SKELETAL HEALTH ASSESSMENT IN BRAZILIAN MEN WITH CELIAC DISEASE AT DIAGNOSIS: HOW IMPORTANT IS IT?

BACKGROUND: Low bone mass density (BMD) is an extraintestinal finding in celiac disease (CD). This may result in bone fractures leading to loss in quality of life. OBJECTIVE: To assess BMD in male CD patients at diagnosis according to the patient's age. METHODS: Descriptive retrospective carried out during the period between 2013 and 2023 in a single office that studied dual-energy X-ray absorptiometry (DXA) results in 28 male patients with a recent diagnosis of CD, divided into three groups: group 1 (age up to 18 years); group 2 (from 19 to 49 years of age) and group 3 (over 50 years of age). Were studied demographic and anthropometric parameters, time delay between symptoms onset and CD diagnosis and fracture occurrence. RESULTS: Celiac patients studied had median age 36.0 years (IQR=16.5-50.7). Among them, 39.3% had osteopenia and 14.3% had osteoporosis. Only 36% of the sample had normal DXA values (group 1 with 37.5%; group 2 with 46% and group 3 with 14.2%). No pathological fracture was observed in this sample. CD diagnosis delay observed had median 1.0 year (IQR=1.0-4.7). When the number of individuals with normal and abnormal DXA results were compared, there was no difference in body mass index, time of diagnosis delay or Marsh classification (P=0.18). CONCLUSION: Male patients at the time of CD diagnosis showed a high prevalence of low BMD, which was particularly evident in individuals over 50 years of age.

Guidelines for fracture risk assessment and management of osteoporosis in postmenopausal women and men above the age of 50 in Qatar.

We present comprehensive guidelines for osteoporosis management in Qatar. Formulated by the Qatar Osteoporosis Association, the guidelines recommend the age-dependent Qatar fracture risk assessment tool for screening, emphasizing risk-based treatment strategies and discouraging routine dual-energy X-ray scans. They offer a vital resource for physicians managing osteoporosis and fragility fractures nationwide. PURPOSE: Osteoporosis and related fragility fractures are a growing public health issue with an impact on individuals and the healthcare system. We aimed to present guidelines providing unified guidance to all healthcare professionals in Qatar regarding the management of osteoporosis. METHODS: The Qatar Osteoporosis Association formulated guidelines for the diagnosis and management of osteoporosis in postmenopausal women and men above the age of 50. A panel of six local rheumatologists who are experts in the field of osteoporosis met together and conducted an extensive review of published articles and local and international guidelines to formulate guidance for the screening and management of postmenopausal women and men older than 50 years in Qatar. RESULTS: The guidelines emphasize the use of the age-dependent hybrid model of the Qatar fracture risk assessment tool for screening osteoporosis and risk categorization. The guidelines include screening, risk stratification, investigations, treatment, and monitoring of patients with osteoporosis. The use of a dual-energy X-ray absorptiometry scan without any risk factors is discouraged. Treatment options are recommended based on risk stratification. CONCLUSION: Guidance is provided to all physicians across the country who are involved in the care of patients with osteoporosis and fragility fractures.

Semi-automatic proximal humeral trabecular bone density assessment tool: technique application and clinical validation.

PURPOSE: This study aimed to apply a newly developed semi-automatic phantom-less QCT (PL-QCT) to measure proximal humerus trabecular bone density based on chest CT and verify its accuracy and precision. METHODS: Subcutaneous fat of the shoulder joint and trapezius muscle were used as calibration references for PL-QCT BMD measurement. A self-developed algorithm based on a convolution map was utilized in PL-QCT for semi-automatic BMD measurements. CT values of ROIs used in PL-QCT measurements were directly used for phantom-based quantitative computed tomography (PB-QCT) BMD assessment. The study included 376 proximal humerus for comparison between PB-QCT and PL-QCT. Two sports medicine doctors measured the proximal humerus with PB-QCT and PL-QCT without knowing each other's results. Among them, 100 proximal humerus were included in the inter-operative and intra-operative BMD measurements for evaluating the repeatability and reproducibility of PL-QCT and PB-QCT. RESULTS: A total of 188 patients with 376 shoulders were involved in this study. The consistency analysis indicated that the average bias between proximal humerus BMDs measured by PB-QCT and PL-QCT was 1.0 mg/cc (agreement range - 9.4 to 11.4; P > 0.05, no significant difference). Regression analysis between PB-QCT and PL-QCT indicated a good correlation (R-square is 0.9723). Short-term repeatability and reproducibility of proximal humerus BMDs measured by PB-QCT (CV: 5.10% and 3.41%) were slightly better than those of PL-QCT (CV: 6.17% and 5.64%). CONCLUSIONS: We evaluated the bone quality of the proximal humeral using chest CT through the semi-automatic PL-QCT system for the first time. Comparison between it and PB-QCT indicated that it could be a reliable shoulder BMD assessment tool with acceptable accuracy and precision. This study developed and verify a semi-automatic PL-QCT for assessment of proximal humeral bone density based on CT to assist in the assessment of proximal humeral osteoporosis and development of individualized treatment plans for shoulders.

