Discrimination of osteoporosis-related vertebral fractures by DXA-derived 3D measurements: a retrospective case-control study

Conventional chest computed tomography-based radiomics for predicting the risk of thoracolumbar osteoporotic vertebral fractures

Our study focused on predicting thoracolumbar osteoporotic vertebral fractures through radiomic analysis of non-fractured thoracic vertebrae using conventional chest CT. Four types of radiomics models were developed and showed acceptable prediction performance. Radiomics models incorporating both cortical-appendicular and trabecular bone may have superior performance compared to those using either feature set individually. The RAD score models based on thoracic vertebral combinations achieved comparable performance with lumbar bone mineral density (BMD) measurements.

PURPOSE

To develop and validate radiomics models based on chest CT for predicting the risk of thoracolumbar osteoporotic vertebral fractures (OVFs).

METHODS

A total of 494 patients (including 198 patients with thoracolumbar OVFs) who underwent conventional chest CT scans were included in this retrospective analysis and were divided into training set 1 (n = 334) and validation set 1 (n = 160). Radiomics features (RFs) were extracted from each thoracic vertebral level on chest CT images. Four types of radiomics models (trabecular RFs, cortical-appendicular RFs, mixed RFs, and RAD score) were constructed and compared. Additionally, RAD score models based on trabecular and cortical-appendicular bone of different vertebral combinations (T1-T6, T7-T12, and top 3 vertebrae) were performed, respectively. A subset of patients with available bone mineral density (BMD) data formed training set 2 (n = 199) and validation set 2 (n = 88). We combined RAD score of different vertebral combinations with lumbar BMD for predicting thoracolumbar OVFs, and further adjusted for age. Predictive performance was evaluated using the area under the receiver operating characteristic curve (AUC).

RESULTS

Among the radiomics models, the RAD score model based on trabecular and cortical-appendicular bone achieved highest AUC at the most vertebral levels. The RAD score model of top 3 (T5 + T8 + T10) vertebrae achieved higher AUC (0.813) than T7-T12 (AUC = 0.780) with a statistically significant difference (P = 0.02) and T1-T6 (AUC = 0.772) without a statistically significant difference (P = 0.062). Prior to adjusting for age, both RAD score models (AUCs 0.774-0.807) and RAD score + BMD models (AUCs 0.771-0.800) demonstrated slightly superior performance compared to BMD (AUC = 0.736) alone in predicting OVFs, although the differences were not statistically significant (P > 0.05). Following adjustment for age, our RAD score models, which utilized different vertebral combinations (AUCs 0.784-0.804), were found to be comparable to lumbar BMD (AUC = 0.785) in predicting OVFs (P > 0.05).

CONCLUSION

Radiomics analysis based on conventional chest CT can provide valuable information for predicting thoracolumbar OVFs. Radiomics models incorporating both cortical-appendicular and trabecular bone may have superior performance compared to those using either feature set alone. RAD score models based on thoracic vertebral combinations comparable performance compared to lumbar BMD highlights its clinical utility.

Computer-aided diagnosis for China-Japan Friendship Hospital classification of necrotic femurs using statistical shape and appearance model based on CT scans

The purpose of this study is to quantify the three-dimensional (3D) structural morphology, bone mineral density (BMD) distribution, and mechanical properties of different China-Japan Friendship Hospital (CJFH) classification types and assist clinicians in classifying necrotic femurs accurately. In this study, 41 cases were classified as types L2 and L3 based on CT images. Then, 3D Statistical Shape and Appearance Models (SSM and SAM) were established, and 80 principal component (PC) modes were extracted from the SSM and SAM as the candidate features. The bone strength of each case was also calculated as the candidate feature using finite element analysis (FEA). Support vector machine (SVM) and Extreme Gradient Boosting (XGBoost) were used to establish 10 machine learning models. Feature selection methods were used to screen the candidate features. The performance of each model was evaluated based on sensitivity, specificity, accuracy, and the area under the receiver operating characteristic (ROC) curve. This resulted in a SVM model for CJFH classification with the performance: accuracy of 87.5%, sensitivity of 85.0%, specificity of 76.0%, and AUC of 94.2%. This study provided effective machine learning models for assisting in diagnosing CJFH types, increasing the objectivity of the diagnosis. They may have great potential for application in clinical assessments of CJFH classification.

