Magnetic resonance elastography (MRE) for measuring viscoelasticity heavily depends on proper tissue segmentation, especially in heterogeneous organs such as the prostate. Using trained network-based ...image segmentation, we investigated if MRE data suffice to extract anatomical and viscoelastic information for automatic tabulation of zonal mechanical properties of the prostate. Overall, 40 patients with benign prostatic hyperplasia (BPH) or prostate cancer (PCa) were examined with three magnetic resonance imaging (MRI) sequences: T2-weighted MRI (T2w), diffusion-weighted imaging (DWI), and MRE-based tomoelastography, yielding six independent sets of imaging data per patient (T2w, DWI, apparent diffusion coefficient, MRE magnitude, shear wave speed, and loss angle maps). Combinations of these data were used to train Dense U-nets with manually segmented masks of the entire prostate gland (PG), central zone (CZ), and peripheral zone (PZ) in 30 patients and to validate them in 10 patients. Dice score (DS), sensitivity, specificity, and Hausdorff distance were determined. We found that segmentation based on MRE magnitude maps alone (DS, PG: 0.93 ± 0.04, CZ: 0.95 ± 0.03, PZ: 0.77 ± 0.05) was more accurate than magnitude maps combined with T2w and DWI_b (DS, PG: 0.91 ± 0.04, CZ: 0.91 ± 0.06, PZ: 0.63 ± 0.16) or T2w alone (DS, PG: 0.92 ± 0.03, CZ: 0.91 ± 0.04, PZ: 0.65 ± 0.08). Automatically tabulated MRE values were not different from ground-truth values (P>0.05). In conclusion, MRE combined with Dense U-net segmentation allows tabulation of quantitative imaging markers without manual analysis and independent of other MRI sequences and can thus contribute to PCa detection and classification.
In patients with aortic coarctation it would be desirable to assess pressure gradients as well as information about blood flow profiles at rest and during exercise. We aimed to assess the hemodynamic ...responses to physical exercise by combining MRI-ergometry with computational fluid dynamics (CFD). MRI was performed on 20 patients with aortic coarctation (13 men, 7 women, mean age 21.5 ± 13.7 years) at rest and during ergometry. Peak systolic pressure gradients, wall shear stress (WSS), secondary flow degree (SFD) and normalized flow displacement (NFD) were calculated using CFD. Stroke volume was determined based on MRI. On average, the pressure gradient was 18.0 ± 16.6 mmHg at rest and increased to 28.5 ± 22.6 mmHg (p < 0.001) during exercise. A significant increase in cardiac index was observed (p < 0.001), which was mainly driven by an increase in heart rate (p < 0.001). WSS significantly increased during exercise (p = 0.006), whereas SFD and NFD remained unchanged. The combination of MRI-ergometry with CFD allows assessing pressure gradients as well as flow profiles during physical exercise. This concept has the potential to serve as an alternative to cardiac catheterization with pharmacological stress testing and provides hemodynamic information valuable for studying the pathophysiology of aortic coarctation.
Background
Wall shear stress (WSS) presents an important parameter for assessing blood flow characteristics and evaluating flow‐mediated lesions in the aorta.
Purpose
To investigate the robustness of ...WSS and oscillatory shear index (OSI) estimation based on 4D flow MRI against vessel wall motion, spatiotemporal resolution, and velocity encoding (VENC).
Study Type
Simulated and prospective.
Population
Synthetic 4D flow MRI data of the aorta, simulated using the Lattice‐Boltzmann method; in vivo 4D flow MRI data of the aorta from healthy volunteers (n = 11) and patients with congenital heart defects (n = 17).
Field Strength/Sequence
1.5T; 4D flow MRI with PEAK‐GRAPPA acceleration and prospective electrocardiogram triggering.
Assessment
Predicated upon 3D cubic B‐splines interpolation of the image velocity field, WSS was estimated in mid‐systole, early‐diastole, and late‐diastole and OSI was derived. We assessed the impact of spatiotemporal resolution and phase noise, and compared results based on tracked—using deformable registration—and static vessel wall location.
Statistical Tests
Bland–Altman analysis to assess WSS/OSI differences; Hausdorff distance (HD) to assess wall motion; and Pearson's correlation coefficient (PCC) to assess correlation of HD with WSS.
