[Show abstract][Hide abstract] ABSTRACT: Objective
We used magnetic resonance imaging (MRI) to study the prevalence and associated clinical characteristics of high-risk plaque (defined as presence of lipid-rich necrotic core [LRNC] and intraplaque hemorrhage) in the superficial femoral arteries (SFA) among people with peripheral artery disease (PAD).
The prevalence and clinical characteristics associated with high-risk plaque in the SFA are unknown.
Three-hundred-three participants with PAD underwent MRI of the proximal SFA using a 1.5 T S platform. Twelve contiguous 2.5 mm cross-sectional images were obtained.
LRNC was present in 68 (22.4%) participants. Only one had intra-plaque hemorrhage. After adjusting for age and sex, smoking prevalence was higher among adults with LRNC than among those without LRNC (35.9% vs. 21.4%, p = 0.02). Among participants with vs. without LRNC there were no differences in mean percent lumen area (31% vs. 33%, p = 0.42), normalized mean wall area (0.71 vs. 0.70, p = 0.67) or maximum wall area (0.96 vs. 0.92, p = 0.54) in the SFA. Among participants with LRNC, cross-sectional images containing LRNC had a smaller percent lumen area (33% ± 1% vs. 39% ± 1%, p < 0.001), greater normalized mean wall thickness (0.25 ± 0.01 vs. 0.22 ± 0.01, p < 0.001), and greater normalized maximum wall thickness (0.41 ± 0.01 vs. 0.31 ± 0.01, p < 0.001), compared to cross-sectional images without LRNC.
Fewer than 25% of adults with PAD had high-risk plaque in the proximal SFA using MRI. Smoking was the only clinical characteristic associated with presence of LRNC. Further study is needed to determine the prognostic significance of LRNC in the SFA.
Clinical trial registration—URL
http://www.clinicaltrials.gov. Unique identifier: NCT00520312.
[Show abstract][Hide abstract] ABSTRACT: We used magnetic resonance imaging (MRI) to study the prevalence and associated clinical characteristics of high-risk plaque (defined as presence of lipid-rich necrotic core [LRNC] and intraplaque hemorrhage) in the superficial femoral arteries (SFA) among people with peripheral artery disease (PAD).
[Show abstract][Hide abstract] ABSTRACT: There exists considerable controversy surrounding the timing and extent of aortic resection for patients with BAV disease. Since abnormal wall shear stress (WSS) is potentially associated with tissue remodeling in BAV-related aortopathy, we propose a methodology that creates patient-specific 'heat maps' of abnormal WSS, based on 4D flow MRI. The heat maps were created by detecting outlier measurements from a volumetric 3D map of ensemble-averaged WSS in healthy controls. 4D flow MRI was performed in 13 BAV patients, referred for aortic resection and 10 age-matched controls. Systolic WSS was calculated from this data, and an ensemble-average and standard deviation (SD) WSS map of the controls was created. Regions of the individual WSS maps of the BAV patients that showed a higher WSS than the mean + 1.96SD of the ensemble-average control WSS map were highlighted. Elevated WSS was found on the greater ascending aorta (35% ± 15 of the surface area), which correlated significantly with peak systolic velocity (R (2) = 0.5, p = 0.01) and showed good agreement with the resected aortic regions. This novel approach to characterize regional aortic WSS may allow clinicians to gain unique insights regarding the heterogeneous expression of aortopathy and may be leveraged to guide patient-specific resection strategies for aorta repair.
[Show abstract][Hide abstract] ABSTRACT: Associations of collateral vessels and lower extremity plaque with functional decline are unknown. Among people with peripheral artery disease (PAD), we determined whether greater superficial femoral artery (SFA) plaque burden combined with fewer lower extremity collateral vessels was associated with faster functional decline, compared to less plaque and/or more numerous collateral vessels. A total of 226 participants with ankle-brachial index (ABI) <1.00 underwent magnetic resonance imaging of lower extremity collateral vessels and cross-sectional imaging of the proximal SFA. Participants were categorized as follows: Group 1 (best), maximum plaque area < median and collateral vessel number ≥6 (median); Group 2, maximum plaque area < median and collateral vessel number <6; Group 3, maximum plaque area > median and collateral vessel number ≥6; Group 4 (worst), maximum plaque area > median and collateral vessel number <6. Functional measures were performed at baseline and annually for 2 years. Analyses adjust for age, sex, race, comorbidities, and other confounders. Annual changes in usual-paced walking velocity were: Group 1, +0.01 m/s; Group 2, -0.02 m/s; Group 3, -0.01 m/s; Group 4, -0.05 m/s (p-trend=0.008). Group 4 had greater decline than Group 1 (p<0.001), Group 2 (p=0.029), and Group 3 (p=0.010). Similar trends were observed for fastest-paced 4-meter walking velocity (p-trend=0.018). Results were not substantially changed when analyses were repeated with additional adjustment for ABI. However, there were no associations of SFA plaque burden and collateral vessel number with decline in 6-minute walk. In summary, a larger SFA plaque burden combined with fewer collateral vessels is associated with a faster decline in usual and fastest-paced walking velocity in PAD.
