Quantitative computed tomography and opportunistic bone density screening by dual use of computed tomography scans

Low bone mineral density: a primer for the spine surgeon

Within spinal surgery, low bone mineral density is associated with several postoperative complications, such as proximal junctional kyphosis, pseudoarthrosis, and screw loosening. Although modalities such as CT and MRI can be utilized to assess bone quality, DEXA scans, the "Gold Standard" for diagnosing osteoporosis, is not routinely included in preoperative workup. With an increasing prevalence of osteoporosis in an aging population, it is critical for spine surgeons to understand the importance of evaluating bone mineral density preoperatively to optimize postoperative outcomes. The purpose of this state-of-the-art review is to provide surgeons a summary of the evaluation, treatment, and implications of low bone mineral density in patients who are candidates for spine surgery.

Estimating lumbar bone mineral density from conventional MRI and radiographs with deep learning in spine patients

PURPOSE

This study aimed to develop machine learning methods to estimate bone mineral density and detect osteopenia/osteoporosis from conventional lumbar MRI (T1-weighted and T2-weighted images) and planar radiography in combination with clinical data and imaging parameters of the acquisition protocol.

METHODS

A database of 429 patients subjected to lumbar MRI, radiographs and dual-energy x-ray absorptiometry within 6 months was created from an institutional database. Several machine learning models were trained and tested (373 patients for training, 86 for testing) with the following objectives: (1) direct estimation of the vertebral bone mineral density; (2) classification of T-score lower than - 1 or (3) lower than - 2.5. The models took as inputs either the images or radiomics features derived from them, alone or in combination with metadata (age, sex, body size, vertebral level, parameters of the imaging protocol).

RESULTS

The best-performing models achieved mean absolute errors of 0.15-0.16 g/cm2 for the direct estimation of bone mineral density, and areas under the receiver operating characteristic curve of 0.82 (MRIs) - 0.80 (radiographs) for the classification of T-scores lower than - 1, and 0.80 (MRIs) - 0.65 (radiographs) for T-scores lower than - 2.5.

CONCLUSIONS

The models showed good discriminative performances in detecting cases of low bone mineral density, and more limited capabilities for the direct estimation of its value. Being based on routine imaging and readily available data, such models are promising tools to retrospectively analyse existing datasets as well as for the opportunistic investigation of bone disorders.

Artificial intelligence-enhanced opportunistic screening of osteoporosis in CT scan: a scoping Review

PURPOSE

This scoping review aimed to assess the current research on artificial intelligence (AI)--enhanced opportunistic screening approaches for stratifying osteoporosis and osteopenia risk by evaluating vertebral trabecular bone structure in CT scans.

METHODS

PubMed, Scopus, and Web of Science databases were systematically searched for studies published between 2018 and December 2023. Inclusion criteria encompassed articles focusing on AI techniques for classifying osteoporosis/osteopenia or determining bone mineral density using CT scans of vertebral bodies. Data extraction included study characteristics, methodologies, and key findings.

RESULTS

Fourteen studies met the inclusion criteria. Three main approaches were identified: fully automated deep learning solutions, hybrid approaches combining deep learning and conventional machine learning, and non-automated solutions using manual segmentation followed by AI analysis. Studies demonstrated high accuracy in bone mineral density prediction (86-96%) and classification of normal versus osteoporotic subjects (AUC 0.927-0.984). However, significant heterogeneity was observed in methodologies, workflows, and ground truth selection.

CONCLUSIONS

The review highlights AI's promising potential in enhancing opportunistic screening for osteoporosis using CT scans. While the field is still in its early stages, with most solutions at the proof-of-concept phase, the evidence supports increased efforts to incorporate AI into radiologic workflows. Addressing knowledge gaps, such as standardizing benchmarks and increasing external validation, will be crucial for advancing the clinical application of these AI-enhanced screening methods. Integration of such technologies could lead to improved early detection of osteoporotic conditions at a low economic cost.

Assessing osteoporosis and bone mineral density through 18F-NaF uptake at lumbar spine

OBJECTIVES

The use of 18F-Sodium fluoride (NaF) PET/CT is established in the detection of metastatic bone disease, yet its utility in osteoporosis remains underexplored. This research aims to assess the variations in 18F-NaF uptake among individuals with differing bone mineral density (BMD) and to examine the relationship between 18F-NaF uptake and BMD.

METHODS

In this retrospective study, 199 patients (average age 56 ± 6, comprising 52 males and 147 females) with a history of cancer were analyzed. Each participant underwent both 18F-NaF PET/CT and lumbar dual-energy X-ray absorptiometry (DXA) scans within a span of 7 days. Based on DXA outcomes, patients and their lumbar vertebrae were categorized into normal BMD, osteopenia, and osteoporosis groups. The lumbar 18F-NaF uptake across these groups were compared, and to explore the association between lumbar standardized uptake values (SUV) values and BMD. The efficacy of 18F-NaF uptake in diagnosing osteoporosis or osteopenia was also evaluated. Analysis was conducted using Mann-Whitney U tests, Spearman regression, and receiver operating characteristic (ROC) curve analysis through GraphPad Prism 10.0.

RESULTS

A total of 796 lumbar vertebrae from 199 patients were measured. It was observed that osteoporotic patients had significantly lower 18F-NaF uptake than those with osteopenia and normal BMD across the L1-L4 lumbar vertebrae (P < 0.0001). In a vertebra-based analysis, normal BMD vertebrae exhibited the highest maximum SUV(SUVmax) compared to osteopenic (8.13 ± 1.28 vs. 6.61 ± 1.01, P < 0.0001) and osteoporotic vertebrae (8.13 ± 1.28 vs. 4.82 ± 1.01, P < 0.0001). There was a positive correlation between lumbar 18F-NaF uptake and BMD across all vertebrae, with correlation coefficients exceeding 0.5 (range: 0.57-0.8). The area under the ROC curve values were notably high, at 0.96 for osteoporosis and 0.83 for osteopenia diagnosis.

CONCLUSION

This study demonstrates distinct 18F-NaF uptake patterns among individuals with varying BMD levels, with a positive correlation between 18F-NaF uptake and BMD. These findings highlight the potential of 18F-NaF PET/CT as a supportive diagnostic method in the management of osteoporosis.

CT in musculoskeletal imaging: still helpful and for what?

Computed tomography (CT) is a common modality employed for musculoskeletal imaging. Conventional CT techniques are useful for the assessment of trauma in detection, characterization and surgical planning of complex fractures. CT arthrography can depict internal derangement lesions and impact medical decision making of orthopedic providers. In oncology, CT can have a role in the characterization of bone tumors and may elucidate soft tissue mineralization patterns. Several advances in CT technology have led to a variety of acquisition techniques with distinct clinical applications. These include four-dimensional CT, which allows examination of joints during motion; cone-beam CT, which allows examination during physiological weight-bearing conditions; dual-energy CT, which allows material decomposition useful in musculoskeletal deposition disorders (e.g., gout) and bone marrow edema detection; and photon-counting CT, which provides increased spatial resolution, decreased radiation, and material decomposition compared to standard multi-detector CT systems due to its ability to directly translate X-ray photon energies into electrical signals. Advanced acquisition techniques provide higher spatial resolution scans capable of enhanced bony microarchitecture and bone mineral density assessment. Together, these CT acquisition techniques will continue to play a substantial role in the practices of orthopedics, rheumatology, metabolic bone, oncology, and interventional radiology.

