Abstract
The noninvasive early detection of specific matrix alterations in degenerative cartilage disease would be of substantial use in basic science studies and clinically, but remains an elusive goal. Recently developed MRI methods exhibit some specificity, but require contrast agents or nonstandard pulse sequences and hardware. We present a multiexponential approach which does not require contrast agents or specialized hardware, and uses a standard multiple-echo spin-echo sequence. Experiments were performed on tissue models of degenerative cartilage using enzymes with distinct actions. MR results were validated using histologic, biochemical and infrared spectroscopic analyses. The sulfated glycosaminoglycan per dry weight (dw) in bovine nasal cartilage was 0.72 ± 0.06 mg/mg dw and was reduced through chondroitinase AC and collagenase digestion to 0.56 ± 0.12 and 0.58 ± 0.13 mg/mg dw, respectively. Multiexponential analysis of data obtained at 9.4 T permitted the identification of tissue compartments assigned to the proteoglycan component of the matrix and to bulk water. Enzymatic treatment resulted in a significant reduction in the ratio of proteoglycan-bound to free water from 0.13 ± 0.02 in control cartilage to 0.03 ± 0.02 and 0.05 ± 0.06 under chondroitinase AC and collagenase treatment, respectively. As expected, monoexponential T(2) increased with both degradation protocols, but without further specificity to the nature of the degradation. An important eventual extension of this approach may be to map articular cartilage degeneration in the clinical setting. As an initial step towards this, localized multiexponential T(2) analysis was performed on control and trypsin treated excised bovine patella. The results obtained on this articular cartilage sample were readily interpretable in terms of proteoglycan-associated and relatively free water compartments. In potential clinical applications, signal-to-noise ratio constraints will define the threshold for the detection of macromolecular compartment changes at a given spatial scale. The multiexponential approach has potential application to the early detection of cartilage degradation with the use of appropriate pulse parameters under high signal-to-noise ratio conditions.
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