association between the risk estimates from Systematic Coronary Risk Evaluation and prevalent subclinical atherosclerosis. Design The design of this study was as a cross-sectional analysis from a population-based study cohort. Methods From the general population, the Swedish Cardiopulmonary Bioimage Study randomly invited individuals aged 50-64 years and enrolled 13,411 participants mean age 57 (standard deviation 4.3) years; 46% males between November 2013-December 2016. Associations between Systematic Coronary Risk Evaluation risk estimates and coronary artery calcification and plaques in the carotid arteries by using imaging data from a computed tomography of the heart and ultrasonography of the carotid arteries were examined. Results Coronary calcification was present in 39.5% and carotid plaque in 56.0%. In men, coronary artery calcium score amp;gt;0 ranged from 40.7-65.9% and presence of carotid plaques from 54.5% to 72.8% in the age group 50-54 and 60-65 years, respectively. In women, the corresponding difference was from 17.1-38.9% and from 41.0-58.4%. A doubling of Systematic Coronary Risk Evaluation was associated with an increased probability to have coronary artery calcium score amp;gt;0 (odds ratio: 2.18 (95% confidence interval 2.07-2.30)) and to have amp;gt;1 carotid plaques (1.67 (1.61-1.74)). Conclusion Systematic Coronary Risk Evaluation estimated risk is associated with prevalent subclinical atherosclerosis in two major vascular beds in a general population sample without established cardiovascular disease or diabetes mellitus. Thus, the Systematic Coronary Risk Evaluation risk chart may be of use for estimating the risk of subclinical atherosclerosis.

Background A method for improving the accuracy of coronary computed tomography angiography (CCTA) is highly sought after as it would help to avoid unnecessary invasive coronary angiographies. Measurement of the transluminal attenuation gradient (TAG) has been proposed as an alternative to other existing methods, i.e. CT perfusion and CT fractional flow reserve (FFR). Purpose To evaluate the incremental value of three types of TAG in high-pitch spiral CCTA with invasive FFR measurements as reference. Material and Methods TAG was measured using two semi-automatic methods and one manual method. A receiver operating characteristic (ROC) analysis was made to determine the usefulness of TAG alone as well as TAG combined with CCTA for detection of significant coronary artery stenoses defined by an invasive FFR value &lt;= 0.80. Results A total of 51 coronary vessels in 37 patients were included in this retrospective study. Hemodynamically significant stenoses were found in 13 vessels according to FFR. The ROC analysis TAG alone resulted in areas under the curve (AUCs) of 0.530 and 0.520 for the semi-automatic TAG and 0.557 for the manual TAG. TAG and CCTA combined resulted in AUCs of 0.567, 0.562 for semi-automatic TAG, and 0.569 for the manual TAG. Conclusion The results from our study showed no incremental value of TAG measured in single heartbeat CCTA in determining the severity of coronary artery stenosis degrees.

Purpose: To determine the effect of tube load, model-based iterative reconstruction (MBIR) strength and slice thickness in abdominal CT using visual comparison of multi-planar reconstruction images. Method: Five image criteria were assessed independently by four radiologists on two data sets at 42- and 98-mAs tube loads for 25 patients examined on a 192-slice dual-source CT scanner. Effect of tube load, MBIR strength, slice thickness and potential dose reduction was estimated with Visual Grading Regression (VGR). Objective image quality was determined by measuring noise (SD), contrast-to-noise (CNR) ratio and noise-power spectra (NPS). Results: Comparing 42- and 98-mAs tube loads, improved image quality was observed as a strong effect of log tube load regardless of MBIR strength (p amp;lt; 0.001). Comparing strength 5 to 3, better image quality was obtained for two criteria (p amp;lt; 0.01), but inferior for liver parenchyma and overall image quality. Image quality was significantly better for slice thicknesses of 2mm and 3mm compared to 1mm, with potential dose reductions between 24%-41%. As expected, with decrease in slice thickness and algorithm strength, the noise power and SD (HU-values) increased, while the CNR decreased. Conclusion: Increasing slice thickness from 1 mm to 2 mm or 3 mm allows for a possible dose reduction. MBIR strength 5 shows improved image quality for three out of five criteria for 1 mm slice thickness. Increasing MBIR strength from 3 to 5 has diverse effects on image quality. Our findings do not support a general recommendation to replace strength 3 by strength 5 in clinical abdominal CT protocols. However, strength 5 may be used in task-based protocols.

