Introduction to Currently Applied Device Pathology

Pathologic evaluation is crucial to the study of medical devices and integral to the Food and Drug Administration and other regulatory entities' assessment of device safety and efficacy. While pathologic analysis is tailored to the type of device, it generally involves at a minimum gross and microscopic evaluation of the medical device and associated tissues. Due to the complex nature of some implanted devices and specific questions posed by sponsors, pathologic evaluation inherently presents many challenges in accurately assessing medical device safety and efficacy. This laboratory's experience in numerous collaborative projects involving veterinary pathologists, biomedical engineers, physicians, and other scientists has led to a set of interrelated assessments to determine pathologic end points as a means to address these challenges and achieve study outcomes. Thorough device evaluation is often accomplished by utilizing traditional paraffin histology, plastic embedding and microground sections, and advanced imaging modalities. Combining these advanced techniques provides an integrative, comprehensive approach to medical device pathology and enhances medical device safety and efficacy assessment.

Effect of strut distribution on neointimal coverage of everolimus-eluting bioresorbable scaffolds: an optical coherence tomography study

The thick struts of bioresorbable vascular scaffolds (BRS) are associated with changes in wall shear stress and contribute to neointimal proliferation. We aimed to evaluate the relationship between the BRS strut distribution and the neointimal proliferation. 50 lesions underwent optical coherence tomography, 12 months after BRS implantation. Scaffold area and neointimal thickness were evaluated in each cross-sectional area (CSA). Scaffold eccentricity was defined as follows: (maximum diameter - minimum diameter) × 100/maximum diameter. CSAs of BRS were divided into four quadrants. The maximal neointimal thickness (Maximal-NIT), Minimal-NIT and the number of struts in each quadrant were measured. The number of struts were classified as 1, 2, 3 and ≥ 4. Furthermore, the mean-NIT acquired in each quadrant was divided by the average-NIT of all struts in the same CSA, which was defined as the unevenness score. In addition, Maximal-NIT minus Minimal-NIT was divided by the average-NIT of all struts in the same CSA, which was defined as heterogenicity of neointimal proliferation. There was a significant difference in the association between the number of struts and not only the unevenness score (no. of strut = 1 (N = 440), unevenness score 1.04 ± 0.34; 2 (N = 696), 0.98 ± 0.27; 3 (N = 994), 0.96 ± 0.23; ≥4 (N = 1202), 1.04 ± 0.22, P < 0.01) but also Maximal-NIT and Minimal-NIT. Furthermore, a significant correlation was observed between scaffold eccentricity in each CSA and the heterogeneity of neointimal proliferation in the same CSA (N = 892, R = 0.38, p = 0.01). Crowding of struts is associated with increased neointimal proliferation after BRS implantation. The scaffold eccentricity causes heterogeneity of neointimal proliferation.