Opportunistic Osteoporosis Screening at Routine Abdominal and Thoracic CT: Normative L1 Trabecular Attenuation Values in More than 20 000 Adults

Artificial Intelligence Applications for Osteoporosis Classification Using Computed Tomography

Osteoporosis, marked by low bone mineral density (BMD) and a high fracture risk, is a major health issue. Recent progress in medical imaging, especially CT scans, offers new ways of diagnosing and assessing osteoporosis. This review examines the use of AI analysis of CT scans to stratify BMD and diagnose osteoporosis. By summarizing the relevant studies, we aimed to assess the effectiveness, constraints, and potential impact of AI-based osteoporosis classification (severity) via CT. A systematic search of electronic databases (PubMed, MEDLINE, Web of Science, ClinicalTrials.gov) was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 39 articles were retrieved from the databases, and the key findings were compiled and summarized, including the regions analyzed, the type of CT imaging, and their efficacy in predicting BMD compared with conventional DXA studies. Important considerations and limitations are also discussed. The overall reported accuracy, sensitivity, and specificity of AI in classifying osteoporosis using CT images ranged from 61.8% to 99.4%, 41.0% to 100.0%, and 31.0% to 100.0% respectively, with areas under the curve (AUCs) ranging from 0.582 to 0.994. While additional research is necessary to validate the clinical efficacy and reproducibility of these AI tools before incorporating them into routine clinical practice, these studies demonstrate the promising potential of using CT to opportunistically predict and classify osteoporosis without the need for DEXA.

Chest CT opportunistic biomarkers for phenotyping high-risk COVID-19 patients: a retrospective multicentre study

OBJECTIVE

To assess the value of opportunistic biomarkers derived from chest CT performed at hospital admission of COVID-19 patients for the phenotypization of high-risk patients.

METHODS

In this multicentre retrospective study, 1845 consecutive COVID-19 patients with chest CT performed within 72 h from hospital admission were analysed. Clinical and outcome data were collected by each center 30 and 80 days after hospital admission. Patients with unknown outcomes were excluded. Chest CT was analysed in a single core lab and behind pneumonia CT scores were extracted opportunistic data about atherosclerotic profile (calcium score according to Agatston method), liver steatosis (≤ 40 HU), myosteatosis (paraspinal muscle F < 31.3 HU, M < 37.5 HU), and osteoporosis (D12 bone attenuation < 134 HU). Differences according to treatment and outcome were assessed with ANOVA. Prediction models were obtained using multivariate binary logistic regression and their AUCs were compared with the DeLong test.

RESULTS

The final cohort included 1669 patients (age 67.5 [58.5-77.4] yo) mainly men 1105/1669, 66.2%) and with reduced oxygen saturation (92% [88-95%]). Pneumonia severity, high Agatston score, myosteatosis, liver steatosis, and osteoporosis derived from CT were more prevalent in patients with more aggressive treatment, access to ICU, and in-hospital death (always p < 0.05). A multivariable model including clinical and CT variables improved the capability to predict non-critical pneumonia compared to a model including only clinical variables (AUC 0.801 vs 0.789; p = 0.0198) to predict patient death (AUC 0.815 vs 0.800; p = 0.001).

CONCLUSION

Opportunistic biomarkers derived from chest CT can improve the characterization of COVID-19 high-risk patients.

CLINICAL RELEVANCE STATEMENT

In COVID-19 patients, opportunistic biomarkers of cardiometabolic risk extracted from chest CT improve patient risk stratification.

KEY POINTS

• In COVID-19 patients, several information about patient comorbidities can be quantitatively extracted from chest CT, resulting associated with the severity of oxygen treatment, access to ICU, and death. • A prediction model based on multiparametric opportunistic biomarkers derived from chest CT resulted superior to a model including only clinical variables in a large cohort of 1669 patients suffering from SARS- CoV2 infection. • Opportunistic biomarkers of cardiometabolic comorbidities derived from chest CT may improve COVID-19 patients' risk stratification also in absence of detailed clinical data and laboratory tests identifying subclinical and previously unknown conditions.

Hounsfield units on abdominal computed tomography: a new tool for predicting osteoporosis

BACKGROUND

Osteoporosis can cause bone fractures and disability, but early diagnosis faces challenges. Our proposed diagnostic indicators offer a new approach for early detection, which benefits early identification.

PURPOSE

To determine the most appropriate threshold for predicting osteoporosis in patients with each section of vertebral body.

MATERIAL AND METHODS

A retrospective analysis of 210 patients, including 646 vertebrae, who had both abdominal computed tomography (CT) and dual-energy X-ray absorptiometry (DXA) within six months. The correlation between DXA T-score and CT Hounsfield units (HU) values was tested by Pearson. The area under the curve (AUC) was calculated using the threshold obtained from the regression equation.

RESULTS

The thresholds matching the T-score of -2.5 were 85, 95, 85, and 90 HU for the upper axial plane of the vertebral body (Lau), the middle axial plane of the vertebral body (Lam), the lower axial plane of the vertebral body (Lad), and the mid-sagittal plane of the vertebral body (Lsm), respectively. Defining osteoporosis using CT as Lau ≤ 85, Lam ≤ 95, Lad ≤ 85, or Lsm ≤ 90 HU had a specificity of 88.1% (116/134) and sensitivity of 90.8% (69/76) for distinguishing DXA osteoporosis of the lumbar spine in 210 patients. T-score ≤-2.5 defined as Lau ≤85 or Lam ≤95 or Lad ≤85 or Lsm ≤90 HU had a specificity of 85.9% (275/320) and sensitivity of 82.8% (270/326) for DXA T-score ≤-2.5 in 646 lumbar vertebrae.

CONCLUSION

CT HU values obtained based on different sections of the vertebral body in abdominal CT can be used as a supplementary measure to assess osteoporosis.

MRI-based radiomics assessment of the imminent new vertebral fracture after vertebral augmentation

BACKGROUND

Imminent new vertebral fracture (NVF) is highly prevalent after vertebral augmentation (VA). An accurate assessment of the imminent risk of NVF could help to develop prompt treatment strategies.

PURPOSE

To develop and validate predictive models that integrated the radiomic features and clinical risk factors based on machine learning algorithms to evaluate the imminent risk of NVF.

MATERIALS AND METHODS

In this retrospective study, a total of 168 patients with painful osteoporotic vertebral compression fractures treated with VA were evaluated. Radiomic features of L1 vertebrae based on lumbar T2-weighted images were obtained. Univariate and LASSO-regression analyses were applied to select the optimal features and construct radiomic signature. The radiomic signature and clinical signature were integrated to develop a predictive model by using machine learning algorithms including LR, RF, SVM, and XGBoost. Receiver operating characteristic curve and calibration curve analyses were used to evaluate the predictive performance of the models.

RESULTS

The radiomic-XGBoost model with the highest AUC of 0.93 of the training cohort and 0.9 of the test cohort among the machine learning algorithms. The combined-XGBoost model with the best performance with an AUC of 0.9 in the training cohort and 0.9 in the test cohort. The radiomic-XGBoost model and combined-XGBoost model achieved better performance to assess the imminent risk of NVF than that of the clinical risk factors alone (p < 0.05).

CONCLUSION

Radiomic and machine learning modeling based on T2W images of preoperative lumbar MRI had an excellent ability to evaluate the imminent risk of NVF after VA.

What is the role of CT-based Hounsfield unit assessment in the evaluation of bone mineral density in patients undergoing 1- or 2-level lumbar spinal fusion for degenerative spinal pathologies? A prospective study

BACKGROUND CONTEXT

Computed tomography-based vertebral attenuation values (CT-based HU) have been shown to correlate with T-scores on DEXA scan; and have been acknowledged as an independent factor for predicting fragility fractures. Most patients undergoing lumbar surgeries require CT as part of their preoperative evaluation.

PURPOSE

The current study was thus planned to evaluate the role of lumbar CT as an opportunistic investigation in determining BMD preoperatively in patients undergoing lumbar fusion.

