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Lecce nei Marsi, Italy

Muratore M.,U. O. di Reumatologia | Conversano F.,National Research Council Italy | Renna M.D.,National Research Council Italy | Villani V.,Echolight Srl | Casciaro S.,National Research Council Italy
3rd IMEKO TC13 Symposium on Measurements in Biology and Medicine 2014: New Frontiers in Biomedical Measurements | Year: 2014

Osteoporosis affects about 200 million subjects in the world and is responsible for 8.9 million fractures each year. The combined annual cost of all osteoporotic fractures in Europe has been estimated to be 30 billion Euros. The frequency of osteoporotic fractures is rising in many countries, in particular because of the increased longevity of the population. In Italy, around 4 million of women and more than 800,000 men are exposed to a high fracture risk. The National Healthcare System spends about 500 million Euros for hospitalization and chirurgical treatment of hip fractures and costs related to rehabilitation are even greater. The situation is more critical in southern Italy, where the incidence of elderly people is higher than in the other regions. Therefore, there is a strong need for the assessment of the best practices in prevention and treatment of osteoporosis. In this paper, after an overview of the socioeconomic impact of osteoporosis in Italy, with particular focus on Apulia region, the most important techniques used to assess the fracture risk are briefly described. In general, they fall into two major categories: physical measurement of skeletal mass and assessment of clinical risk factors. Moreover, the most commonly used pharmacological agents for the treatment of osteoporosis are reported. In conclusion, for a correct management of the disease, it would be necessary to encourage the widespread use of cheap and non-invasive screening techniques for early diagnosis of osteoporosis. Copyright © (2014) by the International Measurement Confederation (IMEKO) All rights reserved.


Casciaro S.,National Research Council Italy | Pisani P.,National Research Council Italy | Conversano F.,National Research Council Italy | Renna M.D.,National Research Council Italy | And 5 more authors.
IET Science, Measurement and Technology | Year: 2016

The aim of this study is to assess the accuracy of a novel ultrasound (US) approach for lumbar spine densitometry on overweight and obese women of variable age through a clinical validation study. The US method was originally developed in women with body mass index (BMI) < 25 kg/m2. In this study, 382 female patients were recruited (45-80 years, BMI > 25 kg/m2) and underwent dual X-ray absorptiometry (DXA) of lumbar spine (L1-L4) and an US scan of the same vertebrae L1-L4, performed with a dedicated device providing both echographic images and 'raw' radiofrequency signals. Acquired US data were analysed through a novel automatic algorithm that performed a series of spectral and statistical analyses to calculate bone mineral density employing an innovative method. Diagnostic accuracy of US investigations was quantitatively assessed through a direct comparison with DXA results. The average agreement between US and DXA diagnoses was acceptable for patients aged 45-65 years (81.5%), while a slight decrement was observed for older patients (69.6%), which can be partially due to a decrease in DXA accuracy because of age-related degenerations. The adopted method has a potential for early osteoporosis diagnosis in people younger than 65 years, independent of their BMI. © The Institution of Engineering and Technology.


Aventaggiato M.,Echolight Srl | Conversano F.,National Research Council Italy | Pisani P.,National Research Council Italy | Casciaro E.,National Research Council Italy | And 4 more authors.
IET Science, Measurement and Technology | Year: 2016

Aim of this study was to perform a detailed clinical validation of a new fully automatic algorithm for vertebral interface segmentation in echographic images. Abdominal echographic scans of lumbar vertebrae L1-L4 were carried out on 150 female subjects with variable age and body mass index (BMI). Acquired datasets were automatically processed by the algorithm and the accuracy of the obtained segmentations was then evaluated by three independent experienced operators. Obtained results showed a very good specificity in vertebra detection (93.3%), coupled with a reasonable sensitivity (68.1%), representing a suitable compromise between the detection of a sufficient number of vertebrae for reliable diagnoses and the limitation of the corresponding computation time. Importantly, there was only a minimum presence of 'false vertebrae' detected (2.8%), resulting in a very low influence on subsequent diagnostic analyses. Furthermore, the algorithm was specifically tuned to provide an improved sensitivity (up to 73.1%) with increasing patient BMI, to keep a suitable number of correctly detected vertebrae even when the acquisition was intrinsically more difficult because of the augmented thickness of abdominal soft tissues. The proposed algorithm will represent an essential added value for developing echographic methods for the diagnosis of osteoporosis on lumbar vertebrae. © The Institution of Engineering and Technology.


Franchini R.,National Research Council Italy | Conversano F.,National Research Council Italy | Pisani P.,National Research Council Italy | Casciaro E.,National Research Council Italy | And 5 more authors.
IET Science, Measurement and Technology | Year: 2016

Aim of this study was to perform a detailed clinical validation of a novel fully automatic method for vertebral morphometry. About 80 spine lateral radiographs were evaluated both automatically, by the proposed algorithm, and manually, by an experienced radiologist. The following metrics were used for algorithm performance assessment: Sensitivity and specificity in vertebra detection; errors in the localisation of characteristic points of vertebral border; errors in the measurement of six diagnostic parameters; level of agreement and correlation between manual and automatic morphometric measurements; overall accuracy of automatic diagnoses with respect to manual ones. Obtained results showed a very good performance in vertebra detection (sensitivity = 89.1% and specificity = 100.0%). Average errors in the localisation of vertebral characteristic points were always smaller than 3 mm (range 0.85-2.79 mm), causing relative errors in diagnostic parameter values ranging from -5.01 to +6.10%. Bland-Altman analysis documented a mean error in automatic measurements of diagnostic ratios of 0.01 ± 0.18 (bias ± 2 SDs), while Pearson's correlation coefficient resulted r = 0.71 (p < 0.001). Finally, an optimal diagnostic coincidence (92.8%) was found between automatic and manual diagnoses. Therefore, the adopted method has a potential for an effective employment in clinical routine for reliable diagnosis of vertebral fractures. © The Institution of Engineering and Technology.


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