A Novel Registration-Based Approach for 3D Assessment of Posttraumatic Distal Humeral Deformities. (6th December 2017)

• Record Type: Journal Article
• Authors: Vlachopoulos, Lazaros; Carrillo, Fabio; Gerber, Christian; Székely, Gábor; Fürnstahl, Philipp
• Is Part Of: Journal of bone and joint surgery. Volume 99:Number 23(2017)
• Publication Date: 2017-12-06
• Subjects: Bones -- Surgery -- Periodicals; Joints -- Surgery -- Periodicals; Orthopedics -- Periodicals; Orthopedics; General Surgery; Bone Diseases; Joint Diseases; Bones -- Surgery; Joints -- Surgery; Orthopedics; Bot (anatomie); Gewrichten; Chirurgie (geneeskunde); Periodicals; Electronic journals; Periodicals; 617.47005
• DOI: 10.2106/JBJS.16.01166
• Languages: English
• ISSNs: 0021-9355

Abstract

Abstract : Background: With current 3-dimensional (3D) computer-based methods for the assessment of deformities, a surface registration method is applied to superimpose a computer model of the pathological bone onto a mirrored computer model of the contralateral side. However, because of bilateral differences, especially in humeral torsion, such template-based approaches may introduce bias in the assessment of a distal humeral deformity. We hypothesized that a novel registration approach might prove superior to the current approach in reducing such bias, thus yielding improved accuracy of 3D assessment of distal humeral deformities. Methods: Three-dimensional triangular surface models were generated from computed tomographic (CT) data of 100 paired humeri without a pathological condition. Humeral segments of varying, predetermined lengths, excluding the distal part of the humerus, were defined. A surface registration algorithm was applied to superimpose the humeral models of both sides based on each selected segment. Humeral contralateral registration (HCR) errors, defined as the residual differences in apparent 3D orientation between the distal parts, were evaluated. Results: The mean HCR error (and standard deviation) using the distal-most humeral shaft segment to assess the angular orientation was 2.3° ± 1.1 (range, 0.5° to 5.8°). Including the humeral head in the surface registration algorithm, however, as is done currently, resulted in a higher HCR error (p < 0.001). The HCR error using the proximal-most segment was >10° in 20% of the cases and between 5° and 10° in an additional 50% of the cases. By comparison, using the proposed distal-most humeral shaft segment, the HCR error was between 5° and 10° in only 2% of cases, and was never >10°. The proximal segments are nevertheless used in the proposed method for registering humeral length. Conclusions: The proposed new approach yields a deformity assessment that is less prone to bias arising from inherent bilateral differences and therefore is more accurate than current surface registration approaches. Clinical Relevance: Accurate 3D assessment is of fundamental importance if computer-based methods are applied in the correction of posttraumatic deformities.