Application of quantitative computed tomography for assessment of trabecular bone mineral density, microarchitecture and mechanical property

Trabecular bone mineral density as measured by thoracic vertebrae predicts incident hip and vertebral fractures: the multi-ethnic study of atherosclerosis

We evaluated the relationship of bone mineral density (BMD) by computed tomography (CT), to predict fractures in a multi-ethnic population. We demonstrated that vertebral and hip fractures were more likely in those patients with low BMD. This is one of the first studies to demonstrate that CT BMD derived from thoracic vertebrae can predict future hip and vertebral fractures.

PURPOSE/INTRODUCTION

Osteoporosis affects an enormous number of patients, of all races and both sexes, and its prevalence increases as the population ages. Few studies have evaluated the association between the vertebral trabecular bone mineral density(vBMD) and osteoporosis-related hip fracture in a multiethnic population, and no studies have demonstrated the predictive value of vBMD for fractures.

METHOD

We sought to determine the predictive value of QCT-based trabecular vBMD of thoracic vertebrae derived from coronary artery calcium scan for hip fractures in the Multi-Ethnic Study of Atherosclerosis(MESA), a nationwide multicenter cohort included 6814 people from six medical centers across the USA and assess if low bone density by QCT can predict future fractures. Measures were done using trabecular bone measures, adjusted for individual patients, from three consecutive thoracic vertebrae (BDI Inc, Manhattan Beach CA, USA) from non-contrast cardiac CT scans.

RESULTS

Six thousand eight hundred fourteen MESA baseline participants were included with a mean age of 62.2 ± 10.2 years, and 52.8% were women. The mean thoracic BMD is 162.6 ± 46.8 mg/cm3 (95% CI 161.5, 163.7), and 27.6% of participants (n = 1883) had osteoporosis (T-score 2.5 or lower). Over a median follow-up of 17.4 years, Caucasians have a higher rate of vertebral fractures (6.9%), followed by Blacks (4.4%), Hispanics (3.7%), and Chinese (3.0%). Hip fracture patients had a lower baseline vBMD as measured by QCT than the non-hip fracture group by 13.6 mg/cm3 [P < 0.001]. The same pattern was seen in the vertebral fracture population, where the mean BMD was substantially lower 18.3 mg/cm3 [P < 0.001] than in the non-vertebral fracture population. Notably, the above substantial relationship was unaffected by age, gender, race, BMI, hypertension, current smoking, medication use, or activity. Patients with low trabecular BMD of thoracic vertebrae showed a 1.57-fold greater risk of first hip fracture (HR 1.57, 95% CI 1.38-1.95) and a nearly threefold increased risk of first vertebral fracture (HR 2.93, 95% CI 1.87-4.59) compared to normal BMD patients.

CONCLUSION

There is significant correlation between thoracic trabecular BMD and the incidence of future hip and vertebral fracture. This study demonstrates that thoracic vertebrae BMD, as measured on cardiac CT (QCT), can predict both hip and vertebral fractures without additional radiation, scanning, or patient burden. Osteopenia and osteoporosis are markedly underdiagnosed. Finding occult disease affords the opportunity to treat the millions of people undergoing CT scans every year for other indications.

Validation of Opportunistic Artificial Intelligence-Based Bone Mineral Density Measurements in Coronary Artery Calcium Scans

BACKGROUND

Previously we reported a manual method of measuring thoracic vertebral bone mineral density (BMD) using quantitative CT in noncontrast cardiac CT scans used for coronary artery calcium (CAC) scoring. In this report, we present validation studies of an artificial intelligence-based automated BMD measurement (AutoBMD) that recently received FDA approval as an opportunistic add-on to CAC scans.

METHODS

A deep learning model was trained to detect vertebral bodies. Subsequently, signal processing techniques were developed to detect intervertebral discs and the trabecular components of the vertebral body. The model was trained using 132 CAC scans comprising 7,649 slices. To validate AutoBMD, we used 5,785 cases of manual BMD measurements previously reported from CAC scans in the Multi-Ethnic Study of Atherosclerosis.

RESULTS

Mean ± SD for AutoBMD and manual BMD were 166.1 ± 47.9 mg/cc and 163.1 ± 46 mg/cc, respectively (P = .006). Multi-Ethnic Study of Atherosclerosis cases were 47.5% male and 52.5% female, with age 62.2 ± 10.3. A strong correlation was found between AutoBMD and manual measurements (R = 0.85, P < .0001). Accuracy, sensitivity, specificity, positive predictive value and negative predictive value for AutoBMD-based detection of osteoporosis were 99.6%, 96.7%, 97.7%, 99.7% and 99.8%, respectively. AutoBMD averaged 15 seconds per report versus 5.5 min for manual measurements (P < .0001).

CONCLUSIONS

AutoBMD is an FDA-approved, artificial intelligence-enabled opportunistic tool that reports BMD with Z-scores and T-scores and accurately detects osteoporosis and osteopenia in CAC scans, demonstrating results comparable to manual measurements. No extra cost of scanning and no extra radiation to patients, plus the high prevalence of asymptomatic osteoporosis, make AutoBMD a promising candidate to enhance patient care.

