Opportunistic screening for osteoporosis and osteopenia by routine computed tomography scan: A heterogeneous, multiethnic, middle-eastern population validation study

Analysis of the Predictive Efficiency of Lumbar Vertebral Body Quantification (VBQ) and CT Hounsfield Units (HUs) for Bone Density: Age and Gender Differences

Study DesignRetrospective Cohort Study.ObjectiveThis study examines the consistency of Vertebral Bone Quality (VBQ) and Computed Tomography Hounsfield Units (CT HUs) with Dual-energy X-ray absorptiometry (DXA) as a reference standard, evaluating the diagnostic performance of these 2 imaging techniques across different age groups and genders. Particular attention is given to the applicability of VBQ in different age and gender cohorts.MethodsWe included 972 eligible patients, from which 569 patients were randomly selected and included in the analysis according to the inclusion criteria. These patients underwent lumbar Magnetic Resonance Imaging (MRI), lumbar CT, and DXA within 3 months of hospital admission. The study assessed the correlation and diagnostic efficacy of these techniques in measuring lumbar and femoral neck bone mineral density (BMD).ResultsIt showed good correlation between VBQ and CT HUs with DXA in individuals under 70 years of age. However, in the population over 70 years, the correlation of VBQ with DXA significantly decreased (lumbar BMD pr = -.145 P > .05; femoral neck BMD r = -.097 P > .05), whereas CT HUs maintained high diagnostic performance. The ROC curve analysis indicated that the AUC for differentiating osteoporosis (based on lumbar spine BMD) by VBQ was .545 in males over 70 and .487 in females over 70. However, CT HUs demonstrated diagnostic performance across all groups.ConclusionVBQ is effective in assessing osteoporosis in patients under 70 but shows decreased efficacy in those over 70. When using VBQ to predict osteoporosis in patients on opportunistic grounds, it is still necessary to incorporate additional reference indicators, such as CT HUs.

Accuracy of Phantomless Calibration of Routine Computed Tomography Scans for Opportunistic Osteoporosis Screening in the Spine Clinic

STUDY DESIGN

Diagnostic accuracy study.

OBJECTIVE

To establish a simple method of phantomless bone mineral density (BMD) measurement by using preoperative lumbar computed tomography (CT) scans, and compare the accuracy of reference tissue combinations to diagnose low BMD against uncalibrated Hounsfield units (HUs).

SUMMARY OF BACKGROUND DATA

HUs are used as a measure of BMD; however, associations between HU and T-scores vary widely. Quantitative CT (qCT) scans are more accurate, but they require density calibration with an object of known density (phantom), which limits feasibility. As an emerging technique, phantomless (internal) calibration of routine CT scans may provide a good opportunity for screening.

MATERIALS AND METHODS

Patients who were scheduled to undergo lumbar surgery, with a preoperative CT scan, and a dual-energy x-ray absorptiometry (DXA) scan within six months were included. Four tissues were selected for calibration: subcutaneous adipose (A), erector spinae (ES), psoas (P), and aortic blood (AB). The HUs of these tissues were used in linear regression against ground-truth values. Calibrations were performed by using two different internal tissues at a time to maintain simplicity and in-office applicability.Volumetric bone mineral densities (vBMD) derived from internally calibrated CT scans were analyzed for new threshold values for low bone density. Areas under the curve (AUC) were calculated with 95% CI.

RESULTS

Forty-five patients were included (M/F=10/35, mean age: 63.3). Calibrated vBMDs had stronger correlations with DXA T -scores when compared with HUs, with L2 exhibiting the highest coefficients. Calibration by using A and ES with the threshold of 162 mg/cm 3 had a sensitivity of 90% in detecting low BMD (AUC=0.671).

CONCLUSIONS

This novel method allows simple, in-office calibration of routine preoperative CT scans without the use of a phantom. Calibration using adipose and erector spinae with a threshold of 162 mg/cm 3 is proposed for low bone density screening with high sensitivity (90%).

LEVEL OF EVIDENCE

Level III.

An improved method for measuring the hounsfield units of the vertebral body and pedicles in patients with lumbar degenerative diseases

BACKGROUND

Although measuring vertebral bone density with the use of the computed tomography-based Hounsfield units (HU) is becoming increasingly popular, a much-desired standardized and robust method for measuring HU values accurately, quickly and conveniently was yet to exist.

