Randomized comparison of atrioventricular node re-entry tachycardia and atrial flutter catheter ablation with and without fluoroscopic guidance: ZeroFluoro study.

AIMS: Interventional cardiology procedures may expose patients and staff to considerable radiation doses. We aimed to assess whether exposure to ionizing radiation during catheter ablation of supraventricular tachycardia (SVT) can be completely avoided. METHODS AND RESULTS: In this prospective randomized study, patients with SVT (atrioventricular re-entrant tachycardia n = 94, typical atrial flutter n = 29) were randomly assigned in a 1:1 ratio to catheter ablation with conventional fluoroscopic guidance (CF group) or with the EnSite Precision mapping system [zerofluoro (ZF) group]. Acute procedural parameters, increased stochastic risk of cancer incidence and 6-month follow-up data were assessed. Between May 2019 and August 2020, 123 patients were enrolled. Clinical parameters were comparable. Median procedural time was 60.0 and 58.0 min, median fluoroscopy time and estimated median effective dose were 240 s vs. 0 and 0.38 mSv vs. 0 and arrhythmia recurrence was 5% and 7.9% in the CF and ZF groups, respectively. The acute success rate was 98.4% in both groups. No procedure-related complications were reported. At an average age of 55.5 years and median radiation exposure of 0.38 mSv, the estimate of increased incidence was approximately 1 in 14 084. The estimated mortality rate was 1 per 17 857 exposed persons. CONCLUSIONS: The procedural safety and efficacy of the zero-fluoroscopic approach are similar to those of conventional fluoroscopy-based ablation for atrioventricular nodal re-entrant tachycardia and atrial flutter. Under the assumption of low radiation dose, the excessive lifetime risk of malignancy in the CF group due to electrophysiology procedure is reasonably small, whilst totally reduced in zero fluoroscopy procedures.

A System Using Artificial Intelligence to Detect and Scare Bird Flocks in the Protection of Ripening Fruit.

Flocks of birds may cause major damage to fruit crops in the ripening phase. This problem is addressed by various methods for bird scaring; in many cases, however, the birds become accustomed to the distraction, and the applied scaring procedure loses its purpose. To help eliminate the difficulty, we present a system to detect flocks and to trigger an actuator that will scare the objects only when a flock passes through the monitored space. The actual detection is performed with artificial intelligence utilizing a convolutional neural network. Before teaching the network, we employed videocameras and a differential algorithm to detect all items moving in the vineyard. Such objects revealed in the images were labeled and then used in training, testing, and validating the network. The assessment of the detection algorithm required evaluating the parameters precision, recall, and F1 score. In terms of function, the algorithm is implemented in a module consisting of a microcomputer and a connected videocamera. When a flock is detected, the microcontroller will generate a signal to be wirelessly transmitted to the module, whose task is to trigger the scaring actuator.