STUDY DESIGN

Prospective cohort study.

PATIENT SAMPLE

Patients older than 45 years, who underwent one- to two-level lumbar (L3-S1 levels) fusions.

OUTCOME MEASURES

Comparison of the quantitative assessment of osteoporosis using Hounsfield Units (HU) on CT (L1-L5) and mean lumbar T-scores on DEXA (Dual Energy X-ray Absorptiometry).

HYPOTHESIS

HU on CT is comparable to T-score on DEXA as a suitable modality for the assessment of osteoporosis in patients undergoing one- to two-level lumbar fusion.

METHODS

A prospective cohort study was conducted between January and December 2021. Patients older than 45 years, who underwent one- to two-level lumbar (L3-S1 levels) fusions and had complete clinico-radiological records, were prospectively enrolled. A comparison was drawn between the HU (measured by placing an oval region of interest [ROI] over axial, sagittal and coronal images of lumbar vertebrae) on CT and T-scores on DEXA, and analyzed statistically. The HU values correlating best with normal (group A), osteopenia (B) and osteoporosis (C) categories (classified based on T-scores of lumbar spines) were determined statistically.

RESULTS

Overall, 87 patients (mean age of 60.56±11.63 years; 63 [72.4%] female patients) were prospectively studied. There was a statistically significant difference in the mean age (p=.01) and sex distribution (predominantly female patients; p=.03) of patients belonging to groups B (osteopenic) and C (osteoporotic patients), as compared with group A. The greatest correlation between T-score (on DEXA) and HU (on CT) for differentiating osteopenia (group B) from group A was observed at levels L1 (p<.001), L2 (p<.001) and L3 (p<.001). Based on receiver-operating characteristic (ROC) curve analysis, the cut-off values for HU for identifying osteopenia were 159 (at L1; sensitivity 81.6 and specificity 80) and 162 (at L2; sensitivity 80 and specificity 71.1). In addition, there was statistically significant correlation between T-score (on DEXA) and HU at all the lumbar levels for distinguishing osteoporosis (group C), although the difference was most evident at the upper lumbar (L1 and L2) levels (p<.001). Based on ROC analysis, cut-off HU values for defining osteoporosis were 127 (at L1; sensitivity 71.3 and specificity 70) and 117 (at L2; sensitivity 65.5 and specificity 90).

CONCLUSION

Based on our study, the measurement of HU on CT at upper lumbar levels can be considered as "surrogate marker" for BMD in the diagnosis of osteopenia (cut-off: 159 at L1, 162 at L2) and osteoporosis (cut-off: 127 at L1, 117 at L2) in patients undergoing lumbar fusion surgeries. The HU measurements on CT at the lower lumbar levels (L4 and L5) are less reliable in this preoperative scenario.

Prognostic role of computed tomography analysis using deep learning algorithm in patients with chronic hepatitis B viral infection

BACKGROUND/AIMS

The prediction of clinical outcomes in patients with chronic hepatitis B (CHB) is paramount for effective management. This study aimed to evaluate the prognostic value of computed tomography (CT) analysis using deep learning algorithms in patients with CHB.

METHODS

This retrospective study included 2,169 patients with CHB without hepatic decompensation who underwent contrast-enhanced abdominal CT for hepatocellular carcinoma (HCC) surveillance between January 2005 and June 2016. Liver and spleen volumes and body composition measurements including subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and skeletal muscle indices were acquired from CT images using deep learning-based fully automated organ segmentation algorithms. We assessed the significant predictors of HCC, hepatic decompensation, diabetes mellitus (DM), and overall survival (OS) using Cox proportional hazard analyses.

RESULTS

During a median follow-up period of 103.0 months, HCC (n=134, 6.2%), hepatic decompensation (n=103, 4.7%), DM (n=432, 19.9%), and death (n=120, 5.5%) occurred. According to the multivariate analysis, standardized spleen volume significantly predicted HCC development (hazard ratio [HR]=1.01, P=0.025), along with age, sex, albumin and platelet count. Standardized spleen volume (HR=1.01, P<0.001) and VAT index (HR=0.98, P=0.004) were significantly associated with hepatic decompensation along with age and albumin. Furthermore, VAT index (HR=1.01, P=0.001) and standardized spleen volume (HR=1.01, P=0.001) were significant predictors for DM, along with sex, age, and albumin. SAT index (HR=0.99, P=0.004) was significantly associated with OS, along with age, albumin, and MELD.

CONCLUSION

Deep learning-based automatically measured spleen volume, VAT, and SAT indices may provide various prognostic information in patients with CHB.

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.

Patterns of Misdiagnosis and Discordance in Detecting Osteoporosis: A Comparison of Dual-energy X-ray Absorptiometry and Lumbar Computed Tomography Hounsfield Units

STUDY DESIGN

This was a retrospective chart review.

OBJECTIVE

This study aims to identify the prevalence of osteoporosis (OP) by lumbar computed tomography (CT) Hounsfield units (HUs) in patients who have normal or osteopenic bone determined by dual-energy x-ray absorptiometry (DEXA).

SUMMARY OF BACKGROUND DATA

OP is a critical issue in the postmenopausal and aging population. Bone mineral density assessment by DEXA has been described as insensitive for diagnosing OP in the lumbar spine. Improving the detection of OP can bring more patients to treatment and reduce the risks associated with low bone mineral density.

PATIENTS AND METHODS

We retrospectively reviewed all patients with DEXA scans and noncontrast CTs of the lumbar spine over a 15-year period. Patients were diagnosed as non-OP if they had a normal DEXA T -score (≥ -1) or osteopenic DEXA T -score (between -1.1 and -2.4). Patients in this cohort were considered osteoporotic by CT if L1-HU ≤110. Demographics and lumbar HUs were compared between these stratified groups.

RESULTS

A total of 74 patients were included for analysis. All patients were demographically, similar, and the average patient age was 70 years. The prevalence of OP determined by CT L1-HU ≤110 was 46% (normal DEXA: 9%, osteopenic DEXA: 63%). A significant number of males in our study were considered osteoporotic by L1-HU ≤110 (74%, P = 0.03). All individual axial and sagittal lumbar HU measurements including L1-L5 average lumbar HUs were statistically significant among non-OP and OP groups except for the lower lumbar levels ( P > 0.05 for L4 axial HUs, and L4-L5 sagittal HUs).

CONCLUSIONS

The prevalence of OP in patients with normal or osteopenic T -scores is high. Among those with osteopenia by DEXA, more than 50% may lack appropriate medical treatment. The DEXA scan may be particularly insensitive to male bone quality making the CT HU the diagnostic method of choice for detecting OP.

LEVEL OF EVIDENCE

Level III.

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

RATIONALE AND OBJECTIVES

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

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.

Opportunistic Computed Tomography Screening for Osteoporosis and Fracture

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

Prevalence of Osteopathy in Chronic Pancreatitis: A Systematic Review and Meta-Analysis

INTRODUCTION

Individuals with chronic pancreatitis (CP) are at increased risk for nutritional complications during their clinical course. We appraised the literature to provide updated estimates of the prevalence and predictors of osteoporosis, osteopenia, and osteopathy in CP using a systematic review and meta-analysis.

METHODS

Search strategies were developed for major databases from inception through October 2021. Outcomes of interest included rates of osteopenia and osteoporosis based on dual-energy X-ray absorptiometry scans and risk factors. A random-effects model was used for analysis, and results were expressed as pooled cumulative rates along with 95% confidence interval (CI).

RESULTS

From an initial total of 1,704 identified articles, we ultimately selected 17 studies that involved 1,659 subjects (n = 1,067 men) with CP. The pooled rate of osteopathy was 58% (95% CI: 49%-67%; P < 0.001; I 2 = 91.8%). The pooled rate of osteoporosis was 18% (95% CI: 12%-23%; P < 0.001; I 2 = 86.3%), and the pooled rate of osteopenia was 39% (95% CI: 31%-48%; P < 0.001; I 2 = 91.53%). In the systematic review, factors associated with decreased bone mineral density included smoking, alcohol consumption, older age, female sex, low body mass index, decreased vitamins D and K, and fecal elastase levels.

