Towards Personalized Management of Type B Aortic Dissection Using STENT: a STandard cta database with annotation of the ENtire aorta and True-false lumen

TL;DR

This paper introduces a comprehensive CTA database and automated methods for precise measurement of Type B Aortic Dissection, aiming to improve personalized treatment planning and reduce subjective errors in clinical assessments.

Contribution

The creation of the STENT database with annotated aorta and lumen, and the development of automated segmentation and measurement methods for TBAD.

Findings

Automated TBAD segmentation achieves high accuracy.

The methods facilitate faster, more consistent measurements.

Results support clinical feasibility for personalized TBAD management.

Abstract

Type B Aortic Dissection(TBAD) is a rare aortic disease with a high 5-year mortality.Personalized and precise management of TBAD has been increasingly desired in clinic which requires the geometric parameters of TBAD specific to the patient be measured accurately.This remains to be a challenging task for vascular surgeons as manual measurement is highly subjective and imprecise. To solve this problem,we introduce STENT-a STandard cta database with annotation of the ENtire aorta and True-false lumen. The database contains 274 CT angiography (CTA) scans from 274 unique TBAD patients and is split into a training set(254 cases including 210 preoperative and 44 postoperative scans ) and a test set(20 cases).Based on STENT,we develop a series of methods including automated TBAD segmentation and automated measurement of TBAD parameters that facilitate personalized and precise management of the disease. In this work, the database and the proposed methods are thoroughly introduced and evaluated and the results of our study shows the feasibility and effectiveness of our approach to easing the decision-making process for vascular surgeons during personalized TBAD management.