RESUMO
BACKGROUND: Acetabular reconstruction in complex primary and revision total hip arthroplasty (THA) with bone loss poses a great challenge. We aim to evaluate the medium-term clinical and radiological outcome of reconstruction rings used in these difficult situations. METHODS: We retrospectively reviewed a consecutive series of acetabular reconstructions with Muller ring or Bursh-Schneider cage from January 2009 to December 2016. The reconstruction rings were used in 66 hips (65 patients). There were 41 complex primary THA and 25 revision THA. The mean follow-up period was 76 months (range, 37-167 months). Clinical evaluation includes the assessment of Harris hip score, visual analogue scale (VAS) score, limb length discrepancy, and activities of daily living. The radiographs were analyzed for any signs of loosening, osteolysis, acetabular migration, and heterotopic ossification. RESULTS: The overall survival rate was 95% for revision in aseptic loosening and 87% for any reason at an average follow-up of 6.3 years. Twelve patients died and 9 patients were lost to follow-up leaving 45 patients for final functional analysis. Among the 45 patients, excellent to good results were seen in 33 patients, fair results were seen in 5 patients, poor results were seen in seven patients. Two patients had aseptic loosening and another two patients developed deep chronic infection awaiting two-stage revision. CONCLUSION: Reconstruction rings still place a role in the armamentarium for complex acetabular reconstruction. It helps to reliably restore the bone stock, have an acceptable survival rate and satisfactory functional outcome at medium to long-term follow-up.
RESUMO
Surgical tool detection is attracting increasing attention from the medical image analysis community. The goal generally is not to precisely locate tools in images, but rather to indicate which tools are being used by the surgeon at each instant. The main motivation for annotating tool usage is to design efficient solutions for surgical workflow analysis, with potential applications in report generation, surgical training and even real-time decision support. Most existing tool annotation algorithms focus on laparoscopic surgeries. However, with 19 million interventions per year, the most common surgical procedure in the world is cataract surgery. The CATARACTS challenge was organized in 2017 to evaluate tool annotation algorithms in the specific context of cataract surgery. It relies on more than nine hours of videos, from 50 cataract surgeries, in which the presence of 21 surgical tools was manually annotated by two experts. With 14 participating teams, this challenge can be considered a success. As might be expected, the submitted solutions are based on deep learning. This paper thoroughly evaluates these solutions: in particular, the quality of their annotations are compared to that of human interpretations. Next, lessons learnt from the differential analysis of these solutions are discussed. We expect that they will guide the design of efficient surgery monitoring tools in the near future.