Results
Synthetic data results show systematic over‐/underestimation of WSS when different spatial resolution (mean ± 1.96 SD up to –0.24 ± 0.40 N/m2 and 0.5 ± 1.38 N/m2 for 8‐fold and 27‐fold voxel size, respectively) and VENC‐depending phase noise (mean ± 1.96 SD up to 0.31 ± 0.12 N/m2 and 0.94 ± 0.28 N/m2 for 2‐fold and 4‐fold VENC increase, respectively) are given. Neglecting wall motion when defining the vessel wall perturbs WSS estimates to a considerable extent (1.96 SD up to 1.21 N/m2) without systematic over‐/underestimation (Bland–Altman mean range –0.06 to 0.05).
Data Conclusion
In addition to sufficient spatial resolution and velocity to noise ratio, accurate tracking of the vessel wall is essential for reliable image‐based WSS estimation and should not be neglected if wall motion is present.
Level of Evidence: 2
Technical Efficacy: Stage 2
J. Magn. Reson. Imaging 2018;48:718–728.
Objectives
Retrograde blood flow from complex atheroma in the descending aorta (DAo) has only recently been described as a potential mechanism of stroke. However, prevalence of this mechanism in the ...general population and the exact factors influencing stroke risk are unclear.
Methods
One hundred twenty-six consecutively recruited inhabitants of Freiburg, Germany, between 20 and 80 years of age prospectively underwent 3-T MRI. Aortic plaque location and thickness were determined by 3D T1 MRI (1 mm
3
). 4D flow MRI (spatial/temporal resolution 2 mm
3
/20 ms) and dedicated software were used to determine prevalence and extent of flow reversal and potential embolization from DAo plaques. Flow was correlated with baseline characteristics and echocardiographic and MRI parameters (aortic diameter, wall thickness, and pulse wave velocity).
Results
The maximum length of retrograde blood flow connecting the DAo with the left subclavian artery (LSA) increased from 16.1 ± 8.3 mm in 20–29-year-old to 24.7 ± 11.7 mm in 70–80-year-old subjects, correlated with age (
r
= 0.37;
p
< 0.001), and was lower in females (
p
= 0.003). Age was the only independent predictor of increased flow reversal. Complex DAo plaques ≥ 4-mm thickness were found in eight subjects (6.3%) and were connected with the LSA, left common carotid artery, and brachiocephalic trunk in 8 (100%), 1 (12.5%), and 0 (0%) cases, respectively.
Conclusions
Retrograde blood flow from the DAo was very frequent. However, potential retrograde embolization was rare due to the low incidence of complex DAo plaques. The magnitude of flow reversal and prevalence of complex atheroma increased with age. Thus, older patients with aortic atherosclerosis are especially vulnerable to this stroke mechanism.
Key Points
•
4D flow MRI allows in vivo visualization and quantification of individual and three-dimensional blood flow patterns within the thoracic aorta including retrograde components.
•
This population-based study showed that blood flow reversal from the proximal descending aorta to the brain-supplying great arteries is very frequent and able to reach all brain territories. The extent of such flow reversal increases with age and with the extent of aortic atherosclerosis.
•
The combination of blood flow reversal with plaque rupture in the proximal descending aorta constitutes a potential stroke mechanism that should be considered in future trials and in the management of stroke patients in clinical routine.
Increased aortic stiffness is an independent predictor of cardiovascular disease. Optimal measurement is highly beneficial for the detection of atherosclerosis and the management of patients at risk. ...Thus, it was our purpose to selectively measure aortic stiffness using a novel imaging method and to provide reference values from a population-based study.
One hundred twenty six inhabitants of Freiburg, Germany, between 20 and 80 years prospectively underwent 3 Tesla cardiovascular magnetic resonance (CMR) of the thoracic aorta. 4D flow CMR (spatial/temporal resolution 2mm
/20ms) was executed to calculate aortic pulse wave velocity (PWV) in m/s using dedicated software. In addition, we calculated distensibility coefficients (DC) using 2D CINE CMR imaging of the ascending (AAo) and descending aorta (DAo). Segmental aortic diameter and thickness of aortic plaques were determined by 3D T1 weighted CMR (spatial resolution 1mm
).
PWV increased from 4.93 ± 0.54 m/s in 20-30 year-old to 8.06 ± 1.03 m/s in 70-80 year-old subjects. PWV was significantly lower in women compared to men (p < 0.0001). Increased blood pressure (systolic r = 0.36, p < 0.0001; diastolic r = 0.33, p = 0.0001; mean arterial pressure r = 0.37, p < 0.0001) correlated with PWV after adjustment for age and gender. Finally, PWV increased with increasing diameter of the aorta (ascending aorta r = 0.20, p = 0.026; aortic arch r = 0.24, p = 0.009; descending aorta r = 0.26, p = 0.004). Correlation of PWV and DC of the AAo and DAo or the mean of both was high (r = 0.69, r = 0.68, r = 0.73; p < 0.001).
