Association of vulnerable plaques with white matter hyperintensities on high-resolution magnetic resonance imaging.

Background: One of the widespread manifestations of cerebral small vessel disease (CSVD) of the brain parenchyma is white matter lesion, which appears as white matter hyperintensities (WMHs) on magnetic resonance imaging (MRI). Previous studies have illustrated that large artery atherosclerosis is related to CSVD, but the precise progress of pathogenesis remains unknown. High-resolution MRI (HR-MRI) has the ability to delineate intracranial vascular walls, enabling a thorough exploration of the structure and composition of unstable plaques. This study aimed to apply HR-MRI to characterize the wall changes and plaque characteristics of middle cerebral arteries in patients with WMHs and to investigate the correlation between plaque vulnerability parameters and different degrees of WMHs. Methods: In this study, 138 patients with acute ischemic stroke at Harbin Medical University's First Clinical Hospital (May 2021 to October 2023) were cross-sectionally reviewed and underwent conventional brain and HR-MRI using T1-weighted 3D volumetric isotropic turbo spin echo acquisition (T1W-3D-VISTA) of the unilateral middle cerebral artery (MCA). According to Fazekas grade (0-6), the patients were divided into two groups: Fazekas score 0-2, no-or-mild WMHs; and Fazekas 3-6, moderate-to-severe WMHs. The intraplaque hemorrhage, plaque distribution, plaque enhancement, plaque load, remodeling pattern, and stenosis of the two groups were measured. Binary logistic regression analysis was conducted to evaluate the relationship between vulnerable plaques and WMHs. Results: Of the participants who were initially considered for inclusion, 71 were deemed eligible, among whom 34 were placed in the no-or-mild WMH group and 37 in the moderate-to-severe WMH group. Between the two groups, there were significant differences in intraplaque hemorrhage (P=0.01), a wide distribution (P=0.02), and plaque enhancement (P=0.02). Univariate analysis showed that WMHs were associated with age [odds ratio (OR) =1.080; 95% confidence interval (CI): 1.020-1.144; P=0.008], hypertension (OR =3.500; 95% CI: 1.276-9.597; P=0.01), intraplaque hemorrhage (OR =3.955; 95% CI: 1.247-12.538; P=0.02), a wide distribution (OR =3.067; 95% CI: 1.159-8.115; P=0.02), and significant plaque enhancement (OR =4.372; 95% CI: 1.101-17.358; P=0.03); however, the multivariate results showed that the only independent factors associated with WMHs were age (OR =1.095; 95% CI: 1.019-1.176; P=0.01) and intraplaque hemorrhage (OR =5.88; 95% CI: 1.466-23.592; P=0.01). Conclusions: Our findings suggest that age and intraplaque hemorrhage may be associated with more severe WMHs in patients with acute ischemic stroke, which may be helpful for further clinical examination and intervention treatment.

Left atrial and left ventricular strain in feature-tracking cardiac magnetic resonance for predicting patients at high risk of sudden cardiac death in hypertrophic cardiomyopathy.

Background: Sudden cardiac death (SCD) represents the most severe complication of hypertrophic cardiomyopathy (HCM). The risk stratification of SCD in patients with HCM remains a subject of ongoing debate, and the utility of left atrial (LA) and left ventricular (LV) myocardial strain for risk stratification of also SCD remains uncertain. Through use of feature-tracking cardiac magnetic resonance (FT-CMR), this study aimed to investigate the attenuation of LA and LV strain in HCM and to assess their predictive value in SCD. Methods: This retrospective and cross-sectional study included patients with HCM who underwent 3.0 T cardiac magnetic resonance (CMR) at a single institution. Feature-tracking strain analysis was conducted to obtain the strain rate (SR) and LV strain and to evaluate LV function. LA strain was measured during different functional phases including left atrial reservoir strain (LARS), LA conduit strain (LACS), and LA booster strain. All patients were categorized into high- and low-risk groups for SCD as defined by the 2020 American Heart Association/American College HCM implantable cardioverter defibrillator class of recommendation algorithm. Comparison between the two groups was conducted using the independent samples t test and the nonparametric rank sum test. Multivariate logistic regression analysis was performed to further identify the factors influencing SCD risk in HCM. Results: Compared with those in the low-risk group, patients in the high-risk group had lower left ventricular ejection fraction (LVEF), LV stroke volume index (LVSVI), and LA stroke volume index (LASVI) but a higher LV end-systolic volume index (LVESVI), LV maximum wall thickness, and late gadolinium enhancement (LGE) (P<0.001). LV strain, SR, and LA strain all showed significant differences between the high- and low-risk groups (LARS: P=0.04; LACS: P=0.02; all other P values <0.001). The LV global circumferential strain (LVGCS) had a strong negative correlation with LVEF in patients with HCM (r=-0.76; P<0.001). Multivariate analysis showed that LV global radial strain (LVGRS) and LARS could be used for categorizing the patients into the high-risk group [LVGRS: odds ratio (OR) =0.69; 95% confidence interval (CI): 0.55-0.87, P<0.001; LARS: OR =1.39; 95% CI: 1.02-1.90, P=0.03]. The combined LVGRS-LARS model exhibited a superior diagnostic value for high risk of SCD [area under the curve (AUC) =0.95; 95% CI: 0.90-1.00; P<0.001] compared to LARS alone (AUC =0.63; 95% CI: 0.51-0.76; P=0.04). Conclusions: LA and LV strain measured by FT-CMR can accurately identify those patients with HCM at a high risk of SCD. This approach may prove considerably value in guiding early therapeutic intervention with implantable cardioverter-defibrillators (ICDs) to prevent adverse clinical outcomes.

