Clinical evaluation of a novel ultrasound-based methodology for osteoporosis diagnosis on overweight and obese women

Abstract

Osteoporosis and overweight/obesityconstitute major worldwide public health burdens that areassociated with aging. The gold standard for osteoporosisdiagnosis is currently represented by bone mineral density(BMD) measurement through dual-energy X-rayabsorptiometry (DXA). However, DXA cannot be used forearly diagnosis through population mass screenings due toionizing radiation employment. Because of this, generally,only people considered at high risk of fracture (underweightwomen after the menopause) undergo to osteoporosisscreening. In fact, a significant risk factor for fracture is thelow body mass index (BMI), while the tendency tooverweight or obesity delays osteoporosis onset.Nevertheless, a high proportion of women after themenopause develop intra-abdominal adiposity, which leadsto metabolic disorders and osteoporosis. This paperdescribes the diagnostic accuracy of a novel ultrasound(US)-based method to perform spinal densitometry. Theproposed innovative methodology is based on a combinedanalysis of both echographic images and "raw"radiofrequency US signals. The diagnostic output isrepresented by the same parameters provided by DXA(BMD, T-score, Z-score). The efficiency of the proposedmethodology was evaluated on a cohort of 280 overweightor obese (BMI > 25 kg/m2) female patients in the age range45-65 years. For 81.4% of the patients, US diagnosis(osteoporotic, osteopenic, healthy) was the same of thecorresponding DXA one, showing the high accuracy of theproposed US technique, especially in the youngest patients(86.4% of correct diagnoses in the age range 45-50 y). Agood correlation was also found between the diagnosticparameters provided by both US and DXA methods: allobtained values of Pearson coefficient (r) were within theinterval 0.66-0.76 (p<0.001). Then, this new non-ionizingapproach to spinal bone densitometry has the potential forbeing extremely useful for early osteoporosis diagnosisthrough population mass screenings.


Tutti gli autori

  • S. Casciaro; M. D. Renna; F. Conversano; G. Soloperto; E. Casciaro; E. Quarta; A. Grimaldi ; M. Muratore

Titolo volume/Rivista

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Anno di pubblicazione

2014

ISSN

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ISBN

978-92-990073-5-8


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Nessuna citazione

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Settori ERC

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