Dual-energy computed tomography and micro-computed tomography for assessing bone regeneration in a rabbit tibia model

To gain a more meaningful understanding of bone regeneration, it is essential to select an appropriate assessment method. Micro-computed tomography (Micro-CT) is widely used for bone regeneration because it provides a substantially higher spatial resolution. Dual-energy computed tomography (DECT) ensure shorter scan time and lower radiation doses during quantitative evaluation. Therefore, in this study, DECT and Micro-CT were used to evaluate bone regeneration. We created 18 defects in the tibial plateau of the rabbits and filled them with porous polyetheretherketone implants to promote bone regeneration. At 4, 8, and 12 weeks, Micro-CT and DECT were used to assess the bone repair in the defect region. In comparison to Micro-CT (152 ± 54 mg/cm3), the calcium density values and hydroxyapatite density values obtained by DECT [DECT(Ca) and DECT(HAP)] consistently achieved lower values (59 ± 25 mg/cm3, 126 ± 53 mg/cm3). In addition, there was a good association between DECT and Micro-CT (R = 0.98; R2 = 0.96; DECT(Ca): y = 0.45x-8.31; DECT(HAP): y = 0.95x-17.60). This study highlights the need to use two different imaging methods, each with its advantages and disadvantages, to better understand the bone regeneration process.

Treatment with PB125® Increases Femoral Long Bone Strength in 15-Month-Old Female Hartley Guinea Pigs

Nuclear factor-erythroid 2-related factor-2 (Nrf2) is a transcription factor that serves as a master regulator of anti-inflammatory agents, phase I xenobiotic, and phase II antioxidant enzymes, all of which provide a cytoprotective role during disease progression. We hypothesized that oral administration of a purported phytochemical Nrf2-activator, PB125®, would increase long bone strength in aging Hartley guinea pigs, a model prone to musculoskeletal decline. Male (N = 56) and female (N = 56) guinea pigs were randomly assigned to receive daily oral treatment with either PB125® or vehicle control. Animals were treated for a consecutive 3-months (starting at 2-months of age) or 10-months (starting at 5-months of age) and sacrificed at 5-months or 15-months of age, respectively. Outcome measures included: (1) ANY-maze™ enclosure monitoring, (2) quantitative microcomputed tomography, and (3) biomechanical testing. Treatment with PB125® for 10 months resulted in increased long bone strength as determined by ultimate bending stress in female Hartley guinea pigs. In control groups, increasing age resulted in significant effects on geometric and structural properties of long bones, as well as a trending increase in ultimate bending stress. Furthermore, both age and sex had a significant effect on the geometric properties of both cortical and trabecular bone. Collectively, this work suggests that this nutraceutical may serve as a promising target and preventive measure in managing the decline in bone mass and quality documented in aging patients. Auxiliary to this main goal, this work also capitalized upon 5 and 15-month-old male and female animals in the control group to characterize age- and sex-specific differences on long bone geometric, structural, and material properties in this animal model.

DeepmdQCT: A multitask network with domain invariant features and comprehensive attention mechanism for quantitative computer tomography diagnosis of osteoporosis

In the medical field, the application of machine learning technology in the automatic diagnosis and monitoring of osteoporosis often faces challenges related to domain adaptation in drug therapy research. The existing neural networks used for the diagnosis of osteoporosis may experience a decrease in model performance when applied to new data domains due to changes in radiation dose and equipment. To address this issue, in this study, we propose a new method for multi domain diagnostic and quantitative computed tomography (QCT) images, called DeepmdQCT. This method adopts a domain invariant feature strategy and integrates a comprehensive attention mechanism to guide the fusion of global and local features, effectively improving the diagnostic performance of multi domain CT images. We conducted experimental evaluations on a self-created OQCT dataset, and the results showed that for dose domain images, the average accuracy reached 91%, while for device domain images, the accuracy reached 90.5%. our method successfully estimated bone density values, with a fit of 0.95 to the gold standard. Our method not only achieved high accuracy in CT images in the dose and equipment fields, but also successfully estimated key bone density values, which is crucial for evaluating the effectiveness of osteoporosis drug treatment. In addition, we validated the effectiveness of our architecture in feature extraction using three publicly available datasets. We also encourage the application of the DeepmdQCT method to a wider range of medical image analysis fields to improve the performance of multi-domain images.

Opportunistic AI-enabled automated bone mineral density measurements in lung cancer screening and coronary calcium scoring CT scans are equivalent

Rationale and objectives

We previously reported a novel manual method for measuring bone mineral density (BMD) in coronary artery calcium (CAC) scans and validated our method against Dual X-Ray Absorptiometry (DEXA). Furthermore, we have developed and validated an artificial intelligence (AI) based automated BMD (AutoBMD) measurement as an opportunistic add-on to CAC scans that recently received FDA approval. In this report, we present evidence of equivalency between AutoBMD measurements in cardiac vs lung CT scans.

Materials and methods

AI models were trained using 132 cases with 7649 (3 mm) slices for CAC, and 37 cases with 21918 (0.5 mm) slices for lung scans. To validate AutoBMD against manual measurements, we used 6776 cases of BMD measured manually on CAC scans in the Multi-Ethnic Study of Atherosclerosis (MESA). We then used 165 additional cases from Harbor UCLA Lundquist Institute to compare AutoBMD in patients who underwent both cardiac and lung scans on the same day.

