Vertebral bone attenuation on low-dose chest CT: quantitative volumetric analysis for bone fragility assessment

Artificial intelligence assisted automatic screening of opportunistic osteoporosis in computed tomography images from different scanners

OBJECTIVES

It is feasible to evaluate bone mineral density (BMD) and detect osteoporosis through an artificial intelligence (AI)-assisted system by using quantitative computed tomography (QCT) as a reference without additional radiation exposure or cost.

METHODS

A deep-learning model developed based on 3312 low-dose chest computed tomography (LDCT) scans (trained with 2337 and tested with 975) achieved a mean dice similarity coefficient of 95.8% for T1-T12, L1, and L2 vertebral body (VB) segmentation on test data. We performed a model evaluation based on 4401 LDCT scans (obtained from scanners of 3 different manufacturers as external validation data). The BMD values of all individuals were extracted from three consecutive VBs: T12 to L2. Line regression and Bland‒Altman analyses were used to evaluate the overall detection performance. Sensitivity and specificity were used to evaluate the diagnostic performance for normal, osteopenia, and osteoporosis patients.

RESULTS

Compared with the QCT results as the diagnostic standard, the BMD assessed had a mean error of (- 0.28, 2.37) mg/cm3. Overall, the sensitivity of a normal diagnosis was greater than that of a diagnosis of osteopenia or osteoporosis. For the diagnosis of osteoporosis, the model achieved a sensitivity > 86% and a specificity > 98%.

CONCLUSION

The developed tool is clinically applicable and helpful for the positioning and analysis of VBs, the measurement of BMD, and the screening of osteopenia and osteoporosis.

CLINICAL RELEVANCE STATEMENT

The developed system achieved high accuracy for automatic opportunistic osteoporosis screening using low-dose chest CT scans and performed well on CT images collected from different scanners.

KEY POINTS

Osteoporosis is a prevalent but underdiagnosed condition that can increase the risk of fractures. This system could automatically and opportunistically screen for osteoporosis using low-dose chest CT scans obtained for lung cancer screening. The developed system performed well on CT images collected from different scanners and did not differ with patient age or sex.

Automated Fast Prediction of Bone Mineral Density From Low-dose Computed Tomography

BACKGROUND

Low-dose chest CT (LDCT) is commonly employed for the early screening of lung cancer. However, it has rarely been utilized in the assessment of volumetric bone mineral density (vBMD) and the diagnosis of osteoporosis (OP).

PURPOSE

This study investigated the feasibility of using deep learning to establish a system for vBMD prediction and OP classification based on LDCT scans.

METHODS

This study included 551 subjects who underwent both LDCT and QCT examinations. First, the U-net was developed to automatically segment lumbar vertebrae from single 2D LDCT slices near the mid-vertebral level. Then, a prediction model was proposed to estimate vBMD, which was subsequently employed for detecting OP and osteopenia (OA). Specifically, two input modalities were constructed for the prediction model. The performance metrics of the models were calculated and evaluated.

RESULTS

The segmentation model exhibited a strong correlation with manual segmentation, achieving a mean Dice similarity coefficient (DSC) of 0.974, sensitivity of 0.964, positive predictive value (PPV) of 0.985, and Hausdorff distance of 3.261 in the test set. Linear regression and Bland-Altman analysis demonstrated strong agreement between the predicted vBMD from two-channel inputs and QCT-derived vBMD, with a root mean square error of 8.958 mg/mm3 and an R2 of 0.944. The areas under the curve for detecting OP and OA were 0.800 and 0.878, respectively, with an overall accuracy of 94.2%. The average processing time for this system was 1.5 s.

CONCLUSION

This prediction system could automatically estimate vBMD and detect OP and OA on LDCT scans, providing great potential for the osteoporosis screening.

Effect of contrast media on CT bone density assessment: comparative analysis of low-dose chest CT and abdominopelvic CT

Detecting individuals with low bone mineral density (BMD) before clinical fractures occur may help improve the outcomes of osteoporosis and osteopenia. Although computed tomography (CT) is useful for opportunistic BMD measurement, the modality most suitable for opportunistic screening remains unclear. In this retrospective study, we compared the diagnostic performance of low-dose chest CT (LDCT) and contrast-enhanced abdominopelvic CT (APCT) for measuring BMD at L1 level using dual-energy X-ray absorptiometry (DEXA) as a reference in individuals who underwent LDCT, APCT, and DEXA assessments on the same day. We included 512 individuals (median age: 60 years; interquartile range, 55-65 years; 307 men). Both LDCT (r = 0.706; P < 0.001) and APCT (r = 0.643; P < 0.001) exhibited strong correlation with DEXA T-scores. As T-scores decreased, the relative difference between LDCT and APCT Hounsfield unit values increased (b = - 6.456; P < 0.001). LDCT outperformed APCT in diagnosing both osteoporosis (AUC, 0.865 vs. 0.833; P = 0.035) and low BMD (AUC, 0.844 vs. 0.815; P = 0.006), which may be attributable to the greater effect of intravenous contrast media on CT scan characteristics in individuals with lower T-scores. These results may help inform the selection of imaging methods suitable for screening.

The influence of proliferative tissue on Hounsfield unit and its correlation with BMD in middle-aged and elderly patients with lumbar degenerative diseases

PURPOSE

The difference of Hounsfield Unit (HU) value in different regions of L3 vertebra in middle-aged and elderly patients with lumbar degeneration diseases (LDD) was analyzed. To investigate the influence of proliferative tissue on HU value of cancellous bone and its correlation with bone mineral density (BMD).

METHODS

The medical records of middle-aged and elderly patients with LDD in our hospital from December 2020 to December 2023 were retrospectively analyzed. The patients were divided into osteophyte group and no-osteophyte group according to the presence or absence of osteophyte formation on lumbar spine X-ray. In osteophyte group, cancellous bone HU value, containing cortical bone overall HU value and containing osteophyte overall HU value in L3 vertebra were measured on the lumbar CT cross-section. In no-osteophyte group, only the cancellous bone HU value and the containing cortical bone overall HU value were measured. Differences in HU value in different regions of the L3 vertebral body were compared within and between groups of middle-aged and elderly patients with LDD, respectively. To investigate its effect on cancellous bone HU measurements and to do a correlation analysis with patients' BMD.

RESULTS

A total of 115 patients with LDD were included in this study, including 65 males and 50 females, with an average age of 67.83 ± 6.59 years. The results of the study showed no statistical differences in age (P = 0.15), gender (P = 0.57), smoking (P = 0.88), drinking history (P = 0.76), medical history (P > 0.05) and BMI(P = 0.29) between the two groups. In osteophyte group, the mean cancellous bone HU value was 98.00 ± 25.50 HU, the containing cortical bone overall HU value was 189.02 ± 46.18 HU, and the containing osteophyte overall HU value was 232.69 ± 56.01 HU. The overall HU values containing cortical bone and containing osteophyte were significantly higher than cancellous bone HU value (P < 0.001). In no-osteophyte group, the mean cancellous bone HU value was 102.04 ± 19.64 HU, and the containing cortical bone overall HU value was 175.00 ± 28.97 HU, which was statistically significantly different (P < 0.001). There was no significant difference in cancellous bone HU value and the containing cortical bone overall HU value between the two groups (P > 0.05). The results of the Pearson correlation analysis showed a significant correlation between the cancellous bone HU value of the L3 vertebrae and the QCT BMD value of the patients (r = 0.95, P < 0.001). However, there was no significant correlation between containing cortical bone overall HU value and containing osteophyte overall HU value and the patient's QCT BMD value (P > 0.05).

CONCLUSIONS

Vertebral HU value is an alternative measurement that effectively reflects the patient's BMD. In middle-aged and elderly LDD patients, HU values in different areas of L3 vertebra are significantly different, and hyperplastic tissues such as cortical bone and osteophytes may exponentially lead to higher HU value in patients. Compared with other measurement areas, vertebral cancellous bone HU value have the advantage of accurately assessing patients' BMD.

Automated Opportunistic Osteoporosis Screening Using Low-Dose Chest CT among Individuals Undergoing Lung Cancer Screening in a Korean Population

Opportunistic osteoporosis screening using deep learning (DL) analysis of low-dose chest CT (LDCT) scans is a potentially promising approach for the early diagnosis of this condition. We explored bone mineral density (BMD) profiles across all adult ages and prevalence of osteoporosis using LDCT with DL in a Korean population. This retrospective study included 1915 participants from two hospitals who underwent LDCT during general health checkups between 2018 and 2021. Trabecular volumetric BMD of L1-2 was automatically calculated using DL and categorized according to the American College of Radiology quantitative computed tomography diagnostic criteria. BMD decreased with age in both men and women. Women had a higher peak BMD in their twenties, but lower BMD than men after 50. Among adults aged 50 and older, the prevalence of osteoporosis and osteopenia was 26.3% and 42.0%, respectively. Osteoporosis prevalence was 18.0% in men and 34.9% in women, increasing with age. Compared to previous data obtained using dual-energy X-ray absorptiometry, the prevalence of osteoporosis, particularly in men, was more than double. The automated opportunistic BMD measurements using LDCT can effectively predict osteoporosis for opportunistic screening and identify high-risk patients. Patients undergoing lung cancer screening may especially profit from this procedure requiring no additional imaging or radiation exposure.

