title: Towards the generation of a parametric foot model using principal component analysis: A pilot study.
abstract: There have been many recent developments in patient-specific models with their potential to provide more information on the human pathophysiology and the increase in computational power. However they are not yet successfully applied in a clinical setting. One of the main challenges is the time required for mesh creation, which is difficult to automate. The development of parametric models by means of the Principle Component Analysis (PCA) represents an appealing solution. In this study PCA has been applied to the feet of a small cohort of diabetic and healthy subjects, in order to evaluate the possibility of developing parametric foot models, and to use them to identify variations and similarities between the two populations. Both the skin and the first metatarsal bones have been examined. Besides the reduced sample of subjects considered in the analysis, results demonstrated that the method adopted herein constitutes a first step towards the realization of a parametric foot models for biomechanical analysis. Furthermore the study showed that the methodology can successfully describe features in the foot, and evaluate differences in the shape of healthy and diabetic subjects.
authors.affiliation: Department of Information Engineering, University of Padova, Via Gradenigo 6b I, 35131 Padova, Italy . Electronic address: alessandra.scarton@dei.unipd.it.
authors.forename: Alessandra
authors.initials: A
authors.lastname: Scarton
authors.affiliation: Department of Information Engineering, University of Padova, Via Gradenigo 6b I, 35131 Padova, Italy . Electronic address: zimi.sawacha@dei.unipd.it.
authors.forename: Zimi
authors.initials: Z
authors.lastname: Sawacha
authors.affiliation: Department of Information Engineering, University of Padova, Via Gradenigo 6b I, 35131 Padova, Italy . Electronic address: cobelli@dei.unipd.it.
authors.forename: Claudio
authors.initials: C
authors.lastname: Cobelli
authors.affiliation: Department of Mechanical Engineering, University of Sheffield, Sheffield, United Kingdom; The Insigneo Institute for in silico Medicine, University of Sheffield, The Pam Liversidge Building, Sir Frederick Mappin Building, Mappin Street, Sheffield S1 3JD, United Kingdom. Electronic address: xinshan.li@sheffield.ac.uk.
authors.forename: Xinshan
authors.initials: X
authors.lastname: Li
mesh_terms: D000328:Adult; D016022:Case-Control Studies; D017719:Diabetic Foot / Q000000981:diagnostic imaging; D005260:Female; D020342:Finite Element Analysis; D005528:Foot / Q000000981:diagnostic imaging; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D010865:Pilot Projects; D025341:Principal Component Analysis
keywords: Diabetic foot; Finite element mesh; Parameterization; Principal component analysis