Results

Mean±SD for age was 69 ± 9.4 years with 52.4% male. AutoBMD in lung and cardiac scans, and manual BMD in cardiac scans were 153.7 ± 43.9, 155.1 ± 44.4, and 163.6 ± 45.3 g/cm³, respectively (p = 0.09). Bland-Altman agreement analysis between AutoBMD lung and cardiac scans resulted in 1.37 g/cm³ mean differences. Pearson correlation coefficient between lung and cardiac AutoBMD was R² = 0.95 (p < 0.0001).

Conclusion

Opportunistic BMD measurement using AutoBMD in CAC and lung cancer screening scans is promising and yields similar results. No extra radiation plus the high prevalence of asymptomatic osteoporosis makes AutoBMD an ideal screening tool for osteopenia and osteoporosis in CT scans done for other reasons.

Lower trabecular bone score in type 2 diabetes mellitus: A role for fat mass and insulin resistance beyond hyperglycaemia

AIMS

To examine the clinical and biochemical determinants of trabecular bone score (TBS) in type 2 diabetes mellitus (T2DM) patients.

METHODS

Cross-sectional observational study in 137 T2DM patients (49-85 years). Whole-body fat percentage was estimated using the relative fat mass (RFM) equation. Bone mineral density (BMD) and TBS were assessed using dual-energy X-ray absorptiometry and TBS iNsight Software respectively.

RESULTS

T2DM patients showed significantly lower TBS values (P < 0.001) despite significantly higher lumbar spine BMD (LS-BMD) (P = 0.025) compared to controls. TBS values ​​were negatively correlated with body mass index (BMI) (P < 0.001), waist circumference (P < 0.001), and HOMA-2IR index (P = 0.004) and positively correlated with sex hormone-binding globulin (SHBG) (P = 0.01) and LS-BMD (P = 0.003). RFM was negatively associated with TBS in both males (P < 0.001) and females (P = 0.005). The multivariate analysis showed that RFM, HOMA2-IR (negative), SHBG, and LS-BMD (positive) were the variables independently associated with TBS. ROC analysis revealed RFM as the variable with the highest predictive value for risk of degraded bone microarchitecture.

CONCLUSIONS

The adiposity estimated by RFM may negatively affect TBS and this relationship may be influenced by insulin resistance and SHBG. RFM could act as a key estimator of degraded bone microarchitecture risk in the T2DM population.

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.

Semi-automatic micro-CT segmentation of the midfoot using calibrated thresholds

PURPOSE

In the field of skeletal research, accurate and reliable segmentation methods are necessary for quantitative micro-CT analysis to assess bone quality. We propose a method of semi-automatic image segmentation of the midfoot, using the cuneiform bones as a model, based on thresholds set by phantom calibration that allows reproducible results in low cortical thickness bones.

METHODS

Manual and semi-automatic segmentation methods were compared in micro-CT scans of the medial and intermediate cuneiforms of 24 cadaveric specimens. The manual method used intensity thresholds, hole filling, and manual cleanup. The semi-automatic method utilized calibrated bone and soft tissue thresholds Boolean subtraction to cleanly identify edges before hole filling. Intra- and inter-rater reliability was tested for the semi-automatic method in all specimens. Mask volume and average bone mineral density (BMD) were measured for all masks, and the three-dimensional models were compared to the initial semi-automatic segmentation using an unsigned distance part comparison analysis. Segmentation methods were compared with paired t-tests with significance level 0.05, and reliability was analyzed by calculating intra-class correlation coefficients.

RESULTS

There were statistically significant differences in mask volume and BMD between the manual and semi-automatic segmentation methods in both bones. The intra- and inter-reliability was excellent for mask volume and bone density in both bones. Part comparisons showed a higher maximum distance between surfaces for the manual segmentation than the repeat semi-automatic segmentations.

CONCLUSION

We developed a semi-automatic micro-CT segmentation method based on calibrated thresholds. This method was designed specifically for use in bones with high rates of curvature and low cortical bone density, such as the cuneiforms, where traditional threshold-based segmentation is more challenging. Our method shows improvement over manual segmentation and was highly reliable, making it appropriate for use in quantitative micro-CT analysis.

Dual-Energy X-Ray Absorptiometry (DEXA) Scan Versus Computed Tomography for Bone Density Assessment

