Reproducibility of Aorta Segmentation on 4D Flow MRI in Healthy Volunteers

Automated intracranial vessel segmentation of 4D flow MRI data in patients with atherosclerotic stenosis using a convolutional neural network

Introduction

Intracranial 4D flow MRI enables quantitative assessment of hemodynamics in patients with intracranial atherosclerotic disease (ICAD). However, quantitative assessments are still challenging due to the time-consuming vessel segmentation, especially in the presence of stenoses, which can often result in user variability. To improve the reproducibility and robustness as well as to accelerate data analysis, we developed an accurate, fully automated segmentation for stenosed intracranial vessels using deep learning.

Methods

154 dual-VENC 4D flow MRI scans (68 ICAD patients with stenosis, 86 healthy controls) were retrospectively selected. Manual segmentations were used as ground truth for training. For automated segmentation, deep learning was performed using a 3D U-Net. 20 randomly selected cases (10 controls, 10 patients) were separated and solely used for testing. Cross-sectional areas and flow parameters were determined in the Circle of Willis (CoW) and the sinuses. Furthermore, the flow conservation error was calculated. For statistical comparisons, Dice scores (DS), Hausdorff distance (HD), average symmetrical surface distance (ASSD), Bland-Altman analyses, and interclass correlations were computed using the manual segmentations from two independent observers as reference. Finally, three stenosis cases were analyzed in more detail by comparing the 4D flow-based segmentations with segmentations from black blood vessel wall imaging (VWI).

Results

Training of the network took approximately 10 h and the average automated segmentation time was 2.2 ± 1.0 s. No significant differences in segmentation performance relative to two independent observers were observed. For the controls, mean DS was 0.85 ± 0.03 for the CoW and 0.86 ± 0.06 for the sinuses. Mean HD was 7.2 ± 1.5 mm (CoW) and 6.6 ± 3.7 mm (sinuses). Mean ASSD was 0.15 ± 0.04 mm (CoW) and 0.22 ± 0.17 mm (sinuses). For the patients, the mean DS was 0.85 ± 0.04 (CoW) and 0.82 ± 0.07 (sinuses), the HD was 8.4 ± 3.1 mm (CoW) and 5.7 ± 1.9 mm (sinuses) and the mean ASSD was 0.22 ± 0.10 mm (CoW) and 0.22 ± 0.11 mm (sinuses). Small bias and limits of agreement were observed in both cohorts for the flow parameters. The assessment of the cross-sectional lumen areas in stenosed vessels revealed very good agreement (ICC: 0.93) with the VWI segmentation but a consistent overestimation (bias ± LOA: 28.1 ± 13.9%).

Discussion

Deep learning was successfully applied for fully automated segmentation of stenosed intracranial vasculatures using 4D flow MRI data. The statistical analysis of segmentation and flow metrics demonstrated very good agreement between the CNN and manual segmentation and good performance in stenosed vessels. To further improve the performance and generalization, more ICAD segmentations as well as other intracranial vascular pathologies will be considered in the future.

The Amputated Limb Gluteus Medius is Biomechanically Disadvantaged in Patients with Unilateral Transfemoral Amputation

