Augmented reality for sentinel lymph node biopsy
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Published:2023-09-25
Issue:1
Volume:19
Page:171-180
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ISSN:1861-6429
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Container-title:International Journal of Computer Assisted Radiology and Surgery
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language:en
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Short-container-title:Int J CARS
Author:
von Niederhäusern Peter A.ORCID, Seppi CarloORCID, Sandkühler RobinORCID, Nicolas GuillaumeORCID, Haerle Stephan K., Cattin Philippe C.ORCID
Abstract
Abstract
Introduction
Sentinel lymph node biopsy for oral and oropharyngeal squamous cell carcinoma is a well-established staging method. One variation is to inject a radioactive tracer near the primary tumor of the patient. After a few minutes, audio feedback from an external hand-held $$\gamma $$
γ
-detection probe can monitor the uptake into the lymphatic system. Such probes place a high cognitive load on the surgeon during the biopsy, as they require the simultaneous use of both hands and the skills necessary to correlate the audio signal with the location of tracer accumulation in the lymph nodes. Therefore, an augmented reality (AR) approach to directly visualize and thus discriminate nearby lymph nodes would greatly reduce the surgeons’ cognitive load.
Materials and methods
We present a proof of concept of an AR approach for sentinel lymph node biopsy by ex vivo experiments. The 3D position of the radioactive $$\gamma $$
γ
-sources is reconstructed from a single $$\gamma $$
γ
-image, acquired by a stationary table-attached multi-pinhole $$\gamma $$
γ
-detector. The position of the sources is then visualized using Microsoft’s HoloLens. We further investigate the performance of our SLNF algorithm for a single source, two sources, and two sources with a hot background.
Results
In our ex vivo experiments, a single $$\gamma $$
γ
-source and its AR representation show good correlation with known locations, with a maximum error of 4.47 mm. The SLNF algorithm performs well when only one source is reconstructed, with a maximum error of 7.77 mm. For the more challenging case to reconstruct two sources, the errors vary between 2.23 mm and 75.92 mm.
Conclusion
This proof of concept shows promising results in reconstructing and displaying one $$\gamma $$
γ
-source. Two simultaneously recorded sources are more challenging and require further algorithmic optimization.
Funder
University of Basel
Publisher
Springer Science and Business Media LLC
Subject
Health Informatics,Radiology, Nuclear Medicine and imaging,General Medicine,Surgery,Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Vision and Pattern Recognition,Biomedical Engineering
Reference15 articles.
1. de Bree R, de Keizer B, Civantos FJ, Takes RP, Rodrigo JP, Hernandez-Prera JC, Halmos GB, Rinaldo A, Ferlito A (2021) What is the role of sentinel lymph node biopsy in the management of oral cancer in 2020? Eur Arch Otorhinolaryngol 278(9):3181–3191 2. Tartaglione G, Stoeckli SJ, De ree R, Schilling C, Flach GB, Bakholdt V, Sorensen JA, Bilde A, Von Buchwald C, Lawson G, Dequanter D, Villarreal PM, Forcelledo MFF, Amezaga JA, Moreira A, Poli T, Grandi C, Vigili MG, O’Doherty M, Donner D, Bloemena E, Rahimi S, Gurney B, Haerle SK, Broglie MA, Huber GF, Krogdah AL, Sebbesen LR, Odell E, Gutierrez LMJ, Barbier L, Santamaria-Zuazua J, Jacome M, Nollevaux MC, Bragantini E, Lothaire P, Silini EM, Sesenna E, Dolivet G, Mastronicola R, Leroux A, Sassoon I, Sloan P, Colletti PM, Rubello D, McGurk M (2016) Sentinel node in oral cancer: The nuclear medicine aspects. A survey from the sentinel European node trial. Clin Nucl Med 41(7):534–542 3. Liebmann F, Roner S, von Atzigen M, Scaramuzza D, Sutter R, Snedeker J, Farshad M, F’’urnstahl P (2019) Pedicle screw navigation using surface digitization on the microsoft hololens. Int J Comput Assist Radiol Surg 14(7):1157–1165 4. Żelechowski M, Karnam M, Faludi B, Gerig N, Rauter G, Cattin PC (2021) Patient positioning by visualising surgical robot rotational workspace in augmented reality. Comput Meth Biomech Biomed Eng: Imag Visualiz 00(00):1–7 5. Henrich B, Bergamaschi A, Broennimann C, Dinapoli R, Eikenberry EF, Johnson I, Kobas M, Kraft P, Mozzanica A, Schmitt B (2009) PILATUS: a single photon counting pixel detector for X-ray applications. Nucl Instrum Meth Phys Res, Sect A 607(1):247–249
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