4D flow CMR was successfully applied to calculate aortic PWV and thus aortic stiffness. Findings showed a high correlation with distensibility coefficients representing local compliance of the aorta. Our novel method and reference data for PWV may provide a reliable biomarker for the identification of patients with underlying cardiovascular disease and optimal guidance of future treatment in studies or clinical routine.
We comprehensively studied morphological and functional aortic aging in a population study using modern three-dimensional MR imaging to allow future comparison in patients with diseases of the aortic ...valve or aorta. We followed 80 of 126 subjects of a population study (20 to 80 years of age at baseline) using the identical methodology 6.0 ± 0.5 years later. All underwent 3 T MRI of the thoracic aorta including 3D T1 weighted MRI (spatial resolution 1 mm
) for measuring aortic diameter and plaque thickness and 4D flow MRI (spatial/temporal resolution = 2 mm
/20 ms) for calculating global and regional aortic pulse wave velocity (PWV) and helicity of aortic blood flow. Mean diameter of the ascending aorta (AAo) decreased and plaque thickness increased significantly in the aortic arch (AA) and descending aorta (DAo) in females. PWV of the thoracic aorta increased (6.4 ± 1.5 to 7.0 ± 1.7 m/s and 6.8 ± 1.5 to 7.3 ± 1.8 m/s in females and males, respectively) over time. Local normalized helicity volumes (LNHV) decreased significantly in the AAo and AA (0.33 to 0.31 and 0.34 to 0.32 in females and 0.34 to 0.32 and 0.32 to 0.28 in males). By contrast, helicity increased significantly in the DAo in both genders (0.28 to 0.29 and 0.29 to 0.30, respectively). 3D MRI was able to characterize changes in aortic diameter, plaque thickness, PWV and helicity during six years in our population. Aortic aging determined by 3D multi-parametric MRI is now available for future comparisons in patients with diseases of the aortic valve or aorta.
Late Gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging can be used to visualise regions of fibrosis and scarring in the left atrium (LA) myocardium. This can be important ...for treatment stratification of patients with atrial fibrillation (AF) and for assessment of treatment after radio frequency catheter ablation (RFCA). In this paper we present a standardised evaluation benchmarking framework for algorithms segmenting fibrosis and scar from LGE CMR images. The algorithms reported are the response to an open challenge that was put to the medical imaging community through an ISBI (IEEE International Symposium on Biomedical Imaging) workshop.
The image database consisted of 60 multicenter, multivendor LGE CMR image datasets from patients with AF, with 30 images taken before and 30 after RFCA for the treatment of AF. A reference standard for scar and fibrosis was established by merging manual segmentations from three observers. Furthermore, scar was also quantified using 2, 3 and 4 standard deviations (SD) and full-width-at-half-maximum (FWHM) methods. Seven institutions responded to the challenge: Imperial College (IC), Mevis Fraunhofer (MV), Sunnybrook Health Sciences (SY), Harvard/Boston University (HB), Yale School of Medicine (YL), King's College London (KCL) and Utah CARMA (UTA, UTB). There were 8 different algorithms evaluated in this study.
Some algorithms were able to perform significantly better than SD and FWHM methods in both pre- and post-ablation imaging. Segmentation in pre-ablation images was challenging and good correlation with the reference standard was found in post-ablation images. Overlap scores (out of 100) with the reference standard were as follows: Pre: IC = 37, MV = 22, SY = 17, YL = 48, KCL = 30, UTA = 42, UTB = 45; Post: IC = 76, MV = 85, SY = 73, HB = 76, YL = 84, KCL = 78, UTA = 78, UTB = 72.
The study concludes that currently no algorithm is deemed clearly better than others. There is scope for further algorithmic developments in LA fibrosis and scar quantification from LGE CMR images. Benchmarking of future scar segmentation algorithms is thus important. The proposed benchmarking framework is made available as open-source and new participants can evaluate their algorithms via a web-based interface.
The posterior wall of the proximal internal carotid artery (ICA) is the predilection site for the development of stenosis. To optimally prevent stroke, identification of new risk factors for plaque ...progression is of high interest. Therefore, we studied the impact of carotid geometry and wall shear stress on cardiovascular magnetic resonance (CMR)-depicted wall thickness in the ICA of patients with high cardiovascular disease risk.