Patients with transfemoral amputation (TFA) are at an increased risk of secondary musculoskeleteal comorbidities, primarily due to asymmetric joint loading. Amputated limb muscle weakness is also prevalent in the TFA population, yet all factors that contribute to muscle strength and thus joint loading are not well understood. Our objective was to bilaterally compare gluteus medius (GMED) muscle factors (volume, fatty infiltration, moment arm) that all contribute to joint loading in patients with TFA. Quantitative magnetic resonance (MR) images of the hip were collected from eight participants with unilateral TFA (2M/6F; age: 47.3 ± 14.7 y/o; BMI: 25.4 ± 5.3 kg/m2; time since amputation: 20.6 ± 15.0 years) and used to calculate normalized GMED muscle volume and fatty infiltration. Six participants participated in an instrumented gait analysis session that collected whole-body kinematics during overground walking. Subject-specific musculoskeletal models were used to calculate bilateral GMED (anterior, middle, posterior) moment arms and frontal plane hip joint angles across three gait cycles. Differences in volume, fatty infiltration, hip adduction-abduction angle, and peak moment arms were compared between limbs using paired Cohen's d effect sizes. Volume was smaller by 36.3 ± 18.8% (d = 1.7) and fatty infiltration was greater by 6.4 ± 7.8% (d = 0.8) in the amputated limb GMED compared to the intact limb. The amputated limb GMED abduction moment arms were smaller compared to the intact limb for both overground walking (anterior: d = 0.9; middle: d = 0.1.2) and during normal range of motion (anterior: d = 0.8; middle: d = 0.8) while bilateral hip adduction-abduction angles were similar during overground walking (d = 0.5). These results indicate that in patients with TFA, the amputated limb GMED is biomechanically disadvantaged compared to the intact limb, which may contribute to the etiology of secondary comorbidities. This population might benefit from movement retraining to lengthen the amputated limb GMED abduction moment arm during gait.

Evaluating a Phase-Specific Approach to Aortic Flow: A 4D Flow MRI Study

BACKGROUND

Aortic flow parameters can be quantified using 4D flow MRI. However, data are sparse on how different methods of analysis influence these parameters and how these parameters evolve during systole.

PURPOSE

To assess multiphase segmentations and multiphase quantification of flow-related parameters in aortic 4D flow MRI.

STUDY TYPE

Prospective.

POPULATION

40 healthy volunteers (50% male, 28.9 ± 5.0 years) and 10 patients with thoracic aortic aneurysm (80% male, 54 ± 8 years).

FIELD STRENGTH/SEQUENCE

4D flow MRI with a velocity encoded turbo field echo sequence at 3 T.

ASSESSMENT

Phase-specific segmentations were obtained for the aortic root and the ascending aorta. The whole aorta was segmented in peak systole. In all aortic segments, time to peak (TTP; for flow velocity, vorticity, helicity, kinetic energy, and viscous energy loss) and peak and time-averaged values (for velocity and vorticity) were calculated.

STATISTICAL TESTS

Static vs. phase-specific models were assessed using Bland-Altman plots. Other analyses were performed using phase-specific segmentations for aortic root and ascending aorta. TTP for all parameters was compared to TTP of flow rate using paired t-tests. Time-averaged and peak values were assessed using Pearson correlation coefficient. P < 0.05 was considered statistically significant.

RESULTS

In the combined group, velocity in static vs. phase-specific segmentations differed by 0.8 cm/sec for the aortic root, and 0.1 cm/sec (P = 0.214) for the ascending aorta. Vorticity differed by 167 sec-1  mL-1 (P = 0.468) for the aortic root, and by 59 sec-1  mL-1 (P = 0.481) for the ascending aorta. Vorticity, helicity, and energy loss in the ascending aorta, aortic arch, and descending aorta peaked significantly later than flow rate. Time-averaged velocity and vorticity values correlated significantly in all segments.

DATA CONCLUSION

Static 4D flow MRI segmentation yields comparable results as multiphase segmentation for flow-related parameters, eliminating the need for time-consuming multiple segmentations. However, multiphase quantification is necessary for assessing peak values of aortic flow-related parameters.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 3.

Reproducibility of 3D thoracic aortic displacement from 3D cine balanced SSFP at 3 T without contrast enhancement

PURPOSE

Aortic motion has direct impact on the mechanical stresses acting on the aorta. In aortic disease, increased stiffness of the aorta may lead to decreased aortic motion over time, which could be a predictor for aortic dissection or rupture. This study investigates the reproducibility of obtaining 3D displacement and diameter maps quantified using accelerated 3D cine MRI at 3 T.

METHODS

A noncontrast-enhanced, free-breathing 3D cine sequence based on balanced SSFP and pseudo-spiral undersampling with high spatial isotropic resolution was developed (spatial/temporal resolution [1.6 mm]3 /67 ms). The thoracic aorta of 14 healthy volunteers was prospectively scanned three times at 3 T: twice on the same day and a third time 2 weeks later. Aortic displacement was calculated using iterative closest point nonrigid registration of manual segmentations of the 3D aorta at end-systole and mid-diastole. Interexamination and interobserver regional analysis of mean displacement for five regions of interest was performed using Bland-Altman analysis. Additionally, a complementary voxel-by-voxel analysis was done, allowing a more local inspection of the method.