Using advanced imaging to measure bone density, compression fracture risk, and risk for construct failure after spine surgery

Low bone mineral density (BMD) can predispose to vertebral body compression fractures and postoperative instrumentation failure. DEXA is considered the gold standard for measurement of BMD, however it is not obtained for all spine surgery patients preoperatively. There is a growing body of evidence suggesting that more routinely acquired spine imaging studies such as computed tomography (CT) and magnetic resonance imaging (MRI) can be opportunistically used to measure BMD. Here we review available studies that assess the validity of opportunistic screening with CT-derived Hounsfield Units (HU) and MRI-derived vertebral vone quality (VBQ) to measure BMD of the spine as well the utility of these measures in predicting postoperative outcomes. Additionally, we provide screening thresholds based on HU and VBQ for prediction of osteopenia/ osteoporosis and postoperative outcomes such as cage subsidence, screw loosening, proximal junctional kyphosis, and implant failure.

CT-derived vertebral bone mineral density is a useful biomarker to predict COVID-19 outcome

The low vertebral bone computed tomography (CT) Hounsfield unit values measured on CT scans reflect low bone mineral density (BMD) and are known as diagnostic indicators for osteoporosis. The potential prognostic significance of low BMD defined by vertebral bone CT values for the coronavirus disease 2019 (COVID-19) remains unclear. This study aimed to assess the impact of BMD on the clinical outcome in Japanese patients with COVID-19 and evaluate the association between BMD and critical outcomes, such as high-flow nasal cannula, non-invasive and invasive positive pressure ventilation, extracorporeal membrane oxygenation, or death. We examined the effects of COVID-19 severity on the change of BMD over time. This multicenter retrospective cohort study enrolled 1132 inpatients with COVID-19 from the Japan COVID-19 Task Force database between February 2020 and September 2022. The bone CT values of the 4th, 7th, and 10th thoracic vertebrae were measured from chest CT images. The average of these values was defined as BMD. Furthermore, a comparative analysis was conducted between the BMD on admission and its value 3 months later. The low BMD group had a higher proportion of critical outcomes than did the high BMD group. In a subanalysis stratifying patients by epidemic wave according to onset time, critical outcomes were higher in the low BMD group in the 1st-4th waves. Multivariable logistic analysis of previously reported factors associated with COVID-19 severity revealed that low BMD, chronic kidney disease, and diabetes were independently associated with critical outcomes. At 3 months post-infection, patients with oxygen demand during hospitalization showed markedly decreased BMD than did those on admission. Low BMD in patients with COVID-19 may help predict severe disease after the disease onset. BMD may decrease over time in patients with severe COVID-19, and the impact on sequelae symptoms should be investigated in the future.

Osteosarcopenia and Mortality in Older Adults Undergoing Transcatheter Aortic Valve Replacement

Importance

Osteosarcopenia is an emerging geriatric syndrome characterized by age-related deterioration in muscle and bone. Despite the established relevance of frailty and sarcopenia among older adults undergoing transcatheter aortic valve replacement (TAVR), osteosarcopenia has yet to be investigated in this setting.

Objective

To determine the association between osteosarcopenia and adverse outcomes following TAVR.

Design, Setting, and Participants

This is a post hoc analysis of the Frailty in Aortic Valve Replacement (FRAILTY-AVR) prospective multicenter cohort study and McGill extension that enrolled patients aged 70 years or older undergoing TAVR from 2012 through 2022. FRAILTY-AVR was conducted at 14 centers in Canada, the United States, and France between 2012 and 2016, and patients at the McGill University-affiliated center in Montreal, Québec, Canada, were enrolled on an ongoing basis up to 2022.

Exposure

Osteosarcopenia as measured on computed tomography (CT) scans prior to TAVR.

Main Outcomes and Measures

Clinically indicated CT scans acquired prior to TAVR were analyzed to quantify psoas muscle area (PMA) and vertebral bone density (VBD). Osteosarcopenia was defined as a combination of low PMA and low VBD according to published cutoffs. The primary outcome was 1-year all-cause mortality. Secondary outcomes were 30-day mortality, hospital length of stay, disposition, and worsening disability. Multivariable logistic regression was used to adjust for potential confounders.

Results

Of the 605 patients (271 [45%] female) in this study, 437 (72%) were octogenarian; the mean (SD) age was 82.6 (6.2) years. Mean (SD) PMA was 22.1 (4.5) cm2 in men and 15.4 (3.5) cm2 in women. Mean (SD) VBD was 104.8 (35.5) Hounsfield units (HU) in men and 98.8 (34.1) HU in women. Ninety-one patients (15%) met the criteria for osteosarcopenia and had higher rates of frailty, fractures, and malnutrition at baseline. One-year mortality was highest in patients with osteosarcopenia (29 patients [32%]) followed by those with low PMA alone (18 patients [14%]), low VBD alone (16 patients [11%]), and normal bone and muscle status (21 patients [9%]) (P < .001). Osteosarcopenia, but not low VBD or PMA alone, was independently associated with 1-year mortality (odds ratio [OR], 3.18; 95% CI, 1.54-6.57) and 1-year worsening disability (OR, 2.11; 95% CI, 1.19-3.74). The association persisted in sensitivity analyses adjusting for the Essential Frailty Toolset, Clinical Frailty Scale, and geriatric conditions such as malnutrition and disability.

Conclusions and Relevance

The findings suggest that osteosarcopenia detected using clinical CT scans could be used to identify frail patients with a 3-fold increase in 1-year mortality following TAVR. This opportunistic method for osteosarcopenia assessment could be used to improve risk prediction, support decision-making, and trigger rehabilitation interventions in older adults.

Performance of calcium quantifications on low-dose photon-counting detector CT with high-pitch: A phantom study

Purpose

To evaluate the performance of calcium quantification on photon-counting detector CT (PCD-CT) with high-pitch at low radiation doses compared to third-generation dual-source energy-integrating detector CT (EID-CT).

Materials and methods

The phantom with three calcium inserts (50, 100, and 300 mg of calcium per milliliter), with and without the elliptical outer layer, was evaluated using high-pitch (3.2) and standard pitch (0.8) on PCD-CT, and standard pitch on EID-CT. Scans were performed with different tube voltages (PCD-CT: 120 and 140 kilo-voltage peak [kVp]; EID-CT: 70/Sn150 and 100/Sn150 kVp) and four radiation doses (1, 3, 5, and, 10 milli-Gray [mGy]). Utilizing the true calcium concentrations (CCtrue) of the phantom as the gold standard references, regression equations for each kVp setting were formulated to convert CT attenuations (CaCT) into measured calcium concentrations (CCm). The correlation analysis between CaCT and CCtrue was performed. The percentage absolute bias (PAB) was calculated from the differences between CCm and CCtrue and used to analyze the effects of scanning parameters on calcium quantification accuracy.

Results

A strong correlation was found between CaCT and CCtrue on PCD-CT (r > 0.99) and EID-CT (r > 0.98). For high- and standard-pitch scans on PCD-CT, the accuracy of calcium quantification is comparable (p = 0.615): the median (interquartile range [IQR]) of PAB was 5.59% (2.79%-8.31%) and 4.87 % (2.62%-8.01%), respectively. The PAB median (IQR) was 7.43% (3.77%-11.75%) for EID-CT. The calcium quantification accuracy of PCD-CT is superior to EID-CT at the large phantom (5.46% [2.68%-9.55%] versus 9.01% [6.22%-12.74%]), and at the radiation dose of 1 mGy (4.43% [2.08%-8.59%] versus 13.89% [8.93%-23.09%]) and 3 mGy (4.61% [2.75%-6.51%] versus 9.97% [5.17%-14.41%]), all p < 0.001.

Conclusions

Calcium quantification using low-dose PCD-CT with high-pitch scanning is feasible and accurate, and superior to EID-CT.

Vertebral HU value and the pectoral muscle index based on chest CT can be used to opportunistically screen for osteoporosis

BACKGROUND

Existing studies have shown that computed tomography (CT) attenuation and skeletal muscle tissue are strongly associated with osteoporosis; however, few studies have examined whether vertebral HU values and the pectoral muscle index (PMI) measured at the level of the 4th thoracic vertebra (T4) are strongly associated with bone mineral density (BMD). In this study, we demonstrate that vertebral HU values and the PMI based on chest CT can be used to opportunistically screen for osteoporosis and reduce fracture risk through prompt treatment.

METHODS

We retrospectively evaluated 1000 patients who underwent chest CT and DXA scans from August 2020-2022. The T4 HU value and PMI were obtained using manual chest CT measurements. The participants were classified into normal, osteopenia, and osteoporosis groups based on the results of dual-energy X-ray (DXA) absorptiometry. We compared the clinical baseline data, T4 HU value, and PMI between the three groups of patients and analyzed the correlation between the T4 HU value, PMI, and BMD to further evaluate the diagnostic efficacy of the T4 HU value and PMI for patients with low BMD and osteoporosis.

RESULTS

The study ultimately enrolled 469 participants. The T4 HU value and PMI had a high screening capacity for both low BMD and osteoporosis. The combined diagnostic model-incorporating sex, age, BMI, T4 HU value, and PMI-demonstrated the best diagnostic efficacy, with areas under the receiver operating characteristic curve (AUC) of 0.887 and 0.892 for identifying low BMD and osteoporosis, respectively.

