Purpose
Tensor‐valued diffusion encoding can probe more specific features of tissue microstructure than what is available by conventional diffusion weighting. In this work, we investigate the ...technical feasibility of tensor‐valued diffusion encoding at high b‐values with q‐space trajectory imaging (QTI) analysis, in the human heart in vivo.
Methods
Ten healthy volunteers were scanned on a 3T scanner. We designed time‐optimal gradient waveforms for tensor‐valued diffusion encoding (linear and planar) with second‐order motion compensation. Data were analyzed with QTI. Normal values and repeatability were investigated for the mean diffusivity (MD), fractional anisotropy (FA), microscopic FA (μFA), isotropic, anisotropic and total mean kurtosis (MKi, MKa, and MKt), and orientation coherence (Cc). A phantom, consisting of two fiber blocks at adjustable angles, was used to evaluate sensitivity of parameters to orientation dispersion and diffusion time.
Results
QTI data in the left ventricular myocardium were MD = 1.62 ± 0.07 μm2/ms, FA = 0.31 ± 0.03, μFA = 0.43 ± 0.07, MKa = 0.20 ± 0.07, MKi = 0.13 ± 0.03, MKt = 0.33 ± 0.09, and Cc = 0.56 ± 0.22 (mean ± SD across subjects). Phantom experiments showed that FA depends on orientation dispersion, whereas μFA was insensitive to this effect.
Conclusion
We demonstrated the first tensor‐valued diffusion encoding and QTI analysis in the heart in vivo, along with first measurements of myocardial μFA, MKi, MKa, and Cc. The methodology is technically feasible and provides promising novel biomarkers for myocardial tissue characterization.
In silico tissue models (viz. numerical phantoms) provide a mechanism for evaluating quantitative models of magnetic resonance imaging. This includes the validation and sensitivity analysis of ...imaging biomarkers and tissue microstructure parameters. This study proposes a novel method to generate a realistic numerical phantom of myocardial microstructure. The proposed method extends previous studies by accounting for the variability of the cardiomyocyte shape, water exchange between the cardiomyocytes (intercalated discs), disorder class of myocardial microstructure, and four sheetlet orientations. In the first stage of the method, cardiomyocytes and sheetlets are generated by considering the shape variability and intercalated discs in cardiomyocyte—cardiomyocyte connections. Sheetlets are then aggregated and oriented in the directions of interest. The morphometric study demonstrates no significant difference (p>0.01) between the distribution of volume, length, and primary and secondary axes of the numerical and real (literature) cardiomyocyte data. Moreover, structural correlation analysis validates that the in-silico tissue is in the same class of disorderliness as the real tissue. Additionally, the absolute angle differences between the simulated helical angle (HA) and input HA (reference value) of the cardiomyocytes (4.3°±3.1°) demonstrate a good agreement with the absolute angle difference between the measured HA using experimental cardiac diffusion tensor imaging (cDTI) and histology (reference value) reported by (Holmes et al., 2000) (3.7°±6.4°) and (Scollan et al. 1998) (4.9°±14.6°). Furthermore, the angular distance between eigenvectors and sheetlet angles of the input and simulated cDTI is much smaller than those between measured angles using structural tensor imaging (as a gold standard) and experimental cDTI. Combined with the qualitative results, these results confirm that the proposed method can generate richer numerical phantoms for the myocardium than previous studies.
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•Presents a novel method for generating in-silico cardiac microstructure.•Discusses biophysical parameters of cardiac tissue that may affect dMRI signal.•In-silico cardiomyocytes statistically follow shape parameters of the real cells.•In-silico cardiac tissue falls into the same class of disorderliness as the real one.•In-silico cardiac tissue is useful for sensitivity analysis of dMRI signal.
Adverse LV remodeling post-ST-segment elevation myocardial infarction (STEMI) is associated with a poor prognosis, but the underlying mechanisms are not fully understood. Diffusion tensor ...(DT)-cardiac magnetic resonance (CMR) allows in vivo characterization of myocardial architecture and provides unique mechanistic insight into pathophysiologic changes following myocardial infarction.
This study evaluated the potential associations between DT-CMR performed soon after STEMI and long-term adverse left ventricular (LV) remodeling following STEMI.
A total of 100 patients with STEMI underwent CMR at 5 days and 12 months post-reperfusion. The protocol included DT-CMR for assessing fractional anisotropy (FA), secondary eigenvector angle (E2A) and helix angle (HA), cine imaging for assessing LV volumes, and late gadolinium enhancement for calculating infarct and microvascular obstruction size. Adverse remodeling was defined as a 20% increase in LV end-diastolic volume at 12 months.
A total of 32 patients experienced adverse remodeling at 12 months. Compared with patients without adverse remodeling, they had lower FA (0.23 ± 0.03 vs 0.27 ± 0.04; P < 0.001), lower E2A (37 ± 6° vs 51 ± 7°; P < 0.001), and, on HA maps, a lower proportion of myocytes with right-handed orientation (RHM) (8% ± 5% vs 17% ± 9%; P < 0.001) in their acutely infarcted myocardium. On multivariable logistic regression analysis, infarct FA (odds ratio OR: <0.01; P = 0.014) and E2A (OR: 0.77; P = 0.001) were independent predictors of adverse LV remodeling after adjusting for left ventricular ejection fraction (LVEF) and infarct size. There were no significant changes in infarct FA, E2A, or RHM between the 2 scans.