METHODS

Lumbar CT images of patients with degenerative lumbar diseases were analyzed. The HU values of the vertebral bodies were measured in three planes: mid-axial (including or not including the posterior venous plexus (PVP)), mid-sagittal and mid-frontal; the HU values of the vertebral pedicles were measured in two planes: axial and sagittal. The existing method was improved to measure the HU values of the S1 pedicles. A comparative analysis was performed, the inter- and intra-observer agreements were calculated.

RESULTS

The HU values of the lumbar vertebrae in the mid-axial planes were the highest (p < 0.001), but showed the most reliable, reproducible and stable values of the intra-class correlation coefficient (ICC) (0.80-0.99 for vertebral bodies and 0.80-0.94 for pedicles). Non-inclusion of the PVP in the ROI did not affect HU values (p > 0.05), and the measurement of the HU values on a slice with the PVP showed high reproducibility (the ICC was 0.93-0.94). Measuring the HU values of the S1 pedicles with the use of the improved method led to an increase in ICC from 0.48 to 0.68.

CONCLUSIONS

Measuring HU values in the L3 alone rather than in the entire lumbar spine or other vertebrae works up to expectations and may be recommended. The ROI should be placed in the mid-axial plane on a slice including the PVP. The most challenging HU measurement is for the S1 pedicles, but the proposed improved method makes it easier to do. These considerations may be particularly relevant to spinal surgeons in their routine practice, including planning the lumbar fusion and screw fixation.

Assessment of trabecular bone Hounsfield units in the lumbar spine for osteoporosis evaluation in individuals aged 65 and above: a review

Osteoporosis is a prevalent condition that significantly increases fracture risk, particularly in the elderly population. Despite its widespread occurrence, osteoporosis is often underdiagnosed and inadequately managed. Traditional diagnostic methods, such as dual-energy X-ray absorptiometry (DXA), have limitations in terms of accessibility and accuracy, necessitating exploration of alternative diagnostic approaches.This review aims to evaluate the diagnostic potential of Hounsfield Unit (HU) values derived from abdominal computed tomography (CT) scans, specifically focusing on the trabecular bone of the lumbar spine, for osteoporosis assessment in individuals aged 65 and older. The review seeks to assess the sensitivity, specificity, and overall diagnostic performance of HU values in distinguishing between normal bone density, osteopenia, and osteoporosis, and to identify areas for further investigation to establish standardized diagnostic criteria.This review compiles existing studies on the use of HU values from abdominal CT scans for osteoporosis diagnosis. It examines the relationship between HU values and DXA T-scores, analyzes optimal HU thresholds for classifying bone density categories, and explores the potential of CT scans as a viable alternative to DXA.The findings indicate that HU values from abdominal CT scans show strong correlations with DXA T-scores, suggesting a promising diagnostic tool for assessing bone density and quality. HU values have demonstrated the ability to differentiate between osteopenia, osteoporosis, and normal bone density, with varying sensitivity and specificity depending on the established HU threshold. CT scans are identified as a scalable, cost-effective alternative to DXA, with the added benefit of utilizing routine abdominal CT scans, which are often conducted for other clinical reasons, thereby reducing additional costs and radiation exposure.HU values derived from abdominal CT scans represent a promising approach for osteoporosis screening, offering a potential solution for routine, cost-effective, and accurate diagnosis, especially in older adults. However, there is a need for standardized HU thresholds and further research to refine diagnostic criteria and enhance the accuracy of osteoporosis detection. Establishing standardized guidelines would improve diagnostic consistency and facilitate early intervention, potentially improving patient outcomes and reducing healthcare burdens.

Assessing bone quality in hounsfield units using computed tomography: what value should be used to classify bone as normal or osteoporotic?

PURPOSE

The purpose of this study was to investigate threshold values for classifying bone as normal or osteoporotic based on Computed Tomography (CT) Hounsfield Units (HU) and to determine if clinically applicable values could be derived to aid spine surgeons evaluating bone quality using CT.

METHODS

This literature review was completed using PubMed and Ovid (MedLine), using syntax specific to bone quality and CT. The included articles were original clinical studies assessing bone quality and utilized composite L1-L4 HU values compared against dual-energy X-ray absorptiometry (DEXA) values. Extracted data study descriptors, CT measurement technique, and CT threshold values. CTs were measured from L1-L4 using either axial or sagittal images, and must classify their bone quality findings for any of the following 3 categories: normal, osteopenia, or osteoporosis.

RESULTS

This review located 34 studies measuring bone density using CT with threshold values, of which, 10 were included in the final review. Number of patients ranged from 74 to 283 and cohort ages from 20s to 70.6 years. CT threshold values for assessing normal and osteoporotic bone quality ranged from 150 to 179 and 87 to 155, respectively. From combining values across studies, a HU value of ≥ 170 HU was associated with normal bone and ≤ 115 HU with osteoporosis.