CONCLUSIONS

The measurement of T4 HU value and PMI on chest CT can be used as an opportunistic screening tool for osteoporosis with excellent diagnostic efficacy. This approach allows the early prevention of osteoporotic fractures via the timely screening of individuals at high risk of osteoporosis without requiring additional radiation.

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

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

Value of Hounsfield units measured by chest computed tomography for assessing bone density in the thoracolumbar segment of the thoracic spine

STUDY DESIGN

A retrospective study.

PURPOSE

To investigate the correlation between Hounsfield unit (HU) values measured by chest computed tomography (CT) and dual-energy Xray absorptiometry (DXA) T-scores. HU-based thoracolumbar (T11 and T12) cutoff thresholds were calculated for a cohort of Chinese patients.

OVERVIEW OF LITERATURE

For patients with osteoporosis, the incidence of fractures in the thoracolumbar segment is significantly higher than that in other sites. However, most current clinical studies have focused on L1.

METHODS

This retrospective study analyzed patients who underwent chest CT and DXA at our hospital between August 2021 and August 2022. Thoracic thoracolumbar segment HU values, lumbar T-scores, and hip T-scores were computed for comparison, and thoracic thoracolumbar segment HU thresholds suggestive of potential bone density abnormalities were established using receiver operating characteristic curves.

RESULTS

In total, 470 patients (72.4% women; mean age, 65.5±12.3 years) were included in this study. DXA revealed that of the 470 patients, 90 (19%) had osteoporosis, 180 (38%) had reduced osteopenia, and 200 (43%) had normal bone mineral density (BMD). To differentiate osteoporosis from osteopenia, the HU threshold was established as 105.1 (sensitivity, 54.4%; specificity, 72.2%) for T11 and 85.7 (sensitivity, 69.4%; specificity, 61.1%) for T12. To differentiate between osteopenia and normal BMD, the HU threshold was 146.7 for T11 (sensitivity, 57.5%; specificity, 84.4%) and 135.7 for T12 (sensitivity, 59.5%; specificity, 80%).

CONCLUSIONS

This study supports the significance of HU values from chest CT for BMD assessment. Chest CT provides a new method for clinical opportunistic screening of osteoporosis. When the T11 HU is >146.7 or the T12 HU is >135.7, additional osteoporosis testing is not needed unless a vertebral fracture is detected. If the T11 HU is <105.1 or the T12 HU is <85.7, further DXA testing is strongly advised. In addition, vertebral HU values that fall faster than those of the T11 and L1 vertebrae may explain the high incidence of T12 vertebral fractures.

Efficacy of Opportunistic Screening with Chest CT in Identifying Osteoporosis and Osteopenia in Patients with T2DM

Purpose

To explore the validity of the thoracic spine Hounsfield Unit (HU) measured by chest computed tomography (CT) for opportunistic screening of diabetic osteoporosis. The current study attempted to establish a diagnostic threshold for thoracic spine HU in a type 2 diabetes mellitus (T2DM) population with osteoporosis.

Patients and Methods

The current study retrospectively included 334 patients with T2DM. They underwent chest CT and Dual-energy X-ray (DXA) between August 2021 and January 2022 in our hospital. HU values were measured on the resulting chest CT images at thoracic spine 11 and 12 to construct regions of interest. All patients were grouped according to the lowest T-value of DXA examination: osteoporosis, osteopenia and normal bone density. HU values were compared with T-values in each group of patients, and receiver operating characteristics curves were plotted to calculate diagnostic thresholds as well as sensitivity and specificity.

Results

There was a strong correlation between the HU values of chest CT and the T-values of DXA (p < 0.01). The sensitivity for osteoporosis was 88.7% for T11 attenuation≤ 98 HU and the specificity for osteoporosis was 87.5% for T12 attenuation ≤ 117HU; the specificity for normal BMD was 85.4% for T11 attenuation ≥ 147 HU and 82% for T12 attenuation ≥ 146 HU.

Conclusion

Chest CT can be used to screen patients with T2DM for opportunistic osteoporosis and help determine if they need DXA screening. The current study suggests that when the HU threshold of T11 ≤ 98/T12 ≤ 117, patients may need further osteoporosis screening.

The Suitable Population for Opportunistic Low Bone Mineral Density Screening Using Computed Tomography

Objective

To explore the suitable population of CT value for predicting low bone mineral density (low-BMD).

Methods

A total of 1268 patients who underwent chest CT examination and DXA within one-month period retrospectively analyzed. The CT attenuation values of trabecular bone were measured in mid-sagittal plane from thoracic vertebra 7 (T7). Receiver operating characteristic (ROC) curves were used to evaluate the ability to diagnose low-BMD.

Results

The AUC for diagnosing low BMD was larger in women than in men (0.894 vs 0.744, p < 0.05). The AUC increased gradually with the increase of age but decreased gradually with the increase in height and weight (p < 0.05). In females, when specificity was adjusted to approximately 90%, a threshold of 140.25 HU has a sensitivity of 69.3%, which is higher than the sensitivity of 36.5% in males for distinguishing low-BMD from normal. At the age of 70 or more, when specificity was adjusted to approximately 90%, a threshold of 126.31 HU has a sensitivity of 76.1%, which was higher than that of other age groups.

Conclusion

For patients who had completed chest CTs, the CT values were more effective in predicting low-BMD in female, elderly, lower height, and lower weight patients.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

ADVANCES IN KNOWLEDGE

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

Diagnostic Accuracy of Deep Learning for the Prediction of Osteoporosis Using Plain X-rays: A Systematic Review and Meta-Analysis

(1) Background: This meta-analysis assessed the diagnostic accuracy of deep learning model-based osteoporosis prediction using plain X-ray images. (2) Methods: We searched PubMed, Web of Science, SCOPUS, and Google Scholar from no set beginning date to 28 February 2023, for eligible studies that applied deep learning methods for diagnosing osteoporosis using X-ray images. The quality of studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 criteria. The area under the receiver operating characteristic curve (AUROC) was used to quantify the predictive performance. Subgroup, meta-regression, and sensitivity analyses were performed to identify the potential sources of study heterogeneity. (3) Results: Six studies were included; the pooled AUROC, sensitivity, and specificity were 0.88 (95% confidence interval [CI] 0.85-0.91), 0.81 (95% CI 0.78-0.84), and 0.87 (95% CI 0.81-0.92), respectively, indicating good performance. Moderate heterogeneity was observed. Mega-regression and subgroup analyses were not performed due to the limited number of studies included. (4) Conclusion: Deep learning methods effectively extract bone density information from plain radiographs, highlighting their potential for opportunistic screening. Nevertheless, additional prospective multicenter studies involving diverse patient populations are required to confirm the applicability of this novel technique.

Differential effect of atorvastatin and pravastatin on thoracic spine attenuation: A sub-analysis of a randomized clinical trial

BACKGROUND

Statins reduce cardiovascular events and may improve bone mineral density.

METHODS

We conducted a sub-analysis of a randomized clinical trial that investigated the differential effect of moderate vs intensive low-density lipoprotein cholesterol (LDL-C) lowering therapies on coronary artery calcium (CAC) scores, and used the acquired images to assess the change in radiological attenuation of selected thoracic vertebrae. Baseline and 12-month unenhanced chest CT scans were performed in 420 hyperlipidemic, postmenopausal women randomized to atorvastatin (ATV) 80 mg/day or pravastatin (PRV) 40 mg/day in the Beyond Endorsed Lipid Lowering with Electron Beam Tomography Scanning (BELLES) trial. Bone attenuation was measured in three contiguous thoracic vertebrae at baseline and 12 months.

RESULTS

There were no differences in baseline demographic and clinical characteristics between treatment arms. The median percent lowering (interquartile range) in LDL-C was significantly greater with ATV than PRV [-53 (-69 to 20)% vs -28 (-55 to 74)%, p < 0.001], although the CAC score change was similar [12 (-63 to 208)% vs 13 (-75 to 358)%; p = 0.44]. At follow-up, the median bone attenuation loss was significantly greater with PRV than with ATV [-2.6 (-27 to 11)% vs 0 (-11 to 25)%; p < 0.001]. The attenuation loss in the PRV group was comparable to that of a historical untreated general population sample. In the entire cohort, the changes in LDL-C and total cholesterol were inversely correlated with bone attenuation change (p < 0.01). In adjusted multivariable linear regression analyses, race and percent change in LDL-C were independent predictors of bone attenuation change. Age, body mass index, history of smoking, diabetes mellitus, hypertension, peripheral vascular disease, or hormone replacement therapy did not affect percent change in BMD.

CONCLUSIONS

These findings support the hypothesis that there is an interaction between bone and cardiometabolic health and that intensive lipid lowering has a beneficial effect on bone health.

Evaluation of multidetector CT Hounsfield unit measurements as a predictor of efficacy and complications in percutaneous vertebroplasty for osteoporotic vertebral compression fractures

Introduction

More than 30 years after the initial experience of Galibert and Deramond with percutaneous vertebroplasty, the procedure has gone through countless refinements and clinical evaluations. Predictors for the success and failure of the procedure in the literature vary and are focused on the duration of complaints, type of fracture, presence of edema on MRI scans, etc. We propose using a quantitative method based on a standard CT examination of the thoracic or lumbar spine to assess the risks and potential success of performing vertebroplasty.

