Managing Iatrogenic Aortic Dissection: Insight from 3D-holographic Imaging and CT Computational Fluid Dynamic Simulations.

Iatrogenic aortic dissection is a rare but life-threatening complication of coronary artery bypass surgery. We report a case with incidentally detected iatrogenic aortic dissection related to aorta cross-clamping successfully managed with watchful follow-up. The decision-making was based on 3D hologram and fluid dynamic analysis guidance.

Opportunistic screening for osteoporosis using routine clinical care computed tomography brain studies.

OBJECTIVE: Osteoporosis and falls are both prevalent in the elderly, and CT brain (CTB) is frequently performed post head-strike. We aim to validate the relationship between frontal bone density (Hounsfield unit) from routine CTB and bone mineral density from dual-energy X-ray absorptiometry (DEXA) scan for opportunistic osteoporosis screening. MATERIALS AND METHODS: Patients who had a non-contrast CTB followed by a DEXA scan in the subsequent year were included in this multi-center retrospective study. The relationship between frontal bone density on CT and femoral neck T-score on DEXA was examined using ANOVA, Pearson's correlation, and receiver operating curve (ROC) analysis. Sensitivity, specificity, negative and positive predictive values, and area under the curve (AUC) were calculated. RESULTS: Three hundred twenty-six patients (205 females and 121 males) were analyzed. ANOVA analysis showed that frontal bone density was lower in patients with DEXA-defined osteoporosis (p < 0.001), while Pearson's correlation analysis demonstrated a fair correlation with femoral neck T-score (r = 0.3, p < 0.001). On subgroup analysis, these were true in females but not in males. On ROC analysis, frontal bone density weakly predicted osteoporosis (AUC 0.6, 95% CI 0.5-0.7) with no optimal threshold identified. HU < 610 was highly specific (87.5%) but poorly sensitive (18.9%). HU > 1200 in females had a strong negative predictive value for osteoporosis (92.6%, 95% CI 87.1-98.1%). CONCLUSION: Frontal bone density from routine CTB is significantly different between females with and without osteoporosis, but not between males. However, frontal bone density was a weak predictor for DEXA-defined osteoporosis. Further research is required to determine the role of CTB in opportunistic osteoporosis screening.

Automated inversion time selection for late gadolinium-enhanced cardiac magnetic resonance imaging.

OBJECTIVES: To develop and share a deep learning method that can accurately identify optimal inversion time (TI) from multi-vendor, multi-institutional and multi-field strength inversion scout (TI scout) sequences for late gadolinium enhancement cardiac MRI. MATERIALS AND METHODS: Retrospective multicentre study conducted on 1136 1.5-T and 3-T cardiac MRI examinations from four centres and three scanner vendors. Deep learning models, comprising a convolutional neural network (CNN) that provides input to a long short-term memory (LSTM) network, were trained on TI scout pixel data from centres 1 to 3 to identify optimal TI, using ground truth annotations by two readers. Accuracy within 50 ms, mean absolute error (MAE), Lin's concordance coefficient (LCCC) and reduced major axis regression (RMAR) were used to select the best model from validation results, and applied to holdout test data. Robustness of the best-performing model was also tested on imaging data from centre 4. RESULTS: The best model (SE-ResNet18-LSTM) produced accuracy of 96.1%, MAE 22.9 ms and LCCC 0.47 compared to ground truth on the holdout test set and accuracy of 97.3%, MAE 15.2 ms and LCCC 0.64 when tested on unseen external (centre 4) data. Differences in vendor performance were observed, with greatest accuracy for the most commonly represented vendor in the training data. CONCLUSION: A deep learning model was developed that can identify optimal inversion time from TI scout images on multi-vendor data with high accuracy, including on previously unseen external data. We make this model available to the scientific community for further assessment or development. CLINICAL RELEVANCE STATEMENT: A robust automated inversion time selection tool for late gadolinium-enhanced imaging allows for reproducible and efficient cross-vendor inversion time selection. KEY POINTS: • A model comprising convolutional and recurrent neural networks was developed to extract optimal TI from TI scout images. • Model accuracy within 50 ms of ground truth on multi-vendor holdout and external data of 96.1% and 97.3% respectively was achieved. • This model could improve workflow efficiency and standardise optimal TI selection for consistent LGE imaging.

