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Diagnosis of tumors during tissue-conserving surgery with integrated autofluorescence and Raman scattering microscopy

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, September 2013
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

news
10 news outlets
twitter
3 tweeters
patent
4 patents
peer_reviews
1 peer review site
weibo
1 weibo user

Citations

dimensions_citation
138 Dimensions

Readers on

mendeley
158 Mendeley
citeulike
2 CiteULike
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Title
Diagnosis of tumors during tissue-conserving surgery with integrated autofluorescence and Raman scattering microscopy
Published in
Proceedings of the National Academy of Sciences of the United States of America, September 2013
DOI 10.1073/pnas.1311289110
Pubmed ID
Authors

K. Kong, C. J. Rowlands, S. Varma, W. Perkins, I. H. Leach, A. A. Koloydenko, H. C. Williams, I. Notingher

Abstract

Tissue-conserving surgery is used increasingly in cancer treatment. However, one of the main challenges in this type of surgery is the detection of tumor margins. Histopathology based on tissue sectioning and staining has been the gold standard for cancer diagnosis for more than a century. However, its use during tissue-conserving surgery is limited by time-consuming tissue preparation steps (1-2 h) and the diagnostic variability inherent in subjective image interpretation. Here, we demonstrate an integrated optical technique based on tissue autofluorescence imaging (high sensitivity and high speed but low specificity) and Raman scattering (high sensitivity and high specificity but low speed) that can overcome these limitations. Automated segmentation of autofluorescence images was used to select and prioritize the sampling points for Raman spectroscopy, which then was used to establish the diagnosis based on a spectral classification model (100% sensitivity, 92% specificity per spectrum). This automated sampling strategy allowed objective diagnosis of basal cell carcinoma in skin tissue samples excised during Mohs micrographic surgery faster than frozen section histopathology, and one or two orders of magnitude faster than previous techniques based on infrared or Raman microscopy. We also show that this technique can diagnose the presence or absence of tumors in unsectioned tissue layers, thus eliminating the need for tissue sectioning. This study demonstrates the potential of this technique to provide a rapid and objective intraoperative method to spare healthy tissue and reduce unnecessary surgery by determining whether tumor cells have been removed.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 158 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 1%
Canada 2 1%
Germany 1 <1%
France 1 <1%
Belgium 1 <1%
Japan 1 <1%
Unknown 150 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 48 30%
Researcher 35 22%
Student > Master 19 12%
Student > Doctoral Student 7 4%
Other 6 4%
Other 21 13%
Unknown 22 14%
Readers by discipline Count As %
Engineering 26 16%
Physics and Astronomy 23 15%
Chemistry 21 13%
Medicine and Dentistry 20 13%
Agricultural and Biological Sciences 17 11%
Other 26 16%
Unknown 25 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 88. 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 12 December 2018.
All research outputs
#221,232
of 14,789,565 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#4,823
of 83,408 outputs
Outputs of similar age
#2,676
of 163,822 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#91
of 916 outputs
Altmetric has tracked 14,789,565 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 83,408 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.4. This one has done particularly well, scoring higher than 94% 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 163,822 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 916 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.