Magnetic resonance imaging based modeling of microvascular perfusion in patients with peripheral artery disease

Contrast-Enhanced Magnetic Resonance Imaging Based T1 Mapping and Extracellular Volume Fractions Are Associated with Peripheral Artery Disease

BACKGROUND

Extracellular volume fraction (ECV), measured with contrast-enhanced magnetic resonance imaging (CE-MRI), has been utilized to study myocardial fibrosis, but its role in peripheral artery disease (PAD) remains unknown. We hypothesized that T1 mapping and ECV differ between PAD patients and matched controls.

METHODS AND RESULTS

A total of 37 individuals (18 PAD patients and 19 matched controls) underwent 3.0T CE-MRI. Skeletal calf muscle T1 mapping was performed before and after gadolinium contrast with a motion-corrected modified look-locker inversion recovery (MOLLI) pulse sequence. T1 values were calculated with a three-parameter Levenberg-Marquardt curve fitting algorithm. ECV and T1 maps were quantified in five calf muscle compartments (anterior [AM], lateral [LM], and deep posterior [DM] muscle groups; soleus [SM] and gastrocnemius [GM] muscles). Averaged peak blood pool T1 values were obtained from the posterior and anterior tibialis and peroneal arteries. T1 values and ECV are heterogeneous across calf muscle compartments. Native peak T1 values of the AM, LM, and DM were significantly higher in PAD patients compared to controls (all p < 0.028). ECVs of the AM and SM were significantly higher in PAD patients compared to controls (AM: 26.4% (21.2, 31.6) vs. 17.3% (10.2, 25.1), p = 0.046; SM: 22.7% (19.5, 27.8) vs. 13.8% (10.2, 19.1), p = 0.020).

CONCLUSIONS

Native peak T1 values across all five calf muscle compartments, and ECV fractions of the anterior muscle group and the soleus muscle were significantly elevated in PAD patients compared with matched controls. Non-invasive T1 mapping and ECV quantification may be of interest for the study of PAD.

A machine learning-based approach to identify peripheral artery disease using texture features from contrast-enhanced magnetic resonance imaging

Diagnosing and assessing the risk of peripheral artery disease (PAD) has long been a focal point for medical practitioners. The impaired blood circulation in PAD patients results in altered microvascular perfusion patterns in the calf muscles which is the primary location of intermittent claudication pain. Consequently, we hypothesized that changes in perfusion and increase in connective tissue could lead to alterations in the appearance or texture patterns of the skeletal calf muscles, as visualized with non-invasive imaging techniques. We designed an automatic pipeline for textural feature extraction from contrast-enhanced magnetic resonance imaging (CE-MRI) scans and used the texture features to train machine learning models to detect the heterogeneity in the muscle pattern among PAD patients and matched controls. CE-MRIs from 36 PAD patients and 20 matched controls were used for preparing training and testing data at a 7:3 ratio with cross-validation (CV) techniques. We employed feature arrangement and selection methods to optimize the number of features. The proposed method achieved a peak accuracy of 94.11% and a mean testing accuracy of 84.85% in a 2-class classification approach (controls vs. PAD). A three-class classification approach was performed to identify a high-risk PAD sub-group which yielded an average test accuracy of 83.23% (matched controls vs. PAD without diabetes vs. PAD with diabetes). Similarly, we obtained 78.60% average accuracy among matched controls, PAD treadmill exercise completers, and PAD exercise treadmill non-completers. Machine learning and imaging-based texture features may be of interest in the study of lower extremity ischemia.

Single and bi-compartment poro-elastic model of perfused biological soft tissues: FEniCSx implementation and tutorial

Soft biological tissues demonstrate strong time-dependent and strain-rate mechanical behavior, arising from their intrinsic visco-elasticity and fluid-solid interactions. The time-dependent mechanical properties of soft tissues influence their physiological functions and are related to several pathological processes. Poro-elastic modeling represents a promising approach because it allows the integration of multiscale/multiphysics data to probe biologically relevant phenomena at a smaller scale and embeds the relevant mechanisms at the larger scale. The implementation of multiphase flow poro-elastic models however is a complex undertaking, requiring extensive knowledge. The open-source software FEniCSx Project provides a novel tool for the automated solution of partial differential equations by the finite element method. This paper aims to provide the required tools to model the mixed formulation of poro-elasticity, from the theory to the implementation, within FEniCSx. Several benchmark cases are studied. A column under confined compression conditions is compared to the Terzaghi analytical solution, using the L2-norm. An implementation of poro-hyper-elasticity is proposed. A bi-compartment column is compared to previously published results (Cast3m implementation). For all cases, accurate results are obtained in terms of a normalized Root Mean Square Error (RMSE). Furthermore, the FEniCSx computation is found three times faster than the legacy FEniCS one. The benefits of parallel computation are also highlighted.

Magnetic Resonance Imaging-Derived Microvascular Perfusion Modeling to Assess Peripheral Artery Disease