Materials and methods

This is a single-center prospective observational study on 139 patients treated with percutaneous vertebroplasty (pVPL) for a single symptomatic osteoporotic vertebral compression fracture (OVCF). We measured the levels of disability and pain preoperatively and again at the 3-, 6- and 12-month marks using the standardized VAS and ODI questionnaires. Every patient in the study was evaluated with postoperative multidetector CT (MDCT) to determine the presence, extent, and localization of vertebral cement leakage and to measure the adjacent vertebrae's minimal and mean density in Hounsfield units (HUmin and HUmean, respectively).

Results

We determined that a slight (r = -0.201) but statistically significant (p = 0.018) correlation existed between HU measurements taken from radiologically intact adjacent vertebrae and the procedure's effect concerning the pain levels at the 3-month follow-up. This correlation failed to reach statistical significance at 12 months (p = 0.072). We found no statistically significant relationship between low vertebral cancellous bone density and cement leakage on postoperative scans (p = 0.6 for HUmin and p = 0.74 for HUmean).

Conclusion

We have moderately strong data that show a negative correlation between the mean values of vertebral cancellous bone density in patients with OVCF and the effect of pVPL in reducing pain. Lower bone densities, measured this way, showed no increased risk of cement leakage.

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

Objective

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

Methods

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

Results

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

Conclusion

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

The axial and sagittal CT values of the 7th thoracic vertebrae in screening for osteoporosis and osteopenia

AIM

To evaluate the difference in computed tomography (CT) attenuation value of different planes of the 7th thoracic vertebra and investigate the efficacy of axial and sagittal vertebral CT measurements in predicting osteoporosis.

MATERIALS AND METHODS

Patients who underwent routine chest CT and dual-energy X-ray absorptiometry (DXA) within 1 month were included in this retrospective study. The CT attenuation values of different planes were compared. Logistic regression and receiver operating characteristic (ROC) were used to analyse the difference of each plane in the diagnosis of osteoporosis.

RESULTS

The study included 1,338 patients (mean age of 61.9±11.9; 54% female). The CT attenuation values decreased successively in the normal group, osteopenia group, and osteoporosis group. The paired t-test results showed that the mid-axial measurements were greater than mid-sagittal measurements, with a mean difference of 9 HU, the difference was statistically significant (p<0.001, 95% confidence interval [CI] = 7.8-10.1). For each one-unit reduction in mid-sagittal CT attenuation value, the risk of osteopenia or osteoporosis increased by 3.6%. To distinguish osteoporosis from non-osteoporosis (osteopenia + normal), the sensitivity was 90% and the specificity was 52.4% at the mid-sagittal threshold of 113.7 HU.

CONCLUSIONS

The CT attenuation values of mid-sagittal plane have higher diagnostic efficacy than axial planes in predicting osteoporosis. For patients with a sagittal CT attenuation value of <113.7 HU in the T7, further DXA examination is warranted.

The prevalence of osteopenia and osteoporosis after heart transplantation assessed using CT

OBJECTIVE

Osteoporosis is frequently observed in patients after heart transplantation (HT), although the prevalence long-term post-HT is unknown. Most studies investigating bone mineral density (BD) after HT were performed using dual-energy X-ray absorptiometry. In this study BD, including the prevalence of osteopenia and osteoporosis, was investigated using coronary computed tomography (CCT) long-term post-HT. Moreover, risk factors for abnormal BD were investigated.

METHODS

All first CCT scans between February 2018 and June 2020 used for the annual screening for cardiac allograft vasculopathy were included. Retransplantations and scans with not fully imaged vertebrae were excluded. BD was measured as a mean of the BD of three consecutive thoracic vertebrae and categorized into normal BD, osteopenia or osteoporosis. Binary logistic regression was used to find determinants for an abnormal BD. Linear regression was used to explore determinants for the mean Hounsfield unit (HU) value of the BD.

RESULTS

In total, 140 patients were included (median age 55.2 [42.9-64.9] years, 51 (36%) female). Time between HT and CT scan was 11.0 [7.3-16.1] years. In total, 80 (57%), 43 (31%), and 17 (12%) patients had a normal BD, osteopenia, or osteoporosis, respectively. Osteoporotic fracture or vertebrae fractures was seen in 11 (8%) patients. Determinants for an abnormal BD were recipient age (OR 1.10 (1.06-1.14), p<0.001) and prednisolone use (OR 3.75 (1.27-11.01), p=0.016). In linear regression, left ventricular assist device use pre-HT (p=0.024) and time since HT (p=0.046) were additional BD determinants.

DISCUSSION

Osteopenia and osteoporosis are frequently seen on CCT post-HT. More investigation on appropriate measures to maintain a normal BD in these patients are needed.

Prediction of low DEXA T-scores by routine computed tomography body scans at different kilovoltage peaks

INTRODUCTION

Previous studies have demonstrated positive correlations between computed tomography (CT) attenuation of lumbar spine vertebrae and their bone mineral density (BMD) measured by dual-energy X-ray absorptiometry (DEXA). However, these studies were performed using a standard 120 kilovoltage peak (kVp) setting. As radiation attenuation in mineralised tissues varies by the tube voltage applied, we determined the diagnostic accuracy of CT attenuation at identifying individuals with low BMD at different kVp settings.

METHODS

Single centre retrospective study of adults who had CT and DEXA scans within 6 months of each other. CT scans were performed at either 100 kVp, 120 kVp or dual energy (80 kVp/140 kVp). Attenuation was measured in axial cross-sections of L1-4 vertebrae and correlated with the results of DEXA. Receiver operated characteristic (ROC) curves were generated to determine diagnostic cut-off thresholds.

RESULTS

Analysis included 268 subjects (169 females; mean age: 70, range: 20-94 years). CT attenuation values at L1 or mean L1-4 correlated positively with DEXA-derived T-scores. At L1, the optimal Hounsfield units (HU) thresholds for predicting DEXA T-scores of -2.5 or less at 100 kVp, 120 kVp and dual-energy scans were <170, <128 and <164, with corresponding AUCs of 0.925, 0.814 and 0.743 respectively. For mean L1-4, the HU thresholds were <173, <134 and <151, with corresponding AUCs of 0.933, 0.824 and 0.707 respectively.

CONCLUSION

CT attenuation thresholds differ depending on the tube voltage used. We provide voltage-specific, probability-optimised thresholds for the identification of persons likely to have low BMD on DEXA scanning.

Addressing Challenges of Opportunistic Computed Tomography Bone Mineral Density Analysis

Computed tomography (CT) offers advanced biomedical imaging of the body and is broadly utilized for clinical diagnosis. Traditionally, clinical CT scans have not been used for volumetric bone mineral density (vBMD) assessment; however, computational advances can now leverage clinically obtained CT data for the secondary analysis of bone, known as opportunistic CT analysis. Initial applications focused on using clinically acquired CT scans for secondary osteoporosis screening, but opportunistic CT analysis can also be applied to answer research questions related to vBMD changes in response to various disease states. There are several considerations for opportunistic CT analysis, including scan acquisition, contrast enhancement, the internal calibration technique, and bone segmentation, but there remains no consensus on applying these methods. These factors may influence vBMD measures and therefore the robustness of the opportunistic CT analysis. Further research and standardization efforts are needed to establish a consensus and optimize the application of opportunistic CT analysis for accurate and reliable assessment of vBMD in clinical and research settings. This review summarizes the current state of opportunistic CT analysis, highlighting its potential and addressing the associated challenges.

Dual-Energy CT-based Opportunistic Volumetric Bone Mineral Density Assessment of the Distal Radius

Background In patients with distal radius fractures (DRFs), low bone mineral density (BMD) is associated with bone substitute use during surgery and bone nonunion, but BMD information is not regularly available. Purpose To evaluate the feasibility of dual-energy CT (DECT)-based BMD assessment from routine examinations in the distal radius and the relationship between the obtained BMD values, the occurrence of DRFs, bone nonunion, and use of surgical bone substitute. Materials and Methods Scans in patients who underwent routine dual-source DECT in the distal radius between January 2016 and December 2021 were retrospectively acquired. Phantomless BMD assessment was performed using the delineated trabecular bone of a nonfractured segment of the distal radius and both DECT image series. CT images and health records were examined to determine fracture severity, surgical management, and the occurrence of bone nonunion. Associations of BMD with the occurrence of DRFs, bone nonunion, and bone substitute use at surgical treatment were examined with generalized additive models and receiver operating characteristic analysis. Results This study included 263 patients (median age, 52 years; IQR, 36-64 years; 132 female patients), of whom 192 were diagnosed with fractures. Mean volumetric BMD was lower in patients who sustained a DRF (93.9 mg/cm3 vs 135.4 mg/cm3; P < .001), required bone substitutes (79.6 mg/cm3 vs 95.5 mg/cm3; P < .001), and developed bone nonunion (71.1 mg/cm3 vs 96.5 mg/cm3; P < .001). Receiver operating characteristic curve analysis identified these patients with an area under the curve of 0.71-0.91 (P < .001). Lower BMD increased the risk to sustain DRFs, develop bone nonunion, and receive bone substitutes at surgery (P < .001). Conclusion DECT-based BMD assessment at routine examinations is feasible and could help predict surgical bone substitute use and the occurrence of bone nonunion in patients with DRFs. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Carrino in this issue.

Automatic segmentation and radiomic texture analysis for osteoporosis screening using chest low-dose computed tomography

OBJECTIVE

This study developed a diagnostic tool combining machine learning (ML) segmentation and radiomic texture analysis (RTA) for bone density screening using chest low-dose computed tomography (LDCT).