Feasibility of Artificial Intelligence Constrained Compressed SENSE Accelerated 3D Isotropic T1 VISTA Sequence For Vessel Wall MR Imaging: Exploring the Potential of Higher Acceleration Factors Compared to Traditional Compressed SENSE.

RATIONALE AND OBJECTIVES: Investigate the feasibility of using deep learning-based accelerated 3D T1-weighted volumetric isotropic turbo spin-echo acquisition (VISTA) for vessel wall magnetic resonance imaging (VW-MRI), compared to traditional Compressed SENSE and optimize acceleration factor (AF) to obtain high-quality clinical images. METHODS: 40 patients with atherosclerotic plaques in the intracranial or carotid artery were prospectively enrolled in our study from October 1, 2022 to October 31, 2023 underwent high-resolution vessel wall imaging on a 3.0 T MR system using variable Compressed SENSE (CS) AFs and reconstructed by an optimized artificial intelligence constrained Compressed SENSE (CS-AI). Images were reconstructed through both traditional CS and optimized CS-AI. Two radiologists qualitatively assessed the image quality scores of CS and CS-AI across different segments and quantitatively evaluated SNR (signal-to-noise ratio) and CNR (contrast-to-noise ratio) metrics. Paired t-tests, ANOVA, and Friedman tests analyzed image quality metrics. Written informed consent was obtained from all patients in this study. RESULTS: CS-AI groups demonstrated good image quality scores compared to reference scans until AF up to 12 (P < 0.05). The CS-AI 10 protocol provided the best images in the lumen of both normal and lesion sites (P < 0.05). The plaque SNR was significantly higher in CS-AI groups compared to CS groups until the AF increased to 12 (P < 0.05). CS-AI protocols had higher CNR compared to CS with whichever AF on both pre-and post-contrast T1WI (P < 0.05), The CNR was highest in the CS-AI 10 protocol on pre-contrast T1WI and in CS-AI 12 on post-contrast T1WI (P < 0.05). CONCLUSION: The study demonstrated the feasibility of using CS-AI technology to diagnose arteriosclerotic vascular disease with 3D T1 VISTA sequences. The image quality and diagnostic efficiency of CS-AI images were comparable or better than traditional CS images. Higher AFs are feasible and have potential for use in VW-MRI. The determination of standardized AFs for clinical scanning protocol is expected to help for empirical evaluation of new imaging technology.

The Feasibility of Left Ventricular Strain and Strain Rate for Evaluating Patients With Risk Factors of Sudden Cardiac Death in Hypertrophic Cardiomyopathy by Feature Tracking Cardiac Magnetic Resonance.

