Background: Hybrid Deep Venous ARterialisation (DVAR) is offered as a last-ditch attempt for limb salvage in patients with chronic limb threatening ischemia (CLTI). It provides non-selective arterialisation independent of the angiosome, which harnesses the complex venous capillary network bed developed in the leg and foot.
Methods: We present two elderly men who underwent DVAR to salvage limb with CLTI. DVAR was performed by creating an arteriovenous connection by anastomosis of the great saphenous vein (GSV) at the level of the distal popliteal and proximal tibio-peroneal trunk. Fasciotomy was performed over the length of the GSV. Subsequently, proximal in-situ catheter valvotomies of the GSV valves were undergone with the adjuvant on-table balloon maturation. The distal tarsal veins underwent balloon valvotomy under direct vision with subsequent proximal and distal tarsal veins valvuloplasties. Completion angiogram demonstrated restoration of the flow in the foot and both the patients were relieved of rest pain.
Conclusion: We successfully performed DVAR in 2 elderly patients. Our experience shows that DVAR is a simple and safe option that is easily reproducible without the need for complex endovascular hardware, only if a suitable GSV to the foot is available with no history of deep vein thrombosis.
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http://dx.doi.org/10.1016/j.avsg.2021.07.027 | DOI Listing |
Med Image Anal
January 2025
Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. Electronic address:
The relationship between brain connections and non-imaging phenotypes is increasingly studied using deep neural networks. However, the local and global properties of the brain's white matter networks are often overlooked in convolutional network design. We introduce TractGraphFormer, a hybrid Graph CNN-Transformer deep learning framework tailored for diffusion MRI tractography.
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January 2025
Department of Electrical Engineering, College of Engineering, Taif University, Taif, Saudi Arabia.
Modernizing power systems into smart grids has introduced numerous benefits, including enhanced efficiency, reliability, and integration of renewable energy sources. However, this advancement has also increased vulnerability to cyber threats, particularly False Data Injection Attacks (FDIAs). Traditional Intrusion Detection Systems (IDS) often fall short in identifying sophisticated FDIAs due to their reliance on predefined rules and signatures.
View Article and Find Full Text PDFWater Res
January 2025
School of Civil, Environmental and Architectural Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea. Electronic address:
Algal blooms in freshwater, which are exacerbated by urbanization and climate change, pose significant challenges in the water treatment process. These blooms affect water quality and treatment efficiency. Effective identification of algal proliferation based on the dominant species is important to ensure safe drinking water and a clean water supply.
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January 2025
Laboratory of Ecology and Environmental Management, Science and Technology Advanced Institute, Van Lang University, Ho Chi Minh City, Vietnam; Faculty of Applied Technology, School of Technology, Van Lang University, Ho Chi Minh City, Vietnam. Electronic address:
Floods, which occur when the amount of precipitation surpasses the capacity of an area to drain it adequately, have detrimental consequences on the survival and future generations of fishes. However, few works have reported the prediction of this natural phenomenon in a relation to certain fish species, especially in fast-flowing rivers. In the specific context of the northern mountainous provinces of Vietnam, where the Spinibarbus sp.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Oncology, The First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, China.
Exploring the potential of advanced artificial intelligence technology in predicting microsatellite instability (MSI) and Ki-67 expression of endometrial cancer (EC) is highly significant. This study aimed to develop a novel hybrid radiomics approach integrating multiparametric magnetic resonance imaging (MRI), deep learning, and multichannel image analysis for predicting MSI and Ki-67 status. A retrospective study included 156 EC patients who were subsequently categorized into MSI and Ki-67 groups.
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