METHODS

A total of 197 patients who underwent LDCT followed by dual-energy X-ray absorptiometry were analyzed. First, an autosegmentation model was trained using LDCT to delineate the thoracic vertebral body (VB). Second, a two-level classifier was developed using radiomic features extracted from VBs for the hierarchical pairwise classification of each patient's bone status. All the patients were initially classified as either normal or abnormal, and all patients with abnormal bone density were then subdivided into an osteopenia group and an osteoporosis group. The performance of the classifier was evaluated through fivefold cross-validation.

RESULTS

The model for automated VB segmentation achieved a Sorenson-Dice coefficient of 0.87 ± 0.01. Furthermore, the area under the receiver operating characteristic curve scores for the two-level classifier were 0.96 ± 0.01 for detecting abnormal bone density (accuracy = 0.91 ± 0.02; sensitivity = 0.93 ± 0.03; specificity = 0.89 ± 0.03) and 0.98 ± 0.01 for distinguishing osteoporosis (accuracy = 0.94 ± 0.02; sensitivity = 0.95 ± 0.03; specificity = 0.93 ± 0.03). The testing prediction accuracy levels for the first- and second-level classifiers were 0.92 ± 0.04 and 0.94 ± 0.05, respectively. The overall testing prediction accuracy of our method was 0.90 ± 0.05.

CONCLUSION

The combination of ML segmentation and RTA for automated bone density prediction based on LDCT scans is a feasible approach that could be valuable for osteoporosis screening during lung cancer screening.

KEY POINTS

• This study developed an automatic diagnostic tool combining machine learning-based segmentation and radiomic texture analysis for bone density screening using chest low-dose computed tomography. • The developed method enables opportunistic screening without quantitative computed tomography or a dedicated phantom. • The developed method could be integrated into the current clinical workflow and used as an adjunct for opportunistic screening or for patients who are ineligible for screening with dual-energy X-ray absorptiometry.

Correlation between bone density measurements on CT or MRI versus DEXA scan: A systematic review

Background

Novel methods of bone density assessment using computed tomography (CT) and magnetic resonance imaging (MRI) have been increasingly reported in the spine surgery literature. Correlations between these newer measurements and traditional Dual-Energy X-ray Absorptiometry (DEXA) is not well known. The purpose of this study is to perform an updated systematic review of correlations between bone mineral density (BMD) from CT or MRI and DEXA.

Methods

Articles published between 2011 and 2021 that reported correlations between the CT-HU or MRI measurements to DEXA t-scores or BMD of lumbar spine or hip were included in this systematic review.

Results

A total of 25 studies (15 CT, 10 MRI) met the inclusion criteria with a total number of 2,745 patients. The pooled correlation coefficient of spine CT-HU versus spine DEXA, spine CT-HU versus hip DEXA and spine CT-HU versus lowest t-score were 0.60, 0.50 and 0.60 respectively. Regarding spine DEXA parameters, the pooled r² for spine CT-HU versus spine t-score was 0.684 and spine CT-HU versus spine BMD was 0.598. Furthermore, in patients undergoing spine surgery in four studies, the pooled correlation between spine CT and spine DEXA was (r²: 0.64). In MRI studies, the pooled r² of spine MRI versus spine DEXA and spine MRI versus hip DEXA were -0.41 and -0.44 respectively.

Conclusions

CT-HU has stronger correlations with DEXA than MRI measurements. Lumbar CT-HU has the highest pooled correlation (r² = 0.6) with both spine DEXA and lowest skeletal t-score followed by lumbar CT-HU with hip DEXA (r² = 0.5) and lumbar MRI with hip (r² = 0.44) and spine (r² = 0.41) DEXA. Both imaging modalities achieved only a moderate correlation with DEXA. Few studies in both modalities have investigated the correlation in spine surgery populations and the available data shows that the correlations are worse in the degenerative spine population. A careful interruption of CT HU and MRI measurement when evaluation of BMD as they only moderately correlated with DEXA scores. At this time, it is unclear which modality is a better predictor of mechanical complications and clinical outcomes in spine surgery patients.

Cortex or cancellous-which is early for the decrease of bone content for vertebral body in health?

OBJECTIVE

To obtain the cortex and cancellous parameter of the vertebral bone of healthy subjects using QCT. To explore which is earlier or faster for bone loss with age.

MATERIALS AND METHODS

733 physical examiners underwent chest low-dose CT examination were recruited, from April 1, 2021 to October 1, 2021. QCT sequence was used to obtain the bone mineral density of T12-L2 vertebral body without additional radiation. The mass and area of vertebral cortex and cancellous at the central level of L2 vertebral body were measured. The age -related characteristics of vertebral cortex and cancellous between male and female was analyzed and compared.

RESULTS

The vBMD of T12-L2 vertebral body decreased with age. Significant differences were found in volumetric bone mineral density (vBMD) of T12-L2 vertebral body. For female, significant differences were found in bone content involving cortical mass, cancellous mass, cortical area, cancellous area, cortical mass/cancellous mass and cortical area/cancellous area in different age groups, respectively. The cortical mass decreased with age in female. The cancellous mass of female increased and then decreased with peak at 31-40 y. The cortical area of female decreased gradually before 71 y. The cancellous area of female increased and then decreased with peak at 51-60 y. The values of mass ratio and area ratio in female showed a slowly downward trend with age. Significant differences of bone content between non-menopausal and menopausal women were found except the cancellous mass. For male, no significant differences were found in all parameters of bone content.

CONCLUSION

The changes of vertebral BMD, bone content of cortex and cancellous have different characteristics in different age. The change of cortex in female maybe earlier and faster than that of cancellous, especially in menopausal women.

Opportunistic osteoporosis screening using chest CT with artificial intelligence

Osteoporosis has a high incidence and a low detection rate. If it is not detected in time, it will cause osteoporotic fracture and other serious consequences. This study showed that the attenuation values of vertebrae on chest CT could be used for opportunistic screening of osteoporosis. This will be beneficial to improve the detection rate of osteoporosis and reduce the incidence of adverse events caused by osteoporosis.

INTRODUCTION

To explore the value of the attenuation values of all thoracic vertebrae and the first lumbar vertebra measured by artificial intelligence on non-enhanced chest CT to do osteoporosis screening.

METHODS

On base of images of chest CT, using artificial intelligence (AI) to measure the attenuation values (HU) of all thoracic and the first vertebrae of patients who underwent CT examination for lung cancer screening and dual-energy X-ray absorptiometry (DXA) examination during the same period. The patients were divided into three groups: normal group, osteopenia group, and osteoporosis group according to the results of DXA. Clinical baseline data and attenuation values were compared among the three groups. The correlation between attenuation values and BMD values was analyzed, and the predictive ability and diagnostic efficacy of attenuation values of thoracic and first lumbar vertebrae on osteopenia or osteoporosis risk were further evaluated.

RESULTS

CT values of each thoracic vertebrae and the first lumbar vertebrae decreased with age, especially in menopausal women and presented high predictive ability and diagnostic efficacy for osteopenia or osteoporosis. After clinical data correction, with every 10 HU increase of CT values, the risk of osteopenia or osteoporosis decreased by 32 ~ 44% and 61 ~ 80%, respectively. And the combined diagnostic efficacy of all thoracic vertebrae was higher than that of a single vertebra. The AUC of recognizing osteopenia or osteoporosis from normal group was 0.831and 0.972, respectively.

CONCLUSIONS

The routine chest CT with AI is of great value in opportunistic screening for osteopenia or osteoporosis, which can quickly screen the population at high risk of osteoporosis without increasing radiation dose, thus reducing the incidence of osteoporotic fracture.

Increased chest CT derived bone and muscle measures capture markers of improved morbidity and mortality in COPD

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a disease of accelerated aging and is associated with comorbid conditions including osteoporosis and sarcopenia. These extrapulmonary conditions are highly prevalent yet frequently underdiagnosed and overlooked by pulmonologists in COPD treatment and management. There is evidence supporting a role for bone-muscle crosstalk which may compound osteoporosis and sarcopenia risk in COPD. Chest CT is commonly utilized in COPD management, and we evaluated its utility to identify low bone mineral density (BMD) and reduced pectoralis muscle area (PMA) as surrogates for osteoporosis and sarcopenia. We then tested whether BMD and PMA were associated with morbidity and mortality in COPD.

METHODS

BMD and PMA were analyzed from chest CT scans of 8468 COPDGene participants with COPD and controls (smoking and non-smoking). Multivariable regression models tested the relationship of BMD and PMA with measures of function (6-min walk distance (6MWD), handgrip strength) and disease severity (percent emphysema and lung function). Multivariable Cox proportional hazards models were used to evaluate the relationship between sex-specific quartiles of BMD and/or PMA derived from non-smoking controls with all-cause mortality.

RESULTS

COPD subjects had significantly lower BMD and PMA compared with controls. Higher BMD and PMA were associated with increased physical function and less disease severity. Participants with the highest BMD and PMA quartiles had a significantly reduced mortality risk (36% and 46%) compared to the lowest quartiles.

CONCLUSIONS

These findings highlight the potential for CT-derived BMD and PMA to characterize osteoporosis and sarcopenia using equipment available in the pulmonary setting.