CONCLUSION

There is variation in HU values used to differentiate normal from compromised bone quality, even after limiting studies. For patients with HU values between or near 170 or 115 HU, a DEXA scan may be warranted for further evaluation. With ongoing investigation in this area, threshold values for classifying bone quality using CT will be continually refined.

Opportunistic screening of osteoporosis by CT scan compared to DXA: A systematic review and meta-analysis

The efficacy of opportunistic osteoporosis screening with computed tomography (CT) scans obtained for other indications has not yet been implemented by the current guidelines. We aimed to compile available evidence on the efficacy of osteoporosis screening with CT scans obtained for other indications compared with dual X-ray absorptiometry (DXA). Studies comparing the diagnostic performance of the CT scan with the DXA published before 2023 were retrieved. We conducted a bias assessment using the Newcastle-Ottawa Scale for cross-sectional studies. Correlation coefficients (CC), area under the curve (AUC), sensitivity, and specificity of the CT scans compared with the DXA were meta-analyzed with random effects modeling. 41 studies fulfilled the inclusion/exclusion criteria. The included studies reported weak to very strong CC (0.35 to 0.95) and low to high accuracy for opportunistic osteoporosis screening with CT scans. The meta-analysis showed a moderate pooled CC of 0.59 (95 % CI: 0.53-0.64, P-value<0.001), and a relatively high AUC of 0.81 (95 % CI: 0.78-0.84, P-value<0.001). Subgroup analysis based on age and menopausal status did not show significant between-group differences. Significantly higher accuracy measures were estimated for CT scans of the proximal femur compared to other anatomic regions (CC: 0.70, 95 % CI: 0.57-0.82; AUC: 0.79, 95 % CI: 0.72-0.87), North American cases (CC: 0.66, 95 % CI: 0.52-0.80; AUC: 0.82, 95 % CI: 0.82-0.83), and populations with a higher percentage of women (CC: 0.60, 95 % CI: 0.52-0.69; AUC: 0.86, 95 % CI: 0.83-0.89). We observed a moderate performance of opportunistic osteoporosis screening with CT scans obtained for other indications.

Opportunistic Screening for Low Bone Mineral Density in Routine Computed Tomography Scans: A Brazilian Validation Study

INTRODUCTION/BACKGROUND

Osteoporotic fractures are a major health concern worldwide due to high mortality rates, deterioration in quality of life, and elevated healthcare costs related to hospital treatment. However, most patients who sustain an osteoporotic fracture have never been formally screened for osteoporosis. Opportunistic screening of osteoporosis through conventional computed tomography (CT) scans performed for unrelated reasons could help identify patients with low bone mass. There are currently no studies validating the opportunistic screening of low bone mass through CT in South America. The aim of our study is to assess whether conventional CT scans could be used for the opportunistic screening of osteopenia and osteoporosis in Brazilian patients.

METHODOLOGY

Patients who underwent unenhanced CT and dual-energy X-ray absorptiometry (DXA) scans within a six-month interval were assessed retrospectively. Mean CT attenuation was measured in the first lumbar vertebra (L1) in axial, coronal, and sagittal planes and compared to their respective DXA T-scores; vertebral fractures were assessed in the sagittal plane. Potential thresholds suggestive of low bone mass density (BMD) were established using receiver operating characteristics analysis.

RESULTS

491 patients were included (93.2 % female; mean age of 64.1 ± 9.8 years; mean interval of 63.5 days between scans). Mean L1 CT attenuation was significantly lower in osteopenic and osteoporotic patients in all CT planes (p < 0.001). Positive linear correlations were found between DXA T-scores and the average L1 attenuations in all CT planes (p < 0.001). An average L1 attenuation equal or below 100 Hounsfield Units (HU) in the sagittal plane identified low BMD (osteopenia or osteoporosis) with a specificity of 96.3 % and a positive predictive value of 96 %. In contrast, an average L1 attenuation above 180 HU demonstrated a sensitivity of 97.6 % and a negative predictive value of 94.9 % for detecting osteoporosis. Patients with L1 sagittal attenuation at or below 100 HU exhibited a significantly higher prevalence of vertebral fractures (prevalence ratio: 8.67; p < 0.001). An online calculator based on the results of this study is freely available at www.osteotc.com.br.

CONCLUSIONS

Routine CT scans can identify probable low bone density (osteopenia or osteoporosis) in Brazilian patients without additional costs or radiation exposure. Opportunistic CT screening does not substitute formal bone mineral density assessment; instead, it assists in identifying patients who may benefit from it.