Enhancing pre-transplant cardiac assessment: Validation and utility of the CAD-LT score with CCTA in liver transplant candidates.

BACKGROUND: Coronary computed tomography angiography (CCTA) is increasingly being used in the preoperative workup for liver transplantation (LT). We sought to assess the utility of integrating CCTA with the novel CAD-LT (Coronary Artery Disease in Liver Transplantation) score and its impact on reducing the need for invasive coronary angiography prior to LT. METHODS: We conducted a retrospective cohort study of consecutive patients (age ≥ 18 years) who underwent CCTA for LT workup between 2011 and 2018 at the Victorian Liver Transplant Unit, Melbourne, Australia. CAD-LT scores, a traditional risk factor-based criteria, were calculated, and patients stratified as low-, intermediate- or high-risk. RESULTS: Overall, 229 patients underwent CCTA. The mean age was 66 ± 5 years (82% male) with a modest-to-high risk factor burden (diabetes, 53%; hypertension, 46%; current or former smoker, 62%). The mean CAD-LT score of our cohort was 12.4 ± 4.0. No patients were classified as low-risk, 49 patients (21.4%) were deemed intermediate-risk and 180 patients (78.6%) were deemed high-risk. A high CAD-LT score (≥ 9) showed high sensitivity (95.3% [95% CI 86-98%]) and modest specificity (27.8% [95% CI 21-35%]) for the detection of obstructive coronary artery disease on CCTA, with a negative predictive value of 94%. Following multidisciplinary discussions, only 41 patients (18%) of patients proceeded to ICA of which 27% received percutaneous coronary intervention. CONCLUSIONS: The use of CCTA in patients deemed intermediate- to high-risk by the CAD-LT score has the potential to reduce the need for invasive coronary angiography in patients undergoing LT workup.

Contemporary and Emerging MRI Strategies for Assessing Kidney Allograft Complications: Arterial Stenosis and Parenchymal Injury, From the AJR Special Series on Imaging of Fibrosis.

MRI plays an important role in the evaluation of kidney allografts for vascular complications as well as parenchymal insults. Transplant renal artery stenosis, the most common vascular complication of kidney transplant, can be evaluated by MRA using gadolinium and nongadolinium contrast agents as well as by unenhanced MRA techniques. Parenchymal injury occurs through a variety of pathways, including graft rejection, acute tubular injury, BK polyomavirus infection, drug-induced interstitial nephritis, and pyelonephritis. Investigational MRI techniques have sought to differentiate among these causes of dysfunction as well as to assess the degree of interstitial fibrosis or tubular atrophy (IFTA)-the common end pathway for all of these processes-which is currently evaluated by invasively obtained core biopsies. Some of these MRI sequences have shown promise in not only assessing the cause of parenchymal injury but also assessing IFTA noninvasively. This review describes current clinically used MRI techniques and previews promising investigational MRI techniques for assessing complications of kidney grafts.

Atherosclerosis on CT coronary angiography and the risk of long-term cardiovascular events after liver transplantation.