Sudden cardiac death (SCD) represents the most severe complication of hypertrophic cardiomyopathy (HCM). However, the relation between strain, strain rate (SR), and risk factors in SCD risk stratification remains elusive. The study aimed to assess the attenuation of strain and SR in HCM by feature tracking cardiac magnetic resonance. All strain and SRs were obtained automatically by feature tracking, with manual adjustment of endocardial and epicardial borders. Strain indicators included left ventricular global longitudinal, circumferential, global radial strain (GRS), peak diastolic-longitudinal, circumferential, and radial SR. Patients were categorized into high-risk and low-risk groups for SCD based on the 2020 American Heart Association/American College HCM risk-SCD model. The correlation between strain/SR and SCD risk factors was assessed through Spearman correlation analysis. Furthermore, a multivariate logistic regression analysis was conducted to explore the factors that influence SCD risk in HCM patients. A total of 105 HCM patients were analyzed in this study, including 38 patients in the high-risk group, and 67 patients in the low-risk group. Compared with the low-risk group, the high-risk group exhibited significantly worse strain and SR (p <0.001). Furthermore, both circumferential and GRS and SR exhibited meaningful associations with risk factors for SCD. Additionally, GRS emerged as an independent risk factor for predicting heightened SCD risk in HCM patients (p <0.001). In conclusion, left ventricular strain and SR based on feature tracking-cardiac magnetic resonance can be evaluated for SCD risk and are strongly associated with SCD risk factors.

Compressed Sensitivity Encoding Artificial Intelligence Accelerates Brain Metastasis Imaging by Optimizing Image Quality and Reducing Scan Time.

BACKGROUND AND PURPOSE: Accelerating the image acquisition speed of MR imaging without compromising the image quality is challenging. This study aimed to evaluate the feasibility of contrast-enhanced (CE) 3D T1WI and CE 3D-FLAIR sequences reconstructed with compressed sensitivity encoding artificial intelligence (CS-AI) for detecting brain metastases (BM) and explore the optimal acceleration factor (AF) for clinical BM imaging. MATERIALS AND METHODS: Fifty-one patients with cancer with suspected BM were included. Fifty participants underwent different customized CE 3D-T1WI or CE 3D-FLAIR sequence scans. Compressed SENSE encoding acceleration 6 (CS6), a commercially available standard sequence, was used as the reference standard. Quantitative and qualitative methods were used to evaluate image quality. The SNR and contrast-to-noise ratio (CNR) were calculated, and qualitative evaluations were independently conducted by 2 neuroradiologists. After exploring the optimal AF, sample images were obtained from 1 patient by using both optimized sequences. RESULTS: Quantitatively, the CNR of the CS-AI protocol for CE 3D-T1WI and CE 3D-FLAIR sequences was superior to that of the CS protocol under the same AF (P < .05). Compared with reference CS6, the CS-AI groups had higher CNR values (all P < .05), with the CS-AI10 scan having the highest value. The SNR of the CS-AI group was better than that of the reference for both CE 3D-T1WI and CE 3D-FLAIR sequences (all P < .05). Qualitatively, the CS-AI protocol produced higher image quality scores than did the CS protocol with the same AF (all P < .05). In contrast to the reference CS6, the CS-AI group showed good image quality scores until an AF of up to 10 (all P < .05). The CS-AI10 scan provided the optimal images, improving the delineation of normal gray-white matter boundaries and lesion areas (P < .05). Compared with the reference, CS-AI10 showed reductions in scan time of 39.25% and 39.93% for CE 3D-T1WI and CE 3D-FLAIR sequences, respectively. CONCLUSIONS: CE 3D-T1WI and CE 3D-FLAIR sequences reconstructed with CS-AI for the detection of BM may provide a more effective alternative reconstruction approach than CS. CS-AI10 is suitable for clinical applications, providing optimal image quality and a shortened scan time.

Right Ventricular Function in Takayasu's Arteritis Patients With Pulmonary Artery Involvement Using MRI Feature Tracking.