DISCUSSION

Patients with CP have high rates of osteopathy when assessed with dual-energy X-ray absorptiometry imaging. Additional studies with longitudinal follow-up are needed to understand the observed heterogeneity, the cumulative burden of disease, and rate of bone loss in CP.

Recommendations for the Management of Incidental Musculoskeletal Findings on MRI and CT

The Canadian Association of Radiologists (CAR) Incidental Findings Working Group consists of both academic subspeciality and general radiologists tasked with either adapting American College of Radiology (ACR) guidelines to meet the needs of Canadian radiologists or authoring new guidelines where appropriate. In this case, entirely new guidelines to deal with incidental musculoskeletal findings that may be encountered on thoracoabdominal computed tomography or magnetic resonance imaging were drafted, focussing on which findings should prompt recommendations for further workup. These recommendations discuss how to deal with incidental marrow changes, focal bone lesions, abnormalities of the pubic symphysis and sacroiliac joints, fatty soft tissue masses, manifestations of renal osteodystrophy and finally discuss opportunistic osteoporosis evaluation.

Computed Tomography Bone Imaging: Pushing the Boundaries in Clinical Practice

Bone microarchitecture has several clinical implications over and above estimating bone strength. Computed tomography (CT) analysis mainly uses high-resolution peripheral quantitative CT and micro-CT, research imaging techniques, most often limited to peripheral skeleton assessment. Ultra-high-resolution (UHR) CT and photon-counting detector CT, two commercially available techniques, provide images that can approach the spatial resolution of the trabeculae, bringing bone microarchitecture analysis into clinical practice and improving depiction of bone vascularization, tumor matrix, and cortical and periosteal bone. This review presents bone microarchitecture anatomy, principles of analysis, reference measurements, and an update on the performance and potential clinical applications of these new CT techniques. We also share our clinical experience and technical considerations using an UHR-CT device.

Can the greater trochanter/femoral neck signal intensity ratio on coronal T1 weighted images of the hip differentiate normal-abnormal bone mineral density?

A simple index calculated by dividing the greater trochanter signal intensity by that of the femoral neck on coronal T1-weighted magnetic resonance images of the hip may be useful as an opportunistic screening tool to differentiate normal vs. abnormal bone mineral density.

PURPOSE

The aim of this study is to evaluate the efficacy of the greater trochanter/femoral neck (T/N) signal intensity (SI) ratio on T1 weighted images of the hip in differentiating patients with normal vs. abnormal bone mineral density (BMD) using hip dual-energy x-ray absorptiometry (DXA) as the reference.

METHODS

Three BMD groups according to the T score of the femoral neck (i.e., normal, osteopenia, and osteoporosis) were created, and 20 patients were included for each group. The T/N ratio was calculated by dividing the greater trochanter SI by that of the femoral neck on coronal T1-weighted images. Receiver-operator characteristic (ROC) analysis was performed to determine diagnostic efficacy.

RESULTS

The mean age was 59.2±9.4; there were 57 women and 3 men. The mean BMD was 0.67±0.14 g/cm2. The mean T/N ratio for the normal, osteopenia, and osteoporosis groups were 1.37 (±0.12), 1.19 (±0.10), and 1.18 (±0.13), respectively. When the osteopenia and osteoporosis groups were combined into one group, i.e., low BMD group, the mean T/N ratio was 1.18 (±0.11), and it was significantly different from that of the normal BMD group (p<0.00001). In ROC analysis, the area under curve (AUC) for the T/N ratio in the diagnosis of low BMD was 0.870. An optimal cutoff value of 1.28 was found for the differentiation of normal vs. abnormal BMD with 80% sensitivity and 80% specificity.

CONCLUSIONS

The T/N ratio seems to be effective at differentiating patients with normal vs. abnormal BMD and may help triage patients for additional evaluation.

Prognostic Value of Vertebral Bone Density in the CT Scans of Sepsis Patients Admitted to the Intensive Care Unit

AIM

To evaluate the prognostic value of vertebral bone mineral density (BMD) and its relationship with mortality using the computed tomography (CT) scans of sepsis patients admitted to the intensive care unit.

METHODS

In this retrospective study, patients diagnosed with sepsis at the intensive care unit between January and December 2022 were evaluated. Bone density was manually measured from the vertebral body using axial CT images. The relationship of clinical variables and patient outcomes with vertebral BMD, mortality, and mechanical ventilation was investigated. A lower BMD (osteoporosis) was defined as ≤100 HU.

RESULTS

The study included 213 patients (95 females, 44.6%). The mean age of all patients was 60.1±18.7 years. At least one comorbidity was present in 64.7% (n=138) of the patients, and the most common comorbidity was hypertension (n=73, 34.2%). The mortality rate was 21.1% (n=45), and the mechanical ventilation rate was 17.4% (n=37), both being statistically significantly higher among the patients with a lower BMD (36.4 vs. 12.9%; p<0.001 and 29.7 vs. 10.8%; p=0.001, respectively). The rate of a lower BMD was significantly higher in the mortality group (59.5 vs. 29.5%; p=0.001). In the regression analysis, a lower BMD [odds ratio (OR), 2.785; 95% confidence interval (CI): 1.231-6.346, p=0.014] was a significant independent predictor of mortality. Interobserver agreement for BMD measurement was excellent, with an intraclass correlation coefficient of 0.919 (95% CI: 0.904-0.951).

CONCLUSION

Vertebral BMD is a strong independent predictor of mortality and can be easily and reproducible evaluated on the thoracoabdominal CT images of patients admitted to the intensive care unit with a diagnosis of sepsis.

Opportunistic Screening: Radiology Scientific Expert Panel

Radiologic tests often contain rich imaging data not relevant to the clinical indication. Opportunistic screening refers to the practice of systematically leveraging these incidental imaging findings. Although opportunistic screening can apply to imaging modalities such as conventional radiography, US, and MRI, most attention to date has focused on body CT by using artificial intelligence (AI)-assisted methods. Body CT represents an ideal high-volume modality whereby a quantitative assessment of tissue composition (eg, bone, muscle, fat, and vascular calcium) can provide valuable risk stratification and help detect unsuspected presymptomatic disease. The emergence of "explainable" AI algorithms that fully automate these measurements could eventually lead to their routine clinical use. Potential barriers to widespread implementation of opportunistic CT screening include the need for buy-in from radiologists, referring providers, and patients. Standardization of acquiring and reporting measures is needed, in addition to expanded normative data according to age, sex, and race and ethnicity. Regulatory and reimbursement hurdles are not insurmountable but pose substantial challenges to commercialization and clinical use. Through demonstration of improved population health outcomes and cost-effectiveness, these opportunistic CT-based measures should be attractive to both payers and health care systems as value-based reimbursement models mature. If highly successful, opportunistic screening could eventually justify a practice of standalone "intended" CT screening.

CT image-based biomarkers acquired by AI-based algorithms for the opportunistic prediction of falls

Objective

Evaluate whether biomarkers measured by automated artificial intelligence (AI)-based algorithms are suggestive of future fall risk.

Methods

In this retrospective age- and sex-matched case-control study, 9029 total patients underwent initial abdominal CT for a variety of indications over a 20-year interval at one institution. 3535 case patients (mean age at initial CT, 66.5 ± 9.6 years; 63.4% female) who went on to fall (mean interval to fall, 6.5 years) and 5494 controls (mean age at initial CT, 66.7 ± 9.8 years; 63.4% females; mean follow-up interval, 6.6 years) were included. Falls were identified by electronic health record review. Validated and fully automated quantitative CT algorithms for skeletal muscle, adipose tissue, and trabecular bone attenuation at the level of L1 were applied to all scans. Uni- and multivariate assessment included hazard ratios (HRs) and area under the receiver operating characteristic (AUROC) curve.

