Advanced 3D imaging and CT-based navigation have emerged as valuable tools to use in total knee arthroplasty (TKA), for both preoperative planning and the intraoperative execution of different philosophies of alignment. Preoperative planning using CT-based 3D imaging enables more accurate prediction of the size of components, enhancing surgical workflow and optimizing the precision of the positioning of components. Surgeons can assess alignment, osteophytes, and arthritic changes better. These scans provide improved insights into the patellofemoral joint and facilitate tibial sizing and the evaluation of implant-bone contact area in cementless TKA. Preoperative CT imaging is also required for the development of patient-specific instrumentation cutting guides, aiming to reduce intraoperative blood loss and improve the surgical technique in complex cases. Intraoperative CT-based navigation and haptic guidance facilitates precise execution of the preoperative plan, aiming for optimal positioning of the components and accurate alignment, as determined by the surgeon’s philosophy. It also helps reduce iatrogenic injury to the periarticular soft-tissue structures with subsequent reduction in the local and systemic inflammatory response, enhancing early outcomes. Despite the increased costs and radiation exposure associated with CT-based navigation, these many benefits have facilitated the adoption of imaged based robotic surgery into routine practice. Further research on ultra-low-dose CT scans and exploration of the possible translation of the use of 3D imaging into improved clinical outcomes are required to justify its broader implementation. Cite this article:
Ceramic bearings have several desirable properties, such as resistance to wear, hardness, and biocompatibility, that favour it as an articulating surface in hip arthroplasty. However, ceramic fracture remains a concern. We have reviewed the contemporary literature, addressing the factors that can influence the incidence of ceramic bearing surface fracture. Cite this article:
‘Big data’ is a term for data sets that are so
large or complex that traditional data processing applications are
inadequate. Billions of dollars have been spent on attempts to build predictive
tools from large sets of poorly controlled healthcare metadata.
Companies often sell reports at a physician or facility level based
on various flawed data sources, and comparative websites of ‘publicly
reported data’ purport to educate the public. Physicians should
be aware of concerns and pitfalls seen in such data definitions,
data clarity, data relevance, data sources and data cleaning when
evaluating analytic reports from metadata in health care. Cite this article:
