The use of fuzzy logic to select which curves need to be instrumented and fused in adolescent idiopathic scoliosis: a feasibility study.

Selection of the appropriate curve fusion levels for surgery in adolescent idiopathic scoliosis (AIS) is a complex and difficult task. Despite numerous publications on this subject, the decision as to which spinal curve, that is proximal thoracic, main thoracic or lumbar, needs to be instrumented and included in the fusion relies mostly on each surgeon's past experience, although recently published data have revealed a high variability of spinal instrumentation configurations among spinal surgeons in AIS. This situation exists because of ambiguity and vagueness in the decision process. Our objective is to capture the proposed rules for the selection of fusion levels and integrate them in a fuzzy logic model to decrease haziness and imprecision in the selection process. Two models have been developed, one for proximal thoracic curves and the other for lumbar curves. These models were constructed using data from a literature review, which allowed the extraction of currently proposed rules and their modeling as inputs in a computer software based on fuzzy logic modeling. Five and four inputs have been respectively chosen for the proximal thoracic and lumbar model. When all input values are entered in the model for a specific subject with AIS, the software calculates the level of suggestion for the indication to perform an instrumentation and fusion of the high thoracic and/or lumbar curves for this particular subject. The usefulness of this approach is demonstrated using illustrative cases. This is the first report on the use of fuzzy logic to assist the decision-making process in the field of spinal deformity surgery and the results suggest that this approach may be useful to facilitate surgical planning in difficult or borderline cases of AIS.