Vascular medicine (London, England). 07/2014; 19(4):281-288.
[Show abstract][Hide abstract] ABSTRACT: Paradoxical embolization is frequently posited as a mechanism of ischemic stroke in patients with patent foramen ovale. Several studies have suggested that the deep lower extremity and pelvic veins might be an embolic source in cryptogenic stroke (CS) patients with patent foramen ovale.
[Show abstract][Hide abstract] ABSTRACT: The objective of this study was to evaluate the potential of 4D flow MRI to assess valve effective orifice area (EOA) in patients with aortic stenosis as determined by the jet shear layer detection (JSLD) method.
[Show abstract][Hide abstract] ABSTRACT: Purpose: Patients with aortic dilation often exhibit eccentric transvalvular flow jets. The angle of the flow jet from the aorta centerline, or the flow jet angle (FJA), has been reported as a risk factor for aortic dilation in bicuspid aortic valve patients 1 . In recent studies, we introduced a jet shear layer detection (JSLD) method for the automated characterization of the transvalvular flow structure across the aortic valve 2,3 . The objective of this study was to develop and apply a new algorithm for the semiautomatic evaluation of FJA using a 3D JSLD structure based on 4D flow MRI data. Results in 30 patients with aortic dilation and varying degrees of aortic valve stenosis were compared to the manual calculation of flow angle using 2D analysis planes placed at the site of the vena contracta. Methods: 30 patients with aortic dilation and tricuspid aortic valves (age=56±17 years, female=7) were identified via retrospective chart review and IRB approval. The mid-ascending aorta (MAA) diameter was used to assess aortic (Ao) dilation and the presence of aortic valve stenosis was assessed with transvalvular peak velocity (PV). Patients were classified into three groups: Controls (MAA<35 mm and PV<1.5 m/s); Ao Dilation (MAA>35 mm and PV<1.5 m/s); Ao Dilation+Stenosis (MAA>35 mm and PV>1.5 m/s). 4D flow MRI was performed at 1.5T and 3T with full volumetric coverage of the thoracic aorta in a sagittal oblique 3D slab (spatial resolution=2.5×2.1×3.2 mm 3 ; temporal resolution=40-50 ms) using prospective ECG gating and a respiratory navigator placed on the lung-liver interface. Pulse sequence parameters were as follows: 1.5 T scan parameters ranged from TE/TR=2.3–3.4/4.8–6.6 ms, flip angle α=7–15° and the field of view was 340–400×200–300 mm; 3 T scans used TE/TR =2.5/5.1 ms, flip angle α=7–15°, and the field of view was 400×308 mm. 4D flow data were used to compute a 3D PC-MRA which allowed for 3D segmentation of the aorta (Mimics, Materialise, Leuven, Belgium). The segmented aorta was used to calculate: the vessel centerline, a masked velocity field, and the 3D JSLD structure (Matlab, Natick, MA, USA). The 3D JSLD structure was obtained from the peak systolic velocity field, V, by ∇(ωΛV) (where ω is the vorticity calculated by a Richardson interpolation scheme) and used to detect the post-valve jet-flow zone, i.e. vena contracta 2, 4 . A centerline segment at the vena contracta was used to obtain a centerline vector and the 3D JSLD structure center of mass vector. Both vectors were then used to estimate FJA (Fig. 1B). A workflow schematic for the 3D JSLD method is shown in Fig. 1C. For reference values, the manual FJA was calculated using 2D planes hand-positioned at the vena contracta (immediately downstream from the aortic