RESULTS

No significant differences were found in mean and maximum displacement for any of the regions of interest for the interexamination and interobserver analysis. The maximum displacement measured in the lower half of the ascending aorta was 11.0 ± 3.4 mm (range: 3.0-17.5 mm) for the first scan. The smallest detectable change in mean displacement in the lower half of the ascending aorta was 3 mm.

CONCLUSION

Detailed 3D cine balanced SSFP at 3 T allows for reproducible quantification of systolic-diastolic mean aortic displacement within acceptable limits.

Hemodynamic Parameters in the Parent Arteries of Unruptured Intracranial Aneurysms Depend on Aneurysm Size and Are Different Compared to Contralateral Arteries: A 7 Tesla 4D Flow MRI Study

BACKGROUND

Different Circle of Willis (CoW) variants have variable prevalences of aneurysm development, but the hemodynamic variation along the CoW and its relation to presence and size of unruptured intracranial aneurysms (UIAs) are not well known.

PURPOSE

Gain insight into hemodynamic imaging markers of the CoW for UIA development by comparing these outcomes to the corresponding contralateral artery without an UIA using 4D flow magnetic resonance imaging (MRI).

STUDY TYPE

Retrospective, cross-sectional study.

SUBJECTS

Thirty-eight patients with an UIA, whereby 27 were women and a mean age of 62 years old.

FIELD STRENGTH/SEQUENCE

Four-dimensional phase-contrast (PC) MRI with a 3D time-resolved velocity encoded gradient echo sequence at 7 T.

ASSESSMENT

Hemodynamic parameters (blood flow, velocity pulsatility index [vPI], mean velocity, distensibility, and wall shear stress [peak systolic (WSSMAX ), and time-averaged (WSSMEAN )]) in the parent artery of the UIA were compared to the corresponding contralateral artery without an UIA and were related to UIA size.

STATISTICAL TESTS

Paired t-tests and Pearson Correlation tests. The threshold for statistical significance was P < 0.05 (two-tailed).

RESULTS

Blood flow, mean velocity, WSSMAX , and WSSMEAN were significantly higher, while vPI was lower, in the parent artery relative to contralateral artery. The WSSMAX of the parent artery significantly increased linearly while the WSSMEAN decreased linearly with increasing UIA size.

CONCLUSIONS

Hemodynamic parameters and WSS differ between parent vessels of UIAs and corresponding contralateral vessels. WSS correlates with UIA size, supporting a potential hemodynamic role in aneurysm pathology.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

Coupling synthetic and real-world data for a deep learning-based segmentation process of 4D flow MRI

BACKGROUND AND OBJECTIVE

Phase contrast magnetic resonance imaging (4D flow MRI) is an imaging technique able to provide blood velocity in vivo and morphological information. This capability has been used to study mainly the hemodynamics of large vessels, such as the thoracic aorta. However, the segmentation of 4D flow MRI data is a complex and time-consuming task. In recent years, neural networks have shown great accuracy in segmentation tasks if large datasets are provided. Unfortunately, in the context of 4D flow MRI, the availability of these data is limited due to its recent adoption in clinical settings. In this study, we propose a pipeline for generating synthetic thoracic aorta phase contrast magnetic resonance angiography (PCMRA) to expand the limited dataset of patient-specific PCMRA images, ultimately improving the accuracy of the neural network segmentation even with a small real dataset.

METHODS

The pipeline involves several steps. First, a statistical shape model is used to synthesize new artificial geometries to improve data numerosity and variability. Secondly, computational fluid dynamics simulations are employed to simulate the velocity fields and, finally, after a downsampling and a signal-to-noise and velocity limit adjustment in both frequency and spatial domains, volumes are obtained using the PCMRA formula. These synthesized volumes are used in combination with real-world data to train a 3D U-Net neural network. Different settings of real and synthetic data are tested.