Background Dual-energy computer tomography (DECT) can detect post-traumatic bone marrow lesions. Prospective studies of the knee with large numbers of participants and intra-observer agreement assessment are limited. Purpose To investigate the diagnostic accuracy of DECT in detecting bone marrow lesions as well as estimating the bone marrow lesion volume in patients with suspected anterior cruciate ligament trauma with magnetic resonance imaging (MRI) as reference standard. Material and Methods Forty-eight consecutive patients with suspected anterior cruciate ligament injury were imaged bilaterally with DECT within a mean of 25 days (range 4-55 days) following injury and MRI within seven days of DECT. Two readers analyzed DECT virtual non-calcium-blinded images. Consensus MRI was reference standard. Intra- and inter-observer agreement were determined using weighted kappa statistics. Sensitivity, specificity, and negative and positive predictive values were calculated. Bone marrow lesion volumes were measured; for comparison, intra-class correlation coefficient was used. Results The 48 patients (26 men, 22 women; mean age 23 years, age range 15-37 years) were imaged bilaterally yielding 52 knees with bone marrow lesions, of which 44 were in the femur and 41 were in the tibia. Intra- and inter-observer agreement to detect bone marrow lesions was moderate and fair to moderate (kappa 0.54-0.66, 95% confidence interval [CI] 0.39-0.80 and 0.37-0.41, 95% CI 0.20-0.57) and overall sensitivity and specificity were 70.1% and 69.1%, respectively. Positive and negative predictive values were 72.9% and 66.1%, respectively. Bone marrow lesion volumes showed excellent intra- and inter-observer agreement (0.83-0.91, 95% CI 0.74-0.94 and 0.76-0.78, 95% CI 0.57-0.87). Conclusion The diagnostic performance of DECT to detect bone marrow lesions in the subacutely injured knee was moderate with intra- and inter-observer agreement ranging from moderate to substantial and fair to moderate. Bone marrow lesion volume correlation was excellent.

Objectives

To evaluate an artificial intelligence (AI)–based, automatic coronary artery calcium (CAC) scoring software, using a semi-automatic software as a reference.

Methods

This observational study included 315 consecutive, non-contrast-enhanced calcium scoring computed tomography (CSCT) scans. A semi-automatic and an automatic software obtained the Agatston score (AS), the volume score (VS), the mass score (MS), and the number of calcified coronary lesions. Semi-automatic and automatic analysis time were registered, including a manual double-check of the automatic results. Statistical analyses were Spearman’s rank correlation coefficient (⍴), intra-class correlation (ICC), Bland Altman plots, weighted kappa analysis (κ), and Wilcoxon signed-rank test.

Results

The correlation and agreement for the AS, VS, and MS were ⍴ = 0.935, 0.932, 0.934 (p < 0.001), and ICC = 0.996, 0.996, 0.991, respectively (p < 0.001). The correlation and agreement for the number of calcified lesions were ⍴ = 0.903 and ICC = 0.977 (p < 0.001), respectively. The Bland Altman mean difference and 1.96 SD upper and lower limits of agreements for the AS, VS, and MS were − 8.2 (− 115.1 to 98.2), − 7.4 (− 93.9 to 79.1), and − 3.8 (− 33.6 to 25.9), respectively. Agreement in risk category assignment was 89.5% and κ = 0.919 (p < 0.001). The median time for the semi-automatic and automatic method was 59 s (IQR 35–100) and 36 s (IQR 29–49), respectively (p < 0.001).

Conclusions

There was an excellent correlation and agreement between the automatic software and the semi-automatic software for three CAC scores and the number of calcified lesions. Risk category classification was accurate but showing an overestimation bias tendency. Also, the automatic method was less time-demanding.

Key Points

• Coronary artery calcium (CAC) scoring is an excellent candidate for artificial intelligence (AI) development in a clinical setting.

• An AI-based, automatic software obtained CAC scores with excellent correlation and agreement compared with a conventional method but was less time-consuming.

OBJECTIVES

This study was conducted to investigate the influence of coronary artery calcium (CAC) score on the diagnostic performance of machine-learning-based coronary computed tomography (CT) angiography (cCTA)-derived fractional flow reserve (CT-FFR).

BACKGROUND

CT-FFR is used reliably to detect lesion-specific ischemia. Novel CT-FFR algorithms using machine-learning artificial intelligence techniques perform fast and require less complex computational fluid dynamics. Yet, influence of CAC score on diagnostic performance of the machine-learning approach has not been investigated.