Results

Fall HRs (with 95% CI) for low muscle Hounsfield unit, high total adipose area, and low bone Hounsfield unit were 1.82 (1.65-2.00), 1.31 (1.19-1.44) and 1.91 (1.74-2.11), respectively, and the 10-year AUROC values for predicting falls were 0.619, 0.556, and 0.639, respectively. Combining all these CT biomarkers further improved the predictive value, including 10-year AUROC of 0.657.

Conclusion

Automated abdominal CT-based opportunistic measures of muscle, fat, and bone offer a novel approach to risk stratification for future falls, potentially by identifying patients with osteosarcopenic obesity.

Advances in knowledge

There are few well-established clinical tools to predict falls. We use novel AI-based body composition algorithms to leverage incidental CT data to help determine a patient's future fall risk.

Opportunistic screening for osteoporosis by abdominal CT in a British population

BACKGROUND

It has previously been shown that CT scans performed for other indications can be used to identify patients with osteoporosis. This has not yet been tested in a British population. We sought to evaluate the use of vertebral CT attenuation measures for predicting osteoporosis in a British cohort, using dual-energy X-ray absorptiometry (DEXA) as a reference standard.

METHODS

Patients who underwent abdominal CT in 2018 and concomitantly underwent DEXA within a six-month interval were retrospectively included. CT attenuation values in Hounsfield units (HU) were measured by placement of a region-of-interest at the central portion of the L1 vertebral body and then compared to their corresponding DEXA score. Receiver operating characteristic (ROC) curves were generated to evaluate the performance of a logistic regression model and to determine sensitivity and specificity thresholds.

RESULTS

536 patients (394 females, mean age 65.8) were included, of which 174 had DEXA-defined osteoporosis. L1 attenuation measures were significantly different (p < 0.01) between the three DEXA-defined groups of osteoporosis (118 HU), osteopenia (143 HU) and normal bone density (178 HU). The area under the ROC curve was 0.74 (95% CI 0.69-0.78). A threshold of 169 HU was 90% sensitive, and a threshold of 104 HU was 90% specific for diagnosing osteoporosis.

CONCLUSIONS

Routine abdominal CT can be used to opportunistically screen for osteoporosis without additional cost or radiation exposure. The thresholds identified in this study are comparable with previous studies in other populations. We recommend radiologists engage with primary care and rheumatology providers to determine appropriate cut-off values for further investigation.

Differences in time-to-fusion based on "absence of peri-graft radiolucency" and "trabecular bone bridging" criteria after transforaminal lumbar interbody fusion in patients with low and normal bone density

OBJECTIVE

To investigate the difference in time-to-fusion between two sets of interbody fusion criteria (absence of peri-graft radiolucency vs. trabecular bone bridging), and to determine the effect of osteoporosis on time-to-fusion.

MATERIALS AND METHODS

This retrospective study enrolled 79 patients treated for degenerative disease with one-level transforaminal lumbar interbody fusion from February 2012 to December 2018, and who had both pre- and post-operative CTs. Patients were divided into osteoporosis, osteopenia, and normal groups based on L1 vertebral body attenuation values in pre-operative CT with cutoff of 90 Hounsfield units (HU) and 120 HU. The osteoporosis, osteopenia, and normal groups included 36 patients (mean age: 69.9 years; 8 men and 28 women), 18 patients (mean age: 62.6 years; 7 men and 11 women), and 25 patients (mean age: 56.6 years; 15 men and 10 women), respectively. Fusion was assessed annually on post-operative CT images using absence of peri-graft radiolucency and trabecular bone bridging criteria. Time-to-fusion was estimated using the Kaplan-Meier method, and differences between the groups were examined using the log-rank test. Cox proportional hazards regression was performed.

RESULTS

Time-to-fusion took significantly longer in the osteoporosis group in both fusion criteria (0.5 years in normal vs. 2 years in osteopenia vs. 3 years in osteoporosis for absence of peri-graft radiolucency; p = 0.003, and 3 years vs. 4 years vs. 5 years for trabecular bone bridging; p = 0.001). Only osteoporosis grouping was independent risk factor for slow trabecular bone fusion (hazard ratio:0.339; p = 0.003).

CONCLUSION

The median time to fusion was significantly longer when using trabecular bone bridging criteria than absence of peri-graft radiolucency criteria.

AI-based opportunistic CT screening of incidental cardiovascular disease, osteoporosis, and sarcopenia: cost-effectiveness analysis

PURPOSE

To assess the cost-effectiveness and clinical efficacy of AI-assisted abdominal CT-based opportunistic screening for atherosclerotic cardiovascular (CV) disease, osteoporosis, and sarcopenia using artificial intelligence (AI) body composition algorithms.

METHODS

Markov models were constructed and 10-year simulations were performed on hypothetical age- and sex-specific cohorts of 10,000 U.S. adults (base case: 55 year olds) undergoing abdominal CT. Using expected disease prevalence, transition probabilities between health states, associated healthcare costs, and treatment effectiveness related to relevant conditions (CV disease/osteoporosis/sarcopenia) were modified by three mutually exclusive screening models: (1) usual care ("treat none"; no intervention regardless of opportunistic CT findings), (2) universal statin therapy ("treat all" for CV prevention; again, no consideration of CT findings), and (3) AI-assisted abdominal CT-based opportunistic screening for CV disease, osteoporosis, and sarcopenia using automated quantitative algorithms for abdominal aortic calcification, bone mineral density, and skeletal muscle, respectively. Model validity was assessed against published clinical cohorts.

RESULTS

For the base-case scenarios of 55-year-old men and women modeled over 10 years, AI-assisted CT-based opportunistic screening was a cost-saving and more effective clinical strategy, unlike the "treat none" and "treat all" strategies that ignored incidental CT body composition data. Over a wide range of input assumptions beyond the base case, the CT-based opportunistic strategy was dominant over the other two scenarios, as it was both more clinically efficacious and more cost-effective. Cost savings and clinical improvement for opportunistic CT remained for AI tool costs up to $227/patient in men ($65 in women) from the $10/patient base-case scenario.

CONCLUSION

AI-assisted CT-based opportunistic screening appears to be a highly cost-effective and clinically efficacious strategy across a broad array of input assumptions, and was cost saving in most scenarios.

Opportunistic screening for osteoporosis and osteopenia from CT scans of the abdomen and pelvis using machine learning

OBJECTIVES

To use multivariable machine learning using the computed tomography (CT) attenuation of each of the bones in the lumbar spine, pelvis, and sacrum, to predict osteoporosis/osteopenia.

METHODS

This was a retrospective study of 394 patients aged 50 years or older with CT scans of the abdomen and pelvis and dual-energy x-ray absorptiometry (DXA) scans obtained within 6 months of each other. Volumetric segmentations were performed for each of the bones from L1-L4 vertebrae, pelvis, and sacrum to obtain the mean CT attenuation of each bone. The data was randomly split into training/validation (n = 274, 70%) and test (n = 120, 30%) datasets. The CT attenuation of the L1 vertebrae, univariate logistic regression, least absolute shrinkage and selection operator (LASSO), and support vector machines (SVM) with radial basis function (RBF) were used to predict osteoporosis/osteopenia. The performance of using the CT attenuation at L1 to the univariate logistic regression, LASSO, and SVM models were compared using DeLong's test in the test dataset.

RESULTS

All CT attenuation measurements were predictive of osteoporosis/osteopenia (p < 0.001 for all). The SVM model (accuracy = 0.892, AUC = 0.886) outperformed the models using the CT attenuation of threshold of 173.9 Hounsfield units (HU) at L1 (accuracy = 0.725, AUC = 0.739, p = 0.010), the univariate logistic regression model (accuracy = 0.767, AUC = 0.533, p < 0.001) and the LASSO model (accuracy = 0.817, AUC = 0.711, p = 0.007) to predict osteoporosis/osteopenia.

CONCLUSION

A SVM model using the CT attenuations of multiple bones within the lumbar spine and pelvis and clinical data has a better ability to predict osteoporosis/osteopenia than using the CT attenuation of L1 or a LASSO model.