Clinical application and prognostic value of computed tomography examination in foals diagnosed with osteomyelitis: Forty-four cases

Computed tomography (CT) is increasingly recognized as superior to conventional imaging methods for diagnosing osteomyelitis in foals. However, comprehensive studies in this area are limited. This study aims to report on clinical cases of osteomyelitis in foals, establishing a relationship between CT findings and survival outcomes. Additionally, it compares CT imaging with conventional methods such as radiography and ultrasound. We hypothesized that CT variables would more accurately predict survival than other clinical factors and provide more detailed information about osteomyelitis lesions. This retrospective study included foals presenting at a single equine referral hospital between July 2019 and December 2022. Inclusion criteria were: (1) foals less than 9 months of age, (2) presumptive clinical diagnosis of osteomyelitis, and (3) CT examination for further evaluation. Forty-four foals met the criteria; 29 (66%) survived to discharge, and 23 (55%) had long-term survival. Key variables associated with survival included joint collapse (P = .011, OR, 0.054, 95% CI, 0.006-0.506) and lesions in multiple locations (P = .015, OR, 0.19, 95% CI, 0.05-0.7). In 93% of cases, CT examination modified the diagnosis, revealing improved lesion localization (72%), lesion size (76%), or detecting additional lesions (45%). Common lesions involved the axial and proximal appendicular skeletons, with 8 foals (18%) having only axial skeleton involvement and 5 (11%) presenting with both axial and appendicular lesions. Coxofemoral joint involvement was diagnosed in 12 foals (27%), while pelvic lesions were found in 8 (18%). These findings underscore the critical role of CT in identifying and localizing complex lesions, ultimately improving prognostic assessments.

PET/CT for the Opportunistic Screening of Osteoporosis and Fractures in Cancer Patients

PURPOSE OF REVIEW

In this review, we outline the different etiologies of osteoporosis in the oncologic setting and describe the basis for using PET/CT as screening tool for osteoporosis with a focus on the radiotracers [18F]FDG and [18F]NaF.

RECENT FINDINGS

Osteoporosis is a condition commonly affecting cancer patients due to their age, cancer-specific treatment agents, and effects of cancer. In terms of the unifying mechanism, decreased ratio of osteoblast-bone formation to osteoclast-bone resorption is responsible for causing osteoporosis. PET/CT, a crucial metabolic imaging modality in the oncologic imaging, could be a useful tool for the opportunistic screening of osteoporosis. There are two approaches with which osteoporosis could be identified with PET/CT-using either the (1) CT- based or (2) PET- based approaches. While the CT-based approach has been used with [18F]FDG PET/CT, both CT- and PET-based approaches can be employed with [18F]NaF-PET/CT as [18F]NaF is a radiotracer specific for osteoblast activity.

Diagnostic Value of Hounsfield Units for Osteoporotic Thoracolumbar Vertebral Non-Compression Fractures in Elderly Patients with Low-Energy Injuries

Background

Thoracolumbar vertebral fractures are common pathological fractures caused by osteoporosis in the elderly. These fractures are challenging to detect. This study aimed to evaluate the diagnostic value of Hounsfield units for osteoporotic thoracolumbar vertebral non-compression fractures in elderly patients with low-energy fractures.

Methods

The retrospective case-control study included elderly patients diagnosed with osteoporotic thoracolumbar vertebral fractures and non-fractured patients who underwent computed tomography examinations for lumbar vertebra issues during July 2017 and June 2020.

Results

This study included 216 patients with fractures (38 males and 178 females; average age: 77.28±8.68 years) and 124 patients without fractures (21 males and 103 females; average age: 75.35±9.57 years). The difference in Hounsfield units of the target (intermediate) vertebral body significantly differed between the two groups (54.74 ± 21.84 vs 5.86 ± 5.14; p<0.001). The ratios of Hounsfield units were also significantly different between the two groups (1.38 ± 1.60 vs 0.13 ± 0.23; p<0.001). The cut-off value for the difference in Hounsfield units to detect osteoporotic spine fractures was 25.35, with high sensitivity (98.5%), specificity (99.9%), and the area under the curve (AUC) (0.999, 95% CI: 0.999-1). The cut-off value for the odds ratio of Hounsfield units was 0.260, with high sensitivity (99.1%), specificity (92.7%), and AUC (0.970, 95% CI: 0.949-0.992).

