Digital Pathology as a Predictive Tool for Aortic Dissection

Project Overview

In aortic surgery, critical decisions must often be made without sufficient information to predict disease progression. Aortic dissection surgery involves removing the damaged section of the aorta and replacing it with a synthetic graft. However, assessing the properties of the diseased aortic tissue is often subjective, with no available techniques to predict future risks to the patient. For example, following an aortic dissection repair, it is challenging to determine if the condition will progress to a more severe dissection or if the patient would benefit from a stent in the future. Early intervention could prevent death.

Enhancing the understanding of aortic disease development.

Histopathology, the study of diseased cells and tissues under a microscope, is crucial in cancer diagnosis but is rarely used routinely for aortic diseases. This is due to a lack of expert histopathologists, the complex nature of the aorta, and the time-consuming nature of histopathology. Nevertheless, recent studies suggest that histopathology could significantly improve the treatment of aortic dissection patients.

This project aims to develop digital pathology software using artificial intelligence to characterise aortic tissue accurately and automatically. This technology will enable surgeons to intervene quickly if problems are detected post-surgery, potentially saving lives. This approach could become a routine method for assessing patient risk through the inclusion of histopathology in multidisciplinary team (MDT) care. Digital pathology results, once evaluated by the MDT, will provide clear guidelines for any further treatment, such as the need for a stent to prevent disease progression.

By combining long-term disease progression data with new digital pathology analysis, this project aims to develop predictive models on the “natural history” of aortic dissection, enhancing the understanding of disease development.