ACR Appropriateness Criteria® Osteoporosis and Bone Mineral Density: 2022 Update

Osteoporosis constitutes a significant public health risk. An estimated 10.2 million adults in the United States >50 years of age have osteoporosis, a systemic condition that weakens the bones increasing the susceptibility for fractures. Approximately one-half of women and nearly one-third of men >50 years of age will sustain an osteoporotic fracture. These fractures are associated with a decrease in quality of life, diminished physical function, and reduced independence. Dual-energy X-ray absorptiometry (DXA) is the primary imaging modality used to screen for osteoporosis in women >65 years of age and men >70 years of age. DXA may be used in patients <65 years of age to evaluate bone mass density if there are additional risk factors. In certain situations, vertebral fracture assessment and trabecular bone score may further predict fracture risk, particularly in patients who are not yet osteoporotic but are in the range of osteopenia. Quantitative CT is useful in patients with advanced degenerative changes in the spine. Given the proven efficacy of pharmacologic therapy, the role of imaging to appropriately identify and monitor high-risk individuals is critical in substantially reducing osteoporosis-associated morbidity and mortality, and reducing the considerable cost to the health care system. The ACR Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Intra-individual comparison of lumbar spine CT, abdomen-pelvis contrast enhanced CT, and low-dose chest CT for bone density measurement

BACKGROUND

Dual-energy X-ray absorptiometry (DXA) is the reference standard for the measurement of bone mineral density (BMD) and subsequent diagnosis of osteoporosis. Since various computed tomography (CT) protocols are scanned for various indications, we can incidentally measure BMD using CT. Previous studies have revealed a correlation between BMD and Hounsfield unit (HU) values obtained with different CT protocols.

PURPOSE

To compare the diagnostic value of CT protocols (lumbar spine CT [LSCT], abdomen-pelvis contrast-enhanced CT [APCT], and low-dose chest CT [LDCT]) for osteoporosis.

MATERIAL AND METHODS

We retrospectively included 17 patients (6 men, 11 women; mean age=68 years) who had undergone all four imaging studies within six months, during 2011-2021. HU values were manually measured at the center of the L1 vertebra by a radiology resident. Pearson correlation test was performed between HU values and BMD of L1 vertebra. The diagnostic performance of each CT protocol was assessed with receiver operating characteristic (ROC) analysis. Intra-individual concordance of the four tests to diagnose osteoporosis was analyzed by tabulating.

RESULTS

The mean HU values were 104.4 ± 47.2 HU with LSCT, 149.0 ± 56.9 HU with APCT, and 114.3 ± 60.0 HU with LDCT. HU values from each protocol were positively correlated (r = 0.676-0.735; P < 0.005) with BMD. LDCT had the highest diagnostic performance (area under the ROC curve [AUC] = 0.701) and APCT the lowest (AUC = 0.569). APCT was discordant with the other protocols for diagnosing osteoporosis.

CONCLUSION

LDCT had the highest diagnostic performance for osteoporosis with predetermined cutoff value. APCT requires the increase of cutoff value for osteoporosis diagnosis.

Machine learning for the prediction of osteopenia/osteoporosis using the CT attenuation of multiple osseous sites from chest CT

PURPOSE

To use machine learning and the CT attenuation of all bones visible on chest CT scans to predict osteopenia/osteoporosis.

METHOD

We retrospectively evaluated 364 patients with CT scans of the chest, and Dual-energy X-ray absorptiometry (DXA) scans within 6 months of each other. Studies were performed between 01/01/2015 and 08/01/2021. Volumetric segmentation of the ribs, thoracic vertebrae, sternum, and clavicle was performed using 3D Slicer to obtain the mean CT attenuation of each bone. The study sample was randomly split into training/validation (80 %, n = 291 patients) and test (20 %, n = 73 patients) datasets. Univariate analyses were used to identify the optimal CT attenuation thresholds to diagnose osteopenia/osteoporosis. We used penalized multivariable logistic regression models including Least Absolute Shrinkage and Selection Operator (LASSO), Elastic Net, and Ridge regression, and Support Vector Machines (SVM) with radial basis functions (RBF) to predict osteopenia/osteoporosis and compared these results to the CT attenuation threshold at T12.

RESULTS

There were positive correlations between the CT attenuation between all bones (r > 0.6, P < 0.001 for all). There were positive correlations between CT attenuation of the bones and the L1-L4 BMD T-score, total hip T-score, and femoral neck T-scores (r > 0.4, P < 0.001 for all). A CT attenuation threshold of 170.2 Hounsfield units (HU) at T12 had an AUC of 0.702, while a threshold of 192.1 HU at T4 had an AUC of 0.757. The SVM with RBF had the highest AUC (AUC = 0.864) and was better than the LASSO (P = 0.011), Elastic Net (P = 0.011), Ridge regression (P = 0.011) but was not better than using the CT attenuation at T12 (P = 0.060).

CONCLUSIONS

The CT attenuation of the ribs, thoracic vertebra, sternum, and clavicle can be used individually and collectively to predict BMD and to predict osteopenia/osteoporosis.

One Novel Phantom-Less Quantitative Computed Tomography System for Auto-Diagnosis of Osteoporosis Utilizes Low-Dose Chest Computed Tomography Obtained for COVID-19 Screening

Background: The diagnosis of osteoporosis is still one of the most critical topics for orthopedic surgeons worldwide. One research direction is to use existing clinical imaging data for accurate measurements of bone mineral density (BMD) without additional radiation.

Methods: A novel phantom-less quantitative computed tomography (PL-QCT) system was developed to measure BMD and diagnose osteoporosis, as our previous study reported. Compared with traditional phantom-less QCT, this tool can conduct an automatic selection of body tissues and complete the BMD calibration with high efficacy and precision. The function has great advantages in big data screening and thus expands the scope of use of this novel PL-QCT. In this study, we utilized lung cancer or COVID-19 screening low-dose computed tomography (LDCT) of 649 patients for BMD calibration by the novel PL-QCT, and we made the BMD changes with age based on this PL-QCT.

Results: The results show that the novel PL-QCT can predict osteoporosis with relatively high accuracy and precision using LDCT, and the AUC values range from 0.68 to 0.88 with DXA results as diagnosis reference. The relationship between PL-QCT BMD with age is close to the real trend population (from ∼160 mg/cc in less than 30 years old to ∼70 mg/cc in greater than 80 years old for both female and male groups). Additionally, the calculation results of Pearson’s r-values for correlation between CT values with BMD in different CT devices were 0.85–0.99.

Conclusion: To our knowledge, it is the first time for automatic PL-QCT to evaluate the performance against dual-energy X-ray absorptiometry (DXA) in LDCT images. The results indicate that it may be a promising tool for individuals screened for low-dose chest computed tomography.

Prognostic factors of worse outcome for hospitalized COVID-19 patients, with emphasis on chest computed tomography data: a retrospective study

OBJECTIVE

To evaluate anthropometric and clinical data, muscle mass, subcutaneous fat, spine bone mineral density, extent of acute pulmonary disease related to COVID-19, quantification of pulmonary emphysema, coronary calcium, and hepatic steatosis using chest computed tomography of hospitalized patients with confirmed diagnosis of COVID-19 pneumonia and verify its association with disease severity.

METHODS

A total of 123 adults hospitalized due to COVID-19 pneumonia were enrolled in the present study, which evaluated the anthropometric, clinical and chest computed tomography data (pectoral and paravertebral muscle area and density, subcutaneous fat, thoracic vertebral bodies density, degree of pulmonary involvement by disease, coronary calcium quantification, liver attenuation measurement) and their association with poorer prognosis characterized through a combined outcome of intubation and mechanical ventilation, need of intensive care unit, and death.

RESULTS

Age (p=0.013), body mass index (p=0.009), lymphopenia (p=0.034), and degree of pulmonary involvement of COVID-19 pneumonia (p<0.001) were associated with poor prognosis. Extent of pulmonary involvement by COVID-19 pneumonia had an odds ratio of 1,329 for a poor prognosis and a cutoff value of 6.5 for increased risk, with a sensitivity of 64.9% and specificity of 67.1%.

CONCLUSION

The present study found an association of high body mass index, older age, extent of pulmonary involvement by COVID-19, and lymphopenia with severity of COVID-19 pneumonia in hospitalized patients.

Efficacy of Hounsfield Units Measured by Lumbar Computer Tomography on Bone Density Assessment: A Systematic Review

STUDY DESIGN

Systematic review.

OBJECTIVE

This work aimed to compare the Hounsfield units (HU) value obtained from computed tomography and the t score of dual-energy x-ray absorptiometry (DXA) in the prediction of the lumbar spine bone mineral density (BMD).

SUMMARY OF BACKGROUND DATA

Several reports have found a correlation between HU and BMD values based on DXA. Using HUs to infer bone quality has a thorough clinical relevance as it could triage patients at risk for osteoporotic and fragility fractures or modify surgical indications.

METHODS

A systematic review in Cochrane Library, Medline, Scopus and Web of Science was performed, using the following query: "hounsfield units" AND ("osteoporosis" OR "spine" OR "bone mineral density" OR "dual x-ray absorptiometry"). We included 18 cohort studies that compared HU value obtained from computed tomography and t score of DXA for predicting regional BMD.

