Quantitative CT screening improved lumbar BMD evaluation in older patients compared to dual-energy X-ray absorptiometry

Developing Cut-off Values for Low and Very Low Bone Mineral Density at the Thoracic Spine Using Quantitative Computed Tomography

Osteoporosis is under-diagnosed while detectable by measuring bone mineral density (BMD) using quantitative computer tomography (QCT). Opportunistic screening for low BMD has previously been suggested using lumbar QCT. However, thoracic QCT also possesses this potential to develop upper and lower cut-off values for low thoracic BMD, corresponding to the current cut-offs for lumbar BMD. In participants referred with chest pain, lumbar and thoracic BMD were measured using non-contrast lumbar- and cardiac CT scans. Lumbar BMD cut-off values for very low (< 80 mg/cm3), low (80-120 mg/cm3), and normal BMD (> 120 mg/cm3) were used to assess the corresponding thoracic values. A linear regression enabled identification of new diagnostic thoracic BMD cut-off values. The 177 participants (mean age 61 [range 31-74] years, 51% women) had a lumbar BMD of 121.6 mg/cm3 (95% CI 115.9-127.3) and a thoracic BMD of 137.0 mg/cm3 (95% CI: 131.5-142.5), p < 0.001. Categorization of lumbar BMD revealed 14%, 35%, and 45% in each BMD category. When applied for the thoracic BMD measurements, 25% of participants were reclassified into a lower group. Linear regression predicted a relationship of Thoracic BMD = 0.85 * Lumbar BMD + 33.5, yielding adjusted thoracic cut-off values of < 102 and > 136 mg/cm3. Significant differences in BMD between lumbar and thoracic regions were found, but a linear relationship enabled the development of thoracic upper and lower cut-off values for low BMD in the thoracic spine. As Thoracic CT scans are frequent, these findings will strengthen the utilization of CT images for opportunistic detection of osteoporosis.

Quantitative metrics of bone quality determined at the distal radius using photon-counting CT

OBJECTIVE

To determine the accuracy of photon-counting-detector CT (PCD-CT) at deriving bone morphometric indices and demonstrate utility in vivo in the distal radius.

METHODS

Ten cadaver wrists were scanned using PCD-CT and high-resolution peripheral quantitative CT (HRpQCT). Correlation between PCD-CT and HRpQCT morphometric indices was determined. Agreement was assessed by Lin's concordance correlation coefficient (Lin's CCC). Wrist PCD-CTs of patients between 02/2022 and 08/2023 were also evaluated for clinical utility. Morphometric indices of the in vivo distal radii were extracted and compared between patients with or without osteoporosis.

RESULTS

In cadavers, strong correlation between PCD-CT and HRpQCT was observed for cortical thickness (Spearman correlation, ρ, 0.85), trabecular spacing (ρ = 0.98), and trabecular bone volume fraction (ρ = 0.68). Moderate negative correlation (ρ =  - 0.49) was observed for trabecular thickness. PCD-CT shows good agreement to HRpQCT for cortical thickness, trabecular spacing, and trabecular bone volume fraction (Lin's CCC = 0.80, 0.94, and 0.86, respectively) but poor agreement (Lin's CCC =  - 0.1) for trabecular thickness. In forty participants (31 adults and 9 pediatric), bone morphometrics indices for cortical thickness, trabecular thickness, trabecular spacing, and trabecular bone volume fraction were 0.99 mm (IQR, 0.89-1.06), 0.38 mm (IQR, 0.25-0.40), 0.82 mm (IQR, 0.72-1.05), and 0.28 (IQR, 0.25-0.33), respectively. Patients with osteoporosis had statistically significantly larger trabecular spacing (p = 0.025) and lower trabecular volumetric bone mineral density (p = 0.042).

CONCLUSION

This study demonstrates the agreement of PCD-CT to HRpQCT in cadavers of most cortical and bone morphometrics examined and provide in vivo quantitative metrics of bone microarchitecture from routine clinical PCD-CT images of the distal radius.