METHODS

A total of 482 vessels from 314 patients (age 62.3 +/- 9.3 years, 77% male) who underwent cCTA followed by invasive FFR were investigated from the MACHINE (Machine Learning based CT Angiography derived FFR: a Multi-center Registry) registry data. CAC scores were quantified using the Agatston convention. The diagnostic performance of CT-FFR to detect lesion-specific ischemia was assessed across all Agatston score categories (CAC 0, >0 to <100, 100 to <400, and >=$400) on a per-vessel level with invasive FFR as the reference standard.

RESULTS

The diagnostic accuracy of CT-FFR versus invasive FFR was superior to cCTA alone on a per-vessel level (78% vs. 60%) and per patient level (83% vs. 73%) across all Agatston score categories. No statistically significant differences in the diagnostic accuracy, sensitivity, or specificity of CT-FFR were observed across the categories. CT-FFR showed good discriminatory power in vessels with high Agatston scores (CAC >= 400) and high performance in low-to-intermediate Agatston scores (CAC >0 to <400) with a statistically significant difference in the area under the receiver-operating characteristic curve (AUC) (AUC: 0.71 [95% confidence interval (CI): 0.57 to 0.85] vs. 0.85 [95% CI: 0.82 to 0.89], p = 0.04). CT-FFR showed superior diagnostic value over cCTA in vessels with high Agatston scores (CAC >= 400: AUC 0.71 vs. 0.55, p = 0.04) and low-to-intermediate Agatston scores (CAC >0 to <400: AUC 0.86 vs. 0.63, p < 0.001).

CONCLUSIONS

Machine-learning-based CT-FFR showed superior diagnostic performance over cCTA alone in CAC with a significant difference in the performance of CT-FFR as calcium burden/Agatston calcium score increased. (Machine Learning Based CT Angiography Derived FFR: a Multicenter, Registry [MACHINE] NCT02805621). (C) 2020 by the American College of Cardiology Foundation.

Coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) is a noninvasive application to evaluate the hemodynamic impact of coronary artery disease by simulating invasively measured FFR based on CT data. CT-FFR is based on the assumption of a normal coronary microvascular response. We assessed the diagnostic performance of a machine-learning based application for on-site computation of CT-FFR in patients with and without diabetes mellitus with suspected coronary artery disease. The study population included 75 diabetic and 276 nondiabetic patients who were enrolled in the MACHINE consortium. The overall diagnostic performance of coronary CT angiography alone and in combination with CT-FFR were analyzed with direct invasive FFR comparison in 110 coronary vessels of the diabetic group and in 415 coronary vessels of the nondiabetic group. Per-vessel discrimination of lesion-specific ischemia by CT-FFR was assessed by the area under the receiver operating characteristic curves. The overall diagnostic accuracy of CT-FFR in diabetic patients was 83% and in nondiabetic patients 75% (p = 0.088), showing improvement over the diagnostic accuracy of coronary CT angiography, which was 58% and 65% (p = 0.223), respectively. In addition, the diagnostic accuracy of CT-FFR was similar between diabetic and nondiabetic patients per stratified CT-FFR group (CT-FFR amp;lt; 0.6, 0.6 to 0.69, 0.7 to 0.79, 0.8 to 0.89, amp;gt;= 0.9). The area under the curves for diabetic and nondiabetic patients were also comparable, 0.88 and 0.82 (p = 0.113), respectively. In conclusion, on-site machine-learning CT-FFR analysis improved the diagnostic performance of coronary CT angiography and accurately discriminated lesion-specific ischemia in both diabetic and nondiabetic patients suspected of coronary artery disease. (C) 2018 Elsevier Inc. All rights reserved.

