• Marie-Lyne Nault, Hubert Labelle, Carl-Eric Aubin, Archana Sangole, and Marek Balazinski.
• Sainte-Justine University Hospital Center, Montreal, Quebec, Canada.
• J Spinal Disord Tech. 2009 Jun 1; 22 (4): 263-9.

Summary Of Background DataSelection of appropriate curve fusion levels for surgery in adolescent idiopathic scoliosis (AIS) is a complex and difficult task and, despite numerous publications, still remains a highly controversial topic.ObjectiveTo evaluate a fuzzy-logic-based surgical planning tool by comparing the results suggested by the software with the average outcome recommended by a panel of 5 expert spinal deformity surgeons. It is hypothesized that, given the same information, the fuzzy-logic tool will perform as favorably as the surgeons.Study DesignProof-of-concept study evaluating the use of a fuzzy-logic-assisted surgical planning tool in AIS to select the appropriate spinal curve to be instrumented.MethodsA cohort of 30 AIS surgical cases with a main thoracic curve was used. Each case included standard measurements recorded from preoperative standing postero-anterior and lateral, supine side bending, and 1-year postoperative standing radiographs. Five experienced spinal deformity surgeons evaluated each case independently and gave their preferred levels of instrumentation and fusion. The cases were then presented to the fuzzy-logic tool to determine whether the high thoracic and/or lumbar curves were to be instrumented. For each case, a percentage value was obtained indicating inclusion/exclusion of the respective curves in the surgical instrumentation procedure. Kappa statistics was used to compare the model output and the average decision of the surgeons.ResultsKappa values of 0.71 and 0.64 were obtained, respectively, for the proximal thoracic and lumbar curves models, thus suggesting a good agreement of the fusion recommendations made by the fuzzy-logic tool and the surgeons.ConclusionsGiven the same information, the fuzzy-logic-assisted recommendation of the curve to be instrumented compared favorably with the collective decision of the surgeons. The findings thus suggest that a fuzzy-logic approach is helpful in assisting surgeons with the preoperative selection of curve instrumentation and fusion levels in AIS.

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