Literature DB >> 30660337

Can low-frequency guided waves at the tibia paired with machine learning differentiate between healthy and osteopenic/osteoporotic subjects? A pilot study.

Florian Vogl1, Bernd Friesenbichler2, Laura Hüsken3, Inès A Kramers-de Quervain4, William R Taylor3.   

Abstract

PURPOSE: Axial transmission quantitative acoustics (ax-QA) has shown to be a promising tool for assessing bone health and properties in a safe, inexpensive, and portable manner. This study investigated the efficacy of low-frequency ax-QA measured at the tibia, paired with a support vector machine (SVM) approach for combining multiple acoustic indicators, to diagnose osteoporosis as defined by bone mineral density.
METHODS: This pilot study measured 41 female subjects using ax-QA (flexural mode, 3 kHz) at the tibia and using dual X-ray absorptiometry (DXA) at the lumbar spine, femoral neck, and distal radius. For each location, a threshold classifier and SVM were trained to differentiate between healthy and non-healthy subjects based on the phase velocity at different frequencies. Receiver Operating Characteristics and area under curve values (AUC) were used to assess the classifiers' performances for various thresholds and class-weights.
RESULTS: The SVM outperformed the threshold classifier for all three bone locations at low false positive rates. While differentiation between healthy and non-healthy bone states was poor for the spine (AUC: 0.56 ± 0.04), good to moderate performances were observed for the radius (AUC: 0.83 ± 0.03) and hip (AUC: 0.71 ± 0.04).
CONCLUSIONS: Low-frequency ax-QA has demonstrated potential for complementing DXA in screening for osteoporosis at the radius and hip. Through further addition of acoustic indicators ax-QA could provide a diagnostic alternative in third-world countries, and bring bone health screening and monitoring into the hands of clinicians and general health practitioners everywhere.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Acoustic waves; Osteoporosis; Quantitative acoustics; Speed of sound

Mesh:

Year:  2018        PMID: 30660337     DOI: 10.1016/j.ultras.2018.11.012

Source DB:  PubMed          Journal:  Ultrasonics        ISSN: 0041-624X            Impact factor:   2.890


  8 in total

1.  Artificial neural network to estimate micro-architectural properties of cortical bone using ultrasonic attenuation: A 2-D numerical study.

Authors:  Kaustav Mohanty; Omid Yousefian; Yasamin Karbalaeisadegh; Micah Ulrich; Quentin Grimal; Marie Muller
Journal:  Comput Biol Med       Date:  2019-09-20       Impact factor: 4.589

Review 2.  Artificial intelligence, osteoporosis and fragility fractures.

Authors:  Uran Ferizi; Stephen Honig; Gregory Chang
Journal:  Curr Opin Rheumatol       Date:  2019-07       Impact factor: 5.006

3.  Signal Processing Techniques Applied to Axial Transmission Ultrasound.

Authors:  Tho N H T Tran; Kailiang Xu; Lawrence H Le; Dean Ta
Journal:  Adv Exp Med Biol       Date:  2022       Impact factor: 2.622

4.  Axial Transmission: Techniques, Devices and Clinical Results.

Authors:  Nicolas Bochud; Pascal Laugier
Journal:  Adv Exp Med Biol       Date:  2022       Impact factor: 2.622

5.  Fully automated radiomic screening pipeline for osteoporosis and abnormal bone density with a deep learning-based segmentation using a short lumbar mDixon sequence.

Authors:  Yinxia Zhao; Tianyun Zhao; Shenglan Chen; Xintao Zhang; Mario Serrano Sosa; Jin Liu; Xianfu Mo; Xiaojun Chen; Mingqian Huang; Shaolin Li; Xiaodong Zhang; Chuan Huang
Journal:  Quant Imaging Med Surg       Date:  2022-02

6.  Classification of Micro-Damage in Piezoelectric Ceramics Using Machine Learning of Ultrasound Signals.

Authors:  Gaurav Tripathi; Habib Anowarul; Krishna Agarwal; Dilip K Prasad
Journal:  Sensors (Basel)       Date:  2019-09-28       Impact factor: 3.576

7.  A hierarchical opportunistic screening model for osteoporosis using machine learning applied to clinical data and CT images.

Authors:  Liyu Liu; Meng Si; Hecheng Ma; Menglin Cong; Quanzheng Xu; Qinghua Sun; Weiming Wu; Cong Wang; Michael J Fagan; Luis A J Mur; Qing Yang; Bing Ji
Journal:  BMC Bioinformatics       Date:  2022-02-10       Impact factor: 3.169

8.  Bone Mineral Content Estimation in People Living with HIV: Prediction and Validation of Sex-Specific Anthropometric Models.

Authors:  Igor Massari Correia; Anderson Marliere Navarro; Jéssica Fernanda Corrêa Cordeiro; Euripedes Barsanulfo Gonçalves Gomide; Lisa Fernanda Mazzonetto; Alcivandro de Sousa Oliveira; Emerson Sebastião; Bruno Augusto Aguilar; Denise de Andrade; Dalmo Roberto Lopes Machado; André Pereira Dos Santos
Journal:  Int J Environ Res Public Health       Date:  2022-09-28       Impact factor: 4.614

  8 in total

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