Conclusion

The difference between Hounsfield units and the odds ratio of Hounsfield units might help diagnose osteoporotic thoracolumbar vertebral non-compression fractures in elderly patients with low-energy fractures.

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.

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.

Preoperative abnormal bone mineral density as a prognostic indicator in patients undergoing gastrectomy for gastric cancer: A cohort study

Predicting postgastrectomy relapse and mortality in patients with gastric cancer (GC) remains challenging, with limitations to traditional staging systems such as the tumor-node-metastasis (TNM) system. This study aimed to investigate the impact of preoperative Hounsfield unit (HU) values, which serve as a surrogate marker for bone mineral density (BMD), in predicting survival outcomes in patients with GC. A retrospective analysis was conducted on data from patients with GC who underwent curative-intent gastrectomy. Opportunistic abdominopelvic computed tomography images were used to assess HU values at the 3rd lumbar vertebra (L3). These values were then categorized using a cutoff value of 110 HU, which has been established in previous studies as a determinant for abnormal versus normal BMD. Cox regression analysis established predictor models for overall survival (OS). Among 501 initial patients, 478 met the inclusion criteria. Multivariate analyses revealed HU values (hazard ratio, 1.51), along with other factors (the 5-factor modified frailty index, type of gastrectomy, TNM stage, anemia, and serum albumin level), as significant predictors of OS. The full model (FM) incorporating these variables demonstrated superior discrimination ability compared to the baseline model (BM), which is based solely on the TNM stage (concordance index: 0.807 vs 0.709; P < .001). Furthermore, the FM outperformed the BM in predicting OS risks at 36- and 60-months post-surgery. In conclusion, among patients undergoing gastrectomy for GC, those with HU values ≤ 110 (indicating abnormal BMD) at the L3 level, as determined through opportunistic CT scans, exhibited a poorer prognosis than those with HU values > 110 (indicating normal BMD). Integrating HU with other clinicopathological parameters enhances predictive accuracy, facilitating individualized risk stratification and treatment decision-making, which could potentially lead to improved survival outcomes.

Detecting whether L1 or other lumbar levels would be excluded from DXA bone mineral density analysis during opportunistic CT screening for osteoporosis using machine learning

PURPOSE

One or more vertebrae are sometimes excluded from dual-energy X-ray absorptiometry (DXA) analysis if the bone mineral density (BMD) T-score estimates are not consistent with the other lumbar vertebrae BMD T-score estimates. The goal of this study was to build a machine learning framework to identify which vertebrae would be excluded from DXA analysis based on the computed tomography (CT) attenuation of the vertebrae.

METHODS

Retrospective review of 995 patients (69.0% female) aged 50 years or greater with CT scans of the abdomen/pelvis and DXA within 1 year of each other. Volumetric semi-automated segmentation of each vertebral body was performed using 3D-Slicer to obtain the CT attenuation of each vertebra. Radiomic features based on the CT attenuation of the lumbar vertebrae were created. The data were randomly split into training/validation (90%) and test datasets (10%). We used two multivariate machine learning models: a support vector machine (SVM) and a neural net (NN) to predict which vertebra(e) were excluded from DXA analysis.

RESULTS

L1, L2, L3, and L4 were excluded from DXA in 8.7% (87/995), 9.9% (99/995), 32.3% (321/995), and 42.6% (424/995) patients, respectively. The SVM had a higher area under the curve (AUC = 0.803) than the NN (AUC = 0.589) for predicting whether L1 would be excluded from DXA analysis (P = 0.015) in the test dataset. The SVM was better than the NN for predicting whether L2 (AUC = 0.757 compared to AUC = 0.478), L3 (AUC = 0.699 compared to AUC = 0.555), or L4 (AUC = 0.751 compared to AUC = 0.639) were excluded from DXA analysis.

CONCLUSIONS

Machine learning algorithms could be used to identify which lumbar vertebrae would be excluded from DXA analysis and should not be used for opportunistic CT screening analysis. The SVM was better than the NN for identifying which lumbar vertebra should not be used for opportunistic CT screening analysis.

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.

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.

Prognostic impact of osteosarcopenia in patients with advanced pancreatic cancer receiving gemcitabine plus nab-paclitaxel

BACKGROUND

Osteosarcopenia, defined as the combination of osteoporosis and sarcopenia, has recently gained attention as a novel prognostic factor for survival in patients with cancer. This study aimed to evaluate the prognostic impact of osteosarcopenia in metastatic pancreatic cancer (PC).

