GRASP reconstruction amplified with view-sharing and KWIC filtering reduces underestimation of peak velocity in highly-accelerated real-time phase-contrast MRI: A preliminary evaluation in pediatric patients with congenital heart disease

PURPOSE

To develop a highly-accelerated, real-time phase contrast (rtPC) MRI pulse sequence with 40 fps frame rate (25 ms effective temporal resolution).

METHODS

Highly-accelerated golden-angle radial sparse parallel (GRASP) with over regularization may result in temporal blurring, which in turn causes underestimation of peak velocity. Thus, we amplified GRASP performance by synergistically combining view-sharing (VS) and k-space weighted image contrast (KWIC) filtering. In 17 pediatric patients with congenital heart disease (CHD), the conventional GRASP and the proposed GRASP amplified by VS and KWIC (or GRASP + VS + KWIC) reconstruction for rtPC MRI were compared with respect to clinical standard PC MRI in measuring hemodynamic parameters (peak velocity, forward volume, backward volume, regurgitant fraction) at four locations (aortic valve, pulmonary valve, left and right pulmonary arteries).

RESULTS

The proposed reconstruction method (GRASP + VS + KWIC) achieved better effective spatial resolution (i.e., image sharpness) compared with conventional GRASP, ultimately reducing the underestimation of peak velocity from 17.4% to 6.4%. The hemodynamic metrics (peak velocity, volumes) were not significantly (p > 0.99) different between GRASP + VS + KWIC and clinical PC, whereas peak velocity was significantly (p < 0.007) lower for conventional GRASP. RtPC with GRASP + VS + KWIC also showed the ability to assess beat-to-beat variation and detect the highest peak among peaks.

CONCLUSION

The synergistic combination of GRASP, VS, and KWIC achieves 25 ms effective temporal resolution (40 fps frame rate), while minimizing the underestimation of peak velocity compared with conventional GRASP.

Associations between 3D-based Left Atrial Volumetric and Blood Flow Parameters in a Single-Site Cohort of the Multi-Ethnic Study of Atherosclerosis

Purpose To investigate associations between left atrial volume (LAV) and function with impaired three-dimensional hemodynamics from four-dimensional flow MRI. Materials and Methods A subcohort of participants from the Multi-Ethnic Study of Atherosclerosis from Northwestern University underwent prospective 1.5-T cardiac MRI including whole-heart four-dimensional flow and short-axis cine imaging between 2019 and 2020. Four-dimensional flow MRI analysis included manual three-dimensional segmentations of the LA and LA appendage (LAA), which were used to quantify LA and LAA peak velocity and blood stasis (% voxels < 0.1 m/sec). Short-axis cine data were used to delineate LA contours on all cardiac time points, and the resulting three-dimensional-based LAVs were extracted for calculation of LA emptying fractions (LAEFtotal, LAEFactive, LAEFpassive). Stepwise multivariable linear models were calculated for each flow parameter (LA stasis, LA peak velocity, LAA stasis, LAA peak velocity) to determine associations with LAV and LAEF. Results This study included 158 participants (mean age, 73 years ± 7 [SD]; 83 [52.5%] female and 75 [47.4%] male participants). In multivariable models, a 1-unit increase of LAEFtotal was associated with decreased LA stasis (β coefficient, -0.47%; P < .001), while increased LAEFactive was associated with increased LA peak velocity (β coefficient, 0.21 cm/sec; P < .001). Furthermore, increased minimum LAV indexed was most associated with impaired LAA flow (higher LAA stasis [β coefficient, 0.65%; P < .001] and lower LAA peak velocity [β coefficient, -0.35 cm/sec; P < .001]). Conclusion Higher minimum LAV and reduced LA function were associated with impaired flow characteristics in the LA and LAA. LAV assessment might therefore be a surrogate measure for LA and LAA flow abnormalities. Keywords: Atherosclerosis, Left Atrial Volume, Left Atrial Blood Flow, 4D Flow MRI Supplemental material is available for this article. © RSNA, 2024.

MRI Investigation of the Association of Left Atrial and Left Atrial Appendage Hemodynamics with Silent Brain Infarction

BACKGROUND

Left atrial (LA) myopathy is thought to be associated with silent brain infarctions (SBI) through changes in blood flow hemodynamics leading to thrombogenesis. 4D-flow MRI enables in-vivo hemodynamic quantification in the left atrium (LA) and LA appendage (LAA).