Comparative effectiveness of four techniques for identifying vertebral fragility fractures among elderly patients

OBJECTIVE

The incidence of vertebral fragile fractures peaked among the elderly population, and identifying individuals at high risk of vertebral fractures and promptly instituting preventions are of critical importance. This study aims to determine the efficacy and values of Hounsfield unit (HU) values, vertebral bone quality (VBQ) scores, bone mineral density (BMD) measured by dual-energy X-ray absorptiometry (DXA), and quantitative computed tomography (QCT) to discriminate between patients with and without vertebral fractures.

METHODS

A thorough search was conducted across PubMed, EMBASE, Cochrane Library, Web of Science, CNKI, and Wan Fang Database to identify potential studies that met the eligibility criteria. Studies that evaluated the utility of HU values, VBQ scores, QCT-measured BMD, and DXA-measured BMD in discriminating vertebral fractures were qualified.

RESULTS

The combined results showed that there were significant differences in HU values, VBQ scores, QCT-measured BMD, and DXA-measured BMD between the fracture and non-fracture groups. Moreover, the pooled sensitivity, specificity, and AUC of HU values were 0.82, 0.67, and 0.76, respectively; the pooled sensitivity, specificity, and AUC of VBQ scores were 0.70, 0.75, and 0.78; the pooled sensitivity, specificity, and AUC of QCT-measured BMD were 0.85, 0.76 and 0.88.

CONCLUSION

All four methods, namely HU values, VBQ scores, QCT-measured BMD, and DXA-measured BMD can effectively distinguish between patients with and without vertebral fragile fractures. Among these, QCT-measured BMD exhibited a relatively high efficacy in discriminating vertebral fractures. VBQ scores and HU values demonstrated comparable efficacy for discriminating vertebral fractures among elderly patients.

KEY POINTS

Question Can four different imaging modalities effectively discriminate vertebral fragility fracture status among elderly patients? Findings These methods can effectively distinguish vertebral fractures status among elderly patients, and quantitative computed tomography (QCT)-measured bone mineral density (BMD) exhibited a relatively high efficacy. Clinical relevance The clinical applications of Hounsfield unit values, vertebral bone quality scores, and BMD measured by dual-energy X-ray absorptiometry and QCT show promising outcomes in identifying individuals at high risk of vertebral fractures.

MRI-based vertebral bone quality score effectively reflects bone quality in patients with osteoporotic vertebral compressive fractures

OBJECTIVE

The present study is aimed to validate the ability of the vertebral bone quality (VBQ) score to evaluate bone quality in patients with osteoporotic vertebral compression fractures (OVCF) and to compare it with the ability of T-score by DXA. In addition, the sensitivity of VBQ score with cerebrospinal fluid (CSF) of L2 and L3 segments as baseline is evaluated.

METHODS

196 inpatients were collected and assigned into OVCF and Non-OVCF groups, respectively. For each patient, the VBQ score was calculated by the signal intensity of the L1-L4 vertebral bodies and CSF at L3 or L2 level from T1-weighted MRIs, while T-score from DXA was also obtained. The VBQ and T-score was compared between OVCF and non-OVCF groups, and among age groups. The OVCF ORs by VBQ score and T-score were calculated using logistic regression.

RESULTS

OVCF group was significantly different to the non-OVCF group in the T-score (- 2.9 vs. - 0.7) and VBQ score (4.0 vs. 3.5). VBQ score and T-score in patient aged 60-79 years old could indicate the bone quality, but only T-score in patients aged 50-59 years old. OVCF are associated with both higher VBQ score and lower T-score. The VBQ scores calculated by L2 CSF and L3 CSF were similar.

CONCLUSIONS

The VBQ score is an effective indicator of bone quality in OVCF patients and comparable to T-score, particularly in people over 60 years old. The VBQ score is not sensitive to CSF of different segments as a baseline.

Statistical Shape and Appearance Models: Development Towards Improved Osteoporosis Care

PURPOSE OF REVIEW

Statistical models of shape and appearance have increased their popularity since the 1990s and are today highly prevalent in the field of medical image analysis. In this article, we review the recent literature about how statistical models have been applied in the context of osteoporosis and fracture risk estimation.

RECENT FINDINGS

Recent developments have increased their ability to accurately segment bones, as well as to perform 3D reconstruction and classify bone anatomies, all features of high interest in the field of osteoporosis and fragility fractures diagnosis, prevention, and treatment. An increasing number of studies used statistical models to estimate fracture risk in retrospective case-control cohorts, which is a promising step towards future clinical application. All the reviewed application areas made considerable steps forward in the past 5-6 years. Heterogeneities in validation hinder a thorough comparison between the different methods and represent one of the future challenges to be addressed to reach clinical implementation.

