Patient-specific modeling of the trochlear morphologic anomalies by means of hyperbolic paraboloids. Issue 1 (1st January 2016)

• Record Type: Journal Article
• Authors: Cerveri, Pietro; Baroni, Guido; Confalonieri, Norberto; Manzotti, Alfonso
• Is Part Of: Computer assisted surgery. Volume 21:Issue 1(2016)
• Page Start: 29
• Page End: 38
• Publication Date: 2016-01-01
• Subjects: Distal femur -- hyperbolic paraboloid modeling -- medial and lateral facets -- trochlear dysplasia; Computer-assisted surgery -- Periodicals
• DOI: 10.1080/24699322.2016.1178330
• Languages: English
• ISSNs: 2469-9322

Abstract

Abstract: Diagnostic and therapeutic purposes are issuing pressing demands to improve the evaluation of the dysplasia condition of the femoral trochlea. The traditional clinical assessment of the dysplasia, based on Dejour classification, recognized 4 increasing (A, B, C, D) levels of severity. It has been extensively questioned in the literature that this classification methodology can be defective suggesting that quantitative measures can ensure more reliable criteria for the dysplasia severity assessment. This study reports on a novel technique to model the trochlear surface (TS), digitally reconstructed by 3D volumetric imaging, using three hyperbolic paraboloids (HP), one to describe the global trochlear aspect, two to represent the local aspects of the medial and lateral compartments, respectively. Results on a cohort of 43 patients, affected by aspecific anterior knee pain, demonstrate the consistency of the estimated model parameters with the morphologic aspect of the TS. The obtained small fitting error (on average lower than 0.80 mm) demonstrated that the ventral aspect of the trochlear morphology can be modeled with high accuracy by HPs. We also showed that HP modeling provides a continuous representation of morphologic variations in shape parameter space while we found that similar morphologic anomalies of the trochlear aspect are actually attributed to different severity grades in the Dejour classification. This finding is in agreement with recent works in the literature reporting that morphometric parameters can only optimistically be used to discriminate between the Grade A and the remaining three grades. In conclusion, we can assert that the proposed methodology is a further step toward modeling of anatomical surfaces that can be used to quantify deviations to normality on a patient-specific basis.