Background Computational fluid dynamics has shown good agreement with contrast-enhanced magnetic resonance imaging measurements in cardiovascular disease applications. We have developed a biomechanical model of microvascular perfusion using contrast-enhanced magnetic resonance imaging signal intensities derived from skeletal calf muscles to study peripheral artery disease (PAD). Methods and Results The computational microvascular model was used to study skeletal calf muscle perfusion in 56 individuals (36 patients with PAD, 20 matched controls). The recruited participants underwent contrast-enhanced magnetic resonance imaging and ankle-brachial index testing at rest and after 6-minute treadmill walking. We have determined associations of microvascular model parameters including the transfer rate constant, a measure of vascular leakiness; the interstitial permeability to fluid flow which reflects the permeability of the microvasculature; porosity, a measure of the fraction of the extracellular space; the outflow filtration coefficient; and the microvascular pressure with known markers of patients with PAD. Transfer rate constant, interstitial permeability to fluid flow, and microvascular pressure were higher, whereas porosity and outflow filtration coefficient were lower in patients with PAD than those in matched controls (all P values ≤0.014). In pooled analyses of all participants, the model parameters (transfer rate constant, interstitial permeability to fluid flow, porosity, outflow filtration coefficient, microvascular pressure) were significantly associated with the resting and exercise ankle-brachial indexes, claudication onset time, and peak walking time (all P values ≤0.013). Among patients with PAD, interstitial permeability to fluid flow, and microvascular pressure were higher, while porosity and outflow filtration coefficient were lower in treadmill noncompleters compared with treadmill completers (all P values ≤0.001). Conclusions Computational microvascular model parameters differed significantly between patients with PAD and matched controls. Thus, computational microvascular modeling could be of interest in studying lower extremity ischemia.

Société de Biomécanique Young Investigator Award 2021: Numerical investigation of the time-dependent stress-strain mechanical behaviour of skeletal muscle tissue in the context of pressure ulcer prevention

BACKGROUND

Pressure-induced tissue strain is one major pathway for Pressure Ulcer development and, especially, Deep Tissue Injury. Biomechanical investigation of the time-dependent stress-strain mechanical behaviour of skeletal muscle tissue is therefore essential. In the literature, a viscoelastic formulation is generally assumed for the experimental characterization of skeletal muscles, with the limitation that the underlying physical mechanisms that give rise to the time dependent stress-strain behaviour are not known. The objective of this study is to explore the capability of poroelasticity to reproduce the apparent viscoelastic behaviour of passive muscle tissue under confined compression.

METHODS

Experimental stress-relaxation response of 31 cylindrical porcine samples tested under fast and slow confined compression by Vaidya and collaborators were used. An axisymmetric Finite Element model was developed in ABAQUS and, for each sample a one-to-one inverse analysis was performed to calibrate the specimen-specific constitutive parameters, namely, the drained Young's modulus, the void ratio, hydraulic permeability, the Poisson's ratio, the solid grain's and fluid's bulk moduli.

FINDINGS

The peak stress and consolidation were recovered for most of the samples (N=25) by the poroelastic model (normalised root-mean-square error ≤0.03 for fast and slow confined compression conditions).

INTERPRETATION

The strength of the proposed model is its fewer number of variables (N=6 for the proposed poroelastic model versus N=18 for the viscohyperelastic model proposed by Vaidya and collaborators). The incorporation of poroelasticity to clinical models of Pessure Ulcer formation could lead to more precise and mechanistic explorations of soft tissue injury risk factors.

Relation of Magnetic Resonance Imaging Based Arterial Signal Enhancement to Markers of Peripheral Artery Disease

Peripheral artery disease (PAD) is associated with impaired lower extremity function. We hypothesized that contrast-enhanced magnetic resonance imaging (CE-MRI) based arterial signal enhancement (SE) measures are associated with markers of PAD. A total of 66 participants were enrolled, 10 were excluded due to incomplete data, resulting in 56 participants for the final analyses (36 PAD, 20 matched controls). MR imaging was performed postreactive hyperemia using bilateral thigh blood-pressure cuffs. First pass-perfusion images were acquired at the mid-calf region with a high-resolution saturation recovery gradient echo pulse sequence, and arterial SE was measured for the lower extremity arteries. As expected, peak walking time (PWT) was reduced in PAD patients compared with controls (282 [248 to 317] sec, vs 353 [346 to 360] sec; p = 0.002), and postexercise ankle brachial index (ABI) decreased in PAD patients but not in controls (PAD: 0.75 ± 0.2, 0.60 [0.5 to 0.7]; p <0.001; vs Controls: 1.17 ± 0.1, 1.19 [1.1 to 1.2]; p = 0.50). Intraclass correlation coefficients were excellent for inter- and intraobserver variability of arterial tracings (n = 10: 0.95 (95%-confidence interval [CI]: 0.94 to 0.96), n = 9: 1.0 (CI: 1.0 to 1.0). Minimum arterial SE was reduced in PAD patients compared with matched controls (128 [110 to 147] A.U. vs 192 [149 to 234] A.U., p = 0.003). Among PAD patients but not in controls the maximum arterial SE was associated with the estimated glomerular filtration rate (eGFR), a marker of renal function (n = 36, ß = 1.37, R² = 0.12, p = 0.025). In conclusion, CE-MRI first-pass arterial perfusion is impaired in PAD patients compared with matched controls and associated with markers of lower extremity ischemia.

Experimental Validation of Perfusion Imaging With HOSVD Clutter Filters

Novel pulsed-Doppler methods for perfusion imaging are validated using dialysis cartridges as perfusion phantoms. Techniques that were demonstrated qualitatively at 24 MHz, in vivo, are here examined quantitatively at 5 and 12.5 MHz using phantoms with the blood-mimicking fluid flow within cellulose microfibers. One goal is to explore a variety of flow states to optimize measurement sensitivity and flow accuracy. The results show that 2-3-s echo acquisitions at roughly 10 frames/s yield the highest sensitivity to flows of 1-4 mL/min. A second goal is to examine methods for setting the parameters of higher order singular value decomposition (HOSVD) clutter filters. For stationary or moving clutter, the velocity of the blood-mimicking fluid in the microfibers is consistently estimated within measurement uncertainty (mean coefficient of variation = 0.26). Power Doppler signals were equivalent for stationary and moving clutter after clutter filtering, increasing approximately 3 dB/mL/min of blood-mimicking fluid flow for 0 ≤ q ≤ 4 mL/min. Comparisons between phantom and preclinical images show that peripheral perfusion imaging can be reliably achieved without contrast enhancement.