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PURPOSE: To improve diagnostic speed and accuracy for the detection of acute ischemic stroke utilizing colored nonenhanced head computed tomography (NECT) images. METHODS: This multi-reader prospective observational study included 100 consecutive adult patients with concern for acute ischemic stroke from 2/1/2018 to 3/17/2018 with grayscale NECT and CT angiogram (CTA) head images and a reference-standard confirmatory brain MRI. Grayscale NECT and CTA head images were collected and colored NECT head images were generated using a custom, fully automated software designed to color the intracranial contents on the head CT images and increase the conspicuity of ischemic strokes. Two randomized imaging sets were generated from each patient's CT exam, including Grayscale and Color+Grayscale images. Two radiology residents and two expert fellowship trained neuroradiologists independently assessed each imaging set, separated by at least two weeks. The mean accuracy, sensitivity, specificity, and time of assessment were compared between individual readers and between the two reader groups, in a multivariate model. RESULTS: Among the 4 readers, the mean accuracy/sensitivity/specificity for correctly diagnosing acute ischemic stroke were 72%/46%/87% using grayscale NECT images only and 69%/36%/86% using Color+Grayscale NECT images (p=0.08/p=0.006/p=0.858). The mean time of assessment with grayscale NECT images only was 59 seconds, which was decreased by an average of 19 seconds when using Color+Grayscale NECT images (p KEYWORDS: ischemic stroke, CT, color, INTRODUCTION Stroke is the 5th most common cause of death in the United States and a leading cause of serious long-term disability (CDC, 2015). Every year, more than 795,000 people [...]

Summary: To harmonise computed tomography (CT) and dual‐energy x‐ray absorptiometry (DXA) body composition measurements allowing easy conversion in longitudinal assessments and across cohorts to assess cardiometabolic risk and disease. Retrospective cross‐sectional observational study from 1996 to 2008 included participants in the Pennington Center Longitudinal Study (PCLS) (N = 1967; 571 African American/1396 White). Anthropometrics, whole‐body DXA and abdominal CT images were obtained. Multi‐layer segmentation techniques (Analyze; Rochester, MN) quantified visceral adipose tissue (VAT). Clinical biomarkers were obtained from routine blood samples. Linear models were used to predict CT‐VAT from DXA‐VAT and examine the effects of traditional biomarkers on cross‐sectional‐VAT. Predicted CT‐VAT was highly associated with measured CT‐VAT using ordinary least square linear regression analysis and random forest models (R2 = 0.84; 0.94, respectively, p <.0001). Model stratification effects showed low variability between races and sexes. Overall, associations between measured CT‐VAT and DXA‐predicted CT‐VAT were good (R2 > 0.7) or excellent (R2 > 0.8) and improved for all stratification groups except African American men using random forest models. The clinical effects on measured CT‐VAT and DXA‐VAT showed no significant clinical difference in the measured adipose tissue areas (mean difference = 0.22 cm2). Random forest modelling seamlessly predicts CT‐VAT from measured DXA‐VAT to a degree of accuracy that falls within the bounds of universally accepted standard error. [ABSTRACT FROM AUTHOR]

Object: Careful preoperative planning with thin-slice computed tomography (CT) scan is useful for hardware placement at C2. Prior studies have shown considerable variability in the proportion of C2 vertebrae considered safe for pedicle screw placement, depending on the imaging technique used. Our work sought to more carefully define that proportion using a refined imaging technique on a large number of submillimeter CT scans. Materials and Methods: We reviewed 150 submillimeter cervical spine studies randomly selected from CT scans performed at a Level 1 trauma center. OsiriX™ image analysis software was used to propagate a 5-mm cylinder through the plane of the pedicle on paracoronal reformatted CT scans. Hounsfield unit attenuation was used to determine whether the cylinder violated the pedicle. Binomial data were generated to determine the proportion of pedicles that would allow safe screw placement. Results: We analyzed 300 pedicles in 150 patients. Using a standard C2 pedicle starting point, 32% of pedicles were breached by the 5-mm diameter cylinder. When screw trajectory was adjusted by moving the cylinder to fit the pedicle isthmus, establishing an optimized starting point, only 14% of pedicles were breached. Average pedicle length was 27.3 mm for screws that would have crossed the isthmus versus 13.2 mm for screws that would have stopped short due to potential breach. Conclusions: Findings of the current work suggest that preoperative imaging analysis or navigation can be useful adjuncts when anatomical variants are present. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate precision of a software-based liver surface nodularity (LSN) score derived from CT images.Methods: An anthropomorphic CT phantom was constructed with simulated liver containing smooth and nodular segments at the surface and simulated visceral and subcutaneous fat components. The phantom was scanned multiple times on a single CT scanner with adjustment of image acquisition and reconstruction parameters (N = 34) and on 22 different CT scanners from 4 manufacturers at 12 imaging centers. LSN scores were obtained using a software-based method. Repeatability and reproducibility were evaluated by intraclass correlation (ICC) and coefficient of variation. Using abdominal CT images from 68 patients with various stages of chronic liver disease, inter-observer agreement and test-retest repeatability among 12 readers assessing LSN by software- vs. visual-based scoring methods were evaluated by ICC.Results: There was excellent repeatability of LSN scores (ICC:0.79-0.99) using the CT phantom and routine image acquisition and reconstruction parameters (kVp 100-140, mA 200-400, and auto-mA, section thickness 1.25-5.0 mm, field of view 35-50 cm, and smooth or standard kernels). There was excellent reproducibility (smooth ICC: 0.97; 95% CI 0.95, 0.99; CV: 7%; nodular ICC: 0.94; 95% CI 0.89, 0.97; CV: 8%) for LSN scores derived from CT images from 22 different scanners. Inter-observer agreement for the software-based LSN scoring method was excellent (ICC: 0.84; 95% CI 0.79, 0.88; CV: 28%) vs. good for the visual-based method (ICC: 0.61; 95% CI 0.51, 0.69; CV: 43%). Test-retest repeatability for the software-based LSN scoring method was excellent (ICC: 0.82; 95% CI 0.79, 0.84; CV: 12%).Conclusion: The software-based LSN score is a quantitative CT imaging biomarker with excellent repeatability, reproducibility, inter-observer agreement, and test-retest repeatability. [ABSTRACT FROM AUTHOR]