METHODS

We retrospectively investigated consecutive metastatic PC patients receiving first-line gemcitabine plus nab-paclitaxel (GnP). Skeletal muscle index at the third lumbar vertebra and bone mineral density at the first lumbar vertebra were measured using pretreatment computed tomography. Treatment outcomes of osteosarcopenia and non-osteosarcopenia groups were compared and analyzed. Multivariate analysis was performed to identify variables associated with survival.

RESULTS

Among 313 patients, osteosarcopenia was present in 59 patients (19%). The osteosarcopenia group was associated with older age, higher proportion of females, worse performance status, and higher modified Glasgow prognostic scores (mGPS). Response rates to chemotherapy, progression-free survival (3.5 months vs. 6.4 months, p < 0.001), and overall survival (5.6 months vs. 13.0 months, p < 0.001) were significantly better in the non-osteosarcopenia group. Osteosarcopenia, performance status of 1-2, mGPS score of 1-2, carcinoembryonic antigen ≥10 ng/mL, and carbohydrate antigen 19-9 ≥ 1000 IU/mL were identified as independent factors predicting shorter survival. Grade 3 or higher anemia and febrile neutropenia occurred more frequently in the osteosarcopenia group.

CONCLUSIONS

Osteosarcopenia was associated with poor survival in metastatic PC treated with first-line GnP. Screening for osteosarcopenia may be helpful for better management of metastatic PC.

Opportunistic Screening Techniques for Analysis of CT Scans

PURPOSE OF REVIEW

Opportunistic screening is a combination of techniques to identify subjects of high risk for osteoporotic fracture using routine clinical CT scans prescribed for diagnoses unrelated to osteoporosis. The two main components are automated detection of vertebral fractures and measurement of bone mineral density (BMD) in CT scans, in which a phantom for calibration of CT to BMD values is not used. This review describes the particular challenges of opportunistic screening and provides an overview and comparison of current techniques used for opportunistic screening. The review further outlines the performance of opportunistic screening.

RECENT FINDINGS

A wide range of technologies for the automatic detection of vertebral fractures have been developed and successfully validated. Most of them are based on artificial intelligence algorithms. The automated differentiation of osteoporotic from traumatic fractures and vertebral deformities unrelated to osteoporosis, the grading of vertebral fracture severity, and the detection of mild vertebral fractures is still problematic. The accuracy of automated fracture detection compared to classical radiological semi-quantitative Genant scoring is about 80%. Accuracy errors of alternative BMD calibration methods compared to simultaneous phantom-based calibration used in standard quantitative CT (QCT) range from below 5% to about 10%. The impact of contrast agents, frequently administered in clinical CT on the determination of BMD and on fracture risk determination is still controversial. Opportunistic screening, the identification of vertebral fracture and the measurement of BMD using clinical routine CT scans, is feasible but corresponding techniques still need to be integrated into the clinical workflow and further validated with respect to the prediction of fracture risk.

Identification of Bone Mineral Density Deficit Using L1 Trabecular Attenuation by Opportunistic Multidetector CT Scan in Adult Patients

BACKGROUND

Multidetector computer tomography (CT) has been used to diagnose pathologies such as osteoporosis via opportunistic screening, where the assessment of the bone structure and the measurement of bone mineral density (BMD) are of great relevance.

PURPOSE

To construct reference BMD values based on the measurement of the attenuation of the L1 vertebral body by multidetector CT scan (in the soft tissue and bone windows) in adult patients and to establish normative ranges by sex and age of BMD values.

MATERIALS AND METHODS

A retrospective cross-sectional study of 5080 patients who underwent multidetector CT scan between January and December 2021. Adult patients (≥18 years) with non-contrast multidetector CT scan of the abdomen or thorax-abdomen at a voltage 120 kV. The attenuation of the L1 vertebral body in Hounsfield units (HU) in both windows were compared using the Mann-Whitney U-test with α = 0.05. Additionally, the quartiles of the BMD were constructed (in both windows) grouped by sex and age.

RESULTS

Only 454 (51.30 ± 15.89 years, 243 women) patients met the inclusion criteria. There is no difference in BMD values between windows (soft tissue: 163.90 ± 57.13, bone: 161.86 ± 55.80, p = 0.625), mean L1 attenuation decreased linearly with age at a rate of 2 HU per year, and the presence of BMD deficit among patients was high; 152 of 454 (33.48%) patients presented BMD values suggestive of osteoporosis, and of these, approximately half 70 of 454 (15.42%) corresponded to patients with BMD values suggestive of a high risk of osteoporotic fracture.

