ACR Appropriateness Criteria® Management of Vertebral Compression Fractures: 2022 Update

Canadian Association of Radiologists Spine Imaging Referral Guideline

The Canadian Association of Radiologists (CAR) Spine Expert Panel is made up of physicians from the disciplines of radiology, emergency medicine, neurology, neurosurgery, physiatry, a patient advisor, and an epidemiologist/guideline methodologist. After developing a list of 10 clinical/diagnostic scenarios, a rapid scoping review was undertaken to identify systematically produced referral guidelines that provide recommendations for one or more of these clinical/diagnostic scenarios. Recommendations from 23 guidelines and contextualization criteria in the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) for guidelines framework were used to develop 22 recommendation statements across the 8 scenarios (one scenario points to the CAR Trauma Referral Guideline and one scenario points to the CAR Musculoskeletal Guideline). This guideline presents the methods of development and the referral recommendations for myelopathy, suspected spinal infection, possible atlanto-axial instability (non-traumatic), axial pain (non-traumatic), radicular pain (non-traumatic), cauda equina syndrome, suspected spinal tumour, and suspected compression fracture. Spondyloarthropathies and spine trauma point to other CAR Diagnostic Imaging Referral Guidelines, Musculoskeletal and Trauma, respectively.

Integrating manual annotation with deep transfer learning and radiomics for vertebral fracture analysis

BACKGROUND

Vertebral compression fractures (VCFs) are prevalent in the elderly, often caused by osteoporosis or trauma. Differentiating acute from chronic VCFs is vital for treatment planning, but MRI, the gold standard, is inaccessible for some. However, CT, a more accessible alternative, lacks precision. This study aimed to enhance CT's diagnostic accuracy for VCFs using deep transfer learning (DTL) and radiomics.

METHODS

We retrospectively analyzed 218 VCF patients scanned with CT and MRI within 3 days from Oct 2022 to Feb 2024. MRI categorized VCFs. 3D regions of interest (ROIs) from CT scans underwent feature extraction and DTL modeling. Receiver operating characteristic (ROC) analysis evaluated models, with the best fused with radiomic features via LASSO. AUCs compared via Delong test, and clinical utility assessed by decision curve analysis (DCA).

RESULTS

Patients were split into training (175) and test (43) sets. Traditional radiomics with LR yielded AUCs of 0.973 (training) and 0.869 (test). Optimal DTL modeling improved to 0.992 (training) and 0.941 (test). Feature fusion further boosted AUCs to 1.000 (training) and 0.964 (test). DCA validated its clinical significance.

CONCLUSION

The feature fusion model enhances the differential diagnosis of acute and chronic VCFs, outperforming single-model approaches and offering a valuable decision-support tool for patients unable to undergo spinal MRI.

Predicting residual pain after vertebral augmentation in vertebral compression fractures: a systematic review and critical appraisal of risk prediction models

BACKGROUND

Patients with vertebral compression fractures may experience unpredictable residual pain following vertebral augmentation. Clinical prediction models have shown potential for early prevention and intervention of such residual pain. However, studies focusing on the quality and accuracy of these prediction models are lacking. Therefore, we systematically reviewed and critically evaluated prediction models for residual pain following vertebral augmentation.

METHODS

We systematically searched eight databases (PubMed, Embase, Web of Science, CNKI, WanFang, VIP, and SinoMed) for studies that developed and/or validated risk prediction models for residual pain after vertebral augmentation. The limitations of existing models were critically assessed using the PROBAST tool. We performed a descriptive analysis of the models' characteristics and predictors. Extracted C-statistics were combined using a weighted approach based on the Restricted Maximum Likelihood (REML) method to represent the models' average performance. All statistical analyses were performed using R 4.3.1 and STATA 17 software.

