» Articles » PMID: 26879165

A Novel Fusion Imaging System for Endoscopic Ultrasound

Overview
Date 2016 Feb 17
PMID 26879165
Citations 5
Authors
Affiliations
Soon will be listed here.
Abstract

Background And Objective: Navigation of a flexible endoscopic ultrasound (EUS) probe inside the gastrointestinal (GI) tract is problematic due to the small window size and complex anatomy. The goal of the present study was to test the feasibility of a novel fusion imaging (FI) system which uses electromagnetic (EM) sensors to co-register the live EUS images with the pre-procedure computed tomography (CT) data with a novel navigation algorithm and catheter.

Methods: An experienced gastroenterologist and a novice EUS operator tested the FI system on a GI tract bench top model. Also, the experienced gastroenterologist performed a case series of 20 patients during routine EUS examinations.

Results: On the bench top model, the experienced and novice doctors reached the targets in 67 ± 18 s and 150 ± 24 s with a registration error of 6 ± 3 mm and 11 ± 4 mm, respectively. In the case series, the total procedure time was 24.6 ± 6.6 min, while the time to reach the clinical target was 8.7 ± 4.2 min.

Conclusions: The FI system is feasible for clinical use, and can reduce the learning curve for EUS procedures and improve navigation and targeting in difficult anatomic locations.

Citing Articles

Image Fusion Involving Real-Time Transabdominal or Endoscopic Ultrasound for Gastrointestinal Malignancies: Review of Current and Future Applications.

Singh B, Cazacu I, Deza C, Rigaud B, Saftoiu A, Gruionu G Diagnostics (Basel). 2022; 12(12).

PMID: 36553225 PMC: 9777678. DOI: 10.3390/diagnostics12123218.


Feasibility of a lung airway navigation system using fiber-Bragg shape sensing and artificial intelligence for early diagnosis of lung cancer.

Gruionu L, Udristoiu A, Iacob A, Constantinescu C, Stan R, Gruionu G PLoS One. 2022; 17(12):e0277938.

PMID: 36476838 PMC: 9728835. DOI: 10.1371/journal.pone.0277938.


Advanced EUS Imaging Techniques.

Cazacu I, Saftoiu A, Bhutani M Dig Dis Sci. 2022; 67(5):1588-1598.

PMID: 35451709 DOI: 10.1007/s10620-022-07486-9.


Determination of optimal ultrasound planes for the initialisation of image registration during endoscopic ultrasound-guided procedures.

Bonmati E, Hu Y, Gibson E, Uribarri L, Keane G, Gurusami K Int J Comput Assist Radiol Surg. 2018; 13(6):875-883.

PMID: 29663274 PMC: 5973980. DOI: 10.1007/s11548-018-1762-2.


The role of contrast-enhanced endoscopic ultrasound in pancreatic adenocarcinoma.

Saftoiu A, Vilmann P, Bhutani M Endosc Ultrasound. 2016; 5(6):368-372.

PMID: 28000627 PMC: 5206824. DOI: 10.4103/2303-9027.190932.

References
1.
Fritscher-Ravens A, Cuming T, Dhar S, Parupudi S, Patel K, Ghanbari A . Endoscopic ultrasound-guided fine needle aspiration training: evaluation of a new porcine lymphadenopathy model for in vivo hands-on teaching and training, and review of the literature. Endoscopy. 2013; 45(2):114-20. DOI: 10.1055/s-0032-1325931. View

2.
Saftoiu A, Gheonea D . Tridimensional (3D) endoscopic ultrasound - a pictorial review. J Gastrointestin Liver Dis. 2010; 18(4):501-5. View

3.
Enquobahrie A, Cheng P, Gary K, Ibanez L, Gobbi D, Lindseth F . The image-guided surgery toolkit IGSTK: an open source C++ software toolkit. J Digit Imaging. 2007; 20 Suppl 1:21-33. PMC: 2039836. DOI: 10.1007/s10278-007-9054-3. View

4.
Vilmann P, Seicean A, Saftoiu A . Tips to overcome technical challenges in EUS-guided tissue acquisition. Gastrointest Endosc Clin N Am. 2013; 24(1):109-24. DOI: 10.1016/j.giec.2013.08.009. View

5.
Kefalides P, Gress F . Simulator training for endoscopic ultrasound. Gastrointest Endosc Clin N Am. 2006; 16(3):543-52, viii. DOI: 10.1016/j.giec.2006.03.018. View