In-vivo validation of interpolation-based phase offset correction in cardiovascular magnetic resonance flow quantification: a multi-vendor, multi-center study

Flow evaluation software for four-dimensional flow MRI: a reliability and validation study

PURPOSE

Four-dimensional time-resolved phase-contrast cardiovascular magnetic resonance imaging (4D flow MRI) enables blood flow quantification in multiple vessels, which is crucial for patients with congenital heart disease (CHD). We investigated net flow volumes in the ascending aorta and pulmonary arteries by four different postprocessing software packages for 4D flow MRI in comparison with 2D cine phase-contrast measurements (2D PC).

MATERIAL AND METHODS

4D flow and 2D PC datasets of 47 patients with biventricular CHD (median age 16, range 0.6-52 years) were acquired at 1.5 T. Net flow volumes in the ascending aorta, the main, right, and left pulmonary arteries were measured using four different postprocessing software applications and compared to offset-corrected 2D PC data. Reliability of 4D flow postprocessing software was assessed by Bland-Altman analysis and intraclass correlation coefficient (ICC). Linear regression of internal flow controls was calculated. Interobserver reproducibility was evaluated in 25 patients.

RESULTS

Correlation and agreement of flow volumes were very good for all software compared to 2D PC (ICC ≥ 0.94; bias ≤ 5%). Internal controls were excellent for 2D PC (r ≥ 0.95, p < 0.001) and 4D flow (r ≥ 0.94, p < 0.001) without significant difference of correlation coefficients between methods. Interobserver reliability was good for all vendors (ICC ≥ 0.94, agreement bias < 8%).

CONCLUSION

Haemodynamic information from 4D flow in the large thoracic arteries assessed by four commercially available postprocessing applications matches routinely performed 2D PC values. Therefore, we consider 4D flow MRI-derived data ready for clinical use in patients with CHD.

Deep learning phase error correction for cerebrovascular 4D flow MRI

Background phase errors in 4D Flow MRI may negatively impact blood flow quantification. In this study, we assessed their impact on cerebrovascular flow volume measurements, evaluated the benefit of manual image-based correction, and assessed the potential of a convolutional neural network (CNN), a form of deep learning, to directly infer the correction vector field. With IRB waiver of informed consent, we retrospectively identified 96 MRI exams from 48 patients who underwent cerebrovascular 4D Flow MRI from October 2015 to 2020. Flow measurements of the anterior, posterior, and venous circulation were performed to assess inflow-outflow error and the benefit of manual image-based phase error correction. A CNN was then trained to directly infer the phase-error correction field, without segmentation, from 4D Flow volumes to automate correction, reserving from 23 exams for testing. Statistical analyses included Spearman correlation, Bland-Altman, Wilcoxon-signed rank (WSR) and F-tests. Prior to correction, there was strong correlation between inflow and outflow (ρ = 0.833-0.947) measurements with the largest discrepancy in the venous circulation. Manual phase error correction improved inflow-outflow correlation (ρ = 0.945-0.981) and decreased variance (p < 0.001, F-test). Fully automated CNN correction was non-inferior to manual correction with no significant differences in correlation (ρ = 0.971 vs ρ = 0.982) or bias (p = 0.82, Wilcoxon-Signed Rank test) of inflow and outflow measurements. Residual background phase error can impair inflow-outflow consistency of cerebrovascular flow volume measurements. A CNN can be used to directly infer the phase-error vector field to fully automate phase error correction.

Comparison of 2D and 4D Flow MRI in Neonates Without General Anesthesia

BACKGROUND

Neonates with critical congenital heart disease require early intervention. Four-dimensional (4D) flow may facilitate surgical planning and improve outcome, but accuracy and precision in neonates are unknown.

PURPOSE

To 1) validate two-dimensional (2D) and 4D flow MRI in a phantom and investigate the effect of spatial and temporal resolution; 2) investigate accuracy and precision of 4D flow and internal consistency of 2D and 4D flow in neonates; and 3) compare scan time of 4D flow to multiple 2D flows.

