PMID- 33855974
OWN - NLM
STAT- MEDLINE
DCOM- 20210920
LR  - 20220416
IS  - 1558-8238 (Electronic)
IS  - 0021-9738 (Print)
IS  - 0021-9738 (Linking)
VI  - 131
IP  - 8
DP  - 2021 Apr 15
TI  - Artificial intelligence for automating the measurement of histologic image 
      biomarkers.
LID - 147966 [pii]
LID - 10.1172/JCI147966 [doi]
LID - e147966
AB  - Artificial intelligence has been applied to histopathology for decades, but the 
      recent increase in interest is attributable to well-publicized successes in the 
      application of deep-learning techniques, such as convolutional neural networks, 
      for image analysis. Recently, generative adversarial networks (GANs) have 
      provided a method for performing image-to-image translation tasks on 
      histopathology images, including image segmentation. In this issue of the JCI, 
      Koyuncu et al. applied GANs to whole-slide images of p16-positive oropharyngeal 
      squamous cell carcinoma (OPSCC) to automate the calculation of a multinucleation 
      index (MuNI) for prognostication in p16-positive OPSCC. Multivariable analysis 
      showed that the MuNI was prognostic for disease-free survival, overall survival, 
      and metastasis-free survival. These results are promising, as they present a 
      prognostic method for p16-positive OPSCC and highlight methods for using deep 
      learning to measure image biomarkers from histopathologic samples in an 
      inherently explainable manner.
FAU - Cornish, Toby C
AU  - Cornish TC
LA  - eng
PT  - Comment
PT  - Journal Article
PL  - United States
TA  - J Clin Invest
JT  - The Journal of clinical investigation
JID - 7802877
RN  - 0 (Biomarkers)
SB  - IM
CON - J Clin Invest. 2021 Apr 15;131(8):. PMID: 33651718
MH  - *Artificial Intelligence
MH  - Biomarkers
MH  - *Head and Neck Neoplasms
MH  - Humans
MH  - Image Processing, Computer-Assisted
MH  - Neural Networks, Computer
PMC - PMC8262491
COIS- Conflict of interest: TCC is a paid advisory board member for Leica Biosystems 
      (Advanced Staining and Imaging Advisory Board) and Bristol Myers Squibb (Ozanimod 
      GI Pathologists Advisory Board). He is a co-inventor of US patent 9,214,019, 
      "Method and System to Digitize Pathology Slides in a Stepwise Fashion for 
      Review."
EDAT- 2021/04/16 06:00
MHDA- 2021/09/21 06:00
PMCR- 2022/04/15
CRDT- 2021/04/15 08:41
PHST- 2021/04/15 08:41 [entrez]
PHST- 2021/04/16 06:00 [pubmed]
PHST- 2021/09/21 06:00 [medline]
PHST- 2022/04/15 00:00 [pmc-release]
AID - 147966 [pii]
AID - 10.1172/JCI147966 [doi]
PST - ppublish
SO  - J Clin Invest. 2021 Apr 15;131(8):e147966. doi: 10.1172/JCI147966.