Rev Saúde Pública 2014;48(n.esp):282-321
2nd IPLeiria Internacional Health Congress | Challenges & Innovation in Health
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BIOMECHANICAL ANALYSIS OF THE CARTILAGE*
DEVELOPMENT OF A COMPUTATIONAL TOOL FOR CHARACTERIZATION OF THERMAL IMAGES IN MEDICAL APPLICATIONS*
Dino FreitasI,a, Henrique AlmeidaII,b, Paulo BártoloI,II,III,c I
Centre for Rapid and Sustainable Product Development. Instituto Politécnico de Leiria. Leiria, Portugal
II
School of Mechanical, Civil and Aerospace Engineering. University of Manchester. Manchester, United Kingdom
III
Manchester Institute of Biotechnology. University of Manchester. Manchester, United Kingdom
Introduction: The increasing number of injuries and diseases affecting cartilage has somehow contributed to the growth of recent studies. For these reasons, the study of FDUWLODJHKDVEHHQDVVXPHGDVDQHPHUJLQJ¿HOGRIWLVVXH engineering because of the constant search for solutions to repair and regenerate cartilage, which makes it highly important to characterize and study the behaviour of cartilage. Objective: To recognize the inherent characteristics of articular cartilage, comparison testing was performed between the characterizations carried out in swine cartiODJHDQGWKHH[LVWLQJ¿QLWHHOHPHQWPRGHOVRIK\SHUHODVticity, using a 3D model of cartilage. Methods: Ten samples of cartilage from the acetabular cavity of the hip joint from 5 different pigs about the same age were characterized. The water content characterization of the cartilage was determined on the basis of weight loss. The cartilage was detached from the subchondral bone for this analysis and samples of 15x15xt (mm) were made, being “t” the thickness that varies through the depth between the three layers that characterize the cartilage. The analysis took 9h at a temperature of 37ºC and measured every 30 min. The cartilage samples lost about 77% of their weight in water and we obtained a relation between time and the water loss content. Results and Conclusions: With this relation, the porosity of the cartilage along with the elasticity modulus was calculated and then computational simulations with 5 different hyperelastic models were performed, being the Arruda-Boyce the most accurate, obtaining a biomechanical behaviour very similar to real cartilage. Descriptors:&DUWLODJH7LVVXH %LRPHFKDQLFDO%HKDYLRXU $UWLFXODU&DUWLODJH +\SHUHODVWLF 7LVVXH(QJLQHHULQJ *Authors acknowledge the support of the FCT (Strategic Project PEST-OE/EME/UI4044/2013) and the European Commission (IREBID Marie Curie Project).
Ana DuarteI,a, Luís CarrãoII,III,b, Margarida EspanhaII,c, Tânia VianaIV,d, Dino FreitasIV,e, Paulo BártoloIV,V,VI,f, Henrique AlmeidaI,IV,g, Paula FariaI,IV,h I
Escola Superior de Tecnologia e Gestão. Instituto Politécnico de Leiria. Leiria, Portugal
II
Desporto e Saúde. Faculdade de Motricidade Humana. Universidade de Lisboa. Lisboa, Portugal
III
Escola Superior de Saúde. Instituto Politécnico de Leiria. Leiria, Portugal
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Centre for Rapid and Sustainable Product Development. Instituto Politécnico de Leiria. Leiria, Portugal
V
School of Mechanical, Civil and Aerospace Engineering. University of Manchester. Manchester, United Kingdom
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Manchester Institute of Biotechnology. University of Manchester. Manchester, United Kingdom
Introduction: Medicine is constantly evolving and looking for non-invasive, safer diagnostics and therapeutic techniques. Medical thermography is being used more often, mainly, in the detection of certain diseases in breast screening, also in allergology and pain. Commercial thermography software has some limitations because it is developed for general applications. In this work we develop an application that makes the analysis of thermal images more accessible to the medical community. Objective: The main goal of this research is to develop a user friendly computational application that facilitates the interpretation of thermal images. Starting by isolating Regions of Interest (ROIs), important data can be obtained. Temperature can be interpreted and related to possible abnormalities, such as lesions or pain distribution. Traditional thermal processing VRIWZDUHDOORZVWKHLGHQWL¿FDWLRQRI52,VVKDSHVZLWKUHFWangular or ellipsoidal forms. As biological ROIs don’t have regular shapes, software capable of processing any kind of ROI shape will improve diagnostic and therapeutic techniques. Methods: The thermal images application was created using Matlab and allows the user to select any ROI, independently of its geometric shape. A functionality that optimizes the chosen region, removing areas that don’t have any relevant statistic data was also added. Results and Conclusions:$IWHU52,¶VLGHQWL¿FDWLRQVRPH statistical measures (such as maximum, minimum, average temperature values) and comparisons of different regions with the aid of histograms or tables may be presented. Descriptors:7KHUPRJUDSK\ %RG\KHDW 7KHUPDO,PDJHV 'LDJQRVLV 7KHUDSHXWLF7HFKQLTXHV *Authors acknowledge the support of the FCT (Strategic Project PEST-OE/EME/UI4044/2013) and the European Commission (IREBID Marie Curie Project).
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