Cytokines CCL2 and CXCL1 may be potential novel predictors of early bone loss

Osteoporosis is a common disorder characterized by decreased bone mineral density (BMD) and increased fracture risk. The current techniques detect real-time BMD precisely but do not provide adequate information to predict early bone loss. If bone loss could be diagnosed and predicted early, severe osteoporosis and unexpected fractures could be prevented, allowing for an improved quality of life for individuals. In the present study, an ovariectomized rat model of bone loss was established and the serum levels of 78 potential cytokines were determined using a protein array. The BMD of ovariectomized rats was dynamically measured by micro-CT and the early stage of bone loss was defined at the fourth week after surgery. The expression of several serum protein cytokines was indicated to be altered in the ovariectomized rats during an 8-week time-course of bone loss. Linear regression analysis revealed that the serum levels of C-C motif chemokine ligand 2 (CCL2, also known as monocyte chemoattractant protein 1) and C-X-C motif chemokine ligand 1 (CXCL1) were significantly associated with a reduction in BMD. The significance of these two factors in indicating bone mass reduction was further verified by analyzing serum samples from 24 patients with BMD using ELISA and performing a linear regression analysis. The serum levels of CCL2 and CXCL1 were inversely correlated with the bone mass. Therefore, the cytokines CCL2 and CXCL1 may be potential novel predictors of early bone loss and may be clinically relevant for the early diagnosis and prevention of osteoporosis.

New technologies in the evaluation of bone fragility and its application in Endocrinology

Bone mineral density using dual-energy X-ray absorptiometry is the gold standard for the assessment of bone and an important predictor of fracture risk. However, most fragility fractures occur in people without densitometric osteoporosis, especially in endocrinological diseases. Fracture risk estimation tools such as FRAX have improved diagnostic sensitivity but do not include additional skeletal features. Bone microarchitecture research represents an improvement in the treatment of these patients. In this document members of the Mineral and Bone Metabolism Working Group of the Spanish Society of Endocrinology and Nutrition review new advances in dual-energy X-ray absorptiometry and other complex techniques for the study of bone microarchitecture as well as the available data on type 2 diabetes and parathyroid pathology.

Association between osteoporotic femoral neck fractures and DXA-derived 3D measurements at lumbar spine: a case-control study

A case-control study assessing the association of DXA-derived 3D measurements at lumbar spine with osteoporotic hip fractures was performed. Stronger association was found between transcervical hip fractures and integral (AUC = 0.726), and cortical (AUC = 0.696) measurements at the lumbar spine compared with measurements at the trabecular bone (AUC = 0.617); although femur areal bone mineral density (aBMD) remains the referent measurement for hip fracture risk evaluation (AUC = 0.838).

PURPOSE

The aim of the present study was to evaluate the association between DXA-derived 3D measurements at lumbar spine and osteoporotic hip fractures.

METHODS

We analyzed a case-control database composed by 61 women with transcervical hip fractures and 61 age-matched women without any type of fracture. DXA scans at lumbar spine were acquired, and areal bone mineral density (aBMD) was measured. Integral, trabecular and cortical volumetric BMD (vBMD), cortical thickness, and cortical surface BMD (sBMD) at different regions of interest were assessed using a DXA-based 3D modeling software. Descriptive statistics, tests of difference, odds ratio (OR), and area under the receiver operating curve (AUC) were used to compare hip fracture and control groups.

RESULTS

Integral vBMD, cortical vBMD, cortical sBMD, and cortical thickness were the DXA-derived 3D measurements at lumbar spine that showed the stronger association with transcervical hip fractures, with AUCs in the range of 0.685-0.726, against 0.670 for aBMD. The highest AUC (0.726) and OR (2.610) at the lumbar spine were found for integral vBMD at the posterior vertebral elements. Significantly, lower AUC (0.617) and OR (1.607) were found for trabecular vBMD at the vertebral body. Overall, total femur aBMD remains the DXA-derived measurement showing the highest AUC (0.838) and OR (6.240).

CONCLUSION

This study showed the association of DXA-derived measurements at lumbar spine with transcervical hip fractures. A strong association between vBMD at the posterior vertebral elements and transcervical hip fractures was observed, probably because of global deterioration of the cortical bone. Further studies should be carried out to investigate on the relative risk of transcervical fracture in patients with long-term cortical structural deterioration.