STUDY TYPE

Phantom and prospective patients.

POPULATION

A total of 17 neonates with surgically corrected aortic coarctation (age 18 days [IQR 11-20]) and a three-dimensional printed neonatal aorta phantom.

FIELD STRENGTH/SEQUENCE

1.5T, 2D flow and 4D flow.

ASSESSMENT

In the phantom, 2D and 4D flow volumes (ascending and descending aorta, and aortic arch vessels) with different resolutions were compared to high-resolution reference 2D flow. In neonates, 4D flow was compared to 2D flow volumes at each vessel. Internal consistency was computed as the flow volume in the ascending aorta minus the sum of flow volumes in the aortic arch vessels and descending aorta, divided by ascending aortic flow.

STATISTICAL TESTS

Bland-Altman plots, Pearson correlation coefficient (r), and Student's t-tests.

RESULTS

In the phantom, 2D flow differed by 0.01 ± 0.02 liter/min with 1.5 mm spatial resolution and -0.01 ± 0.02 liter/min with 0.8 mm resolution; 4D flow differed by -0.05 ± 0.02 liter/min with 2.4 mm spatial and 42 msec temporal resolution, -0.01 ± 0.02 liter/min with 1.5 mm, 42 msec resolution and -0.01 ± 0.02 liter/min with 1.5 mm, 21 msec resolution. In patients, 4D flow and 2D flow differed by -0.06 ± 0.08 liter/min. Internal consistency in patients was -11% ± 17% for 2D flow and 5% ± 13% for 4D flow. Scan time was 17.1 minutes [IQR 15.5-18.5] for 2D flow and 6.2 minutes [IQR 5.3-6.9] for 4D flow, P < 0.0001.

DATA CONCLUSION

Neonatal 4D flow MRI is time efficient and can be acquired with good internal consistency without contrast agents or general anesthesia, thus potentially expanding 4D flow use to the youngest and smallest patients.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.

Higher blood pressure in adolescent boys after very preterm birth and fetal growth restriction

BACKGROUND

Although preterm birth predisposes for cardiovascular disease, recent studies in children indicate normal blood pressure and arterial stiffness. This prospective cohort study therefore assessed blood pressure and arterial stiffness in adolescents born very preterm due to verified fetal growth restriction (FGR).

METHODS

Adolescents (14 (13-17) years; 52% girls) born very preterm with FGR (preterm FGR; n = 24) and two control groups born with appropriate birth weight (AGA), one in similar gestation (preterm AGA; n = 27) and one at term (term AGA; n = 28) were included. 24-hour ambulatory blood pressure and aortic pulse wave velocity (PWV) and distensibility by magnetic resonance imaging were acquired.

RESULTS

There were no group differences in prevalence of hypertension or in arterial stiffness (all p ≥ 0.1). In boys, diastolic and mean arterial blood pressures increased from term AGA to preterm AGA to preterm FGR with higher daytime and 24-hour mean arterial blood pressures in the preterm FGR as compared to the term AGA group. In girls, no group differences were observed (all p ≥ 0.1).

CONCLUSIONS

Very preterm birth due to FGR is associated with higher, yet normal blood pressure in adolescent boys, suggesting an existing but limited impact of very preterm birth on cardiovascular risk in adolescence, enhanced by male sex and FGR.

IMPACT

Very preterm birth due to fetal growth restriction was associated with higher, yet normal blood pressure in adolescent boys. In adolescence, very preterm birth due to fetal growth restriction was not associated with increased thoracic aortic stiffness. In adolescence, very preterm birth in itself showed an existing but limited effect on blood pressure and thoracic aortic stiffness. Male sex and fetal growth restriction enhanced the effect of preterm birth on blood pressure in adolescence. Male sex and fetal growth restriction should be considered as additional risk factors to that of preterm birth in cardiovascular risk stratification.

