BACKGROUND AND PURPOSE: Intracerebral hemorrhage represents a potentially severe complication of revascularization of acute ischemic stroke. The aim of our study was to assess the capability of iodine extravasation quantification on dual-energy CT performed immediately after mechanical thrombectomy to predict hemorrhagic complications. MATERIALS AND METHODS: Because this was a retrospective study, the need for informed consent was waived. Eighty-five consecutive patients who underwent brain dual-energy CT immediately after mechanical thrombectomy for acute ischemic stroke between August 2013 and January 2017 were included. Two radiologists independently evaluated dual-energy CT images for the presence of parenchymal hyperdensity, iodine extravasation, and hemorrhage. Maximum iodine concentration was measured. Follow-up CT examinations performed until patient discharge were reviewed for intracerebral hemorrhage development. The correlation between dual-energy CT parameters and intracerebral hemorrhage development was analyzed by the Mann-Whitney U test and Fisher exact test. Receiver operating characteristic curves were generated for continuous variables. RESULTS: Thirteen of 85 patients (15.3%) developed hemorrhage. On postoperative dual-energy CT, parenchymal hyperdensities and iodine extravasation were present in 100% of the patients who developed intracerebral hemorrhage and in 56.3% of the patients who did not (P = .002 for both). Signs of bleeding were present in 35.7% of the patients who developed intracerebral hemorrhage and in none of the patients who did not (P < .001). Median maximum iodine concentration was 2.63 mg/mL in the patients who developed intracerebral hemorrhage and 1.4 mg/mL in the patients who did not (P < .001). Maximum iodine concentration showed an area under the curve of 0.89 for identifying patients developing intracerebral hemorrhage. CONCLUSIONS: The presence of parenchymal hyperdensity with a maximum iodine concentration of >1.35 mg/mL may identify patients developing intracerebral hemorrhage with 100% sensitivity and 67.6% specificity.

OBJECTIVE. The purpose of this study was to assess the accuracy and short-term complication rate of ultrasound-guided fine-needle aspiration cytologic sampling of focal pancreatic lesions.MATERIALS AND METHODS. We reviewed 545 consecutive ultrasound-guided fine-needle aspiration cytologic sampling procedures for focal pancreatic lesions from January 2004 through June 2008. The procedures were performed with a 20- or 21-gauge needle. The onsite cytopathologist evaluated the appropriateness of the sample and made a diagnosis. We reviewed the final diagnosis and the radiologic and medical records of all patients for onset of complications during or within 7 days of the procedure.RESULTS. The study sample included 262 women and 283 men (mean age, 62 years; range, 25–86 years). The head or uncinate process of the pancreas was the location of 63.0% of the lesions, and 35.2% of the lesions were located in the body or tail of the pancreas. The site of 10 lesions (1.8%) was not specified. Sampling was diagnostic i...

Background: Our study aims to provide an overview of existing evidence regarding the image quality of dual-energy CT (DECT) employing reduced contrast media (CM) volumes, in comparison to single-energy CT (SECT) with standard CM loads. The advantages, indications, and possible applications of DECT were investigated from the perspective of providing better patient care, minimizing CM volume and managing CM shortage. Methods: In this systematic review (PRISMA methodology), PubMed and WOS were searched from January 2010 to January 2023 by two independent reviewers. The scan and CM characteristics, radiation dose, and results of quantitative (contrast to noise ratio, CNR, and signal to noise ratio, SNR) and qualitative assessment of image quality were collected. Sixty non-duplicated records eligible for full-text screening were examined. Results: Finally, 22 articles (1818 patients) were included. The average CM reduction with DECT ranged between 43.4 ± 11%. Despite the wide variability in CT scan protocols, no differences were found in radiation doses between DECT and SECT. Conclusions: DECT scanners allow the employment of lower CM volumes with equal or better image quality evaluated by quantitative and qualitative analyses and similar dose radiation compared to SECT. Using image reconstructions at low monochromatic energy levels, DECT increases iodine conspicuity and attenuation contributing to CM containment measures.

Standard imaging cannot assess the pathology details of intrahepatic cholangiocarcinoma (ICC). We investigated whether CT-based radiomics may improve the prediction of tumor characteristics. All consecutive patients undergoing liver resection for ICC (2009-2019) in six high-volume centers were evaluated for inclusion. On the preoperative CT, we segmented the ICC (Tumor-VOI, i.e., volume-of-interest) and a 5-mm parenchyma rim around the tumor (Margin-VOI). We considered two types of pathology data: tumor grading (G) and microvascular invasion (MVI). The predictive models were internally validated. Overall, 244 patients were analyzed: 82 (34%) had G3 tumors and 139 (57%) had MVI. For G3 prediction, the clinical model had an AUC = 0.69 and an Accuracy = 0.68 at internal cross-validation. The addition of radiomic features extracted from the portal phase of CT improved the model performance (Clinical data+Tumor-VOI: AUC = 0.73/Accuracy = 0.72; +Tumor-/Margin-VOI: AUC = 0.77/Accuracy = 0.77). Also for MVI prediction, the addition of portal phase radiomics improved the model performance (Clinical data: AUC = 0.75/Accuracy = 0.70; +Tumor-VOI: AUC = 0.82/Accuracy = 0.73; +Tumor-/Margin-VOI: AUC = 0.82/Accuracy = 0.75). The permutation tests confirmed that a combined clinical–radiomic model outperforms a purely clinical one (p < 0.05). The addition of the textural features extracted from the arterial phase had no impact. In conclusion, the radiomic features of the tumor and peritumoral tissue extracted from the portal phase of preoperative CT improve the prediction of ICC grading and MVI.