Rationale and objective Osteoporosis, a common non-pathological disease of bones, has been the cause of many disastrous consequences, in terms of physical, psychological, social, and economic loss. Therefore, it is crucial to diagnose it early for timely prevention and treatment of osteoporotic fractures. Dual-Energy X-Ray Absorptiometry (DEXA) is currently routinely used for determining bone mineral density. However, it has its limitations. Nowadays, CT technology has advanced so rapidly that the Hounsfield units (HU) values can be used in opportunistic screening for osteoporosis in patients during routine CT abdomen for other causes. Hence, there would be no need for additional study with DEXA and also reduce radiation exposure. The aim of our research is to determine whether there is a correlation between the bone mineral density and the T-score measured by DEXA and the HU values measured from the diagnostic CT images of L1-4 vertebrae. Also, to determine reference CT values that would help in screening the patients with osteoporosis. Materials and methods We conducted a retrospective study of 78 female patients who underwent CT lumbar spine, abdomen, and pelvis in our hospital between the years 2016-2020. We collected data of patients who performed DEXA and CT scans within an interval of up to two years. The final collected data was analyzed to find correlation values of HU with age group and with DEXA bone mineral density (BMD) and T-score using Pearson correlation coefficient. Results The mean of the 78 patients was 61.1 (range 37-88 years). Mean HU values decreased consistently with age, from 202.17 HU in the fifth decade to 71 HU in the ninth decade. Average L1-4 HU values ranged from 71 HU to 202.17 HU (mean with standard deviation), while their T-score ranged from -4.4 to +2.4 (mean was -1.7±1.41), and their BMD ranged from 0.62 to 1.465 g/cm2 (mean, 0.974±0.175 g/cm2). For each lumbar vertebra, the correlations of HU values with bone mineral density and T-score were calculated separately. For L1-4 vertebrae, the correlation coefficients (r2) for the HU value and T-score were 0.544, 0.600, 0.611, and 0.600, respectively. The correlation coefficients (r2) for the HU value and bone mineral density were 0.581, 0.623, 0.653,0.612, respectively. All the calculated correlations were significant (p<0.001). Therefore, it was concluded that there was a positive correlation between the HU values and the DEXA for the BMD and between the HU values and the T-score. Based on the WHO guidelines, the T-scores of the lumbar vertebrae were classified into three groups. The mean HU values for the subjects in the normal group were 174.05 (95% confidence interval, 153-194.49), in the osteopenia group were 120.45 HU (95% confidence interval, 106.98-133.91), and in the osteoporosis group were 115 HU (95% confidence interval, 104.60-125.40). The differences in the mean HU values between the groups were significant. Conclusion On analyzing the results of our study, we reached the conclusion that there is a positive correlation between the HU calculated from CT with automated exposure control and BMD calculated from the DEXA. Thus CT scans done for various reasons, for example, the abdomen, lumbar spine, etc. can provide us with information about the patient's bone density as well. CT is a very popular, easily accessible, reproducible, and reliable tool for measuring HU values and thereby in the opportunistic screening of osteoporosis.

Evaluation of patient tissue selection methods for deriving equivalent density calibration for femoral bone quantitative CT analyses

Osteoporosis affects an increasing number of people every year and patient specific finite element analysis of the femur has been proposed to identify patients that could benefit from preventative treatment. The aim of this study was to demonstrate, verify, and validate an objective process for selecting tissues for use as the basis of phantomless calibration to enable patient specific finite element analysis derived hip fracture risk prediction. Retrospective reanalysis of patient computed tomography (CT) scans has the potential to yield insights into more accurate prediction of osteoporotic fracture. Bone mineral density (BMD) specific calibration scans are not typically captured during routine clinical practice. Tissue-based BMD calibration can therefore empower the retrospective study of patient CT scans captured during routine clinical practice. Together the method for selecting tissues as the basis for phantomless calibration coupled with the post-processing steps for deriving a calibration equation using the selected tissues provide an estimation of quantitative equivalent density results derived using calibration phantoms. Patient tissues from a retrospective cohort of 211 patients were evaluated. The best phantomless calibration resulted in a femoral strength (FS) [N] bias of 0.069 ± 0.07% over FS derived from inline calibration and a BMD [kg/cm³] bias of 0.038 ± 0.037% over BMD derived from inline calibration. The phantomless calibration slope for the best method presented was within the range of patient specific calibration curves available for comparison and demonstrated a small bias of 0.028 ± 0.054 HU/(mg/cm³), assuming the Mindways Model 3 BMD inline calibration phantom as the gold standard. The presented method of estimating a calibration equation from tissues showed promise for CT-based femoral fracture analyses of retrospective cohorts without readily available calibration data.

Association of Aspirin and Other Nonsteroidal Anti-inflammatory Drugs With Vertebral Trabecular Bone: Data From Multiethnic Study of Atherosclerosis, a Population-Based Multicenter Cohort Study

OBJECTIVE

The objective of this article was to study the association of aspirin and other nonsteroidal anti-inflammatory drugs (NSAIDs) with bone mineral density (BMD).

METHODS

Spine BMD was evaluated in a subset of 2028 participants from the Multiethnic Study of Atherosclerosis cohort who were NSAID users (including aspirin) and underwent both lumbar and thoracic imaging. Multiethnic Study of Atherosclerosis is a prospective cohort study that includes 4 ethnic groups (white, Asian, African American, and Hispanic). Trabecular BMD was evaluated by quantitative computed tomography based on cardiac computed tomography images, which were obtained during coronary calcium scans. The analyses were cross sectional using baseline examination data for exposure and outcomes.