RESULTS

Incorporating synthetic data into the training set significantly improved the segmentation performance compared to using only real data. The experiments with synthetic data achieved a DICE score (DS) value of 0.83 and a better target reconstruction with respect to the case with only real data (DS = 0.65).

CONCLUSION

The proposed pipeline demonstrated the ability to increase the dataset in terms of numerosity and variability and to improve the segmentation accuracy for the thoracic aorta using PCMRA.

Automatic 4D Flow MRI Segmentation Using the Standardized Difference of Means Velocity

We present a method to automatically segment 4D flow magnetic resonance imaging (MRI) by identifying net flow effects using the standardized difference of means (SDM) velocity. The SDM velocity quantifies the ratio between the net flow and observed flow pulsatility in each voxel. Vessel segmentation is performed using an F-test, identifying voxels with significantly higher SDM velocity values than background voxels. We compare the SDM segmentation algorithm against pseudo-complex difference (PCD) intensity segmentation of 4D flow measurements in in vitro cerebral aneurysm models and 10 in vitro Circle of Willis (CoW) datasets. We also compared the SDM algorithm to convolutional neural network (CNN) segmentation in 5 thoracic vasculature datasets. The in vitro flow phantom geometry is known, while the ground truth geometries for the CoW and thoracic aortas are derived from high-resolution time-of-flight (TOF) magnetic resonance angiography and manual segmentation, respectively. The SDM algorithm demonstrates greater robustness than PCD and CNN approaches and can be applied to 4D flow data from other vascular territories. The SDM to PCD comparison demonstrated an approximate 48% increase in sensitivity in vitro and 70% increase in the CoW, respectively; the SDM and CNN sensitivities were similar. The vessel surface derived from the SDM method was 46% closer to the in vitro surfaces and 72% closer to the in vitro TOF surfaces than the PCD approach. The SDM and CNN approaches both accurately identify vessel surfaces. The SDM algorithm is a repeatable segmentation method, enabling reliable computation of hemodynamic metrics associated with cardiovascular disease.

4D Flow cardiovascular magnetic resonance consensus statement: 2023 update

Hemodynamic assessment is an integral part of the diagnosis and management of cardiovascular disease. Four-dimensional cardiovascular magnetic resonance flow imaging (4D Flow CMR) allows comprehensive and accurate assessment of flow in a single acquisition. This consensus paper is an update from the 2015 '4D Flow CMR Consensus Statement'. We elaborate on 4D Flow CMR sequence options and imaging considerations. The document aims to assist centers starting out with 4D Flow CMR of the heart and great vessels with advice on acquisition parameters, post-processing workflows and integration into clinical practice. Furthermore, we define minimum quality assurance and validation standards for clinical centers. We also address the challenges faced in quality assurance and validation in the research setting. We also include a checklist for recommended publication standards, specifically for 4D Flow CMR. Finally, we discuss the current limitations and the future of 4D Flow CMR. This updated consensus paper will further facilitate widespread adoption of 4D Flow CMR in the clinical workflow across the globe and aid consistently high-quality publication standards.

Radiomics-based aortic flow profile characterization with 4D phase-contrast MRI

4D PC MRI of the aorta has become a routinely available examination, and a multitude of single parameters have been suggested for the quantitative assessment of relevant flow features for clinical studies and diagnosis. However, clinically applicable assessment of complex flow patterns is still challenging. We present a concept for applying radiomics for the quantitative characterization of flow patterns in the aorta. To this end, we derive cross-sectional scalar parameter maps related to parameters suggested in literature such as throughflow, flow direction, vorticity, and normalized helicity. Derived radiomics features are selected with regard to their inter-scanner and inter-observer reproducibility, as well as their performance in the differentiation of sex-, age- and disease-related flow properties. The reproducible features were tested on user-selected examples with respect to their suitability for characterizing flow profile types. In future work, such signatures could be applied for quantitative flow assessment in clinical studies or disease phenotyping.

Automatic Time-Resolved Cardiovascular Segmentation of 4D Flow MRI Using Deep Learning

BACKGROUND

Segmenting the whole heart over the cardiac cycle in 4D flow MRI is a challenging and time-consuming process, as there is considerable motion and limited contrast between blood and tissue.

PURPOSE

To develop and evaluate a deep learning-based segmentation method to automatically segment the cardiac chambers and great thoracic vessels from 4D flow MRI.

STUDY TYPE

Retrospective.

SUBJECTS

A total of 205 subjects, including 40 healthy volunteers and 165 patients with a variety of cardiac disorders were included. Data were randomly divided into training (n = 144), validation (n = 20), and testing (n = 41) sets.

FIELD STRENGTH/SEQUENCE

A 3 T/time-resolved velocity encoded 3D gradient echo sequence (4D flow MRI).

ASSESSMENT

A 3D neural network based on the U-net architecture was trained to segment the four cardiac chambers, aorta, and pulmonary artery. The segmentations generated were compared to manually corrected atlas-based segmentations. End-diastolic (ED) and end-systolic (ES) volumes of the four cardiac chambers were calculated for both segmentations.

STATISTICAL TESTS

Dice score, Hausdorff distance, average surface distance, sensitivity, precision, and miss rate were used to measure segmentation accuracy. Bland-Altman analysis was used to evaluate agreement between volumetric parameters.

RESULTS

The following evaluation metrics were computed: mean Dice score (0.908 ± 0.023) (mean ± SD), Hausdorff distance (1.253 ± 0.293 mm), average surface distance (0.466 ± 0.136 mm), sensitivity (0.907 ± 0.032), precision (0.913 ± 0.028), and miss rate (0.093 ± 0.032). Bland-Altman analyses showed good agreement between volumetric parameters for all chambers. Limits of agreement as percentage of mean chamber volume (LoA%), left ventricular: 9.3%, 13.5%, left atrial: 12.4%, 16.9%, right ventricular: 9.9%, 15.6%, and right atrial: 18.7%, 14.4%; for ED and ES, respectively.

DATA CONCLUSION

The addition of this technique to the 4D flow MRI assessment pipeline could expedite and improve the utility of this type of acquisition in the clinical setting.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 1.

Distribution and regional variation of wall shear stress in the curved middle cerebral artery using four-dimensional flow magnetic resonance imaging

BACKGROUND

To investigate the distribution and regional variation of wall shear stress (WSS) in the curved middle cerebral artery (MCA) in healthy individuals using four-dimensional (4D) flow magnetic resonance imaging (MRI).

METHODS

A total of 44 healthy participants (18 males; mean ages: 27.16±5.69 years) were included in this cross-sectional study. The WSS parameters of mean, minimum, and maximum values, the coefficient of variation of time-averaged WSS (TAWSSCV), and the maximum values of the oscillatory shear index (OSI) were calculated and compared in the curved proximal (M1) segments. Three cross-sectional planes were selected: the location perpendicular to the beginning of the long axis of the curved M1 segment of the MCA (proximal section), the most curved M1 location (curved M1 section), and the location before the insular (M2) segment bifurcation (distal section). The WSS and OSI parameters of the proximal, curved, and distal sections of the curved M1 segment were compared, including the inner and outer curvatures of the curved M1 section.

RESULTS

Of the curved M1 segments, the curved M1 section had significantly lower minimum TAWSS values than the proximal (P=0.031) and distal sections (P=0.002), and the curved M1 section had significantly higher maximum OSI values than the distal section (P=0.001). The TAWSSCV values at the curved M1 section were significantly higher than the proximal (P=0.001) and distal sections (P<0.001). At the curved M1 section, the inner curvature showed a significantly lower minimum TAWSS (P=0.013) and higher maximum OSI values (P=0.002) than the outer curvature.

CONCLUSIONS

There are distribution variation of WSS and OSI parameters at the curved M1 section of the curved MCA, and the inner curvature of the curved M1 section has the lowest WSS and highest OSI distribution. The local hemodynamic features of the curved MCA may be related to the predilection for atherosclerotic plaque development.

4D Flow MRI in Ascending Aortic Aneurysms: Reproducibility of Hemodynamic Parameters

(1) Background: Aorta hemodynamics have been associated with aortic remodeling, but the reproducibility of its assessment has been evaluated marginally in patients with thoracic aortic aneurysm (TAA). The current study evaluated intra- and interobserver reproducibility of 4D flow MRI-derived hemodynamic parameters (normalized flow displacement, flow jet angle, wall shear stress (WSS) magnitude, axial WSS, circumferential WSS, WSS angle, vorticity, helicity, and local normalized helicity (LNH)) in TAA patients; (2) Methods: The thoracic aorta of 20 patients was semi-automatically segmented on 4D flow MRI data in 5 systolic phases by 3 different observers. Each time-dependent segmentation was manually improved and partitioned into six anatomical segments. The hemodynamic parameters were quantified per phase and segment. The coefficient of variation (COV) and intraclass correlation coefficient (ICC) were calculated; (3) Results: A total of 2400 lumen segments were analyzed. The mean aneurysm diameter was 50.8 ± 2.7 mm. The intra- and interobserver analysis demonstrated a good reproducibility (COV = 16–30% and ICC = 0.84–0.94) for normalized flow displacement and jet angle, a very good-to-excellent reproducibility (COV = 3–26% and ICC = 0.87–1.00) for all WSS components, helicity and LNH, and an excellent reproducibility (COV = 3–10% and ICC = 0.96–1.00) for vorticity; (4) Conclusion: 4D flow MRI-derived hemodynamic parameters are reproducible within the thoracic aorta in TAA patients.

4D flow cardiovascular magnetic resonance derived energetics in the Fontan circulation correlate with exercise capacity and CMR-derived liver fibrosis/congestion

AIM

This study explores the relationship between in vivo 4D flow cardiovascular magnetic resonance (CMR) derived blood flow energetics in the total cavopulmonary connection (TCPC), exercise capacity and CMR-derived liver fibrosis/congestion.

BACKGROUND

The Fontan circulation, in which both caval veins are directly connected with the pulmonary arteries (i.e. the TCPC) is the palliative approach for single ventricle patients. Blood flow efficiency in the TCPC has been associated with exercise capacity and liver fibrosis using computational fluid dynamic modelling. 4D flow CMR allows for assessment of in vivo blood flow energetics, including kinetic energy (KE) and viscous energy loss rate (EL).

METHODS

Fontan patients were prospectively evaluated between 2018 and 2021 using a comprehensive cardiovascular and liver CMR protocol, including 4D flow imaging of the TCPC. Peak oxygen consumption (VO2) was determined using cardiopulmonary exercise testing (CPET). Iron-corrected whole liver T1 (cT1) mapping was performed as a marker of liver fibrosis/congestion. KE and EL in the TCPC were computed from 4D flow CMR and normalized for inflow. Furthermore, blood flow energetics were compared between standardized segments of the TCPC.

RESULTS

Sixty-two Fontan patients were included (53% male, 17.3 ± 5.1 years). Maximal effort CPET was obtained in 50 patients (peak VO2 27.1 ± 6.2 ml/kg/min, 56 ± 12% of predicted). Both KE and EL in the entire TCPC (n = 28) were significantly correlated with cT1 (r = 0.50, p = 0.006 and r = 0.39, p = 0.04, respectively), peak VO2 (r = - 0.61, p = 0.003 and r = - 0.54, p = 0.009, respectively) and % predicted peak VO2 (r = - 0.44, p = 0.04 and r = - 0.46, p = 0.03, respectively). Segmental analysis indicated that the most adverse flow energetics were found in the Fontan tunnel and left pulmonary artery.

CONCLUSIONS

Adverse 4D flow CMR derived KE and EL in the TCPC correlate with decreased exercise capacity and increased levels of liver fibrosis/congestion. 4D flow CMR is promising as a non-invasive screening tool for identification of patients with adverse TCPC flow efficiency.

Quality Control for 4D Flow MR Imaging

In recent years, 4D flow MRI has become increasingly important in clinical applications for the blood vessels in the whole body, heart, and cerebrospinal fluid. 4D flow MRI has advantages over 2D cine phase-contrast (PC) MRI in that any targeted area of interest can be analyzed post-hoc, but there are some factors to be considered, such as ensuring measurement accuracy, a long imaging time and post-processing complexity, and interobserver variability.Due to the partial volume phenomenon caused by low spatial and temporal resolutions, the accuracy of flow measurement in 4D flow MRI is reduced. For spatial resolution, it is recommended to include at least four voxels in the vessel of interest, and if possible, six voxels. In large vessels such as the aorta, large voxels can be secured and SNR can be maintained, but in small cerebral vessels, SNR is reduced, resulting in reduced accuracy. A temporal resolution of less than 40 ms is recommended. The velocity-to-noise ratio (VNR) of low-velocity blood flow is low, resulting in poor measurement accuracy. The use of dual velocity encoding (VENC) or multi-VENC is recommended to avoid velocity wrap around and to increase VNR. In order to maintain sufficient spatio-temporal resolution, a longer imaging time is required, leading to potential patient movement during examination and a corresponding decrease in measurement accuracy.For the clinical application of new technologies, including various acceleration techniques, in vitro and in vivo accuracy verification based on existing accuracy-validated 2D cine PC MRI and 4D flow MRI, as well as accuracy verification on the conservation of mass' principle, should be performed, and intraobserver repeatability, interobserver reproducibility, and test-retest reproducibility should be checked.

Does the Internal Carotid Artery Attenuate Blood-Flow Pulsatility in Small Vessel Disease? A 7 T 4D-Flow MRI Study

Background

Increased cerebral blood‐flow pulsatility is associated with cerebral small vessel disease (cSVD). Reduced pulsatility attenuation over the internal carotid artery (ICA) could be a contributing factor to the development of cSVD and could be associated with intracranial ICA calcification (iICAC).

Purpose

To compare pulsatility, pulsatility attenuation, and distensibility along the ICA between patients with cSVD and controls and to assess the association between iICAC and pulsatility and distensibility.

Study Type

Retrospective, explorative cross‐sectional study.

Subjects

A total of 17 patients with cSVD, manifested as lacunar infarcts or deep intracerebral hemorrhage, and 17 age‐ and sex‐matched controls.

Field Strength/Sequence

Three‐dimensional (3D) T1‐weighted gradient echo imaging and 4D phase‐contrast (PC) MRI with a 3D time‐resolved velocity encoded gradient echo sequence at 7 T.

Assessment

Blood‐flow velocity pulsatility index (vPI) and arterial distensibility were calculated for seven ICA segments (C1–C7). iICAC presence and volume were determined from available brain CT scans (acquired as part of standard clinical care) in patients with cSVD.

Statistical Tests

Independent t‐tests and linear mixed models. The threshold for statistically significance was P < 0.05 (two tailed).

Results

The cSVD group showed significantly higher ICA vPI and significantly lower distensibility compared to controls. Controls showed significant attenuation of vPI over the carotid siphon (−4.9% ± 3.6%). In contrast, patients with cSVD showed no attenuation, but a significant increase of vPI (+6.5% ± 3.1%). iICAC presence and volume correlated positively with vPI (r = 0.578) in patients with cSVD and negatively with distensibility (r = −0.386).

Conclusion

Decreased distensibility and reduced pulsatility attenuation are associated with increased iICAC and may contribute to cSVD. Confirmation in a larger prospective study is required.

Evidence Level

2

Technical Efficacy

Stage 2

Ascending aorta curvature and flow displacement are associated with accelerated aortic growth at long-term follow-up: A MRI study in Marfan and thoracic aortic aneurysm patients

Background

Aortic aneurysm formation is associated with increased risk of aortic dissection. Current diagnostic strategies are focused on diameter growth, the predictive value of aortic morphology and function remains underinvestigated. We aimed to assess the long-term prognostic value of ascending aorta (AA) curvature radius, regional pulse wave velocity (PWV) and flow displacement (FD) on aortic dilatation/elongation and evaluated adverse outcomes (proximal aortic surgery, dissection/rupture, death) in Marfan and non-syndromic thoracic aortic aneurysm (NTAA) patients.

Methods

Long-term magnetic resonance imaging (MRI) and clinical follow-up of two previous studies consisting of 21 Marfan and 40 NTAA patients were collected. Baseline regional PWV, AA curvature radius and normalized FD were assessed as well as diameter and length growth rate at follow-up. Multivariate linear regression was performed to evaluate whether baseline predictors were associated with aortic growth.=.

Results

Of the 61 patients, 49 patients were included with MRI follow-up (n = 44) and/or adverse aortic events (n = 7). Six had undergone aortic surgery, no dissection/rupture occurred and one patient died during follow-up. During 8.0 [7.3-10.7] years of follow-up, AA growth rate was 0.40 ± 0.31 mm/year. After correction for confounders, AA curvature radius (p = 0.01), but not FD or PWV, was a predictor of AA dilatation. Only FD was associated with AA elongation (p = 0.01).

Conclusion

In Marfan and non-syndromic thoracic aortic aneurysm patients, ascending aorta curvature radius and flow displacement are associated with accelerated aortic growth at long-term follow-up. These markers may aid in the risk stratification of ascending aorta elongation and aneurysm formation.

Before and after Endovascular Aortic Repair in the Same Patients with Aortic Dissection: A Cohort Study of Four-Dimensional Phase-Contrast Magnetic Resonance Imaging

(1) Background: We used four-dimensional phase-contrast magnetic resonance imaging (4D PC-MRI) to evaluate the impact of an endovascular aortic repair (TEVAR) on aortic dissection. (2) Methods: A total of 10 patients received 4D PC-MRI on a 1.5-T MR both before and after TEVAR. (3) Results: The aortas were repaired with either a GORE TAG Stent (Gore Medical; n = 7) or Zenith Dissection Endovascular Stent (Cook Medical; n = 3). TEVAR increased the forward flow volume of the true lumen (TL) (at the abdominal aorta, p = 0.047). TEVAR also reduced the regurgitant fraction in the TL at the descending aorta but increased it in the false lumen (FL). After TEVAR, the stroke distance increased in the TL (at descending and abdominal aorta, p = 0.018 and 0.015), indicating more effective blood transport per heartbeat. Post-stenting quantitative flow revealed that the reductions in stroke volume, backward flow volume, and absolute stroke volume were greater when covered stents were used than when bare stents were used in the FL of the descending aorta. Bare stents had a higher backward flow volume than covered stents did. (4) Conclusions: TEVAR increased the stroke volume in the TL and increased the regurgitant fraction in the FL in patients with aortic dissection.

Geometrically induced wall shear stress variability in CFD-MRI coupled simulations of blood flow in the thoracic aortas

Aortic aneurysm is associated with aberrant blood flow and wall shear stress (WSS). This can be studied by coupling magnetic resonance imaging (MRI) with computational fluid dynamics (CFD). For patient-specific simulations, extra attention should be given to the variation in segmentation of the MRI data-set and its effect on WSS. We performed CFD simulations of blood flow in the aorta for ten different volunteers and provided corresponding WSS distributions. The aorta of each volunteer was segmented four times. The same inlet and outlet boundary conditions were applied for all segmentation variations of each volunteer. Steady-state CFD simulations were performed with inlet flow based on phase-contrast MRI during peak systole. We show that the commonly used comparison of mean and maximal values of WSS, based on CFD in the different segments of the thoracic aorta, yields good to excellent correlation (0.78-0.95) for rescan and moderate to excellent correlation (0.64-1.00) for intra- and interobserver reproducibility. However, the effect of geometrical variations is higher for the voxel-to-voxel comparison of WSS. With this analysis method, the correlation for different segments of the whole aorta is poor to moderate (0.43-0.66) for rescan and poor to good (0.48-0.73) for intra- and interobserver reproducibility. Therefore, we advise being critical about the CFD results based on the MRI segmentations to avoid possible misinterpretation. While the global values of WSS are similar for different modalities, the variation of results is high when considering the local distributions.