Literature DB >> 12632015

An original approach for quantification of blood vessels on the whole tumour section.

Nga Tran Kim1, Nicolas Elie, Benoît Plancoulaine, Paulette Herlin, Michel Coster.   

Abstract

Relative abundance of tumour angiogenesis has been shown to be of clinical relevance in cancers of various locations such as the ovary. Nevertheless, several problems are encountered when quantifying tumour microvessels: (i) as many other tumour markers, vascularity pattern is often heterogeneous within the tumour mass and even within the same histological section. As a consequence, an adequate acquisition method must be developed for accurate field sampling. (ii) Manual microvessel counting is long, tedious and subject to poor reproducibility. Introduction in routine practice requires a fast, reproducible and reliable automatic image processing. In this study we present an original procedure combining a slide scanner image acquisition and a fully automatic image analysis sequence. The slide scanner offers the advantage of recording an image of the whole histological section for subsequent automatic blood vessel detection and hot spot area location. Microvessel density and surface fraction were measured for the whole section as well as within hot spots. Different immunostaining methods were tested in order to optimise the procedure. Moreover, the method proposed was submitted to a quality control procedure, with reference to interactive identification of microvessels at scanner level. This experiment showed that 93 to 97% of blood vessels were detected, according to the staining protocol used. Colour figures can be viewed on http://www.esacp.org/acp/2003/25-2/kim.htm.

Entities:  

Mesh:

Year:  2003        PMID: 12632015      PMCID: PMC4618584          DOI: 10.1155/2003/473902

Source DB:  PubMed          Journal:  Anal Cell Pathol        ISSN: 0921-8912            Impact factor:   2.916


  8 in total

Review 1.  Automated image analysis programs for the quantification of microvascular network characteristics.

Authors:  Kristen T Morin; Paul D Carlson; Robert T Tranquillo
Journal:  Methods       Date:  2015-04-02       Impact factor: 3.608

Review 2.  Mapping spatial heterogeneity in the tumor microenvironment: a new era for digital pathology.

Authors:  Andreas Heindl; Sidra Nawaz; Yinyin Yuan
Journal:  Lab Invest       Date:  2015-01-19       Impact factor: 5.662

3.  Orchestrating the Dermal/Epidermal Tissue Ratio during Wound Healing by Controlling the Moisture Content.

Authors:  Alexandru-Cristian Tuca; Ives Bernardelli de Mattos; Martin Funk; Raimund Winter; Alen Palackic; Florian Groeber-Becker; Daniel Kruse; Fabian Kukla; Thomas Lemarchand; Lars-Peter Kamolz
Journal:  Biomedicines       Date:  2022-05-31

4.  Digital microscopy assessment of angiogenesis in different breast cancer compartments.

Authors:  Anca Haisan; Radu Rogojanu; Camelia Croitoru; Daniela Jitaru; Cristina Tarniceriu; Mihai Danciu; Eugen Carasevici
Journal:  Biomed Res Int       Date:  2013-09-01       Impact factor: 3.411

5.  Computer-aided Image Processing of Angiogenic Histological.

Authors:  Matvey Sprindzuk; Alexander Dmitruk; Vassili Kovalev; Armen Bogush; Alexander Tuzikov; Victor Liakhovski; Mikhail Fridman
Journal:  J Clin Med Res       Date:  2009-12-28

6.  Osteosarcoma microenvironment: whole-slide imaging and optimized antigen detection overcome major limitations in immunohistochemical quantification.

Authors:  Pierre Kunz; Jörg Fellenberg; Linda Moskovszky; Zoltan Sápi; Tibor Krenacs; Johannes Poeschl; Burkhard Lehner; Miklos Szendrõi; Volker Ewerbeck; Ralf Kinscherf; Benedikt Fritzsching
Journal:  PLoS One       Date:  2014-03-03       Impact factor: 3.240

7.  Effect of an anti-human Co-029/tspan8 mouse monoclonal antibody on tumor growth in a nude mouse model.

Authors:  Naouel Ailane; Céline Greco; Yingying Zhu; Monica Sala-Valdés; Martine Billard; Ibrahim Casal; Olivia Bawa; Paule Opolon; Eric Rubinstein; Claude Boucheix
Journal:  Front Physiol       Date:  2014-09-19       Impact factor: 4.566

8.  Quantification metrics for telangiectasia using optical coherence tomography.

Authors:  Jillian L Cardinell; Joel M Ramjist; Chaoliang Chen; Weisong Shi; Nhu Q Nguyen; Tiffany Yeretsian; Matthew Choi; David Chen; Dewi S Clark; Anne Curtis; Helen Kim; Marie E Faughnan; Victor X D Yang
Journal:  Sci Rep       Date:  2022-02-02       Impact factor: 4.379

  8 in total

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