Parsimonious modeling of skeletal muscle perfusion: Connecting the stretched exponential and fractional Fickian diffusion

Feasibility of Multiparametric Perfusion Assessment in Diabetic Foot Ulcer Using Intravoxel Incoherent Motion and Blood Oxygenation-Level Dependent MRI

BACKGROUND

Patients with type-2 diabetes (T2DM) are at increased risk of developing diabetic foot ulcers (DFU) and experiencing impaired wound healing related to underlying microvascular disease.

PURPOSE

To evaluate the sensitivity of intra-voxel incoherent motion (IVIM) and blood oxygen level dependent (BOLD) MRI to microvascular changes in patients with DFUs.

STUDY TYPE

Case-control.

POPULATION

20 volunteers who were age and body mass index matched, including T2DM patients with DFUs (N = 10, mean age = 57.5 years), T2DM patients with controlled glycemia and without DFUs (DC, N = 5, mean age = 57.4 years) and healthy controls (HC, N = 5, mean age = 52.8 years).

FIELD STRENGTH/SEQUENCE

3T/multi-b-value IVIM and dynamic BOLD.

ASSESSMENT

Resting IVIM parameters were obtained using a multi-b-value diffusion-weighted imaging sequence and two IVIM models were fit to obtain diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f) and microvascular volume fraction (MVF) parameters. Microvascular reactivity was evaluated by inducing an ischemic state in the foot with a blood pressure cuff during dynamic BOLD imaging. Perfusion indices were assessed in two regions of the foot: the medial plantar (MP) and lateral plantar (LP) regions.

STATISTICAL TESTS

Effect sizes of group mean differences were assessed using Hedge's g adjusted for small sample sizes.

RESULTS

DFU participants exhibited elevated D*, f, and MVF values in both regions (g ≥ 1.10) and increased D (g = 1.07) in the MP region compared to DC participants. DC participants showed reduced f and MVF compared to HC participants in the MP region (g ≥ 1.06). Finally, the DFU group showed reduced tolerance for ischemia in the LP region (g = -1.51) and blunted reperfusion response in both regions (g < -2.32) compared to the DC group during the cuff-occlusion challenge.

DATA CONCLUSION

The combined use of IVIM and BOLD MRI shows promise in differentiating perfusion abnormalities in the feet of diabetic patients and suggests hyperperfusion in DFU patients.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 1.

Quantitative analysis of masticatory muscle changes by Eichner index using diffusion-weighted imaging

OBJECTIVES

Diffusion-weighted imaging (DWI) provides quantitative functional information about the microscopic movement of water at the cellular level. However, few reports have quantitatively evaluated histological changes in masticatory muscles due to changes in occlusal relationships using DWI. This study aimed to assess the changes in masticatory muscles by Eichner index using DWI.

METHODS

We analyzed magnetic resonance imaging (MRI) studies of 201 patients from November 2017 to April 2018. Each Eichner index group, age, and sex were used as criterion variables, and the average apparent diffusion coefficient (ADC) values of the masticatory muscles were the explanatory variable. The mean ADC value differences were analyzed in each Eichner index group. We analyzed the data using the Kruskal-Wallis test and post hoc Mann-Whitney test with Bonferroni adjustment multiple regression analysis with Shapiro-Wilk test and Spearman's correlation coefficients. P < 0.05 was considered statistically significant.

RESULTS

The mean ADC values of each Eichner classification group were significantly different, with the lowest value in group C (P < 0.001). There was a negative correlation between the ADC value of the masseter, lateral pterygoid muscle, and age (P < 0.001). There were significant differences between the sex groups (P < 0.001).

CONCLUSIONS

ADC values of masticatory muscles were significantly different in the Eichner index groups. The ADC values of masticatory muscles may be useful for the quantitative evaluation of the masticatory muscles affected by the occlusal state.

Intravoxel Incoherent Motion Magnetic Resonance Imaging in Skeletal Muscle: Review and Future Directions

Throughout the body, muscle structure and function can be interrogated using a variety of noninvasive magnetic resonance imaging (MRI) methods. Recently, intravoxel incoherent motion (IVIM) MRI has gained momentum as a method to evaluate components of blood flow and tissue diffusion simultaneously. Much of the prior research has focused on highly vascularized organs, including the brain, kidney, and liver. Unique aspects of skeletal muscle, including the relatively low perfusion at rest and large dynamic range of perfusion between resting and maximal hyperemic states, may influence the acquisition, postprocessing, and interpretation of IVIM data. Here, we introduce several of those unique features of skeletal muscle; review existing studies of IVIM in skeletal muscle at rest, in response to exercise, and in disease states; and consider possible confounds that should be addressed for muscle-specific evaluations. Most studies used segmented nonlinear least squares fitting with a b-value threshold of 200 sec/mm2 to obtain IVIM parameters of perfusion fraction (f), pseudo-diffusion coefficient (D*), and diffusion coefficient (D). In healthy individuals, across all muscles, the average ± standard deviation of D was 1.46 ± 0.30 × 10-3  mm2 /sec, D* was 29.7 ± 38.1 × 10-3  mm2 /sec, and f was 11.1 ± 6.7%. Comparisons of reported IVIM parameters in muscles of the back, thigh, and leg of healthy individuals showed no significant difference between anatomic locations. Throughout the body, exercise elicited a positive change of all IVIM parameters. Future directions including advanced postprocessing models and potential sequence modifications are discussed. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

The Mathematics of Quasi-Diffusion Magnetic Resonance Imaging

Quasi-diffusion imaging (QDI) is a novel quantitative diffusion magnetic resonance imaging (dMRI) technique that enables high quality tissue microstructural imaging in a clinically feasible acquisition time. QDI is derived from a special case of the continuous time random walk (CTRW) model of diffusion dynamics and assumes water diffusion is locally Gaussian within tissue microstructure. By assuming a Gaussian scaling relationship between temporal (α) and spatial (β) fractional exponents, the dMRI signal attenuation is expressed according to a diffusion coefficient, D (in mm2 s−1), and a fractional exponent, α. Here we investigate the mathematical properties of the QDI signal and its interpretation within the quasi-diffusion model. Firstly, the QDI equation is derived and its power law behaviour described. Secondly, we derive a probability distribution of underlying Fickian diffusion coefficients via the inverse Laplace transform. We then describe the functional form of the quasi-diffusion propagator, and apply this to dMRI of the human brain to perform mean apparent propagator imaging. QDI is currently unique in tissue microstructural imaging as it provides a simple form for the inverse Laplace transform and diffusion propagator directly from its representation of the dMRI signal. This study shows the potential of QDI as a promising new model-based dMRI technique with significant scope for further development.