RESULTS

After adjustment for potential confounders including age, sex, race, and traditional cardiovascular risk factors, a small association between trabecular BMD and baseline use of COX-2-selective NSAID was observed. COX-2-selective NSAID use was associated with 7.4 mg/cm (95% confidence interval [CI], 1.6-13.3; P = 0. 013) higher trabecular BMD in thoracic spine and 10.6 mg/cm higher at lumbar spine (95% CI, 5.1-16.1; P < 0.001). Among regular aspirin users, there was no association between drug use and trabecular BMD. Considering all spine fractures together, the prevalence ratio of fractures among aspirin users was 1.0 (95% CI, 0.6-1.6) and 1.1 (95% CI, 0.5-2.3) among COX-2-selective NSAID users.

CONCLUSIONS

Regular use of aspirin has no significant association with trabecular BMD in either the thoracic or lumbar spine and no association with fracture prevalence. COX-2-selective NSAIDs may have modest positive association with BMD, but the mechanisms were not assessed and the observational study design makes residual confounding a possible alternate explanation. Potential pathological mechanisms warrant further longitudinal exploration.

Non-hematologic diagnosis of systemic mastocytosis: Collaboration of radiology and pathology

Systemic mastocytosis (SM) is a hematologic disease with a wide range of clinical courses ranging from an indolent condition with normal life expectancy to exceedingly aggressive disorder with a poor prognosis. The symptoms and signs of SM result from the release of mast cell mediators with heterogeneous functions, and/or organ damage from neoplastic mast cell infiltration, or both. Diagnostic criteria for SM are well-defined by the World Health Organization (WHO). However, the diagnosis of SM can be difficult when especially it is not in the differential diagnosis. Routinely used radiologic techniques (e.g., X-ray, ultrasound, CT scans can show findings such as lytic-, sclerotic- or mixed-bone lesions, splenomegaly, hepatomegaly, retroperitoneal or periportal mesenteric lymphadenopathy, and omental thickening). It is essential to emphasize that the constellation of these radiologic findings should strongly concern of SM, especially in patients who also have a skin rash, allergic reactions, gastrointestinal tract symptoms (lasting, intermittent nausea, diarrhea), paroxysmal tachycardias, unexplained weight loss, persistent bone pain, cytopenias, liver dysfunction, eosinophilia. These findings, even coincidentally noted, will likely lead to a tissue biopsy, which reveals diagnosis (as we discussed and illustrated some tissue biopsies here). Moreover, the role of MRI and new techniques such as [18-fluorodeoxyglucose positron emission computed tomography, fibroscan] in the diagnosis of SM have been discussed. Furthermore, we reviewed the use of radiologic methods to evaluate treatment response and prognostication of SM..

Automatic opportunistic osteoporosis screening using low-dose chest computed tomography scans obtained for lung cancer screening

Objective

Osteoporosis is a prevalent and treatable condition, but it remains underdiagnosed. In this study, a deep learning-based system was developed to automatically measure bone mineral density (BMD) for opportunistic osteoporosis screening using low-dose chest computed tomography (LDCT) scans obtained for lung cancer screening.

Methods

First, a deep learning model was trained and tested with 200 annotated LDCT scans to segment and label all vertebral bodies (VBs). Then, the mean CT numbers of the trabecular area of target VBs were obtained based on the segmentation mask through geometric operations. Finally, a linear function was built to map the trabecular CT numbers of target VBs to their BMDs collected from approved software used for osteoporosis diagnosis. The diagnostic performance of the developed system was evaluated using an independent dataset of 374 LDCT scans with standard BMDs and osteoporosis diagnosis.

Results

Our deep learning model achieved a mean Dice coefficient of 86.6% for VB segmentation and 97.5% accuracy for VB labeling. Line regression and Bland-Altman analyses showed good agreement between the predicted BMD and the ground truth, with correlation coefficients of 0.964–0.968 and mean errors of 2.2–4.0 mg/cm³. The area under the curve (AUC) was 0.927 for detecting osteoporosis and 0.942 for distinguishing low BMD.

Conclusion

The proposed deep learning-based system demonstrated the potential to automatically perform opportunistic osteoporosis screening using LDCT scans obtained for lung cancer screening.

Key Points

• Osteoporosis is a prevalent but underdiagnosed condition that can increase the risk of fracture.

• A deep learning-based system was developed to fully automate bone mineral density measurement in low-dose chest computed tomography scans.

• The developed system achieved high accuracy for automatic opportunistic osteoporosis screening using low-dose chest computed tomography scans obtained for lung cancer screening.

Three-Dimensional Characterization of Trabecular Bone Mineral Density of the Distal Radius Utilizing Quantitative Computed Tomography