BACKGROUND: Pulmonary artery involvement (PAI) is not rare in Takayasu arteritis (TA). Persistently elevated pulmonary arterial pressure in TA-PAI patients leads to pulmonary hypertension (PH), and eventually cardiac death. Thus, the early detection of right ventricular dysfunction before the onset of PH is important. PURPOSE: To explore the potential of right ventricular global peak longitudinal and circumferential strain (RVGLS and RVGCS, respectively) in detecting right ventricular myocardial damage in TA-PAI patients without PH. STUDY TYPE: Retrospective. POPULATION: One hundred and six TA patients (39.6 ± 13.9 years), of whom 52 were non-PAI and 54 were PAI patients (36 without PH and 18 with PH), along with 58 sex- and age-matched healthy volunteers (HVs) (36.7 ± 13.2 years). The involved arteries were validated by aorta magnetic resonance (MR) angiography and pulmonary artery computed tomography angiography. FIELD STRENGTH/SEQUENCE: 3 T/Cine imaging sequence with a steady-state free precession readout. ASSESSMENT: Cardiac MRI-derived parameters measured by two radiologists independently were compared among HVs, and TA patients with and without PAI. In addition, these indices were further compared among HVs, and TA-PAI patients with and without PH. STATISTICAL TESTS: Student's t test, one-way ANOVA analysis, Pearson and Spearman correlation analysis, and reproducibility analysis. A P-value of <0.05 was considered statistically significant. RESULTS: Although the TA-PAI patients without PH had a similar RV ejection fraction (RVEF) with HV (P = 0.348), RVGLS (non-PH 20.6 ± 3.7% vs. HV 24.0 ± 3.1%) was significantly lower and RVGCS (non-PH 14.8 ± 3.9% vs. HV 13.0 ± 2.7%) higher. The TA-PAI patients with PH had significantly poorer RVGLS (PH 13.5 ± 3.8% vs. non-PH 20.6 ± 3.7%) and RVGCS (PH 10.9 ± 3.2% vs. non-PH 14.8 ± 3.9%) than those without PH. DATA CONCLUSION: Right ventricular dysfunction was detected in the TA-PAI patients without PH. MR-feature tracking may be an effective method for detecting early cardiac damage in the TA-PAI patients without PH. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 3.

Predicting acute ischemic stroke using the revised Framingham stroke risk profile and multimodal magnetic resonance imaging.

Background and purpose: Patients with transient ischemic attacks (TIA) have a significant risk of developing acute ischemic strokes (AIS), emphasizing the critical need for hierarchical management. This study aims to develop a clinical-imaging model utilizing multimodal magnetic resonance imaging (mMRI) and the revised Framingham Stroke Risk Profile (FSRP) to predict AIS and achieve early secondary prevention. Methods: mMRI scans were conducted on patients with symptomatic intracranial atherosclerotic disease (ICAD) to assess vascular wall features and cerebral perfusion parameters. Based on diffusion-weighted imaging (DWI), patients were divided into two groups: TIA and AIS. Clinical data were evaluated to calculate the FSRP score. Differences in clinical and imaging characteristics between the groups were analyzed, and a predictive model for AIS probability in patients with ICAD was established. Results: A total of 112 TIA and AIS patients were included in the study. The results showed that the AIS group had higher proportions of FSRP-high risk, hyperhomocysteinemia, and higher value of low-density lipoprotein (LDL), standardized plaque index (SQI), and enhancement rate (ER) compared to the TIA group (p < 0.05). Mean transit time (MTT) and time to peak (TTP) in the lesion area were significantly longer in the AIS group (p < 0.05). Multivariate analysis identified FSRP-high risk (p = 0.027) and high ER (p = 0.046) as independent risk factors for AIS. The combined clinical and mMRI model produced an area under the curve (AUC) of 0.791 in receiver operating characteristic (ROC) analysis. The constructed nomogram model combining clinical and mMRI features demonstrated favorable clinical net benefits. Conclusion: FSRP-high risk and high ER were confirmed as independent risk factors for AIS. The combined prediction model utilizing clinical and imaging markers effectively predicts stroke risk in symptomatic ICAD patients.

Evaluation of activity of Graves' orbitopathy with multiparameter orbital magnetic resonance imaging (MRI).

Background: When quantitative magnetic resonance imaging (MRI) is used to assess the activity of Graves' orbitopathy (GO), the examination is generally focused on a specific orbital tissue, especially the extraocular muscles (EOMs). However, GO usually involves the entire intraorbital soft tissue. The aim of this study was to use multiparameter MRI on multiple orbital tissues to distinguish the active and inactive GO. Methods: From May 2021 to March 2022, consecutive patients with GO were prospectively enrolled at Peking University People's Hospital (Beijing, China) and divided into those with active disease and those with inactive disease based on a clinical activity score. Patients then underwent MRI, including sequences of conventional imaging, T1 mapping, T2 mapping, and mDIXON Quant. Width, T2 signal intensity ratio (SIR), T1 values, T2 values, and fat fraction of EOMs, as well as water fraction (WF) of orbital fat (OF), were measured. Parameters were compared between the 2 groups, and a combined diagnostic model was constructed using logistic regression analysis. Receiver operating characteristic analysis was used to test the diagnostic performance of the model. Results: Sixty-eight patients with GO (27 with active GO, 41 with inactive GO) were included in the study. The active GO group had higher values of EOM thickness, T2 SIR, and T2 values, as well as higher WF of OF. The diagnostic model, which included EOM T2 value and WF of OF, demonstrated a good ability to distinguish between active and inactive GO (area under the curve, 0.878; 95% CI: 0.776-0.945; sensitivity, 88.89%; specificity, 75.61%). Conclusions: A combined model incorporating the T2 value of EOMs and the WF of OF was able to identify cases of active GO, potentially offering an effective and noninvasive method to assess pathological changes in this disease.

