Background The purpose of this study is to find the high-risk morphological features in type B aortic dissection (TBAD) population and to establish an early detection model. Methods From June 2018 to February 2022, 234 patients came to our hospital because of chest pain. After examination and definite diagnosis, we excluded people with previous cardiovascular surgery history, connective tissue disease, aortic arch variation, valve malformation, and traumatic dissection. Finally, we included 49 patients in the TBAD group and 57 in the control group. The imaging data were retrospectively analyzed by Endosize (Therevna 3.1.40) software. The aortic morphological parameters mainly include diameter, length, direct distance, and tortuosity index. Multivariable logistic regression models were performed and systolic blood pressure (SBP), aortic diameter at the left common carotid artery (D3), and length of ascending aorta (L1) were chosen to build a model. The predictive capacity of the models was evaluated through the receiver operating characteristic (ROC) curve analysis. Results The diameters in the ascending aorta and aortic arch are larger in the TBAD group (33.9 ± 5.9 vs. 37.8 ± 4.9 mm, p < 0.001; 28.2 ± 3.9 vs. 31.7 ± 3.0 mm, p < 0.001). The ascending aorta was significantly longer in the TBAD group (80.3 ± 11.7 vs. 92.3 ± 10.6 mm, p < 0.001). Besides, the direct distance and tortuosity index of the ascending aorta in the TBAD group increased significantly (69.8 ± 9.0 vs. 78.7 ± 8.8 mm, p < 0.001; 1.15 ± 0.05 vs. 1.17 ± 0.06, p < 0.05). Multivariable models demonstrated that SBP, aortic diameter at the left common carotid artery (D3), and length of ascending aorta (L1) were independent predictors of TBAD occurrence. Based on the ROC analysis, area under the ROC curve of the risk prediction models was 0.831. Conclusion Morphological characteristic including diameter of total aorta, length of ascending aorta, direct distance of ascending aorta, and tortuosity index of ascending aorta are valuable geometric risk factors. Our model shows a good performance in predicting the incidence of TBAD.

BackgroundTo establish models for predicting descending thoracic aortic diameters and provide evidence for selecting the size of the stent graft for TBAD patients.MethodsA total of 200 candidates without severe deformation of aorta were included. CTA information was collected and 3D reconstructed. In the reconstructed CTA, a total of 12 cross-sections of peripheral vessels were made perpendicular to the axis of flow of the aorta. Parameters of the cross sections and basic clinical characteristics were used for prediction. The data was randomly split into the training set and the test set in an 8:2 ratio. To fully describe diameters of descending thoracic aorta, three predicted points were set based quadrisection, and a total of 12 models at three predicted points were established using four algorithms included linear regression (LR), support vector machine (SVM), Extra-Tree regression (ETR) and random forest regression (RFR). The performance of models was evaluated by mean square error (MSE) of the prediction value, and the ranking of feature importance was given by Shapley value. After modeling, prognosis of five TEVAR cases and stent oversizing were compared.ResultsWe identified a series of parameters which affect the diameter of descending thoracic aorta, including age, hypertension, the area of proximal edge of superior mesenteric artery, etc. Among four predictive models, all the MSEs of SVM models at three different predicted position were less than 2 mm2, with approximately 90% predicted diameters error less than 2 mm in the test sets. In patients with dSINE, stent oversizing was about 3 mm, while only 1 mm in patients without complications.ConclusionThe predictive models established by machine learning revealed the relationship between basic characteristics and diameters of different segment of descending aorta, which help to provide evidence for selecting the matching distal size of the stent for TBAD patients, thereby reducing the incidence of TEVAR complications.

Background: Left subclavian artery revascularization (LSA) is frequently performed in the setting of thoracic endovascular repair (TEVAR). The purpose of this study was to compare different techniques for LSA revascularization during TEVAR.Methods: We performed a single center’s retrospective cohort study from 2016 to 2019. Patients were categorized by LSA revascularization methods, including direct coverage without revascularization (Unrevascularized), carotid-subclavian bypass (CSB), fenestrated TEVAR (F-TEVAR). Indications, demographics, operation details, and outcomes were analyzed using standard statistical analysis.Results: 171 patients underwent TEVAR with LSA coverage, 16.4% (n=28) were unrevascularized and the remaining patients underwent CSB (n=100 [58.5%]) or F-TEVAR (n=43 [25.1%]). Demographics were similar between the unrevascularized and revascularized groups, except for procedure urgent status (p = 0.005). The incidence of postoperative spinal cord ischemia was significantly higher between unrevascularized and revascularized group (10.7% vs 1.4%; p = 0.032). There was no difference in 30-day and mid-term rates of mortality, stroke, and left upper extremity ischemia. CSB was more likely time-consuming than F-TEVAR [3.25 (2.83 - 4) vs 2 (1.67 – 2.67) hours, p = 0], but there were no statistically significant differences in 30-day or midterm outcomes for CSB vs F-TEVAR. During a mean follow-up time of 24.8 months, estimates survival rates had no difference.Conclusions: LSA revascularization in zone 2 TEVAR is necessary which is associated with a low 30-day rate of spinal cord ischemia. When LSA revascularization is required during TEVAR, CSB and F-TEVAR are all safe and effective methods, and F-TEVAR appears to offer equivalent clinical outcomes as a less time-consuming and minimally invasive alternative.