Background: Distal radius (DR) fractures demonstrate patterns of predictable fragments. Bone mineral density (BMD) measurements of these regions of interest (ROIs) may guide more precise treatment. Methods: Computed tomography (CT) scans of the DR of 42 healthy volunteers (23 female) were analyzed using quantitative CT software, measuring BMD within trabecular bone. Seven ROIs were described by alignment with the distal (volar ulnar distal [VUD], dorsal ulnar distal [DUD], volar radial distal [VRD], and dorsal radial distal [DRD]) or proximal (middle ulnar proximal [MUP], middle proximal [MP], and middle radial proximal [MRP]) sigmoid notch. Additional ROIs were the radial styloid (RS) and metadiaphysis (MD). A general estimation equation assessed subject's BMDs with predictive factors of gender, ROI, and age. The interaction between gender, ROI, and age was included in the model to allow for differences in ROI to vary with gender and/or age. Results: Comparing ROIs within the same gender and, separately, within the same age group revealed significantly higher BMD adjacent to the radioulnar and radiocarpal joints. Male and female individuals aged ≥50 years (mean: 172.7 mg/cm³ ± 6.1) had significantly lower BMD than those aged <50 years (mean: 202.7 mg/cm³ ± 5.8) when all ROIs were considered. Males had higher mean BMD at each ROI compared with females; these differences were significant in 5 of the 9 ROIs: VUD, DUD, DRD, RS, MUP. Conclusions: Trabecular BMD of the DR is highest adjacent to the radioulnar and radiocarpal joints. Female patients and those ≥50 years have lower trabecular BMD.

Trends in the Diagnosis of Osteoporosis in Patients with Distal Radius Fractures Based on a National Claims Database

Background

A history of osteoporotic fractures is strongly associated with the subsequent osteoporotic fractures. To prevent subsequent fractures, the diagnosis and treatment of osteoporosis following osteoporotic fractures are very important. A distal radius fracture (DRF) is the second most common type of osteoporotic fracture in South Korea. We analyzed the rate of osteoporosis diagnosis within 6 months post-DRF.

Methods

We used data from the Korean Health Insurance Review and Assessment Service nationwide claims database from 2010 to 2016. International Classification of Diseases, 10th revision codes and procedures codes were used to identify patients aged over 50 years with newly diagnosed DRFs; the osteoporosis assessments of these patients were then analyzed. We used Cochran-Armitage trend test to examine trends in osteoporosis diagnosis.

Results

A search of database identified 77,209 DRFs in patient aged above 50 years of age from 2011 to 2016. Among these patients, only 19,305 (25.0%) underwent diagnostic examination for osteoporosis. The number of osteoporosis examinations increased slightly, but not significantly, every year (P=0.061).

Conclusions

Clinicians who treat DRFs shoulder also evaluated patients for osteoporosis after DRFs.

Differences in bone density on chest CT according to smoking status in males without chronic obstructive lung disease

The goals of this study were to determine whether bone density measured using CT (CTBD) can show significant differences in bone loss according to smoking status and pack-years, and to examine the correlation between CTBD and bone mineral density when measured by dual-energy X-ray absorptiometry (DEXA-BMD) in males without chronic obstructive pulmonary disease (COPD). In this cross-sectional study, 1,011 males without airflow obstruction ≥50 years old were included. CTBD and DEXA-BMD were compared among groups with different smoking statuses. The correlation between CTBD and DEXA-BMD and the association of CTBD with pack-years were also investigated. CTBD of all vertebral bodies (VBs) and DEXA-BMD of all VBs without L1 showed significant differences among never, former, and current smokers. CTBD was significantly lowest in ≥30-pack-year smokers and was significantly lower in ≥30-pack-year smokers than in <15-pack-year smokers (all P < 0.05). There were significant correlations between DEXA-BMD and CTBD at all VB levels (correlation coefficient [r], 0.448~0.640; all P < 0.01). A lower CTBD had a significant association with a 15 ≤ x < 30-pack-year smoking history and ≥30-pack-year smoking history, while there was no association with never-smokers. In conclusion, CTBD demonstrated significant differences in bone quality according to smoking status and pack-years in males without COPD.

Opportunistic osteoporosis screening in multi-detector CT images via local classification of textures

Our study proposed an automatic pipeline for opportunistic osteoporosis screening using 3D texture features and regional vBMD using multi-detector CT images. A combination of different local and global texture features outperformed the global vBMD and showed high discriminative power to identify patients with vertebral fractures.

INTRODUCTION

Many patients at risk for osteoporosis undergo computed tomography (CT) scans, usable for opportunistic (non-dedicated) screening. We compared the performance of global volumetric bone mineral density (vBMD) with a random forest classifier based on regional vBMD and 3D texture features to separate patients with and without osteoporotic fractures.

METHODS

In total, 154 patients (mean age 64 ± 8.5, male; n = 103) were included in this retrospective single-center analysis, who underwent contrast-enhanced CT for other reasons than osteoporosis screening. Patients were dichotomized regarding prevalent vertebral osteoporotic fractures (noFX, n = 101; FX, n = 53). Vertebral bodies were automatically segmented, and trabecular vBMD was calculated with a dedicated phantom. For 3D texture analysis, we extracted gray-level co-occurrence matrix Haralick features (HAR), histogram of gradients (HoG), local binary patterns (LBP), and wavelets (WL). Fractured vertebrae were excluded for texture-feature and vBMD data extraction. The performance to identify patients with prevalent osteoporotic vertebral fractures was evaluated in a fourfold cross-validation.

RESULTS

The random forest classifier showed a high discriminatory power (AUC = 0.88). Parameters of all vertebral levels significantly contributed to this classification. Importantly, the AUC of the proposed algorithm was significantly higher than that of volumetric global BMD alone (AUC = 0.64).

CONCLUSION

The presented classifier combining 3D texture features and regional vBMD including the complete thoracolumbar spine showed high discriminatory power to identify patients with vertebral fractures and had a better diagnostic performance than vBMD alone.

