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Algorithm based automatic templating is less accurate than manual digital templating in total knee arthroplasty.

Thomas SeaverKenneth McAlpineEnrique GarciaRuijia NiuEric L Smith
Published in: Journal of orthopaedic research : official publication of the Orthopaedic Research Society (2020)
The purpose of the study was to evaluate the accuracy of a commercial automatic digital templating algorithm compared to manual digital templating in total knee arthroplasty (TKA). The study also evaluated if race and the presence of a standardized calibration marker on preoperative radiographs effect the accuracy of digital templating. One hundred twenty-five consecutive patients undergoing primary TKA were included in the study. Patient demographics, etiology of arthritis, and the presence of a standardized calibration marker on preoperative anteroposterior (AP) and lateral radiographs was recorded. Manual digital templating and the use of the "auto-knee" templating algorithm with "Traumacad" software was performed and recorded. Intraoperative sizes of the actual implants used were recorded. Pearson χ2 test was used to evaluate the accuracy of auto versus manual templating. Manual templating was within 1 size of the implant used intraoperatively for femoral and tibial implants 97.6% and 94.2% of the time, respectively. The "auto-knee" algorithm was within one size of the implant used for femoral and tibial implants 51.2% and 71.2% of the time, respectively. The presence of a standardized calibration marker on the AP view did not change accuracy of templating for both components. There was no difference in accuracy of templating between races. We caution surgeons from exclusively using an automatic algorithm as it is less accurate than manual templating for TKA.
Keyphrases
  • total knee arthroplasty
  • deep learning
  • total hip
  • machine learning
  • patients undergoing
  • neural network
  • soft tissue
  • rheumatoid arthritis
  • transcription factor
  • low cost
  • mass spectrometry