KEY POINTS

• Multivariable SVM model using the CT attenuation of multiple bones and clinical/demographic data was more predictive than using the CT attenuation at L1 only.

Technical Adequacy of Fully Automated Artificial Intelligence Body Composition Tools: Assessment in a Heterogeneous Sample of External CT Examinations

Please see the Editorial Comment by Robert D. Boutin discussing this article. Chinese (audio/PDF) and Spanish (audio/PDF) translations are available for this article's abstract. Background: Clinically usable artificial intelligence (AI) tools analyzing imaging studies should be robust to expected variations in study parameters. Objective: To assess the technical adequacy of a set of automated AI abdominal CT body composition tools on a heterogeneous sample of external CT examinations performed outside of the authors' hospital system, as well as to explore possible reasons for tool failure. Methods: This retrospective study included 8949 patients (mean age, 55.5±15.9 years; 4256 men, 4693 women) who underwent 11,699 abdominal CT examinations performed at 777 different external institutions using 82 different scanner models from 6 different manufacturers, and subsequently transferred to the local PACS for clinical purposes. Three independent automated AI tools assessing body composition (bone attenuation, muscle amount and attenuation, visceral and subcutaneous fat amounts) were deployed, evaluating one axial series per examination. Technical adequacy was defined as tool output values within empirically derived reference ranges. Failures (i.e., tool output outside of reference range) were reviewed to identify possible causes. Results: All three tools were technically adequate in 11,431/11,699 (97.7%) examinations, with at least one tool failing in 268/11,699 (2.3%). Individual adequacy rates were 97.8%, 99.1%, and 98.0% for bone, muscle, and fat tools, respectively. A single type of image processing error (anisometry error, due to incorrect DICOM header voxel dimension information) accounted for 81/92 (88%) examinations for which all three tools failed, and all three tools failed whenever this error occurred. Anisometry error was the most common specific cause for failure for all tools (31.6% for bone, 81.0% for muscle, and 62.8% for fat). A total of 79/81 (97.5%) anisometry errors occurred on scanners from a single manufacturer; 80/81 (98.8%) occurred on the same scanner model. No cause for failure was identified in 59.4%, 16.0%, and 34.9% of failures for the bone, muscle, and fat tools, respectively. Conclusion: The automated AI body composition tools had high technical adequacy rates in a heterogeneous sample of external CT examinations, supporting the tools' generalizability and potential for broad use. Clinical Impact: Certain reasons for AI tool failure relating to technical factors may be largely preventable through proper acquisition and reconstruction protocols.

Opportunistic measures of bone mineral density at multiple skeletal sites during whole-body CT in polytrauma patients

Whole-body CT in polytrauma patients revealed bone mineral density variations throughout the skeleton. Bone density was the highest in cranial bones and the lowest in proximal extremities and pelvis. Skeletal age-related changes were generally more pronounced than sex-related changes. Cranial bones did not follow the same aging pattern compared to other bones.

INTRODUCTION

Whole-body CT (WBCT) in polytrauma patients enables the detection of numerous incidental findings, such as estimates of bone mineral density (BMD) at multiple skeletal sites. This could help in better understanding of age- and sex-related changes in BMD through skeleton.

METHODS

Data were retrospectively retrieved from the WBCTs requested during a 2-year period. BMD, expressed in CT Hounsfield units (HU), was measured at frontal and occipital bone, four vertebrae (C4, Th7, L4, and S2), iliac bone, and proximal humerus and femur. Measurements were done on native and postcontrast scans. The population sample was age-, sex-, and visceral fat volume adjusted for analysis.

RESULTS

A total of 296 patients were included, with a median age of 51 years. BMD varied from the highest HU in cranial bones (629 HU) to the lowest HU in the pelvic bones (114 HU), P < 0.001. Sex differences were independent predictors of BMD in cranial bones and proximal humerus. The age-related decline in BMD was significant in all other bones, but the association with age differed among the measurement's sites. Visceral fat showed the strongest correlation with the lumbar spine and iliac wing, although multivariate analysis revealed it was not an independent predictor of bone density, such as age and sex.

CONCLUSIONS

BMD varies through skeleton, being the highest in the proximal axial skeleton. Age-related changes in BMD are significant and more pronounced than sex-related changes in almost all bones. Cranial bones do not follow the same pattern compared to other bones.

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.

Body Composition in Patients with Follicular Lymphoma: Asso-Ciations between Changes in Radiomic Parameters in Patients Treated with R-CHOP-like and R-B Regimens: LyRa 01F

In patients with follicular lymphoma (FL), therapeutic advances have led to improved survival, and within this framework, it is important to identify treatment strategies offering a better quality of life. Using (18)F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT), in patients treated with R-CHOP-like or R-Bendamustine regimens, we assessed changes in the bone mineral density (BMD), musculoskeletal index (SMI), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) at disease onset and at the end of therapy. We evaluated whether the high-steroid regimen could lead to more significant radiological changes than those induced by the steroid-free regimen and whether a low BMD at disease onset is an unfavorable prognostic index. Seventy-nine patients between 60 and 80 years old with a new diagnosis of FL were included in the study. Evaluation of Delta values (pre- and post-therapy mean values) in the two immunochemotherapy regimens showed differences in radiomic parameters within the two patient cohorts. The R-CHOP-like regimen was associated with a significant reduction in BMD, an increase in SAT and VAT, and a reduction in skeletal muscle density (SMD) and SMI. Moreover, patients with high FLIPI showed a BMD below the cut-off value. This study represents the first study demonstrating a prognostic correlation between FLIPI and low BMD.

The vertebral Hounsfield units can quantitatively predict the risk of adjacent vertebral fractures after percutaneous kyphoplasty

Background

Measuring the Hounsfield units (HU) of the vertebrae may yield diagnostic information for fracture risk. This study aimed to measure HU of vertebrae in percutaneous kyphoplasty (PKP) patients using computed tomography (CT) imaging to determine the HU measurements threshold for adjacent vertebral fracture and to assess the relationship between HU measurements and the risk of adjacent vertebral fracture.

Methods

A retrospective study was conducted on consecutive patients who underwent PKP between January 2019 and October 2021 in the China-Japan Union Hospital of Jilin University. The HU of the vertebra was measured on the reconstructed CT images by 2 independent spine surgeons. The HU measurements of adjacent vertebrae and the ratio of HU measurements between the surgical vertebra and adjacent vertebrae were statistically analyzed to determine the best critical value and evaluate the prediction effectiveness and accuracy of the best critical value.

Results

A total of 105 patients were identified with complete imaging and follow-up information. Of these, 47 patients (44.8%) had evidence of an adjacent vertebral fracture on follow-up imaging. The mean HU measurements of the fractured adjacent vertebra were significantly different from the mean HU measurements of the unfractured adjacent vertebra (50.94±20.59 vs. 81.74±18.97 HU; P<0.001). There was a significant difference in the ratio of HU measurements between the surgical vertebra and the fractured adjacent vertebra and between the surgical vertebra and the unfractured adjacent vertebra (26.34±17.52 vs. 14.53±9.40; P<0.001). Interactive scatter plots and receiver operating characteristic (ROC) curve showed that a HU measurement of 66.9 and a HU measurements ratio of 15.18 were the best thresholds for predicting the risk of fracture of adjacent vertebrae after PKP surgery, with an area under the curve (AUC) of 0.901 [95% confidence interval (CI): 0.822-0.953; P<0.001] and 0.874 (95% CI: 0.790-0.934; P<0.001), respectively. The prediction accuracy was 90.4% and 84.0%, respectively.

Conclusions

A low mean HU measurements of adjacent vertebrae or a high ratio of the mean HU measurements of the operated vertebrae to the adjacent vertebrae are risk factors for the vulnerability of adjacent vertebrae to fracture. The risk of fracture in the adjacent vertebrae after PKP can be predicted by measuring HU.

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.