Computed tomography coronary angiography (CTCA) is increasingly utilized for preoperative risk stratification before liver transplantation (LT). We sought to assess the predictors of advanced atherosclerosis on CTCA using the recently developed Coronary Artery Disease-Reporting and Data System (CAD-RADS) score and its impact on the prediction of long-term major adverse cardiovascular events (MACE) following LT. We conducted a retrospective cohort study of consecutive patients who underwent CTCA for LT work-up between 2011 and 2018. Advanced atherosclerosis was defined as coronary artery calcium scores > 400 or CAD-RADS score ≥ 3 (≥50% coronary artery stenosis). MACE was defined as myocardial infarction, heart failure, stroke, or resuscitated cardiac arrest. Overall, 229 patients underwent CTCA (mean age 66 ± 5 y, 82% male). Of these, 157 (68.5%) proceeded with LT. The leading etiology of cirrhosis was hepatitis (47%), and 53% of patients had diabetes before transplant. On adjusted analysis, male sex (OR 4.6, 95% CI 1.5-13.8, p = 0.006), diabetes (OR 2.2, 95% CI 1.2-4.2, p = 0.01) and dyslipidemia (OR 3.1, 95% CI 1.3-6.9, p = 0.005) were predictors of advanced atherosclerosis on CTCA. Thirty-two patients (20%) experienced MACE. At a median follow-up of 4 years, CAD-RADS ≥ 3, but not coronary artery calcium scores, was associated with a heightened risk of MACE (HR 5.8, 95% CI 1.6-20.6, p = 0.006). Based on CTCA results, 71 patients (31%) commenced statin therapy which was associated with a lower risk of all-cause mortality (HR 0.48, 95% CI 0.24-0.97, p = 0.04). The standardized CAD-RADS classification on CTCA predicted the occurrence of cardiovascular outcomes following LT, with a potential to increase the utilization of preventive cardiovascular therapies.

Differential sensitivities to blood pressure variations in internal carotid and intracranial arteries: a numerical approach to stroke prediction.

Stroke remains a global health concern, necessitating early prediction for effective management. Atherosclerosis-induced internal carotid and intra cranial stenosis contributes significantly to stroke risk. This study explores the relationship between blood pressure and stroke prediction, focusing on internal carotid artery (ICA) branches: middle cerebral artery (MCA), anterior cerebral artery (ACA), and their role in hemodynamics. Computational fluid dynamics (CFD) informed by the Windkessel model were employed to simulate patient-specific ICA models with introduced stenosis. Central to our investigation is the impact of stenosis on blood pressure, flow velocity, and flow rate across these branches, incorporating Fractional Flow Reserve (FFR) analysis. Results highlight differential sensitivities to blood pressure variations, with M1 branch showing high sensitivity, ACA moderate, and M2 minimal. Comparing blood pressure fluctuations between ICA and MCA revealed heightened sensitivity to potential reverse flow compared to ICA and ACA comparisons, emphasizing MCA's role. Blood flow adjustments due to stenosis demonstrated intricate compensatory mechanisms. FFR emerged as a robust predictor of stenosis severity, particularly in the M2 branch. In conclusion, this study provides comprehensive insights into hemodynamic complexities within major intracranial arteries, elucidating the significance of blood pressure variations, flow attributes, and FFR in stenosis contexts. Subject-specific data integration enhances model reliability, aiding stroke risk assessment and advancing cerebrovascular disease understanding.

Merging virtual and physical experiences: extended realities in cardiovascular medicine.

Technological advancement and the COVID-19 pandemic have brought virtual learning and working into our daily lives. Extended realities (XR), an umbrella term for all the immersive technologies that merge virtual and physical experiences, will undoubtedly be an indispensable part of future clinical practice. The intuitive and three-dimensional nature of XR has great potential to benefit healthcare providers and empower patients and physicians. In the past decade, the implementation of XR into cardiovascular medicine has flourished such that it is now integrated into medical training, patient education, pre-procedural planning, intra-procedural visualization, and post-procedural care. This review article discussed how XR could provide innovative care and complement traditional practice, as well as addressing its limitations and considering its future perspectives.

MRI in CFD for chronic type B aortic dissection: Ready for prime time?

