Influence of IABP-Induced Abdominal Occlusions on Aortic Hemodynamics: A Patient-Specific Computational Evaluation

Reduction in Balloon Pump Size Reduces Axillary Intraaortic Balloon Pump Failure Risk

Axillary artery intra-aortic balloon pump (axIABP) placement has been implemented as a bridging solution before heart transplantation. This study evaluates complications associated with axIABP support and describes an approach to minimize adverse events. We previously described a percutaneous approach for axIABP placement. However, patients receiving axIABP between September 1, 2017, and September 26, 2019 (n = 32) demonstrated a high rate of balloon pump malfunction (8/32; 25%) and other complications (totaling 15/32; 47%). Sixty-four patients were sequentially treated under a revised protocol. Compared to the initial cohort, no significant differences in demographics were noted. A significant reduction in rate of balloon malfunction (8/32, 25% vs. 1/64, 2%; p < 0.001) and total complications (15/32, 47% vs. 10/64, 16%; p = 0.0025) during the period of support were noted after intervention. Subsequent analysis of total complications per device size (40 vs. ≤ 34 ml balloon) revealed significantly reduced complications in patients with smaller devices (40% vs. 13%, respectively; p = 0.0022). This study provides guidelines to limit complications in patients supported with axIABP, facilitating a protracted period of bridging support.

Fully Automated Segmentation of Lower Extremity Deep Vein Thrombosis Using Convolutional Neural Network

OBJECTIVE

Deep vein thrombosis (DVT) is a disease caused by abnormal blood clots in deep veins. Accurate segmentation of DVT is important to facilitate the diagnosis and treatment. In the current study, we proposed a fully automatic method of DVT delineation based on deep learning (DL) and contrast enhanced magnetic resonance imaging (CE-MRI) images.

METHODS

58 patients (25 males; 28~96 years old) with newly diagnosed lower extremity DVT were recruited. CE-MRI was acquired on a 1.5 T system. The ground truth (GT) of DVT lesions was manually contoured. A DL network with an encoder-decoder architecture was designed for DVT segmentation. 8-Fold cross-validation strategy was applied for training and testing. Dice similarity coefficient (DSC) was adopted to evaluate the network's performance.

RESULTS

It took about 1.5s for our CNN model to perform the segmentation task in a slice of MRI image. The mean DSC of 58 patients was 0.74± 0.17 and the median DSC was 0.79. Compared with other DL models, our CNN model achieved better performance in DVT segmentation (0.74± 0.17 versus 0.66±0.15, 0.55±0.20, and 0.57±0.22).

CONCLUSION

Our proposed DL method was effective and fast for fully automatic segmentation of lower extremity DVT.

Model and Application to Support the Coronary Artery Diseases (CAD): Development and Testing

Cardiovascular diseases are among the main causes of morbidity, disability, and mortality. Most of them occur because of an atherosclerotic plaque developing within a coronary artery, which can cause a narrowing of the vessel lumen (coronary stenosis) or even break it. It is, therefore, useful to evaluate the role of the stress state of the endothelial layer of the arterial tissue, both for the maintenance of the blood circulation and for the implications in presence of a pathology that can lead to thromboembolic complications. The aim of the following study was to develop and test an application that is able to evaluate specific hemodynamic shear stress indicators in coronary arteries at different percentages of stenosis and in different patients' specific conditions. The application, based on Java, allows users to view the results of simulations performed on a coronary anatomy that can be customized with a stenosis of different degrees and positions. Being in possession of a predictive tool for disturbed flow factors may be important for the location and development of atherosclerotic plaque. Moreover, the application can be a valid tool to help in the evaluation of the condition and in the follow-up of the coronary affected by pathology.