Three-dimensional multifractal analysis of trabecular bone under clinical computed tomography

Autor: Juan Carlos Gómez, Borko Stosic, Tatijana Stosic, Felix Sebastian Leo Thomsen, Rodrigo Baravalle, Claudio Delrieux, Yongtao Lu
Rok vydání: 2017
Předmět:
FAILURE LOAD
030209 endocrinology & metabolism
Computed tomography
02 engineering and technology
Risk Assessment
purl.org/becyt/ford/1 [https]
03 medical and health sciences
0302 clinical medicine
Imaging
Three-Dimensional
Bone Density
0202 electrical engineering
electronic engineering
information engineering
medicine
Humans
Quantitative computed tomography
MULTIFRACTAL
Mathematics
Bone mineral
medicine.diagnostic_test
business.industry
THREE-DIMENSIONAL MULTIFRACTAL ANALYSIS
Linear model
Pattern recognition
purl.org/becyt/ford/1.2 [https]
General Medicine
Multifractal system
Ciencias de la Computación
Trabecular bone
Fractals
Skewness
Ciencias de la Computación e Información
Cancellous Bone
Kurtosis
020201 artificial intelligence & image processing
Artificial intelligence
BONE
business
Tomography
X-Ray Computed
CIENCIAS NATURALES Y EXACTAS
Zdroj: CONICET Digital (CONICET)
Consejo Nacional de Investigaciones Científicas y Técnicas
instacron:CONICET
ISSN: 2473-4209
Popis: Purpose: An adequate understanding of bone structural properties is critical for predicting fragility conditions caused by diseases such as osteoporosis, and in gauging the success of fracture prevention treatments. In this work we aim to develop multiresolution image analysis techniques to extrapolate high-resolution images predictive power to images taken in clinical conditions. Methods: We performed multifractal analysis (MFA) on a set of 17 ex vivo human vertebrae clinical CT scans. The vertebræ failure loads (FFailure) were experimentally measured. We combined bone mineral density (BMD) with different multifractal dimensions, and BMD with multiresolution statistics (e.g., skewness, kurtosis) of MFA curves, to obtain linear models to predict FFailure. Furthermore we obtained short- and long-term precisions from simulated in vivo scans, using a clinical CT scanner. Ground-truth data - high-resolution images - were obtained with a High-Resolution Peripheral Quantitative Computed Tomography (HRpQCT) scanner. Results: At the same level of detail, BMD combined with traditional multifractal descriptors (Lipschitz-Hölder exponents), and BMD with monofractal features showed similar prediction powers in predicting FFailure (87%, adj. R2). However, at different levels of details, the prediction power of BMD with multifractal features raises to 92% (adj. R2) of FFailure. Our main finding is that a simpler but slightly less accurate model, combining BMD and the skewness of the resulting multifractal curves, predicts 90% (adj. R2) of FFailure. Conclusions: Compared to monofractal and standard bone measures, multifractal analysis captured key insights in the conditions leading to FFailure. Instead of raw multifractal descriptors, the statistics of multifractal curves can be used in several other contexts, facilitating further research. Fil: Baravalle, Rodrigo Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina Fil: Thomsen, Felix Sebastian Leo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Sur; Argentina Fil: Delrieux, Claudio Augusto. Universidad Nacional del Sur; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Lu, Yongtao. Dalian University of Technology; China Fil: Gómez, Juan Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina Fil: Stošić, Borko. Universidade Federal Rural Pernambuco; Brasil Fil: Stošić, Tatijana. Universidade Federal Rural Pernambuco; Brasil
Databáze: OpenAIRE
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