OBJECTIVE. Coronary CT angiography (CCTA)-based methods allow noninvasive estimation of fractional flow reserve (cFFR), recently through use of a machine learning (ML) algorithm (cFFR(ML)). However, attenuation values vary according to the tube voltage used, and it has not been shown whether this significantly affects the diagnostic performance of cFFR and cFFR(ML). Therefore, the purpose of this study is to retrospectively evaluate the effect of tube voltage on the diagnostic performance of cFFR(ML). MATERIALS AND METHODS. A total of 525 coronary vessels in 351 patients identified in the MACHINE consortium registry were evaluated in terms of invasively measured FFR and cFFR(ML). CCTA examinations were performed with a tube voltage of 80, 100, or 120 kVp. For each tube voltage value, correlation (assessed by Spearman rank correlation coefficient), agreement (evaluated by intraclass correlation coefficient and Bland-Altman plot analysis), and diagnostic performance (based on ROC AUC value, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy) of the cFFR(ML) in terms of detection of significant stenosis were calculated. RESULTS. For tube voltages of 80, 100, and 120 kVp, the Spearman correlation coefficient for cFFR(ML) in relation to the invasively measured FFR value was rho = 0.684, rho = 0.622, and rho = 0.669, respectively (p amp;lt; 0.001 for all). The corresponding intraclass correlation coefficient was 0.78, 0.76, and 0.77, respectively (p amp;lt; 0.001 for all). Sensitivity was 100.0%, 73.5%, and 85.0%, and specificity was 76.2%, 79.0%, and 72.8% for tube voltages of 80, 100, and 120 kVp, respectively. The ROC AUC value was 0.90, 0.82, and 0.80 for 80, 100, and 120 kVp, respectively (p amp;lt; 0.001 for all). CONCLUSION. CCTA-derived cFFR(ML) is a robust method, and its performance does not vary significantly between examinations performed using tube voltages of 100 kVp and 120 kVp. However, because of rapid advancements in CT and postprocessing technology, further research is needed.

Purpose: This study investigated the impact of gender differences on the diagnostic performance of machine-learning based coronary CT angiography (cCTA)-derived fractional flow reserve (CT-FFR mL ) for the detection of lesion-specific ischemia. Method: Five centers enrolled 351 patients (73.5% male) with 525 vessels in the MACHINE (Machine leArning Based CT angiograpHy derIved FFR: a Multi-ceNtEr) registry. CT-FFRML and invasive FFR amp;lt;= 0.80 were considered hemodynamically significant, whereas cCTA luminal stenosis amp;gt;= 50% was considered obstructive. The diagnostic performance to assess lesion-specific ischemia in both men and women was assessed on a per-vessel basis. Results: In total, 398 vessels in men and 127 vessels in women were included. Compared to invasive FFR, CT-FFRML reached a sensitivity, specificity, positive predictive value, and negative predictive value of 78% (95%CI 72-84), 79% (95%CI 73-84), 75% (95%CI 69-79), and 82% (95%CI: 76-86) in men vs. 75% (95%CI 58-88), 81 (95%CI 72-89), 61% (95%CI 50-72) and 89% (95%CI 82-94) in women, respectively. CT-FFRML showed no statistically significant difference in the area under the receiver-operating characteristic curve (AUC) in men vs. women (AUC: 0.83 [95%CI 0.79-0.87] vs. 0.83 [95%CI 0.75-0.89], p = 0.89). CT-FFRML was not superior to cCTA alone [AUC: 0.83 (95%CI: 0.75-0.89) vs. 0.74 (95%CI: 0.65-0.81), p = 0.12] in women, but showed a statistically significant improvement in men [0.83 (95%CI: 0.79-0.87) vs. 0.76 (95%CI: 0.71-0.80), p = 0.007]. Conclusions: Machine-learning based CT-FFR performs equally in men and women with superior diagnostic performance over cCTA alone for the detection of lesion-specific ischemia.

Background

Our aim was to compare CT images from native, nephrographic and excretory phases using image quality criteria as well as the detection of positive pathological findings in CT Urography, to explore if the radiation burden to the younger group of patients or patients with negative outcomes can be reduced.

Methods

This is a retrospective study of 40 patients who underwent a CT Urography examination on a 192-slice dual source scanner. Image quality was assessed for four specific renal image criteria from the European guidelines, together with pathological assessment in three categories: renal, other abdominal, and incidental findings without clinical significance. Each phase was assessed individually by three radiologists with varying experience using a graded scale. Certainty scores were derived based on the graded assessments. Statistical analysis was performed using visual grading regression (VGR). The limit for significance was set at p = 0.05.

Results

For visual reproduction of the renal parenchyma and renal arteries, the image quality was judged better for the nephrogram phase (p < 0.001), whereas renal pelvis/calyces and proximal ureters were better reproduced in the excretory phase compared to the native phase (p < 0.001). Similarly, significantly higher certainty scores were obtained in the nephrogram phase for renal parenchyma and renal arteries, but in the excretory phase for renal pelvis/calyxes and proximal ureters. Assessment of pathology in the three categories showed no statistically significant differences between the three phases. Certainty scores for assessment of pathology, however, showed a significantly higher certainty for renal pathology when comparing the native phase to nephrogram and excretory phase and a significantly higher score for nephrographic phase but only for incidental findings.