Identifying Smoking-Related Disease on Lung Cancer Screening CT Scans: Increasing the Value

Background

Lung cancer screening (LCS) via chest computed tomography (CT) scans can save lives by identifying early-stage tumors. However, most smokers die of comorbid smoking-related diseases. LCS scans contain information about smoking-related conditions that is not currently systematically assessed. Identifying these common comorbid diseases on CT could increase the value of screening with minimal impact on LCS programs. We determined the prevalence of 3 comorbid diseases from LCS eligible scans and quantified related adverse outcomes.

Methods

We studied COPD Genetic Epidemiology study (COPDGene^®) participants (n=4078) who met criteria for LCS screening at enrollment (age > 55 years, and < 80 years, > 30 pack years smoking, current smoker or former smoker within 15 years of smoking cessation). CT scans were assessed for coronary artery calcification (CAC), emphysema, and vertebral bone density. We tracked the following clinically significant events: myocardial infarctions (MIs), strokes, pneumonia, respiratory exacerbations, and hip and vertebral fractures.

Results

Overall, 77% of eligible CT scans had one or more of these diagnoses identified. CAC (> 100 mg) was identified in 51% of scans, emphysema in 44%, and osteoporosis in 54%. Adverse events related to the underlying smoking-related diseases were common, with 50% of participants reporting at least one. New diagnoses of cardiovascular disease, emphysema and osteoporosis were made in 25%, 7% and 46%, of participants respectively. New diagnosis of disease was associated with significantly more adverse events than in participants who did not have CT diagnoses for both osteoporosis and cardiovascular risk.

Conclusions

Expanded analysis of LCS CT scans identified individuals with evidence of previously undiagnosed cardiovascular disease, emphysema or osteoporosis that corresponded with adverse events. LCS CT scans can potentially facilitate diagnoses of these smoking-related diseases and provide an opportunity for treatment or prevention.

Design and Validation of Synchronous QCT Calibration Phantom: Practical Methodology

INTRODUCTION

Quantitative computed tomography (QCT) can supplement dual x-ray absorptiometry by enabling geometric and compartmental bone assessments. Whole-body spiral CT scanners are widely available and require a short scanning time of seconds, in contrast to peripheral QCT scanners, which require several minutes of scanning time. This study designed and evaluated the accuracy and precision of a homemade QCT calibration phantom using a whole-body spiral CT scanner.

MATERIALS AND METHODS

The QCT calibration phantom consisted of K₂HPO₄ solutions as reference. The reference material with various concentrations of 0, 50, 100, 200, 400, 1000, and 1200 mg/cc of K₂HPO₄ in water were used. For designing the phantom, we used the ABAQUS software.

RESULTS

The phantoms were used for performance assessment of QCT method through measurement of accuracy and precision errors, which were generally less than 5.1% for different concentrations. The correlation between CT numbers and concentration were close to one (R² = 0.99).

DISCUSSION

Because whole-body spiral CT scanners allow central bone densitometry, evaluating the accuracy and precision for the easy to use calibration phantom may improve the QCT bone densitometry test.

CONCLUSION

This study provides practical directions for applying a homemade calibration phantom for bone mineral density quantification in QCT technique.

Vertebral Bone Mineral Density Measured by Quantitative Computed Tomography With and Without a Calibration Phantom: A Comparison Between 2 Different Software Solutions

Quantitative computed tomography (CT) can be used to quantify bone mineral density (BMD) in the spine from clinical CT scans. We aimed to determine agreement and precision of BMD measurements by 2 different methods: phantom-less internal tissue calibration and asynchronous phantom-based calibration in a cohort of patients with chronic kidney disease (CKD). Patients with CKD were recruited for CT angiography of the chest, abdomen, and pelvis. BMD was analyzed by 2 different software solutions using different calibration techniques; phantom-based by QCT Pro (Mindways Inc.) and phantom-less by Extended Brilliance Workspace (Philips Healthcare). Intraoperator reanalysis was performed on 53 patients (36%) for both methods. An interoperator reanalysis on 30 patients (20%) using the phantom-based method and 29 patients (19%) using the phantom-less method was made. XY- and Bland-Altman plots were used to evaluate method agreement. Phantom-based measured BMD was systematically higher than phantom-less measured BMD. Despite a small absolute difference of 3.3 mg/cm³ (CI: -0.2-6.9 mg/cm³) and a relative difference of 5.1% (CI: 2.2%-8.1%), interindividual differences were large, as seen by a wide prediction interval (PI: -47-40 mg/cm³). The Bland-Altman plot showed no systematic bias, apart from 5 outliers. Intraoperator variability was high for the phantom-less method (5.8%) compared to the phantom-based (0.8%) and the interoperator variability was also high for the phantom-less method (5.8%) compared to the phantom-based (1.8%). Despite high correlation between methods, the between-method difference on an individual level showed great variability. Our results suggest agreement between these 2 methods is insufficient to allow them to be used interchangeably in patients with CKD.

