A transient, closed-loop network of wireless, body-integrated devices for autonomous electrotherapy.

Temporary postoperative cardiac pacing requires devices with percutaneous leads and external wired power and control systems. This hardware introduces risks for infection, limitations on patient mobility, and requirements for surgical extraction procedures. Bioresorbable pacemakers mitigate some of these disadvantages, but they demand pairing with external, wired systems and secondary mechanisms for control. We present a transient closed-loop system that combines a time-synchronized, wireless network of skin-integrated devices with an advanced bioresorbable pacemaker to control cardiac rhythms, track cardiopulmonary status, provide multihaptic feedback, and enable transient operation with minimal patient burden. The result provides a range of autonomous, rate-adaptive cardiac pacing capabilities, as demonstrated in rat, canine, and human heart studies. This work establishes an engineering framework for closed-loop temporary electrotherapy using wirelessly linked, body-integrated bioelectronic devices.

Fully implantable and bioresorbable cardiac pacemakers without leads or batteries.

Temporary cardiac pacemakers used in periods of need during surgical recovery involve percutaneous leads and externalized hardware that carry risks of infection, constrain patient mobility and may damage the heart during lead removal. Here we report a leadless, battery-free, fully implantable cardiac pacemaker for postoperative control of cardiac rate and rhythm that undergoes complete dissolution and clearance by natural biological processes after a defined operating timeframe. We show that these devices provide effective pacing of hearts of various sizes in mouse, rat, rabbit, canine and human cardiac models, with tailored geometries and operation timescales, powered by wireless energy transfer. This approach overcomes key disadvantages of traditional temporary pacing devices and may serve as the basis for the next generation of postoperative temporary pacing technology.

Real-time estimation of lesion depth and control of radiofrequency ablation within ex vivo animal tissues using a neural network.

BACKGROUND: Radiofrequency ablation (RFA), a method of inducing thermal ablation (cell death), is often used to destroy tumours or potentially cancerous tissue. Current techniques for RFA estimation (electrical impedance tomography, Nakagami ultrasound, etc.) require long compute times (≥ 2 s) and measurement devices other than the RFA device. This study aims to determine if a neural network (NN) can estimate ablation lesion depth for control of bipolar RFA using complex electrical impedance - since tissue electrical conductivity varies as a function of tissue temperature - in real time using only the RFA therapy device's electrodes. METHODS: Three-dimensional, cubic models comprised of beef liver, pork loin or pork belly represented target tissue. Temperature and complex electrical impedance from 72 data generation ablations in pork loin and belly were used for training the NN (403 s on Xeon processor). NN inputs were inquiry depth, starting complex impedance and current complex impedance. Training-validation-test splits were 70%-0%-30% and 80%-10%-10% (overfit test). Once the NN-estimated lesion depth for a margin reached the target lesion depth, RFA was stopped for that margin of tissue. RESULTS: The NN trained to 93% accuracy and an NN-integrated control ablated tissue to within 1.0 mm of the target lesion depth on average. Full 15-mm depth maps were calculated in 0.2 s on a single-core ARMv7 processor. CONCLUSIONS: The results show that a NN could make lesion depth estimations in real-time using less in situ devices than current techniques. With the NN-based technique, physicians could deliver quicker and more precise ablation therapy.