Ultrasound-guided facet joint injection training using Perk Tutor

Moult, Eric M.; Ungi, Tamás; Welch, Mattea; Lu, Jie; McGraw, Robert; Fichtinger, Gabor

doi:10.1007/s11548-012-0811-5

Cited by 39 publications

(40 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Perk Station [41–43] is a training platform for image-guided interventions. While training on a phantom, trainees perform tasks using AR image overlay.…”

Section: Resultsmentioning

confidence: 99%

Systematic review on the effectiveness of augmented reality applications in medical training

2016

View full text Add to dashboard Cite

BackgroundComputer-based applications are increasingly used to support the training of medical professionals. Augmented reality applications (ARAs) render an interactive virtual layer on top of reality. The use of ARAs is of real interest to medical education because they blend digital elements with the physical learning environment. This will result in new educational opportunities. The aim of this systematic review is to investigate to which extent augmented reality applications are currently used to validly support medical professionals training.MethodsPubMed, Embase, INSPEC and PsychInfo were searched using predefined inclusion criteria for relevant articles up to August 2015. All study types were considered eligible. Articles concerning AR applications used to train or educate medical professionals were evaluated.ResultsTwenty-seven studies were found relevant, describing a total of seven augmented reality applications. Applications were assigned to three different categories. The first category is directed toward laparoscopic surgical training, the second category toward mixed reality training of neurosurgical procedures and the third category toward training echocardiography. Statistical pooling of data could not be performed due to heterogeneity of study designs. Face-, construct- and concurrent validity was proven for two applications directed at laparoscopic training, face- and construct validity for neurosurgical procedures and face-, content- and construct validity in echocardiography training. In the literature, none of the ARAs completed a full validation process for the purpose of use.ConclusionAugmented reality applications that support blended learning in medical training have gained public and scientific interest. In order to be of value, applications must be able to transfer information to the user. Although promising, the literature to date is lacking to support such evidence.

show abstract

“…The Perk Station [41–43] is a training platform for image-guided interventions. While training on a phantom, trainees perform tasks using AR image overlay.…”

Section: Resultsmentioning

confidence: 99%

Systematic review on the effectiveness of augmented reality applications in medical training

2016

View full text Add to dashboard Cite

show abstract

“…All eight insertions into the facet joint were deemed technically successful by the expert spine surgeon (needle tip in the gap between the articular processes [7]), with average orthogonal positioning errors for robotic and conventional way of guidance of 1.36 ± 0. 33 tively.…”

Section: Needle Insertion Accuracymentioning

confidence: 99%

“…While the cumbersome procedure induces a slow learning curve [6,7], work-related musculoskeletal disorders have been associated with medical sonographers [8], impeding the quality of USbased interventions over time. Both of these issues relate to the freehand nature of previous US-guided facet joint injections, suggesting more automated solutions [9].…”

Section: Introductionmentioning

confidence: 99%

3D ultrasound registration-based visual servoing for neurosurgical navigation

et al. 2017

View full text Add to dashboard Cite

Purpose We present a fully image-based visual servoing framework for neurosurgical navigation and needle guidance. The proposed servo-control scheme allows for compensation of target anatomy movements, maintaining high navigational accuracy over time, and automatic needle guide alignment for accurate manual insertions. Method Our system comprises a motorized 3D ultrasound (US) transducer mounted on a robotic arm and equipped with a needle guide. It continuously registers US sweeps in real time with a pre-interventional plan based on CT or MR images and annotations. While a visual control law maintains anatomy visibility and alignment of the needle guide, a force controller is employed for acoustic coupling and tissue pressure. We validate the servoing capabilities of our method on a geometric gel phantom and real human anatomy, and the needle targeting accuracy using CT images on a lumbar spine gel phantom under neurosurgery conditions. Results Despite the varying resolution of the acquired Oliver Zettinig and Benjamin Frisch have contributed equally to this work. Yu-Mi Ryang and Nassir Navab have contributed equally to this work.B Oliver Zettinig 3D sweeps, we achieved direction-independent positioning errors of 0.35±0.19 mm and 0.61 • ±0.45 • , respectively. Our method is capable of compensating movements of around 25 mm/s and works reliably on human anatomy with errors of 1.45 ± 0.78 mm. In all four manual insertions by an expert surgeon, a needle could be successfully inserted into the facet joint, with an estimated targeting accuracy of 1.33±0.33 mm, superior to the gold standard. Conclusion The experiments demonstrated the feasibility of robotic ultrasound-based navigation and needle guidance for neurosurgical applications such as lumbar spine injections.

show abstract

“…In previous studies, the Perk Tutor was shown to be beneficial in teaching novices to use ultrasound to guide spinal facet joint injections. 9,10 We designed a randomized controlled trial to determine if Perk Tutor could help residents learn to use ultrasound to guide LP in simulation phantoms with abnormal spinal anatomy. Real-time needle position tracking was used as a measure of needle movement within tissue.…”

Section: Résumémentioning

confidence: 99%

Computerized training system for ultrasound-guided lumbar puncture on abnormal spine models: a randomized controlled trial

Keri

Sydor

Ungi

et al. 2015

Can J Anesth/J Can Anesth

View full text Add to dashboard Cite

Purpose A randomized controlled trial was carried out to determine whether Perk Tutor, a computerized training platform that displays an ultrasound image and real-time needle position in a three-dimensional (3D) anatomical model, would benefit residents learning ultrasound-guided lumbar puncture (LP) in simulation phantoms with abnormal spinal anatomy. Methods Twenty-four residents were randomly assigned to either the Perk Tutor (P) or the Control (C) group and asked to perform an LP with ultrasound guidance on parttask trainers with spinal pathology. Group P was trained with the 3D display along with conventional ultrasound imaging, while Group C used conventional ultrasound only. Both groups were then tested solely with conventional ultrasound guidance on an abnormal spinal model not previously seen. We measured potential tissue damage, needle path in tissue, total procedure time, and needle insertion time. Procedural success rate was a secondary outcome.

show abstract

Ultrasound-guided facet joint injection training using Perk Tutor

Abstract: The results of this pilot study suggest that Perk Tutor provides an improved training environment for US-guided facet joint injections on a synthetic model.

Cited by 39 publications

References 14 publications

Systematic review on the effectiveness of augmented reality applications in medical training

Systematic review on the effectiveness of augmented reality applications in medical training

3D ultrasound registration-based visual servoing for neurosurgical navigation

Computerized training system for ultrasound-guided lumbar puncture on abnormal spine models: a randomized controlled trial

Contact Info

Product

Resources

About