Reproducibility of CT-based opportunistic vertebral volumetric bone mineral density measurements from an automated segmentation framework

BACKGROUND

To investigate the reproducibility of automated volumetric bone mineral density (vBMD) measurements from routine thoracoabdominal computed tomography (CT) assessed with segmentations by a convolutional neural network and automated correction of contrast phases, on diverse scanners, with scanner-specific asynchronous or scanner-agnostic calibrations.

METHODS

We obtained 679 observations from 278 CT scans in 121 patients (77 males, 63.6%) studied from 04/2019 to 06/2020. Observations consisted of two vBMD measurements from Δdifferent reconstruction kernels (n = 169), Δcontrast phases (n = 133), scan Δsessions (n = 123), Δscanners (n = 63), or Δall of the aforementioned (n = 20), and observations lacking scanner-specific calibration (n = 171). Precision was assessed using root-mean-square error (RMSE) and root-mean-square coefficient of variation (RMSCV). Cross-measurement agreement was assessed using Bland-Altman plots; outliers within 95% confidence interval of the limits of agreement were reviewed.

RESULTS

Repeated measurements from Δdifferent reconstruction kernels were highly precise (RMSE 3.0 mg/cm3; RMSCV 1.3%), even for consecutive scans with different Δcontrast phases (RMSCV 2.9%). Measurements from different Δscan sessions or Δscanners showed decreased precision (RMSCV 4.7% and 4.9%, respectively). Plot-review identified 12 outliers from different scan Δsessions, with signs of hydropic decompensation. Observations with Δall differences showed decreased precision compared to those lacking scanner-specific calibration (RMSCV 5.9 and 3.7, respectively).

CONCLUSION

Automatic vBMD assessment from routine CT is precise across varying setups, when calibrated appropriately. Low precision was found in patients with signs of new or worsening hydropic decompensation, what should be considered an exclusion criterion for both opportunistic and dedicated quantitative CT.

RELEVANCE STATEMENT

Automated CT-based vBMD measurements are precise in various scenarios, including cross-session and cross-scanner settings, and may therefore facilitate opportunistic screening for osteoporosis and surveillance of BMD in patients undergoing routine clinical CT scans.

KEY POINTS

Artificial intelligence-based tools facilitate BMD measurements in routine clinical CT datasets. Automated BMD measurements are highly reproducible in various settings. Reliable, automated opportunistic osteoporosis diagnostics allow for large-scale application.

Medial Calcar Density Measured via Opportunistic Computed Tomography Is Well Represented by the Dorr C Classification

Introduction The canal-to-calcar isthmus (CC) ratio has been previously correlated with proximal femur osteology, but its relationship with bone density is not well established. Our purpose was to assess the relationship between femoral bone density, measured on opportunistic quantitative CT in Hounsfield units (HU), and CC ratio. Methods A total of 148 THA patients were included. The CC ratio was measured on anteroposterior hip radiographs. Using perioperative CT scans, a 1 cm diameter area was identified on a single mid-coronal slice in the medial calcar just proximal to the intertrochanteric ridge. The mean HU was calculated in this region to represent calcar bone density. Results Twenty-four percent (n = 35) of patients were classified as Dorr A (average CC ratio 0.47 [0.45; 0.48]), 67% (n = 96) as Dorr B (0.62 [0.55; 0.68]), and 11% (n = 17) as Dorr C (0.78 [0.77; 0.80]). There was a significant difference between Dorr A and Dorr C femurs (769 (144) vs. 588 (154) HU) as well as between B and C femurs (718 (166) vs. 588 (154) HU). The CC ratio was correlated with calcar bone density on CT (-0.370). Conclusion CC ratio is correlated with bone density determined by HU measurements on an opportunistic quantitative computed tomography scan, and bone density HU values were able to accurately differentiate bone density in Dorr A and B from Dorr C femurs. These findings suggest that the CC ratio is a reliable measurement to predict bone density in Dorr C femurs. Therefore, arthroplasty surgeons can confidently use the Dorr classification for patients with Dorr C femurs when preoperatively planning for THA.

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.

Assessing lumbar vertebral bone quality: a methodological evaluation of CT and MRI as alternatives to traditional DEXA

PURPOSE

The purpose of this study was to investigate the impact of various methods on the assessment of vertebral bone quality.

METHODS

A consecutive series of 427 candidates for lumbar disc replacement with lumbar DEXA and MRI and/or CT scans were included. Two measurement techniques were used on CTs-a sagittal and axial. From axial images, the upper, mid, and lower portions of each vertebral body were measured. Four MRI vertebral bone quality (VBQ) calculations were generated using separate equations.

RESULTS

All CT measures were highly correlated with each other, regardless of measurement or calculation method (range 0.925-0.995). Sagittal measurements were highly correlated with axial (r = 0.928, p < 0.001). CT values were correlated with DEXA (range 0.446-0.534). There was no benefit to measuring multiple axial images of each vertebral body vs. just midbody (r = 0.441 and 0.455, respectively). No MRI VBQ values were highly correlated with DEXA (r =  -  0.103, p = 0.045). In receiver operating curve analysis, the area under the curve ranged from 0.539 to 0.558, indicating poor ability of VBQ to identify osteoporosis/osteopenia.

CONCLUSION

CT produced values more closely related to DEXA, while MRI was less reliable for osteoporosis/osteopenia screening. On CT, there was no benefit to making multiple measurements for each vertebral body to calculate a composite. Measuring sagittal CT images produced values similar to axial and required less time. While assessing bone quality from existing images rather than getting an additional DEXA scan is appealing, the methods of measuring these images needs standardization to maximize their utility.

Opportunistic Evaluation of Trabecular Bone Texture by MRI Reflects Bone Mineral Density and Microarchitecture

CONTEXT

Many individuals at high risk for fracture are never evaluated for osteoporosis and subsequently do not receive necessary treatment. Utilization of magnetic resonance imaging (MRI) is burgeoning, providing an ideal opportunity to use MRI to identify individuals with skeletal deficits. We previously reported that MRI-based bone texture was more heterogeneous in postmenopausal women with a history of fracture compared to controls.

OBJECTIVE

The present study aimed to identify the microstructural characteristics that underlie trabecular texture features.

METHODS

In a prospective cohort, we measured spine volumetric bone mineral density (vBMD) by quantitative computed tomography (QCT), peripheral vBMD and microarchitecture by high-resolution peripheral QCT (HRpQCT), and areal BMD (aBMD) by dual-energy x-ray absorptiometry. Vertebral trabecular bone texture was analyzed using T1-weighted MRIs. A gray level co-occurrence matrix was used to characterize the distribution and spatial organization of voxelar intensities and derive the following texture features: contrast (variability), entropy (disorder), angular second moment (ASM; uniformity), and inverse difference moment (IDM; local homogeneity).

RESULTS

Among 46 patients (mean age 64, 54% women), lower peripheral vBMD and worse trabecular microarchitecture by HRpQCT were associated with greater texture heterogeneity by MRI-higher contrast and entropy (r ∼ -0.3 to 0.4, P < .05), lower ASM and IDM (r ∼ +0.3 to 0.4, P < .05). Lower spine vBMD by QCT was associated with higher contrast and entropy (r ∼ -0.5, P < .001), lower ASM and IDM (r ∼ +0.5, P < .001). Relationships with aBMD were less pronounced.

CONCLUSION

MRI-based measurements of trabecular bone texture relate to vBMD and microarchitecture, suggesting that this method reflects underlying microstructural properties of trabecular bone. Further investigation is required to validate this methodology, which could greatly improve identification of patients with skeletal fragility.

