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BACKGROUND Gout, caused by hyperuricemia and subsequent deposition of aggregated monosodium urate crystals (MSU) in the joints or extra-articular regions, is the most common inflammatory arthritis. There is increasing evidence that gout is an independent risk factor for hypertension, cardiovascular disease progression and mortality. AIM To evaluate if dual energy computed tomography (DECT) could identify MSU within vessel walls of gout patients, and if MSU deposits within the vasculature differed between patients with gout and controls. This study may help elucidate why individuals with gout have increased risk for cardiovascular disease. METHODS 31 gout patients and 18 controls underwent DECT scans of the chest and abdomen. A material decomposition algorithm was used to distinguish regions of MSU (coded green), and calcifications (coded purple) from soft tissue (uncoded). Volume of green regions was calculated using a semi-automated volume assessment program. Between-group differences were analyzed using Mann-Whitney U exact test and nonparametric rank regression. RESULTS Gout patients had significantly higher volume of MSU within the aorta compared to controls [Median (Min-Max) of 43.9 (0-1113.5) vs 2.9 (0-219.4), P = 0.01]. Number of deposits was higher in gout patients compared to controls [Median (Min-Max) of 20 (0-739) vs 1.5 (0-104), P = 0.008]. However, the difference was insignificant after adjustment for age, gender, history of cardiovascular disease and diabetes. Increased age was positively associated with total urate volume (rs = 0.64; 95% confidence interval: 0.43-0.78). CONCLUSION This pilot study showed that DECT can quantify vascular urate deposits with variation across groups, with gout patients possibly having higher deposition. This relationship disappeared when adjusted for age, and there was a positive relationship between age and MSU deposition. While this study does not prove that green coded regions are truly MSU deposition, it corroborates recent studies that show the presence of vascular deposition.

AIM To evaluate reproducibility of pulmonary embolism (PE) clot volume quantification using computed tomography pulmonary angiogram (CTPA) in a multicenter setting. METHODS This study was performed using anonymized data in conformance with HIPAA and IRB Regulations (March 2015-November 2016). Anonymized CTPA data was acquired from 23 scanners from 18 imaging centers using each site’s standard PE protocol. Two independent analysts measured PE volumes using a semi-automated region-growing algorithm on an FDA-approved image analysis platform. Total thrombus volume (TTV) was calculated per patient as the primary endpoint. Secondary endpoints were individual thrombus volume (ITV), Qanadli score and modified Qanadli score per patient. Inter- and intra-observer reproducibility were assessed using intra-class correlation coefficient (ICC) and Bland-Altman analysis. RESULTS Analyst 1 found 72 emboli in the 23 patients with a mean number of emboli of 3.13 per patient with a range of 0-11 emboli per patient. The clot volumes ranged from 0.0041 - 47.34 cm3 (mean +/- SD, 5.93 +/- 10.15cm3). On the second read, analyst 1 found the same number and distribution of emboli with a range of volumes for read 2 from 0.0041 – 45.52 cm3 (mean +/- SD, 5.42 +/- 9.53cm3). Analyst 2 found 73 emboli in the 23 patients with a mean number of emboli of 3.17 per patient with a range of 0-11 emboli per patient. The clot volumes ranged from 0.00459-46.29 cm3 (mean +/- SD, 5.91 +/- 10.06 cm3). Inter- and intra-observer variability measurements indicated excellent reproducibility of the semi-automated method for quantifying PE volume burden. ICC for all endpoints was greater than 0.95 for inter- and intra-observer analysis. Bland-Altman analysis indicated no significant biases. CONCLUSION Semi-automated region growing algorithm for quantifying PE is reproducible using data from multiple scanners and is a suitable method for image analysis in multicenter clinical trials.

AIM To examine effects of computed tomography (CT) image acquisition/reconstruction parameters on clot volume quantification in vitro for research method validation purposes. METHODS This study was performed in conformance with HIPAA and IRB Regulations (March 2015-November 2016). A ten blood clot phantom was designed and scanned on a dual-energy CT scanner (SOMATOM Force, Siemens Healthcare GmBH, Erlangen, Germany) with varying pitch, iterative reconstruction, energy level and slice thickness. A range of clot and tube sizes were used in an attempt to replicate in vivo emboli found within central and segmental branches of the pulmonary arteries in patients with pulmonary emboli. Clot volume was the measured parameter and was analyzed by a single image analyst using a semi-automated region growing algorithm implemented in the FDA-approved Siemens syngo.via image analysis platform. Mixed model analysis was performed on the data. RESULTS On the acquisition side, the continuous factor of energy showed no statistically significant effect on absolute clot volume quantification (P = 0.9898). On the other hand, when considering the fixed factor of pitch, there were statistically significant differences in clot volume quantification (P < 0.0001). On the reconstruction side, with the continuous factor of reconstruction slice thickness no statistically significant effect on absolute clot volume quantification was demonstrated (P = 0.4500). Also on the reconstruction side, with the fixed factor of using iterative reconstructions there was also no statistically significant effect on absolute clot volume quantification (P = 0.3011). In addition, there was excellent R2 correlation between the scale-measured mass of the clots both with respect to the CT measured volumes and with respect to volumes measure by the water displacement method. CONCLUSION Aside from varying pitch, changing CT acquisition parameters and using iterative reconstructions had no significant impact on clot volume quantification with a semi-automated region growing algorithm.