Conclusion

Visualisation of renal anatomy was as expected with each post-contrast phase showing favourable scores compared to the native phase. No statistically significant differences in the assessment of pathology were found between the three phases. The low-dose CT (LDCT) seems to be sufficient in differentiating between normal and pathological examinations. To reduce the radiation burden in certain patient groups, the LDCT could be considered a suitable alternative as a first line imaging method. However, radiologists should be aware of its limitations.

Background

Elevated body weight in adolescence is strongly associated with early cardiovascular disease, but whether this association is traceable to weight in early adulthood, or to weight gain with subsequent high adult weight is not known. Using data from the Swedish CArdioPulmonary bioImage Study (SCAPIS), we investigated the association between weight at age 20, weight gain to midlife and coronary artery calcium score (CACS) at midlife.

Methods

In the first 15,810 participants in SCAPIS (mean age 58 years, 52% women), data on CACS at midlife, self-reported body weight at age 20 and weight at examination in SCAPIS were recorded.

Results

CACS in midlife was significantly higher with increasing weight at age 20 (p<0.001 for both sexes), and then increased with weight gain until midlife at all levels of body weight at age 20 after adjusting for age, height, smoking, alcohol intake, education level, exercise levels and LDL cholesterol. However, the association with weight gain was only significant in men (p = 0.047), not in women (p=0.474). No significant interaction was seen between weight at age 20 and midlife weight with CACS. The effect of weight at age 20 on CACS was significantly more marked in men than in women, as was the effect of weight gain (p<0.001 for both interactions).

Conclusion

Weight at age 20 and weight gain to midlife were both related to CACS, but much more markedly so in men than in women, indicating a generally larger effect of both early adult weight and further weight gain until midlife on CACS in men, compared to women.

Blood flow simulations are making their way into the clinic, and much attention is given to estimation of fractional flow reserve in coronary arteries. Intracardiac blood flow simulations also show promising results, and here the flow field is expected to depend on the pulmonary venous (PV) flow rates. In the absence of in vivo measurements, the distribution of the flow from the individual PVs is often unknown and typically assumed. Here, we performed intracardiac blood flow simulations based on time-resolved computed tomography on three patients, and investigated the effect of the distribution of PV flow rate on the flow field in the left atrium and ventricle. A design-of-experiment approach was used, where PV flow rates were varied in a systematic manner. In total 20 different simulations were performed per patient, and compared to in vivo 4D flow MRI measurements. Results were quantified by kinetic energy, mitral valve velocity profiles and root-mean-square errors of velocity. While large differences in atrial flow were found for varying PV inflow distributions, the effect on ventricular flow was negligible, due to a regularizing effect by mitral valve. Equal flow rate through all PVs most closely resembled in vivo measurements and is recommended in the absence of a priori knowledge.

Background Coronary computed tomography angiography (CCTA) is increasingly used to detect coronary artery disease (CAD), but long-term follow-up studies are still scarce. Purpose To evaluate the prognostic value of CCTA in patients with suspected CAD. Material and Methods A total of 1205 consecutive CCTA patients with chest pain were classified as normal coronary arteries, non-obstructive CAD, or obstructive CAD. The primary outcome was major adverse cardiac event (MACE), defined as a composite outcome including cardiac death, myocardial infarction, unstable angina pectoris, or late revascularization (after >90 days). Results Over 7.5 years follow-up (median = 3.1 years), Kaplan-Meier estimates demonstrated a MACE in 1.0%, 4.6%, and 20.7% in normal coronary arteries, non-obstructive CAD, and obstructive CAD, respectively. Log rank test for pairwise comparisons showed significant differences between non-obstructive CAD and normal coronary arteries ( P = 0.023) and between obstructive CAD and normal coronary arteries ( P < 0.001). In a multivariable analysis, adjusting for classical risk factors, non-obstructive CAD and obstructive CAD were independent predictors of MACE, with hazard ratios (HR) of 3.22 ( P = 0.041) and 25.18 ( P < 0.001), respectively. Conclusion Patients with normal coronary arteries have excellent long-term prognosis, but the risk for MACE increases with non-obstructive and obstructive CAD. Both non-obstructive and obstructive CAD are independently associated with future ischemic events.

