http://www.cnr.it/ontology/cnr/individuo/prodotto/ID174577

Software to calculate vessel distributions in tissues (Software)

Type

Prodotto della ricerca (Classe)
Software (Classe)

Label

Software to calculate vessel distributions in tissues (Software) (literal)

Anno

2009-01-01T00:00:00+01:00 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi

10.1038/labinvest.2009.76 (literal)

Alternative label

Marco Righi (2009)
Software to calculate vessel distributions in tissues
(literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

Marco Righi (literal)

Pagina inizio

1063 (literal)

Pagina fine

1070 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni

Please find enclosed to this record the files of the macros previously described. The same files can be downloaded from a web site of the IN - Milan section at the URL http://www.fcm.in.cnr.it/H-index/software.htm or from the News page of the official ImageJ site at the URL http://rsbweb.nih.gov/ij/notes.html. This last link is located close to the date August 24, 2009. (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url

http://www.fcm.in.cnr.it/H-index/software.htm (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume

89 (literal)

Rivista

Laboratory investigation (Rivista)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali

7 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

CNR - Istituto Neuroscienze - Milano (literal)

Titolo

Software to calculate vessel distributions in tissues (literal)

Descrizione sintetica

The following ImageJ macros allow to calculate the distribution state of a set of elements on the basis of their space-filling properties. In the reference publication they have been applied to the dispersion of tumor vessels in nodules treated, or not, with antiangiogenic drugs. Single Folder Analyzing a set of images in a folder * This macro calculates the distribution/space-filling indexes (H) of black pixels for each bitmap image of a set, grouped in a folder. H indexes are calculated through alternated convolutions of 3x3 square and cross kernels. Two permeation curves are constructed starting with one or the other kernel and results are interpolated to obtain index values. The macro is limited to the analysis of images with H indexes lower than 500. * The percentage of initial black pixels is calculated for every image (binary - inverted LUT) of the folder and the maximal value obtained is set as the normalization value. * The macro generates an output .txt file reporting the normalization value, initial area covered by black pixels together with raw and normalized H90%, H95% and H99% indexes. * Version 1.1 created 07.03.2008 Multi Folders Analyzing multiple folders grouped in a folder * The advantage of this macro resides in the possibility to analyze a number of indipendent folders, each containing a set of images, nested in a higher level folder. Image normalization is calculated indipendently for each folder. To normalize the H-index of all images in all folders against a common (maximal) value it is suggested to add the image showing that value to each single folder to be analyzed. * This macro generates a number of output .txt files, one for each analyzed folder, reporting the same type of data as in the single-folder macro. * Version 1.0 created 31.07.2008 (literal)

Abstract

Experimental approaches currently used to quantify the activity of antiangiogenic treatments in cancer therapy do not generally address the importance of spatial distribution of microvessels in target tissues. We report a new computerized method to assess tumor vascularization by quantifying the distribution of functional microvessels as revealed by in vivo staining with sulfosuccinimidyl-6-(biotinamido) hexanoate. Our approach was based on pixel dilation of digital images of blood vessels and addressed the space-filling property of the vessel layouts. This was practically achieved computing the number of dilation cycles (Halo index) needed to permeate a pre-defined amount of each image. Our approach was validated on human tumor xenografts in nonobese diabetic/severe combined immunodeficient mice treated with the antiangiogenic drug sorafenib. For each experimental model, area normalization allowed the unbiased comparison of several hundreds of images showing different amounts of vascular tissue. In two different tumor types, comparison of Halo values showed statistically significant differences between control and sorafenib-treated samples. Conversely, this effect was not observed in samples from an additional xenograft known to resist the antiangiogenic treatment. By separating the analysis of vessel area from the quantification of vessel distributions, our approach can potentially contribute to a better evaluation of the antiangiogenic or vascular-disrupting activity of new drugs or treatments. (literal)

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