DXA-based Bone Strain Index: A New Tool to Evaluate Bone Quality in Primary Hyperparathyroidism

Abstract Context Primary hyperparathyroidism (PHPT) is associated with impaired bone quality and increased fracture risk. Reliable tools for the evaluation of bone quality parameters are not yet clinically available. Bone Strain Index (BSI) is a new metric for bone strength based on Finite Element Analysis from lumbar spine and femoral neck dual X-ray absorptiometry images. Objective To assess the lumbar spine (LS), femoral neck (FN), and total hip (TH) BSI in PHPT compared to controls and to investigate the association of BSI with vertebral fractures (VFs) in PHPT. Design case-control study Setting Outpatient clinic Patients 50 PHPT and 100 age- and sex-matched control subjects. Main Outcome Measures LS-BSI, FN-BSI, TH-BSI. Results FN bone mineral density (BMD) and 1/3 distal radius BMD were lower in the PHPT group than in controls (FN 0.633 ± 0.112 vs 0.666 ± 0.081 p= 0.042; radius 0.566 ± 0.07 vs 0.625 ± 0.06 p<0.001). PHPT group has significant lower TBS score compared to controls (1.24 ± 0.09 vs 1.30 ± 0.10 p <0.001).BSI was significantly higher at LS (2.28±0.59 vs 2.02±0.43, p=0.009), FN (1.72±0.41 vs 1.49±0.35, p=0.001) and TH (1.51±0.33 vs 1.36±0.25, p=0.002) in PHPT. LS-BSI showed moderate accuracy for discriminating VFs (AUC 0.667; 95% CI 0.513-0.820). LS-BSI ≥ 2.2 and was a statistically significant independent predictor of VFs, with an adjusted OR ranging from 5.7 to 15.1. Conclusion BSI, a DXA-derived bone quality index, is impaired in PHPT and may help to identify PHPT subjects at high risk of fractures.

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Evaluation of bone quality by dxa-based bone strain index in primary hyperparathyroidism

Endocrine Abstracts ◽

10.1530/endoabs.73.aep104 ◽

2021 ◽

Author(s):

Gaia Tabacco ◽

Anda Mihaela Naciu ◽

Carmelo Messina ◽

Luca Rinaudo ◽

Roberto Cesareo ◽

...

Keyword(s):

Primary Hyperparathyroidism ◽

Bone Quality ◽

Bone Strain ◽

Strain Index

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Beyond Bone Mineral Density: A New Dual X-Ray Absorptiometry Index of Bone Strength to Predict Fragility Fractures, the Bone Strain Index

Frontiers in Medicine ◽

10.3389/fmed.2020.590139 ◽

2021 ◽

Vol 7 ◽

Author(s):

Fabio Massimo Ulivieri ◽

Luca Rinaudo

Keyword(s):

Bone Mineral Density ◽

Density Distribution ◽

Bone Strength ◽

Bone Quality ◽

Bone Mineral ◽

Fragility Fracture ◽

Bone Strain ◽

Mineral Density ◽

Strain Index ◽

X Ray

For a proper assessment of osteoporotic fragility fracture prediction, all aspects regarding bone mineral density, bone texture, geometry and information about strength are necessary, particularly in endocrinological and rheumatological diseases, where bone quality impairment is relevant. Data regarding bone quantity (density) and, partially, bone quality (structure and geometry) are obtained by the gold standard method of dual X-ray absorptiometry (DXA). Data about bone strength are not yet readily available. To evaluate bone resistance to strain, a new DXA-derived index based on the Finite Element Analysis (FEA) of a greyscale of density distribution measured on spine and femoral scan, namely Bone Strain Index (BSI), has recently been developed. Bone Strain Index includes local information on density distribution, bone geometry and loadings and it differs from bone mineral density (BMD) and other variables of bone quality like trabecular bone score (TBS), which are all based on the quantification of bone mass and distribution averaged over the scanned region. This state of the art review illustrates the methodology of BSI calculation, the findings of its in reproducibility and the preliminary data about its capability to predict fragility fracture and to monitor the follow up of the pharmacological treatment for osteoporosis.