Diagnostic power of vertebral hydroxyapatite concentration measurements in spectral CT for osteoporosis-associated fractures and impact of intravenous contrast administration

OBJECTIVES

To evaluate the diagnostic power of using vertebral hydroxyapatite concentration measurements in unenhanced and contrast-enhanced spectral CT for detecting and predicting the risk of osteoporosis-associated fractures.

METHODS

L1 of 210 patients (105 men, 105 women; mean age, 64 years, range, 19-103 years) who had undergone spectral CT examinations from January 1, 2018, to March 1, 2019, were retrospectively analyzed. Patient data for 3 years after spectral CT were retrieved from electronic medical record information systems to obtain the incidence of osteoporotic fractures. Baseline vertebral cancellous hydroxyapatite concentration from unenhanced and contrast-enhanced late-arterial-phase images was measured. The receiver operating characteristic curves were used to evaluate the diagnostic power for detecting and predicting the 3-year risk of osteoporosis-associated fractures using hydroxyapatite concentrations in both phases.

RESULTS

The hydroxyapatite concentrations in both phases had good diagnostic power to detect fractures at baseline. The sensitivity and specificity for predicting one or more osteoporosis-associated fractures within 3 years after spectral CT were 76.80% and 93.10%, respectively, using the cutoff of 74.79 mg/cm³ in vertebral hydroxyapatite concentration in the unenhanced CT phase, and 82.87% and 82.76%, respectively, using the cutoff of 84.65 mg/cm³ in the late-arterial phase. Furthermore, there was no significant difference in the diagnosis between unenhanced and enhanced CT-derived hydroxyapatite concentrations (p = 0.360).

CONCLUSIONS

Both unenhanced and enhanced spectral CT-derived hydroxyapatite concentrations can accurately detect and predict future risk of osteoporosis-associated fractures. The hydroxyapatite concentration assessed in the late-arterial phase may have a similar diagnostic efficacy to that in the unenhanced phase.

KEY POINTS

• A cutoff of 74.79 mg/cm³ of vertebral hydroxyapatite concentration in the unenhanced CT scans had 76.80% sensitivity and 93.10% specificity to predict one or more osteoporosis-associated fractures within 3 years after spectral CT examinations. • A cutoff of 84.65 mg/cm³ of vertebral hydroxyapatite concentration in the late-arterial-enhanced CT scans had 82.87% sensitivity and 82.76% specificity to predict one or more osteoporosis-associated fractures within 3 years after spectral CT examinations. • The hydroxyapatite concentration assessed in the late-arterial phase may have a similar diagnostic efficacy to that in the unenhanced phase.

CT evaluation of bone fragility 2 years after bariatric surgery: an observational study

INTRODUCTION

The objectives were to evaluate bone fragility on computed tomography (CT) in patients with obesity before and 2 years after bariatric surgery and to identify risk factors for a decrease in the scanographic bone attenuation coefficient of the first lumbar vertebra (SBAC-L1).

MATERIALS AND METHODS

Patients with obesity who underwent bariatric surgery and CT before and 2 years (± 6 months) after bariatric surgery were included. SBAC-L1 was measured on CT with a fracture threshold at 145 HU.

RESULTS

78 patients were included, 85.9% women, mean age of 48.5 years (± 11.4); the mean BMI was 46.2 kg/m² (± 7) before surgery and 29.8 kg/m² (± 6.7) 2 years after surgery. There was a significant change in SBAC-L1 2 years after surgery (p = 0.037). In multivariate analysis, the risk factors for having an SBAC-L1 ≤ 145HU 2 years after bariatric surgery in those with an SBAC-L1 > 145HU before surgery were age and sex, with men and older patients having a higher risk (OR 32.6, CI 95% [1.86-568.77], and OR 0.85, CI 95% [0.74-0.98], respectively).

CONCLUSION

SBAC-L1 was significantly lower two years after bariatric surgery. Men sex and older patients were the risk factors for having an SBAC-L1 below the fracture threshold 2 years after surgery.

Low bone mineral density is a prognostic factor for elderly patients with HCC undergoing TACE: results from a multicenter study

OBJECTIVES

Low bone mineral density (BMD) was recently identified as a novel risk factor for patients with hepatocellular carcinoma (HCC). In this multicenter study, we aimed to validate the role of BMD as a prognostic factor for patients with HCC undergoing transarterial chemoembolization (TACE).

METHODS

This retrospective multicenter trial included 908 treatment-naïve patients with HCC who were undergoing TACE as a first-line treatment, at six tertiary care centers, between 2010 and 2020. BMD was assessed by measuring the mean Hounsfield units (HUs) in the midvertebral core of the 11^th thoracic vertebra, on contrast-enhanced computer tomography performed before treatment. We assessed the influence of BMD on median overall survival (OS) and performed multivariate analysis including established estimates for survival.

RESULTS

The median BMD was 145 HU (IQR, 115-175 HU). Patients with a high BMD (≥ 114 HU) had a median OS of 22.2 months, while patients with a low BMD (< 114 HU) had a lower median OS of only 16.2 months (p < .001). Besides albumin, bilirubin, tumor number, and tumor diameter, BMD remained an independent prognostic factor in multivariate analysis.

CONCLUSIONS

BMD is an independent predictive factor for survival in elderly patients with HCC undergoing TACE. The integration of BMD into novel scoring systems could potentially improve survival prediction and clinical decision-making.

KEY POINTS

• Bone mineral density can be easily assessed in routinely acquired pre-interventional computed tomography scans. • Bone mineral density is an independent predictive factor for survival in elderly patients with HCC undergoing TACE. • Thus, bone mineral density is a novel imaging biomarker for prognosis prediction in elderly patients with HCC undergoing TACE.

Lumbar Bone Mineral Density Estimation From Chest X-Ray Images: Anatomy-Aware Attentive Multi-ROI Modeling

Osteoporosis is a common chronic metabolic bone disease often under-diagnosed and under-treated due to the limited access to bone mineral density (BMD) examinations, e.g., via Dual-energy X-ray Absorptiometry (DXA). This paper proposes a method to predict BMD from Chest X-ray (CXR), one of the most commonly accessible and low-cost medical imaging examinations. The proposed method first automatically detects Regions of Interest (ROIs) of local CXR bone structures. Then a multi-ROI deep model with transformer encoder is developed to exploit both local and global information in the chest X-ray image for accurate BMD estimation. The proposed method is evaluated on 13719 CXR patient cases with ground truth BMD measured by the gold standard DXA. The model predicted BMD has a strong correlation with the ground truth (Pearson correlation coefficient 0.894 on lumbar 1). When applied in osteoporosis screening, it achieves a high classification performance (average AUC of 0.968). As the first effort of using CXR scans to predict the BMD, the proposed algorithm holds strong potential to promote early osteoporosis screening and public health.

Advancement in the Treatment of Osteoporosis and the Effects on Bone Healing

Osteoporosis (OP) is a major global health concern, with aging being one of the most important risk factors. Osteoarthritis (OA) is also an age-related disorder. Patients with OP and/or OA may be treated surgically for fractures or when their quality of life is impaired. Poor bone quality due to OP can seriously complicate the stability of a bone fixation construct and/or surgical fracture treatment. This review summarizes the current knowledge on the pathophysiology of normal and osteoporotic bone healing, the effect of a bone fracture on bone turnover markers, the diagnosis of a low bone mineral density (BMD) before surgical intervention, and the effect of available anti-osteoporosis treatment. Interventions that improve bone health may enhance the probability of favorable surgical outcomes. Fracture healing and the treatment of atypical femoral fractures are also discussed.

Routine chest CT combined with the osteoporosis self-assessment tool for Asians (OSTA): a screening tool for patients with osteoporosis

INTRODUCTION

The osteoporosis self-assessment tool for Asians (OSTA) is a common screening tool for osteoporosis. The seventh thoracic CT (CT-T7) Hounsfield unit (HU) measured by chest CT correlates with osteoporosis. This study aimed to investigate the diagnostic value of OSTA alone, CT-T7 alone, or the combination of OSTA and CT-T7 in osteoporosis.

