Objective: To investigate the clinical efficacy and safety of 3D printed artificial vertebral body for patients who underwent multilevel total en bloc spondylectomy (TES) and analyze whether it could reduce the incidence of implant subsidence.
Methods: This is a retrospective study. From January 2017 to May 2018, eight consecutive cases with spine tumor undergoing multilevel TES were analyzed. All patients underwent X-ray and CT examinations to evaluate the stability of internal fixation during the postoperative follow-up. Demographic, surgical details, clinical data, and perioperative complications was collected. Visual analog scale, Frankel score, and spinal instability neoplastic score (SINS) classification were also recorded.
Results: There were six cases of primary spinal tumor and two cases of metastatic spinal tumor. All patients achieved remarkable pain relief and improvement in neurological function. Five patients underwent operation through the posterior approach, one patient underwent operation through the anterior approach and the remaining two patients through a combined anterior and posterior approach. At the last follow-up period, X-rays showed that the 3D printed artificial vertebral body of all cases matched well, and the fixation was reliable. Hardware failure such as loosening, sinking, breaking, and displacement wasn't observed during the follow-up period.
Conclusion: 3D printed customized artificial vertebral body can provide satisfying good clinical and radiological outcomes for patients who have undergone multilevel TES.
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http://dx.doi.org/10.1111/os.13357 | DOI Listing |
J Magn Reson Imaging
January 2025
Department of Radiology, Peking University Third Hospital, Beijing, China.
Background: The spinal column is a frequent site for metastases, affecting over 30% of solid tumor patients. Identifying the primary tumor is essential for guiding clinical decisions but often requires resource-intensive diagnostics.
Purpose: To develop and validate artificial intelligence (AI) models using noncontrast MRI to identify primary sites of spinal metastases, aiming to enhance diagnostic efficiency.
Radiol Med
January 2025
Department of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
Purpose: To develop an artificial intelligence (AI) algorithm for automated measurements of spinopelvic parameters on lateral radiographs and compare its performance to multiple experienced radiologists and surgeons.
Methods: On lateral full-spine radiographs of 295 consecutive patients, a two-staged region-based convolutional neural network (R-CNN) was trained to detect anatomical landmarks and calculate thoracic kyphosis (TK), lumbar lordosis (LL), sacral slope (SS), and sagittal vertical axis (SVA). Performance was evaluated on 65 radiographs not used for training, which were measured independently by 6 readers (3 radiologists, 3 surgeons), and the median per measurement was set as the reference standard.
Radiother Oncol
January 2025
The Royal Marsden NHS Foundation Trust, Sutton, UK; The Institute of Cancer Research, Sutton, UK.
Background: While SBRT to NSBM has become common, particularly in the oligometastatic population, the approach to treating non-spine bone metastases (NSBM) with stereotactic body radiotherapy (SBRT) varies widely across institutions and clinical trial protocols. We present a comprehensive systematic review of the literatures to inform practice recommendations on behalf of the International Stereotactic Radiosurgery Society (ISRS).
Methods: A systematic literature review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.
J Clin Med
January 2025
Department of Neurosurgery, University of Luebeck, 23562 Luebeck, Germany.
: This study aims to retrospectively detect associations with postoperative complications in spinal surgeries during the hospitalization period using standardized, single-center data to validate a method for complication detection and discuss the potential future use of generated data. : Data were generated in 2006-2019 from a standardized, weekly complications conference reviewing all neurosurgical operations at the University Hospital Luebeck. Paper-based data were recorded in a standardized manner during the conference and transferred with a time delay of one week into a proprietary complication register.
View Article and Find Full Text PDFMedicina (Kaunas)
January 2025
Department of Orthopedic Surgery, The Keck School of Medicine of USC, Los Angeles, CA 90033, USA.
: Measuring joint range of motion (ROM) is essential for diagnosing and treating musculoskeletal diseases. However, most clinical measurements are conducted using conventional devices, and their reliability may significantly depend on the tester. This study implemented an RGB-D (red/green/blue-depth) sensor-based artificial intelligence (AI) device to measure joint ROM and compared its reliability with that of a universal goniometer (UG).
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