PMID- 32488381
OWN - NLM
STAT- MEDLINE
DCOM- 20210428
LR  - 20210428
IS  - 1434-4726 (Electronic)
IS  - 0937-4477 (Print)
IS  - 0937-4477 (Linking)
VI  - 277
IP  - 10
DP  - 2020 Oct
TI  - Evaluation of digital image analysis as a supportive tool for the stratification 
      of head and neck vascular anomalies.
PG  - 2893-2906
LID - 10.1007/s00405-020-06097-2 [doi]
AB  - BACKGROUND: The histological differentiation of individual types of vascular 
      anomalies (VA), such as lymphatic malformations (LM), hemangioma (Hem), 
      paraganglioma (PG), venous malformations (VeM), arteriovenous malformations 
      (AVM), pyogenic granulomas (GP), and (not otherwise classified) vascular 
      malformations (VM n.o.c.) is frequently difficult due to the heterogeneity of 
      these anomalies. The aim of the study was to evaluate digital image analysis as a 
      method for VA stratification METHODS: A total of 40 VA tissues were examined 
      immunohistologically using a selection of five vascular endothelial-associated 
      markers (CD31, CD34, CLDN5, PDPN, VIM). The staining results were documented 
      microscopically followed by digital image analyses based quantification of the 
      candidate-marker-proteins using the open source program ImageJ/Fiji. RESULTS: 
      Differences in the expression patterns of the candidate proteins could be 
      detected particularly when deploying the quotient of the quantified 
      immunohistochemical signal values. Deploying signal marker quotients, LM could be 
      fully distinguished from all other tested tissue types. GP achieved 
      stratification from LM, Hem, VM, PG and AVM tissues, whereas Hem, PG, VM and AVM 
      exhibited significantly different signal marker quotients compared with LM and GP 
      tissues. CONCLUSION: Although stratification of different VA from each other was 
      only achieved in part with the markers used, the results of this study strongly 
      support the usefulness of digital image analysis for the stratification of VA. 
      Against the background of upcoming new diagnostic techniques involving artificial 
      intelligence and deep (machine) learning, our data serve as a paradigm of how 
      digital evaluation methods can be deployed to support diagnostic decision making 
      in the field of VAs.
FAU - Ehrenreich, Jovine
AU  - Ehrenreich J
AD  - Department of Otorhinolaryngology, Head and Neck Surgery, University Hospital 
      Marburg, Philipps-Universitat Marburg, 3. BA, +3/08070 Baldingerstrasse, 35033, 
      Marburg, Germany.
FAU - Bette, Michael
AU  - Bette M
AD  - Institute of Anatomy and Cell Biology, Philipps-Universitat Marburg, Marburg, 
      Germany.
FAU - Schmidt, Ansgar
AU  - Schmidt A
AD  - Institute of Pathology, University Hospital Giessen and Marburg, Marburg, 
      Germany.
FAU - Roessler, Marion
AU  - Roessler M
AD  - Institute of Pathology, University Hospital Giessen and Marburg, Marburg, 
      Germany.
FAU - Bakowsky, Udo
AU  - Bakowsky U
AD  - Department of Pharmaceutical Technology and Biopharmacy, Philipps-Universitat 
      Marburg, Marburg, Germany.
FAU - Geisthoff, Urban W
AU  - Geisthoff UW
AD  - Department of Otorhinolaryngology, Head and Neck Surgery, University Hospital 
      Marburg, Philipps-Universitat Marburg, 3. BA, +3/08070 Baldingerstrasse, 35033, 
      Marburg, Germany.
FAU - Stuck, Boris A
AU  - Stuck BA
AD  - Department of Otorhinolaryngology, Head and Neck Surgery, University Hospital 
      Marburg, Philipps-Universitat Marburg, 3. BA, +3/08070 Baldingerstrasse, 35033, 
      Marburg, Germany.
FAU - Mandic, Robert
AU  - Mandic R
AUID- ORCID: 0000-0003-2379-5515
AD  - Department of Otorhinolaryngology, Head and Neck Surgery, University Hospital 
      Marburg, Philipps-Universitat Marburg, 3. BA, +3/08070 Baldingerstrasse, 35033, 
      Marburg, Germany. mandic@med.uni-marburg.de.
LA  - eng
PT  - Journal Article
DEP - 20200602
PL  - Germany
TA  - Eur Arch Otorhinolaryngol
JT  - European archives of oto-rhino-laryngology : official journal of the European 
      Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the 
      German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
JID - 9002937
SB  - IM
MH  - Artificial Intelligence
MH  - Head
MH  - *Hemangioma/diagnostic imaging
MH  - Humans
MH  - Neck
MH  - *Vascular Malformations/diagnostic imaging
PMC - PMC7496082
OTO - NOTNLM
OT  - Digital image analysis
OT  - Head and neck
OT  - Immunohistochemistry
OT  - Stratification
OT  - Vascular anomaly
COIS- The authors declare that they have no conflict of interest.
EDAT- 2020/06/04 06:00
MHDA- 2021/04/29 06:00
PMCR- 2020/06/02
CRDT- 2020/06/04 06:00
PHST- 2020/03/12 00:00 [received]
PHST- 2020/05/27 00:00 [accepted]
PHST- 2020/06/04 06:00 [pubmed]
PHST- 2021/04/29 06:00 [medline]
PHST- 2020/06/04 06:00 [entrez]
PHST- 2020/06/02 00:00 [pmc-release]
AID - 10.1007/s00405-020-06097-2 [pii]
AID - 6097 [pii]
AID - 10.1007/s00405-020-06097-2 [doi]
PST - ppublish
SO  - Eur Arch Otorhinolaryngol. 2020 Oct;277(10):2893-2906. doi: 
      10.1007/s00405-020-06097-2. Epub 2020 Jun 2.