Coronary artery fistulas (CAFs) are abnormal communications of coronary arteries whereby venous circuits bypass the normal capillaries within the myocardium. CAFs are rare, and most affected patients are asymptomatic. However, these fistulas are the most common coronary artery anomalies that can alter coronary hemodynamic parameters. Although most CAFs are asymptomatic in young patients, symptoms and complications become more frequent with increasing age. CAFs are characterized by variable clinical manifestations that are based on the size, origin, and drainage site of the fistula. In symptomatic cases, surgical ligation or percutaneous transcatheter closure is often recommended. Although CAFs historically have been evaluated with conventional invasive angiography, electrocardiographically gated cardiac computed tomographic (CT) angiography has emerged as the noninvasive alternative modality of choice owing to the high spatial and temporal resolution and short acquisition time. Furthermore, three-dimensional volume-rendered CT angiograms facilitate accurate assessment of the complex anatomy of CAFs, including their origin, drainage site, and complexity and the number and size of fistulous tracts. Knowledge of these characteristics is crucial for therapeutic planning. Radiologists must be aware of the pathophysiology, clinical manifestations, and characteristic CT angiographic findings of CAFs; appropriate CT angiographic protocols for evaluation of various CAFs; and the role of CT angiography in preprocedural planning and follow-up. Online supplemental material is available for this article. RSNA, 2018.

The value of image based texture features as a powerful method to predict prognosis and assist clinical management in cancer patients has been established recently. However, texture analysis using histograms and grey-level co-occurrence matrix in pancreas cancer patients has rarely been reported. We aimed to analyze the association of survival outcomes with texture features in pancreas head cancer patients. Eighty-eight pancreas head cancer patients who underwent preoperative CT images followed by curative resection were included. Texture features using different filter values were obtained. The texture features of average, contrast, correlation, and standard deviation with no filter, and fine to medium filter values as well as the presence of nodal metastasis were significantly different between the recurred (n = 70, 79.5%) and non-recurred group (n = 18, 20.5%). In the multivariate Cox regression analysis, lower standard deviation and contrast and higher correlation with lower average value representing homogenous texture were significantly associated with poorer DFS (disease free survival), along with the presence of lymph node metastasis. Texture parameters from routinely performed pre-operative CT images could be used as an independent imaging tool for predicting the prognosis in pancreas head cancer patients who underwent curative resection.

PurposeTo retrospectively investigate whether texture features obtained from preoperative CT images of advanced gastric cancer (AGC) patients could be used for the prediction of occult peritoneal carcinomatosis (PC) detected during operation.Materials and methods51 AGC patients with occult PC detected during operation from January 2009 to December 2012 were included as occult PC group. For the control group, other 51 AGC patients without evidence of distant metastasis including PC, and whose clinical T and N stage could be matched to those of the patients of the occult PC group, were selected from the period of January 2011 to July 2012. Each group was divided into test (n = 41) and validation cohort (n = 10). Demographic and clinical data of these patients were acquired from the hospital database. Texture features including average, standard deviation, kurtosis, skewness, entropy, correlation, and contrast were obtained from manually drawn region of interest (ROI) over the omentum on the axial CT image showing the omentum at its largest cross sectional area. After using Fisher's exact and Wilcoxon signed-rank test for comparison of the clinical and texture features between the two groups of the test cohort, conditional logistic regression analysis was performed to determine significant independent predictor for occult PC. Using the optimal cut-off value from receiver operating characteristic (ROC) analysis for the significant variables, diagnostic sensitivity and specificity were determined in the test cohort. The cut-off value of the significant variables obtained from the test cohort was then applied to the validation cohort. Bonferroni correction was used to adjust P value for multiple comparisons.ResultsBetween the two groups, there was no significant difference in the clinical features. Regarding the texture features, the occult PC group showed significantly higher average, entropy, standard deviation, and significantly lower correlation (P value < 0.004 for all). Conditional logistic regression analysis demonstrated that entropy was significant independent predictor for occult PC. When the cut-off value of entropy (> 7.141) was applied to the validation cohort, sensitivity and specificity for the prediction of occult PC were 80% and 90%, respectively.ConclusionFor AGC patients whose PC cannot be detected with routine imaging such as CT, texture analysis may be a useful adjunct for the prediction of occult PC.

TI-RADS is applicable for the evaluation of MTC nodules with good inter-observer agreement.

No abstract