MRI-based vertebral bone quality score compared to quantitative computed tomography bone mineral density in patients undergoing cervical spinal surgery

PURPOSE

The vertebral bone quality (VBQ) score based on magnetic resonance imaging (MRI) was introduced as a bone quality marker in the lumbar spine. Prior studies showed that it could be utilized as a predictor of osteoporotic fracture or complications after instrumented spine surgery. The objective of this study was to evaluate the correlation between VBQ scores and bone mineral density (BMD) measured by quantitative computer tomography (QCT) in the cervical spine.

METHODS

Preoperative cervical CT and sagittal T1-weighted MRIs from patients undergoing ACDF were retrospectively reviewed and included. The VBQ score in each cervical level was calculated by dividing the signal intensity of the vertebral body by the signal intensity of the cerebrospinal fluid on midsagittal T1-weighted MRI images and correlated with QCT measurements of the C2-T1 vertebral bodies. A total of 102 patients (37.3% female) were included.

RESULTS

VBQ values of C2-T1 vertebrae strongly correlated with each other. C2 showed the highest VBQ value [Median (range) 2.33 (1.33, 4.23)] and T1 showed the lowest VBQ value [Median (range) 1.64 (0.81, 3.88)]. There was significant weak to moderate negative correlations between and VBQ Scores for all levels [C2: p < 0.001; C3: p < 0.001; C4: p < 0.001; C5: p < 0.004; C6: p < 0.001; C7: p < 0.025; T1: p < 0.001].

CONCLUSION

Our results indicate that cervical VBQ scores may be insufficient in the estimation of BMDs, which might limit their clinical application. Additional studies are recommended to determine the utility of VBQ and QCT BMD to evaluate their potential use as bone status markers.

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.

Emerging Role of 18F-NaF PET/Computed Tomographic Imaging in Osteoporosis: A Potential Upgrade to the Osteoporosis Toolbox

Osteoporosis is a metabolic bone disorder that leads to a decline in bone microarchitecture, predisposing individuals to catastrophic fractures. The current standard of care relies on detecting bone structural change; however, these methods largely miss the complex biologic forces that drive these structural changes and response to treatment. This review introduces sodium fluoride (18F-NaF) positron emission tomography/computed tomography (PET/CT) as a powerful tool to quantify bone metabolism. Here, we discuss the methods of 18F-NaF PET/CT, with a special focus on dynamic scans to quantify parameters relevant to bone health, and how these markers are relevant to osteoporosis.

The role of opportunistic quantitative computed tomography in the evaluation of bone disease and risk of fracture in thalassemia major

OBJECTIVE

Dual-energy X-ray absorptiometry (DXA) remains the cornerstone for osteoporosis evaluation in Thalassemia major. However, several drawbacks have been observed in this unique setting. We sought to determine the correlation between quantitative CT (QCT) and DXA-derived parameters; secondarily, we aimed to investigate the role of the two techniques in predicting the risk of fracture.

METHODS

We retrospectively included patients with β-thalassemia major who had undergone both lumbar and femoral DXA examinations, and CT scans including the lumbar spine, performed for disparate diagnostic issues, within 4 months from the DXA. CT data were examined employing a phantom-less QCT method for bone mineral density (BMD) assessment. We also retrieved any spontaneous or fragility fractures occurring from 1 year before up to 5 years after the date of DXA scans.

RESULTS

The 43 patients were included. QCT measures were significantly higher than those determined by DXA. The gap between QCT and DXA values was strongly associated with patient age. The most powerful predictive variable for risk of fracture was the ACR classification based on volumetric BMD obtained by QCT.

CONCLUSIONS

DXA provided more negative measures than those determined by QCT. However, QCT seemed to evaluate thalassaemic osteopathy better than DXA, since volumetric BMD was a stronger predictor of fracture.

Asynchronous calibration of quantitative computed tomography bone mineral density assessment for opportunistic osteoporosis screening: phantom-based validation and parameter influence evaluation

Asynchronous calibration could allow opportunistic screening based on routine CT for early osteoporosis detection. In this phantom study, a bone mineral density (BMD) calibration phantom and multi-energy CT (MECT) phantom were imaged on eight different CT scanners with multiple tube voltages (80-150 kV_p) and image reconstruction settings (e.g. soft/hard kernel). Reference values for asynchronous BMD estimation were calculated from the BMD-phantom and validated with six calcium composite inserts of the MECT-phantom with known ground truth. Relative errors/changes in estimated BMD were calculated and investigated for influence of tube voltage, CT scanner and reconstruction setting. Reference values for 282 acquisitions were determined, resulting in an average relative error between calculated BMD and ground truth of - 9.2% ± 14.0% with a strong correlation (R² = 0.99; p < 0.0001). Tube voltage and CT scanner had a significant effect on calculated BMD (p < 0.0001), with relative differences in BMD of 3.8% ± 28.2% when adapting reference values for tube voltage, - 5.6% ± 9.2% for CT scanner and 0.2% ± 0.2% for reconstruction setting, respectively. Differences in BMD were small when using reference values from a different CT scanner of the same model (0.0% ± 1.4%). Asynchronous phantom-based calibration is feasible for opportunistic BMD assessment based on CT images with reference values adapted for tube voltage and CT scanner model.

A Mini Review on Osteoporosis: From Biology to Pharmacological Management of Bone Loss

Osteoporosis refers to excessive bone loss as reflected by the deterioration of bone mass and microarchitecture, which compromises bone strength. It is a complex multifactorial endocrine disease. Its pathogenesis relies on the presence of several endogenous and exogenous risk factors, which skew the physiological bone remodelling to a more catabolic process that results in net bone loss. This review aims to provide an overview of osteoporosis from its biology, epidemiology and clinical aspects (detection and pharmacological management). The review will serve as an updated reference for readers to understand the basics of osteoporosis and take action to prevent and manage this disease.

Quantitative Assessment of Pancreatic Fat by Quantitative CT in Type 2 Diabetes Mellitus

Objective

To characterize the pancreatic fat deposition (PFD) in patients with type 2 diabetes mellitus (T2DM) by quantitative computed tomography (QCT) and investigate the relationship between PFD and clinical metabolic parameters and islet function.

Materials and Methods

A total of 150 patients with T2DM and 93 age-matched healthy subjects underwent QCT to quantify PFD were included. PFD and various biochemical parameters were correlated by statistical methods and multiple stepwise linear regression modeling.

Results

PFD measured by QCT in the T2DM group was statistically higher than that in the healthy control group, and the pancreatic CT value was statistically lower than that in the control group. The QCT measured PFD was negatively correlated with the pancreatic CT values (P < 0.001), and positively correlated with triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), visceral fat area (VAT) and insulin resistance index (HOMA-IR) (P < 0.05) in the T2DM patients. Multiple stepwise linear regression analysis identified PFD as the dependent variable factor for T2DM.

Conclusion

This study suggests QCT as a reliable technique in measuring PFD in T2DM. High PFD is positively correlated with the degree of insulin resistance and may play an important role in islet cell dysfunction in T2DM.

