Fibrosis of the subsynovial connective tissue (SSCT) in carpal tunnel syndrome (CTS) patients is increasingly recognized as an important aspect of CTS pathophysiology. In this study, we evaluated the effect of blocking profibrotic pathways in fibroblasts from the SSCT in CTS patients. Fibroblasts were stimulated with transforming growth factor β1 (TGF‐β1), and then treated either with a specific fibrosis pathway inhibitor targeting TGF‐β receptor type 1 (TβRI), platelet‐derived growth factor receptor (PDGFR), epidermal growth factor receptor (EGFR), or vascular endothelial growth factor receptor (VEGFR). Fibrosis array and quantitative real‐time polymerase chain reaction of fibrotic genes were evaluated. Array gene expression analysis revealed significant down‐regulation of multiple fibrotic genes after treatment with TβRI, PDGFR, and VEGFR inhibitors. No array fibrotic genes were significantly down‐regulated with EGFR inhibition. Further gene expression analysis of known CTS fibrosis markers collagen type I A2 (Col1), collagen type III A1 (Col3), connective tissue growth factor (CTGF), and SERPINE1 showed significantly down‐regulation after TβRI inhibition. In contrast, VEGFR inhibition significantly down‐regulated CTGF and SERPINE1, whereas, PDGFR and EGFR inhibition significantly down‐regulated Col3. Taken together the inhibition of TβRI appears to be the primary mediator of fibrotic gene expression in fibroblasts from CTS patients. TGF‐β/Smad activity was further evaluated, and as expected inhibition of Smad activity was significantly down‐regulated after inhibition of TβRI, but not with PDGFR, VEGFR, or EGFR inhibition. These results indicate that local therapies specifically targeting TGF‐β signaling alone or in combination offer the potential of a novel local antifibrosis therapy for patients with CTS.
Collagen gel contraction as a measure of fibroblast function in an animal model of subsynovial connective tissue fibrosis
Quantifying the pathological features of flexor tendon pulleys is essential for grading the trigger finger since it provides clinicians with objective evidence derived from microscopic images. Although manual grading is time consuming and dependent on the observer experience, there is a lack of image processing methods for automatically extracting pulley pathological features. In this paper, we design and develop a color-based image segmentation system to extract the color and shape features from pulley microscopic images. Two parameters which are the size ratio of abnormal tissue regions and the number ratio of abnormal nuclei are estimated as the pathological progression indices. The automatic quantification results show clear discrimination among different levels of diseased pulley specimens which are prone to misjudgments for human visual inspection. The proposed system provides a reliable and automatic way to obtain pathological parameters instead of manual evaluation which is with intra- and interoperator variability. Experiments with 290 microscopic images from 29 pulley specimens show good correspondence with pathologist expectations. Hence, the proposed system has great potential for assisting clinical experts in routine histopathological examinations.