Quantitative CT lumbar spine BMD cutpoint value for classifying osteoporosis among older East Asian women should be lower than the value for Caucasians

For Caucasian women, the QCT (quantitative CT) lumbar spine (LS) bone mineral density (BMD) cutpoint value for classifying osteoporosis is 80 mg/ml. At the age of approximate 78 years, US Caucasian women QCT LS BMD population mean is 80 mg/ml, while that of Chinese women and Japanese women is around 50 mg/ml. Correlation analyses show, for Chinese women and Japanese women, QCT LS BMD of 45 mg/ml corresponds to the dual-energy X-ray absorptiometry cutpoint value for classifying osteoporosis. For Chinese and Japanese women, if QCT LS BMD 80 mg/ml is used as the threshold to classify osteoporosis, then the specificity of classifying subjects with vertebral fragility fracture into the osteoporotic group is low, whereas threshold of 45 mg/ml approximately achieve a similar separation for women with and without vertebral fragility fracture as the reports for Caucasian women. Moreover, by using 80mg/ml as the cutpoint value, LS QCT leads to excessively high prevalence of osteoporosis for Chinese women, with the discordance between hip dual-energy X-ray absorptiometry and LS QCT measures far exceeding expectation. Considering the different bone properties and the much lower prevalence of fragility fractures in the East Asian women compared with Caucasians, we argue that the QCT cutpoint value for classifying osteoporosis among older East Asian women will be close to and no more than 50 mg/ml LS BMD. We suggest that it is also imperative the QCT osteoporosis classification criterion for East Asian male LS, and male and female hips be re-examined.

Independent Risk Factors of Proximal Junctional Kyphosis with Vertebral Fracture After Spinal Long Fusion: Survivorship Analysis of Adult Spinal Deformity Surgery Patients

OBJECTIVE

This study aimed to identify risk factors for postoperative proximal junctional kyphosis (PJK) with vertebral fracture in adult spinal deformity (ASD) patients. We performed a survival analysis considering various factors, including osteoporosis.

METHODS

This single-center retrospective study included 101 ASD patients (mean age: 67.2 years, mean follow-up: 8.1 years). We included patients aged ≥50 years with abnormal radiographic variables undergoing corrective long spinal fusion. The main outcome measure was PJK with vertebral fracture, analyzed based on patient data, radiographic measurements, sagittal parameters, bone mineral density, and osteoporosis medication.

RESULTS

PJK occurred in 37.6% of patients, with vertebral fracture type 2 accounting for 65% of these cases. Kaplan-Meier analysis indicated a median PJK-free survival time of 60.7 months. Existing vertebral fracture (grade 1 or higher or grade 2 or higher) was a significant risk factor for PJK with vertebral fracture, with hazard ratios of 4.58 and 5.61, respectively. The onset time of PJK with vertebral fracture was 1.5 months postoperatively, with 44% of these cases occurring within 1 month and 64% within 2 months.

CONCLUSIONS

PJK with vertebral fracture affected 25% of ASD patients, emphasizing the importance of osteoporosis evaluation. Existing vertebral fracture emerged as a significant independent risk factor, surpassing bone mineral density. This study provides valuable insights for spine surgeons, highlighting the need to provide osteoporosis treatment and emphasize potential postoperative complications during discussions with patients.

Quantitative CT lumbar spine BMD cutpoint value for classifying osteoporosis among older Chinese men can be the same as that of older Chinese women, both much lower than the value for Caucasians

For older Caucasian women and men, the QCT (quantitative CT) lumbar spine (LS) bone mineral density (BMD) threshold for classifying osteoporosis is 80 mg/ml. It was recently proposed that, for older East Asian women, the QCT LS BMD value equivalent to the Caucasian women's threshold of 80 mg/mL is about 45∼50 mg/ml. For a data of 328 cases of Chinese men (age: 73.6 ± 4.4 years) who had QCT LS BMD and DXA LS BMD at the same time and with the DXA BMD value of ≤ 0.613 g/cm2 to classify osteoporosis, the corresponding QCT LS BMD threshold is 53 mg/ml. Osteoporotic-like vertebral fracture sum score (OLVFss) ≤ -2.5 has been proposed to diagnose osteoporosis. For 316 cases of Chinese men (age:73.7±4.5 years), OLVFss ≤ -2.5 defines an osteoporosis prevalence of 4.4%; to achieve this osteoporosis prevalence, the corresponding QCT LS BMD value is < 47.5 mg/ml. In the China Action on Spine and Hip Status study, a Genant grades 2/3 radiographic 'osteoporotic vertebral fracture' prevalence was 2.84% for Chinese men (total n = 1267, age: 62.77 ± 9.20 years); to achieve this osteoporosis prevalence, the corresponding BMD value was < 42.5 mg/ml. In a study of 357 Beijing older men, according to the clinical fragility fracture prevalence and femoral neck DXA T-score, the QCT LS BMD value to classify osteoporosis was between 39.45 mg/ml and 51.38 mg/ml. For older Chinese men (≥ 50 years), we recommend the cutpoint for the QCT LS BMD definition of osteoporosis to be 45∼50 mg/ml which is the same as the value for Chinese women.