Osteoporosis diagnosis in knee X-rays by transfer learning based on convolution neural network

Osteoporosis degrades the quality of bones and is the primary cause of fractures in the elderly and women after menopause. The high diagnostic and treatment costs urge the researchers to find a cost-effective diagnostic system to diagnose osteoporosis in the early stages. X-ray imaging is the cheapest and most common imaging technique to detect bone pathologies butmanual interpretation of x-rays for osteoporosis is difficult and extraction of required features and selection of high-performance classifiers is a very challenging task. Deep learning systems have gained the popularity in image analysis field over the last few decades. This paper proposes a convolution neural network (CNN) based approach to detect osteoporosis from x-rays. In our study, we have used the transfer learning of deep learning-based CNNs namely AlexNet, VggNet-16, ResNet, and VggNet -19 to classify the x-ray images of knee joints into normal, osteopenia, and osteoporosis disease groups. The main objectives of the current study are: (i) to present a dataset of 381 knee x-rays medically validated by the T-scores obtained from the Quantitative Ultrasound System, and (ii) to propose a deep learning approach using transfer learning to classify different stages of the disease. The performance of these classifiers is compared and the best accuracy of 91.1% is achieved by pretrained Alexnet architecture on the presented dataset with an error rate of 0.09 and validation loss of 0.54 as compared to the accuracy of 79%, an error rate of 0.21, and validation loss of 0.544 when pretrained network was not used.. The results of the study suggest that a deep learning system with transfer learning can help clinicians to detect osteoporosis in its early stages hence reducing the risk of fractures.

Predicting Lumbar Vertebral Osteopenia Using LvOPI Scores and Logistic Regression Models in an Exploratory Study of Premenopausal Taiwanese Women

Purpose

To propose hybrid predicting models integrating clinical and magnetic resonance imaging (MRI) features to diagnose lumbar vertebral osteopenia (LvOPI) in premenopausal women.

Methods

This prospective study enrolled 101 Taiwanese women, including 53 before and 48 women after menopause. Clinical information, including age, body height, body weight and body mass index (BMI), were recorded. Bone mineral density (BMD) was measured by the dual-energy X-ray absorptiometry. Lumbar vertebral fat fraction (LvFF) was measured by MRI. LvOPI scores (LvOPISs) comprising different clinical features and LvFF were constructed to diagnose LvOPI. Statistical analyses included normality tests, linear regression analyses, logistic regression analyses, group comparisons, and diagnostic performance. A P value less than 0.05 was considered as statistically significant.

Results

The post-menopausal women had higher age, body weight, BMI, LvFF and lower BMD than the pre-menopausal women (all P < 0.05). The lumbar vertebral osteoporosis group had significantly higher age, longer MMI, and higher LvFF than the LvOPI group (all P < 0.05) and normal group (all P < 0.005). LvOPISs (AUC, 0.843 to 0.864) outperformed body weight (0.747; P = 0.0566), BMI (0.737; P < 0.05), age (0.649; P < 0.05), and body height (0.5; P < 0.05) in diagnosing LvOPI in the premenopausal women. Hybrid predicting models using logistic regression analysis (0.894 to 0.9) further outperformed all single predictors in diagnosing LvOPI in the premenopausal women (P < 0.05).

Conclusion

The diagnostic accuracy of the LvOPI can be improved by using our proposed hybrid predicting models in Taiwanese premenopausal women.

BMD accuracy errors specific to phantomless calibration of CT scans of the lumbar spine

Opportunistic screening using existing CT images may be a new strategy to identify subjects at increased risk for osteoporotic fracture. Low bone mineral density (BMD) is a key parameter but routine clinical CT scans do not include a calibration phantom to calculate BMD from the measured CT values. An alternative is internal or phantomless calibration, which is based on the CT values of air and of internal tissues of the subject such as blood, muscle or adipose tissue. However, the composition and as a consequence the CT values of these so-called internal calibration materials vary among subjects, which introduces additional BMD accuracy errors compared to phantom based calibration. The objective of this study was to quantify these accuracy errors and to identify optimum combinations of internal calibration materials (IM) for BMD assessments in opportunistic screening. Based on the base material decomposition theory we demonstrate how BMD can be derived from the CT values of the internal calibration materials. 121 CT datasets of the lumbar spine form postmenopausal women were used to determine the population variance of blood assessed in the aorta or the inferior vena cava, skeletal muscle of the erector spinae or psoas, subcutaneous adipose tissue (SAT) and air. The corresponding standard deviations were used for error propagation to determine phantomless calibration related BMD accuracy errors. Using a CT value of 150 HU, a typical value of trabecular bone, simulated BMD accuracy errors for most IM combinations containing air as one of the two base materials were below 5% or 6 mg/cm³. The lowest errors were determined for the combination of blood and air (<2 mg/cm³). The combination of blood and skeletal muscle resulted in higher errors (>10.5% or >12 mg/cm³) and is not recommended. Due to possible age-related differences in tissue composition, the selection of IMs is suggested to be adapted according to the measured subject. In younger subjects without significant aortic calcifications, air and blood of the aorta may be the best combination whereas in elderly subjects, air and SAT (error of 4%) may be preferable. The use of skeletal muscle as one of the two IMs is discouraged, in particular in elderly subjects because of varying fatty infiltration. A practical implementation of the internal calibration with different IM pairs confirmed the theoretical results. In summary, compared to a phantom based calibration the phantomless approach used for opportunistic screening creates additional BMD accuracy errors of 2% or more, dependent on the used internal reference tissues. The impact on fracture prediction still must be evaluated.

Use of 3-D Models for Surgical Planning of a Malunion in a Dog

Background

An 8-year-old, 18.9 kg, male, intact Kai Ken with a femoral shaft fracture experienced recurrent implant breakage after two fracture reductions using an internal fixator.

Objectives

This case report is aimed at using a three-dimensional (3-D) printer to diagnose residual femoral rotational deviation. Implant failures and malunion occurred after two attempts at synthesis. Thus, a 3-D model was designed for preoperative planning of a third surgery.

Methods

To evaluate the alignment in the postoperative state after the second surgery, we removed a broken plate from the affected limb. Subsequently, a computed tomography image produced a bone replica using 3-D printing. The distal fragment was fixed and rotated externally by 42°. In addition to correcting the rotational deformity of the femur, we used an intramedullary pin and two locking plates to stabilize the proximal and distal femoral fracture segments.

Results

The bone union was confirmed four months after surgery, and no postoperative complications were observed 11 months after surgery.

Conclusion

3-D printing is a valuable tool that increases the accuracy of presurgical planning.

Should Q-CT Be the Gold Standard for Detecting Spinal Osteoporosis?

STUDY DESIGN

Prospective comparative study.

OBJECTIVE

Refinement of the guidelines for screening of osteoporosis and considering quantitative computed tomography (Q-CT) for detecting spinal osteoporosis.

SUMMARY OF BACKGROUND DATA

Spinal osteoporosis is often underestimated and under-evaluated due to either lack of availability of the diagnostic modality or lack of awareness about the possibility of overestimation by dual X-ray absorptiometry (DXA) scan. There is a need for reconsidering osteoporosis evaluation with a site specific and patient specific inclination.

METHODS

Post-menopausal women that underwent bone mineral density (BMD) evaluation from January-2018 to December-2020 with either Q-CT or DXA were evaluated. Comparison studies of the distribution of age and T-scores of the bone densities obtained from the two study groups: age-matched, sex-matched, and common skeletal site of interest (L1-4 vertebrae) were performed. Mann-Whitney U test, correlation and regression analyses were performed and bell curves were plotted.