CONCLUSIONS

From clinical practice, the bone mineral density (BMD) of a patient in either window below the first quartile for age- and sex-matched peers suggests a deficit in BMD that cannot be ignored and requires clinical management that enables identification of the etiology, its evolution, and the consequences of this alteration.

Prediction of osteoporosis and osteopenia by routine computed tomography of the lumbar spine in different regions of interest

Background

We aimed to investigate the utility of Hounsfield units (HU) obtained from different regions of interest in opportunistic lumbar computed tomography (CT) to predict osteoporosis coupling with data of dual-energy X-ray absorptiometry (DXA).

Methods

A total of 100 patients who attended a university hospital in Shanghai, China, and had undergone CT and DXA tests of the lumbar spine within 3 months were included in this retrospective review. Images were reviewed on axial sections, and regions of interest (ROI) markers were placed on the round, oval, anterior, left, and right of the L1–L4 vertebra to measure the HU. The mean values of CT HU were then compared to the bone mineral density (BMD) measured by DXA. Receiver operator characteristic curves were generated to determine the threshold for diagnosis and its sensitivity and specificity values.

Results

The differences in CT HU of different ROI based on DXA definitions of osteoporosis, osteopenia, and normal individuals were statistically significant (p < 0.01). The HU values of the different ROI correlated well with the BMD values (Spearman coefficient all > 0.75, p < 0.01). The threshold for diagnosing osteoporosis varies from 87 to 111 HU in different ROIs, and the threshold for excluding osteoporosis or osteopenia is 99–125 HU.

Conclusion

This is the first study on osteoporosis diagnosis of different ROI with routine CT lumbar scans. There is a strong correlation between CT HU of different ROI in the lumbar spine and BMD, and HU measurements can be used to predict osteoporosis.

Support vector machines are superior to principal components analysis for selecting the optimal bones’ CT attenuations for opportunistic screening for osteoporosis using CT scans of the foot or ankle

Objectives

To use the computed tomography (CT) attenuation of the foot and ankle bones for opportunistic screening for osteoporosis.

Methods

Retrospective study of 163 consecutive patients from a tertiary care academic center who underwent CT scans of the foot or ankle and dual-energy X-ray absorptiometry (DXA) within 1 year of each other. Volumetric segmentation of each bone of the foot and ankle was done in 3D Slicer to obtain the mean CT attenuation. Pearson's correlations were used to correlate the 10.13039/100004811CT attenuations with each other and with DXA measurements. Support vector machines (SVM) with various kernels and principal components analysis (PCA) were used to predict osteoporosis and osteopenia/osteoporosis in training/validation and test datasets.

Results

CT attenuation measurements at the talus, calcaneus, navicular, cuboid, and cuneiforms were correlated with each other and positively correlated with BMD T-scores at the L1-4 lumbar spine, hip, and femoral neck; however, there was no significant correlation with the L1-4 trabecular bone scores. A CT attenuation threshold of 143.2 Hounsfield units (HU) of the calcaneus was best for detection of osteoporosis in the training/validation dataset. SVMs with radial basis function (RBF) kernels were significantly better than the PCA model and the calcaneus for predicting osteoporosis in the test dataset.

Conclusions

Opportunistic screening for osteoporosis is possible using the CT attenuation of the foot and ankle bones. SVMs with RBF using all bones is more accurate than the CT attenuation of the calcaneus.

Improved CT-based Osteoporosis Assessment with a Fully Automated Deep Learning Tool

Purpose

To develop, test, and validate a deep learning (DL) tool that improves upon a previous feature-based CT image processing bone mineral density (BMD) algorithm and compare it against the manual reference standard.

Materials and Methods

This single-center, retrospective, Health Insurance Portability and Accountability Act-compliant study included manual L1 trabecular Hounsfield unit measurements from abdominal CT scans in 11 035 patients (mean age, 58 years ± 12 [SD]; 6311 women) as the reference standard. Automated level selection and L1 trabecular region of interest (ROI) placement were then performed in this CT cohort with both a previously validated feature-based image processing tool and a new DL tool. Overall technical success rates and agreement with the manual reference standard were assessed.

Results

The overall success rate of the DL tool in this heterogeneous patient cohort was significantly higher than that of the older image processing BMD algorithm (99.3% vs 89.4%, P < .001). Using this DL tool, the closest median Hounsfield unit values for single-, three-, and seven-slice vertebral ROIs were within 5% of the manual reference standard Hounsfield unit values in 35.1%, 56.9%, and 85.8% of scans; within 10% in 56.6%, 75.6%, and 92.9% of scans; and within 25% in 76.5%, 89.3%, and 97.1% of scans, respectively. Trade-offs in sensitivity and specificity for osteoporosis assessment were observed from the single-slice approach (sensitivity, 39.4%; specificity, 98.3%) to the minimum value of the multislice approach (for seven contiguous slices; sensitivity, 71.3% and specificity, 94.6%).