RESULTS

A total of 18 studies were included, enrolling 5307 patients. The HU measurement was most frequently made at L1 (N = 3; 18.8%). The mean HU values differentiated based on BMD measured through DXA were reported in seven studies, with values from 54.7 to 130 for osteoporotic, 78.8 to 146 for osteopenic, and from 120.8 to 230 in normal patients. Eight studies identified thresholds for diagnosing osteoporosis through receiver-operating characteristic (ROC) curves, with values ranging from 0.66 to 0.96. Medium HU values reported as diagnostic of osteoporosis ranged between 110 and 150, after exclusion of the two papers presenting outlier values. We infer an HU interval value of 90.9 to 138.7 (95% CI, P  < 0.001) for the diagnosis osteoporosis.

CONCLUSIONS

Present data evidence favorable results regarding the possibility of establishing a threshold value for osteoporosis diagnosis from CT measurements of HU. Prospective large-scale studies are needed to more robustly infer the possibility of quantifying BMD based on CT as a screening test and infer a prognostic value of the CT-based evaluation.Level of Evidence: 2.

Correlation between Hounsfield unit derived from head, thorax, abdomen, spine and pelvis CT and t-scores from DXA

OBJECTIVES

CT examination can potentially be utilised for early detection of bone density changes with no additional procedure and radiation dose. We hypothesise that the Hounsfield unit (HU) measured from CT images is correlated to the t-scores derived from dual energy X-ray absorptiometry (DXA) in multiple anatomic regions.

MATERIALS & METHODS

Data were obtained retrospectively from all patients who underwent both CT examinations - brain (frontal bone), thorax (T7), abdomen (L3), spine (T7 & L3) or pelvis (left hip) - and DXA between 2014 and 2018 in our centre. To ensure comparability, the period between CT and DXA studies must not exceed one year. Correlations between HU values and t-scores were calculated using Pearson's correlation. Receiver operating characteristic (ROC) curves were generated, and the area under the curve (AUC) was used to determine threshold HU values for predicting osteoporosis.

RESULTS

The inclusion criteria were met by 1043 CT examinations (136 head, 537 thorax, 159 lumbar and 151 left hip). The left hip consistently provided the most robust correlations (r = 0.664-0.708, p < 0.001) and the best AUC (0.875-0.893). Meanwhile, thorax T7 and lumbar L3 showed average correlations (range of r values is 0.497-0.679, p < 0.001, AUC range = 0.680-0.783, 95% CI 0.561-0.922, all p < 0.02) and moderate AUC (0.680-0.783). Frontal bone shows low correlation and weak AUC with r < 0.5, AUC = 0.538-0.655, all p > 0.05.

CONCLUSION

HU values derived from the hip, T7 and L3 provided a good to moderate correlation to t-scores with a good prediction for osteoporosis. The suggested optimal thresholds may be used in clinical settings after external validations are performed.

Diagnostic accuracy of quantitative dual-energy CT-based volumetric bone mineral density assessment for the prediction of osteoporosis-associated fractures

OBJECTIVES

To evaluate the predictive value of volumetric bone mineral density (BMD) assessment of the lumbar spine derived from phantomless dual-energy CT (DECT)-based volumetric material decomposition as an indicator for the 2-year occurrence risk of osteoporosis-associated fractures.

METHODS

L1 of 92 patients (46 men, 46 women; mean age, 64 years, range, 19-103 years) who had undergone third-generation dual-source DECT between 01/2016 and 12/2018 was retrospectively analyzed. For phantomless BMD assessment, dedicated DECT postprocessing software using material decomposition was applied. Digital files of all patients were sighted for 2 years following DECT to obtain the incidence of osteoporotic fractures. Receiver operating characteristic (ROC) analysis was used to calculate cut-off values and logistic regression models were used to determine associations of BMD, sex, and age with the occurrence of osteoporotic fractures.

RESULTS

A DECT-derived BMD cut-off of 93.70 mg/cm³ yielded 85.45% sensitivity and 89.19% specificity for the prediction to sustain one or more osteoporosis-associated fractures within 2 years after BMD measurement. DECT-derived BMD was significantly associated with the occurrence of new fractures (odds ratio of 0.8710, 95% CI, 0.091-0.9375, p < .001), indicating a protective effect of increased DECT-derived BMD values. Overall AUC was 0.9373 (CI, 0.867-0.977, p < .001) for the differentiation of patients who sustained osteoporosis-associated fractures within 2 years of BMD assessment.

CONCLUSIONS

Retrospective DECT-based volumetric BMD assessment can accurately predict the 2-year risk to sustain an osteoporosis-associated fracture in at-risk patients without requiring a calibration phantom. Lower DECT-based BMD values are strongly associated with an increased risk to sustain fragility fractures.

KEY POINTS

•Dual-energy CT-derived assessment of bone mineral density can identify patients at risk to sustain osteoporosis-associated fractures with a sensitivity of 85.45% and a specificity of 89.19%. •The DECT-derived BMD threshold for identification of at-risk patients lies above the American College of Radiology (ACR) QCT guidelines for the identification of osteoporosis (93.70 mg/cm³ vs 80 mg/cm³).

A meta-analysis of the diagnostic accuracy of Hounsfield units on computed topography relative to dual-energy X-ray absorptiometry for the diagnosis of osteoporosis in the spine surgery population

BACKGROUND

The preoperative identification of osteoporosis in the spine surgery population is of crucial importance. Limitations associated with dual-energy x-ray absorptiometry, such as access and reliability, have prompted the search for alternative methods to diagnose osteoporosis. The Hounsfield Unit(HU), a readily available measure on computed tomography, has garnered considerable attention in recent years as a potential diagnostic tool for reduced bone mineral density. However, the optimal threshold settings for diagnosing osteoporosis have yet to be determined.

METHODS

We selected studies that included comparison of the HU(index test) with dual-energy x-ray absorptiometry evaluation(reference test). Data quality was assessed using the standardised QUADAS-2 criteria. Studies were characterised into 3 categories, based on the threshold of the index test used with the goal of obtaining a high sensitivity, high specificity or balanced sensitivity-specificity test.

RESULTS

9 studies were eligible for meta-analysis. In the high specificity group, the pooled sensitivity was 0.652 (95% CI 0.526 - 0.760), specificity 0.795 (95% CI 0.711 - 0.859) and diagnostic odds ratio was 6.652 (95% CI 4.367 - 10.133). In the high sensitivity group, the overall pooled sensitivity was 0.912 (95% CI 0.718 - 0.977), specificity was 0.67 (0.57 - 0.75) and diagnostic odds ratio was 19.424 (5.446 - 69.275). In the balanced sensitivity-specificity group, the overall pooled sensitivity was 0.625 (95% CI 0.504 - 0.732), specificity was 0.914 (0.823 - 0.960) and diagnostic odds ratio was 14.880 (7.521 - 29.440). Considerable heterogeneity existed throughout the analysis.

CONCLUSION

In conclusion, the HU is a clinically useful tool to aide in the diagnosis of osteoporosis. However, the heterogeneity seen in this study warrants caution in the interpretation of results. We have demonstrated the impact of differing HU threshold values on the diagnostic ability of this test. We would propose a threshold of 135 HU to diagnose OP. Future work would investigate the optimal HU cut-off to differentiate normal from low bone mineral density.

Advancements in Osteoporosis Imaging, Screening, and Study of Disease Etiology

PURPOSE OF REVIEW

The purpose of this review is to inform researchers and clinicians with the most recent imaging techniques that are employed (1) to opportunistically screen for osteoporosis and (2) to provide a better understanding into the disease etiology of osteoporosis.

RECENT FINDINGS

Phantomless calibration techniques for computed tomography (CT) may pave the way for better opportunistic osteoporosis screening and the retroactive analysis of imaging data. Additionally, hardware advances are enabling new applications of dual-energy CT and cone-beam CT to the study of bone. Advances in MRI sequences are also improving imaging evaluation of bone properties. Finally, the application of image registration techniques is enabling new uses of imaging to investigate soft tissue-bone interactions as well as bone turnover. While DXA remains the most prominent imaging tool for osteoporosis diagnosis, new imaging techniques are becoming more widely available and providing additional information to inform clinical decision-making.

Opportunistic CT screening of osteoporosis on thoracic and lumbar spine: a meta-analysis

BACKGROUND

Osteoporotic fractures are a major contributor to late life morbidity and mortality, and impose a substantial societal cost, yet osteoporosis remains substantially underdiagnosed and undertreated. The purpose of this meta-analysis was to assess the pooled diagnostic sensitivity and specificity of computed tomography (CT) images for diagnosing osteoporosis in patients who meet WHO dual X-ray absorptiometry (DXA) osteoporosis criteria using specific Hounsfield unit (HU) values as a threshold.

METHODS

Systematic literature searches in PubMed, Embase, Web of Science and Google Scholar were performed from the earliest available date through 1 July 2018, restricted to publications in English. Participants in all studies underwent CT scans that included the lumbar and/or thoracic spine for different indications and HU measurements were used to identify osteoporosis. DXA scans served as the reference standard.

RESULTS

Ten eligible studies were identified. The mean area under the hierarchical summary receiver operating characteristic (ROC) curve for diagnosis osteoporosis was 0.84 (95% CI: 0.81, 0.87). The pooled diagnostic sensitivity and specificity of CT images to identify osteoporosis were 0.83 (95% CI: 0.73, 0.90) and 0.74 (95% CI: 0.69, 0.79). The positive likelihood ratio (LR+), negative likelihood ratio (LR-), and diagnostic odds ratio were 3.4 (95% CI: 2.7, 4.5), 0.21 (95% CI: 0.12, 0.36), and 16.4 (95% CI: 7.8, 34.3), respectively. The bias-adjusted sensitivity and specificity of CT were 0.73 and 0.71. Meta-regression demonstrated that country of study, DXA criteria and scanner manufacturer were significant factors associated with the sensitivity of CT in detecting osteoporosis while scanner manufacturer was the only factor associated with specificity of CT.

