Imaging the Spine with Dual-Energy CT

CT-based radiomics can identify physiological modifications of bone structure related to subjects' age and sex

PURPOSE

Radiomics of vertebral bone structure is a promising technique for identification of osteoporosis. We aimed at assessing the accuracy of machine learning in identifying physiological changes related to subjects' sex and age through analysis of radiomics features from CT images of lumbar vertebrae, and define its generalizability across different scanners.

MATERIALS AND METHODS

We annotated spherical volumes-of-interest (VOIs) in the center of the vertebral body for each lumbar vertebra in 233 subjects who had undergone lumbar CT for back pain on 3 different scanners, and we evaluated radiomics features from each VOI. Subjects with history of bone metabolism disorders, cancer, and vertebral fractures were excluded. We performed machine learning classification and regression models to identify subjects' sex and age respectively, and we computed a voting model which combined predictions.

RESULTS

The model was trained on 173 subjects and tested on an internal validation dataset of 60. Radiomics was able to identify subjects' sex within single CT scanner (ROC AUC: up to 0.9714), with lower performance on the combined dataset of the 3 scanners (ROC AUC: 0.5545). Higher consistency among different scanners was found in identification of subjects' age (R2 0.568 on all scanners, MAD 7.232 years), with highest results on a single CT scanner (R2 0.667, MAD 3.296 years).

CONCLUSION

Radiomics features are able to extract biometric data from lumbar trabecular bone, and determine bone modifications related to subjects' sex and age with great accuracy. However, acquisition from different CT scanners reduces the accuracy of the analysis.

Dual Energy Computed Tomography Collagen Material Decomposition for Detection of Lumbar Spine Disc Extrusion and Sequestration: A Comparative Study With Greyscale Computed Tomography

Purpose: To assess value of dual energy computed tomography (DECT) collagen material decomposition algorithm when combined with standard computed tomography (CT) in detection of lumbar disc extrusion and sequestration. Materials and Methods: Retrospective analysis of all patients with acute low back pain who had a diagnosis of lumbar spine disc extrusion and/or sequestration on Magnetic Resonance Imaging (MRI) (reference standard), and had undergone non-contrast DECT of the lumbar spine within 60 days of the MRI. Age and sex-matched control patients (n = 42) were included. Patients were grouped into standard, grey-scale CT only group and standard CT + DECT tendon images group. Two double-blinded radiologists reviewed both groups for presence of extrusion or sequestration. They also rated their diagnostic confidence on Likert 5-point scale. McNemar Chi-square test was used to compare diagnostic accuracy, unpaired t-test to compare reviewers diagnostic confidence, and Cohen's k (kappa) test for interobserver agreement. Results: The combined group showed higher overall sensitivity (96.6% vs 87.2%), specificity (99% vs 95.4%), and diagnostic accuracy (98.7% vs 94.5%) with a lower false positive rate (1.1% vs 4.6%). McNemar Chi-square test confirmed statistical significance (P = .03 and P = .02 for Reviewers R1 and R2, respectively). The mean diagnostic confidence was also significantly higher on combined group (R1: 3.74 ± 1.1 vs 3.47 ± 1.15 (P < .01) and R2: 3.91 ± 1.15 vs 3.72 ± 1.16 [mean ± SD] (P = .02)). Conclusion: Utilizing MRI as a reference standard, DECT tendon application combined with standard CT increases the sensitivity, specificity, and accuracy of detection of lumbar spine disc extrusion and sequestration, when compared to standard CT alone.

Quantification of bone marrow edema using dual-energy CT at fracture sites in trauma

PURPOSE

The purpose of our study was to analyze the change in water and fat density within the bone marrow using the GE Revolution dual-energy computed tomography (DECT) platform using two-material decomposition analyses at extremity, spine, and pelvic fracture sites compared to normal bone marrow at equivalent anatomic sites in adult patients who sustained blunt trauma.

METHODS

This retrospective study included 26 consecutive adults who sustained blunt torso trauma and an acute fracture of the thoracolumbar vertebral body, pelvis, or upper and lower extremities with a total of 32 fractures evaluated. Two-material decomposition images were analyzed for quantitative analysis. Statistical analysis was performed using the paired t-test and Shapiro-Wilk test for normality.

RESULTS

There were statistically significant differences in the water and fat densities in the bone marrow at the site of an extremity, vertebral body, or pelvic fracture when compared to the normal anatomic equivalent (p < 0.01).

CONCLUSION

In this preliminary study, DECT basis material images, using water (calcium) and fat (calcium) decomposition illustrated significant differences in water and fat content between fracture sites and normal bone in a variety of anatomical sites.

Diagnostic performance of dual-energy computed tomography for detection of acute spinal fractures

OBJECTIVE

To assess the diagnostic performance of dual-energy computed tomography (DECT) with the color-coded virtual non-calcium (VNC) technique for detecting acute fractures in patients after acute spine trauma, especially in an emergency clinical setting.

MATERIALS AND METHODS

Our retrospective study included 31 patients presented to emergency department with suspected spine trauma. All patients underwent both DECT (80 kVp and 140 kVp) and MRI. Post-processing was performed using color-coded VNC technique. Two independent radiologists visually assessed color-coded VNC images in a random order, and one of the two readers re-assessed the images in 4 weeks after the initial assessment. They were allowed to read only color-coded VNC images and asked to determine the presence of acute fracture. To determine the standard reference point, the other two experienced radiologists made consensus readings on both grayscale CT and MRI. Sensitivity, specificity, PPV, NPV, and accuracy analyses were determined. Both intra- and inter-observer agreements were also calculated.

RESULTS

A total of 217 vertebral bodies (65 thoracic and 152 lumbar vertebrae) were included in our study. Sensitivity was 83.3% and 76.7% for first and second readers, respectively. Specificity of 99.5% and 98.9%, PPV of 96.1% and 96.3%, NPV of 97.3% and 96.3%, and accuracy of 97.2% and 95.8%, respectively, were noted. Both intra-observer and inter-observer agreements indicated excellent agreement (κ = 0.86 and κ = 0.84, respectively).

CONCLUSION

In spite of the relatively low sensitivity, DECT-based detection of acute spinal fractures showed good specificity, positive predictive value, negative predictive value, accuracy, and inter-/intra-observer agreements.