OBJECTIVES: Better tools are needed for risk assessment of Type B aortic dissection (TBAD) to determine optimal treatment for patients with uncomplicated disease. Magnetic resonance imaging (MRI) has the potential to inform computational fluid dynamics (CFD) simulations for TBAD by providing individualised quantification of haemodynamic parameters, for assessment of complication risks. This systematic review aims to present an overview of MRI applications for CFD studies of TBAD. METHODS: Following PRISMA guidelines, a search in Medline, Embase, and the Scopus Library identified 136 potentially relevant articles. Studies were included if they used MRI to inform CFD simulation in TBAD. RESULTS: There were 20 articles meeting the inclusion criteria. 19 studies used phase contrast MRI (PC-MRI) to provide data for CFD flow boundary conditions. In 12 studies, CFD haemodynamic parameter results were validated against PC-MRI. In eight studies, geometric models were developed from MR angiography. In three studies, aortic wall or intimal flap motion data were derived from PC/cine MRI. CONCLUSIONS: MRI provides complementary patient-specific information in CFD haemodynamic studies for TBAD that can be used for personalised care. MRI provides structural, dynamic and flow data to inform CFD for pre-treatment planning, potentially advancing its integration into clinical decision-making. The use of MRI to inform CFD in TBAD surgical planning is promising, however further validation and larger cohort studies are required.

CardiSort: a convolutional neural network for cross vendor automated sorting of cardiac MR images.

OBJECTIVES: To develop an image-based automatic deep learning method to classify cardiac MR images by sequence type and imaging plane for improved clinical post-processing efficiency. METHODS: Multivendor cardiac MRI studies were retrospectively collected from 4 centres and 3 vendors. A two-head convolutional neural network ('CardiSort') was trained to classify 35 sequences by imaging sequence (n = 17) and plane (n = 10). Single vendor training (SVT) on single-centre images (n = 234 patients) and multivendor training (MVT) with multicentre images (n = 434 patients, 3 centres) were performed. Model accuracy and F1 scores on a hold-out test set were calculated, with ground truth labels by an expert radiologist. External validation of MVT (MVTexternal) was performed on data from 3 previously unseen magnet systems from 2 vendors (n = 80 patients). RESULTS: Model sequence/plane/overall accuracy and F1-scores were 85.2%/93.2%/81.8% and 0.82 for SVT and 96.1%/97.9%/94.3% and 0.94 MVT on the hold-out test set. MVTexternal yielded sequence/plane/combined accuracy and F1-scores of 92.7%/93.0%/86.6% and 0.86. There was high accuracy for common sequences and conventional cardiac planes. Poor accuracy was observed for underrepresented classes and sequences where there was greater variability in acquisition parameters across centres, such as perfusion imaging. CONCLUSIONS: A deep learning network was developed on multivendor data to classify MRI studies into component sequences and planes, with external validation. With refinement, it has potential to improve workflow by enabling automated sequence selection, an important first step in completely automated post-processing pipelines. KEY POINTS: • Deep learning can be applied for consistent and efficient classification of cardiac MR image types. • A multicentre, multivendor study using a deep learning algorithm (CardiSort) showed high classification accuracy on a hold-out test set with good generalisation to images from previously unseen magnet systems. • CardiSort has potential to improve clinical workflows, as a vital first step in developing fully automated post-processing pipelines.

Consensus-Based Technical Recommendations for Clinical Translation of Renal Phase Contrast MRI.

BACKGROUND: Phase-contrast (PC) MRI is a feasible and valid noninvasive technique to measure renal artery blood flow, showing potential to support diagnosis and monitoring of renal diseases. However, the variability in measured renal blood flow values across studies is large, most likely due to differences in PC-MRI acquisition and processing. Standardized acquisition and processing protocols are therefore needed to minimize this variability and maximize the potential of renal PC-MRI as a clinically useful tool. PURPOSE: To build technical recommendations for the acquisition, processing, and analysis of renal 2D PC-MRI data in human subjects to promote standardization of renal blood flow measurements and facilitate the comparability of results across scanners and in multicenter clinical studies. STUDY TYPE: Systematic consensus process using a modified Delphi method. POPULATION: Not applicable. SEQUENCE FIELD/STRENGTH: Renal fast gradient echo-based 2D PC-MRI. ASSESSMENT: An international panel of 27 experts from Europe, the USA, Australia, and Japan with 6 (interquartile range 4-10) years of experience in 2D PC-MRI formulated consensus statements on renal 2D PC-MRI in two rounds of surveys. Starting from a recently published systematic review article, literature-based and data-driven statements regarding patient preparation, hardware, acquisition protocol, analysis steps, and data reporting were formulated. STATISTICAL TESTS: Consensus was defined as ≥75% unanimity in response, and a clear preference was defined as 60-74% agreement among the experts. RESULTS: Among 60 statements, 57 (95%) achieved consensus after the second-round survey, while the remaining three showed a clear preference. Consensus statements resulted in specific recommendations for subject preparation, 2D renal PC-MRI data acquisition, processing, and reporting. DATA CONCLUSION: These recommendations might promote a widespread adoption of renal PC-MRI, and may help foster the set-up of multicenter studies aimed at defining reference values and building larger and more definitive evidence, and will facilitate clinical translation of PC-MRI. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 1.