Despite very rapid changes in the Palestinian-Israeli conflict and throughout the Middle East, the EU continues to support a two-state solution. During the 1970s, the member states of the European Community jointly developed this approach as a pioneering concept for a just peace in the Middle East. Today, the EUs Middle East policy is on the verge of becoming irrelevant. Furthermore, the member states are finding it increasingly difficult to agree on a common position. However, those that criticise the continued adherence to the two-state solution offer no alternative concepts for peace in the Middle East. The EU would therefore be wise, with its new concept of resilience, not throw what is regarded as being the right approach overboard.

Observer-driven pattern recognition is the standard for interpretation of medical images. To achieve global parity in interpretation, semi-quantitative scoring systems have been developed based on observer assessments; these are widely used in scoring coronary artery disease, the arthritides and neurological conditions and for indicating the likelihood of malignancy. However, in an era of machine learning and artificial intelligence, it is increasingly desirable that we extract quantitative biomarkers from medical images that inform on disease detection, characterisation, monitoring and assessment of response to treatment. Quantitation has the potential to provide objective decision-support tools in the management pathway of patients. Despite this, the quantitative potential of imaging remains under-exploited because of variability of the measurement, lack of harmonised systems for data acquisition and analysis, and crucially, a paucity of evidence on how such quantitation potentially affects clinical decision-making and patient outcome. This article reviews the current evidence for the use of semi-quantitative and quantitative biomarkers in clinical settings at various stages of the disease pathway including diagnosis, staging and prognosis, as well as predicting and detecting treatment response. It critically appraises current practice and sets out recommendations for using imaging objectively to drive patient management decisions.

Purpose To estimate potential dose reduction in abdominal CT by visually comparing images reconstructed with filtered back projection (FBP) and strengths of 3 and 5 of a specific MBIR.

Material and methods A dual-source scanner was used to obtain three data sets each for 50 recruited patients with 30, 70 and 100% tube loads (mean CTDIvol 1.9, 3.4 and 6.2 mGy). Six image criteria were assessed independently by five radiologists. Potential dose reduction was estimated with Visual Grading Regression (VGR).

Results Comparing 30 and 70% tube load, improved image quality was observed as a significant strong effect of log tube load and reconstruction method with potential dose reduction relative to FBP of 22–47% for MBIR strength 3 (p < 0.001). For MBIR strength 5 no dose reduction was possible for image criteria 1 (liver parenchyma), but dose reduction between 34 and 74% was achieved for other criteria. Interobserver reliability showed agreement of 71–76% (κw 0.201–0.286) and intra-observer reliability of 82–96% (κw 0.525–0.783).

Conclusion MBIR showed improved image quality compared to FBP with positive correlation between MBIR strength and increasing potential dose reduction for all but one image criterion.

Background Assessment of myocardial deformation from time-resolved cardiac computed tomography (4D CT) would augment the already available functional information from such an examination without incurring any additional costs. A deformable image registration (DIR) based approach is proposed to allow fast and automatic myocardial tracking in clinical 4D CT images.

Methods Left ventricular myocardial tissue displacement through a cardiac cycle was tracked using a B-spline transformation based DIR. Gradient of such displacements allowed Lagrangian strain estimation with respect to end-diastole in clinical 4D CT data from ten subjects with suspected coronary artery disease. Dice similarity coefficient (DSC), point-to-curve error (PTC), and tracking error were used to assess the tracking accuracy. Wilcoxon signed rank test provided significance of tracking errors. Topology preservation was verified using Jacobian of the deformation. Reliability of estimated strains and torsion (normalized twist angle) was tested in subjects with normal function by comparing them with normal strain in the literature.

Results Comparison with manual tracking showed high accuracy (DSC: 0.99± 0.05; PTC: 0.56mm± 0.47 mm) and resulted in determinant(Jacobian) > 0 for all subjects, indicating preservation of topology. Average radial (0.13 mm), angular (0.64) and longitudinal (0.10 mm) tracking errors for the entire cohort were not significant (p > 0.9). For patients with normal function, average strain [circumferential, radial, longitudinal] and peak torsion estimates were: [-23.5%, 31.1%, −17.2%] and 7.22°, respectively. These estimates were in conformity with the reported normal ranges in the existing literature.