Conclusion

The new DL BMD tool demonstrated a higher success rate than the older feature-based image processing tool, and its outputs can be targeted for higher specificity or sensitivity for osteoporosis assessment.Keywords: CT, CT-Quantitative, Abdomen/GI, Skeletal-Axial, Spine, Deep Learning, Machine Learning Supplemental material is available for this article. © RSNA, 2022.

Imaging of Metabolic Bone Diseases: The Spine View, Part II

Metabolic bone diseases comprise a wide spectrum. Osteoporosis, the most frequent, characteristically involves the spine, with a high impact on health care systems and on the morbidity of patients due to the occurrence of vertebral fractures (VFs).Part II of this review completes an overview of state-of-the-art techniques on the imaging of metabolic bone diseases of the spine, focusing on specific populations and future perspectives. We address the relevance of diagnosis and current status on VF assessment and quantification. We also analyze the diagnostic techniques in the pediatric population and then review the assessment of body composition around the spine and its potential application. We conclude with a discussion of the future of osteoporosis screening, through opportunistic diagnosis and the application of artificial intelligence.

The value of radiomics to predict abnormal bone mass in type 2 diabetes mellitus patients based on CT imaging for paravertebral muscles

OBJECTIVE

To investigate the value of CT imaging features of paravertebral muscles in predicting abnormal bone mass in patients with type 2 diabetes mellitus.

METHODS

The clinical and QCT data of 149 patients with type 2 diabetes mellitus were collected retrospectively. Patients were randomly divided into the training group (n = 90) and the validation group (n = 49). The radiologic model and Nomogram model were established by multivariate Logistic regression analysis. Predictive performance was evaluated using receiver operating characteristic (ROC) curves.

RESULTS

A total of 829 features were extracted from CT images of paravertebral muscles, and 12 optimal predictive features were obtained by the mRMR and Lasso feature selection methods. The radiomics model can better predict bone abnormality in type 2 diabetes mellitus, and the (Area Under Curve) AUC values of the training group and the validation group were 0.94(95% CI, 0.90-0.99) and 0.90(95% CI, 0.82-0.98). The combined Nomogram model, based on radiomics and clinical characteristics (vertebral CT values), showed better predictive efficacy with an AUC values of 0.97(95% CI, 0.94-1.00) in the training group and 0.95(95% CI, 0.90-1.00) in the validation group, compared with the clinical model.

CONCLUSION

The combination of Nomogram model and radiomics-clinical features of paravertebral muscles has a good predictive value for abnormal bone mass in patients with type 2 diabetes mellitus.

Radiomics analysis based on lumbar spine CT to detect osteoporosis

OBJECTIVES

Undiagnosed osteoporosis may lead to severe complications after spinal surgery. This study aimed to construct and validate a radiomic signature based on CT scans to screen for lumbar spine osteoporosis.

METHODS

Using a stratified random sample method, 386 vertebral bodies were randomly divided into a training set (n = 270) and a test set (n = 116). A total of 1040 radiomics features were automatically retracted from lumbar spine CT scans using the 3D slicer pyradiomics module, and a radiomic signature was created. The sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) of the Hounsfield and radiomics signature models were calculated. The AUCs of the two models were compared using the DeLong test. Their clinical usefulness was assessed using a decision curve analysis.

RESULTS

Twelve features were chosen to establish the radiomic signature. The AUCs of the radiomics signature and Hounsfield models were 0.96 and 0.88 in the training set and 0.92 and 0.84 in the test set, respectively. According to the DeLong test, the AUCs of the two models were significantly different (p < 0.05). The radiomics signature model indicated a higher overall net benefit than the Hounsfield model, as determined by decision curve analysis.

CONCLUSIONS

The CT-based radiomic signature can differentiate patients with/without osteoporosis prior to lumbar spinal surgery. Without additional medical cost and radiation exposure, the radiomics method may provide valuable information facilitating surgical decision-making.

KEY POINTS

• The goal of the study was to evaluate the efficacy of a radiomics signature model based on routine preoperative lumbar spine CT scans in screening osteoporosis. • The radiomics signature model demonstrated excellent prediction performance in both the training and test sets. • This radiomics method may provide valuable information and facilitate surgical decision-making without additional medical costs and radiation exposure.

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.