Echo planar imaging-induced errors in intracardiac 4D flow MRI quantification

Purpose

To assess errors associated with EPI‐accelerated intracardiac 4D flow MRI (4DEPI) with EPI factor 5, compared with non‐EPI gradient echo (4DGRE).

Methods

Three 3T MRI experiments were performed comparing 4DEPI to 4DGRE: steady flow through straight tubes, pulsatile flow in a left‐ventricle phantom, and intracardiac flow in 10 healthy volunteers. For each experiment, 4DEPI was repeated with readout and blip phase‐encoding gradient in different orientations, parallel or perpendicular to the flow direction. In vitro flow rates were compared with timed volumetric collection. In the left‐ventricle phantom and in vivo, voxel‐based speed and spatio‐temporal median speed were compared between sequences, as well as mitral and aortic transvalvular net forward volume.

Results

In steady‐flow phantoms, the flow rate error was largest (12%) for high velocity (>2 m/s) with 4DEPI readout gradient parallel to the flow. Voxel‐based speed and median speed in the left‐ventricle phantom were ≤5.5% different between sequences. In vivo, mean net forward volume inconsistency was largest (6.4 ± 8.5%) for 4DEPI with nonblip phase‐encoding gradient parallel to the main flow. The difference in median speed for 4DEPI versus 4DGRE was largest (9%) when the 4DEPI readout gradient was parallel to the flow.

Conclusions

Velocity and flow rate are inaccurate for 4DEPI with EPI factor 5 when flow is parallel to the readout or blip phase‐encoding gradient. However, mean differences in flow rate, voxel‐based speed, and spatio‐temporal median speed were acceptable (≤10%) when comparing 4DEPI to 4DGRE for intracardiac flow in healthy volunteers.

Deep Learning Automated Background Phase Error Correction for Abdominopelvic 4D Flow MRI

Background Four-dimensional (4D) flow MRI has the potential to provide hemodynamic insights for a variety of abdominopelvic vascular diseases, but its clinical utility is currently impaired by background phase error, which can be challenging to correct. Purpose To assess the feasibility of using deep learning to automatically perform image-based background phase error correction in 4D flow MRI and to compare its effectiveness relative to manual image-based correction. Materials and Methods A convenience sample of 139 abdominopelvic 4D flow MRI acquisitions performed between January 2016 and July 2020 was retrospectively collected. Manual phase error correction was performed using dedicated imaging software and served as the reference standard. After reserving 40 examinations for testing, the remaining examinations were randomly divided into training (86% [85 of 99]) and validation (14% [14 of 99]) data sets to train a multichannel three-dimensional U-Net convolutional neural network. Flow measurements were obtained for the infrarenal aorta, common iliac arteries, common iliac veins, and inferior vena cava. Statistical analyses included Pearson correlation, Bland-Altman analysis, and F tests with Bonferroni correction. Results A total of 139 patients (mean age, 47 years ± 14 [standard deviation]; 108 women) were included. Inflow-outflow correlation improved after manual correction (ρ = 0.94, P < .001) compared with that before correction (ρ = 0.50, P < .001). Automated correction showed similar results (ρ = 0.91, P < .001) and demonstrated very strong correlation with manual correction (ρ = 0.98, P < .001). Both correction methods reduced inflow-outflow variance, improving mean difference from -0.14 L/min (95% limits of agreement: -1.61, 1.32) (uncorrected) to 0.05 L/min (95% limits of agreement: -0.32, 0.42) (manually corrected) and 0.05 L/min (95% limits of agreement: -0.38, 0.49) (automatically corrected). There was no significant difference in inflow-outflow variance between manual and automated correction methods (P = .10). Conclusion Deep learning automated phase error correction reduced inflow-outflow bias and variance of volumetric flow measurements in four-dimensional flow MRI, achieving results comparable with manual image-based phase error correction. © RSNA, 2021 See also the editorial by Roldán-Alzate and Grist in this issue.

Brain perfusion imaging in neonates

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MRI is the modality of choice to image and quantify cerebral perfusion.