PURPOSE

To determine whether LA and LAA hemodynamic and volumetric parameters are associated with SBI.

STUDY TYPE

Prospective observational study.

POPULATION

A single-site cohort of 125 Participants of the multiethnic study of atherosclerosis (MESA), mean age: 72.3 ± 7.2 years, 56 men.

FIELD STRENGTH/SEQUENCE

1.5T. Cardiac MRI: Cine balanced steady state free precession (bSSFP) and 4D-flow sequences. Brain MRI: T1- and T2-weighted SE and FLAIR.

ASSESSMENT

Presence of SBI was determined from brain MRI by neuroradiologists according to routine diagnostic criteria in all participants without a history of stroke based on the MESA database. Minimum and maximum LA volumes and ejection fraction were calculated from bSSFP data. Blood stasis (% of voxels <10 cm/sec) and peak velocity (cm/sec) in the LA and LAA were assessed by a radiologist using an established 4D-flow workflow.

STATISTICAL TESTS

Student's t test, Mann-Whitney U test, one-way ANOVA, chi-square test. Multivariable stepwise logistic regression with automatic forward and backward selection. Significance level P < 0.05.

RESULTS

26 (20.8%) had at least one SBI. After Bonferroni correction, participants with SBI were significantly older and had significantly lower peak velocities in the LAA. In multivariable analyses, age (per 10-years) (odds ratio (OR) = 1.99 (95% confidence interval (CI): 1.30-3.04)) and LAA peak velocity (per cm/sec) (OR = 0.87 (95% CI: 0.81-0.93)) were significantly associated with SBI.

CONCLUSION

Older age and lower LAA peak velocity were associated with SBI in multivariable analyses whereas volumetric-based measures from cardiac MRI or cardiovascular risk factors were not. Cardiac 4D-flow MRI showed potential to serve as a novel imaging marker for SBI.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Focused navigation for respiratory-motion-corrected free-running radial 4D flow MRI

PURPOSE

To validate a respiratory motion correction method called focused navigation (fNAV) for free-running radial whole-heart 4D flow MRI.

METHODS

Using fNAV, respiratory signals derived from radial readouts are converted into three orthogonal displacements, which are then used to correct respiratory motion in 4D flow datasets. Hundred 4D flow acquisitions were simulated with non-rigid respiratory motion and used for validation. The difference between generated and fNAV displacement coefficients was calculated. Vessel area and flow measurements from 4D flow reconstructions with (fNAV) and without (uncorrected) motion correction were compared to the motion-free ground-truth. In 25 patients, the same measurements were compared between fNAV 4D flow, 2D flow, navigator-gated Cartesian 4D flow, and uncorrected 4D flow datasets.

RESULTS

For simulated data, the average difference between generated and fNAV displacement coefficients was 0.04± $$ \pm $$ 0.32 mm and 0.31± $$ \pm $$ 0.35 mm in the x and y directions, respectively. In the z direction, this difference was region-dependent (0.02± $$ \pm $$ 0.51 mm up to 5.85± $$ \pm $$ 3.41 mm). For all measurements (vessel area, net volume, and peak flow), the average difference from ground truth was higher for uncorrected 4D flow datasets (0.32± $$ \pm $$ 0.11 cm2 , 11.1± $$ \pm $$ 3.5 mL, and 22.3± $$ \pm $$ 6.0 mL/s) than for fNAV 4D flow datasets (0.10± $$ \pm $$ 0.03 cm2 , 2.6± $$ \pm $$ 0.7 mL, and 5.1± 0 $$ \pm 0 $$ .9 mL/s, p < 0.05). In vivo, average vessel area measurements were 4.92± $$ \pm $$ 2.95 cm2 , 5.06± $$ \pm $$ 2.64 cm2 , 4.87± $$ \pm $$ 2.57 cm2 , 4.87± $$ \pm $$ 2.69 cm2 , for 2D flow and fNAV, navigator-gated and uncorrected 4D flow datasets, respectively. In the ascending aorta, all 4D flow datasets except for the fNAV reconstruction had significantly different vessel area measurements from 2D flow. Overall, 2D flow datasets demonstrated the strongest correlation to fNAV 4D flow for both net volume (r2  = 0.92) and peak flow (r2  = 0.94), followed by navigator-gated 4D flow (r2  = 0.83 and r2  = 0.86, respectively), and uncorrected 4D flow (r2  = 0.69 and r2  = 0.86, respectively).