RESULTS

Of the 718 women evaluated, 447 underwent Q-CT and 271 underwent DXA. There was no significant difference among the age distribution of the two study groups (P-value > 0.05). The mean and mode T-scores obtained by Q-CT and DXA were found to be -2.71, -3.8 and -1.63, -1.7 respectively. A highly significant difference in the T-scores was observed in the Q-CT and DXA groups (P-value < 0.0001). Among those who were screened by Q-CT, 58.16% were osteoporotic, 37.58% were osteopenic, and 4.25% were normal. The respective percentages in the DXA group were 30.63%, 49.82%, and 19.55%.

CONCLUSION

Q-CT provides more precise estimation of cancellous bone mineral density than DXA. With the reliance on DXA for spinal BMD estimation being questionable, new standards have to be established for spinal osteoporosis evaluation. Q-CT can be a better alternative to replace DXA as the gold standard for the evaluation of spinal osteoporosis.Level of Evidence: 2.

Prospective comparative study of quantitative X-ray (QXR) versus dual energy X-ray absorptiometry to determine the performance of QXR as a predictor of bone health for adult patients in secondary care

OBJECTIVES

To evaluate a method of quantitative X-ray (QXR) for obtaining bone health information from standard radiographs aimed at identifying early signs of osteoporosis to enable improved referral and treatment. This QXR measurement is performed by postexposure analysis of standard radiographs, meaning bone health data can be acquired opportunistically, alongside routine imaging.

DESIGN

The relationship between QXR and dual energy X-ray absorptiometry (DEXA) was demonstrated with a phantom study. A prospective clinical study was conducted to establish areal bone mineral density (aBMD) prediction model and a risk prediction model of a non-normal DEXA outcome. This was then extrapolated to a larger patient group with DEXA referral data.

SETTING

Secondary care National Health Service Hospital.

PARTICIPANTS

126 consenting adult patients from a DEXA clinic.

INTERVENTIONS

All participants underwent a DEXA scan to determine BMD at the lumbar spine (L2-L4) and both hips. An additional Antero-Posterior pelvis X-ray on a Siemens Ysio, fixed digital radiograph system was performed for the study.

OUTCOME

Performance of QXR as a risk predictor for non-normal (osteoporotic) BMD.

RESULTS

Interim clinical study data from 78 patients confirmed a receiver operator curve (area under the ROC curve) of 0.893 (95% CI 0.843 to 0.942) for a risk prediction model of non-normal DEXA outcome. Extrapolation of these results to a larger patient group of 11 029 patients indicated a positive predictive value of 0.98 (sensitivity of 0.8) for a population of patients referred to DEXA under current clinical referral criteria.

CONCLUSIONS

This study confirms that the novel QXR method provides accurate prediction of a DEXA outcome.

TRIAL REGISTRATION NUMBER

ISRCTN98160454; Pre-results.

Accuracy and precision of volumetric bone mineral density assessment using dual-source dual-energy versus quantitative CT: a phantom study

BACKGROUND

Dual-source dual-energy computed tomography (DECT) offers the potential for opportunistic osteoporosis screening by enabling phantomless bone mineral density (BMD) quantification. This study sought to assess the accuracy and precision of volumetric BMD measurement using dual-source DECT in comparison to quantitative CT (QCT).

METHODS

A validated spine phantom consisting of three lumbar vertebra equivalents with 50 (L1), 100 (L2), and 200 mg/cm3 (L3) calcium hydroxyapatite (HA) concentrations was scanned employing third-generation dual-source DECT and QCT. While BMD assessment based on QCT required an additional standardised bone density calibration phantom, the DECT technique operated by using a dedicated postprocessing software based on material decomposition without requiring calibration phantoms. Accuracy and precision of both modalities were compared by calculating measurement errors. In addition, correlation and agreement analyses were performed using Pearson correlation, linear regression, and Bland-Altman plots.

RESULTS

DECT-derived BMD values differed significantly from those obtained by QCT (p < 0.001) and were found to be closer to true HA concentrations. Relative measurement errors were significantly smaller for DECT in comparison to QCT (L1, 0.94% versus 9.68%; L2, 0.28% versus 5.74%; L3, 0.24% versus 3.67%, respectively). DECT demonstrated better BMD measurement repeatability compared to QCT (coefficient of variance < 4.29% for DECT, < 6.74% for QCT). Both methods correlated well to each other (r = 0.9993; 95% confidence interval 0.9984-0.9997; p < 0.001) and revealed substantial agreement in Bland-Altman plots.

CONCLUSIONS

Phantomless dual-source DECT-based BMD assessment of lumbar vertebra equivalents using material decomposition showed higher diagnostic accuracy compared to QCT.

Opportunistic diagnosis of osteoporosis, fragile bone strength and vertebral fractures from routine CT scans; a review of approved technology systems and pathways to implementation

Osteoporosis causes bones to become weak, porous and fracture more easily. While a vertebral fracture is the archetypal fracture of osteoporosis, it is also the most difficult to diagnose clinically. Patients often suffer further spine or other fractures, deformity, height loss and pain before diagnosis. There were an estimated 520,000 fragility fractures in the United Kingdom (UK) in 2017 (costing £4.5 billion), a figure set to increase 30% by 2030. One way to improve both vertebral fracture identification and the diagnosis of osteoporosis is to assess a patient's spine or hips during routine computed tomography (CT) scans. Patients attend routine CT for diagnosis and monitoring of various medical conditions, but the skeleton can be overlooked as radiologists concentrate on the primary reason for scanning. More than half a million CT scans done each year in the National Health Service (NHS) could potentially be screened for osteoporosis (increasing 5% annually). If CT-based screening became embedded in practice, then the technique could have a positive clinical impact in the identification of fragility fracture and/or low bone density. Several companies have developed software methods to diagnose osteoporosis/fragile bone strength and/or identify vertebral fractures in CT datasets, using various methods that include image processing, computational modelling, artificial intelligence and biomechanical engineering concepts. Technology to evaluate Hounsfield units is used to calculate bone density, but not necessarily bone strength. In this rapid evidence review, we summarise the current literature underpinning approved technologies for opportunistic screening of routine CT images to identify fractures, bone density or strength information. We highlight how other new software technologies have become embedded in NHS clinical practice (having overcome barriers to implementation) and highlight how the novel osteoporosis technologies could follow suit. We define the key unanswered questions where further research is needed to enable the adoption of these technologies for maximal patient benefit.

Opportunistic application of phantom-less calibration methods for fracture risk prediction using QCT/FEA

OBJECTIVES

Quantitative computed tomography (QCT)-based finite element analysis (FEA) implements a calibration phantom to estimate bone mineral density (BMD) and assign material properties to the models. The objectives of this study were to (1) propose robust phantom-less calibration methods, using subject-specific tissues, to obtain vertebral fracture properties estimations using QCT/FEA; and (2) correlate QCT/FEA predictions to DXA values of areal BMD.

METHODS

Eighty of a cohort of 111 clinical QCT scans were used to obtain subject-specific parameters using a phantom calibration approach and for the development of the phantom-less calibration equations. Equations were developed based on the HU measured from various soft tissues and regions, and using multiple linear regression analyses. Thirty-one additional QCT scans were used for cross-validation of QCT/FEA estimated fracture loads from the L₃ vertebrae based on the phantom and phantom-less equations. Finally, QCT/FEA-predicted fracture loads were correlated with aBMD obtained from DXA.

