Living Donor Liver Transplantation (LDLT) emerged as an alternative treatment option for patients with end-stage liver disease waiting for an organ from a deceased donor. In addition to allowing for a faster access to transplantation, LDLT provides improved recipient outcomes when compared to deceased donor LT. However, it represents a more complex and demanding procedure for the transplant surgeon. In addition to a comprehensive preoperative donor assessment and stringent technical considerations during the donor hepatectomy to ensure upmost donor safety, the recipient procedure also comes with intrinsic challenges during LDLT. A proper approach during both procedures will result in favorable donor and recipient's outcomes. Hence, it is critical for the transplant surgeon to know how to overcome such technical challenges and avoid deleterious complications. One of the most feared complications following LDLT is small-for-size syndrome (SFSS). Although, surgical advances and deeper understanding of the pathophysiology behind SFSS has allowed for a safer implementation of LDLT, there is currently no consensus on the best strategy to prevent or manage this complication. Therefore, we aim to review current practices in technically challenging situations during LDLT, with a particular focus on management of small grafts and venous outflow reconstructions, as they possess one of the biggest technical challenges faced during LDLT.
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http://dx.doi.org/10.1016/j.trre.2023.100750 | DOI Listing |
Comput Med Imaging Graph
January 2025
CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China; National Key Laboratory of Kidney Diseases, Beijing 100853, China. Electronic address:
In clinical optical molecular imaging, the need for real-time high frame rates and low excitation doses to ensure patient safety inherently increases susceptibility to detection noise. Faced with the challenge of image degradation caused by severe noise, image denoising is essential for mitigating the trade-off between acquisition cost and image quality. However, prevailing deep learning methods exhibit uncontrollable and suboptimal performance with limited interpretability, primarily due to neglecting underlying physical model and frequency information.
View Article and Find Full Text PDFSurgery
January 2025
Breast Surgery Unit, Veneto Institute of Oncology IOV, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Padova, Italy.
Background: Intraoperative ultrasound-guided breast-conserving surgery guarantees real-time direct visualization of tumor and resection margins. We compared surgical, oncologic, and cosmetic outcomes between intraoperative ultrasound-guided breast-conserving surgery and traditional (palpation- or wire-guided) surgery across all breast cancer lesion types.
Methods: This prospective observational cohort study was conducted at the Veneto Institute of Oncology between January 2021 and October 2022.
JMIR Form Res
January 2025
Early Intervention in Psychosis Advisory Unit for South-East Norway, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.
Background: Shared decision-making between clinicians and service users is crucial in mental health care. One significant barrier to achieving this goal is the lack of user-centered services. Integrating digital tools into mental health services holds promise for addressing some of these challenges.
View Article and Find Full Text PDFJMIR Med Educ
January 2025
Department of Orthopedics, First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Background: Teaching severe pelvic trauma poses a significant challenge in orthopedic surgery education due to the necessity of both clinical reasoning and procedural operational skills for mastery. Traditional methods of instruction, including theoretical teaching and mannequin practice, face limitations due to the complexity, the unpredictability of treatment scenarios, the scarcity of typical cases, and the abstract nature of traditional teaching, all of which impede students' knowledge acquisition.
Objective: This study aims to introduce a novel experimental teaching methodology for severe pelvic trauma, integrating virtual reality (VR) technology as a potent adjunct to existing teaching practices.
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