Dual-Energy CT and Cinematic Rendering to Improve Assessment of Pelvic Fracture Instability.

Background Grading of pelvic fracture instability is challenging in patients with pelvic binders. Dual-energy CT (DECT) and cinematic rendering can provide ancillary information regarding osteoligamentous integrity, but the utility of these tools remains unknown. Purpose To assess the added diagnostic value of DECT and cinematic rendering, with respect to single-energy CT (SECT), for discriminating any instability and translational instability in patients with pelvic binders. Materials and Methods In this retrospective analysis, consecutive adult patients (age ≥18 years) were stabilized with pelvic binders and scanned in dual-energy mode using a 128-section CT scanner at one level I trauma center between August 2016 and January 2019. Young-Burgess grading by orthopedists served as the reference standard. Two radiologists performed blinded consensus grading with the Young-Burgess system in three reading sessions (session 1, SECT; session 2, SECT plus DECT; session 3, SECT plus DECT and cinematic rendering). Lateral compression (LC) type 1 (LC-1) and anteroposterior compression (APC) type 1 (APC-1) injuries were considered stable; LC type 2 and APC type 2, rotationally unstable; and LC type 3, APC type 3, and vertical shear, translationally unstable. Diagnostic performance for any instability and translational instability was compared between reading sessions using the McNemar and DeLong tests. Radiologist agreement with the orthopedic reference standard was calculated with the weighted κ statistic. Results Fifty-four patients (mean age, 41 years ± 16 [SD]; 41 men) were analyzed. Diagnostic performance was greater with SECT plus DECT and cinematic rendering compared with SECT alone for any instability, with an area under the receiver operating characteristic curve (AUC) of 0.67 for SECT alone and 0.82 for SECT plus DECT and cinematic rendering (P = .04); for translational instability, the AUCs were 0.80 for SECT alone and 0.95 for SECT plus DECT and cinematic rendering (P = .01). For any instability, corresponding sensitivities were 61% (22 of 36 patients) for SECT alone and 86% (31 of 36 patients) for SECT plus DECT and cinematic rendering (P < .001). The corresponding specificities were 72% (13 of 18 patients) and 78% (14 of 18 patients), respectively (P > .99). Agreement (κ value) between radiologists and orthopedist reference standard improved from 0.44 to 0.76 for SECT versus the combination of SECT, DECT, and cinematic rendering. Conclusion Combined use of single-energy CT, dual-energy CT, and cinematic rendering improved instability assessment over that with single-energy CT alone. © RSNA, 2022 Online supplemental material is available for this article.

Targeted gene expression profiling predicts meningioma outcomes and radiotherapy responses.

Surgery is the mainstay of treatment for meningioma, the most common primary intracranial tumor, but improvements in meningioma risk stratification are needed and indications for postoperative radiotherapy are controversial. Here we develop a targeted gene expression biomarker that predicts meningioma outcomes and radiotherapy responses. Using a discovery cohort of 173 meningiomas, we developed a 34-gene expression risk score and performed clinical and analytical validation of this biomarker on independent meningiomas from 12 institutions across 3 continents (N = 1,856), including 103 meningiomas from a prospective clinical trial. The gene expression biomarker improved discrimination of outcomes compared with all other systems tested (N = 9) in the clinical validation cohort for local recurrence (5-year area under the curve (AUC) 0.81) and overall survival (5-year AUC 0.80). The increase in AUC compared with the standard of care, World Health Organization 2021 grade, was 0.11 for local recurrence (95% confidence interval 0.07 to 0.17, P < 0.001). The gene expression biomarker identified meningiomas benefiting from postoperative radiotherapy (hazard ratio 0.54, 95% confidence interval 0.37 to 0.78, P = 0.0001) and suggested postoperative management could be refined for 29.8% of patients. In sum, our results identify a targeted gene expression biomarker that improves discrimination of meningioma outcomes, including prediction of postoperative radiotherapy responses.