RESULTS

Fifteen models were evaluated, involving 4802 patients with vertebral compression fractures post-vertebral augmentation. The overall pooled C-statistic was 0.87, with a 95% CI of 0.83 to 0.89 and a prediction interval ranging from 0.72 to 0.94. The models included 35 different predictors, with posterior fascia injury (PFI), bone mineral density (BMD), and intravertebral vacuum cleft (IVC) being the most common. Most models were rated high risk due to concerns about population selection and modeling methodology, yet their clinical applicability remains promising.

CONCLUSION

The development and validation of current models exhibit a certain risk of bias, and our study highlights these existing flaws and limitations. Although these models demonstrate satisfactory predictive performance and clinical applicability, further external validation is needed to confirm their accuracy in clinical practice. Clinicians can utilize these models alongside relevant risk factors to predict and prevent residual pain after vertebral augmentation, or to formulate personalized treatment plans.

ACR Appropriateness Criteria® Thoracic Back Pain

Thoracic back pain is a common site for inflammatory, neoplastic, metabolic, infectious, and degenerative conditions, and may be associated with significant disability and morbidity. Uncomplicated acute thoracic back pain and/or radiculopathy does not typically warrant imaging. Imaging may be considered in those patients who have persistent pain despite 6 weeks of conservative treatment. Early imaging may also be warranted in patients presenting with "red flag" history or symptoms, including those with a known or suspected history of cancer, infection, immunosuppression, or trauma; in myelopathic patients; or in those with a history of prior thoracic spine fusion. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Radiomics Based on Multimodal magnetic resonance imaging for the Differential Diagnosis of Benign and Malignant Vertebral Compression Fractures

OBJECTIVES

Recent studies have indicated that radiomics may have excellent performance and clinical application prospects in the differential diagnosis of benign and malignant vertebral compression fractures (VCFs). However, multimodal magnetic resonance imaging (MRI)-based radiomics model is rarely used in the differential diagnosis of benign and malignant VCFs, and is limited to lumbar. Herein, this study intends to develop and validate MRI radiomics models for differential diagnoses of benign and malignant VCFs in patients.

METHODS

This cross-sectional study involved 151 adult patients diagnosed with VCF in The First Affiliated Hospital of Soochow University in 2016-2021. The study was conducted in three steps: (i) the original MRI images were segmented, and the region of interest (ROI) was marked out; (ii) among the extracted features, those features with Pearson's correlation coefficient lower than 0.9 and the top 15 with the highest variance and Lasso regression coefficient less than and more than 0 were selected; (iii) MRI images and combined data were studied by logistic regression, decision tree, random forest and extreme gradient boosting (XGBoost) models in training set and the test set (ratio of 8:2), respectively; and the models were further verified and evaluated for the differential diagnosis performance. The evaluated indexes included area under receiver (AUC) of operating characteristic curve, accuracy, sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and 95% confidence intervals (CIs). The AUCs were used to assess the predictive performance of different machine learning modes for benign and malignant VCFs.

RESULTS

A total of 1144 radiomics features, and 14 clinical features were extracted. Finally, 12 radiomics features were included in the radiomics model, and 12 radiomics features with 14 clinical features were included in the combined model. In the radiomics model, the differential diagnosis performance in the logistic regression model with the AUC of 0.905 ± 0.026, accuracy of 0.817 ± 0.057, sensitivity of 0.831 ± 0.065, and negative predictive value of 0.813 ± 0.042, was superior to the other three. In the combined model, XGBoost model had the superior differential diagnosis performance with specificity (0.979 ± 0.026) and positive predictive value (0.971 ± 0.035).

CONCLUSION

The multimodal MRI-based radiomics model performed well in the differential diagnosis of benign and malignant VCFs, which may provide a tool for clinicians to differentially diagnose VCFs.

[Translated article] Diagnostic imaging in patients with vertebral compression fractures

Vertebral compression fractures by osteoporosis (OVF) is usually a diagnostic problem and coincides on the age group of metastatic vertebral compression fractures (MVF). Although radiography is the first diagnostic technique, generally is not accurate for depicting demineralization and soft tissue lesions. Magnetic resonance (MRI) is the diagnostic choice. The most relevant signs are intravertebral fluid collection or fluid signal, other vertebral deformities without oedema and older age. Among the most relevant findings for diagnosis MVF are soft tissue mass and pedicle intensity signal asymmetries. However, reproducibility of these findings in clinical practice is moderate.