Functional MRI in assessment of diabetic kidney disease in people with type 1 diabetes.

AIMS: To compare levels of renal hypoxia measured by Blood Oxygen Level Dependent (BOLD) magnetic resonance imaging (MRI) with measured transverse relaxation rate (R2*) and renal structural changes including apparent diffusion coefficient (ADC) and fractional anisotropy (FA) in patients with type 1 diabetes and healthy controls. METHODS: Cohort study comparing MRI metrics in type 1 diabetes (n = 32, GFR 105 (77, 120) ml/min.1.73m2) and controls (n = 10). Renal function and selected inflammatory renal biomarkers were also measured. RESULTS: For BOLD, we found reduced cortical [14.7 (13.7,15.8) (1/s) vs 15.7 (15.1,16.6) (1/s), p < 0.001] and medullary [24.8 (21.8,28.2) (1/s) vs. 29.3 (24.3,32.4) (1/s), p < 0.001] R2*, indicating more oxygenated parenchyma, in type 1 diabetes vs. controls, respectively. We observed reduced cortical FA, indicating decreased structural integrity in type 1 diabetes -0.04 (-0.07, -0.01), (p = 0.02). We found reduced cortical ADC, reflecting reduced water diffusion, in non-hyperfiltering [2.40 (2.29,2.53) (103mm2/s)] versus hyperfiltering [2.61 (2.53,2.74) (103mm2/s)] type 1 diabetes patients. MRI parameters correlated with renal function and inflammatory renal biomarkers. CONCLUSIONS: MRI derived indices of renal function and structure differed between (i) type 1 diabetes and healthy controls, and (ii) between non-hyperfiltering and hyperfiltering type 1 diabetes patients, providing insight into the role of hypoxia and renal structural, and functional changes in DKD.

Impact of Image Reconstruction Parameters on Abdominal Aortic Calcification Measurement Using Abdominal Computed Tomography.

BACKGROUND AND AIMS: Abdominal aortic calcification (AAC) is correlated with cardiovascular outcomes independent of traditional risk factors. Quantification of AAC on computed tomography (CT) has not been standardized. Reconstruction parameters have been shown to impact coronary calcium scores. The aim of our study was to assess the impact of abdominal CT reconstruction parameters, slice thickness (ST), and display field of view (DFOV) on AAC quantitative scoring on abdominal CT examinations. METHODS: We retrospectively measured AAC on noncontrast CT of 46 patients (mean age, 64.1 years; 35 males) using 5 different reconstruction protocols with a range of ST and DFOV: protocol A, 2.5 mm ST, 35 cm DFOV; protocol B, 2.5 mm ST, 50 cm DFOV; protocol C, 2.5 mm ST, 25 cm DFOV; protocol D, 5 mm ST, 35 cm DFOV; and protocol E: 0.625 mm ST, 35 cm DFOV. The AAC scores from each protocol were compared using concordance correlation coefficient and Bland-Altman agreement analyses. RESULTS: The AAC mean (SD) scores for each protocol were as follows: A, 2022 (2418); B, 2022 (2412); C, 1939 (2310); D, 2220 (2695); and E, 1862 (2234). The AAC mean score differences between protocols and reference protocol A were -0.47, 82.01, -198.94, and 160 for protocols B, C, D, and E, respectively, with differences between protocols C to E statistically significantly different (P < 0.05). The different protocols showed overall excellent correlation (concordance correlation coefficient, >0.9) between AAC scores. CONCLUSIONS: Slice thickness and DFOV can impact AAC score measurement. A description of reconstruction parameters is important to allow comparisons across different cohorts.