valve, Fig. 1B). Both methods were compared by linear regression and Bland-Altman analysis with the 2D FJA as the reference. Results and Discussion: Patient characteristics are summarized in Table 1. A significant difference between Ao Dilation and Ao Dilation+Stenosis vs. Control was observed for age (p<0.05) and MAA (p<0.001). The ejection fraction was higher in Ao Dilation (p<0.05 vs. Control). Bland-Altman analysis (Fig. 2A) showed that difference between 2D velocity and 3D JSLD FJA increases with MAA diameter and valve stenosis. The FJA derived from 3D JSLD and 2D planar analysis were significantly different between Ao Dilation and Ao Dilation+Stenosis, as compared to Controls (p<0.05, Fig. 2B). Noticeably, the 3D JSLD FJA method detected significant differences between stenotic vs. non-stenotic Ao dilatation (p<0.001) while planar FJA analysis did not. A higher FJA was most likely found in Ao Dilation+Stenosis due to the presence of a larger MAA and a higher degree of valvular obstruction. A significant relationship was found between PV and 3D JSLD FJA (r=0.515, p<0.05), suggesting a relationship of FJA and aortic stenosis severity. The 3D JSLD FJA method detected differences between stenotic and non-stenotic Ao dilation groups, while the 2D method did not. Manual interaction while placing 2D analysis planes may have increased measurement noise. The decreased user interaction required for the 3D JSLD method may reduce measurement noise and enable stratification of flow angle differences between the stenotic and non-stenotic Ao dilation groups. Previous studies suggest that flow jet impingement on the convexity aortic area may led to wall remodeling (i.e. aortic dilation) 5 . Although this is a cross-sectional study and longitudinal outcomes were not examined, it is important to note the positive correlation between aortic dilation and FJA. Furthermore, FJA was observed to be closely related to valve hemodynamics (i.e. PV). This is important given recent findings that FJA is associated with aortic stenosis severity and left ventricle remodeling 6 . Thus, FJA is important to investigate for a relationship to aortic wall remodeling and valve and left ventricle function. These findings highlight a potential application of the JSLD FJA algorithm. Conclusion: The assessment of FJA can be automated using the volumetric 3D JSLD structure and the aorta centerline using data from 4D flow MRI exams. Using this technique, the FJA was found to be significantly higher in patients with severe aortic dilation and aortic valve stenosis. Future longitudinal studies are needed to evaluate the impact of FJA on the progression of aortic dilation.: Flow jet angle estimation using 4D flow data and jet shear layer detection method. A) Velocity streamlines inside the 3D segmentation of the aorta (segmentation obtained from the 3D PC-MRA). The black box indicates the region magnified in 'B'. B) Dashed lines indicate the level of the left ventricle outflow tract (LVOT) and vena contracta (AoVC). The AoVC plane was used to estimate the 2D flow jet angle. Jet shear layer detection (JSLD) was computed from the full 4D flow dataset. The resulting lateral view of the 3D JSLD structure (red volume) and volume centerline (black) is shown. The centerline vector (yellow arrow) and 3D JSLD center of mass vector (green arrow) determine the jet flow angle. C) Workflow schematic for the computation of the 3D JSLD jet angle.
