| Literature DB >> 33550514 |
Peter Legeza1,2, Gavin W Britz3, Alpesh Shah4, Kalyna Sconzert5, John-Michael Sungur5, Ponraj Chinnadurai6, Kavya Sinha7, Alan B Lumsden7.
Abstract
Remote robotic-assisted endovascular interventions require real-time control of the robotic system to conduct precise device navigation. The delay (latency) between the input command and the catheter response can be affected by factors such as network speed and distance. This study evaluated the effect of network latency on robotic-assisted endovascular navigation in three vascular beds using in-vivo experimental model. Three operators performed femoral, carotid, and coronary endovascular robotic navigation blinded from the hybrid room with the prototype remote-enabled CorPath GRX system in a porcine model. Navigation was performed to different targets with randomly assigned network latencies from 0 to 1000 ms. Outcome measurements included navigation success, navigation time, perceived lag (1 = imperceptible, 5 = too long), and procedural impact scored by the operators (1 = no impact, 5 = unacceptable). Robotic-assisted remote endovascular navigation was successful in all 65 cases (9 femoral, 38 external carotid, 18 coronary). Guidewire times were not significantly different across the simulated network latency times. Compared to 0 ms added latency, both the procedural impact and perceived lag scores were significantly higher when the added latency was 400 ms or greater (< 0.01). Remote endovascular intervention was feasible in all studied anatomic regions. Network latency of 400 ms or above is perceptible, although acceptable to operators, which suggests that remote robotic-assisted femoral, carotid or coronary arterial interventions should be performed with network latency below 400 ms to provide seamless remote device control.Entities:
Keywords: Endovascular surgery; Network latency; Remote surgery; Robotic-PCI; Robotic-assisted
Mesh:
Year: 2021 PMID: 33550514 PMCID: PMC8863762 DOI: 10.1007/s11701-021-01196-6
Source DB: PubMed Journal: J Robot Surg ISSN: 1863-2483
Fig. 1Layout of the hybrid suite and the remote workstation. The operator performed the robotic navigation from the control room, facing away from the hybrid room. Connection was achieved between the two nodes via institutional network connection (stars). TP telepresence system, Table operating table, Arm robotic arm
Fig. 2a Overall procedural impact score (mean ± SD) with different added command latencies (ms), b Overall perceived latency score (mean ± SD) with different added command latencies (ms)
Fig. 3(a) Procedural impact score (mean ± SD) with different added command latencies (ms), b Perceived latency score (mean ± SD) with different added command latencies (ms). Blue: coronary arterial navigation, red: peripheral arterial navigation
Mean procedural impact scores with different added command latencies
| Added latency (ms) | Procedural impact score | |
|---|---|---|
| 0 | 1 | N/A |
| 150 | 1.07 ± 0.7 | 0.548 |
| 250 | 1.11 ± 0.33 | 0.55 |
| 400 | 1.55 ± 0.93 | 0.03 |
| 600 | 1.8 ± 1.23 | 0.01 |
| 1000 | 1.67 ± 1 | 0.02 |
The scores with added latencies were compared to scores with 0 ms added latency
Mean perceived latency scores with different added command latencies
| Added latency (ms) | Perceived latency score | |
|---|---|---|
| 0 | 1 | N/A |
| 150 | 1.14 ± 0.1 | 0.32 |
| 250 | 1.33 ± 0.5 | 0.13 |
| 400 | 1.91 ± 1.04 | < 0.01 |
| 600 | 1.9 ± 1.45 | 0.03 |
| 1000 | 2 ± 1.41 | 0.02 |
The scores with added latencies were compared to scores with 0 ms added latency