Assessment of Osteoporosis at the Lumbar Spine Using Ultrashort Echo Time Magnetization Transfer (UTE-MT) MRI.

BACKGROUND: Bone collagen-matrix contributes to the mechanical properties of bone by imparting tensile strength and elasticity, which can be indirectly quantified by ultrashort echo time magnetization transfer ratio (UTE-MTR) to assess osteoporosis. PURPOSE: To evaluate osteoporosis at the human lumbar spine using UTE-MTR. STUDY TYPE: Prospective. POPULATION: One hundred forty-eight-volunteers (age-range, 50-85; females, N = 90), including 81-normal bone density, 35-osteopenic, and 32-osteoporotic subjects. Ten additional healthy volunteers were recruited to study the intrasession reproducibility of the UTE-MT. FIELD STRENGTH/SEQUENCE: 3T/UTE-MT, short repetition-time adiabatic inversion recovery prepared UTE (STAIR-UTE), and iterative decomposition of water-and-fat with echo-asymmetry and least-squares estimation (IDEAL-IQ). ASSESSMENT: Fracture risk was calculated using Fracture-Risk-Assessment-Tool (FRAX). Region-of-interests (ROIs) were delineated on the trabecular area in the maps of bone-mineral-density, UTE-MTR, collagen-bound water proton-fraction (CBWPF), and bone-marrow fat fraction (BMFF). STATISTICAL TESTS: Linear-regression and Bland-Altman analysis were performed to assess the reproducibility of UTE-MTR measurements in the different scans. UTE-MTR and BMFF were correlated with bone-mineral-density using Pearson's regression and with FRAX scores using nonlinear regression. The abilities of UTE-MTR, CBWPF, and BMFF to discriminate between the three patient subgroups were evaluated using receiver-operator-characteristic (ROC) analysis and area-under-the-curve (AUC). Decision-curve-analysis (DCA) and clinical-impact curves were used to evaluate the value of UTE-MTR in clinical diagnosis. The DeLong test was used to compare the ROC curves. P-value <0.05 was considered statistically significant. RESULTS: Excellent reproducibility was obtained for the UTE-MT measurements. UTE-MTR strongly correlated with bone-mineral-density (r = 0.76) and FRAX scores (r = -0.77). UTE-MTR exhibited higher AUCs (≥0.723) than BMFF, indicating its superior ability to distinguish between the three patient subgroups. The DCA and clinical-impact curves confirmed the diagnostic value of UTE-MTR. UTE-MTR and CBWPF showed similar performance in correlation with bone-mineral-density and cohort classification. DATA CONCLUSION: UTE-MTR strongly correlates with bone-mineral-density and FRAX and shows great potential in distinguishing between normal, osteopenic, and osteoporotic subjects. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

Radiographic Assessment of Bone Quality Using 4 Radiographic Indexes: Canal Diaphysis Ratio Is Superior.

BACKGROUND: Osteoporosis increases the risk of periprosthetic fracture and loosening in hip arthroplasty. Many methods have been proposed to assess bone quality in X-rays, including both qualitative such as the Dorr classification and quantitative such as the Calcar-Canal Ratio (CCR) and Cortical-Thickness index/Canal-Bone ratio (CTI/CBR). The Canal-Diaphysis ratio (CDR) has been described as a predictor for hip fragility fractures; however, its relationship with bone mineral density (BMD) has not been described. The purpose of this study was to evaluate the correlation of the Dorr classification, CCR, CTI/CBR, and CDR with BMD of the proximal femur in patients without hip fracture. METHODS: Forty-seven patients over 45 years of age who had less than 6 months between radiographs and dual-energy X-ray absorptiometry were evaluated. Measurements of CCR, CBR, CDR, and Dorr classification were performed in all radiographs by 2 independent observers. RESULTS: The CDR had a high correlation (r = 0.74, P=<0.01) with BMD, whereas the CTI/CBR had a moderate correlation (r = 0.49, P=<0.01), and the CCR had no correlation with BMD (r = 0.06, P = .96). When evaluating the receiver operating characteristic curve, CDR showed the best performance (area under curve [AUC] = 0.75) followed by CBR (AUC = 0.73) and CCR (AUC = 0.61). The optimal cutoff value for the CDR was 0.49, with 100% sensitivity and 58% specificity. The inter- and intra-observer variability was good for all methods. No differences were found between Dorr classification of patients who had or did not have osteoporosis. CONCLUSION: Of all the analyzed methods, the CDR was found to have the best correlation with BMD. This study proposes the use of CDR as a tool for assessing bone quality when deciding the implant fixation method in hip arthroplasty.

Combining Deep Learning and Radiomics for Automated, Objective, Comprehensive Bone Mineral Density Assessment From Low-Dose Chest Computed Tomography.

RATIONALE AND OBJECTIVES: To develop an intelligent diagnostic model for osteoporosis screening based on low-dose chest computed tomography (LDCT). The model incorporates automatic deep-learning thoracic vertebrae of cancellous bone (TVCB) segmentation model and radiomics analysis. MATERIALS AND METHODS: A total of 442 participants who underwent both LDCT and quantitative computed tomography (QCT) examinations were enrolled and were randomly allocated to the training, internal testing, and external testing cohorts. The TVCB automatic segmentation model was trained using VB-Net. The accuracy of the segmentation was evaluated using the Dice coefficient. Predictive models for assessing bone mineral density (BMD) were constructed utilizing radiomics analysis based on automatic segmentation (ASeg model) and manual segmentation (MSeg model), respectively. The BMD predictive model based on ASeg and MSeg included the identification of normal and abnormal BMD (first-level model), and osteopenia and osteoporosis (second-level model). The diagnostic performance of the radiomics models were evaluated using the area under the curve (AUC), sensitivity and specificity. RESULTS: The Dice coefficients of the TVCB segmentation model in the internal and external testing cohorts were found to be 0.988 ± 0.014 and 0.939 ± 0.034, respectively. In the first-level model, the AUC of the ASeg model exhibited comparable performance to that of the MSeg model for both the internal (0.985 vs. 0.946, P = 0.080) and external (0.965 vs. 0.955, P = 0.724) testing cohorts. Similarly, in the second-level model, the AUC of the ASeg model was found to be comparable to that of the MSeg model for both the internal (0.933 vs. 0.920, P = 0.794) and external (0.907 vs. 0.892, P = 0.805) testing cohorts. CONCLUSION: A fully automated pipeline for TVCB segmentation and BMD assessment with radiomics analysis can be used for opportunistic BMD screening in chest LDCT.

Clinical Outcomes and Cost-Effectiveness of Osteoporosis Screening With Dual-Energy X-ray Absorptiometry.

OBJECTIVE: This study aimed to evaluate the clinical outcomes and cost-effectiveness of dual-energy X-ray absorptiometry (DXA) for osteoporosis screening. MATERIALS AND METHODS: Eligible patients who had and had not undergone DXA screening were identified from among those aged 50 years or older at Kaohsiung Veterans General Hospital, Taiwan. Age, sex, screening year (index year), and Charlson comorbidity index of the DXA and non-DXA groups were matched using inverse probability of treatment weighting (IPTW) for propensity score analysis. For cost-effectiveness analysis, a societal perspective, 1-year cycle length, 20-year time horizon, and discount rate of 2% per year for both effectiveness and costs were adopted in the incremental cost-effectiveness (ICER) model. RESULTS: The outcome analysis included 10337 patients (female:male, 63.8%:36.2%) who were screened for osteoporosis in southern Taiwan between January 1, 2012, and December 31, 2021. The DXA group had significantly better outcomes than the non-DXA group in terms of fragility fractures (7.6% vs. 12.5%, P < 0.001) and mortality (0.6% vs. 4.3%, P < 0.001). The DXA screening strategy gained an ICER of US$ -2794 per quality-adjusted life year (QALY) relative to the non-DXA at the willingness-to-pay threshold of US$ 33004 (Taiwan's per capita gross domestic product). The ICER after stratifying by ages of 50-59, 60-69, 70-79, and ≥ 80 years were US$ -17815, US$ -26862, US$ -28981, and US$ -34816 per QALY, respectively. CONCLUSION: Using DXA to screen adults aged 50 years or older for osteoporosis resulted in a reduced incidence of fragility fractures, lower mortality rate, and reduced total costs. Screening for osteoporosis is a cost-saving strategy and its effectiveness increases with age. However, caution is needed when generalizing these cost-effectiveness results to all older populations because the study population consisted mainly of women.

CT and MR for bone mineral density and trabecular bone score assessment in osteoporosis evaluation.

Dual energy X-ray absorptiometry (DXA) is widely used modality for measuring bone mineral density (BMD). DXA is used to measure the quantitative areal BMD of bone, but has the disadvantage of not reflecting the bone architecture. To compensate for this disadvantage, trabecular bone score (TBS), a qualitative parameter of trabecular microarchitecture, is used. Meanwhile, there have been recent attempts to diagnose osteoporosis using the Hounsfield unit (HU) from CT and MR-based proton density fat fraction (PDFF) measurements. In our study, we aimed to find out the correlation between HU/PDFF and BMD/TBS, and whether osteoporosis can be diagnosed through HU/PDFF. Our study revealed that the HU value showed a moderate to good positive correlation with BMD and TBS. PDFF showed a fair negative correlation with BMD and TBS. In diagnosing osteopenia and osteoporosis, the HU value showed good performance, whereas the PDFF showed fair performance. In conclusion, both HU values and PDFF can play a role in predicting BMD and TBS. Both HU values and PDFF can be used to predict osteoporosis; further, CT is expected to show better results.

Performance of iCare quantitative computed tomography in bone mineral density assessment of the hip and vertebral bodies in European spine phantom.

BACKGROUND: Osteoporosis is a systemic bone disease which can increase the risk of osteoporotic fractures. Dual-energy X-ray absorptiometry (DXA) is considered as the clinical standard for diagnosing osteoporosis by detecting the bone mineral density (BMD) in patients, but it has flaws in distinguishing between calcification and other degenerative diseases, thus leading to inaccurate BMD levels in subjects. Mindways quantitative computed tomography (Mindways QCT) is a classical QCT system. Similar to DXA, Mindways QCT can directly present the density of trabecular bone, vascular or tissue calcification; therefore, it is more accurate and sensitive than DXA and has been widely applied in clinic to evaluate osteoporosis. iCare QCT osteodensitometry was a new phantom-based QCT system, recently developed by iCare Inc. (China). It has been gradually applied in clinic by its superiority of taking 3-dimensional BMD of bone and converting BMD values to T value automatically. This study aimed at evaluating the osteoporosis detection rate of iCare QCT, compared with synchronous Mindways QCT (USA). METHODS: In this study, 131 patients who underwent hip phantom-based CT scan were included. Bone mineral density (BMD) of the unified region of interests (ROI) defined at the European spine phantom (ESP, German QRM) including L1 (low), L2 (medium), and L3 (high) vertebral bodies was detected for QCT quality control and horizontal calibration. Every ESP scan were taken for 10 times, and the mean BMD values measured by iCare QCT and Mindways QCT were compared. Hip CT scan was conducted with ESP as calibration individually. T-scores gained from iCare QCT and Mindways QCT were analyzed with Pearson correlation test. The detection rates of osteoporosis were compared between iCare QCT and Mindways QCT. The unified region of interests (ROI) was delineated in the QCT software. RESULTS: The results showed that there was no significant difference between iCare QCT and Mindways QCT in the evaluation of L1, L2, and L3 vertebrae bodies in ESP. A strong correlation between iCare QCT and Mindways QCT in the assessment of hip T-score was found. It was illustrated that iCare QCT had a higher detection rate of osteoporosis with the assessment of hip T-score than Mindways QCT did. In patients < 50 years subgroup, the detection rate of osteoporosis with iCare QCT and Mindways QCT was equal. In patients ≥ 50 years subgroup, the detection rate of osteoporosis with iCare QCT (35/92, 38.0%) was higher than that with Mindways QCT. In female subgroup, the detection rate of osteoporosis with iCare QCT was significantly higher than Mindways QCT. In male subgroup, the detection rate of osteoporosis with iCare QCT was also markedly higher than Mindways QCT. The detection rate of osteoporosis by iCare QCT was higher than Mindways QCT with hip bone assessment. Of course, the results of the present study remain to be further verified by multicenter studies in the future.

Combinations of two imaging parameters to improve bone mineral density (BMD) assessment in patients with lumbar degenerative diseases.

PURPOSE: To explore whether combining the Hounsfield unit (HU) values and vertebral bone quality (VBQ) scores can improve the BMD assessment in patients with lumbar degenerative diseases. METHODS: The HU values were measured by CT image, and VBQ scores were calculated by lumbar MRI image. The correlations of the opportunistic imaging parameters to the lowest T-scores were analyzed. Receiver-operating characteristic curve (ROC) analysis was used to evaluate the accuracy in detecting osteoporosis. Finally, the specificity and sensitivity of different combined methods of the HU values and VBQ scores in the diagnosis of osteoporosis were compared. RESULTS: Patients with osteoporosis had the lowest HU values and the highest VBQ scores. The correlation coefficients between the VBQ scores and the T-scores were smaller than HU values (L1 HU value: 0.702; average HU value:0.700; L1 VBQ score: -0.413; VBQ score: -0.386). The areas under the curve (AUCs) of the HU values were greater than those of the VBQ scores, and the AUCs of the L1 VBQ score were similar to the VBQ score (L1 HU value: 0.850; average HU value:0.857; L1 VBQ score: 0.704; VBQ score: 0.673). When combining the two imaging parameters in series, the specificity of the detection of osteoporosis was improved (L1 HU value and L1 VBQ score: 87.3%; Average HU value and VBQ score: 85.9%). When combining the two imaging parameters in parallel, the sensitivity of the detection of osteoporosis was improved (L1 HU value or L1 VBQ score: 88.1%; Average HU value or VBQ score: 91.5%). CONCLUSIONS: Combinations of the HU values and VBQ scores could improve the diagnostic performance of osteoporosis. In addition, considering the same diagnostic performance but easier measurement, parameters at the single-segment level were recommended to assist in the diagnosis of osteoporosis.

Toward the use of MRI measurements of bound and pore water in fracture risk assessment.

The current clinical assessment of fracture risk lacks information about the inherent quality of a person's bone tissue. Working toward an imaging-based approach to quantify both a bone tissue quality marker (tissue hydration as water bound to the matrix) and a bone microstructure marker (porosity as water in pores), we hypothesized that the concentrations of bound water (Cbw) are lower and concentrations of pore water (Cpw) are higher in patients with osteoporosis (OP) than in age- and sex-matched adults without the disease. Using recent developments in ultrashort echo time (UTE) magnetic resonance imaging (MRI), maps of Cbw and Cpw were acquired from the uninjured distal third radius (Study 1) of 20 patients who experienced a fragility fracture of the distal radius (Fx) and 20 healthy controls (Non-Fx) and from the tibia mid-diaphysis (Study 2) of 30 women with clinical OP (low T-scores) and 15 women without OP (normal T-scores). In Study 1, Cbw was significantly lower (p = 0.0018) and Cpw was higher (p = 0.0022) in the Fx than in the Non-Fx group. In forward stepwise, logistic regression models using Bayesian Information Criterion for selecting the best set of predictors (from imaging parameters, age, BMI, and DXA scanner type), the area-under-the-receiver operator characteristics-curve (AUC with 95 % confidence intervals) was 0.73 (0.56, 0.86) for hip aBMD (best predictors without MRI) and 0.86 (0.70, 0.95) for the combination of Cbw and Cpw (best predictors overall). In Study 2, Cbw was significantly lower (p = 0.0005) in women with OP (23.8 ± 4.3 1H mol/L) than in women without OP (29.9 ± 6.4 1H mol/L); Cpw was significantly higher by estimate of 2.9 1H mol/L (p = 0.0298) with clinical OP, but only when accounting for the type of UTE-MRI scan with 3D providing higher values than 2D (p < 0.0001). Lastly, Cbw, but not Cpw, was sensitive to bone forming osteoporosis medications over 12-months. UTE-MRI-derived measurements of bound and pore water concentrations are potential, aBMD-independent predictors of fracture risk.

Cost-effectiveness of opportunistic QCT-based osteoporosis screening for the prediction of incident vertebral fractures.

Objectives: Opportunistic quantitative computed tomography (oQCT) derived from non-dedicated routine CT has demonstrated high accuracy in diagnosing osteoporosis and predicting incident vertebral fractures (VFs). We aimed to investigate the cost-effectiveness of oQCT screening compared to dual-energy X-ray absorptiometry (DXA) as the standard of care for osteoporosis screening. Methods: Three screening strategies ("no osteoporosis screening", "oQCT screening", and "DXA screening") after routine CT were simulated in a state-transition model for hypothetical cohorts of 1,000 patients (women and men aged 65 years) over a follow-up period of 5 years (base case). The primary outcomes were the cumulative costs and the quality-adjusted life years (QALYs) estimated from a U.S. health care perspective for the year 2022. Cost-effectiveness was assessed based on a willingness-to-pay (WTP) threshold of $70,249 per QALY. The secondary outcome was the number of prevented VFs. Deterministic and probabilistic sensitivity analyses were conducted to test the models' robustness. Results: Compared to DXA screening, oQCT screening increased QALYs in both sexes (additional 2.40 per 1,000 women and 1.44 per 1,000 men) and resulted in total costs of $3,199,016 and $950,359 vs. $3,262,934 and $933,077 for women and men, respectively. As a secondary outcome, oQCT screening prevented 2.6 and 2.0 additional VFs per 1,000 women and men, respectively. In the probabilistic sensitivity analysis, oQCT screening remained cost-effective in 88.3% (women) and 90.0% (men) of iterations. Conclusion: oQCT screening is a cost-effective ancillary approach for osteoporosis screening and has the potential to prevent a substantial number of VFs if considered in daily clinical practice.

Cost-Effectiveness of Osteoporosis Opportunistic Screening Using Computed Tomography in China.

OBJECTIVES: Underutilization and insufficient availability of dual-energy X-ray absorptiometry (DXA) in diagnosing osteoporosis in China could be changed by adopting unindicated quantitative computed tomography. We aimed to assess the cost-effectiveness of quantitative computed tomography (QCT) as a screening tool for osteoporosis in China. METHODS: A Markov microsimulation model was developed to assess the long-term costs and quality-adjusted life-years (QALYs) saved associated with 2 examinations as opportunistic screening for osteoporosis in a general population without prior histories of fracture. The diagnostic performance of both examinations was incorporated into the model. In lifetime modeling, opportunistically screened people may face the risk of experiencing hip, vertebral, and wrist fractures depending on their osteoporosis, age, and sex. Model parameters were informed by published literature. RESULTS: The base-case result showed that QCT was associated with higher costs ($6054 vs $5883) and higher benefits (10.081 vs 10.071 QALYs) in comparison with DXA, making QCT a cost-effective option for opportunistic screening (incremental cost-effectiveness ratio of US $16 430/QALY). Screening with QCT led to fewer fractures over the lifetime simulation: for every 10 000 people screened, 129 fractures (32 hip, 78 vertebral, and 19 wrist fractures) could be avoided because of the early initiation of antiosteoporotic treatment. CONCLUSIONS: Using QCT to screen people for osteoporosis is more cost-effective than standard practice in China, where access to DXA is minimal. This finding could support opportunistic osteoporosis screening using QCT in other countries with similar status.

Novel techniques for assessment of bone tissue material properties.

PURPOSE OF REVIEW: The purpose of this review will be to shed light on novel techniques for assessment of bone tissue material properties. RECENT FINDINGS: Recently there has been an increase in modalities to investigate bone tissue material properties. Historically, clinicians treating patients with bone disorders have relied upon the use of bone mineral density (BMD) as assessed by dual-energy X-ray absorptiometry (DXA). Although DXA provides an ability to screen at a large-scale population level, it only explains about 60% of the fracture risk. Recent advances include the use of imaging modalities, responses to load, and novel infrared (IR) techniques. SUMMARY: These newer techniques have not reached a point for population level screening; however, they may inform the science of bone biology further and help discern various bone disease states.

What is the role of CT-based Hounsfield unit assessment in the evaluation of bone mineral density in patients undergoing 1- or 2-level lumbar spinal fusion for degenerative spinal pathologies? A prospective study.

BACKGROUND CONTEXT: Computed tomography-based vertebral attenuation values (CT-based HU) have been shown to correlate with T-scores on DEXA scan; and have been acknowledged as an independent factor for predicting fragility fractures. Most patients undergoing lumbar surgeries require CT as part of their preoperative evaluation. PURPOSE: The current study was thus planned to evaluate the role of lumbar CT as an opportunistic investigation in determining BMD preoperatively in patients undergoing lumbar fusion. STUDY DESIGN: Prospective cohort study. PATIENT SAMPLE: Patients older than 45 years, who underwent one- to two-level lumbar (L3-S1 levels) fusions. OUTCOME MEASURES: Comparison of the quantitative assessment of osteoporosis using Hounsfield Units (HU) on CT (L1-L5) and mean lumbar T-scores on DEXA (Dual Energy X-ray Absorptiometry). HYPOTHESIS: HU on CT is comparable to T-score on DEXA as a suitable modality for the assessment of osteoporosis in patients undergoing one- to two-level lumbar fusion. METHODS: A prospective cohort study was conducted between January and December 2021. Patients older than 45 years, who underwent one- to two-level lumbar (L3-S1 levels) fusions and had complete clinico-radiological records, were prospectively enrolled. A comparison was drawn between the HU (measured by placing an oval region of interest [ROI] over axial, sagittal and coronal images of lumbar vertebrae) on CT and T-scores on DEXA, and analyzed statistically. The HU values correlating best with normal (group A), osteopenia (B) and osteoporosis (C) categories (classified based on T-scores of lumbar spines) were determined statistically. RESULTS: Overall, 87 patients (mean age of 60.56±11.63 years; 63 [72.4%] female patients) were prospectively studied. There was a statistically significant difference in the mean age (p=.01) and sex distribution (predominantly female patients; p=.03) of patients belonging to groups B (osteopenic) and C (osteoporotic patients), as compared with group A. The greatest correlation between T-score (on DEXA) and HU (on CT) for differentiating osteopenia (group B) from group A was observed at levels L1 (p<.001), L2 (p<.001) and L3 (p<.001). Based on receiver-operating characteristic (ROC) curve analysis, the cut-off values for HU for identifying osteopenia were 159 (at L1; sensitivity 81.6 and specificity 80) and 162 (at L2; sensitivity 80 and specificity 71.1). In addition, there was statistically significant correlation between T-score (on DEXA) and HU at all the lumbar levels for distinguishing osteoporosis (group C), although the difference was most evident at the upper lumbar (L1 and L2) levels (p<.001). Based on ROC analysis, cut-off HU values for defining osteoporosis were 127 (at L1; sensitivity 71.3 and specificity 70) and 117 (at L2; sensitivity 65.5 and specificity 90). CONCLUSION: Based on our study, the measurement of HU on CT at upper lumbar levels can be considered as "surrogate marker" for BMD in the diagnosis of osteopenia (cut-off: 159 at L1, 162 at L2) and osteoporosis (cut-off: 127 at L1, 117 at L2) in patients undergoing lumbar fusion surgeries. The HU measurements on CT at the lower lumbar levels (L4 and L5) are less reliable in this preoperative scenario.