MR Angiography Series: Fundamentals of Non-Contrast-enhanced MR Angiography.

Unlike CT angiography, which requires the use of contrast medium, MR angiography (MRA) can be performed without the use of contrast agents. This subfield of MRA is referred to as non-contrast-enhanced MRA (NC-MRA). While NC-MRA can be performed in many patients, it is especially useful in the imaging of pediatric and pregnant patients, as well as in patients with renal impairment. NC-MRA can also provide unique functional and hemodynamic information that is not obtainable with CT angiography or contrast-enhanced MRA. This module gives an overview of the predominant NC-MRA techniques that are currently available on modern clinical MRI systems, while also discussing some new and emerging topics in the field. This module is the second in a series created on behalf of the Society for Magnetic Resonance Angiography (SMRA), a group of researchers and clinicians who are passionate about the benefits of MRA but understand its challenges. The full digital presentation is available online. ©RSNA, 2021.

Geometric Distortion Correction of Renal Diffusion Tensor Imaging Using the Reversed Gradient Method.

ABSTRACT: Renal echo planar diffusion tensor imaging (DTI) has clinical potential but suffers from geometric distortion. We evaluated feasibility of reversed gradient distortion correction in 10 diabetic patients and 6 volunteers. Renal area, apparent diffusion coefficient, fractional anisotropy, and tensor eigenvalues were measured on uncorrected and distortion-corrected DTI. Corrected DTI correlated better than uncorrected DTI (r = 0.904 vs 0.840, P = 0.002) with reference anatomic T2-weighted imaging, with no significant difference in DTI metrics.

Noncontrast Magnetic Resonance Angiography in the Era of Nephrogenic Systemic Fibrosis and Gadolinium Deposition.

ABSTRACT: Gadolinium-based contrast agents for clinical magnetic resonance imaging are overall safe. However, the discovery of nephrogenic systemic fibrosis in patients with severe renal impairment and gadolinium deposition in patients receiving contrast have generated developments in contrast-free imaging of the vasculature, that is, noncontrast magnetic resonance angiography. This article presents an update on noncontrast magnetic resonance angiography techniques, with comparison to other imaging alternatives. Potential benefits and challenges to implementation, and evidence to date for various clinical applications are discussed.

Arrhythmia insensitive rapid cardiac T1 mapping: comparison to modified look locker inversion recovery T1 mapping in mitral valve prolapse patients.

We compare a saturation recovery arrhythmia insensitive rapid (AIR) T1 mapping technique which is less sensitive to heart rate and requires shorter breath-holds to modified Look-Locker inversion recovery (MOLLI) T1 mapping in patients with mitral valve prolapse. 55 patients underwent AIR and MOLLI at 1.5 T. AIR and MOLLI-derived blood and myocardial T1 values and extracellular volume (ECV) were measured by two independent readers. T1 values and ECV from both techniques and inter-reader agreement were compared with Lin's concordance correlation coefficient (LCC) and reduced major axis regression. T1 values were consistently overestimated for AIR compared to MOLLI and vice versa for ECV. In the mitral valve prolapse population, mean native and post contrast myocardial T1 value for MOLLI were 1000 ± 40 ms and 411.9 ± 44.2 ms respectively and 1090.6 ± 58.7 ms and 488.2 ± 45.7 ms for AIR. Mean native and post contrast blood T1 values for MOLLI were 1566.6 ± 72.3 ms and 276.6 ± 34.1 ms respectively versus 1657.2 ± 180.9 ms and 294.9 ± 35.6 ms for AIR. AIR underestimated ECV relative to MOLLI (23.5 ± 0.4% vs 27.7 ± 0.4%). We found excellent inter-reader agreement (LCC all > 0.94, p < 0.0001) for both AIR and MOLLI techniques as well as intra-reader reliability (LCC all > 0.97, p < 0.0001). AIR can be performed in patients with mitral valve prolapse with excellent inter and intra-reader agreement, with higher T1 values compared to MOLLI, in line with other saturation recovery techniques. A consistent T1 mapping technique should be used when performing serial imaging.