CONCLUSION

fNAV corrected respiratory motion in vitro and in vivo, resulting in fNAV 4D flow measurements that are comparable to those derived from 2D flow and navigator-gated Cartesian 4D flow datasets, with improvements over those from uncorrected 4D flow.

Comparison of Biplane Area-Length Method and 3D Volume Quantification by Using Cardiac MRI for Assessment of Left Atrial Volume in Atrial Fibrillation

Purpose

To compare maximum left atrial (LA) volume (LAV) from the routinely used biplane area-length (BAL) method with three-dimensional (3D)-based volumetry from late gadolinium-enhanced MRI (3D LGE MRI) and contrast-enhanced MR angiography (3D CE-MRA) in patients with atrial fibrillation (AF).

Materials and Methods

Sixty-four patients with AF (mean age, 63 years ± 9 [SD]; 40 male patients) were retrospectively included from a prospective cohort acquired between October 2018 and February 2021. All patients underwent a research MRI examination that included standard two- and four-chamber cine acquisitions, 3D CE-MRA, and 3D LGE MRI performed prior to the atrial kick. Contour delineation on cine imaging and LA 3D segmentations were performed by a radiologist. Maximum LAV (BALmax) was extracted from the BAL volume-time curve and compared with LAV from 3D CE-MRA and 3D LGE MRI. The Kruskal-Wallis test was performed, followed by the Dunn post hoc test and Bland-Altman analyses. Interobserver variability was assessed in 10 patients.

Results

BALmax underestimated LAV compared with 3D CE-MRA (bias: -23.5 mL ± 46.2, P < .001) and 3D LGE MRI (bias: -31.3 mL ± 58.3, P < .001), whereas 3D LGE MRI volumes showed no evidence of a difference from 3D CE-MRA (bias: 7.8 mL ± 45.7, P = .38). Interobserver variability yielded excellent agreement for each method (intraclass correlation coefficient, 0.96-0.98).

Conclusion

BALmax underestimated LAV in patients with AF compared with 3D LGE MRI and 3D CE-MRA, suggesting that the geometric assumption of an ellipsoidal LA shape in BAL does not reflect LA geometry in patients with AF.Keywords: Left Atrial Volume, Biplane Area-Length, Late Gadolinium-enhanced 3D MRI, Contrast-enhanced 3D MR Angiography, Atrial Fibrillation Supplemental material is available for this article. © RSNA, 2023.

Quantification of left atrial function by the area-length method overestimates left atrial emptying fraction

PURPOSE

The biplane area-length method is commonly used in cardiac magnetic resonance (CMR) to assess left atrial (LA) volume (LAV) and function. Associations between left atrial emptying fraction (LAEF) and clinical outcomes have been reported. However, only limited data are available on the calculation of LAEF using the biplane method compared to 3D assessment. This study aimed to compare volumetric and functional LA parameters obtained from the biplane method with 3D assessment in a large, multiethnic cohort.

METHOD

158 participants of MESA (Multi-Ethnic Study of Atherosclerosis) underwent CMR that included standard two- and four-chamber steady-state free precession (SSFP) cine imaging for the biplane method. For 3D-based assessment, short-axis SSFP cine series covering the entire LA were obtained, followed by manual delineation of LA contours to create a time-resolved 3D LAV dataset. Paired t-tests and Bland-Altman plots were used to analyze the data.

RESULTS

Standard volumetric assessment showed that LAVmin (bias: -8.35 mL, p < 0.001), LAVmax (bias: -9.38 mL, p < 0.001) and LAVpreA (bias: -10.27 mL, p < 0.001) were significantly smaller using the biplane method compared to 3D assessment. Additionally, the biplane method reported significantly higher LAEFtotal (bias: 7.22 %, p < 0.001), LAEFactive (bias: 6.08 %, p < 0.001), and LAEFpassive (bias: 4.51 %, p < 0.001) with wide limits of agreement.

CONCLUSIONS

LA volumes were underestimated using the biplane method compared to 3D assessment, while LAEF parameters were overestimated. These findings demonstrate a lack of precision using the biplane method for LAEF assessment. Our results support the usage of 3D assessment in specific settings when LA volumetric and functional parameters are in focus.