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Bone strain index in the prediction of vertebral fragility refracture

European Radiology Experimental ◽

10.1186/s41747-020-00151-8 ◽

2020 ◽

Vol 4 (1) ◽

Cited By ~ 2

Author(s):

Fabio Massimo Ulivieri ◽

Luca Petruccio Piodi ◽

Luca Rinaudo ◽

Paolo Scanagatta ◽

Bruno Mario Cesana

Keyword(s):

Bone Strain ◽

Strain Index

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Bone Histomorphometry and Bone Quality in Primary Hyperparathyroidism

The Parathyroids ◽

10.1016/b978-0-12-397166-1.00029-1 ◽

2015 ◽

pp. 429-445 ◽

Cited By ~ 4

Author(s):

David W. Dempster ◽

Shonni J. Silverberg ◽

Elizabeth Shane ◽

John P. Bilezikian

Keyword(s):

Primary Hyperparathyroidism ◽

Bone Quality ◽

Bone Histomorphometry

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Bone quality, as measured by trabecular bone score, in patients with primary hyperparathyroidism

Acta Endocrinologica ◽

10.1530/eje-13-0305 ◽

2013 ◽

Vol 169 (2) ◽

pp. 155-162 ◽

Cited By ~ 73

Author(s):

Cristina Eller-Vainicher ◽

Marcello Filopanti ◽

Serena Palmieri ◽

Fabio Massimo Ulivieri ◽

Valentina Morelli ◽

...

Keyword(s):

Primary Hyperparathyroidism ◽

Trabecular Bone ◽

Bone Quality ◽

Trabecular Bone Score ◽

Dual Energy ◽

Mineral Density ◽

Texture Measurement ◽

X Ray ◽

Spinal Radiograph ◽

And Gender

ObjectiveIn primary hyperparathyroidism (PHPT), vertebral fractures (VFx) occur regardless of bone mineral density (BMD) and may depend on decreased bone quality. Trabecular bone score (TBS) is a texture measurement acquired during a spinal dual-energy X-ray absorptiometry (DXA). Recently, TBS has been proposed as an index of bone micro-architecture.DesignWe studied 92 PHPT patients (74 females, age 62.1±9.7 years) and 98 control subjects. In all patients at baseline, in 20 surgically treated patients and in 10 conservatively treated patients after 24 months, TBS, spinal (lumbar spine (LS)) and femoral (total hip (TH) and femoral neck (FN)) BMD were assessed by DXA and VFx by spinal radiograph.ResultsPHPT patients had lower TBS (−2.39±1.8) and higher VFx prevalence (43.5%) than controls (−0.98±1.07 and 8.2% respectively, bothP<0.0001). TBS was associated with VFx (odds ratio 1.4, 95% CI 1.1–1.9,P=0.02), regardless of LS-BMD, age, BMI and gender, and showed a better compromise between sensitivity (75%) and specificity (61.5%) for detecting VFx than LS-BMD, TH-BMD and FN-BMD (31 and 75%, 72 and 44.2%, and 64 and 65% respectively). In surgically treated patients, TBS, LS-BMD, TH-BMD and FN-BMD increased (+47±44.8,+29.2±34.1,+49.4±48.7 and +30.2±39.3% respectively, allP<0.0001). Among patients treated conservatively, TBS decreased significantly in those (n=3) with incident VFx (−1.3±0.3) compared with those without (−0.01±0.9,P=0.048), while BMD changes were not statistically different (LS 0.3±1.2 vs −0.8±0.9 respectively,P=0.19; TH 0.4±0.8 vs −0.8±1.4 respectively,P=0.13 and FN 0.4±0.9 vs −0.8±1.4 respectively,P=0.14).ConclusionsIn PHPT, bone quality, as measured by TBS, is reduced and associated with VFx and improves after surgery.

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Bone quality, as measured by trabecular bone score (TBS), in patients with primary hyperparathyroidism

Endocrine Abstracts ◽

10.1530/endoabs.32.p74 ◽

2013 ◽

Author(s):

Cristina Eller-Vainicher ◽

Marcello Filopanti ◽

Serena Palmieri ◽

Fabio Massimo Ulivieri ◽

Valentina Morelli ◽

...