Four-Dimensional Magnetic Resonance Imaging Assessment of Intracranial Aneurysms: A State-of-the-Art Review.

Treatment of unruptured intracranial aneurysms can reduce the risk of subarachnoid hemorrhage and its associated morbidity and mortality. However, current methods to predict the risk of rupture and optimize treatment strategies for intracranial aneurysms are limited. Assessment of intra-aneurysmal flow using 4-dimensional magnetic resonance imaging (4D MRI) is a novel tool that could be used to guide therapy. A systematic search of the literature was performed to provide a state-of-the-art review on 4D MRI assessment of unruptured intracranial aneurysms. A total of 18 studies were available for review. Eccentric flow on 4D MRI is associated with a greater aspect ratio and peak wall shear stress (WSS). WSS, vorticity, and peak velocity are greater in saccular than fusiform aneurysms. Unstable aneurysms are associated with greater WSS, peak wall stress, and flow jet angle and may exhibit wall enhancement. In comparison to computational fluid dynamics (CFD), 4D MRI has a lower spatial resolution and reports lower WSS and velocity magnitudes, but these parameters equalize when spatial resolution is matched. 4D MRI demonstrates the intra-aneurysmal hemodynamic changes associated with flow diversion, including significantly decreased flow velocity. Thus, 4D MRI is a novel, noninvasive imaging tool used for the evaluation of hemodynamics within intracranial aneurysms. Hemodynamic indices derived from 4D MRI appear to correlate well with the simulated (CFD) values and may be used to measure the success of endovascular therapies and risk factors for aneurysm growth and rupture.

Accuracy of non-contrast quiescent-interval single-shot and quiescent-interval single-shot arterial spin-labelled magnetic resonance angiography in assessment of peripheral arterial disease in a diabetic population.

INTRODUCTION: Diabetic patients with peripheral arterial disease (PAD) are challenging to assess. Non-contrast magnetic resonance angiography (MRA) offers a safe alternative in patients with renal impairment. The study objective is to evaluate accuracy of lower limb quiescent-interval single-shot (QISS) MRA and pedal QISS-arterial spin-labelled (ASL) MRA for detection of significant stenosis in diabetic patients with PAD. METHODS: Combined QISS and QISS-ASL MRA was performed in 32 diabetic PAD patients (20 male, 12 female; mean 69 years; 8 with critical ischaemia). Two readers assessed haemodynamically significant (>50%) stenosis and diagnostic confidence on MRA, against digital subtraction angiography (DSA) as the reference standard, with subgroup analysis of patients with severe renal impairment (n = 7). Inter-reader agreement of stenosis and diagnostic confidence were evaluated. Test-retest reproducibility was evaluated in 10 subjects who underwent repeat MRA on a different day. RESULTS: At DSA, 262/645 segments (40.6%) had haemodynamically significant stenoses. MRA accuracy was 78.1% (478/612) and 75.6% (464/614), sensitivity 64.7% (161/249) and 77.5% (193/249), and specificity 87.3% (317/363) and 74.2% (271/365) for 2 readers. MRA accuracy was 80.9% and 80.7% for readers 1 and 2, respectively, in patients with severe renal impairment. QISS MRA but not pedal QISS-ASL MRA was considered of diagnostic image quality. Inter-reader agreement was moderate for stenosis (ĸ = 0.60) and diagnostic confidence (ĸ = 0.41). Test-retest reproducibility was high (ĸ = 0.87) and moderate (ĸ = 0.54) for individual readers. CONCLUSIONS: Quiescent-interval single-shot MRA has reasonable accuracy in a diabetic PAD population with high burden of disease, providing a non-contrast option in patients with renal impairment. QISS-ASL MRA requires further optimisation to be clinically feasible.

Correction to: Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI.

The article Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI.