Improved prediction of incident vertebral fractures using opportunistic QCT compared to DXA

Dark-field radiography for the detection of bone microstructure changes in osteoporotic human lumbar spine specimens

BACKGROUND

Dark-field radiography imaging exploits the wave character of x-rays to measure small-angle scattering on material interfaces, providing structural information with low radiation exposure. We explored the potential of dark-field imaging of bone microstructure to improve the assessment of bone strength in osteoporosis.

METHODS

We prospectively examined 14 osteoporotic/osteopenic and 21 non-osteoporotic/osteopenic human cadaveric vertebrae (L2-L4) with a clinical dark-field radiography system, micro-computed tomography (CT), and spectral CT. Dark-field images were obtained in both vertical and horizontal sample positions. Bone microstructural parameters (trabecular number, Tb.N; trabecular thickness, Tb.Th; bone volume fraction, BV/TV; degree of anisotropy, DA) were measured using standard ex vivo micro-CT, while hydroxyapatite density was measured using spectral CT. Correlations were assessed using Spearman rank correlation coefficients.

RESULTS

The measured dark-field signal was lower in osteoporotic/osteopenic vertebrae (vertical position, 0.23 ± 0.05 versus 0.29 ± 0.04, p < 0.001; horizontal position, 0.28 ± 0.06 versus 0.34 ± 0.04, p = 0.003). The dark-field signal from the vertical position correlated significantly with Tb.N (ρ = 0.46, p = 0.005), BV/TV (ρ = 0.45, p = 0.007), DA (ρ = -0.43, p = 0.010), and hydroxyapatite density (ρ = 0.53, p = 0.010). The calculated ratio of vertical/horizontal dark-field signal correlated significantly with Tb.N (ρ = 0.43, p = 0.011), BV/TV (ρ = 0.36, p = 0.032), DA (ρ = -0.51, p = 0.002), and hydroxyapatite density (ρ = 0.42, p = 0.049).

CONCLUSION

Dark-field radiography is a feasible modality for drawing conclusions on bone microarchitecture in human cadaveric vertebral bone.

RELEVANCE STATEMENT

Gaining knowledge of the microarchitecture of bone contributes crucially to predicting bone strength in osteoporosis. This novel radiographic approach based on dark-field x-rays provides insights into bone microstructure at a lower radiation exposure than that of CT modalities.

KEY POINTS

Dark-field radiography can give information on bone microstructure with low radiation exposure. The dark-field signal correlated positively with bone microstructure parameters. Dark-field signal correlated negatively with the degree of anisotropy. Dark-field radiography helps to determine the directionality of trabecular loss.

Opportunistic Computed Tomography: A Novel Opportunity for Osteoporosis Screening

STUDY DESIGN

Retrospective review.

OBJECTIVE

To use opportunistic computed tomography (CT) screening to determine the prevalence of osteoporosis (OP) in patients presenting with spinal fractures and the rate of identification and treatment at our institution.

BACKGROUND

OP remains a highly underdiagnosed and undertreated disease. Opportunistic abdominopelvic CT scans offer a feasible, accessible, and cost-effective screening tool for OP.

METHODS

Retrospective review of 519 patients presenting as trauma activation to the emergency department of a Level 1 Trauma Center after a spinal fracture. Patients were excluded if under the age of 18 or lacking a CT scan upon arrival in the emergency department. Hounsfield Units (HU) were measured at the L1 vertebral level on CT scans to determine bone density levels. Values of ≤100 HU were considered osteoporotic, whereas 101-150 HU were osteopenic.

RESULTS

A total of 424 patients were included. The average HU was 204.8 ± 74.3 HU. Of the patients, 16.7% were diagnosed as osteopenic and 9.9% as osteoporotic. The mean age was 65 ± 14 years for osteopenic patients and 77 ± 11 years for osteoporotic. A statistically significant inverse relationship was found between age and bone density. Of the patients, 42.5% with low bone density HU measurements had a previously documented history of OP/osteopenia. There was a statistically significant association between females and low bone density. Patients injured in a fall were statistically significantly more likely to have lower bone densities than those in motor vehicle accidents. Of the osteoporotic patients, 9.5% were treated by our institution's fragility fracture team.

CONCLUSIONS

Our study shows that among a cohort of patients with spinal fractures, 58% of patients with radiographic signs of OP are currently undiagnosed, resulting in a low treatment rate of OP. Increasing and standardizing the use of opportunistic CT scans would allow an increase in the diagnosis and treatment of OP in patients with spinal fractures. Further, opportunistic CT scans could also be useful for a broader orthopedic population at high risk of fragility fractures.

LEVEL OF EVIDENCE

Level II-therapeutic.

Using QCT for the prediction of spontaneous age- and gender-specific thoracolumbar vertebral fractures and accompanying distant vertebral fractures

PURPOSE

To investigate the value and age- and gender-specific threshold values of bone mineral density (BMD) by quantitative computed tomography (QCT) for the prediction of spontaneous thoracolumbar vertebral fractures and thoracolumbar junction fractures accompanying distant vertebral fractures.

METHODS

Among the 556 patients included, 68 patients had thoracolumbar vertebral fractures (12 patients with distant vertebral fractures, 56 patients without distant vertebral fractures) and 488 patients had no vertebral fractures. All patients were grouped by gender and age. According to the principle of Youden index, the threshold values were calculated from receiver operating characteristic (ROC) curves.

RESULTS

The threshold values for predicting thoracolumbar vertebral fractures were 89.8 mg/cm3 for all subjects, 90.1 mg/cm3 for men, and 88.6 mg/cm3 for women. The threshold values for men aged < 60 years old and ≥ 60 years old were 117.4 mg/cm3 and 87.5 mg/cm3, respectively. The threshold values for women aged < 60 years old and ≥ 60 years old were 88.6 and 68.4 mg/cm3, respectively. The threshold value for predicting spontaneous thoracolumbar junction fractures with distant vertebral fractures was 62.7 mg/cm3.

CONCLUSIONS

QCT provides a good ability to predict age- and gender-specific spontaneous thoracolumbar vertebral fractures, and to further predict spontaneous thoracolumbar junction fractures with distant vertebral fractures.

Feasibility study of opportunistic osteoporosis screening on chest CT using a multi-feature fusion DCNN model

A multi-feature fusion DCNN model for automated evaluation of lumbar vertebrae L1 on chest combined with clinical information and radiomics permits estimation of volumetric bone mineral density for evaluation of osteoporosis.

PURPOSE

To develop a multi-feature deep learning model based on chest CT, combined with clinical information and radiomics to explore the feasibility in screening for osteoporosis based on estimation of volumetric bone mineral density.

METHODS

The chest CT images of 1048 health check subjects were retrospectively collected as the master dataset, and the images of 637 subjects obtained from a different CT scanner were used for the external validation cohort. The subjects were divided into three categories according to the quantitative CT (QCT) examination, namely, normal group, osteopenia group, and osteoporosis group. Firstly, a deep learning-based segmentation model was constructed. Then, classification models were established and selected, and then, an optimal model to build bone density value prediction regression model was chosen.

RESULTS

The DSC value was 0.951 ± 0.030 in the testing dataset and 0.947 ± 0.060 in the external validation cohort. The multi-feature fusion model based on the lumbar 1 vertebra had the best performance in the diagnosis. The area under the curve (AUC) of diagnosing normal, osteopenia, and osteoporosis was 0.992, 0.973, and 0.989. The mean absolute errors (MAEs) of the bone density prediction regression model in the test set and external testing dataset are 8.20 mg/cm3 and 9.23 mg/cm3, respectively, and the root mean square errors (RMSEs) are 10.25 mg/cm3 and 11.91 mg/cm3, respectively. The R-squared values are 0.942 and 0.923, respectively. The Pearson correlation coefficients are 0.972 and 0.965.

CONCLUSION

The multi-feature fusion DCNN model based on only the lumbar 1 vertebrae and clinical variables can perform bone density three-classification diagnosis and estimate volumetric bone mineral density. If confirmed in independent populations, this automated opportunistic chest CT evaluation can help clinical screening of large-sample populations to identify subjects at high risk of osteoporotic fracture.

Correlation Between Osteoporosis and Endplate Damage in Degenerative Disc Disease Patients: A Study Based on Phantom-Less Quantitative Computed Tomography and Total Endplate Scores

BACKGROUND

Osteoporosis and degenerative disc disease (DDD) are prevalent in the elderly population. Damage to the vertebral endplate, which impairs nutrient supply to the disc, serves as both a significant initiator and a hallmark of DDD. This study was aimed to explore the association between osteoporosis and endplate damage.

METHODS

This retrospective study included 205 patients with DDD who were treated at Tianjin Hospital from January 2019 to May 2023. We collected data on age, sex, body mass index, phantom-less quantitative computed tomography (PL-QCT) values, and total endplate scores (TEPS). The average PL-QCT value of L1-L4 and TEPS were used to represent volumetric bone mineral density (BMD) and the degree of endplate damage, respectively. Based on the average PL-QCT value of L1 and L2, patients were divided into 3 groups: normal group (BMD > 120 mg/cm3), osteopenic group (80 mg/cm3 ≤ BMD ≤ 120 mg/cm3), and osteoporosis group (BMD < 80 mg/cm3). Multiple linear regression models were used to identify independent factors associated with endplate damage.

RESULTS

The overall TEPS (4.3 ± 1.3 vs. 5.0 ± 1.0 vs. 5.9 ± 1.5, P < 0.01) and segment (L1/2-L4/5) TEPS (P < 0.05) in each group showed significant difference (R = -0.5), increasing in order from normal group to osteoporosis group. A significant negative correlation was found between TEPS and PL-QCT values in overall and each segment (P < 0.001). The PL-QCT values and age (P < 0.05) were independent factors influencing endplate damage. There were significant differences in the average number of TEPS ≥7 segments per patient among the 3 groups, with 1.16, 0.41, and 0.2 segments/person from osteoporosis group to normal group.

CONCLUSIONS

Our study showed a significant positive correlation between osteoporosis and endplate damage. Attention is warranted for patients with osteopenia to prevent progression to osteoporosis, potentially leading to exacerbated DDD. The management of patients with both DDD and osteoporosis necessitates comprehensive treatment strategies that address both the BMD and endplate aspects of these conditions.

Multi-site phantomless bone mineral density from clinical quantitative computed tomography in males

Volumetric bone mineral density (vBMD) is commonly assessed using QCT. Although standard vBMD calculation methods require phantom rods that may not be available, internal-reference phantomless (IPL) and direct measurements of Hounsfield units (HU) can be used to calculate vBMD in their absence. Yet, neither approach has been systemically assessed across skeletal sites, and HU need further validation as a vBMD proxy. This study evaluated the accuracy of phantomless methods, including IPL and regression-based phantomless (RPL) calibration using HU to calculate vBMD, compared to phantom-based (PB) methods. vBMD from QCT scans of 100 male post-mortem human subjects (PMHS) was calculated using site-specific PB calibration at multiple skeletal sites throughout the body. A development sample of 50/100 PMHS was used to determine site-specific reference material density for IPL calibration and RPL equations. Reference densities and equations from the development sample were used to calculate IPL and RPL vBMD on the remaining 50/100 PMHS for method validation. PB and IPL/RPL vBMD were not significantly different (p > .05). Univariate regressions between PB and IPL/RPL vBMD were universally significant (p < 0.05), except for IPL Rad-30 (p = 0.078), with a percent difference across all sites of 6.97% ± 5.95% and 5.22% ± 4.59% between PB and IPL/RPL vBMD, respectively. As vBMD increased, there were weaker relationships and larger differences between PB vBMD and IPL/RPL vBMD. IPL and RPL vBMD had strong relationships with PB vBMD across sites (R2 = 97.99, R2 = 99.17%, respectively), but larger residual differences were found for IPL vBMD. As the accuracy of IPL/RPL vBMD varied between sites, phantomless methods should be site-specific to provide values more comparable to PB vBMD. Overall, this study suggests that RPL calibration may better represent PB vBMD compared to IPL calibration, increases the utility of opportunistic QCT, and provides insight into bone quality and fracture risk.

Opportunistic use of lumbar computed tomography and magnetic resonance imaging for osteoporosis screening

Compared with the healthy patients, patients with osteoporosis had a lower Hounsfield unit (HU) value and a higher vertebral bone quality (VBQ) score. Both the HU value and VBQ score can simply distinguish patients with osteoporosis (OP), with a cutoff value of HU value < 97.06 and VBQ score > 3.08.

INTRODUCTION

The purpose of this study is to determine whether the opportunistic use of computed tomography (CT) or magnetic resonance imaging (MRI) is effective for identifying spine surgical patients with OP.

METHODS

We retrospectively evaluated 109 lumbar spine surgery patients who received lumbar quantitative CT (QCT) and MRI. Using the area under the curve, the CT-based HU value and MRI-based VBQ score were calculated. Then, based on the QCT results, receiver operating characteristic (ROC) curves were constructed to determine the diagnostic performance of the HU value and VBQ score.

RESULTS

The HU value was significantly lower in the OP group, and the VBQ score was significantly higher in the OP group. Using the area under the curve, the diagnostic performance of the HU value and VBQ score for OP were 0.959 and 0.880, respectively. The diagnostic threshold values determined with optimal sensitivity and specificity were an HU value of 97.06 and a VBQ score of 3.08.

CONCLUSION

Opportunistic use of CT and MRI can simply distinguish patients with OP, which are expected to be potential alternatives to T-score for the osteoporosis screening.

Cervical Vertebra Bone Quality Score Predicts Zero-Profile Anchored Spacer Interbody Fusion Cage Subsidence after Anterior Cervical Diskectomy and Fusion: A Retrospective Study

STUDY DESIGN

Retrospective study.

OBJECTIVE

This retrospective study primary focus is to investigate the relationship between the C-VBQ score and the occurrence of postoperative zero-profile anchored spacer (ROI-C) interbody fusion cage subsidence. Additionally, we aim to evaluate the predictive efficacy of the C-VBQ scoring system for subsidence in the context of ACDF with the ROI-C.

METHODS

Patients who underwent ACDF with the ROI-C cage at our hospital between January 2016 and December 2022 were included in this study. Univariate analysis and multivariate logistic regression were employed to identify independent risk factors associated with ROI-C cage subsidence after ACDF. Pearson correlation analysis was utilized to assess the correlation between the C-VBQ score and the height of ROI-C cage subsidence.

RESULTS

A total of 102 patients underwent ACDF with ROI-C in our hospital were included in this study. Univariate analysis showed that age (P = 0.021) and C-VBQ score (P < 0.001) were the influencing factors of cage subsidence. Pearson correlation analysis showed that there was a significant positive correlation between the subsidence height of ROI-C cage and C-VBQ (r = 0.55, P < 0.01). Multivariate binary logistic regression analysis showed that C-VBQ score was the only variable that could significantly predict the subsidence of ROI-C cage after ACDF. Higher C-VBQ score was significantly associated with cage subsidence (P < 0.001).The AUC was 0.89, and the cutoff value for C-VBQ was 2.70.

CONCLUSION

The findings indicate a significant correlation between a higher C-VBQ score before surgery and ROI-C cage subsidence after ACDF. The preoperative assessment of C-VBQ proves valuable for clinicians, enabling them to identify patients with low bone mineral density and predict the risk of zero-profile anchored spacer interbody fusion cage subsidence following ACDF.

Diagnostic Accuracy of Dual-Energy CT-Derived Metrics for the Prediction of Osteoporosis-Associated Fractures

RATIONALE AND OBJECTIVES

This study aimed to compare the diagnostic value of dual-energy CT (DECT)-based volumetric material decomposition with that of Hounsfield units (HU)-based values and cortical thickness ratio for predicting the 2-year risk of osteoporosis-associated fractures.

METHODS

The L1 vertebrae of 111 patients (55 men, 56 women; median age, 62 years) who underwent DECT between 01/2015 and 12/2018 were retrospectively analyzed. For phantomless bone mineral density (BMD) assessment, a specialized DECT postprocessing software employing material decomposition was utilized. The digital records of all patients were monitored for two years after the DECT scans to track the incidence of osteoporotic fractures. Diagnostic accuracy parameters were calculated for all metrics using receiver-operating characteristic (ROC) and precision-recall (PR) curves. Logistic regression models were used to determine associations of various predictive metrics with the occurrence of osteoporotic fractures.

RESULTS

Patients who sustained one or more osteoporosis-associated fractures in a 2-year interval were significantly older (median age 74.5 years [IQR 57-83 years]) compared those without such fractures (median age 50.5 years [IQR 38.5-69.5 years]). According to logistic regression models, DECT-derived BMD was the sole predictive parameter significantly associated with osteoporotic fracture occurrence across all age groups. ROC and PR curve analyses confirmed the highest diagnostic accuracy for DECT-based BMD, with an area under the curve (AUC) of 0.95 [95% CI: 0.89-0.98] for the ROC curve and an AUC of 0.96 [95% CI: 0.85-0.99] for the PR curve.

CONCLUSION

The diagnostic performance of DECT-based BMD in predicting the 2-year risk of osteoporotic fractures is greater than that of HU-based metrics and the cortical thickness ratio. DECT-based BMD values are highly valuable in identifying patients at risk for osteoporotic fractures.

Effect of fully automatic classification model from different tube voltage images on bone density screening: A self-controlled study

PURPOSE

To develop two bone status prediction models combining deep learning and radiomics based on standard-dose chest computed tomography (SDCT) and low-dose chest computed tomography (LDCT), and to evaluate the effect of tube voltage on reproducibility of radiomics features and predictive efficacy of these models.

METHODS

A total of 1508 patients were enrolled in this retrospective study. LDCT was conducted using 80 kVp, tube current ranging from 100 to 475 mA. On the other hand, SDCT was performed using 120 kVp, tube current ranging from 100 to 520 mA. We developed an automatic thoracic vertebral cancellous bone (TVCB) segmentation model. Subsequently, 1184 features were extracted and two classifiers were developed based on LDCT and SDCT images. Based on the diagnostic results of quantitative computed tomography examination, the first-level classifier was initially developed to distinguish normal or abnormal BMD (including osteoporosis and osteopenia), while the second-level classifier was employed to identify osteoporosis or osteopenia. The Dice coefficient was used to evaluate the performance of the automated segmentation model. The Concordance Correlation Coefficients (CCC) of radiomics features were calculated between LDCT and SDCT, and the performance of these models was evaluated.

RESULTS

Our automated segmentation model achieved a Dice coefficient of 0.98 ± 0.01 and 0.97 ± 0.02 in LDCT and SDCT, respectively. Alterations in tube voltage decreased the reproducibility of the extracted radiomic features, with 85.05 % of the radiomic features exhibiting low reproducibility (CCC < 0.75). The area under the curve (AUC) using LDCT-based and SDCT-based models was 0.97 ± 0.01 and 0.94 ± 0.02, respectively. Nonetheless, cross-validation with independent test sets of different tube voltage scans suggests that variations in tube voltage can impair the diagnostic efficacy of the model. Consequently, radiomics models are not universally applicable to images of varying tube voltages. In clinical settings, ensuring consistency between the tube voltage of the image used for model development and that of the acquired patient image is critical.

CONCLUSIONS

Automatic bone status prediction models, utilizing either LDCT or SDCT images, enable accurate assessment of bone status. Tube voltage impacts reproducibility of features and predictive efficacy of models. It is necessary to account for tube voltage variation during the image acquisition.

Comparison of QCT and DEXA findings for lumbar vertebra in young adults and the elderly

BACKGROUND

The use of dual-energy X-ray absorptiometry (DEXA) and quantitative computed tomography (QCT) methods are important for the diagnosis and follow-up of osteoporosis, and are used especially in cases to determine the degree of osteoporosis and the risk of fracture, monitoring the effectiveness of the treatment applied.

PURPOSE

To compare the parameters measured using the DEXA method from the lumbar (L1-L4) vertebrae and the Hounsfield unit (HU) values measured with QCT at the same levels among young adults and the elderly.

MATERIAL AND METHODS

The study included 155 patients (age range = 26-93 years). A total of 57 (36.8%) patients (age range = 26-64 years) were defined as the first group, and 98 (63.2%) patients (aged ≥65 years) were defined as the second group. T-test and correlation analysis were performed to compare bone mineral density (BMD), T score, and HU values measured using DEXA and QCT.

RESULTS

A statistically significant difference was found between T score, lumbar total BMD, and HU values according to age and sex (P < 0.05). When the values measured from lumbar vertebrae were compared using both DEXA and CT, a high correlation was found between them.

CONCLUSION

In the study, it was observed that QCT attenuation measurements of the lumbar spine measured between different age groups provided reliable results in terms of BMD scanning, as in DEXA. It should be noted that QCT has a longer imaging time and higher radiation dose compared to DEXA, and unnecessary scans should be avoided.