MATERIALS AND METHODS

In this study, 1268 participants were grouped into 586 men and 682 women. We established multiple linear regression models by combining CT-T7 and OSTA. Receiver operating characteristic (ROC) curves were used to evaluate the ability to diagnose osteoporosis.

RESULTS

In the male group, the mean age was 59.02 years, and 108 patients (18.4%) had osteoporosis. In the female group, the mean age was 63.23 years, and 308 patients (45.2%) had osteoporosis. By ROC curve comparison, the CT-T7 (male, AUC = 0.789, 95% CI 0.745-0.832; female, AUC = 0.835, 95% CI 0.805-0.864) in the diagnosis of osteoporosis was greater than the OSTA (male, AUC = 0.673, 95% CI 0.620-0.726; female, AUC = 0.775, 95% CI 0.741-0.810) in both the male and female groups (p < 0.001). When OSTA was combined with CT, the equation of multiple linear regression (MLR) was obtained as follows: female = 3.020-0.028*OSTA-0.004*CT-T7. In the female group, it was found that the AUC of MLR (AUC = 0.853, 95% CI 0.825-0.880) in the diagnosis of osteoporosis was larger than that of CT-T7 (p < 0.01). When the MLR was 2.65, the sensitivity and specificity were 53.9% and 90%, respectively.

CONCLUSION

For a patient who has completed chest CT, CT-T7 (HU) combined with OSTA is recommended to identify the high-risk population of osteoporosis, and it has a higher diagnostic value than OSTA alone or CT-T7 alone, especially among females. For a female with MLR greater than 2.65, further DXA examination is needed.

Opportunistic screening for osteoporosis using hydroxyapatite measurements of the vertebral by thorax dual-energy spectral CT in postmenopausal females

The purpose of this study was to evaluate the feasibility of opportunistic screening for osteoporosis in postmenopausal females using the dual-energy CT(DECT)-derived hydroxyapatite (HAP) concentration and CT value of L1-vertebra. 239 consecutive postmenopausal female patients were enrolled and underwent both chest DECT and Dual energy X-ray absorptiometry (DXA). According to the T-score of the 1st lumbar vertebra on DXA, patients were divided into the osteoporosis group (T [Formula: see text]- 2.5, n = 112) and non-osteoporosis group (T [Formula: see text] - 2.5, n = 127). The HAP values of the 1st lumbar vertebra were measured from the coronal-view HAP(Fat)-based material decomposition(MD) images, and CT values were measured on the 75 keV monochromatic image. The cutoff values of using HAP and CT value for diagnosing osteoporosis were obtained by drawing receiver operating characteristic (ROC) curves. Both HAP and CT value of the 1st lumbar vertebra had moderate-high correlation with bone-mineral-density measurement on DXA (HAP, r = 0.614; CT value, r = 0.625; all p < 0.01). The area-under-the-curve (AUC), sensitivity, specificity, PPV and NPV for diagnosing osteoporosis was 0.754, 0.714, 0.693, 0.68 and 0.752 using HAP (cutoff value: 142.05 mg/cm³) and 0.766, 0.741, 0.7, 0.685 and 0.754 using CT value (cutoff value: 132HU), respectively. HAP measurements on HAP(Fat)-based MD images in DECT could provide reasonably accurate BMD quantification for diagnosing osteoporosis in postmenopausal females. DECT prescribed for lung cancer screening could also provide opportunistic screening for osteoporosis, extending the clinical application of DECT without additional radiation to patients.

Effects of whole-body vibration at different periods on lumbar vertebrae in female rats

The current study aimed to investigate the effects of whole-body vibration (WBV) before and after ovariectomy on lumbar vertebrae, and to observe whether the positive effects of WBV before and after ovariectomy on lumbar vertebrae in rats could be maintained after vibration stopped. Three-month-old female rats were divided into four groups (n = 45/group): control (CON), ovariectomy (OVA), WBV before ovariectomy (WBV-BO), and WBV after ovariectomy (WBV-AO) groups. For 1-8 weeks, WBV-BO group was subjected to vertical WBV. At the 9th week, the rats in WBV-BO, WBV-AO, and OVA groups were ovariectomized. During 11-18 weeks, WBV-AO group was subjected to vibration. For 19-26 weeks, no intervention was done for rats. The lumbar vertebrae were examined by Micro-CT, compressive test, creep test, and microindentation test. At the 8th week, the displacement of the L1-L2 annulus fibrosus in WBV-BO group was 18% smaller compared with CON group (p<0.05). At the 18th week, the elastic modulus of the L5 vertebral body in WBV-BO and WBV-AO groups was 53% and 57% higher than that in CON group, respectively (p<0.05); the displacement of the L1-L2 annulus fibrosus in WBV-BO group was 25% smaller than those in the other groups (p<0.05). At the 26th week, there was no significant difference in the displacement of the L1-L2 annulus fibrosus between WBV-BO group and other groups (p>0.05); the elastic modulus of the L5 vertebral body had no significant difference between WBV-AO group and CON group (p>0.05). Our results demonstrated that WBV before ovariectomy effectively prevented disc degeneration with significant effects up to 8 weeks after ovariectomy. The vertebral mechanical properties could be significantly improved by WBV after ovariectomy, but the residual effect did not maintain after WBV stopped.

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.

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

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

Long‐term changes in bone mineral density in postoperative patients with esophageal cancer

Aim

The aim of this study was to investigate long-term changes in bone mineral density (BMD) after esophagectomy, identify the risk factors for postoperative osteoporosis in patients with esophageal cancer and survival outcomes related to osteoporosis.

Methods

We retrospectively evaluated BMD changes for 197 consecutive patients with thoracic esophageal cancer who were disease-free for 5 years after radical esophagectomy. Osteoporosis was diagnosed using computed tomography with an L1 attenuation threshold of ≤110 HU. Survival analysis was performed on 381 consecutive patients with 5-year follow-up after radical esophagectomy.

Results

BMD decreased annually after esophagectomy. The median attenuation (HU) was 134.2 before surgery and 135.2, 127.4, 123.3, 115.2, 105.6, and 102.4 at 6 months and 1, 2, 3, 4, and 5 years after surgery, respectively. Osteoporosis was diagnosed in 25.9% patients before surgery and 23.3%, 29.4%, 40.1%, 46.7%, 54.8%, and 60.4% patients with osteoporosis were observed at 6 months and 1, 2, 3, 4, and 5 years after surgery, respectively. Postoperative BMD did not decrease in patients aged ≤54 years, those who had never been smokers, and those with no weight loss after esophagectomy. Multivariate analysis identified that age (≥65 years) at surgery and smoking history were independent risk factors for osteoporosis at 5 years after esophagectomy. Patients with preoperative osteoporosis tended to have worse prognosis in disease-free survival and overall survival than those without osteoporosis, who were more likely to die due to non-esophageal cancer.

Conclusion

Esophageal cancer survivors are more likely to develop osteoporosis after esophagectomy, and preoperative osteoporosis might be associated with prognosis.

Low skull bone density is associated with poor motor prognosis in women with Parkinson’s disease

Parkinson’s disease (PD) and osteoporosis are degenerative diseases that have shared pathomechanisms. To investigate the associations of skull bone density with nigrostriatal dopaminergic degeneration and longitudinal motor prognosis in female patients with PD. We analyzed the data of 260 drug-naïve female PD patients aged ≥50 years old who were followed-up for ≥3 years after their first visit to the clinic with baseline dopamine transporter (DAT) imaging. We measured skull bone density as a surrogate marker for systemic bone loss by calculating the Hounsfield unit (HU) in computed tomography scans. A Cox proportional hazard model was built to compare the rates of levodopa-induced dyskinesia (LID) or wearing-off according to skull HU. Longitudinal changes in levodopa-equivalent dose (LED) during a 3-year follow-up were assessed using a linear mixed model. A lower skull HU was associated with lower baseline DAT availability in striatal subregions; however, this relationship was not significant after adjusting for age, disease duration, body mass index, and white matter hyperintensities. After adjusting for confounding factors, a lower skull HU was significantly associated with an increased risk of LID development (hazard ratio = 1.660 per 1 standard deviation decrease, p = 0.007) and wearing-off (hazard ratio = 1.613, p = 0.016) in younger (&lt;67 years) but not in older patients. Furthermore, a lower skull HU was associated with a steeper increase in LED during follow-up in younger patients only (β = –21.99, p &lt; 0.001). This study suggests that baseline skull bone density would be closely linked to motor prognosis in drug naïve women with PD.