Conclusions Accurate wall deformation tracking and subsequent strain estimation are feasible with the proposed method using only routine time-resolved 3D cardiac CT.

Background: Coronary computed tomographic angiography (CTA) is a reliable modality to detect coronary artery disease. However, CTA generally overestimates stenosis severity compared with invasive angiography, and angiographic stenosis does not necessarily imply hemodynamic relevance when fractional flow reserve (FFR) is used as reference. CTA-based FFR (CT-FFR), using computational fluid dynamics (CFD), improves the correlation with invasive FFR results but is computationally demanding. More recently, a new machine-learning (ML) CT-FFR algorithm has been developed based on a deep learning model, which can be performed on a regular workstation. In this large multicenter cohort, the diagnostic performance ML-based CT-FFR was compared with CTA and CFD-based CT-FFR for detection of functionally obstructive coronary artery disease. Methods and Results: At 5 centers in Europe, Asia, and the United States, 351 patients, including 525 vessels with invasive FFR comparison, were included. ML-based and CFD-based CT-FFR were performed on the CTA data, and diagnostic performance was evaluated using invasive FFR as reference. Correlation between ML-based and CFD-based CT-FFR was excellent (R=0.997). ML-based (area under curve, 0.84) and CFD-based CT-FFR (0.84) outperformed visual CTA (0.69; Pamp;lt;0.0001). On a per-vessel basis, diagnostic accuracy improved from 58% (95% confidence interval, 54%-63%) by CTA to 78% (75%-82%) by ML-based CT-FFR. The per-patient accuracy improved from 71% (66%-76%) by CTA to 85% (81%-89%) by adding ML-based CT-FFR as 62 of 85 (73%) false-positive CTA results could be correctly reclassified by adding ML-based CT-FFR. Conclusions: On-site CT-FFR based on ML improves the performance of CTA by correctly reclassifying hemodynamically nonsignificant stenosis and performs equally well as CFD-based CT-FFR.

Purpose

To investigate four-dimensional (4D) flow CT for the assessment of intracardiac blood flow patterns as compared with 4D flow MRI.

Materials and Methods

This prospective study acquired coronary CT angiography and 4D flow MRI data between February and December 2016 in a cohort of 12 participants (age range, 36–74 years; mean age, 57 years; seven men [age range, 36–74 years; mean age, 57 years] and five women [age range, 52–73 years; mean age, 64 years]). Flow simulations based solely on CT-derived cardiac anatomy were assessed together with 4D flow MRI measurements. Flow patterns, flow rates, stroke volume, kinetic energy, and flow components were quantified for both techniques and were compared by using linear regression.

Results

Cardiac flow patterns obtained by using 4D flow CT were qualitatively similar to 4D flow MRI measurements, as graded by three independent observers. The Cohen κ score was used to assess intraobserver variability (0.83, 0.79, and 0.70) and a paired Wilcoxon rank-sum test showed no significant change (P > .05) between gradings. Peak flow rate and stroke volumes between 4D flow MRI measurements and 4D flow CT measurements had high correlation (r = 0.98 and r = 0.81, respectively; P < .05 for both). Integrated kinetic energy quantified at peak systole correlated well (r = 0.95, P < .05), while kinetic energy levels at early and late filling showed no correlation. Flow component analysis showed high correlation for the direct and residual components, respectively (r = 0.93, P < .05 and r = 0.87, P < .05), while the retained and delayed components showed no correlation.

Conclusion

Four-dimensional flow CT produced qualitatively and quantitatively similar intracardiac blood flow patterns compared with the current reference standard, four-dimensional flow MRI.

Educators must select the best tools to teach anatomy to future physicians and traditionally, cadavers have always been considered the "gold standard" simulator for living anatomy. However, new advances in technology and radiology have created new teaching tools, such as virtual dissection, which provide students with new learning opportunities. Virtual dissection is a novel way of studying human anatomy through patient computed tomography (CT) scans. Through touchscreen technology, students can work together in groups to "virtually dissect" the CT scans to better understand complex anatomic relationships. This article presents the anatomic and pedagogic limitations of cadaveric dissection and explains what virtual dissection is and how this new technology may be used to overcome these limitations.