Extensive cardiomyocyte disorganization (evidenced by low FA), acute loss of sheetlet angularity (evidenced by low E2A), and a greater loss of organization among cardiomyocytes with RHM, corresponding to the subendocardium, can be detected within 5 days post-STEMI. These changes persist post-injury, and low FA and E2A are independently associated with long-term adverse remodeling.
Diffusion tensor imaging (DTI) is widely used to assess tissue microstructure non-invasively. Cardiac DTI enables inference of cell and sheetlet orientations, which are altered under pathological ...conditions. However, DTI is affected by many factors, therefore robust validation is critical. Existing histological validation is intrinsically flawed, since it requires further tissue processing leading to sample distortion, is routinely limited in field-of-view and requires reconstruction of three-dimensional volumes from two-dimensional images. In contrast, synchrotron radiation imaging (SRI) data enables imaging of the heart in 3D without further preparation following DTI. The objective of the study was to validate DTI measurements based on structure tensor analysis of SRI data.
One isolated, fixed rat heart was imaged ex vivo with DTI and X-ray phase contrast SRI, and reconstructed at 100 μm and 3.6 μm isotropic resolution respectively. Structure tensors were determined from the SRI data and registered to the DTI data.
Excellent agreement in helix angles (HA) and transverse angles (TA) was observed between the DTI and structure tensor synchrotron radiation imaging (STSRI) data, where HA
= -1.4° ± 23.2° and TA
= -1.4° ± 35.0° (mean ± 1.96 standard deviation across all voxels in the left ventricle). STSRI confirmed that the primary eigenvector of the diffusion tensor corresponds with the cardiomyocyte long-axis across the whole myocardium.
We have used STSRI as a novel and high-resolution gold standard for the validation of DTI, allowing like-with-like comparison of three-dimensional tissue structures in the same intact heart free of distortion. This represents a critical step forward in independently verifying the structural basis and informing the interpretation of cardiac DTI data, thereby supporting the further development and adoption of DTI in structure-based electro-mechanical modelling and routine clinical applications.
Cardiac architecture is fundamental to cardiac function and can be assessed non-invasively with diffusion tensor imaging (DTI). Here, we aimed to overcome technical challenges in ex vivo DTI in order ...to extract fine anatomical details and to provide novel insights in the 3D structure of the heart. An integrated set of methods was implemented in ex vivo rat hearts, including dynamic receiver gain adjustment, gradient system scaling calibration, prospective adjustment of diffusion gradients, and interleaving of diffusion-weighted and non-diffusion-weighted scans. Together, these methods enhanced SNR and spatial resolution, minimised orientation bias in diffusion-weighting, and reduced temperature variation, enabling detection of tissue structures such as cell alignment in atria, valves and vessels at an unprecedented level of detail. Improved confidence in eigenvector reproducibility enabled tracking of myolaminar structures as a basis for segmentation of functional groups of cardiomyocytes. Ex vivo DTI facilitates acquisition of high quality structural data that complements readily available in vivo cardiac functional and anatomical MRI. The improvements presented here will facilitate next generation virtual models integrating micro-structural and electro-mechanical properties of the heart.
Microvascular dysfunction in hypertrophic cardiomyopathy (HCM) is predictive of clinical decline, however underlying mechanisms remain unclear. Cardiac diffusion tensor imaging (cDTI) allows in vivo ...characterization of myocardial microstructure by quantifying mean diffusivity (MD), fractional anisotropy (FA) of diffusion, and secondary eigenvector angle (E2A). In this cardiac magnetic resonance (CMR) study, we examine associations between perfusion and cDTI parameters to understand the sequence of pathophysiology and the interrelation between vascular function and underlying microstructure.
Twenty HCM patients underwent 3.0T CMR which included: spin-echo cDTI, adenosine stress and rest perfusion mapping, cine-imaging, and late gadolinium enhancement (LGE). Ten controls underwent cDTI. Myocardial perfusion reserve (MPR), MD, FA, E2A, and wall thickness were calculated per segment and further divided into subendocardial (inner 50%) and subepicardial (outer 50%) regions. Segments with wall thickness ≤11 mm, MPR ≥2.2, and no visual LGE were classified as 'normal'. Compared to controls, 'normal' HCM segments had increased MD (1.61 ± 0.09 vs. 1.46 ± 0.07 × 10-3 mm2/s, P = 0.02), increased E2A (60 ± 9° vs. 38 ± 12°, P < 0.001), and decreased FA (0.29 ± 0.04 vs. 0.35 ± 0.02, P = 0.002). Across all HCM segments, subendocardial regions had higher MD and lower MPR than subepicardial (MDendo 1.61 ± 0.08 × 10-3 mm2/s vs. MDepi 1.56 ± 0.18 × 10-3 mm2/s, P = 0.003, MPRendo 1.85 ± 0.83, MPRepi 2.28 ± 0.87, P < 0.0001).
In HCM patients, even in segments with normal wall thickness, normal perfusion, and no scar, diffusion is more isotropic than in controls, suggesting the presence of underlying cardiomyocyte disarray. Increased E2A suggests the myocardial sheetlets adopt hypercontracted angulation in systole. Increased MD, most notably in the subendocardium, is suggestive of regional remodelling which may explain the reduced subendocardial blood flow.
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