RESULTS

Overall, 217 QCT/FEA models from 31 subjects (20 females, 11 men) with mean ages of 69.6 (13.1) and 67.3 (14) were used to cross-validate the phantom-less equations and assess bone strength. The proposed phantom-less equations showed high correlations with phantom-based estimates of BMD (99%). Cross-validation of QCT/FEA-predicted fracture loads from phantom-less equations and phantom-specific outcomes resulted in high correlations for all proposed methods (0.94-0.99). QCT/FEA correlation outcomes from the phantom-less equations and DXA-aBMD were moderately high (0.64-0.68).

CONCLUSIONS

The proposed QCT/FEA subject-specific phantom-less calibration methods demonstrated the potential to be applied to both prospective and retrospective applications in the clinical setting.

KEY POINTS

• QCT/FEA overcomes the disadvantages of DXA and improves fracture properties predictions of vertebrae. • QCT/FEA fracture estimates using the phantom-less approach highly correlated to values obtained using a calibration phantom. • QCT/FEA prediction using a phantom-less approach is an accurate alternative over phantom-based methods.

MDCT-Based Finite Element Analyses: Are Measurements at the Lumbar Spine Associated with the Biomechanical Strength of Functional Spinal Units of Incidental Osteoporotic Fractures along the Thoracolumbar Spine?

Assessment of osteoporosis-associated fracture risk during clinical routine is based on the evaluation of clinical risk factors and T-scores, as derived from measurements of areal bone mineral density (aBMD). However, these parameters are limited in their ability to identify patients at high fracture risk. Finite element models (FEMs) have shown to improve bone strength prediction beyond aBMD. This study aims to investigate whether FEM measurements at the lumbar spine can predict the biomechanical strength of functional spinal units (FSUs) with incidental osteoporotic vertebral fractures (VFs) along the thoracolumbar spine. Multi-detector computed tomography (MDCT) data of 11 patients (5 females and 6 males, median age: 67 years) who underwent MDCT twice (median interval between baseline and follow-up MDCT: 18 months) and sustained an incidental osteoporotic VF between baseline and follow-up scanning were used. Based on baseline MDCT data, two FSUs consisting of vertebral bodies and intervertebral discs (IVDs) were modeled: one standardly capturing L1-IVD-L2-IVD-L3 (FSU_L1-L3) and one modeling the incidentally fractured vertebral body at the center of the FSU (FSU_F). Furthermore, volumetric BMD (vBMD) derived from MDCT, FEM-based displacement, and FEM-based load of the single vertebrae L1 to L3 were determined. Statistically significant correlations (adjusted for a BMD ratio of fracture/L1-L3 segments) were revealed between the FSU_F and mean load of L1 to L3 (r = 0.814, p = 0.004) and the mean vBMD of L1 to L3 (r = 0.745, p = 0.013), whereas there was no statistically significant association between the FSU_F and FSU_L1-L3 or between FSU_F and the mean displacement of L1 to L3 (p > 0.05). In conclusion, FEM measurements of single vertebrae at the lumbar spine may be able to predict the biomechanical strength of incidentally fractured vertebral segments along the thoracolumbar spine, while FSUs seem to predict only segment-specific fracture risk.

A Review on Multiscale Bone Damage: From the Clinical to the Research Perspective

The investigation of bone damage processes is a crucial point to understand the mechanisms of age-related bone fractures. In order to reduce their impact, early diagnosis is key. The intricate architecture of bone and the complexity of multiscale damage processes make fracture prediction an ambitious goal. This review, supported by a detailed analysis of bone damage physical principles, aims at presenting a critical overview of how multiscale imaging techniques could be used to implement reliable and validated numerical tools for the study and prediction of bone fractures. While macro- and meso-scale imaging find applications in clinical practice, micro- and nano-scale imaging are commonly used only for research purposes, with the objective to extract fragility indexes. Those images are used as a source for multiscale computational damage models. As an example, micro-computed tomography (micro-CT) images in combination with micro-finite element models could shed some light on the comprehension of the interaction between micro-cracks and micro-scale bone features. As future insights, the actual state of technology suggests that these models could be a potential substitute for invasive clinical practice for the prediction of age-related bone fractures. However, the translation to clinical practice requires experimental validation, which is still in progress.

Predicting Vertebral Bone Strength Using Finite Element Analysis for Opportunistic Osteoporosis Screening in Routine Multidetector Computed Tomography Scans-A Feasibility Study

Purpose

To investigate the feasibility of using routine clinical multidetector computed tomography (MDCT) scans for conducting finite element (FE) analysis to predict vertebral bone strength for opportunistic osteoporosis screening.

Methods

Routine abdominal MDCT with and without intravenous contrast medium (IVCM) of seven subjects (five male; two female; mean age: 71.86 ± 7.40 years) without any bone disease were used. FE analysis was performed on individual vertebrae (T11, T12, L1, and L2) including the posterior elements to investigate the effect of IVCM and slice thickness (1 and 3 mm) on vertebral bone strength. Another subset of data from subjects with vs. without osteoporotic vertebral fractures (n = 9 age and gender-matched pairs) was analyzed for investigating the ability of FE-analysis to differentiate the two cohorts. Bland-Altman plots, box plots, and coefficient of correlation (R2) were calculated to determine the variations in FE-predicted failure loads for different conditions.

Results

The FE-predicted failure loads obtained from routine MDCT scans were strongly correlated with those from without IVCM (R2 = 0.91 for 1mm; R2 = 0.92 for 3mm slice thickness, respectively) and different slice thicknesses (R2 = 0.93 for 1mm vs. 3mm with IVCM). Furthermore, a good correlation was observed for 3mm slice thickness with IVCM vs. 1mm without IVCM (R2 = 0.87). Significant difference between FE-predicted failure loads of healthy and fractured patients was observed (4,705 ± 1,238 vs. 4,010 ± 1,297 N; p=0.026).

Conclusion

Routine clinical MDCT scans could be reliably used for assessment of fracture risk based on FE analysis and may be beneficial for patients who are at increased risk for osteoporotic fractures.

Biomechanical effects of posterior pedicle screw-based instrumentation using titanium versus carbon fiber reinforced PEEK in an osteoporotic spine human cadaver model

BACKGROUND

Aim of this biomechanical investigation was to compare the biomechanical effects of a carbon fiber reinforced PEEK and titanium pedicle screw/rod device in osteoporotic human cadaveric spine.

METHODS

Ten human fresh-frozen cadaveric lumbar spines (L1-L5) have been used and were randomized into two groups according to the bone mineral density. A monosegmental posterior instrumentation (L3-L4) using titanium pedicle screws and rods was carried out in group A and using carbon fiber reinforced PEEK in group B. A cyclic loading test was performed at a frequency of 3 Hz, starting with a peak of 500 N for the first 2000 cycles, up to 950 N for 100,000 cycles under a general preload with 100 N. All specimens were evaluated with regard to a potential collapse of the implanted pedicle screws. A CT supported digital measurement of cavities around the pedicle at 3 defined measuring points was performed. Finally, the maximum zero-time failure load of all specimens was determined using a universal testing machine (80% F_max).

FINDINGS

Regarding maximum axial force (group A: 2835 N, group B: 3006 N, p = 0.595) and maximum compression (group A: 11.67 mm, group B: 15.15 mm, p = 0.174) no statistical difference could be shown between the two groups. However, significant smaller cavity formation around the pedicle screws could be observed in group B (p = 0.007), especially around the screw tip (p < 0.001).

INTERPRETATION

Carbon fiber reinforced PEEK devices seem to be advantageous in terms of microscopic screw loosening compared to titanium devices.

Evaluation of Goose-beak Bone Particles for Dentoalveolar Reconstruction in Dogs

BACKGROUND/AIM

Tooth extraction is a common procedure in dental clinics. Tooth extraction can destroy gingiva, alveolar bone, periodontal ligaments and cement. If dental sockets are left as extracted, it will result in loss of teeth, as well as voice and aesthetic problems. A natural hydroxyapatite (HA) bioceramic bone graft substitute developed from goose-beak bone particles (GBPs) was used for dentoalveolar reconstruction in a canine model.

MATERIALS AND METHODS

Four adult (18-22 months old) male beagle dogs weighing 8.2-9.6 kg were included in the study. Eight alveolar extraction sockets in the four dogs were divided randomly into two groups and a split-mouth design was established; control group, socket filled with commercial synthetic HA; tested group, socket filled with granulated GBP.

RESULTS

Micro-CT analysis and hematoxylin and eosin and Masson's trichrome staining of non-decalcified sections were undertaken. Examination revealed that dentoalveolar reconstruction was initiated from the periphery of the host bone, and newly formed bone was well integrated with the GBP. Bone apposition was observed at the edge of the host bone-GBP interface.

CONCLUSION

A natural ceramic powder obtained from GBP is suitable for use in dentoalveolar reconstruction in dogs.

High detection rate of osteoporosis with screening of a general hospitalized population: a 6-year study in 6406 patients in a university hospital setting

Background

Osteoporosis is a highly prevalent disease identified by Dual Energy X-ray Absorptiometry (DEXA) that can be performed in an ambulatory (out-patient) or hospitalized population. We evaluated the use of baseline in-hospital DEXA screening to identify osteoporosis in ambulatory care and hospitalized patients; we also assessed specific risk factors for osteoporosis among these populations.

Methods

We included a baseline initial DEXA from 6406 consecutive patients at our tertiary referral University Hospital.

Results

Osteoporosis was diagnosed in 22.3% of the study population. In univariate analysis, osteoporosis risk factors were age, fracture history and low BMI (for all 3 sites), but also corticotherapy (lumbar spine and femoral neck) and male (lumbar spine). In multivariate analysis, age, fracture history, low BMI, and male increased osteoporosis risk. In-hospital screening yielded a higher percentage of osteoporosis positive scans than ambulatory care screening (31.8% vs 18.5%, p < 0.001). In-hospital screening targeted an older and more predominantly male population with a higher fracture history. Z-scores revealed that this difference was not only due to an older age of the population and mainly concerned cortical bone.

Conclusions

In-hospital osteoporosis screening revealed more osteoporosis than screening in ambulatory practice and could be an additional tool to improve the identification and management of osteoporosis. In addition to typical risk factors, we identified male gender as associated with osteoporosis detection in our cohort.

Finite Element Analysis-Based Vertebral Bone Strength Prediction Using MDCT Data: How Low Can We Go?

Objective: To study the impact of dose reduction in MDCT images through tube current reduction or sparse sampling on the vertebral bone strength prediction using finite element (FE) analysis for fracture risk assessment. Methods: Routine MDCT data covering lumbar vertebrae of 12 subjects (six male; six female; 74.70 ± 9.13 years old) were included in this study. Sparsely sampled and virtually reduced tube current-based MDCT images were computed using statistical iterative reconstruction (SIR) with reduced dose levels at 50, 25, and 10% of the tube current and original projections, respectively. Subject-specific static non-linear FE analyses were performed on vertebra models (L1, L2, and L3) 3-D-reconstructed from those dose-reduced MDCT images to predict bone strength. Coefficient of correlation (R²), Bland-Altman plots, and root mean square coefficient of variation (RMSCV) were calculated to find the variation in the FE-predicted strength at different dose levels, using high-intensity dose-based strength as the reference. Results: FE-predicted failure loads were not significantly affected by up to 90% dose reduction through sparse sampling (R² = 0.93, RMSCV = 8.6% for 50%; R² = 0.89, RMSCV = 11.90% for 75%; R² = 0.86, RMSCV = 11.30% for 90%) and up to 50% dose reduction through tube current reduction method (R² = 0.96, RMSCV = 12.06%). However, further reduction in dose with the tube current reduction method affected the ability to predict the failure load accurately (R² = 0.88, RMSCV = 22.04% for 75%; R² = 0.43, RMSCV = 54.18% for 90%). Conclusion: Results from this study suggest that a 50% radiation dose reduction through reduced tube current and a 90% radiation dose reduction through sparse sampling can be used to predict vertebral bone strength. Our findings suggest that the sparse sampling-based method performs better than the tube current-reduction method in generating images required for FE-based bone strength prediction models.

Opportunistic screening for osteoporosis using thoraco-abdomino-pelvic CT-scan assessing the vertebral density in rheumatoid arthritis patients

INTRODUCTION

Screening for osteoporosis is crucial in rheumatoid arthritis (RA) patients. The aim of this study was to assess the value of thoraco-abdomino-pelvic CT-derived bone mineral density (BMD) results in L1, compared to dual energy X-ray absorptiometry (DXA) results for osteoporosis screening in rheumatoid arthritis patients.

METHODS

Consecutive RA patients who underwent a CT-scan and DXA within a 2-year period were retrospectively included. The CT sagittal images were then evaluated for vertebral fractures from T4 to L5 using the Genant classification. The CT-attenuation values (in Hounsfield units (HU)) of trabecular bone in L1 were measured on axial images and compared to the DXA results.

RESULTS

This study included 105 patients (mean age 61.1 years (± 9.5), 78.1% women). There were 28 patients (26.7%) with DXA-defined osteoporosis and 32 (30%) with osteoporotic fractures (vertebral and/or non-vertebral). The CT assessment indicated that the mean (SD) vertebral L1 attenuation was 142.2 HU (± 18.5). The diagnostic performance for the vertebral CT-attenuation measurement was acceptable: the AUC was 0.67 for predicting osteoporotic fractures and of 0.69 for predicting vertebral fractures. Among patients with osteoporotic fractures, there were 23 (74%) patients categorized as osteoporotic with a L1 CT-attenuation of 135 HU or less, whereas there were only 13 patients (42%) identified by DXA.

CONCLUSION

CT offers a combined opportunistic screening for osteoporosis by assessing both vertebral fractures and bone density on routine CT-scans. This approach may be particularly interesting for RA patients with a high osteoporosis risk.

DXA-equivalent quantification of bone mineral density using dual-layer spectral CT scout scans

OBJECTIVES

To develop and evaluate a method for areal bone mineral density (aBMD) measurement based on dual-layer spectral CT scout scans.

METHODS

A post-processing algorithm using a pair of 2D virtual mono-energetic scout images (VMSIs) was established in order to semi-automatically compute the aBMD at the spine similarly to DXA, using manual soft tissue segmentation, semi-automatic segmentation for the vertebrae, and automatic segmentation for the background. The method was assessed based on repetitive measurements of the standardized European Spine Phantom (ESP) using the standard scout scan tube current (30 mA) and other tube currents (10 to 200 mA), as well as using fat-equivalent extension rings simulating different patient habitus, and was compared to dual-energy X-ray absorptiometry (DXA). Moreover, the feasibility of the method was assessed in vivo in female patients.

RESULTS

Derived from standard scout scans, aBMD values measured with the proposed method significantly correlated with DXA measurements (r = 0.9925, p < 0.001), and mean accuracy (DXA, 4.12%; scout, 1.60%) and precision (DXA, 2.64%; scout, 2.03%) were comparable between the two methods. Moreover, aBMD values assessed at different tube currents did not differ significantly (p ≥ 0.20 for all), suggesting that the presented method could be applied to scout scans with different settings. Finally, data derived from sample patients were concordant with BMD values from a reference age-matched population.

