Compressed Sensing on Multi-pinhole Collimator SPECT Camera for Sentinel Lymph Node Biopsy

Seppi, Carlo; Nahum, Uri; Niederhäusern, Peter A. von; Pezold, Simon; Rissi, M.; Haerle, Stephan K.; Cattin, Philippe C.

doi:10.1007/978-3-319-66185-8_47

Cited by 3 publications

(4 citation statements)

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“…In previous experiments (von Niederhäusern et al 2016, Seppi et al 2017 the collimator in figure 3 was used.…”

Section: Optimal Design Of the Pinhole Distributionmentioning

confidence: 99%

“…Although, Seppi et al (2017) achieved a good localization in the xy-plane, its depth accuracy (z-axis) was limited.…”

Section: Optimal Design Of the Pinhole Distributionmentioning

confidence: 99%

“…We start with 200 possible pinholes (all of them have a diameter of 1 mm), shown in figure 4. In figure 5, the 24 white dots correspond to the resulting 24 pinholes with the highest weight (the number 24 is taken from Seppi et al (2017), to compare the results with the symmetric collimator discussed in this paper) and the big red dots corresponding to the (x, y) position of the source(s) (they were located at a distance of 100-150 mm from the collimator front plate respectively).…”

Section: Optimal Design For Known Sourcesmentioning

confidence: 99%

“…In this publication, we propose a novel multi-pinhole based collimator together with a processing algorithm that overcomes the above mentioned drawbacks. In contrast to our previous work (von Niederhäusern et al 2016, Seppi et al 2017, we introduce here a fast and accurate processing approach, inspired by MR-fingerprinting. Fingerprinting for MR images became very popular in the last years.…”

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confidence: 99%

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Sentinel lymph node fingerprinting

et al. 2019

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Background. When locating the sentinel lymph node (SLN), surgeons use state-of-the-art imaging devices, such as a 1D gamma probe or less widely spread a 2D gamma camera. These devices project the 3D subspace onto a 1D respectively 2D space, hence loosing accuracy and the depth of the SLN which is very important, especially in the head and neck area with many critical structures in close vicinity. Recent methods which use a multi-pinhole collimator and a single gamma detector image try to gain a depth estimation of the SLN. The low intensity of the sources together with the computational cost of the optimization process make the reconstruction in real-time, however, very challenging. Results. In this paper, we use an optimal design approach to improve the classical pinhole design, resulting in a non-symmetric distribution of the pinholes of the collimator. This new design shows a great improvement of the accuracy when reconstructing the position and depth of the radioactive tracer. Then, we introduce our Sentinel lymph node fingerprinting (SLNF) algorithm, inspired by MR-fingerprinting, for fast and accurate reconstruction of the tracer distribution in 3D space using a single gamma detector image. As a further advantage, the method requires no pre-processing, i.e. filtering of the detector image. The method is very stable in its performance even for low exposure times. In our ex vivo experiments, we successfully located multiple Technetium 99m (Tc-99m) sources with an exposure time of only one second and still, with a very small L2-error. Conclusion. These promising results under short exposure time are very encouraging for SLN biopsy. Although, this device has not been tested on patients yet, we believe: that this approach will give the surgeon accurate 3D positions of the SLN and hence, can potentially reduce the trauma for the patient.

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“…In previous experiments (von Niederhäusern et al 2016, Seppi et al 2017 the collimator in figure 3 was used.…”

Section: Optimal Design Of the Pinhole Distributionmentioning

confidence: 99%

“…Although, Seppi et al (2017) achieved a good localization in the xy-plane, its depth accuracy (z-axis) was limited.…”

Section: Optimal Design Of the Pinhole Distributionmentioning

confidence: 99%

Section: Optimal Design For Known Sourcesmentioning

confidence: 99%

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Sentinel lymph node fingerprinting

et al. 2019

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Gamma Source Location Learning from Synthetic Multi-pinhole Collimator Data

Niederhäusern

Seppi

Pezold

et al. 2019

Lecture Notes in Computer Science

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Augmented reality for sentinel lymph node biopsy

von Niederhäusern,

Seppi,

Sandkühler

et al. 2023

Int J CARS

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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.

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Compressed Sensing on Multi-pinhole Collimator SPECT Camera for Sentinel Lymph Node Biopsy

Cited by 3 publications

References 10 publications

Sentinel lymph node fingerprinting

Sentinel lymph node fingerprinting

Gamma Source Location Learning from Synthetic Multi-pinhole Collimator Data

Augmented reality for sentinel lymph node biopsy

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