Demystifying the Risk Factors and Preventive Measures for Osteoporosis

Background

Osteoporosis is a major health problem, globally. It is characterized by structural bone weakness leading to an increased risk of fragility fractures. These fractures commonly affect the spine, hip and wrist bones. Consequently, Osteoporosis related proximal femur and vertebral fractures represent a substantial, growing social and economic burden on healthcare systems worldwide. Indentification of the risk factors, clinical risk assessment, utilization of risk assessment tools and appropriate management that play a crucial role in reducing the burden of Osteoporosis by tackling modifiable risk factors.

Methods

This chapter explores various risk factors that are associated with Osteoporosis and provides an overview of various clinical and diagnostic risk assessment tools with a particular emphasis on evidence-based strategies for their prevention.

Conclusion

The role of emerging technologies such as Artificial Intelligence (AI) and perspectives such as newer diagnostic modalities, monitoring and surveillance approaches in prevention of risk factors in the pathogenesis of Osteoporosis is highlighted.

A diagnostic approach integrated multimodal radiomics with machine learning models based on lumbar spine CT and X-ray for osteoporosis

INTRODUCTION

The aim of this analysis is to construct a combined model that integrates radiomics, clinical risk factors, and machine learning algorithms to diagnose osteoporosis in patients and explore its potential in clinical applications.

MATERIALS AND METHODS

A retrospective analysis was conducted on 616 lumbar spine. Radiomics features were extracted from the computed tomography (CT) scans and anteroposterior and lateral X-ray images of the lumbar spine. Logistic regression (LR), support vector machine (SVM), and random forest (RF) algorithms were used to construct radiomics models. The receiver operating characteristic curve (ROC) was employed to select the best-performing model. Clinical risk factors were identified through univariate logistic regression analysis (ULRA) and multivariate logistic regression analysis (MLRA) and utilized to develop a clinical model. A combined model was then created by merging radiomics and clinical risk factors. The performance of the models was evaluated using ROC curve analysis, and the clinical value of the models was assessed using decision curve analysis (DCA).

RESULTS

A total of 4858 radiomics features were extracted. Among the radiomics models, the SVM model demonstrated the optimal diagnostic capabilities and accuracy, with an area under the curve (AUC) of 0.958 (0.9405-0.9762) in the training cohort and 0.907 (0.8648-0.9492) in the test cohort. Furthermore, the combined model exhibited an AUC of 0.959 (0.9412-0.9763) in the training cohort and 0.910 (0.8690-0.9506) in the test cohort.

CONCLUSION

The combined model displayed outstanding ability in diagnosing osteoporosis, providing a safe and efficient method for clinical decision-making.

Quantitative analysis of vertebral fat fraction and R2* in osteoporosis using IDEAL-IQ sequence

OBJECTIVE

To investigate the correlation between FF, R2* value of IDEAL-IQ sequence and bone mineral density, and to explore their application value in the osteoporosis.

METHODS

We recruited 105 women and 69 men aged over 30 years who voluntarily underwent DXA and MRI examination of lumbar spine at the same day. Participants were divided into normal, osteopenia and osteoporosis group based on T-score and BMD value of DXA examination. One-way ANOVA was adopted to compare the quantitative parameters among the three groups. Independent samples t-test was utilized to compare FF and R2* value between men and women.Pearson correlation analysis was used to research the correlation between FF, R2* value and BMD.

RESULTS

Age, height, weight, BMD and FF value were significantly different among three groups (p < 0.05). No significant difference was found in FF value between male and female group, while R2* value were significantly different. Vertebral FF was moderately negatively correlated with aBMD, especially in women (r = -0.638, p < 0.001). R2* was mildly to moderately positively correlated with aBMD in men (r = 0.350, p = 0.003), but not in women. Moreover, FF was positively correlated with age, R2* was negatively correlated with age in men, and BMD was negatively correlated with age.

CONCLUSIONS

The vertebral FF value of IDEAL-IQ sequence has the potential to be a new biological marker for the assessment of osteoporosis. Vertebral FF is moderately negatively correlated with aBMD, especially in women, allowing accuratly quantify the bone marrow fat. R2* value is mildly to moderately correlated with BMD in men and can be served as a complementary tool in the assessment of osteoporosis.