CONCLUSIONS

Based on dual-layer spectral scout scans, aBMD measurements were fast and reliable and significantly correlated with the according DXA measurements in phantoms. Considering the number of CT acquisitions performed worldwide, this method could allow truly opportunistic osteoporosis screening.

KEY POINTS

• 2D scout scans (localizer radiographs) from a dual-layer spectral CT scanner, which are mandatory parts of a CT examination, can be used to automatically determine areal bone mineral density (aBMD) at the spine. • The presented method allowed fast (< 25 s/patient), semi-automatic, and reliable DXA-equivalent aBMD measurements for state-of-the-art DXA phantoms at different tube settings and for various patient habitus, as well as for sample patients. • Considering the number of CT scout scan acquisitions performed worldwide on a daily basis, the presented technique could enable truly opportunistic osteoporosis screening with DXA-equivalent metrics, without involving higher radiation exposure since it only processes existing data that is acquired during each CT scan.

Opportunistic Screening for Osteoporosis Using Computed Tomography: State of the Art and Argument for Paradigm Shift

PURPOSE OF REVIEW

Osteoporosis is disproportionately common in rheumatology patients. For the past three decades, the diagnosis of osteoporosis has benefited from well-established practice guidelines that emphasized the use of dual x-ray absorptiometry (DXA). Despite these guidelines and the wide availability of DXA, approximately two thirds of eligible patients do not undergo testing. One strategy to improve osteoporosis testing is to employ computed tomography (CT) examinations obtained as part of routine patient care to "opportunistically" screen for osteoporosis, without additional cost or radiation exposure to patients. This review examines the role of opportunistic CT in the evaluation of osteoporosis.

RECENT FINDINGS

Recent evidence suggests that opportunistic measurement of bone attenuation (radiodensity) using CT has sensitivity comparable to DXA. More importantly, such an approach has been shown to predict osteoporotic fractures. The paradigm shift of using CTs obtained for other reasons to opportunistically screen for osteoporosis promises to substantially improve patient care.

Fracture Prediction by Computed Tomography and Finite Element Analysis: Current and Future Perspectives

PURPOSE OF REVIEW

This review critiques the ability of CT-based methods to predict incident hip and vertebral fractures.

RECENT FINDINGS

CT-based techniques with concurrent calibration all show strong associations with incident hip and vertebral fracture, predicting hip and vertebral fractures as well as, and sometimes better than, dual-energy X-ray absorptiometry areal biomass density (DXA aBMD). There is growing evidence for use of routine CT scans for bone health assessment. CT-based techniques provide a robust approach for osteoporosis diagnosis and fracture prediction. It remains to be seen if further technical advances will improve fracture prediction compared to DXA aBMD. Future work should include more standardization in CT analyses, establishment of treatment intervention thresholds, and more studies to determine whether routine CT scans can be efficiently used to expand the number of individuals who undergo evaluation for fracture risk.

Current and Emerging Diagnostic Imaging-Based Techniques for Assessment of Osteoporosis and Fracture Risk

Osteoporosis is a metabolic bone disorder characterized by low bone mass, degradation of bone microarchitecture, and susceptibility to fracture. It is a growing major health concern across the world, especially in the elderly population. Osteoporosis can cause hip or spinal fractures that may lead to high morbidity and socio-economic burden. Therefore, there is a need for early diagnosis of osteoporosis and prediction of fragility fracture risk. In this review, state of the art and recent advances in imaging techniques for diagnosis of osteoporosis and fracture risk assessment have been explored. Segmentation methods used to segment the regions of interest and texture analysis methods used for classification of healthy and osteoporotic subjects are also presented. Furthermore, challenges posed by the current diagnostic tools have been studied and feasible solutions to circumvent the limitations are discussed. Early diagnosis of osteoporosis and prediction of fracture risk require the development of highly precise and accurate low-cost diagnostic techniques that would help the elderly population in low economies.

Quantitative Computed Tomography-Current Status and New Developments

This review focuses on new developments and current controversies in the field of quantitative computed tomography. Recent positions of the International Society for Clinical Densitometry acknowledged the clinical value of quantitative computed tomography of the spine and the hip using clinical whole-body computed tomography (CT) scanners. Opportunistic screening summarizes a number of new approaches describing the dual use of clinical CT scans. For example, CT scans may have been taken for tumor diagnosis but may also be used for the prediction of high or low fracture risks as an additional benefit for the patient. The assessment of the cortical parameters is another topic of current research. In CT images of the spine and the hip, a number of techniques have been developed to determine the thickness, mass, and bone density of the cortex. In higher-spatial resolution peripheral CT images of the radius and tibia obtained from special purpose scanners, 1 focus is the measurement of cortical porosity. Two different approaches, one based on the direct segmentation of the pores and one based on cortical density, will be reviewed.

Multicenter analysis of CIREN occupant lumbar bone mineral density and correlation with age and fracture incidence

OBJECTIVE

This study aimed to quantify lumbar volumetric bone mineral density (vBMD) for 873 seriously injured Crash Injury Research and Engineering Network (CIREN) motor vehicle crash occupants (372 male, 501 female) from 8 centers using phantomless computed tomography scans and to associate vBMD with age, fracture incidence, and osteopenia/osteoporosis diagnoses. The novelty of this work is that it associates vBMD with region of injury by applying an established method for vBMD measurement using phantomless computed tomography (CT).

METHODS

A validated phantomless CT calibration method that uses patient-specific fat and muscle measurements to calibrate vBMD measured from the L1-L5 trabeculae was applied on 873 occupants from various CIREN centers. CT-measured lumbar vBMD < 145 mg/cc is indicative of osteopenia using a published threshold. CIREN occupant lumbar vBMD in milligrams per cubic centimeter was regressed against age, osteopenia/osteoporosis comorbidities, height, weight, body mass index (BMI), and the incidence of fracture in vertebral (cervical, thoracic, lumbar) and rib/sternum regions.

RESULTS

Among the 873 occupants analyzed, 11% (92 occupants) were diagnosed as osteopenic in CIREN. Of these 92 occupants, 42% (39 occupants) had normal vBMD measures (≥145 mg/cc), suggesting possible misclassification in CIREN. Of the 134 occupants classified as osteopenic in vBMD analysis, 60% were not classified as osteopenic in CIREN, suggesting undiagnosed osteopenia, and 40% were correctly classified in CIREN. Age was negatively correlated with vBMD (P <.0001) and occupants with <145 mg/cc vBMD sustained a median number of 2 rib/sternum fractures compared to a median value of 0 rib/sternum fractures for the ≥145 mg/cc vBMD group (P <.0001). Vertebral fracture analysis revealed that the thoracolumbar region was the most common region of injury in the spine. Though the incidence of fracture was not significantly different in the thoracic (10% versus 6%, P =.122) and lumbar (16% versus 13%, P =.227) regions between the 2 bone quality groups, the proportion of thoracolumbar fractures was significantly higher in occupants with <145 mg/cc vBMD versus occupants with ≥145 mg/cc vBMD (24% versus 17%, P =.043).

CONCLUSIONS

Low lumbar vertebral bone quality is associated with an increased number of rib/sternum fractures and a greater incidence of thoracolumbar vertebral body fractures within the CIREN population analyzed.