Keyword(s):

Primary Hyperparathyroidism ◽

Trabecular Bone ◽

Bone Quality ◽

Trabecular Bone Score

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Bone Mineral Density Compared to Trabecular Bone Score in Primary Hyperparathyroidism

Journal of Clinical Medicine ◽

10.3390/jcm11020330 ◽

2022 ◽

Vol 11 (2) ◽

pp. 330

Author(s):

Alicia R. Jones ◽

Koen Simons ◽

Susan Harvey ◽

Vivian Grill

Keyword(s):

Bone Mineral Density ◽

Lumbar Spine ◽

Primary Hyperparathyroidism ◽

Fracture Risk ◽

Trabecular Bone ◽

Bone Quality ◽

Bone Mineral ◽

Trabecular Bone Score ◽

Statistical Significance ◽

Mineral Density

Individuals with primary hyperparathyroidism (PHPT) have reduced bone mineral density (BMD) according to dual X-ray absorptiometry at cortical sites, with relative sparing of trabecular BMD. However, fracture risk is increased at all sites. Trabecular bone score (TBS) may more accurately describe their bone quality and fracture risk. This study compared how BMD and TBS describe bone quality in PHPT. We conducted a retrospective cross-sectional study with a longitudinal component, of adults with PHPT, admitted to a tertiary hospital in Australia over ten years. The primary outcome was the TBS at the lumbar spine, compared to BMD, to describe bone quality and predict fractures. Secondary outcomes compared changes in TBS after parathyroidectomy. Of 68 included individuals, the mean age was 65.3 years, and 79% were female. Mean ± SD T-scores were −1.51 ± 1.63 at lumbar spine and mean TBS was 1.19 ± 0.12. Only 20.6% of individuals had lumbar spine BMD indicative of osteoporosis, while 57.4% of TBS were ≤1.20, indicating degraded architecture. There was a trend towards improved fracture prediction using TBS compared to BMD which did not reach statistical significance. Comparison of 15 individuals following parathyroidectomy showed no improvement in TBS.

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Bone strain index as a predictor of further vertebral fracture in osteoporotic women: An artificial intelligence-based analysis

PLoS ONE ◽

10.1371/journal.pone.0245967 ◽

2021 ◽

Vol 16 (2) ◽

pp. e0245967

Author(s):

Fabio Massimo Ulivieri ◽

Luca Rinaudo ◽

Luca Petruccio Piodi ◽

Carmelo Messina ◽

Luca Maria Sconfienza ◽

...

Keyword(s):

Artificial Intelligence ◽

Vertebral Fracture ◽

Fragility Fracture ◽

Bone Strain ◽

Spine Deformity ◽

Connectivity Map ◽

Strain Index ◽

X Ray ◽

Prospective Longitudinal

Background Osteoporosis is an asymptomatic disease of high prevalence and incidence, leading to bone fractures burdened by high mortality and disability, mainly when several subsequent fractures occur. A fragility fracture predictive model, Artificial Intelligence-based, to identify dual X-ray absorptiometry (DXA) variables able to characterise those patients who are prone to further fractures called Bone Strain Index, was evaluated in this study. Methods In a prospective, longitudinal, multicentric study 172 female outpatients with at least one vertebral fracture at the first observation were enrolled. They performed a spine X-ray to calculate spine deformity index (SDI) and a lumbar and femoral DXA scan to assess bone mineral density (BMD) and bone strain index (BSI) at baseline and after a follow-up period of 3 years in average. At the end of the follow-up, 93 women developed a further vertebral fracture. The further vertebral fracture was considered as one unit increase of SDI. We assessed the predictive capacity of supervised Artificial Neural Networks (ANNs) to distinguish women who developed a further fracture from those without it, and to detect those variables providing the maximal amount of relevant information to discriminate the two groups. ANNs choose appropriate input data automatically (TWIST-system, Training With Input Selection and Testing). Moreover, we built a semantic connectivity map usingthe Auto Contractive Map to provide further insights about the convoluted connections between the osteoporotic variables under consideration and the two scenarios (further fracture vs no further fracture). Results TWIST system selected 5 out of 13 available variables: age, menopause age, BMI, FTot BMC, FTot BSI. With training testing procedure, ANNs reached predictive accuracy of 79.36%, with a sensitivity of 75% and a specificity of 83.72%. The semantic connectivity map highlighted the role of BSI in predicting the risk of a further fracture. Conclusions Artificial Intelligence is a useful method to analyse a complex system like that regarding osteoporosis, able to identify patients prone to a further fragility fracture. BSI appears to be a useful DXA index in identifying those patients who are at risk of further vertebral fractures.

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