[Show abstract][Hide abstract] ABSTRACT: Purpose: Time-resolved 3D PC-MRI with three-directional velocity encoding (4D flow MRI) has been successfully applied in a number of studies for the analysis of altered hemodynamics in patients with cardiovascular disease 1 . Data analysis, however, can be time consuming and often relies on the manual placement of 2D analysis planes at user defined vascular regions of interest. The analysis of flow parameters and derived metrics of hemodynamics are thus often limited by observer variability. In addition, the inherent volumetric 3D coverage of the vascular system of interest provided by 4D flow MRI is not fully utilized by analysis based on 2D planes. Nevertheless, a number of studies have shown that 4D flow MRI can detect the impact of vascular disease on changes in vascular hemodynamics. It was thus the aim of this study to evaluate a novel automated flow distribution analysis based on the evaluation the blood flow velocity distributions in the entire 3D vessel segments to identify hemodynamic 'fingerprints' of different aortic pathologies. Our goal was to test the feasibility of in-vivo hemodynamic fingerprinting to identify altered 3D flow characteristics in patients with aortic dilation and aortic valve stenosis without the need for the manual definition of 2D analysis planes. Methods: 40 subjects (10 controls and 30 patients with aortic dilation and tricuspid aortic valves) (age=56±17 years, female=11) were identified via an IRB-approved retrospective chart review. The mid-ascending aorta (MAA) diameter was used to stratify by aortic (Ao) dilation and aortic valve peak velocity (PV) was used to determine the presence of aortic valve stenosis (AS). Each subject was classified into four groups: controls (n=10, MAA<35 mm and PV<1.5 m/s); moderate Ao dilation (n=10, 35<MAA<45 mm and PV<1.5 m/s); severe Ao dilation (n=10, MAA>45 mm and PV<1.5 m/s); Ao dilation + AS (n=10, MAA>35 mm and PV>1.5 m/s). 4D flow MRI was performed at 1.5T and 3T with full 3D coverage of the thoracic aorta (spatial resolution=2.5×2.1×3.2 mm 3 ; temporal resolution=40-50 ms) using prospective ECG gating and a respiratory navigator gating. Pulse sequence parameters were as follows: 1.5 T scan parameters ranged from TE/TR=2.3–3.4/4.8–6.6 ms, flip angle α=7–15° and a field of view of 340–400×200–300 mm; 3T scans used TE/TR =2.5/5.1 ms, flip angle α=7–15°, and a field of view of 400×308 mm. 3D PC-MR angiograms were computed and used to obtain a 3D segmentation of the aorta (Mimics, Materialise, Leuven, Belgium). Based on the segmentation, 4 aortic sub-regions were analyzed (see Fig. 1), including: Segment 1, traversing the left ventricle outflow tract to the sinotubular junction; Segment 2, which progresses from the sino-tubular junction to the aortic arch; Segment 3, which covers the aortic arch; and Segment 4, which includes the proximal descending aorta. The four vascular 3D segments were used to compute a masked 4D velocity field (3 spatial dimensions + time) for each aortic segment. The masked aorta velocity fieled was used to generate a time-resolved maximum intensity projection (MIP) in an oblique sagittal plane using the three peak systolic velocity phases, Fig. 1A. The velocities for all voxels and cardiac time-frames inside an aortic segment were plotted in histogram form and normalized by the total number of voxels in order to create a cohort-specific hemodynamic fingerprint that can be compared across subjects and cohorts. In addition, mean, median, standard deviation, and the normalized number of voxels >1m/s (incidence) were calculated as shown in Fig. 1B for Segment 2 (Matlab, Natick, MA, USA). A sensitivity analysis was conducted to identify which proportions of the velocity distribution (number of time frames and top % of velocities) were most sensitive to differences in flow distribution between patient groups and controls. At each threshold, a t-test was conducted to evaluate the significance of difference between groups and it was determined that the first 8 time steps of the cardiac cycle (320-400ms) and 100% of the data were optimal for the detection of cohort differences. Results: Subject characteristics are summarized in Table 1. All subjects had normal ejection fraction (60±7%), although severe Ao Dilation was significantly elevated (p<0.05 vs. Controls). Examples of velocity MIPs in Fig. 1A visually illustrate disease specific differences in the aortic velocity patterns and distribution. The appearance of the patient flow patterns, as seen in the velocity MIPs, were heterogeneous compared to controls. The dilated aortas displayed outflow jets and high flow regions (red color) which were most pronounced for the AS patients. Examples of spider web plots for flow parameter fingerprints are shown in Fig. 1C, which provide a visual impression of the flow characteristics. The velocity histogram parameters are shown in Fig. 1C-F. The mean velocity for Ao Dilation+AS was significantly different from other groups in all segments due to aortic stenosis, Fig. 1C. Interestingly for median velocities, Segment 2 showed a significant difference between moderate Ao Dilation and Ao Dilation+AS, Fig. 1D. These differences may be due to the severity of Ao dilation and helical flow in groups