The goal of the present study was to evaluate if quantitative postmortem cardiac 3-T magnetic resonance (QPMCMR) T1 and T2 relaxation times and proton density values of histopathological early acute and chronic myocardial infarction differ to the quantitative values of non-pathologic myocardium and other histopathological age stages of myocardial infarction with regard to varying corpse temperatures. In 60 forensic corpses (25 female, 35 male), a cardiac 3-T MR quantification sequence was performed prior to autopsy and cardiac dissection. Core body temperature was assessed during MR examinations. Focal myocardial signal alterations in synthetically generated MR images were measured for their T1, T2, and proton density (PD) values. Locations of signal alteration measurements in PMCMR were targeted at heart dissection, and myocardial tissue specimens were taken for histologic examinations. Quantified signal alterations in QPMCMR were correlated to their according histologic age stage of myocardial infarction, and quantitative values were corrected for a temperature of 37 A degrees C. In QPMCMR, 49 myocardial signal alterations were detected in 43 of 60 investigated hearts. Signal alterations were diagnosed histologically as early acute (n = 16), acute (n = 10), acute with hemorrhagic component (n = 9), subacute (n = 3), and chronic (n = 11) myocardial infarction. Statistical analysis revealed that based on their temperature-corrected quantitative T1, T2, and PD values, a significant difference between early acute, acute, and chronic myocardial infarction can be determined. It can be concluded that quantitative 3-T postmortem cardiac MR based on temperature-corrected T1, T2, and PD values may be feasible for pre-autopsy diagnosis of histopathological early acute, acute, and chronic myocardial infarction, which needs to be confirmed histologically.

In this study, cardiac blood flow was simulated using Computational Fluid Dynamics and compared to in vivo flow measurements by 4D Flow MRI. In total, nine patients with various heart diseases were studied. Geometry and heart wall motion for the simulations were obtained from clinical CT measurements, with 0.3x0.3x0.3 mm spatial resolution and 20 time frames covering one heartbeat. The CFD simulations included pulmonary veins, left atrium and ventricle, mitral and aortic valve, and ascending aorta. Mesh sizes were on the order of 6-16 million cells, depending on the size of the heart, in order to resolve both papillary muscles and trabeculae. The computed flow field agreed visually very well with 4D Flow MRI, with characteristic vortices and flow structures seen in both techniques. Regression analysis showed that peak flow rate as well as stroke volume had an excellent agreement for the two techniques. We demonstrated the feasibility, and more importantly, fidelity of cardiac flow simulations by comparing CFD results to in vivo measurements. Both qualitative and quantitative results agreed well with the 4D Flow MRI measurements. Also, the developed simulation methodology enables “what if” scenarios, such as optimization of valve replacement and other surgical procedures.

Recently, quantitative MR sequences have started being used in post-mortem imaging. The goal of the present study was to evaluate if early acute and following age stages of myocardial infarction can be detected and discerned by quantitative 1.5 T post-mortem cardiac magnetic resonance (PMCMR) based on quantitative T1, T2 and PD values. In 80 deceased individuals (25 female, 55 male), a cardiac MR quantification sequence was performed prior to cardiac dissection at autopsy in a prospective study. Focal myocardial signal alterations detected in synthetically generated MR images were MR quantified for their T1, T2 and PD values. The locations of signal alteration measurements in PMCMR were targeted at autopsy heart dissection and cardiac tissue specimens were taken for histologic examinations. Quantified signal alterations in PMCMR were correlated to their according histologic age stage of myocardial infarction. In PMCMR seventy-three focal myocardial signal alterations were detected in 49 of 80 investigated hearts. These signal alterations were diagnosed histologically as early acute (n = 39), acute (n = 14), subacute (n = 10) and chronic (n = 10) age stages of myocardial infarction. Statistical analysis revealed that based on their quantitative T1, T2 and PD values, a significant difference between all defined age groups of myocardial infarction can be determined. It can be concluded that quantitative 1.5 T PMCMR quantification based on quantitative T1, T2 and PD values is feasible for characterization and differentiation of early acute and following age stages of myocardial infarction. (C) 2016 Elsevier Ireland Ltd. All rights reserved.

Background Postmortem imaging has been used for more than a century as a complement to medico-legal autopsies. The technique has also emerged as a possible alternative to compensate for the continuous decline in the number of clinical autopsies. To evaluate the diagnostic accuracy of postmortem imaging for various types of findings, we performed this systematic literature review. Data sources The literature search was performed in the databases PubMed, Embase and Cochrane Library through January 7, 2015. Relevant publications were assessed for risk of bias using the QUADAS tool and were classified as low, moderate or high ris