Osteopenia is associated with inferior survival in patients undergoing partial hepatectomy for hepatocellular carcinoma

Osteopenia is known to be associated with clinical frailty which is linked to inferior outcomes in various clinical scenarios. However, the exact prognostic value of osteopenia in patients undergoing curative intent-surgery for hepatocellular carcinoma (HCC) is not completely understood. This retrospective study was conducted in a cohort of 151 patients who underwent partial hepatectomy for HCC in curative intent at a German university medical center (05/2008-12/2019). Preoperative computed tomography-based segmentation was used to assess osteopenia, and the prognostic impact of pathological changes in bone mineral density (BMD) on perioperative morbidity, mortality, and long-term oncological outcome was analyzed. Five-year overall survival of osteopenic patients was significantly worse compared to those with normal BMD (29% vs. 65%, p = 0.014). In line with this, the probability of disease-free survival at 5 years was significantly worse for patients with osteopenia (21% vs. 64%, p = 0.005). In our multivariable model, osteopenia was confirmed as an independent risk-factor for inferior overall survival (Hazard-ratio 7.743, p = 0.002). Concerning perioperative complications, osteopenic patients performed slightly worse, even though no statistical difference was detected (Clavien-Dindo ≥ 3b; 21% vs. 9%, p = 0.139). The present study confirms osteopenia as an independent risk-factor for inferior survival in patients undergoing partial hepatectomy for HCC in a European cohort. Further studies are warranted to validate these findings.

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

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

Interest in curves: when the radius of curvature matters in femur fractures. A CT based morphometric study

PURPOSE

In today's era, fractures of the femur are primarily managed with intramedullary devices. Keeping in mind the anatomical sagittal bow of the femur, intramedullary devices have been devised with an anterior bow, but this varies amongst various manufacturers - leading to complications such as anterior cortex impingement beyond the isthmus and posterior cortical opening at the fracture site. We intend to find the average radius of curvature (ROC) of the anatomical bow of the femur and the variation of the same.

METHODS

Radiographic data of 150 normal femur scans done in 81 patients were loaded in the Mimics 21.0 software (Materialise, Leuven, Belgium). A centerline (of the medullary cavity) was created using the software. A best-fit circle was created in the sagittal plane involving a major part of the centerline, and ROC was calculated.

RESULTS

We found the average ROC of our data was 1027.2, with a standard deviation of 241.55. ROC and length of the femur (an indirect measure of height) had a slight positive correlation (r = 0.36; p < 0.05); and a highly positive correlation in the ROC of the left and right femurs of the same individuals (r = 0.605; p < 0.05).

CONCLUSIONS

The usual ROC of intramedullary nails is commonly > 1300 mm, much higher than the average ROC we identified in our population. Thus, we conclude that implants with smaller ROC in the range of 1100 mm are needed, leading to better implant placement in the canal and avoiding complications of anterior cortex impingement and preventing fracture gap widening in our setting.

Prevalence of Osteoporosis Assessed by DXA and/or CT in Severe Obese Patients

The primary objective was to evaluate bone fragility prevalence on dual X-ray absorptiometry (DXA) and computed tomography (CT) in patients with severe obesity. The secondary objective was to evaluate the risk factors for bone fragility. This monocentric study was conducted in patients with grade 2 and 3 obesity. Bone mineral density (BMD) and T-score were studied on DXA, and the scanographic bone attenuation coefficient of L1 (SBAC-L1) was measured on CT. Among the 1386 patients included, 1013 had undergone both DXA and CT within less than 2 years. The mean age was 48.4 (±11.4) years, 77.6% were women, and the mean BMI was 45.6 (±6.7) kg/m². Eight patients (0.8%) had osteoporosis in at least one site. The mean SBAC-L1 was 192.3 (±52.4) HU; 163 patients (16.1%) were under the threshold of 145 HU. Older age (OR[CI95] = 1.1 [1.08–1.16]), lower BMD on the femoral neck and spine (OR[CI95] = 0.04[0.005–0.33] and OR[CI95] = 0.001[0.0001–0.008], respectively), and higher lean mass (OR[CI95] = 1.1 [1.03–1.13]) were significantly associated with an SBAC-L1 ≤ 145 HU in multivariate analysis. Approximately 16% of patients with severe obesity were under the SBAC-L1 threshold, while less than 1% were classified as osteoporotic on DXA.

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.

Hounsfield unit measurement method and related factors that most appropriately reflect bone mineral density on cervical spine computed tomography

OBJECTIVE

Our study's purpose was to determine the most reliable Hounsfield unit (HU) measurement method to reflect bone mineral density (BMD) on cervical spine computed tomography (CT) and to identify any factors that influence these results.

MATERIALS AND METHODS

We retrospectively analyzed 439 consecutive patients with mild head and neck injuries. Mean HU values of the C2-C7 vertebra were determined on each sagittal, coronal, and axial CT image. Correlation patterns were analyzed between the HU value and corresponding dual-energy X-ray absorptiometry (DXA) in the lumbar vertebra (T-score) and femoral neck (T-score). A sub-group analysis was performed according to patient age, sex, and degree of spinal degeneration.

RESULTS

The correlation coefficients for HU and DXA ranged from 0.52 to 0.65 in all cervical segments. A simple linear regression analysis revealed the following formula: T-score = 0.01 × (HU) - 4.55. The mean HU values for osteopenia and osteoporosis were 284.0 ± 63.3 and 231.5 ± 52.8, respectively. The ROC curve indicated that the HU method has a sensitivity of 89.2% and specificity of 88.7% to diagnose osteoporosis. The HU measurement showed a high correlation value (range: r = 0.64-0.70) with spine DXA score regardless of the degree of degeneration or patient age or sex.

CONCLUSION

HU values using the upper two cervical vertebrae (C2 and C3) reflected a more reliable BMD level than other segments. Additionally, the HU of cervical CT provided reliable information regardless of measurement plane, age or sex, and degree of degeneration.

Proceedings of the 2022 Santa Fe Bone Symposium: Current Concepts in the Care of Patients with Osteoporosis and Metabolic Bone Diseases

The 22^nd Annual Santa Fe Bone Symposium (SFBS) was a hybrid meeting held August 5-6, 2022, with in-person and virtual attendees. Altogether, over 400 individuals registered, a majority of whom attended in-person, representing many states in the USA plus 7 other countries. The SFBS included 10 plenary presentations, 2 faculty panel discussions, satellite symposia, Bone Health & Osteoporosis Foundation Fracture Liaison Service Boot Camp, and a Project ECHO workshop, with lively interactive discussions for all events. Topics of interest included fracture prevention at different stages of life; how to treat and when to change therapy; skeletal health in cancer patients; advanced imaging to assess bone strength; the state of healthcare in the USA; osteosarcopenia; vitamin D update; perioperative bone health care; new guidelines for managing primary hyperparathyroidism; new concepts on bone modeling and remodeling; and an overview on the care of rare bone diseases, including hypophosphatasia, X-linked hypophosphatemia, tumor induced osteomalacia, osteogenesis imperfecta, fibrodysplasia ossificans progressiva, and osteopetrosis. The SFBS was preceded by the Santa Fe Fellows Workshop on Osteoporosis and Metabolic Bone Diseases, a collaboration of the Endocrine Fellows Foundation and the Osteoporosis Foundation of New Mexico. From the Workshop, 4 participating fellows were selected to give oral presentations at the bone symposium. These proceedings represent the clinical highlights of 2022 SFBS presentations and the discussions that followed, all with the aim of optimizing skeletal health and minimizing the consequences of fragile bones.