For older women, the majority of hip fragility fractures and radiographic vertebral fragility fractures occur among the densitometrically osteoporotic population: a literature analysis

It has been frequently cited that 'the majority of fragility fractures (FF) occur at non-osteoporotic bone mineral density (BMD)'. For the reports with T-score measured around the time of a hip fracture, we conducted a systematic literature search in December 2022, and resulted in 10 studies with five for Caucasian women and five for East Asian women. Femoral neck (FN) T-score was reported in five Caucasian studies and three East Asian studies, three of five Caucasian studies had a mean T-score ≤-2.5, and one study had the majority of their patients measuring a mean T-score ≤-2.5. All three East Asian studies reported a mean FN T-score ≤-2.7. Total hip T-score was reported in two Caucasian studies and three East Asian studies, the two Caucasian studies both had a mean T-score ≤-2.5, and all three East Asian studies had a mean T-score ≤-2.6. A new literature search conducted in April 2024 results in additional three studies, with results being consistent with the data described above. A trend was noted that 'younger' patients suffer from hip fractures at a 'higher' T-score. For the highly cited articles where the notion the majority of FF occur at non-osteoporotic BMD was derived from, authors reported prospective epidemiological studies where BMD was not measured at the timepoint of hip fracture, instead, BMD was measured at the study baseline. These epidemiological studies suggest that >50% of hip fractures likely occur in women with an osteoporotic FN or hip T-score. However, a pattern was seen that older men suffer from hip fracture at a notably higher T-score than older women. For the cases of radiographic vertebral FF, despite varying criteria being used to classify these FFs, the majority of female patients had spine densitometric osteoporosis. Literature shows, compared with the cases of hip fracture, distal forearm fracture occurs at a 'younger' age and 'higher' BMD, suggesting distal forearm fracture is more likely associated with a 'higher' trauma energy level.

CT image-based biomarkers for opportunistic screening of osteoporotic fractures: a systematic review and meta-analysis

The use of opportunistic computed tomography (CT) image-based biomarkers may be a low-cost strategy for screening older individuals at high risk for osteoporotic fractures and populations that are not sufficiently targeted. This review aimed to assess the discriminative ability of image-based biomarkers derived from existing clinical routine CT scans for hip, vertebral, and major osteoporotic fracture prediction. A systematic search in PubMed MEDLINE, Embase, Cochrane, and Web of Science was conducted from the earliest indexing date until July 2023. The evaluation of study quality was carried out using a modified Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS-2) checklist. The primary outcome of interest was the area under the curve (AUC) and its corresponding 95% confidence intervals (CIs) obtained for four main categories of biomarkers: areal bone mineral density (BMD), image attenuation, volumetric BMD, and finite element (FE)-derived biomarkers. The meta-analyses were performed using random effects models. Sixty-one studies were included in this review, among which 35 were synthesized in a meta-analysis and the remaining articles were qualitatively synthesized. In comparison to the pooled AUC of areal BMD (0.73 [95% CI 0.71-0.75]), the pooled AUC values for predicting osteoporotic fractures for FE-derived parameters (0.77 [95% CI 0.72-0.81]; p < 0.01) and volumetric BMD (0.76 [95% CI 0.71-0.81]; p < 0.01) were significantly higher, but there was no significant difference with the pooled AUC for image attenuation (0.73 [95% CI 0.66-0.79]; p = 0.93). Compared to areal BMD, volumetric BMD and FE-derived parameters may provide a significant improvement in the discrimination of osteoporotic fractures using opportunistic CT assessments.

Correlation between vertebral bone mineral density and multi-level virtual non-calcium imaging parameters from dual-layer spectral detector computed tomography

Background

Virtual non-calcium (VNCa) imaging based on dual-energy computed tomography (CT) plays an increasingly important role in diagnosing spinal diseases. However, the utility of VNCa technology in the measurement of vertebral bone mineral density (BMD) is limited, especially the VNCa CT value at multiple calcium suppression levels and the slope of VNCa curve. This retrospective cross-sectional study aimed to explore the correlation between vertebral BMD and new VNCa parameters from dual-layer spectral detector CT.

Methods

The dual-layer spectral detector CT and quantitative CT (QCT) data of 4 hydroxyapatite (HAP) inserts and 667 vertebrae of 234 patients (132 male and 102 female) who visited a university teaching hospital between April and May 2023 were retrospectively analyzed. The BMD values of 3 vertebrae (T12, L1, and L2) and inserts were measured using QCT, defined as QCT-BMD. The VNCa CT values and the slope λ of the VNCa attenuation curve of vertebrae and inserts were recorded. The correlations between VNCa parameters (VNCa CT value, slope λ) and QCT-BMD were analyzed.

Results

For the vertebrae, the correlation coefficient ranged from -0.904 to 0.712 (all P<0.05). As the calcium suppression index (CaSI) increased, the correlation degree exhibited a decrease first and then increased, with the best correlation (r=-0.904, P<0.001) observed at the index of 25%. In contrast, the correlation coefficient for the inserts remained relatively stable (r=-0.899 to -1, all P<0.05). For the vertebrae, the values of 3 slopes λ (λ1, λ2, and λ3) derived from the VNCa attenuation curve were 6.50±1.99, 3.75±1.15, and 2.04±0.62, respectively. Regarding the inserts, the λ1, λ2, and λ3 values were 11.56 [interquartile range (IQR): 2.40-22.62], 6.68 (IQR: 1.39-13.49), and 3.63 (IQR: 0.75-7.8), respectively. For the vertebrae, all 3 correlation coefficients between 3 slopes λ and QCT-BMD were 0.956 (all P<0.05). For the inserts, the 3 correlation coefficients were 0.996, 0.998, and 1 (all P<0.05), respectively.

Conclusions

A promising correlation was detected between VNCa CT parameters and QCT-BMD in vertebrae, warranting further investigation to explore the possibility of VNCa imaging to assess BMD.

Comparisons of Hounsfield units and volumetric bone density in discriminating vertebral fractures on lumbar CT scans

OBJECTIVES

To compare the performance of areal Hounsfield units (aHUs), volumetric Hounsfield units (vHUs), and volumetric bone mineral density (vBMD) by quantitative CT (QCT) in discriminating vertebral fractures (VFs) risk.

METHODS

We retrospectively included CT scans of the lumbar spine 101 VFs cases (60 women, mean age: 64 ± 4 years; 41 men, mean age: 73 ± 10 years) and sex- and age-matched 101 control subjects (60 women, mean age: 64 ± 4 years; 41 men, mean age: 72 ± 7 years). In order to assess the discriminatory capability of aHU, vHU, and vBMD measurements at the L1 and L2 levels in identifying VFs, we conducted binary logistic regression and receiver operating characteristic (ROC) curve analyses in men and women. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated.

RESULTS

In both men and women with and without VFs, aHU, vHU, and vBMD were highly correlated with each other (r2 from 0.832 to 0.957, all P < .001). There was a statistically significant difference in aHU, vHU, and vBMD between subjects with and without VFs (P < .001). When age, gender, and BMI were taken into account as covariances and adjusted simultaneously, odds ratios (ORs) for aHU, vHU, and vBMD values, which represent the risk of VFs, were significant (P < .001). Compared with aHU and vHU, vBMD was more strongly associated with VF risk (vBMD: OR, 6.29; 95% CI, 3.83-10.35 vs vHU: OR, 3.64; 95% CI, 2.43-5.46 vs aHU: OR, 2.56; 95% CI, 1.79-3.67). In both men and women, further, vBMD had higher values for AUC, sensitivity, specificity, PPV, and NPV compared to vHU, with vHU in turn surpassing aHU. The area under the receiver operating characteristic curve (AUC) for discriminating VFs using the average aHU, vHU, and vBMD of 2 vertebrae was 0.72, 0.77, and 0.87 in men and 0.76, 0.79, and 0.86 in women. In both men and women, there exist statistically significant differences in the AUC when employing the 3 measurements-namely, aHU, vHU, and vBMD-to discriminate fractures (P < .05).

CONCLUSIONS

The QCT-measured vBMD is more associated with acute VFs than vHU and aHU values of the lumbar spine. Although the use of vHU and aHU values for the diagnosis of osteoporosis and discriminating fracture risk is limited to scanner- and imaging protocol-specific, they have great potential for opportunistic osteoporosis screening, particularly vHU.

ADVANCES IN KNOWLEDGE

The novelty of this study presents a comparison of the VF discriminative capabilities among aHU, vHU, and vBMD. The vHU values introduced in this study demonstrate a greater capacity to discriminate fractures compared to aHU, presenting an improved clinical choice. Although its discriminatory capability is slightly lower than that of vBMD, it is more convenient to measure and does not require specialized software.

Longitudinal MR-based proton-density fat fraction (PDFF) and T2* for the assessment of associations between bone marrow changes and myelotoxic chemotherapy

OBJECTIVES

MR imaging-based proton density fat fraction (PDFF) and T2* imaging has shown to be useful for the evaluation of degenerative changes in the spine. Therefore, the aim of this study was to investigate the influence of myelotoxic chemotherapy on the PDFF and T2* of the thoracolumbar spine in comparison to changes in bone mineral density (BMD).

METHODS

In this study, 19 patients were included who had received myelotoxic chemotherapy (MC) and had received a MR imaging scan of the thoracolumbar vertebrates before and after the MC. Every patient was matched for age, sex, and time between the MRI scans to two controls without MC. All patients underwent 3-T MR imaging including the thoracolumbar spine comprising chemical shift encoding-based water-fat imaging to extract PDFF and T2* maps. Moreover, trabecular BMD values were determined before and after chemotherapy. Longitudinal changes in PDFF and T2* were evaluated and compared to changes in BMD.

RESULTS

Absolute mean differences of PDFF values between scans before and after MC were at 8.7% (p = 0.01) and at -0.5% (p = 0.57) in the control group, resulting in significantly higher changes in PDFF in patients with MC (p = 0.008). BMD and T2* values neither showed significant changes in patients with nor in those without myelotoxic chemotherapy (p = 0.15 and p = 0.47). There was an inverse, yet non-significant correlation between changes in PDFF and BMD found in patients with myelotoxic chemotherapy (r = -0.41, p = 0.12).

CONCLUSION

Therefore, PDFF could be a useful non-invasive biomarker in order to detect changes in the bone marrow in patients receiving myelotoxic therapy.

CLINICAL RELEVANCE STATEMENT

Using PDFF as a non-invasive biomarker for early bone marrow changes in oncologic patients undergoing myelotoxic treatment may help enable more targeted countermeasures at commencing states of bone marrow degradation and reduce risks of possible fragility fractures.

KEY POINTS

Quantifying changes in bone marrow fat fraction, as well as T2* caused by myelotoxic pharmaceuticals using proton density fat fraction, is feasible. Proton density fat fraction could potentially be established as a non-invasive biomarker for early bone marrow changes in oncologic patients undergoing myelotoxic treatment.

Effectiveness of opportunistic osteoporosis screening on chest CT using the DCNN model

OBJECTIVE

To develop and evaluate a deep learning model based on chest CT that achieves favorable performance on opportunistic osteoporosis screening using the lumbar 1 + lumbar 2 vertebral bodies fusion feature images, and explore the feasibility and effectiveness of the model based on the lumbar 1 vertebral body alone.

MATERIALS AND METHODS

The chest CT images of 1048 health check subjects from January 2021 to June were retrospectively collected as the internal dataset (the segmentation model: 548 for training, 100 for tuning and 400 for test. The classification model: 530 for training, 100 for validation and 418 for test set). The subjects were divided into three categories according to the quantitative CT measurements, namely, normal, osteopenia and osteoporosis. First, a deep learning-based segmentation model was constructed, and the dice similarity coefficient(DSC) was used to compare the consistency between the model and manual labelling. Then, two classification models were established, namely, (i) model 1 (fusion feature construction of lumbar vertebral bodies 1 and 2) and (ii) model 2 (feature construction of lumbar 1 alone). Receiver operating characteristic curves were used to evaluate the diagnostic efficacy of the models, and the Delong test was used to compare the areas under the curve.

RESULTS

When the number of images in the training set was 300, the DSC value was 0.951 ± 0.030 in the test set. The results showed that the model 1 diagnosing normal, osteopenia and osteoporosis achieved an AUC of 0.990, 0.952 and 0.980; the model 2 diagnosing normal, osteopenia and osteoporosis achieved an AUC of 0.983, 0.940 and 0.978. The Delong test showed that there was no significant difference in area under the curve (AUC) values between the osteopenia group and osteoporosis group (P = 0.210, 0.546), while the AUC value of normal model 2 was higher than that of model 1 (0.990 vs. 0.983, P = 0.033).

CONCLUSION

This study proposed a chest CT deep learning model that achieves favorable performance on opportunistic osteoporosis screening using the lumbar 1 + lumbar 2 vertebral bodies fusion feature images. We further constructed the comparable model based on the lumbar 1 vertebra alone which can shorten the scan length, reduce the radiation dose received by patients, and reduce the training cost of technologists.

Incident fractures of the distal radius: Dual-energy CT-derived metrics for opportunistic risk stratification

BACKGROUND

Dual-energy CT (DECT)-derived bone mineral density (BMD) of the distal radius and other CT-derived metrics related to bone health have been suggested for opportunistic osteoporosis screening and risk evaluation for sustaining distal radius fractures (DRFs).

METHODS

The distal radius of patients who underwent DECT between 01/2016 and 08/2021 was retrospectively analyzed. Cortical Hounsfield Unit (HU), trabecular HU, cortical thickness, and DECT-based BMD were acquired from a non-fractured, metaphyseal area in all examinations. Receiver-operating characteristic (ROC) analysis was conducted to determine the area under the curve (AUC) values for predicting DRFs based on DECT-derived BMD, HU values, and cortical thickness. Logistic regression models were then employed to assess the associations of these parameters with the occurrence of DRFs.

RESULTS

In this study, 263 patients (median age: 52 years; interquartile range: 36-64; 132 women; 192 fractures) were included. ROC curve analysis revealed a higher area under the curve (AUC) value for DECT-derived BMD compared to cortical HU, trabecular HU, and cortical thickness (0.91 vs. 0.61, 0.64, and 0.69, respectively; p <.001). Logistic regression models confirmed the association between lower DECT-derived BMD and the occurrence of DRFs (Odds Ratio, 0.83; p <.001); however, no influence was observed for cortical HU, trabecular HU, or cortical thickness.

CONCLUSIONS

DECT can be used to assess the BMD of the distal radius without dedicated equipment such as calibration phantoms to increase the detection rates of osteoporosis and stratify the individual risk to sustain DRFs. In contrast, assessing HU-based values and cortical thickness does not provide clinical benefit.

Opportunistic screening for osteoporosis using enhanced images based on dual-energy computed tomography material decomposition: a comparison with quantitative computed tomography

Background

Many patients with malignant tumors require chemotherapy and radiation therapy, which can result in a decline in physical function and potentially influence bone mineral density (BMD). Furthermore, these treatments necessitate enhanced computed tomography (CT) scans for determining disease staging or treatment outcomes, and opportunistic screening with available imaging data is beneficial for patients at high risk for osteoporosis if existing imaging data can be used. The study aimed to investigate the feasibility of opportunistic screening for osteoporosis using enhanced CT based on a dual-energy CT (DECT) material decomposition technique.

Methods

We prospectively enrolled 346 consecutive patients who underwent abdominal unenhanced and triphasic contrast-enhanced CT (arterial, portal venous, and delayed phases) between June 2021 and June 2022. The BMD, and the density of hydroxyapatite (HAP) on HAP-iodine images and calcium (Ca) on Ca-iodine images were measured on the L1-L3 vertebral bodies. The iodine intake was recorded. Pearson analysis was conducted to assess the correlation between iodine intake and the density values in three phases and the correlation between BMD and the densities of HAP and Ca. Furthermore, linear regression was employed for quantitative evaluation. Bland-Altman analysis was used to evaluate the agreement between calculated BMD derived from DECT (BMD-DECT) and reference BMD derived from quantitative CT (BMD-QCT). Receiver operating characteristic (ROC) analysis was applied to assess the diagnostic efficacy.

Results

The HAP and Ca density of the L1-L3 vertebral bodies did not differ significantly among the three phases of contrast-enhanced CT (F=0.001-0.049; P>0.05). Significant positive correlations were found between HAP, Ca densities, and BMD (HAP-BMD: r=0.9472, R2=0.8973; Ca-BMD: r=0.9470, R2=0.8968; all P<0.001). Bland-Altman plots showed high agreement between BMD-DECT and BMD-QCT. The area under the curve (AUC) using HAP and Ca measurements was 0.963 [95% confidence interval (CI): 0.937-0.980] and 0.964 (95% CI: 0.939-0.981), respectively, for diagnosing osteoporosis and was 0.951 (95% CI: 0.917-0.973) and 0.950 (95% CI: 0.916-0.973), respectively, for diagnosing osteopenia.

Conclusions

The HAP and Ca density measurements generated through the material decomposition technique in DECT have good diagnostic performances in assessing BMD, which offers a new perspective for opportunistic screening of osteoporosis on contrast-enhanced CT.

Quantitative computed tomography has higher sensitivity detecting critical bone mineral density compared to dual-energy X-ray absorptiometry in postmenopausal women and elderly men with osteoporotic fractures: a real-life study

INTRODUCTION

Dual-energy X-ray absorptiometry (DXA) is considered the gold standard for the diagnosis of osteoporosis and assessment of fracture risk despite proven limitations. Quantitative computed tomography (QCT) is regarded as a sensitive method for diagnosis and follow-up. Pathologic fractures are classified as the main clinical manifestation of osteoporosis. The objective of the study was to compare DXA and QCT to determine their sensitivity and discriminatory power.

MATERIALS AND METHODS

Patients aged 50 years and older were included who had DXA of the lumbar spine and femur and additional QCT of the lumbar spine within 365 days. Fractures and bone mineral density (BMD) were retrospectively examined. BMD measurements were analyzed for the detection of osteoporotic fractures. Sensitivity and receiver operating characteristic curve were used for calculations. As an indication for a second radiological examination was given, the results were compared with control groups receiving exclusively DXA or QCT for diagnosis or follow-up.

RESULTS

Overall, BMD measurements of 404 subjects were analyzed. DXA detected 15 (13.2%) patients having pathologic fractures (n = 114) with normal bone density, 66 (57.9%) with osteopenia, and 33 (28.9%) with osteoporosis. QCT categorized no patients having pathologic fractures with healthy bone density, 14 (12.3%) with osteopenia, and 100 (87.7%) with osteoporosis. T-score DXA, trabecular BMD QCT, and cortical BMD QCT correlated weakly. Trabecular BMD QCT and cortical BMD QCT classified osteoporosis with decreased bone mineral density (AUC 0.680; 95% CI 0.618-0.743 and AUC 0.617; 95% CI 0.553-0.682, respectively). T-score DXA could not predict prevalent pathologic fractures. In control groups, each consisting of 50 patients, DXA and QCT were significant classifiers to predict prevalent pathologic fractures.

CONCLUSION

Our results support that volumetric measurements by QCT in preselected subjects represent a more sensitive method for the diagnosis of osteoporosis and prediction of fractures compared to DXA.

Based on HbA1c Analysis: Bone Mineral Density and Osteoporosis Risk in Postmenopausal Female with T2DM

INTRODUCTION

This study aims to investigate association between glycosylated hemoglobin (HbA1c) with bone mineral density (BMD) and osteoporosis-risk in postmenopausal female with type 2 diabetes mellitus (T2DM).

METHODOLOGY

HbA1c values, BMD of L3 vertebra and basic clinical data of 152 postmenopausal females with T2DM and 326 postmenopausal females without T2DM were retrospectively analyzed. The propensity score matching was used to match the T2DM and the non-T2DM group at a ratio of 1:1. Restricted cubic spline (RCS) analysis and piecewise linear regression were used to evaluate the relationship between HbA1c and BMD. Univariable and multivariable logistic regression were utilized to evaluate the effect of HbA1c on the risk of osteoporosis in matched diabetes population.

RESULTS

After matching, the BMD (66.60 (46.58, 93.23) vs. 63.50 (36.70, 83.33), P < 0.05), HbA1c value (7.50 (6.72, 8.80) vs 5.30 (5.14, 5.50), P  <  0.05) in the T2DM group were significantly higher than that of non-T2DM group. We found a nonlinear relation between HbA1c value and BMD, which showing a U-shaped curve with the cutoff value around 7.5 % (Poverall < 0.001, Pnonliearity < 0.05). The prevalence of osteoporosis in T2DM group was similar to that in controls (64.9 % vs 73.6 %, P = 0.102). Age-adjusted HbA1c value was not risk factor of osteoporosis in postmenopausal females with T2DM.

CONCLUSION

In postmenopausal females with T2DM, high BMD and similar risk of osteoporosis were confirmed; HbA1c was a contributing factor to BMD when values exceed 7.5 %. However, HbA1c does not seem to be associated with osteoporosis risk.

A study on whether deep learning models based on CT images for bone density classification and prediction can be used for opportunistic osteoporosis screening

This study utilized deep learning to classify osteoporosis and predict bone density using opportunistic CT scans and independently tested the models on data from different hospitals and equipment. Results showed high accuracy and strong correlation with QCT results, showing promise for expanding osteoporosis screening and reducing unnecessary radiation and costs.

PURPOSE

To explore the feasibility of using deep learning to establish a model for osteoporosis classification and bone density value prediction based on opportunistic CT scans and to verify its generalization and diagnostic ability using an independent test set.

METHODS

A total of 1219 cases of opportunistic CT scans were included in this study, with QCT results as the reference standard. The training set: test set: independent test set ratio was 703: 176: 340, and the independent test set data of 340 cases were from 3 different hospitals and 4 different CT scanners. The VB-Net structure automatic segmentation model was used to segment the trabecular bone, and DenseNet was used to establish a three-classification model and bone density value prediction regression model. The performance parameters of the models were calculated and evaluated.

RESULTS

The ROC curves showed that the mean AUCs of the three-category classification model for categorizing cases into "normal," "osteopenia," and "osteoporosis" for the training set, test set, and independent test set were 0.999, 0.970, and 0.933, respectively. The F1 score, accuracy, precision, recall, precision, and specificity of the test set were 0.903, 0.909, 0.899, 0.908, and 0.956, respectively, and those of the independent test set were 0.798, 0.815, 0.792, 0.81, and 0.899, respectively. The MAEs of the bone density prediction regression model in the training set, test set, and independent test set were 3.15, 6.303, and 10.257, respectively, and the RMSEs were 4.127, 8.561, and 13.507, respectively. The R-squared values were 0.991, 0.962, and 0.878, respectively. The Pearson correlation coefficients were 0.996, 0.981, and 0.94, respectively, and the p values were all < 0.001. The predicted values and bone density values were highly positively correlated, and there was a significant linear relationship.

CONCLUSION

Using deep learning neural networks to process opportunistic CT scan images of the body can accurately predict bone density values and perform bone density three-classification diagnosis, which can reduce the radiation risk, economic consumption, and time consumption brought by specialized bone density measurement, expand the scope of osteoporosis screening, and have broad application prospects.

Quantitative CT Evaluation of Bone Mineral Density in the Thoracic Spine on 18F-Fluorocholine PET/CT Imaging in Patients With Primary Hyperparathyroidism

INTRODUCTION

Measurement of bone mineral density (BMD) with quantitative CT (QCT) carries several advantages over other densitometric techniques, including superior assessment of the spine. As most QCT studies evaluated the lumbar spine, measurements of the thoracic spine are limited. We performed QCT analysis of the thoracic spine in a cohort of patients with primary hyperparathyroidism.

MATERIALS AND METHODS

This study was a retrospective QCT analysis of the thoracic spine on 18F-fluorocholine PET/CT scans in patients with primary hyperparathyroidism patients between March 2018 and December 2022. Correlations between QCT-derived BMD or Hounsfield units (HU) and demographic data, laboratory parameters, results from histopathological examination after parathyroidectomy and results of DXA imaging were analyzed, when available.

RESULTS

In 189 patients, mean QCT-derived BMD at the thoracic spine was 85.6 mg/cm3. Results from recent DXA were available in 122 patients. Mean thoracic QCT-derived BMD and HU were significantly correlated with DXA-derived BMD in lumbar spine, total hip and femoral neck and with the lowest T-score at DXA imaging. Only weak correlations were found with BMI or 18F-fluorocholine uptake, while no significant correlations were found with adenoma weight, PTH or calcium levels.

CONCLUSION

Our study confirms correlation between QCT-derived BMD in the thoracic spine with age and DXA-derived BMD measurements within a population of patients with primary hyperparathyroidism. Establishment of reference BMD values for individual thoracic vertebrae, may allow direct osteoporosis classification on thoracic CT imaging.

Vertebral Fracture Risk Thresholds from Phantom-Less Quantitative Computed Tomography-Based Finite Element Modeling Correlate to Phantom-Based Outcomes

INTRODUCTION

Osteoporosis indicates weakened bones and heightened fracture susceptibility due to diminished bone quality. Dual-energy x-ray absorptiometry is unable to assess bone strength. Volumetric bone mineral density (vBMD) from quantitative computed tomography (QCT) has been used to establish guidelines as equivalent measurements for osteoporosis. QCT-based finite element analysis (FEA) has been implemented using calibration phantoms to establish bone strength thresholds based on the established vBMD. The primary aim was to validate vertebral failure load thresholds using a phantom-less approach with previously established thresholds, advancing a phantom-free approach for fracture risk prediction.

METHODOLOGY

A controlled cohort of 108 subjects (68 females) was used to validate sex-specific vertebral fracture load thresholds for normal, osteopenic, and osteoporotic subjects, obtained using a QCT/FEA-based phantom-less calibration approach and two material equations.

RESULTS

There were strong prediction correlations between the phantom-less and phantom-based methods (R2: 0.95 and 0.97 for males, and R2: 0.96 and 0.98 for females) based on the two equations. Bland Altman plots and paired t-tests showed no significant differences between methods. Predictions for bone strengths and thresholds using the phantom-less method matched those obtained using the phantom calibration and those previously established, with ≤4500 N (fragile) and ≥6000 N (normal) bone strength in females, and ≤6500 N (fragile) and ≥8500 N (normal) bone strength in males.

CONCLUSION

Phantom-less QCT-based FEA can allow for prospective and retrospective studies evaluating incidental vertebral fracture risk along the spine and their association with spine curvature and/or fracture etiology. The findings of this study further supported the application of phantom-less QCT-based FEA modeling to predict vertebral strength, aiding in identifying individuals prone to fractures. This reinforces the rationale for adopting this method as a comprehensive approach in predicting and managing fracture risk.

Different cervical vertebral bone quality scores for bone mineral density assessment for the patients with cervical degenerative disease undergoing ACCF/ACDF: computed tomography and magnetic resonance imaging-based study

BACKGROUND

Bone mineral density (BMD) is important for the outcome of cervical spine surgery. As the gold standard of assessing BMD, dual-energy X-ray absorptiometry scans are often not ordered or go unreviewed in patients' charts. As the supplement, MRI-based vertebral bone quality (VBQ) was found to accurately predict osteopenia/osteoporosis and postoperative complications in lumbar spine. However, discussion of the efficiency of VBQ in cervical spine is lacking. And measurement methods of VBQ in cervical spine are diverse and not universally acknowledged like lumbar spine. We aimed to compare the predictive performance of three kinds of different Cervical-VBQ (C-VBQ) scores for bone mineral density assessment in patients undergoing cervical spine surgery. HU value of cervical spine was set as a reference.

METHODS

Adult patients receiving cervical spine surgery for degenerative diseases were retrospectively included between Jan 2015 and Dec 2022 in our hospital. The VBQ scores and HU value were measured from preoperative MRI and CT. The correlation between HU value/C-VBQs (named C-VBQ1/2/3 according to different calculating methods) and DEXA T-score was analyzed using univariate linear correlation and Pearson's correlation. We evaluated the predictive performance of those two parameters and achieved the most appropriate cutoff value by comparing the receiver operating characteristic (ROC) curves.

RESULTS

106 patients (34 patients with T ≥ - 1.0 vs 72 patients with T < - 1.0) were included (mean age: 51.95 ± 10.94, 48 men). According to Pearson correlation analysis, C-VBQ1/2/3 and HU value were all significantly correlated to DEXA T-score (Correlation Coefficient (r): C-VBQ1: - 0.393, C-VBQ2: - 0.368, C-VBQ3: - 0.395, HU value: 0.417, p < 0.001). The area under the ROC curve (AUC) was calculated (C-VBQ1: 0.717, C-VBQ2: 0.717, C-VBQ3: 0.727, HU value: 0.746). The AUC of the combination of C-VBQ3 and HU value was 0.786. At last, the most appropriate cutoff value was determined (C-VBQ1: 3.175, C-VBQ2: 3.005, C-VBQ3: 2.99, HU value: 299.85 HU).

CONCLUSIONS

Different MRI-based C-VBQ scores could all be potential and alternative tools for opportunistically screening patients with osteopenia and osteoporosis before cervical spine surgery. Among them, C-VBQ calculated in ASIC2-C7/SIT1-CSF performed better. We advised patients with C-VBQ higher than cutoff value to accept further BMD examination.

Evaluation of Bone Mineral Density in Lung Transplant Recipients by Chest Computed Tomography

INTRODUCTION

Lung transplantation (LT) recipients are at risk of bone mineral density (BMD) loss. Pre- and post-LT BMD loss has been reported in some cross-sectional studies; however, there are limited studies regarding the serial BMD change in LT recipients. The aim of this study was to investigate the serial BMD changes and the clinical characteristics associated with BMD decline.

METHODS

This was a single-center, retrospective observational study. BMD was serially measured in thoracic vertebral bodies (Th4, 7, 10) using computed tomography (CT) before and 3 and 12 months after LT. The frequency of osteoporosis and factors associated with pre-LT osteoporosis and post-LT BMD loss were evaluated. The frequency of post-LT compression fracture and its associated factors were also analyzed.

RESULTS

This study included 128 adult LT recipients. LT recipients had decreased BMD (151.8 ± 42.2 mg/mL) before LT compared with age-, sex-, and smoking index-matched controls (176.2 ± 35.7 mg/mL). The diagnosis of COPD was associated with pre-LT osteoporosis. LT recipients experience further BMD decline after transplantation, and the percentage of recipients classified as exhibiting osteoporosis increased from 20% at baseline to 43% at 12 months. Recipients who had been taking no or small doses of glucocorticoids before LT had rapid BMD loss after LT. Early bisphosphonate use (within 3 months) after LT attenuated BMD loss and decreased new-onset compression fracture.

CONCLUSION

LT recipients are at high risk for BMD loss and compression fracture after LT. Early bisphosphonate use may decrease BMD loss and compression fracture.

Screw Insertional Torque Measurement in Spine Surgery: Correlation With Bone Mineral Density and Hounsfield Unit

OBJECTIVE

Achieving successful fusion during spine surgery is dependent on rigid pedicle screw fixation. To assess fixation strength, the insertional torque can be measured during intraoperative screw fixation. This study aimed to explore the technical feasibility of measuring the insertional torque of a pedicle screw, while investigating its relationship with bone density.

METHODS

Thoraco-lumbar screw fixation fusion surgery was performed on 53 patients (mean age, 65.5 ± 9.8 years). The insertional torque of 284 screws was measured at the point passing through the pedicle using a calibrated torque wrench, with a specially designed connector to the spine screw system. The Hounsfield units (HU) value was determined by assessing the trabecular portion of the index vertebral body on sagittal computed tomography images. We analyzed the relationship between the measured insertional torque and the following bone strength parameters: bone mineral density (BMD) and HU of the vertebral body.

RESULTS

The mean insertion torque was 105.55 ± 58.08 N∙cm and T-score value (BMD) was -1.14 ± 1.49. Mean HU value was 136.37 ± 57.59. Screw insertion torque was positively correlated with BMD and HU in whole patients. However, in cases of osteopenia, all variables showed very weak correlations with insertional torque. In patients with osteoporosis, there was no statistically significant correlation between BMD and torque strength; HU showed a significant correlation.

CONCLUSION

The insertional torque of screw fixation significantly correlated with bone density (BMD and HU). HU measurements showed greater clinical significance than did BMD values in patients with osteoporosis.

Automated vertebral bone mineral density measurement with phantomless internal calibration in chest LDCT scans using deep learning

OBJECTIVE

To develop and evaluate a fully automated method based on deep learning and phantomless internal calibration for bone mineral density (BMD) measurement and opportunistic low BMD (osteopenia and osteoporosis) screening using chest low-dose CT (LDCT) scans.

METHODS

A total of 1175 individuals were enrolled in this study, who underwent both chest LDCT and BMD examinations with quantitative computed tomography (QCT), by two different CT scanners (Siemens and GE). Two convolutional neural network (CNN) models were employed for vertebral body segmentation and labeling, respectively. A histogram technique was applied for vertebral BMD calculation using paraspinal muscle and surrounding fat as references. 195 cases (by Siemens scanner) as fitting cohort were used to build the calibration function. 698 cases as validation cohort I (VCI, by Siemens scanner) and 282 cases as validation cohort II (VCII, by GE scanner) were performed to evaluate the performance of the proposed method, with QCT as the standard for analysis.

RESULTS

The average BMDs from the proposed method were strongly correlated with QCT (in VCI: r = 0.896, in VCII: r = 0.956, p < 0.001). Bland-Altman analysis showed a small mean difference of 1.1 mg/cm3, and large interindividual differences as seen by wide 95% limits of agreement (-29.9 to +32.0 mg/cm3) in VCI. The proposed method measured BMDs were higher than QCT measured BMDs in VCII (mean difference = 15.3 mg/cm3, p < 0.001). Osteoporosis and low BMD were diagnosed by proposed method with AUCs of 0.876 and 0.903 in VCI, 0.731 and 0.794 in VCII, respectively. The AUCs of the proposed method were increased to over 0.920 in both VCI and VCII after adjusting the cut-off.

CONCLUSION

Without manual selection of the region of interest of body tissues, the proposed method based on deep learning and phantomless internal calibration has the potential for preliminary screening of patients with low BMD using chest LDCT scans. However, the agreement between the proposed method and QCT is insufficient to allow them to be used interchangeably in BMD measurement.

ADVANCES IN KNOWLEDGE

This study proposed an automated vertebral BMD measurement method based on deep learning and phantomless internal calibration with paraspinal muscle and fat as reference.

Vertebral bone quality score for opportunistic osteoporosis screening: a correlation and optimal threshold analysis

PURPOSE

This study investigated the vertebral bone quality (VBQ) score as a potential tool for opportunistic osteoporosis screening and its correlation with dual-energy X-ray absorptiometry (DXA) values.

METHODS

In a single-center retrospective cohort of 130 patients, VBQ and DXA measures were compared using various statistical analyses. The optimal VBQ threshold for predicting osteoporosis was determined using receiver operating characteristic (ROC) analysis.

RESULTS

VBQ exhibited a significant negative association with DXA values, suggesting that higher VBQ scores are indicative of lower bone density. Age and VBQ were significant predictors of osteoporosis, with both increasing the log-odds of the condition. An optimal VBQ threshold of 2.7 was determined, demonstrating fair discriminatory power and high negative predictive value.

CONCLUSION

The study highlighted the potential of VBQ as a diagnostic tool for osteoporosis with high intra- and inter-observer reliability. The optimal VBQ threshold of 2.7 can aid in ruling out osteoporosis and identifying individuals for further evaluation.

The correlation between osteoporotic vertebrae fracture risk and bone mineral density measured by quantitative computed tomography and dual energy X-ray absorptiometry: a systematic review and meta-analysis

This paper presents a comparison of quantitative computed tomography (QCT) and dual-energy X-ray absorptiometry (DXA) in osteoporosis with vertebral fracture and osteoporosis without fracture. It has been proved that the volumetric bone mineral density (vBMD) measured by QCT exhibits a stronger correlation with fracture risk than areal bone mineral density (aBMD) measured by DXA.

PURPOSE

This study aims to systematically evaluate the ability of QCT and DXA to distinguish between osteoporosis with vertebral fracture and osteoporosis without fracture according to vBMD and aBMD.

METHODS

We conducted a primary literature search of the online databases up to 3 July, 2022, in both English and Chinese publications, combining synonyms for "QCT", "DXA" and "osteoporosis". The Newcastle-Ottawa scale (NOS) was employed to evaluate the quality of the selected articles. vBMD obtained through QCT and aBMD obtained through DXA were extracted, and were analyzed by Review Manager 5.4 and RStudio.

RESULTS

Six studies with 610 individuals aged 45 to 90, of which 179 had vertebral fractures, were included in the final analysis. The weighted mean difference (WMD) between osteoporosis with vertebral fracture and osteoporosis without fracture for vBMD was - 27.08 (95% CI  - 31.24 to  - 22.92), while for aBMD was - 0.05 (95% CI - 0.08 to - 0.03).

CONCLUSIONS

Both vBMD detected by QCT and aBMD detected by DXA could discriminate fracture status in the spine, and vBMD performed a stronger correlation with fracture risk.

TRIAL REGISTRATION

PROSPERO 2022 CRD42022349185.

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.

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.

Smoking index and COPD duration as potential risk factors for development of osteoporosis in patients with non-small cell lung cancer - A retrospective case control study evaluated by CT Hounsfield unit

Objective

To investigate the effect of smoking index (calculated as number of cigarettes per day × smoking years) and chronic obstructive pulmonary disease (COPD) duration on osteoporosis (OP)evaluated by opportunistic chest CT in patients with non-small cell lung cancer (NSCLC).

Methods

A total of 101 patients diagnosed with NSCLC were included in our cohort study. Among them, 50 patients with a history of smoking and COPD were assigned to the experimental group, while 51 patients without a history of smoking and COPD were assigned to the control group. Hounsfield unit (HU) value was measured by conventional chest CT to investigate the bone mineral density; and the mean values of axial HU value in the upper, middle and lower parts of T4, T7, T10 and L1 vertebral bodies were measured as the study variables.

Results

There were no significant differences in gender, age, body mass index, type of lung cancer, clinical stage of lung cancer and comorbidities between the two groups (P = 0.938，P = 0.158，P = 0.722,P = 0.596,P = 0.813,P = 0.655). The overall mean HU values of T4, T7, T10, L1 in the experimental group were 116.60 ± 30.67, 110.56 ± 30.03, 109.18 (96.85-122.95), 94.63 (85.20-104.12) and 106.86 ± 22.26, respectively, which were significantly lower than those in the control group (189.55 ± 34.57, 174.54 ± 35.30, 172.73 (156.33-199.50), 158.20 (141.60-179.40) and 177.50 ± 33.49) (P ＜0.05). And in the experimental group, smoking index and COPD duration were significantly and negatively correlated with HU values (r = -0.627, -0.542, P ＜0.05, respectively).

Conclusion

Patients with NSCLC who have a history of smoking and COPD exhibit a notably lower HU value compared to the control groups. Additionally, it has been observed that the smoking index and duration of COPD may be influential factors affecting bone mineral density in NSCLC patients.

Association of Phantomless Dual-Energy CT-based Volumetric Bone Mineral Density with the Prevalence of Acute Insufficiency Fractures of the Spine

RATIONALE AND OBJECTIVES

To evaluate the bone mineral density (BMD) of the lumbar spine derived from dual-energy CT (DECT)-based volumetric material decomposition and its association with acute insufficiency fractures of the thoracolumbar spine.

MATERIALS AND METHODS

L1 of 160 patients (77 men, 83 women; mean age 64.3 years, range, 22-94 years) who underwent third-generation dual-source DECT between January 2016 and December 2021 due to suspected insufficiency fractures was retrospectively analyzed. All depicted vertebrae were examined for signs of recent fractures. A dedicated DECT postprocessing software using material decomposition was applied for phantomless BMD assessment. Receiver-operating characteristic (ROC) analysis identified optimal BMD thresholds. Associations of BMD, sex, and age with the occurrence of insufficiency fractures were examined with logistic regression models.

RESULTS

A DECT-derived BMD threshold of 120.40 mg/cm³ yielded 90.1% specificity and 59.32% sensitivity to differentiate patients with at least one insufficiency fracture from patients without fracture. No patient without fracture had a DECT-derived BMD below 85 mg/cm3. Lower DECT-derived bone mineral density was associated with an increased risk of insufficiency fractures (Odds ratio of 0.93, 95% CI, 0.91-0.96, p < 0.001). Overall ROC-derived AUC was 0.82 (p < 0.0001) for the differentiation of patients that sustained an insufficiency fracture from the control group.

CONCLUSION

Dual-Energy CT-based BMD assessment can accurately differentiate patients with acute insufficiency fractures of the thoracolumbar spine from patients without fracture. This algorithm can be used for phantomless risk stratification of patients undergoing routine CT to sustain insufficiency fractures of the thoracolumbar spine The identified cut-off value of 120.4 mg/cm³ is in line with current American College of Radiology (ACR) recommendations to differentiate healthy individuals from those with reduced bone mineral density.

Feasibility analysis of bone density evaluation with Hounsfield unit value after fibula flap reconstruction of jaw defect

BACKGROUND

Implant-supported dentures have become an essential means of restoring occlusal function after jaw reconstruction. Bone mineral density (BMD) may influence the success rate of implant denture restorations. This study aimed to explore whether the Hounsfield unit (HU) value can be used to monitor the changing trend of fibular BMD after jaw reconstruction.

RESULTS

A total of 54 patients who underwent maxillar/mandibular reconstruction with a fibula flap were included in this study. There was a significant correlation between the HU value and BMD at 1 week, 3 months, and 6 months after surgery, and both were significantly correlated with follow-up time. The difference between each pair of absorption rates (DAR) was less than 10% in 66.7% and 75.9% of patients at 3 and 6 months; however, the DAR was more than 20% in 12% and 13.8% of patients at 3 and 6 months, respectively.

CONCLUSIONS

There is a significant correlation between HU value and BMD. The HU value can be used to roughly reflect the fibular BMD changing trend in a group of patients as opposed to an individual, and the HU value is not equivalent to BMD.

TRIAL REGISTRATION

ChiCTR, ChiCTR2300069661, retrospectively registered on 22 March 2023. Retrospectively registered, https://www.chictr.org.cn/showproj.html?proj=188953 .

Opportunistic Computed Tomography Screening for Osteoporosis and Fracture

Osteoporosis is underdiagnosed and undertreated, leading to loss of treatment for the patient and high costs for the health care system. Routine thoracic and/or abdominal computed tomography (CT) performed for other indications can screen opportunistically for osteoporosis with no extra cost, time, or irradiation. Various methods can quantify fracture risk on opportunistic clinical CT: vertebral Hounsfield unit bone mineral density (BMD), usually of L1; BMD measurement with asynchronous or internal calibration; quantitative CT; bone texture assessment; and finite element analysis. Screening for osteoporosis and vertebral fractures on opportunistic CT is a promising approach, providing automated fracture risk scores by means of artificial intelligence, thus enabling earlier management.

Comparison of volumetric and areal bone mineral density in CT and scout scans using spectral detector technology

BACKGROUND

To determine whether denoised areal bone mineral density (BMD) measurements from scout scans in spectral detector computed tomography (CT) correlate with volumetric trabecular BMD for opportunistic osteoporosis screening.

METHODS

A 64-slice single-source dual-layer spectral CT scanner was used to acquire scout scan data of 228 lumbar vertebral bodies within 57 patients. Scout scans in anterior-posterior (AP) view were performed with a dose of < 0.06 mSv and spectrally decomposed into areal BMD (aBMD) values. A spectral dictionary denoising algorithm was applied to increase the signal-to-noise ratio (SNR). Volumetric trabecular bone mineral density (vBMD) was determined via material decomposition. A 3D convolutional network for image segmentation and labeling was applied for automated vBMD quantification. Projected maps were used to compare the classification accuracy of AP and lateral scout scans.

RESULTS

The denoising algorithm led to the minimization of anticorrelated noise in spectral maps and an SNR increase from 5.23 to 13.4 (p < 0.002). Correlation analysis between vBMD and measured AP aBMD, projected AP, and lateral aBMD showed a Pearson correlation coefficient of 0.68, 0.81, and 0.90, respectively. The sensitivity and specificity for the osteoporosis classification task were higher in lateral projection images than in AP crystallizing in an increased area under the curve value of 0.99 versus 0.90.

CONCLUSION

Denoised material-specific aBMD maps show a positive correlation to vBMD, enabling spectral scout scans as an opportunistic predictor for osteoporotic patients. This could be applied routinely as a screening tool in patients undergoing a CT examination.

RELEVANCE STATEMENT

Scout-based DEXA could be applied routinely as a screening tool in patients undergoing a CT examination.

KEY POINTS

• Spectral scout scans can be used as a dual-energy x-ray absorptiometry-like screening tool. • Spectral dictionary denoising on projection images increases the signal-to-noise ratio. • Positive correlation between volumetric and areal bone mineral density is observed. • Lateral projections increase osteoporosis classification accuracy compared to anterior-posterior projections.

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.

Dark-field X-ray imaging for the assessment of osteoporosis in human lumbar spine specimens

Background: Dark-field imaging is a novel imaging modality that allows for the assessment of material interfaces by exploiting the wave character of x-ray. While it has been extensively studied in chest imaging, only little is known about the modality for imaging other tissues. Therefore, the purpose of this study was to evaluate whether a clinical X-ray dark-field scanner prototype allows for the assessment of osteoporosis. Materials and methods: In this prospective study we examined human cadaveric lumbar spine specimens (vertebral segments L2 to L4). We used a clinical prototype for dark-field radiography that yields both attenuation and dark-field images. All specimens were scanned in lateral orientation in vertical and horizontal position. All specimens were additionally imaged with CT as reference. Bone mineral density (BMD) values were derived from asynchronously calibrated quantitative CT measurements. Correlations between attenuation signal, dark-field signal and BMD were assessed using Spearman's rank correlation coefficients. The capability of the dark-field signal for the detection of osteoporosis/osteopenia was evaluated with receiver operating characteristics (ROC) curve analysis. Results: A total of 58 vertebrae from 20 human cadaveric spine specimens (mean age, 73 years ±13 [standard deviation]; 11 women) were studied. The dark-field signal was positively correlated with the BMD, both in vertical (r = 0.56, p < .001) and horizontal position (r = 0.43, p < .001). Also, the dark-field signal ratio was positively correlated with BMD (r = 0.30, p = .02). No correlation was found between the signal ratio of attenuation signal and BMD (r = 0.14, p = .29). For the differentiation between specimens with and without osteoporosis/osteopenia, the area under the ROC curve (AUC) was 0.80 for the dark-field signal in vertical position. Conclusion: Dark-field imaging allows for the differentiation between spine specimens with and without osteoporosis/osteopenia and may therefore be a potential biomarker for bone stability.

Incidental vertebral fracture prediction using neuronal network-based automatic spine segmentation and volumetric bone mineral density extraction from routine clinical CT scans

Objectives

To investigate vertebral osteoporotic fracture (VF) prediction by automatically extracted trabecular volumetric bone mineral density (vBMD) from routine CT, and to compare the model with fracture prevalence-based prediction models.

Methods

This single-center retrospective study included patients who underwent two thoraco-abdominal CT scans during clinical routine with an average inter-scan interval of 21.7 ± 13.1 months (range 5-52 months). Automatic spine segmentation and vBMD extraction was performed by a convolutional neural network framework (anduin.bonescreen.de). Mean vBMD was calculated for levels T5-8, T9-12, and L1-5. VFs were identified by an expert in spine imaging. Odds ratios (ORs) for prevalent and incident VFs were calculated for vBMD (per standard deviation decrease) at each level, for baseline VF prevalence (yes/no), and for baseline VF count (n) using logistic regression models, adjusted for age and sex. Models were compared using Akaike's and Bayesian information criteria (AIC & BIC).

Results

420 patients (mean age, 63 years ± 9, 276 males) were included in this study. 40 (25 female) had prevalent and 24 (13 female) had incident VFs. Individuals with lower vBMD at any spine level had higher odds for VFs (L1-5, prevalent VF: OR,95%-CI,p: 2.2, 1.4-3.5,p=0.001; incident VF: 3.5, 1.8-6.9,p<0.001). In contrast, VF status (2.15, 0.72-6.43,p=0.170) and count (1.38, 0.89-2.12,p=0.147) performed worse in incident VF prediction. Information criteria revealed best fit for vBMD-based models (AIC vBMD=165.2; VF status=181.0; count=180.7).

Conclusions

VF prediction based on automatically extracted vBMD from routine clinical MDCT outperforms prediction models based on VF status and count. These findings underline the importance of opportunistic quantitative osteoporosis screening in clinical routine MDCT data.

Prevalence and influencing factors of hyperuricemia in middle-aged and older adults in the Yao minority area of China: a cross-sectional study

Hyperuricemia (HUA) endangers human health, and its prevalence has increased rapidly in recent decades. The current study investigated HUA's prevalence and influencing factors in Gongcheng, southern China. A cross-sectional investigation was conducted; 2128 participants aged 30-93 years were included from 2018 to 2019. Univariate and multivariate logistic regression models were used to screen HUA variables. A Bayesian network model was constructed using the PC algorithm to evaluate the association between influencing factors and HUA. The prevalence of HUA was 15.6% (23.2% in men, 10.7% in women). After screening the variables using a logistic regression analysis model, fatty liver disease (FLD), dyslipidemia, abdominal obesity, creatinine (CREA), somatotype, bone mass, drinking, and physical activity level at work were included in the Bayesian network model. The model results showed that dyslipidemia, somatotype, CREA, and drinking were directly related to HUA. Bone mass and FLD were indirectly associated with HUA by affecting the somatotype. The prevalence of HUA in Gongcheng was high in China. The prevalence of HUA was related to somatotype, drinking, bone mass, physical activity level at work, and other metabolic diseases. A good diet and moderate exercise are recommended to maintain a healthy somatotype and reduce the prevalence rate of HUA.

Automated Opportunistic Trabecular Volumetric Bone Mineral Density Extraction Outperforms Manual Measurements for the Prediction of Vertebral Fractures in Routine CT

Opportunistic osteoporosis screening using multidetector CT-scans (MDCT) and convolutional neural network (CNN)-derived segmentations of the spine to generate volumetric bone mineral density (vBMD) bears the potential to improve incidental osteoporotic vertebral fracture (VF) prediction. However, the performance compared to the established manual opportunistic vBMD measures remains unclear. Hence, we investigated patients with a routine MDCT of the spine who had developed a new osteoporotic incidental VF and frequency matched to patients without incidental VFs as assessed on follow-up MDCT images after 1.5 years. Automated vBMD was generated using CNN-generated segmentation masks and asynchronous calibration. Additionally, manual vBMD was sampled by two radiologists. Automated vBMD measurements in patients with incidental VFs at 1.5-years follow-up (n = 53) were significantly lower compared to patients without incidental VFs (n = 104) (83.6 ± 29.4 mg/cm³ vs. 102.1 ± 27.7 mg/cm³, p < 0.001). This comparison was not significant for manually assessed vBMD (99.2 ± 37.6 mg/cm³ vs. 107.9 ± 33.9 mg/cm³, p = 0.30). When adjusting for age and sex, both automated and manual vBMD measurements were significantly associated with incidental VFs at 1.5-year follow-up, however, the associations were stronger for automated measurements (β = -0.32; 95% confidence interval (CI): -20.10, 4.35; p < 0.001) compared to manual measurements (β = -0.15; 95% CI: -11.16, 5.16; p < 0.03). In conclusion, automated opportunistic measurements are feasible and can be useful for bone mineral density assessment in clinical routine.

Diagnostic Accuracy of Dual-Energy CT Material Decomposition Technique for Assessing Bone Status Compared with Quantitative Computed Tomography

PURPOSE

The purpose of this study was to evaluate the diagnostic accuracy when using various base material pairs (BMPs) in dual-energy computed tomography (DECT), and to establish corresponding diagnostic standards for assessing bone status through comparison with quantitative computed tomography (QCT).

METHODS

This prospective study enrolled a total of 469 patients who underwent both non-enhanced chest CT scans under conventional kVp and abdominal DECT. The bone densities of hydroxyapatite (water), hydroxyapatite (fat), hydroxyapatite (blood), calcium (water), and calcium (fat) (D_{HAP (water)}, D_{HAP (fat)}, D_{HAP (blood)}, D_{Ca (water)}, and D_{Ca (fat)}) in the trabecular bone of vertebral bodies (T11-L1) were measured, along with bone mineral density (BMD) via QCT. Intraclass correlation coefficient (ICC) analysis was used to assess the agreement of the measurements. Spearman's correlation test was performed to analyze the relationship between the DECT- and QCT-derived BMD. Receiver operator characteristic (ROC) curves were generated to determine the optimal diagnostic thresholds of various BMPs for diagnosing osteopenia and osteoporosis.

RESULTS

A total of 1371 vertebral bodies were measured, and QCT identified 393 with osteoporosis and 442 with osteopenia. Strong correlations were observed between D_{HAP (water)}, D_{HAP (fat)}, D_{HAP (blood)}, D_{Ca (water)}, and D_{Ca (fat)} and the QCT-derived BMD. D_{HAP (water)} showed the best predictive capability for osteopenia and osteoporosis. The area under the ROC curve, sensitivity, and specificity for identifying osteopenia were 0.956, 86.88%, and 88.91% with D_{HAP (water)} ≤ 107.4 mg/cm³, respectively. The corresponding values for identifying osteoporosis were 0.999, 99.24%, and 99.53% with D_{HAP (water)} ≤ 89.62 mg/cm³, respectively.

CONCLUSIONS

Bone density measurement using various BMPs in DECT enables the quantification of vertebral BMD and the diagnosis of osteoporosis, with D_{HAP (water)} having the highest diagnostic accuracy.

Quantitative CT screening improved lumbar BMD evaluation in older patients compared to dual-energy X-ray absorptiometry

BACKGROUND

Robust evidence on whether diagnostic discordance exists between lumbar osteoporosis detected by quantitative computed tomography (QCT) vs. dual-energy X-ray absorptiometry (DXA) is still lacking. In this study involving a relatively large prospective cohort of older men (aged > 60 years) and postmenopausal women, we assessed lumbar QCT-derived volumetric bone mineral density (vBMD) and DXA-derived area BMD and evaluated their predictive performance for prevalent vertebral fracture (VF).

METHODS

A total of 501 patients who underwent spinal surgery from September 2020 to September 2022 were enrolled. The criteria recommended by the American College of Radiology and the World Health Organization were used for lumbar osteoporosis diagnosis. The osteoporosis detection rates between QCT and DXA were compared. QCT-vBMD was plotted against the DXA T score, and the line of best fit was calculated based on linear regression. Multivariate logistic regression was used to analyze the associations between risk factors and VF. Receiver operating characteristic curve analysis was performed, and the corresponding area under the curve (AUC) was calculated.

RESULTS

QCT screening showed that 60.7% of patients had osteoporosis, whereas DXA screening showed that 50.7% of patients had osteoporosis. Diagnoses were concordant for 325 (64.9%) patients. In all, 205 patients suffered a VF of at least one anatomic level. Of these, 84.4% (173/205) were diagnosed with osteoporosis by QCT, while only 73.2% (150/205) were diagnosed by DXA. Multivariate logistic regression showed that osteoporosis detected by QCT exhibited a stronger relationship with VF than that detected by DXA (unadjusted OR, 6.81 vs. 5.04; adjusted OR, 3.44 vs. 2.66). For discrimination between patients with and without VF, QCT-vBMD (AUC = 0.802) showed better performance than DXA T score (AUC = 0.76).

CONCLUSION

In older patients undergoing spinal surgery, QCT-vBMD is more helpful than DXA in terms of osteoporosis detection rate and prediction of patients with prevalent VFs.

Addressing gaps in osteoporosis screening in kuwait using opportunistic quantitative computer tomography (QCT): a retrospective study

Osteoporosis is a common skeletal disorder which is underdiagnosed and undertreated. Consequent fragility fractures are associated with high morbidity and mortality. Prevention of these fractures is possible by timely osteoporosis screening followed by timely therapeutic interventions when needed. Utilizing all available modalities such as bone density measurements on preexisting CT scans could help narrow the diagnostic gap.

PURPOSE

To demonstrate the feasibility and clinical utility of opportunistic osteoporosis screening in Kuwait using QCT, aiming to increase screening rates in a country with a relatively high prevalence of osteoporosis and an alarming trend of increasing incidence of fractures.

METHODS

At a tertiary referral center, all abdominal CT scans performed on females ≥60 years old between 12/2020 and 12/2021 were retrospectively utilized for asynchronous QCT acquisition. The average volumetric bone mineral density (vBMD) was calculated, and rates of osteoporosis (vBMD < 80 mg/cm³ calcium hydroxyapatite) and osteopenia (80-120 mg/cm³) were determined. CT images were reviewed to assess for the presence of vertebral fractures. For each patient, the electronic health record was reviewed for any previous DXA scans.

RESULTS

vBMD was calculated in 305 females ≥60 years old (mean [SD] 71 [8.7], range 60-93). Low bone mass was detected in 258 patients (84.6%); 148 (48.5%) met criteria for osteopenia and 110 (36.1%) for osteoporosis. Osteoporotic vertebral fractures were observed in 64 (21.0%) study participants. Only 73 patients (23.9% of total) had a previous DXA documented in the reviewed health records. For 231 patients who were ≥65 years old, who would routinely qualify for a screening DXA, only 63 (27.3%) had a documented DXA available.

CONCLUSION

vBMD measurements obtained by opportunistic QCT had comparable rates of osteopenia and osteoporosis detection to those previously reported using DXA in a similar population in Kuwait. These findings suggest that opportunistic QCT on preexisting CT scans can be effectively utilized to narrow gaps in osteoporosis screening.

A Novel Cervical Vertebral Bone Quality Score Independently Predicts Cage Subsidence After Anterior Cervical Diskectomy and Fusion

BACKGROUND

Surgeons can preoperatively assess bone quality using dual-energy X-ray absorptiometry or computed tomography; however, this is not feasible for all patients. Recently, a MRI-based scoring system was used to evaluate the lumbar spine's vertebral bone quality.

OBJECTIVE

To create a similar MRI-based scoring system for the cervical spine (C-VBQ), correlate C-VBQ scores with computed tomography-Hounsfield units (HU), and evaluate the utility of this scoring system to independently predict cage subsidence after single-level anterior cervical diskectomy and fusion (ACDF).

METHODS

Demographic, procedure-related, and radiographic data were collected for patients. Pearson correlation test was used to determine the correlation between C-VBQ and HU. Cage subsidence was defined as ≥3 mm loss of fusion segmental height. A multivariate logistic regression model was built to determine the correlation between potential risk factors for subsidence.

RESULTS

Of 59 patients who underwent single-level ACDF, subsidence was found in 17 (28.8%). Mean C-VBQ scores were 2.22 ± 0.36 for no subsidence levels and 2.83 ± 0.38 ( P < .001) for subsidence levels. On multivariate analysis, a higher C-VBQ score was significantly associated with subsidence (odds ratio = 1.85, 95% CI = 1.39-2.46, P < .001) and was the only significant independent predictor of subsidence after ACDF. There was a significant negative correlation between HU and C-VBQ (r 2 = -0.49, P < .001).

CONCLUSION

We found that a higher C-VBQ score was significantly associated with cage subsidence after ACDF. Furthermore, there was a significant negative correlation between C-VBQ and HU. The C-VBQ score may be a valuable tool for assessing preoperative bone quality and independently predicting cage subsidence after ACDF.

New Horizons: Artificial Intelligence Tools for Managing Osteoporosis

Osteoporosis is a disease characterized by low bone mass and microarchitectural deterioration leading to increased bone fragility and fracture risk. Typically, osteoporotic fractures occur at the spine, hip, distal forearm, and proximal humerus, but other skeletal sites may be affected as well. One of the major challenges in the management of osteoporosis lies in the fact that although the operational diagnosis is based on bone mineral density (BMD) as measured by dual x-ray absorptiometry, the majority of fractures occur at nonosteoporotic BMD values. Furthermore, osteoporosis often remains undiagnosed regardless of the low severity of the underlying trauma. Also, there is only weak consensus among the major guidelines worldwide, when to treat, whom to treat, and which drug to use. Against this background, increasing efforts have been undertaken in the past few years by artificial intelligence (AI) developers to support and improve the management of this disease. The performance of many of these newly developed AI algorithms have been shown to be at least comparable to that of physician experts, or even superior. However, even if study results appear promising at a first glance, they should always be interpreted with caution. Use of inadequate reference standards or selection of variables that are of little or no value in clinical practice are limitations not infrequently found. Consequently, there is a clear need for high-quality clinical research in this field of AI. This could, eg, be achieved by establishing an internationally consented "best practice framework" that considers all relevant stakeholders.

Three-Dimensional Hounsfield Units Measurement of Pedicle Screw Trajectory for Predicating Screw Loosening in Lumbar Fusion Surgery

Purpose

Dual-energy X-ray absorptiometry (DXA) is commonly used for evaluation of bone mineral density before spinal surgery, but frequently leads to overestimation in degenerative spinal diseases due to osteoproliferation factors. We introduce a novel method to compare the predictive ability of Hounsfield Units (HU) and DXA methods to predict screw loosening after lumbar interbody fusion surgery in degenerative spinal diseases by measuring HU of pedicle screw trajectory on computed tomography (CT) images preoperatively.

Patients and Methods

This retrospective study was conducted on patients who underwent posterior lumbar fusion surgery for degenerative diseases. CT HUs measurement was performed using medical imaging software, including the cancellous region on cross-sections of the vertebral body and three-dimensional pedicle screw trajectory. Receiver operating characteristic (ROC) curve analyses were performed for the risk of pedicle screw loosening in association with the Hounsfield scale and preoperative BMD, and the area under the curve (AUC) and the cutoff values were calculated.

Results

A total of 90 patients were enrolled and were divided into loosening (n = 33, 36.7%) and non-loosening groups (n = 57, 63.3%). No significant differences in age, gender, length of fixation and preoperative BMD were found between both groups. The loosening group showed lower CT HU values in the vertebral body and screw trajectory than the non-loosening group. Screw trajectory HU (ST-HU) exhibited a higher AUC value than vertebral body HU (B-HU). The cutoff values of B-HU and ST-HU were 160 and 110 HUs, respectively.

Conclusion

Three-dimensional pedicle screw trajectory HU values yields a stronger predictive value than vertebral body HU values and BMD and may provide more guidance for surgery. The risk of screw loosening is significantly increased at ST-HU <110 or B-HU <160 at L₅ segment.

Diagnosis of Osteoporosis by Quantifying Volumetric Bone Mineral Density of Lumbar Vertebrae Using Abdominal CT Images and Two-Compartment Model

With the aging population, osteoporosis has become an important public health issue. The purpose of this study was to establish a two-compartment model (TCM) to quantify the volumetric bone mineral density (vBMD) of the lumbar spine using abdominal computed tomography (CT) images. The TCM approach uses water as the bone marrow equivalent and K₂HPO₄ solution as the cortical bone equivalent. A phantom study was performed to evaluate the accuracy of vBMD estimation at 100 kVp and 120 kVp. The data of 180 patients who underwent abdominal CT imaging and dual-energy X-ray absorptiometry (DXA) within one month were retrospectively collected. vBMD of L1-L4 vertebrae were calculated, and the receiver-operating characteristic curve analysis was performed to establish the diagnostic thresholds for osteoporosis and osteopenia in terms of vBMD. The average difference between the measured vBMD following TCM and the theoretical vBMD of the self-made phantom was 0.2%, and the maximum difference was 0.5%. vBMD of lumbar vertebrae obtained from TCM and aBMD obtained by DXA had a significant positive correlation (r = 0.655 to 0.723). The average diagnostic threshold for osteoporosis was 0.116 g/cm³. The sensitivity, specificity, and accuracy were 95.7%, 75.6.5%, and 80.0%, respectively. The average diagnostic threshold for osteopenia was 0.126 g/cm³. The sensitivity, specificity, and accuracy were 81.3%, 82.5%, and 82.7%, respectively. The aforementioned threshold values were used to perform the diagnostics on a test cohort, and the performance was equivalent to that in the experimental cohort. From the perspective of preventive medicine, opportunistic screening of bone mineral density using abdominal CT images and the TCM approach can facilitate early detection of osteoporosis and osteopenia and, with in-time treatment, slow down their progression.