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Imaging of neonatal brain perfusion is possible using MRI and ultrasound.

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Novel ultrafast ultrasound imaging allows for excellent spatiotemporal resolution.

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Understanding cerebral hemodynamic changes of neonatal adaptation is key.

Abnormal variations of the neonatal brain perfusion can result in long-term neurodevelopmental consequences and cerebral perfusion imaging can play an important role in diagnostic and therapeutic decision-making. To identify at-risk situations, perfusion imaging of the neonatal brain must accurately evaluate both regional and global perfusion. To date, neonatal cerebral perfusion assessment remains challenging. The available modalities such as magnetic resonance imaging (MRI), ultrasound imaging, computed tomography (CT), near-infrared spectroscopy or nuclear imaging have multiple compromises and limitations. Several promising methods are being developed to achieve better diagnostic accuracy and higher robustness, in particular using advanced MRI and ultrasound techniques.

The objective of this state-of-the-art review is to analyze the methodology and challenges of neonatal brain perfusion imaging, to describe the currently available modalities, and to outline future perspectives.

Natural History of Functional Tricuspid Regurgitation Quantified by Cardiovascular Magnetic Resonance

BACKGROUND

Quantitation of tricuspid regurgitant (TR) severity can be challenging with conventional echocardiographic imaging and may be better evaluated using cardiovascular magnetic resonance (CMR).

OBJECTIVES

In patients with functional TR, this study sought to examine the relationship between TR volume (TRVol) and TR fraction (TRF) with all-cause mortality.

METHODS

We examined 547 patients with functional TR using CMR to quantify TRVol and TRF. The primary outcome was all-cause mortality. Thresholds for mild, moderate, and severe TR were derived based on natural history outcome data.

RESULTS

During a median follow-up of 2.6 years (interquartile range: 1.7 to 3.3 years), there were 93 deaths, with an estimated 5-year survival of 79% (95% confidence interval [CI]: 73% to 83%). After adjustment of clinical and imaging variables, including RV function, both TRF (adjusted hazard ratio [AHR] per 10% increment: 1.26; 95% CI: 1.10 to 1.45; p = 0.001) and TRVol (AHR per 10-ml increment: 1.15; 95% CI: 1.04 to 1.26; p = 0.004) were associated with mortality. Patients in the highest-risk strata of TRVol ≥45 ml or TRF ≥50% had the worst prognosis (AHR: 2.26; 95% CI: 1.36 to 3.76; p = 0.002 for TRVol and AHR: 2.60; 95% CI: 1.45 to 4.66; p = 0.001 for TRF).

CONCLUSIONS

This is the first study to use CMR to assess independent prognostic implications of functional TR. Both TRF and TRVol were associated with increased mortality after adjustment for clinical and imaging covariates, including right ventricular ejection fraction. A TRVol of ≥45 ml or TRF of ≥50% identified patients in the highest-risk strata for mortality. These CMR thresholds should be used for patient selection in future trials to determine if tricuspid valve intervention improves outcomes in this high-risk group.

CMR in Evaluating Valvular Heart Disease: Diagnosis, Severity, and Outcomes

Cardiac magnetic resonance (CMR) is a versatile imaging tool that brings much to the assessment of valvular heart disease. Although it is best known for myocardial imaging (even in valve disease), it provides excellent assessment of all 4 heart valves, with some distinct advantages, including a free choice of image planes and accurate flow and volumetric quantification. These allow the severity of each valve lesion to be characterized, in addition to optimal visualization of the surrounding outflow tracts and vessels, to deliver a comprehensive package. It can assess each valve lesion separately (in multiple valve disease) and is not affected by hemodynamic status. The accurate quantitation of regurgitant lesions and the ability to characterize myocardial changes also provides an ability to predict future clinical outcomes in asymptomatic patients. This review outlines how CMR can be used in cardiac valve disease to compliment echocardiography and enhance the patient assessment. It covers the main CMR methods used, their strengths and limitations, and the optimal way to apply them to evaluate valve disease.