One hundred twenty-one consecutive patients ≥50 years with hypertension, ≥1 additional cardiovascular risk factor and ICA plaque ≥1.5 mm thickness and < 50% stenosis were prospectively included. High-resolution 3D-multi-contrast (time of flight, T1, T2, proton density) and 4D flow CMR were performed for the assessment of morphological (bifurcation angle, ICA/common carotid artery (CCA) diameter ratio, tortuosity, and wall thickness) and hemodynamic parameters (absolute/systolic wall shear stress (WSS), oscillatory shear index (OSI)) in 242 carotid bifurcations.
We found lower absolute/systolic WSS, higher OSI and increased wall thickness in the posterior compared to the anterior wall of the ICA bulb (p < 0.001), whereas this correlation disappeared in ≥10% stenosis. Higher carotid tortuosity (regression coefficient = 0.764; p < 0.001) and lower ICA/CCA diameter ratio (regression coefficient = - 0.302; p < 0.001) were independent predictors of increased wall thickness even after adjustment for cardiovascular risk factors. This association was not found for bifurcation angle, WSS or OSI in multivariate regression analysis.
High carotid tortuosity and low ICA diameter were independent predictors for wall thickness of the ICA bulb in this cross-sectional study, whereas this association was not present for WSS or OSI. Thus, consideration of geometric parameters of the carotid bifurcation could be helpful to identify patients at increased risk of carotid plaque generation. However, this association and the potential benefit of WSS measurement need to be further explored in a longitudinal study.
Different software programs are available for the evaluation of 4D Flow cardiovascular magnetic resonance (CMR). A good agreement of the results between programs is a prerequisite for the acceptance ...of the method. Therefore, the goal was to compare quantitative results from a cross-over comparison in individuals examined on two scanners of different vendors analyzed with four postprocessing software packages.
Eight healthy subjects (27 ± 3 years, 3 women) were each examined on two 3T CMR systems (Ingenia, Philips Healthcare; MAGNETOM Skyra, Siemens Healthineers) with a standardized 4D Flow CMR sequence. Six manually placed aortic contours were evaluated with Caas (Pie Medical Imaging, SW-A), cvi42 (Circle Cardiovascular Imaging, SW-B), GTFlow (GyroTools, SW-C), and MevisFlow (Fraunhofer Institute MEVIS, SW-D) to analyze seven clinically used parameters including stroke volume, peak flow, peak velocity, and area as well as typically scientifically used wall shear stress values. Statistical analysis of inter- and intrareader variability, inter-software and inter-scanner comparison included calculation of absolute and relative error (ER), intraclass correlation coefficient (ICC), Bland–Altman analysis, and equivalence testing based on the assumption that inter-software differences needed to be within 80% of the range of intrareader differences.
SW-A and SW-C were the only software programs showing agreement for stroke volume (ICC = 0.96; ER = 3 ± 8%), peak flow (ICC: 0.97; ER = −1 ± 7%), and area (ICC = 0.81; ER = 2 ± 22%). Results from SW-A/D and SW-C/D were equivalent only for area and peak flow. Other software pairs did not yield equivalent results for routinely used clinical parameters. Especially peak maximum velocity yielded poor agreement (ICC ≤ 0.4) between all software packages except SW-A/D that showed good agreement (ICC = 0.80). Inter- and intrareader consistency for clinically used parameters was best for SW-A and SW-D (ICC = 0.56–97) and worst for SW-B (ICC = -0.01–0.71). Of note, inter-scanner differences per individual tended to be smaller than inter-software differences.
Of all tested software programs, only SW-A and SW-C can be used equivalently for determination of stroke volume, peak flow, and vessel area. Irrespective of the applied software and scanner, high intra- and interreader variability for all parameters have to be taken into account before introducing 4D Flow CMR in clinical routine. Especially in multicenter clinical trials a single image evaluation software should be applied.
The quality and acceptance of machine learning (ML) approaches in cardiovascular data interpretation depends strongly on model design and training and the interaction with the clinical experts. We ...hypothesize that a software infrastructure for the training and application of ML models can support the improvement of the model training and provide relevant information for understanding the classification-relevant data features. The presented solution supports an iterative training, evaluation, and exploration of machine-learning-based multimodal data interpretation methods considering cardiac MRI data. Correction, annotation, and exploration of clinical data and interpretation of results are supported through dedicated interactive visual analytics tools. We test the presented concept with two use cases from the ACDC and EMIDEC cardiac MRI image analysis challenges. In both applications, pre-trained 2D U-Nets are used for segmentation, and classifiers are trained for diagnostic tasks using radiomics features of the segmented anatomical structures. The solution was successfully used to identify outliers in automatic segmentation and image acquisition. The targeted curation and addition of expert annotations improved the performance of the machine learning models. Clinical experts were supported in understanding specific anatomical and functional characteristics of the assigned disease classes.
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