What Is the Optimal Abdominal Aortic Aneurysm Sac Measurement on CT Images during Follow-up after Endovascular Repair?

Purpose To develop a computed tomographic (CT) angiographic postprocessing protocol with two- and three-dimensional measurements for follow-up of patients who underwent endovascular aortic repair. Materials and Methods This HIPAA-compliant institutional review board-approved retrospective study included 159 patients (129 men, 30 women; mean age ± standard deviation, 74.9 years ± 8.2) who underwent 824 CT examinations (median of five examinations per patient; range, two to 14) with unenhanced and arterial -phase imaging performed between September 2004 and March 2015. The largest diameter on the axial plane; coronal, sagittal, and maximal diameter perpendicular to the reconstructed centerline; volume of the abdominal aortic aneurysm sac; and volume from the lowest renal artery to the aortic bifurcation and to the common iliac artery bifurcation were measured. Endoleaks on contrast material-enhanced images were considered the reference standard, and the predictive value of diameter and volume changes was analyzed. Intraclass correlation was used to compare diameters and volumes. Results All diameters and volumes showed excellent correlation (intraclass coefficient, 0.95 and 0.94, respectively). Average interobserver difference for diameters and volumes was 2%-3% and 4%-12%, respectively. Endoleaks were observed in 80 (50%) of 159 patients (59 [74%] at initial and 21 [26%] at later CT angiography). New endo-leaks were associated with increased aneurysm size measured as the largest diameter on the axial plane (P = .04) and perpendicular to the centerline (P = .01), and volume was measured from the lowest renal artery to the aortic bifurcation (P = .03) and to the common iliac artery bifurcation (P = .01). With a 5% size threshold, sensitivity and specificity for detection of endoleaks was optimal for centerline diameter (64.3% and 81.7%, respectively) and volume from the lowest renal artery to the common iliac artery bifurcation (57.1% and 63.5%). Conclusion The maximal diameter and volume of an abdominal aortic aneurysm sac can be used for temporal monitoring after endovascular aortic repair, with excellent correlation and interobserver agreement. An increase in the centerline diameter and volume from the lowest renal artery to the iliac bifurcation were the most sensitive criteria for detecting endoleaks. © RSNA, 2017 Online supplemental material is available for this article.

CT Intensity Distribution Curve (Histogram) Analysis of Patients Undergoing Antiangiogenic Therapy for Metastatic Renal Cell Carcinoma.

OBJECTIVE: The purpose of this study was to evaluate the median versus mean attenuation obtained from histograms in the response assessment of renal cell carcinoma (RCC) target lesions in patients treated with vascular endothelial growth factor receptor (VEGFR) tyrosine kinase inhibitors. MATERIALS AND METHODS: Imaging findings of 19 patients with RCC and treated with a VEGFR tyrosine kinase inhibitor that included a baseline study and at least two follow-up studies were retrospectively analyzed. Histograms of target lesions were created from ROI measurements, and mean and median lesion attenuation were obtained. Shift of mean and median was used to classify response of lesions between baseline CT and the first follow-up examination according to the Choi criteria; morphology, attenuation, size, and structure (MASS) criteria; and the Response Evaluation Criteria in Solid Tumors (RECIST). RECIST classification of the last follow-up CT examination was considered the reference standard. RESULTS: Among the 19 patients (six women, 13 men; mean age, 60 ± 8 [SD] years; body mass index, 24.5 ± 4.6 kg/m2), three (16%) had evidence of disease progression; nine (47%), partial response; and seven (37%), stable disease. Temporal change in the shape of the histograms from or to gaussian occurred in 11 of the 19 (58%) lesions, which accounted for a significant difference between mean (64.3 ± 38.5 HU) and median (71.0 ± 36.5 HU) lesion attenuation (p < 0.001). According to the shift of median for outcome analysis, the number of properly classified lesions increased from 12 of 19 (63%) to 13 of 19 (68%) for the Choi criteria and from 14 of 19 (74%) to 15 of 19 (79%) for the MASS criteria. CONCLUSION: Mean and median attenuation of RCC target lesions differed significantly. Use of shift of median rather than shift of mean increased the number of accurate classifications of lesions at the first follow-up CT examination.

Outcome analysis of patients with acute pancreatitis by using an artificial neural network.

RATIONALE AND OBJECTIVES: The authors performed this study to evaluate the ability of an artificial neural network (ANN) that uses radiologic and laboratory data to predict the outcome in patients with acute pancreatitis. MATERIALS AND METHODS: An ANN was constructed with data from 92 patients with acute pancreatitis who underwent computed tomography (CT). Input nodes included clinical, laboratory, and CT data. The ANN was trained and tested by using a round-robin technique, and the performance of the ANN was compared with that of linear discriminant analysis and Ranson and Balthazar grading systems by using receiver operating characteristic analysis. The length of hospital stay was used as an outcome measure. RESULTS: Hospital stay ranged from 0 to 45 days, with a mean of 8.4 days. The hospital stay was shorter than the mean for 62 patients and longer than the mean for 30. The 23 input features were reduced by using stepwise linear discriminant analysis, and an ANN was developed with the six most statistically significant parameters (blood pressure, extent of inflammation, fluid aspiration, serum creatinine level, serum calcium level, and the presence of concurrent severe illness). With these features, the ANN successfully predicted whether the patient would exceed the mean length of stay (Az = 0.83 +/- 0.05). Although the Az performance of the ANN was statistically significantly better than that of the Ranson (Az = 0.68 +/- 0.06, P < .02) and Balthazar (Az = 0.62 +/- 0.06, P < .003) grades, it was not significantly better than that of linear discriminant analysis (Az = 0.82 +/- 0.05, P = .53). CONCLUSION: An ANN may be useful for predicting outcome in patients with acute pancreatitis.