ArticleUpdates in surgery2021
Robotic assistance for quick and accurate image-guided needle placement.
Article in Updates in surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 16 citations in OpenAlex.
- Robot-assisted CT-guided interventions: Where are we now and where are we going?European radiology · 2026Review
- Enhancing the Precision and Efficiency of Pulmonary Tumor Detection With Robotic-AssistedThoracic cancer · 2025Article
- Robotic Assistance in Percutaneous Liver Ablation Therapies: A Systematic Review and Meta-Analysis.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2024Article
- Imaging of Ganglioneuroma: A Literature Review and a Rare Case of Cystic Presentation in an Adolescent Girl.Diagnostics (Basel, Switzerland) · 2023Article
- Technological Advancements in Interventional Oncology.Diagnostics (Basel, Switzerland) · 2023Review
- Minimally invasive trans-superior articular process percutaneous endoscopic lumbar discectomy with robot assistance.BMC musculoskeletal disorders · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
Computed tomography (CT) image-guided procedures including biopsy, drug delivery, and ablation are gaining increasing application in medicine. Robotic technology holds the promise for allowing surgeons, and other proceduralists, access to such CT-guided procedures by potentially shortening training, improving accuracy, decreasing needle passes, and reducing radiation exposure. We evaluated surgeon learning and proficiency for image-guided needle placement with an FDA-cleared robotic arm. Five out of six surgeons had no prior CT-guided procedural experience, while one had prior experience with freehand CT-guided needle placement. All surgeons underwent a 60-min training with the MAXIO robot (Perfint Healthcare, Redmond, WA). The robot was used to place needles into three different pre-specified targets on a spine model. Performance time, procedural errors, and needle placement accuracy were recorded. All participants successfully placed needles into the targets using the robotic arm. The average time for needle placement was 3:44 ± 1:43 min. Time for needle placement decreased with subsequent attempts, with average third placement taking 2:29 ± 1:51 min less than the first attempt. The average vector distance from the target was 2.3 ± 1.2 mm. One error resulted in the need for reimaging by CT scan. No errant needle placement occurred. Surgeons (attending fellows and residents) without previous experience and minimal training could successfully place percutaneous needles under CT guidance quickly, accurately, and reproducibly using a robotic arm. This suggests that robotic technology may be used to facilitate surgeon adoption of CT image-guided needle-based procedures in the future.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.