Diagnostic imaging in patients with vertebral compression fractures

Vertebral compression fractures by osteoporosis (OVF) is usually a diagnostic problem and coincides on the age group of metastatic vertebral compression fractures (MVF). Although radiography is the first diagnostic technique, generally is not accurate for depicting demineralization and soft tissue lesions. Magnetic resonance (MRI) is the diagnostic choice. The most relevant signs are Intravertebral fluid collection or fluid signal, other vertebral deformities without edema and older age. Among the most relevant findings for diagnosis MVF are soft tissue mass and pedicle intensity signal asymmetries. However, reproducibility of these findings in clinical practice is moderate.

Thoracic Pyogenic Spondylitis Misdiagnosed As Osteoporotic Compression Fracture Status Post Vertebral Augmentation With Resultant Paraplegia: A Case Report

This paper describes a case of serious complications following vertebral augmentation resulting from a misdiagnosis of pyogenic spondylitis as osteoporotic compression fracture (OCF). A 56-year-old female with systemic lupus erythematosus underwent vertebral augmentation following a diagnosis of T10 OCF based on plain film analysis. Note that preoperative computed tomography (CT) and magnetic resonance imaging (MRI) were not performed. One day after vertebral augmentation, the patient experienced a recurrence of low back pain with fever and paraplegia. MRI findings revealed paravertebral and epidural soft tissue over T9 and T10 with cord compression. Subsequent laminectomy of T9 and T10 revealed devitalized lamina, epidural abscess, and granulation tissue. Pathological analysis indicated a combination of acute and chronic inflammation. A pus culture identified Staphylococcus aureus, indicative of pre-existing pyogenic spondylitis. Further revision surgery was performed at another hospital. The patient remained in a paraplegic state one year after surgery. Infectious spondylitis often manifests with nonspecific symptoms similar to those of compression fracture, and plain radiographs are insufficient to differentiate between the two, often leading to misdiagnosis and mistreatment. Nonetheless, many practitioners base preoperative planning solely on plain film imaging. We advocate the routine usage of CT and/or MRI for patients diagnosed with compression fractures, particularly for immunocompromised individuals.

Can TBS reference values be a valid indicator for clinical vertebral fracture? A cross-sectional study

INTRODUCTION

Trabecular bone score (TBS) is partially independent of fracture risk. Reference values for TBS have not been established in official guidelines, and thus clinicians often have difficulty interpreting TBS results. This study aimed to investigate whether reference values for TBS could be a valid indicator for clinical vertebral fracture (CVF).

MATERIALS AND METHODS

This cross-sectional study involved 231 women with CVF and 563 women without CVF aged 60-90 years who underwent dual-energy X-ray absorptiometry during 2019-2023. They were divided into osteoporosis, osteopenia, and normal groups according to bone mineral density of the lumbar spine. Reference values for TBS were defined as low (≤ 1.23), intermediate (1.23-1.31), and high (≥ 1.31).

RESULTS

Among patients without anti-osteoporosis treatment (n = 476), the proportion with low TBS was 36.7% in the CVF group and 10.7% in the control group. The proportion with CVF was higher in the low TBS group than in the intermediate and high TBS groups, especially in the osteoporosis group (p < 0.001). The odds ratio for CVF was higher in the low TBS group than in the intermediate and high especially in patients with normal BMD and osteoporosis. The TBS cut-off values for incidence of CVF in the osteoporosis, osteopenia, and normal groups were 1.224, 1.319, and 1.322, respectively.

CONCLUSIONS

The reference value for low TBS (≤ 1.23) was useful as an indicator for CVF, especially in patients with osteoporosis. It is expected that reference values for TBS will be established in official guidelines in the future.