Automated segmentation of biventricular contours in tissue phase mapping using deep learning

Tissue phase mapping (TPM) is an MRI technique for quantification of regional biventricular myocardial velocities. Despite its potential, clinical use is limited due to the requisite labor-intensive manual segmentation of cardiac contours for all time frames. The purpose of this study was to develop a deep learning (DL) network for automated segmentation of TPM images, without significant loss in segmentation and myocardial velocity quantification accuracy compared with manual segmentation. We implemented a multi-channel 3D (three dimensional; 2D + time) dense U-Net that trained on magnitude and phase images and combined cross-entropy, Dice, and Hausdorff distance loss terms to improve the segmentation accuracy and suppress unnatural boundaries. The dense U-Net was trained and tested with 150 multi-slice, multi-phase TPM scans (114 scans for training, 36 for testing) from 99 heart transplant patients (44 females, 1-4 scans/patient), where the magnitude and velocity-encoded (V_x , V_y , V_z ) images were used as input and the corresponding manual segmentation masks were used as reference. The accuracy of DL segmentation was evaluated using quantitative metrics (Dice scores, Hausdorff distance) and linear regression and Bland-Altman analyses on the resulting peak radial and longitudinal velocities (V_r and V_z ). The mean segmentation time was about 2 h per patient for manual and 1.9 ± 0.3 s for DL. Our network produced good accuracy (median Dice = 0.85 for left ventricle (LV), 0.64 for right ventricle (RV), Hausdorff distance = 3.17 pixels) compared with manual segmentation. Peak V_r and V_z measured from manual and DL segmentations were strongly correlated (R ≥ 0.88) and in good agreement with manual analysis (mean difference and limits of agreement for V_z and V_r were -0.05 ± 0.98 cm/s and -0.06 ± 1.18 cm/s for LV, and -0.21 ± 2.33 cm/s and 0.46 ± 4.00 cm/s for RV, respectively). The proposed multi-channel 3D dense U-Net was capable of reducing the segmentation time by 3,600-fold, without significant loss in accuracy in tissue velocity measurements.

Divergence-Free Constrained Phase Unwrapping and Denoising for 4D Flow MRI Using Weighted Least-Squares

A novel divergence-free constrained phase unwrapping method was proposed and evaluated for 4D flow MRI. The unwrapped phase field was obtained by integrating the phase variations estimated from the wrapped phase data using weighted least-squares. The divergence-free constraint for incompressible blood flow was incorporated to regulate and denoise the resulting phase field. The proposed method was tested on synthetic phase data of left ventricular flow and in vitro 4D flow measurement of Poiseuille flow. The method was additionally applied to in vivo 4D flow measurements in the thoracic aorta from 30 human subjects. The performance of the proposed method was compared to the state-of-the-art 4D single-step Laplacian algorithm. The synthetic phase data were completely unwrapped by the proposed method for all the cases with velocity encoding (venc) as low as 20% of the maximum velocity and signal-to-noise ratio as low as 5. The in vitro Poiseuille flow data were completely unwrapped with a 60% increase in the velocity-to-noise ratio. For the in-vivo aortic datasets with venc ratio less than 0.4, the proposed method significantly improved the success rate by as much as 40% and reduced the velocity error levels by a factor of 10 compared to the state-of-the-art method. The divergence-free constrained method exhibits reliability and robustness on phase unwrapping and shows improved accuracy of velocity and hemodynamic quantities by unwrapping the low-venc 4D flow MRI data.

Automated Prediction of Hepatic Arterial Stenosis

Several thousand life-saving liver transplants are performed each year. One of the most common causes of early transplant failure is arterial stenosis of the anastomotic junction. Early detection of transplant arterial stenosis can help prevent transplant failure and the need to re-transplant. Doppler ultrasound is the most common screening method, but it suffers from poor specificity. Positive screening cases proceed to angiography which is an invasive and expensive procedure. A more accurate test could decrease the number of normal patients who would have to undergo this invasive diagnostic procedure. We present a turnkey clinical decision support tool for automated prediction of stenosis based on Fourier spectrum analysis of Doppler sonograms to compute a Stenosis Index that has been shown to have higher accuracy than traditional measures. The results of the automated approach compare favorably with the manual approach. Software is available from the authors on request.