The feasibility of relaxation-enhanced angiography without contrast and triggering for preprocedural planning of transcatheter aortic valve implantation.

Background: Cardiovascular MRI is advantageous in transcatheter aortic valve implantation (TAVI) planning. This study aimed to evaluate the feasibility of comprehensive non-contrast MRI [relaxation-enhanced angiography without contrast and triggering (REACT)] combined with a three-dimensional whole-heart MRI protocol for preprocedural planning of TAVI vs. computed tomography angiography (CTA). Methods: Thirty patients with severe aortic stenosis were prospectively enrolled. The anatomical properties of the aortic root anatomy, including the perimeter and area of the virtual aortic valve annulus and coronary heights, were determined from 3D whole-heart MRI and cardiac CTA (CCTA) images, respectively. The diameters of the aorta (thoracic and abdominal aorta) and iliofemoral arteries were measured from REACT and aortic CTA (ACTA) images, respectively. A paired t-test was used to compare these two modalities. Bland-Altman plots were used to assess cardiovascular MRI and CTA measurements. Transcatheter heart valve (THV) sizing was performed based on CCTA measurements and compared with 3D whole-heart MRI measurements. The extent of annular calcification on 3D whole-heart MRI images was evaluated by a four-point grading scale and compared with CCTA data. Results: All 30 patients completed CTA and cardiovascular MRI examinations, with the TAVI procedure being administered in 25 patients. The mean acquisition time of the comprehensive MRI protocol was 18 ± 3.2 min. There were no significant differences between ACTA and REACT data in regard to the diameters of aortic and iliofemoral arteries, including the ascending thoracic aorta (37 ± 4.6 mm vs. 37.7 ± 5.2 mm, p = 0.085), descending thoracic aorta (24.3 ± 2.8 mm vs. 24.3 ± 2.8 mm, p = 0.832), abdominal aorta (20.9 ± 2.5 mm vs. 20.8 ± 2.5 mm, p = 0.602), bilateral common iliac arteries (right: 8.36 ± 1.44 mm vs. 8.42 ± 1.27 mm, p = 0.590; left: 8.61 ± 1.71 mm vs. 8.86 ± 1.46 mm, p = 0.050), and bilateral femoral arteries (right: 6.77 ± 1.06 mm vs. 6.87 ± 1.00 mm, p = 0.157; left: 6.75 ± 1.02 mm vs. 6.90 ± 0.80 mm, p = 0.142). Both modalities showed similar aortic valve morphology and semi-quantitative valve calcification (all, p's > 0.05). Overall agreement for implanted THV was found in all 25 (100%) patients assessed with both modalities. Conclusion: REACT combined with 3D whole-heart MRI enables reliable measurements of aortic root anatomy, annular calcification, and aorta and iliofemoral access in patients under evaluation for TAVI.

Numerical analysis of the hemodynamics of rat aorta based on magnetic resonance imaging and fluid-structure interaction.

Murine models have been widely used to investigate the mechanobiology of aortic atherosclerosis and dissections, which develop preferably at different anatomic locations of aorta. Based MRI and finite element analysis with fluid-structure interaction, we numerically investigated factors that may affect the blood flow and structural mechanics of rat aorta. The results indicated that aortic root motion greatly increases time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), displacement of the aorta, and enhances helical flow pattern but has limited influence on effective stress, which is highly modulated by blood pressure. Moreover, the influence of the motion component on these indicators is different with axial motion more obvious than planar motion. Surrounding fixation of the intercostal arteries and the branch vessels on aortic arch would reduce the influence of aortic root motion. The compliance of the aorta has different influences at different regions, leading to decrease in TAWSS and helical flow, increase in OSI, RRT at the aortic arch, but has reversed effects on the branch vessels. When compared with the steady flow, the pulsatile blood flow would obviously increase the WSS, the displacement, and the effective stress in most regions. In conclusion, to accurately quantify the blood flow and structural mechanics of rat aorta, the motion of the aortic root, the compliance of aortic wall, and the pulsation of blood flow should be considered. However, when only focusing on the effective stress in rat aorta, the motion of the aortic root may be neglected.