Feasibility of Bone Mineral Density and Bone Microarchitecture Assessment Using Deep Learning With a Convolutional Neural Network.

OBJECTIVES: We evaluated the feasibility of using deep learning with a convolutional neural network for predicting bone mineral density (BMD) and bone microarchitecture from conventional computed tomography (CT) images acquired by multivendor scanners. METHODS: We enrolled 402 patients who underwent noncontrast CT examinations, including L1-L4 vertebrae, and dual-energy x-ray absorptiometry (DXA) examination. Among these, 280 patients (3360 sagittal vertebral images), 70 patients (280 sagittal vertebral images), and 52 patients (208 sagittal vertebral images) were assigned to the training data set for deep learning model development, the validation, and the test data set, respectively. Bone mineral density and the trabecular bone score (TBS), an index of bone microarchitecture, were assessed by DXA. BMDDL and TBSDL were predicted by deep learning with a convolutional neural network (ResNet50). Pearson correlation tests assessed the correlation between BMDDL and BMD, and TBSDL and TBS. The diagnostic performance of BMDDL for osteopenia/osteoporosis and that of TBSDL for bone microarchitecture impairment were evaluated using receiver operating characteristic curve analysis. RESULTS: BMDDL and BMD correlated strongly (r = 0.81, P < 0.01), whereas TBSDL and TBS correlated moderately (r = 0.54, P < 0.01). The sensitivity and specificity of BMDDL for identifying osteopenia or osteoporosis were 93% and 90%, and 100% and 94%, respectively. The sensitivity and specificity of TBSDL for identifying patients with bone microarchitecture impairment were 73% for all values. CONCLUSIONS: The BMDDL and TBSDL derived from conventional CT images could identify patients who should undergo DXA, which could be a gatekeeper tool for detecting latent osteoporosis/osteopenia or bone microarchitecture impairment.

Assessment of bone density using the 1.5 T or 3.0 T MRI-based vertebral bone quality score in older patients undergoing spine surgery: does field strength matter?

BACKGROUND CONTEXT: Recently published studies have revealed a correlation between MRI-based vertebral bone quality (VBQ) score and bone mineral density (BMD) measured using dual X-ray absorptiometry (DXA) or quantitative computed tomography (QCT). However, no studies have determined if differences in field strength (1.5 vs 3.0 T) could affect the comparability of the VBQ score among different individuals. PURPOSE: To compare the VBQ score obtained from 1.5 T and 3.0 T MRI (VBQ1.5T vs VBQ3.0T) in patients undergoing spine surgery and assess the predictive performance of VBQ for osteoporosis and osteoporotic vertebral fracture (VCF). DESIGN: A nested case‒control study based on an ongoing prospective cohort study of patients undergoing spine surgery. PATIENT SAMPLE: All older patients (men aged >60 years and postmenopausal women) with available DXA, QCT and MR images within 1 month were included. OUTCOME MEASURES: VBQ score, DXA T-score, and QCT derived vBMD. METHODS: The osteoporotic classifications recommended by the World Health Organization and American College of Radiology were used to categorize the DXA T-score and QCT-derived BMD, respectively. For each patient, the VBQ score was calculated using T1-weighted MR images. Correlation analysis between VBQ and DXA/QCT was performed. Receiver operating characteristic (ROC) curve analysis, including determination of the area under the curve (AUC), was performed to assess the predictive performance of VBQ for osteoporosis. RESULTS: A total of 452 patients (98 men aged >60 years and 354 postmenopausal women) were included in the analysis. Across different BMD categories, the correlation coefficients between the VBQ score and BMD ranged from -0.211 to -0.511, and the VBQ1.5T score and QCT BMD demonstrated the strongest correlation. The VBQ score was a significant classifier of osteoporosis detected by either DXA or QCT, with VBQ1.5T showing the highest discriminative power for QCT-osteoporosis (AUC=0.744, 95% CI=0.685-0.803). In ROC analysis, the VBQ1.5T threshold values ranged from 3.705 to 3.835 with a sensitivity between 48% and 55.6% and a specificity between 70.8% and 74.8%, while the VBQ3.0T threshold values ranged from 2.59 to 2.605 with a sensitivity between 57.6% and 67.1% and a specificity between 67.8% and 69.7%. CONCLUSIONS: VBQ1.5T exhibited better discriminability between patients with and without osteoporosis than VBQ3.0T. Considering the non-negligible difference in osteoporosis diagnosis threshold values between the VBQ1.5T and VBQ3.0T scores, it is essential to clearly distinguish the magnetic field strength when assessing the VBQ score.

Correlation of R2* with fat fraction and bone mineral density and its role in quantitative assessment of osteoporosis.