CONCLUSIONS

This meta-analysis showed reasonable pooled sensitivity and specificity for using threshold values measured on CT scans to identify osteoporosis opportunistically.

The radiologist's role in lung cancer screening

Lung cancer is still the deadliest cancer in men and women worldwide. This high mortality is related to diagnosis in advanced stages, when curative treatment is no longer an option. Large randomized controlled trials have shown that lung cancer screening (LCS) with low-dose computed tomography (CT) can detect lung cancers at earlier stages and reduce lung cancer-specific mortality. The recent publication of the significant reduction of cancer-related mortality by 26% in the Dutch-Belgian NELSON LCS trial has increased the likelihood that implementation of LCS in Europe will move forward. Radiologists are important stakeholders in numerous aspects of the LCS pathway. Their role goes beyond nodule detection and nodule management. Being part of a multidisciplinary team, radiologists are key players in numerous aspects of implementation of a high quality LCS program. In this non-systematic review we discuss the multifaceted role of radiologists in LCS.

Risk of vertebral fractures: evaluation on vertebral trabecular attenuation value and hydroxyapatite concentration in patients by chest spectral CT

OBJECTIVES

To analyze vertebral fractures risk in patients with chest scans by evaluating vertebral hydroxyapatite concentration measured on spectral CT compared to trabecular attenuation value measured on conventional CT.

METHODS

Our retrospective study reviewed CT of 216 patients. Analysis of vertebral (T11 - L1) hydroxyapatite concentration by spectral imaging and trabecular attenuation value by conventional CT imaging were performed in patients with chest CT examinations. Specificity, sensitivity, negative predictive value (NPV), and positive predictive value (PPV) were performed by using receiver operating characteristic (ROC) curves in patients with and without vertebral fractures.

RESULTS

In male patients, vertebral hydroxyapatite concentration had high area under the ROC curve (0.916), by using the optimal threshold of 72.27 mg/cm³, specificity, sensitivity, NPV, and PPV were 91.7, 80.2, 36.7, and 98.7%, respectively. In female patients, vertebral hydroxyapatite concentration also had high area under the ROC curve (0.870), by using the optimal threshold of 74.79 mg/cm³, specificity, sensitivity, NPV, and PPV were 100.0, 77.8, 47.4, and 100.0%, respectively. Area under the ROC curve was significantly different between spectral CT-measured bone hydroxyapatite concentration and conventional CT-measured attenuation value in distinguishing vertebral fractures (p = 0.007 for males; p = 0.005 for females).

CONCLUSIONS

Quantitative assessment with spectral CT may appear as higher accuracy than that of conventional CT imaging to analyze risk of vertebral fractures. Hydroxyapatite concentration measured with chest spectral CT may be used to evaluate risk of bone fractures.

ADVANCES IN KNOWLEDGE

Hydroxyapatite concentration measured with chest spectral CT may be used to evaluate risk of bone fractures.

CT Imaging and Comorbidities in COPD: Beyond Lung Cancer Screening

Comorbidities significantly contribute to morbidity, mortality, and health-care costs in individuals with COPD. Comorbidity prevalence does not always correlate with lung disease severity, and the elevated risk of certain comorbidities is often independent of shared risk factors such as tobacco burden. Although COPD management guidelines recognize the importance of identifying and treating comorbidities as part of the comprehensive management of COPD patients, little guidance is provided regarding best screening practices. Whereas universal comorbidity screening in COPD patients is likely not cost-effective, targeted early screening and treatment in those at highest risk may have a significant impact on COPD outcomes. Recent studies suggest that certain radiographic features on thoracic imaging may serve as surrogate markers of comorbidity in patients with COPD. This review evaluates these studies in the context of the growing availability of chest CT scans in the lung cancer screening era and discusses how chest CT imaging can be leveraged to identify those COPD patients at highest risk for comorbid disease.

Opportunistic Computed Tomography and Spine Surgery: A Narrative Review

STUDY DESIGN

Narrative review.

OBJECTIVE

This article seeks to provide a narrative review regarding the ability of opportunistic information available from computed tomography (CT) scans to guide decisions in spine surgery related to patient bone quality.

METHODS

A review of the literature (limited to human and English language) was performed via PubMed and Google Scholar using the search terms; "osteoporosis" AND "opportunistic" AND "computed tomography" AND "spine surgery." The titles and then abstracts of all identified citations were reviewed for inclusion by 2 of the authors (MS, BAF). Relevant articles were then studied in full text.

RESULTS

A review of the literature found 25 articles that were selected for inclusion in this narrative review. These articles were broadly divided into 4 subcategories: (1) opportunistic CT (oCT) and osteoporosis detection, (2) oCT data and the quality of screw fixation, (3) utilization of Hounsfield units to assess clinical and/or radiographic outcomes following spine fusion, and (4) virtual stress testing in spine surgery.

CONCLUSION

The literature on oCT, as well as associated virtual stress-testing techniques, demonstrate the potential to enhance spine surgery outcomes by preoperatively identifying at-risk patients in need of bone health optimization and informing best techniques for performing spinal fusion surgery on patients with diminished bone quality. While our narrative summary of the limited literature to date suggests a promising future for oCT data, significant additional research and/or radiographic workflow standardization is needed to validate these methods for clinical use.

Association between vertebral bone mineral density, myocardial perfusion, and long-term cardiovascular outcomes: A sex-specific analysis

BACKGROUND

Sexual dimorphism in the manifestation of coronary artery disease (CAD) has unleashed a call to reconsider cardiovascular risk assessment. Alterations of bone mineral density (BMD) have been associated with congestive heart failure and appear to be modified by sex. However, the sex-specific association between BMD, myocardial perfusion, and cardiovascular outcomes is currently unknown.

METHODS

A total number of 491 patients (65.9 ± 10.7 years, 32.4% women) underwent 13N-ammonia positron emission tomography/computed tomography for evaluation of CAD, and were tracked for major adverse cardiac events (MACEs).

RESULTS

Event-free survival (median follow-up time of 4.3 ± 2.0 years) was significantly reduced in patients with low (≤ 100 Hounsfield units) compared to those with higher BMD (log-rank P = .037). Accordingly, reduced BMD was chosen as significant predictor of MACE in a fully adjusted proportional hazards regression model (P = .015). Further, a first-order interaction term consisting of sex and BMD was statistically significant (P = .007). BMD was significantly lower in patients with abnormal myocardial perfusion or impaired left ventricular ejection fraction (P < .05). This difference, however, was noticed in men, but not in women.

CONCLUSIONS

The association between low BMD and cardiovascular disease is sex dependent. Our data suggest that quantification of BMD during myocardial perfusion imaging for evaluation of CAD may be particularly useful in men.

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.

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.

Vertebral bone attenuation in Hounsfield Units and prevalent vertebral fractures are associated with the short-term risk of vertebral fractures in current and ex-smokers with and without COPD: a 3-year chest CT follow-up study

CT scans performed to evaluate chronic obstructive pulmonary disease (COPD) also enable evaluation of bone attenuation (BA; a measure of bone density) and vertebral fractures (VFs). In 1239 current/former smokers with (n = 999) and without (n = 240) COPD, the combination of BA and prevalent VFs was associated with the incident VF risk.

INTRODUCTION

Chest CT scans are increasingly used to evaluate pulmonary diseases, including COPD. COPD patients have increased risk of osteoporosis and VFs. BA on CT scans is correlated with bone mineral density and prevalent VFs. The aim of this study was to evaluate the association between BA and prevalent VFs on chest CT scans, and the risk of incident VFs in current and former smokers with and without COPD.

METHODS

In participants of the ECLIPSE study with baseline and 1-year and 3-year follow-up CT scans, we evaluated BA in vertebrae T₄-T₁₂ and prevalent and incident VFs.

RESULTS

A total of 1239 subjects were included (mean age 61.3 ± 8.0, 61.1% men, 999 (80.6%) COPD patients). The mean BA was 155.6 ± 47.5 Hounsfield Units (HU); 253 (20.5%) had a prevalent VF and 296 (23.9%) sustained an incident VF within 3 years. BA and prevalent VFs were associated with incident VFs within 1 (per - 1SD HR = 1.38 [1.08-1.76] and HR = 3.97 [2.65-5.93] resp.) and 3 years (per - 1SD HR = 1.25 [1.08-1.45] and HR = 3.10 [2.41-3.99] resp.), while age, sex, body mass index (BMI), smoking status and history, or presence of COPD was not. In subjects without prevalent VFs and BA, and for 1-year incidence, BMI values were associated with incident fractures (1 year, BA per - 1SD HR = 1.52 [1.05-2.19], BMI per SD HR = 1.54 [1.13-2.11]; 3 years, per - 1SD HR = 1.37 [1.12-1.68]).

CONCLUSIONS

On CT scans performed for pulmonary evaluation in (former) smokers with and without COPD, the combination of BA and prevalent VFs was strongly associated with the short-term risk of incident VFs.