PMID- 26799613
OWN - NLM
STAT- MEDLINE
DCOM- 20160708
LR  - 20240327
IS  - 1932-6203 (Electronic)
IS  - 1932-6203 (Linking)
VI  - 11
IP  - 1
DP  - 2016
TI  - Structured Illumination Microscopy and a Quantitative Image Analysis for the 
      Detection of Positive Margins in a Pre-Clinical Genetically Engineered Mouse 
      Model of Sarcoma.
PG  - e0147006
LID - 10.1371/journal.pone.0147006 [doi]
LID - e0147006
AB  - Intraoperative assessment of surgical margins is critical to ensuring residual 
      tumor does not remain in a patient. Previously, we developed a fluorescence 
      structured illumination microscope (SIM) system with a single-shot field of view 
      (FOV) of 2.1 x 1.6 mm (3.4 mm2) and sub-cellular resolution (4.4 mum). The goal of 
      this study was to test the utility of this technology for the detection of 
      residual disease in a genetically engineered mouse model of sarcoma. Primary soft 
      tissue sarcomas were generated in the hindlimb and after the tumor was surgically 
      removed, the relevant margin was stained with acridine orange (AO), a vital stain 
      that brightly stains cell nuclei and fibrous tissues. The tissues were imaged 
      with the SIM system with the primary goal of visualizing fluorescent features 
      from tumor nuclei. Given the heterogeneity of the background tissue (presence of 
      adipose tissue and muscle), an algorithm known as maximally stable extremal 
      regions (MSER) was optimized and applied to the images to specifically segment 
      nuclear features. A logistic regression model was used to classify a tissue site 
      as positive or negative by calculating area fraction and shape of the segmented 
      features that were present and the resulting receiver operator curve (ROC) was 
      generated by varying the probability threshold. Based on the ROC curves, the 
      model was able to classify tumor and normal tissue with 77% sensitivity and 81% 
      specificity (Youden's index). For an unbiased measure of the model performance, 
      it was applied to a separate validation dataset that resulted in 73% sensitivity 
      and 80% specificity. When this approach was applied to representative whole 
      margins, for a tumor probability threshold of 50%, only 1.2% of all regions from 
      the negative margin exceeded this threshold, while over 14.8% of all regions from 
      the positive margin exceeded this threshold.
FAU - Fu, Henry L
AU  - Fu HL
AD  - Department of Biomedical Engineering, Duke University, Durham, North Carolina, 
      United States of America.
FAU - Mueller, Jenna L
AU  - Mueller JL
AD  - Department of Biomedical Engineering, Duke University, Durham, North Carolina, 
      United States of America.
FAU - Whitley, Melodi J
AU  - Whitley MJ
AD  - Department of Pharmacology & Cancer Biology, Duke University School of Medicine, 
      Durham, North Carolina, United States of America.
FAU - Cardona, Diana M
AU  - Cardona DM
AD  - Department of Pathology, Duke University School of Medicine, Durham, North 
      Carolina, United States of America.
FAU - Willett, Rebecca M
AU  - Willett RM
AD  - Department of Electrical and Computer Engineering, University of 
      Wisconsin-Madison, Madison, Wisconsin, United States of America.
FAU - Kirsch, David G
AU  - Kirsch DG
AD  - Department of Pharmacology & Cancer Biology, Duke University School of Medicine, 
      Durham, North Carolina, United States of America.
AD  - Department of Radiation Oncology, Duke University School of Medicine, Durham, 
      North Carolina, United States of America.
FAU - Brown, J Quincy
AU  - Brown JQ
AD  - Department of Biomedical Engineering, Tulane University, New Orleans, Louisiana, 
      United States of America.
FAU - Ramanujam, Nimmi
AU  - Ramanujam N
AD  - Department of Biomedical Engineering, Duke University, Durham, North Carolina, 
      United States of America.
LA  - eng
GR  - R01 EB011574/EB/NIBIB NIH HHS/United States
GR  - R21 CA159936/CA/NCI NIH HHS/United States
GR  - T32 GM007171/GM/NIGMS NIH HHS/United States
GR  - 1R01EB011574-01/EB/NIBIB NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
DEP - 20160122
PL  - United States
TA  - PLoS One
JT  - PloS one
JID - 101285081
SB  - IM
MH  - Animals
MH  - *Disease Models, Animal
MH  - *Genetic Engineering
MH  - Mice
MH  - Microscopy, Fluorescence/*methods
MH  - Sarcoma/genetics/*pathology
PMC - PMC4723137
COIS- Competing Interests: Dr. Ramanujam has founded a company called Zenalux 
      Biomedical and she and other team members have developed technologies related to 
      this work where the investigators or Duke University may benefit financially if 
      this system is sold commercially. Dr. Kirsch consults for and owns stock in 
      Lumicell Diagnoistics, which is a company commercializing intraoperative imaging 
      systems. This does not alter the authors' adherence to all the PLOS ONE policies 
      on sharing data and materials. The other authors declare no competing financial 
      interests.
EDAT- 2016/01/23 06:00
MHDA- 2016/07/09 06:00
PMCR- 2016/01/22
CRDT- 2016/01/23 06:00
PHST- 2015/02/13 00:00 [received]
PHST- 2015/12/28 00:00 [accepted]
PHST- 2016/01/23 06:00 [entrez]
PHST- 2016/01/23 06:00 [pubmed]
PHST- 2016/07/09 06:00 [medline]
PHST- 2016/01/22 00:00 [pmc-release]
AID - PONE-D-15-06859 [pii]
AID - 10.1371/journal.pone.0147006 [doi]
PST - epublish
SO  - PLoS One. 2016 Jan 22;11(1):e0147006. doi: 10.1371/journal.pone.0147006. 
      eCollection 2016.