David A. Reiter
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Articles (11)
Year:
2023
Year:
2023
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
Year:
2023
Purpose Knee cartilage experiences repetitive loading during physical activities, which is altered during the pathogenesis of diseases like osteoarthritis. Analyzing the biomechanics during motion provides a clear understanding of the dynamics of cartilage deformation and may establish essential imaging biomarkers of early‐stage disease. However, in vivo biomechanical analysis of cartilage during rapid motion is not well established. Methods We used spiral displacement encoding with stimulated echoes (DENSE) MRI on in vivo human tibiofemoral cartilage during cyclic varus loading (0.5 Hz) and used compressed sensing on the k‐space data. The applied compressive load was set for each participant at 0.5 times body weight on the medial condyle. Relaxometry methods were measured on the cartilage before (T 1ρ , T 2 ) and after (T 1ρ ) varus load. Results Displacement and strain maps showed a gradual shift of displacement and strain in time. Compressive strain was observed in the medial condyle cartilage and shear strain was roughly half of the compressive strain. Male participants had more displacement in the loading direction compared to females, and T 1ρ values did not change after cyclic varus load. Compressed sensing reduced the scanning time up to 25% to 40% when comparing the displacement maps and substantially lowered the noise levels. Conclusion These results demonstrated the ease of which spiral DENSE MRI could be applied to clinical studies because of the shortened imaging time, while quantifying realistic cartilage deformations that occur through daily activities and that could serve as biomarkers of early osteoarthritis.
Year:
2023
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2022
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2022
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2022
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2022
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2022
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2022
Year:
2022
Collaborators (5)
Candace C. Fleischer
-
Eric Sigmund
Associate Professor (Research)
NYU Langone Health
Dean Jones
Professor
Emory University
Corey P. Neu
-
Ceereena Ubaida-Mohien
National Institute on Aging
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