with Ao dilation. For almost all segments, the velocity standard deviation was significantly higher for Ao Dilation+AS vs. other groups (Fig. 1E). The incidence for velocities > 1 m/s was significantly increased for Ao Dilation+AS in segment 1 due to valve stenosis. Discussion: The volumetric velocity distribution analysis presented here has demonstrated: 1) 3D blood flow velocity distributions may identify hemodynamic fingerprints of different aortic pathologies via basic statistical descriptors (i.e. mean, median, standard deviation and incidence), and 2) the characterization of hemodynamic fingerprints along regional aortic segments in subjects with aortic disease. The automatic distribution analysis of 4D flow data may be useful in the automated characterization or hemodynamic 'fingerprinting' of cardiovascular disease by identifying simple characteristic parameters associated with the presence of pathology. The results indicate a selection of blood flow behaviours which are capable of stratifying the presence of disease, as shown for Ao Dilation+AS group. Conclusion: The systematic velocity distribution analysis of 4D flow velocity data may identify fingerprint characteristic of blood flow patterns in aortic diseases. Further studies are needed to evaluate the association of velocity distribution derived descriptors with patient outcome. Acknowledgment: Grant support by NIH R01HL115828, AHA 13SDG14360004, CONACyT postdoctoral fellow grant (223355). References: 1. Markl M et al. J Magn Res Imaging 2012; 36:1015-36. FIG. 1: Velocity distribution analysis. A) Time-resolved maximum intensity projection of the masked velocity field in an oblique-sagittal view for example patients from each group. B) Volumetric segmentation of the entire aorta and the regional segments used in the velocity distribution analysis. The velocity distribution for segment 2 is shown. C) Spider web plots provide a visual impression of the histogram characteristics for Segment 1 (left) and 2 (right). Plots are in arbitrary units (AU). D-G) Plots for the mean, median, standard deviation and incidence obtained from the velocity field analysis for each segment of the aorta as stratified by group. : p<0.05 with Controls; : p<0.001 with moderate Ao Dilation;*: p<0.001 with severe Ao Dilation. Each symbol is color-coded to the corresponding group.
[Show abstract][Hide abstract] ABSTRACT: Aortic 3D blood flow was analyzed to investigate altered ascending aorta (AAo) hemodynamics in bicuspid aortic valve (BAV) patients and its association with differences in cusp fusion patterns (right-left, RL versus right-noncoronary, RN) and expression of aortopathy.
4D flow MRI measured in vivo 3D blood flow in the aorta of 75 subjects: BAV patients with aortic dilatation stratified by leaflet fusion pattern (n=15 RL-BAV, mid AAo diameter=39.9±4.4mm; n=15 RN-BAV, 39.6±7.2mm); aorta size controls with tricuspid aortic valves (n=30, 41.1±4.4mm); healthy volunteers (n=15, 24.9±3.0mm). Aortopathy type (0-3), systolic flow angle, flow displacement, and regional wall shear stress (WSS) were determined for all subjects. Eccentric outflow jet patterns in BAV patients resulted in elevated regional WSS (p<0.0125) at the right-anterior walls for RL-BAV and right-posterior walls for RN-BAV compared to aorta size controls. Dilatation of the aortic root only (type 1) or involving the entire AAo and arch (type 3) was found in the majority of RN-BAV patients (87%) but was mostly absent for RL-BAV (87% type 2). Differences in aortopathy type between RL-BAV and RN-BAV were associated with altered flow displacement in the proximal and mid AAo for type 1 (42-81% decrease versus type 2) and distal AAo for type 3 (33-39% increase versus type 2).
The presence and type of BAV fusion was associated with changes in regional WSS distribution, systolic flow eccentricity, and expression of BAV aortopathy. Hemodynamic markers suggest a physiologic mechanism by which valve morphology phenotype can influence phenotypes of BAV aortopathy.
[Show abstract][Hide abstract] ABSTRACT: Thoracic aortic aneurysm is one of the most common aorta pathologies worldwide, which is commonly evaluated by computed tomography angiography (CTA). One of the routine methods to improve the image quality of CTA is heart rate reduction prior to study by beta-blockade administration.
To assess the effect of beta-blockade on image quality of the ascending aorta in electrocardiography (ECG)-gated dual-source CTA (DSCTA) images.
In this retrospective study, ECG-gated thoracic aorta CTA images of 40 patients without beta-blocker administration were compared with ECG-gated images of 40 patients with beta-blockade. Images of the aorta were analyzed objectively and subjectively at three levels: sinus of Valsalva (sinus), sinotubular junction (STJ), and mid ascending aorta (MAA). Quantitative sharpness index (SI) and signal-to-noise ratio (SNR) were calculated and two radiologists evaluated the image quality using a 3-point scale.
Mean heart rate in beta-blocker and non-beta-blocker groups was 61.7 beats per minute (bpm) (range, 58.1-63.9 bpm) and 72.9 bpm (range, 69.3-84.1 bpm), respectively (P <0.05). Aorta wall SI, SNR, and subjective grading were comparable between the two groups at all three levels (P >0.05).
