Background: Virtual reality (VR) technology has been implemented as a pre-procedural planning tool for cardiovascular interventions to enable detailed evaluation of patient anatomy from different vantage points. Here, we employed a VR platform to preoperatively plan for percutaneous valve-in-valve transcatheter mitral replacement (ViV-TMVR) in a prohibitive surgical candidate.
Case Summary: An 85-year-old male with a history of two prior sternotomies for bioprosthetic aortic valve (AV) and mitral valve (MV) 31 mm Medtronic Mosaic bioprosthesis presented with severe mitral regurgitation from a degenerative bioprosthetic MV. The patient was deemed a prohibitive surgical candidate for a third sternotomy and instead was recommended a percutaneous transseptal ViV-TMVR. An electrocardiogram-gated chest computed tomography (CT) provided a neo-left-ventricular outflow tract (neo-LVOT) of 1.89 cm. This CT was reconstructed to create a 360° VR (360VR) model. A 29 mm SAPIEN three bioprosthetic valve, selected based on the already implanted MV, was placed inside the bioprosthetic MV and analysed in VR at different angles to ensure it would not obstruct the LVOT. The neo-LVOT measured in VR was 3.02 cm, which would allow for sufficient blood flow without significant obstruction from the new SAPIEN three bioprosthetic valve. The patient tolerated the procedure well.
Discussion: This case demonstrates the utility of VR as a pre-procedural planning tool for interventional cardiology procedures. Preoperative planning in VR alleviated concerns regarding obstruction of the neo-LVOT and helped confirm safe implantation by clearly showing the three-dimensional spatial relationship between the implants and surrounding patient anatomy.
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http://dx.doi.org/10.1093/ehjcr/ytac384 | DOI Listing |
Curr Oncol Rep
January 2025
Department of Radiation Oncology, Mayo Clinic, Phoenix, AZ, USA.
Purpose: To review recent advances with radiation therapy (RT) for soft tissue sarcomas (STS).
Recent Findings: Newer data showcases hypofractionated preoperative RT for soft tissue sarcomas treated with surgery to be safe and effective, however, long-term follow up data is pending. Hypofractionated and dose-escalated RT in patients with unresectable STS is also being studied, for which we remain optimistic given advances in RT planning approaches.
Cureus
December 2024
Department of Orthopaedic Surgery, The Jikei University School of Medicine, Tokyo, JPN.
Ossification of the ligamentum flavum (OLF) can lead to dural ossification, significantly increasing the risk of complications, including intraoperative nerve injury. The application of augmented reality (AR) and advanced digital technologies in spine surgery has the potential to reduce these risks. This case report highlights a perioperative nerve injury-free microsurgery using elastic image fusion technology, which integrates preoperative imaging with intraoperative computed tomography for a patient with severe stenotic OLF and dural ossification.
View Article and Find Full Text PDFGenome Med
January 2025
Department of Pathology and Laboratory Medicine, Dartmouth-Hitchcock Medical Center, Lebanon, NH, 03756, USA.
Background: Central nervous system tumors are among the most lethal types of cancer. A critical factor for tailored neurosurgical resection strategies depends on specific tumor types. However, it is uncommon to have a preoperative tumor diagnosis, and intraoperative morphology-based diagnosis remains challenging.
View Article and Find Full Text PDFTotal knee arthroplasty (TKA) with hardware around the knee is a challenge to preserve bone while boney landmarks are distorted. Robotic assisted (RA) TKA may assist in simultaneous hardware removal and TKA due to preoperative planning and retention of bone. The aim of this study is to identify if there are differences in component fixation, component constraint and functional outcomes dependent during simultaneous removal of hardware (ROH) around the knee and TKA comparing RA-TKA to manual.
View Article and Find Full Text PDFJ Arthroplasty
January 2025
Orthopedic Surgery Artificial Intelligence Laboratory, Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA; Mayo Clinic Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA. Electronic address:
Background: A drastic increase in the volume of primary total knee arthroplasties (TKAs) performed nationwide will inevitably lead to higher volumes of revision TKAs in which the primary knee implant must be removed. An important step in preoperative planning for revision TKA is implant identification, which is time-consuming and difficult even for experienced surgeons. We sought to develop a deep learning algorithm to automatically identify the most common models of primary TKA implants.
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