↓ Skip to main content

Multimodal US–gamma imaging using collaborative robotics for cancer staging biopsies

Overview of attention for article published in International Journal of Computer Assisted Radiology and Surgery, August 2016
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

twitter
1 X user
patent
2 patents

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
34 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Multimodal US–gamma imaging using collaborative robotics for cancer staging biopsies
Published in
International Journal of Computer Assisted Radiology and Surgery, August 2016
DOI 10.1007/s11548-016-1464-6
Pubmed ID
Authors

Marco Esposito, Benjamin Busam, Christoph Hennersperger, Julia Rackerseder, Nassir Navab, Benjamin Frisch

Abstract

The staging of female breast cancer requires detailed information about the level of cancer spread through the lymphatic system. Common practice to obtain this information for patients with early-stage cancer is sentinel lymph node (SLN) biopsy, where LNs are radioactively identified for surgical removal and subsequent histological analysis. Punch needle biopsy is a less invasive approach but suffers from the lack of combined anatomical and nuclear information. We present and evaluate a system that introduces live collaborative robotic 2D gamma imaging in addition to live 2D ultrasound to identify SLNs in the surrounding anatomy. The system consists of a robotic arm equipped with both a gamma camera and a stereoscopic tracking system that monitors the position of an ultrasound probe operated by the physician. The arm cooperatively places the gamma camera parallel to the ultrasound imaging plane to provide live multimodal visualization and guidance. We validate the system by evaluating the target registration errors between fused nuclear and US image data in a phantom consisting of two spheres, one of which is filled with radioactivity. Medical experts perform punch biopsies on agar-gelatine phantoms with complex configurations of hot and cold lesions to provide a qualitative and quantitative evaluation of the system. The average point registration error for the overlay is [Formula: see text] mm. The time of the entire procedure was reduced by 36 %, with 80v of the biopsies being successful. The users' feedback was very positive, and the system was deemed to be very intuitive, with handling similar to classic US-guided needle biopsy. We present and evaluate the first medical collaborative robotic imaging system. Feedback from potential users for SLN punch needle biopsy is encouraging. Ongoing work investigates the clinical feasibility with more complex and realistic phantoms.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 24%
Researcher 5 15%
Student > Ph. D. Student 5 15%
Student > Bachelor 4 12%
Student > Doctoral Student 2 6%
Other 4 12%
Unknown 6 18%
Readers by discipline Count As %
Medicine and Dentistry 9 26%
Computer Science 8 24%
Engineering 7 21%
Biochemistry, Genetics and Molecular Biology 1 3%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Other 2 6%
Unknown 6 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 January 2024.
All research outputs
#5,304,682
of 25,323,244 outputs
Outputs from International Journal of Computer Assisted Radiology and Surgery
#94
of 949 outputs
Outputs of similar age
#88,370
of 372,157 outputs
Outputs of similar age from International Journal of Computer Assisted Radiology and Surgery
#2
of 15 outputs
Altmetric has tracked 25,323,244 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 949 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done well, scoring higher than 89% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 372,157 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.