OBJECTIVES: To investigate the correlation of R2* with vertebral fat fraction (FF) and bone mineral density (BMD), and to explore its role in the quantitative assessment of osteoporosis (OP). METHODS: A total of 83 patients with low back pain (59.77 ± 7.46 years, 30 males) were enrolled, which underwent lumbar MRI in IDEAL-IQ sequences and quantitative computed tomography (QCT) scanning within 48h. The FF, R2*, and BMD of all 415 lumbar vertebrae were respectively measured. According to BMD, all vertebrae were divided into BMD normal, osteopenia, and OP groups, and the difference of FF and R2* among groups was analyzed by one-way ANOVA. The correlation between R2*, FF, and BMD was analyzed by Pearson's test. Taking BMD as the gold standard, the efficacies for FF and R2* in diagnosis of OP and osteopenia were assessed by receiver operating characteristic curve, and their area under the curve (AUC) was compared with DeLong's test. RESULTS: The FF and R2* were statistically different among groups (F values of 102.521 and 11.323, both p < 0.05), and R2* were significantly correlated with FF and BMD, respectively (r values of -0.219 and 0.290, both p < 0.05). In diagnosis of OP and osteopenia, the AUCs were 0.776 and 0.778 for FF and 0.638 and 0.560 for R2*, and the AUCs of R2* were lower than those of FF, with Z values of 4.030 and 4.087, both p < 0.001. CONCLUSION: R2* is significantly correlated with FF and BMD and can be used as a complement to FF and BMD for quantitative assessment of OP. KEY POINTS: • R2* based on IDEAL-IQ sequences has a definite but weak linear relationship with FF and BMD. • FF is significantly correlated with BMD and can effectively evaluate BMAT. • R2* can be used as a complement to FF and BMD for fine quantification of bone mineral loss and bone marrow fat conversion.

Discrepancy between DXA and CT-based assessment of spine bone mineral density.

PURPOSE: Adequate bone mineral density (BMD) is necessary for success in spine surgery. Dual-energy X-ray absorptiometry (DXA) is the gold standard in determining BMD but may give spuriously high values. Hounsfield units (HU) from computed tomography (CT) may provide a more accurate depiction of the focal BMD encountered during spine surgery. Our objective is to determine the discrepancy rate between DXA and CT BMD determinations and how often DXA overestimates BMD compared to CT. METHODS: We retrospectively reviewed 93 patients with both DXA and CT within 6 months. DXA lumbar spine and overall T scores were classified as osteoporotic (T Score ≤ - 2.5) or non-osteoporotic (T Score > -2.5). L1 vertebral body HU were classified as osteoporotic or non-osteoporotic using cutoff thresholds of either ≤ 135 HU or ≤ 110 HU. Corresponding DXA and HU classifications were compared to determine disagreement and overestimation rates. RESULTS: Using lumbar T scores, the CT vs DXA disagreement rate was 40-54% depending on the HU threshold. DXA overestimated BMD 97-100% of the time compared to CT. Using overall DXA T scores, the disagreement rate was 33-47% with DXA greater than CT 74-87% of the time. In the sub-cohort of 10 patients with very low HU (HU < 80), DXA overestimated BMD compared to CT in every instance. CONCLUSIONS: There is a large discrepancy between DXA and CT BMD determinations. DXA frequently overestimates regional BMD encountered during spine surgery compared with CT. While DXA remains the gold standard in determining BMD, CT may play an important role in defining the focal BMD pertinent to spine surgery.

Application of intelligent X-ray image analysis in risk assessment of osteoporotic fracture of femoral neck in the elderly.

The paper focuses on establishing a risk assessment model of femoral neck osteoporotic fracture (FNOF) in the elderly population and improving the screening efficiency and accuracy of such diseases in specific populations. In literature research, the main risk factors of femoral neck osteoporosis (FNOP) in the elderly were studied and analyzed; the femur region of interest (ROI) and the hard bone edge segmentation model were selected from the X-ray digital image by using the image depth learning method. On this basis, the femoral trabecular score and femoral neck strength (FNS) in the set region were selected as the main evaluation elements, and the quantitative analysis method was established; an X-ray image processing method was applied to the feasibility study of FNOP and compared with dual-energy X-ray absorptiometry measurements of bone mineral density; Finally, the main risk factors of FNOP were selected and the prediction model of FNOP in the elderly population was established based on medical image processing, machine learning model construction and other methods. Some FNOP health records were selected as test samples for comparative analysis with traditional manual evaluation methods. The paper shows the risk assessment model of FNOF in the elderly population, which is feasible in testing. Among them, the artificial neural network model had a better accuracy (95.83%) and recall rate (100.00%), and the support vector machine prediction model had high specificity (62.50%). With the help of a machine learning method to establish the risk assessment model of FNOF for the elderly, one can provide decision support for the fracture risk assessment of the elderly and remind the clinic to give targeted interventions for the above high-risk groups in order to reduce the fracture risk.