Beta-blocker premedication may not be necessary for imaging of ascending aorta with ECG-gated DSCTA.
[Show abstract][Hide abstract] ABSTRACT: To investigate the influence of atherosclerotic plaques on femoral haemodynamics assessed by two-dimensional (2D) phase-contrast (PC) magnetic resonance imaging (MRI) with three-directional velocity encoding.
During 1 year, patients with peripheral artery disease and an ankle brachial index <1.00 were enrolled. After institutional review board approval and written informed consent, 44 patients (age, 70 ± 12 years) underwent common femoral artery MRI. Patients with contra-indications for MRI were excluded. Sequences included 2D time-of-flight, proton-density, T1-weighted and T2-weighted MRI. Electrocardiogram (ECG)-gated 2D PC-MRI with 3D velocity encoding was acquired. A radiologist classified images in five categories. Blood flow, velocity and wall shear stress (WSS) along the vessel circumference were quantified from the PC-MRI data.
The acquired images were of good quality for interpretation. There were no image quality problems related to poor ECG-gating or slice positioning. Velocities, oscillatory shear stress and total flow were similar between patients with normal arteries and wall thickening/plaque. Patients with plaques demonstrated regionally increased peak systolic WSS and enhanced WSS eccentricity.
Combined multi-contrast morphological imaging of the peripheral arterial wall with PC-MRI with three-directional velocity encoding is a feasible technique. Further study is needed to determine whether flow is an appropriate marker for altered endothelial cell function, vascular remodelling and plaque progression.
• Femoral plaques are associated with altered dynamics of peripheral blood flow. • Multi-contrast MRI can investigate the presence and type of atherosclerotic plaques. • Three-dimensional velocity-encoding phase-contrast MRI can investigate flow and wall shear stress. • Atherosclerotic peripheral arteries demonstrate increased systolic velocities and wall shear stress.
[Show abstract][Hide abstract] ABSTRACT: We present an analysis of 3D blood flow in two cases of Sinus of Valsalva to right heart fistulae based on 4D flow MRI. Despite similar underlying pathology, 3D visualization revealed intricate differences in flow patterns connecting the systemic and pulmonary circulation. The cases illustrates the potential of 4D flow MRI to complement the evaluation of complex structural heart disease by assessing complex flow dynamics and providing quantitative information of flow ratios and flow rates.
Magnetic Resonance Imaging 10/2013; 31(8):1453-5. · 2.06 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The aim of this study was to investigate changes in segmental, three-directional left ventricular (LV) velocities in patients after heart transplantation (Tx).
Magnetic resonance tissue phase mapping was used to assess myocardial velocities in patients after Tx (n = 27) with normal LV ejection fraction (63 ± 5%) and those without signs of rejection. Regional wall motion and dyssynchrony were analysed in relation to cold ischaemic time (150 ± 57 min, median = 154 min), age of the donor heart (35 ± 13 years, median = 29 years), time after transplantation (32 ± 26 months, median = 31 months) and global LV morphology and function.
Segmental myocardial velocities were significantly altered in patients with cold ischaemic times >155 min resulting in an increase in peak systolic radial velocities (2 of 16 segments, P = 0.03-0.04) and reduced segmental diastolic long-axis velocities (5 of 16 segments, P = 0.01-0.04). Time after transplantation (n = 8 patients <12 months after Tx vs n = 19 >12 months) had a significant influence on systolic radial velocities (increased in 2 of 16 segments, P = 0.01-0.04) and diastolic long-axis velocities (reduced in 5 of 16 segments, P = 0.02-0.04). Correlation analysis and multiple regression revealed significant relationships of cold ischaemic time (R = -0.384, P = 0.048), the donor heart's age (β = 0.9, P = 0.01) and time from transplantation (β = -0.36, P = 0.03) with long-axis diastolic dyssynchrony.
Time after transplantation and cold ischaemic time strongly affect segmental systolic and diastolic motion in patients after Tx. The understanding of alterations in regional LV motion in the transplanted heart under stable conditions is essential in order to utilize this methodology in the future as a potentially non-invasive means of diagnosing transplant rejection.
European journal of cardio-thoracic surgery: official journal of the European Association for Cardio-thoracic Surgery 09/2013; · 2.40 Impact Factor