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Fast STIR imaging of the heart with effective suppression of flow and motion artifacts was implemented. The approach has much potential for high-contrast imaging in a variety of diseases affecting the heart and mediastinum.

Background-Standard mapping and ablation of focal sources of atrial fibrillation are associated with very long procedure times and low efficacy. An anatomic approach to complete pulmonary vein isolation could overcome these limitations. Methods and Results-Fifteen patients with atrial fibrillation refractory to medication underwent circumferential isolation of the pulmonary veins by using a novel catheter, with an ultrasound transducer (8-MHz) mounted near the tip, in a saline-filled balloon. Twelve atrial foci and/or atrial fibrillation triggers were identified in 9 patients (pulmonary vein locations: left upper, 3; right upper, 6; right middle, 1; right lower, 1; and left inferior, 1). In 5 patients, lesions were placed in the absence of any mapped triggers. Irrespective of trigger mapping, circumferential isolation of both upper pulmonary veins was attempted in all patients. The lower pulmonary veins were ablated when sinus rhythm activation mapping revealed evidence of a sleeve of atrial muscle in the vein. The median number of lesions per patient required to isolate 1 pulmonary vein was 4 (range, 1 to 29). After ablation, no evidence of narrowing was seen with repeat venography or follow-up computed tomography scan. After a mean follow-up of 35Ϯ6 weeks, 5 patients had recurrence of atrial fibrillation. Three responded to drugs that were previously ineffective, and 2 remained in atrial fibrillation. Conclusions-This novel ultrasound ablation system can successfully isolate multiple pulmonary veins. At early follow-up, this approach seems to be effective in preventing recurrent atrial fibrillation in a significant number of patients.

Severe pulmonary vein stenosis after catheter ablation of atrial fibrillation is associated with respiratory symptoms that frequently mimic more common diseases, often leading to erroneous diagnostic and therapeutic procedures. Awareness of this syndrome is important for proper and prompt management.

Purpose To evaluate the performance of an artificial intelligence (AI) tool using a deep learning algorithm for detecting hemorrhage, mass effect, or hydrocephalus (HMH) at non-contrast material-enhanced head computed tomographic (CT) examinations and to determine algorithm performance for detection of suspected acute infarct (SAI). Materials and Methods This HIPAA-compliant retrospective study was completed after institutional review board approval. A training and validation dataset of noncontrast-enhanced head CT examinations that comprised 100 examinations of HMH, 22 of SAI, and 124 of noncritical findings was obtained resulting in 2583 representative images. Examinations were processed by using a convolutional neural network (deep learning) using two different window and level configurations (brain window and stroke window). AI algorithm performance was tested on a separate dataset containing 50 examinations with HMH findings, 15 with SAI findings, and 35 with noncritical findings. Results Final algorithm performance for HMH showed 90% (45 of 50) sensitivity (95% confidence interval [CI]: 78%, 97%) and 85% (68 of 80) specificity (95% CI: 76%, 92%), with area under the receiver operating characteristic curve (AUC) of 0.91 with the brain window. For SAI, the best performance was achieved with the stroke window showing 62% (13 of 21) sensitivity (95% CI: 38%, 82%) and 96% (27 of 28) specificity (95% CI: 82%, 100%), with AUC of 0.81. Conclusion AI using deep learning demonstrates promise for detecting critical findings at noncontrast-enhanced head CT. A dedicated algorithm was required to detect SAI. Detection of SAI showed lower sensitivity in comparison to detection of HMH, but showed reasonable performance. Findings support further investigation of the algorithm in a controlled and prospective clinical setting to determine whether it can independently screen noncontrast-enhanced head CT examinations and notify the interpreting radiologist of critical findings. RSNA, 2017 Online supplemental material is available for this article.

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Only a small fraction of patients undergoing a PC proceed to a cholecystectomy with a high risk of conversion to an open procedure. A quarter of patients presented with recurrent cholecystitis during follow-up. The mortality rate is high during the index admission from sepsis and within the 1 year of follow-up from other causes.

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