Practical considerations for obtaining high quality quantitative computed tomography data of the skeletal system

Quantitative CT (QCT) analysis involves the calculation of specific parameters such as bone volume and density from CT image data, and can be a powerful tool for understanding bone quality and quantity. However, without careful attention to detail during all steps of the acquisition and analysis process, data can be of poor- to unusable-quality. Good quality QCT for research requires meticulous attention to detail and standardization of all aspects of data collection and analysis to a degree that is uncommon in a clinical setting. Here, we review the literature to summarize practical and technical considerations for obtaining high quality QCT data, and provide examples of how each recommendation affects calculated variables. We also provide an overview of the QCT analysis technique to illustrate additional opportunities to improve data reproducibility and reliability. Key recommendations include: standardizing the scanner and data acquisition settings, minimizing image artifacts, selecting an appropriate reconstruction algorithm, and maximizing repeatability and objectivity during QCT analysis. The goal of the recommendations is to reduce potential sources of error throughout the analysis, from scan acquisition to the interpretation of results.

Thoracic Quantitative Computed Tomography (QCT) Can Sensitively Monitor Bone Mineral Metabolism: Comparison of Thoracic QCT vs Lumbar QCT and Dual-energy X-ray Absorptiometry in Detection of Age-relative Change in Bone Mineral Density

RATIONALE AND OBJECTIVE

Sensitive detection of bone mineral density (BMD) change is a key issue to monitor and evaluate the individual bone health status, as well as bone metabolism and bone mineral status. The ability to use thoracic quantitative computed tomography (QCT) to detect the annual change of BMD remains unclear. We aimed to investigate the sensitivity in detecting age-related bone mineral loss using the thoracic QCT from the electrocardiographically gated heart scans in comparison to whole-body dual-energy X-ray absorptiometry (DXA) and standard lumbar QCT.

MATERIALS AND METHODS

A total of 121 asymptomatic patients' imaging data, including DXA whole body scan, cardiac CT scan, and abdomen scans were analyzed. The BMD of the thoracolumbar spine, upper, and lower extremities were measured using QCT and DXA, respectively. The age-related annual rate of bone density loss was computed and compared to the thoracic and lumbar QCT, as well DXA measures.

RESULTS

The age-related annual rate of bone loss with QCT was -0.70 mg/mL³ (-0.75%/y) in women, -0.83 mg/mL³ (-0.86%/y) in men in the thoracic and the lumbar trabecular QCT, respectively. Compared to the QCT, DXA demonstrates a lower annual rate of bone loss in the area of BMD measurement (P < .05 in all, excluding legs of women) in -0.45, -0.42, -0.67, and -0.46 in women, in -0.32, -0.02, -0.12, and -0.08 in men for thoracic, lumbar, leg, and arm, respectively.

CONCLUSION

We conclude that the thoracic and the lumbar QCT provide a similar and more sensitive method for detecting bone mineral loss when compared to DXA.

Bone Mineral Density Estimations From Routine Multidetector Computed Tomography: A Comparative Study of Contrast and Calibration Effects

Introduction

Phantom-based (synchronous and asynchronous) and phantomless (internal tissue calibration based) assessment of bone mineral density (BMD) in routine MDCT (multidetector computed tomography) examinations potentially allows for diagnosis of osteoporosis. Although recent studies investigated the effects of contrast-medium application on phantom-calibrated BMD measurements, it remains uncertain to what extent internal tissue-calibrated BMD measurements are also susceptible to contrast-medium associated density variation. The present study is the first to systemically evaluate BMD variations related to contrast application comparing different calibration techniques.

Purpose

To compare predicative performance of different calibration techniques for BMD measurements obtained from triphasic contrast-enhanced MDCT.

Materials and Methods

Bone mineral density was measured on nonenhanced (NE), arterial (AR) and portal-venous (PV) contrast phase MDCT images of 46 patients using synchronous (SYNC) and asynchronous (ASYNC) phantom calibration as well as internal calibration (IC). Quantitative computed tomography (QCT) served as criterion standard. Density variations were analyzed for each contrast phase and calibration technique, and respective linear fitting was performed.

Results

Both asynchronous calibration-derived BMD values (NE-ASYNC) and values estimated using IC (NE-IC) on NE MDCT images did reasonably well in predicting QCT BMD (root-mean-square deviation, 8.0% and 7.8%, respectively). Average NE-IC BMD was 2.7% lower when compared with QCT (P = 0.017), whereas no difference could be found for NE-ASYNC (P = 0.957). All average BMD estimates derived from contrast-enhanced scans differed significantly from QCT BMD (all P < 0.005) and led to notable systemic BMD biases (mean difference at least > 6.0 mg/mL). All regression fits revealed a consistent linear dependency (R² range, 0.861–0.963). Overall accuracy and goodness of fit tended to decrease from AR to PV contrast phase. Highest precision and best linear fit could be reached using a synchronously scanned phantom (root-mean-square deviation, 9.4% for AR and 14.4% for PV). Both ASYNC and IC estimations performed comparably accurate and precise.

Conclusions

Our data suggest that internal calibration driven BMD measurements derived from contrast-enhanced MDCT need the same amount of post hoc contrast-effect adjustment as measurements using phantom calibration. Adjustment using linear correction equations can correct for systematic bias of bone density variations related to contrast application, irrespective of the calibration technique used.