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Purpose: Using a fully automated multitask deep learning method, which enabled simultaneous segmentation and quantification of all major anterior segment structures with swept-source optical coherence tomography (SS-OCT), we aimed to investigate the three-dimensional (3D) alterations in iris morphology before and after implantable collamer lens (ICL) surgery.

Methods: All enrolled patients underwent anterior segment SS-OCT (ANTERION) within one week before and after ICL surgery. A multitask network automatically performed iris SS-OCT image segmentation and quantitative measurements of 3D iris morphology (iris thickness and volume of the inner 1-mm annular area and the outer 1-2-mm annular area, iris curvature [I-Curve], and iris smooth index [SI]).

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Objective: The objective of this study was to improve long-term postoperative survival in a porcine cardiac valve surgery model by utilizing cardiopulmonary bypass (CPB) via left thoracotomy. The study aimed to share refined techniques and insights accumulated over years at a single-center animal clinical trial facility.

Method: A total of 196 Chinese Large White pigs weighing between 60 and 75 kg were used in the study.

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Background: The ideal anteversion at which the acetabular and femoral components for a total hip arthroplasty (THA) should be implanted is still a subject of debate. One alignment philosophy being explored is restoration of individual constitutional femoral and acetabular anteversion. This study aimed to measure combined anteversion in a healthy hip population and understand the expected phenotypes and ranges for constitutional hip alignment.

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Total Knee Arthroplasty Automated Implant Detector: An Uncertainty-Aware Deep Learning Classifier to Identify Total Knee Arthroplasty Implants.

J 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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Effect of Laminectomy Methods on the Surgical Safety of Automatic Laminectomy Robot.

Int J Med Robot

February 2025

Beijing Key Laboratory for Design and Evaluation Technology of Advanced Implantable & Interventional Medical Devices, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China.

Background: The efficacy of laminectomy procedures is contingent on the method of resection. The objective of this study was to investigate the impact of different methods of resection on the surgical safety of automated laminectomy robots, an area that remains uncharted.

Methods: Lamina resection surgeries using both drilling and layer-by-layer methods, are performed on ovine spinal samples.

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