This review summarizes the largest available series in the literature on ECAA management. The number of ECAAs reported in current literature is scarce. The early and long-term outcome of invasive treatment in ECAA is favorable; however, cranial nerve damage after surgery occurs frequently. Unfortunately, due to limitations in reporting of results and confounding by indication in the available literature, it was not possible to determine the optimal treatment strategy. There is a need for a multicenter international registry to reveal the optimal treatment for ECAA.

IntroductionExtracranial carotid artery aneurysms (ECAA) are rare but may be accompanied with significant morbidity. Previous studies mostly focused on diagnostic imaging and treatment. In contrast, the pathophysiological mechanisms and natural course of ECAA are largely unknown. Understanding the pathophysiological background may add to prediction of risk for adverse outcome and need for surgical exclusion. The aim of this study was to investigate the histopathological characteristics of ECAA in patients who underwent complete surgical ECAA resection.Material and MethodsFrom March 2004 till June 2013, 13 patients were treated with open ECAA repair. During surgery the aneurysm sac was resected and processed for standardized histological analysis. Sections were stained with routine hematoxylin and eosin and special stains to detect elastin, collagen, different types of inflammatory cells, vascular smooth muscle cells and endothelial cells.ResultsHistopathological characterization revealed two distinct categories: dissection (abrupt interruption of the media; n = 3) and degeneration (general loss of elastin fibers in the media; n = 10). In the degenerative samples the elastin fibers in the media were fragmented and were partly absent. Inflammatory cells were observed in the vessel wall of the aneurysms.ConclusionHistological analysis in this small sample size revealed dissection and degeneration as the two distinct underlying mechanisms in ECAA formation.

The demand for accurate and reproducible phenotyping of a disease trait increases with the rising number of biobanks and genome wide association studies. Detailed analysis of histology is a powerful way of phenotyping human tissues. Nonetheless, purely visual assessment of histological slides is time-consuming and liable to sampling variation and optical illusions and thereby observer variation, and external validation may be cumbersome. Therefore, within our own biobank, computerized quantification of digitized histological slides is often preferred as a more precise and reproducible, and sometimes more sensitive approach. Relatively few free toolkits are, however, available for fully digitized microscopic slides, usually known as whole slides images. In order to comply with this need, we developed the slideToolkit as a fast method to handle large quantities of low contrast whole slides images using advanced cell detecting algorithms. The slideToolkit has been developed for modern personal computers and high-performance clusters (HPCs) and is available as an open-source project on github.com. We here illustrate the power of slideToolkit by a repeated measurement of 303 digital slides containing CD3 stained (DAB) abdominal aortic aneurysm tissue from a tissue biobank. Our workflow consists of four consecutive steps. In the first step (acquisition), whole slide images are collected and converted to TIFF files. In the second step (preparation), files are organized. The third step (tiles), creates multiple manageable tiles to count. In the fourth step (analysis), tissue is analyzed and results are stored in a data set. Using this method, two consecutive measurements of 303 slides showed an intraclass correlation of 0.99. In conclusion, slideToolkit provides a free, powerful and versatile collection of tools for automated feature analysis of whole slide images to create reproducible and meaningful phenotypic data sets.