The clinical impact of phase offset errors and different correction methods in cardiovascular magnetic resonance phase contrast imaging: a multi-scanner study

BACKGROUND

Cardiovascular magnetic resonance (CMR) phase contrast (PC) flow measurements suffer from phase offset errors. Background subtraction based on stationary phantom measurements can most reliably be used to overcome this inaccuracy. Stationary tissue correction is an alternative and does not require additional phantom scanning. The aim of this study was 1) to compare measurements with and without stationary tissue correction to phantom corrected measurements on different GE Healthcare CMR scanners using different software packages and 2) to evaluate the clinical implications of these methods.

METHODS

CMR PC imaging of both the aortic and pulmonary artery flow was performed in patients on three different 1.5 T CMR scanners (GE Healthcare) using identical scan parameters. Uncorrected, first, second and third order stationary tissue corrected flow measurement were compared to phantom corrected flow measurements, our reference method, using Medis QFlow, Circle cvi42 and MASS software. The optimal (optimized) stationary tissue order was determined per scanner and software program. Velocity offsets, net flow, clinically significant difference (deviation > 10% net flow), and regurgitation severity were assessed.

RESULTS

Data from 175 patients (28 (17-38) years) were included, of which 84% had congenital heart disease. First, second and third order and optimized stationary tissue correction did not improve the velocity offsets and net flow measurements. Uncorrected measurements resulted in the least clinically significant differences in net flow compared to phantom corrected data. Optimized stationary tissue correction per scanner and software program resulted in net flow differences (> 10%) in 19% (MASS) and 30% (Circle cvi42) of all measurements compared to 18% (MASS) and 23% (Circle cvi42) with no correction. Compared to phantom correction, regurgitation reclassification was the least common using uncorrected data. One CMR scanner performed worse and significant net flow differences of > 10% were present both with and without stationary tissue correction in more than 30% of all measurements.

CONCLUSION

Phase offset errors had a significant impact on net flow quantification, regurgitation assessment and varied greatly between CMR scanners. Background phase correction using stationary tissue correction worsened accuracy compared to no correction on three GE Healthcare CMR scanners. Therefore, careful assessment of phase offset errors at each individual scanner is essential to determine whether routine use of phantom correction is necessary.

TRIAL REGISTRATION

Observational Study.

Stationary tissue background correction increases the precision of clinical evaluation of intra-cardiac shunts by cardiovascular magnetic resonance

We aimed to evaluate the clinical utility of stationary tissue background phase correction for affecting precision in the measurement of Qp/Qs by cardiovascular magnetic resonance (CMR). We enrolled consecutive patients (n = 91) referred for CMR at 1.5T without suspicion of cardiac shunt, and patients (n = 10) with verified cardiac shunts in this retrospective study. All patients underwent phase contrast flow quantification in the ascending aorta and pulmonary trunk. Flow was quantified using two semi-automatic software platforms (SyngoVia VA30, Vendor 1; Segment 2.0R4534, Vendor 2). Measurements were performed both uncorrected and corrected for linear (Vendor 1 and Vendor 2) or quadratic (Vendor 2) background phase. The proportion of patients outside the normal range of Qp/Qs was compared using the McNemar’s test. Compared to uncorrected measurements, there were fewer patients with a Qp/Qs outside the normal range following linear correction using Vendor 1 (10% vs 18%, p < 0.001), and Vendor 2 (10% vs 18%, p < 0.001), and following quadratic correction using Vendor 2 (7% vs 18%, p < 0.001). No patient with known shunt was reclassified as normal following stationary background correction. Therefore, we conclude that stationary tissue background correction reduces the number of patients with a Qp/Qs ratio outside the normal range in a consecutive clinical population, while simultaneously not reclassifying any patient with known cardiac shunts as having a normal Qp/Qs. Stationary tissue background correction may be used in clinical patients to increase diagnostic precision.