Capturing complexity of the diffusion-weighted MR signal decay.

Diffusion-weighted MRI (dMRI) is a key component of clinical radiology. When analyzing diffusion-weighted images, radiologists often seek to infer microscopic tissue structure through measurements of the diffusion coefficient, D0 (mm2/s). This multi-scale problem is framed by the creation of diffusion models of signal decay based on physical laws, histological structure, and biophysical constraints. The purpose of this paper is to simplify the model building process by focusing on the observed decay in the effective diffusion coefficient as a function of diffusion weighting (b-value), D(b), that is often observed in complex biological tissues. We call this approach the varying diffusion curvature (VDC) model. Since this is a heuristic model, the exact functional form of this decay is not important, so here we examine a simple exponential function, D(b) = D0exp(-bD1), where D0 and D1 capture aspects of hindered and restricted diffusion, respectively. As an example of the potential of the VDC model, we applied it to dMRI data collected from normal and diseased human brain tissue using Stejskal-Tanner diffusion gradient pulses. In order to illustrate the connection between D0 and D1 and the sub-voxel structure we also analyzed dMRI data from families of Sephadex beads selected with increasing tortuosity. Finally, we applied the VDC model to dMRI simulations of nested muscle fiber phantoms whose permeability, atrophy, and fiber size distribution could be changed. These results demonstrate that the VDC model is sensitive to sub-voxel tissue structure and composition (porosity, tortuosity, and permeability), hence can capture tissue complexity in a manner that could be easily applied in clinical dMRI.

Assessment of glenoid chondral healing: comparison of microfracture to autologous matrix-induced chondrogenesis in a novel rabbit shoulder model.

BACKGROUND: Management of glenohumeral arthrosis in young patients is a considerable challenge, with a growing need for non-arthroplasty alternatives. The objectives of this study were to develop an animal model to study glenoid cartilage repair and to compare surgical repair strategies to promote glenoid chondral healing. METHODS: Forty-five rabbits underwent unilateral removal of the entire glenoid articular surface and were divided into 3 groups--untreated defect (UD), microfracture (MFx), and MFx plus type I/III collagen scaffold (autologous matrix-induced chondrogenesis [AMIC])--for the evaluation of healing at 8 weeks (12 rabbits) and 32 weeks (33 rabbits) after injury. Contralateral shoulders served as unoperated controls. Tissue assessments included 11.7-T magnetic resonance imaging (long-term healing group only), equilibrium partitioning of an ionic contrast agent via micro-computed tomography (EPIC-µCT), and histologic investigation (grades on International Cartilage Repair Society II scoring system). RESULTS: At 8 weeks, x-ray attenuation, thickness, and volume did not differ by treatment group. At 32 weeks, the T2 index (ratio of T2 values of healing to intact glenoids) was significantly lower for the MFx group relative to the AMIC group (P = .01) whereas the T1ρ index was significantly lower for AMIC relative to MFx (P = .01). The micro-computed tomography-derived repair tissue volume was significantly higher for MFx than for UD. Histologic investigation generally suggested inferior healing in the AMIC and UD groups relative to the MFx group, which exhibited improvements in both integration of repair tissue with subchondral bone and tidemark formation over time. DISCUSSION: Improvements conferred by AMIC were limited to magnetic resonance imaging outcomes, whereas MFx appeared to promote increased fibrous tissue deposition via micro-computed tomography and more hyaline-like repair histologically. The findings from this novel model suggest that MFx promotes biologic resurfacing of full-thickness glenoid articular injury.

MR assessment of osteogenic differentiation in tissue-engineered constructs.

Bone marrow stromal cells (MSC) are a promising source of osteoprogenitor cells for bone tissue engineering. However, the population of the osteoprogenitor cells and their differentiation potentials change with the gender, age, and health of the donor. Development of a noninvasive method to assess osteogenic progression is critical for successful bone tissue regeneration. High-resolution magnetic resonance imaging (MRI) (at 11.7 T, with spatial resolution of 62.5 x 62.5 microm in 500 microm slices) is used in the present study to monitor osteogenic differentiation of tissue-engineered constructs prepared by seeding human bone MSCs on gelatin sponge scaffolds. Quantitative measurements of the MR relaxation times (T1, T2) and the apparent diffusion coefficient (ADC) were performed for four successive weeks on control tissue constructs and constructs exposed to osteogenic differentiation medium. The T1 and T2 relaxation times and ADC were found to decrease as osteogenic progression proceeded in samples exposed to osteogenic differentiation medium. At week 4, the T1, T2, and ADC of TE constructs were 1.81 +/- 0.11 s, 19.5 +/- 11.02 ms, and 1.01 +/- 0.47 x 10(3) mm(2)/s, respectively, for osteogenic differentiated constructs, significantly different from control constructs 2.22 +/- 0.08 s, 50.39 +/- 5.57 ms, and 1.86 +/- 0.18 x 107(3) mm(2)/s (p < 0.05). The MR parameters were also highly correlated with the cell seeding densities and alkaline phosphatase (ALP) activities of the osteogenic constructs. In conclusion, periodic measurements of MR parameters (T1, T2, and ADC) provide a promising method for noninvasive monitoring of the status of tissue-engineered bone growth and differentiation.