Platform for Quantitative Evaluation of Spatial Intratumoral Heterogeneity in Multiplexed Fluorescence Images

We introduce THRIVE (Tumor Heterogeneity Research Interactive Visualization Environment), an open-source tool developed to assist cancer researchers in interactive hypothesis testing. The focus of this tool is to quantify spatial intratumoral heterogeneity (ITH), and the interactions between differe...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Cancer research (Chicago, Ill.) Ročník 77; číslo 21; s. e71
Hlavní autori: Spagnolo, Daniel M, Al-Kofahi, Yousef, Zhu, Peihong, Lezon, Timothy R, Gough, Albert, Stern, Andrew M, Lee, Adrian V, Ginty, Fiona, Sarachan, Brion, Taylor, D Lansing, Chennubhotla, S Chakra
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States 01.11.2017
Predmet:
Algorithms
Genetic Heterogeneity
Humans
Image Processing, Computer-Assisted - methods
Neoplasms - genetics
Neoplasms - pathology
Optical Imaging - methods
Optical Imaging - statistics & numerical data
Software
Tissue Array Analysis - statistics & numerical data
ISSN:1538-7445, 1538-7445
On-line prístup:Zistit podrobnosti o prístupe
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:We introduce THRIVE (Tumor Heterogeneity Research Interactive Visualization Environment), an open-source tool developed to assist cancer researchers in interactive hypothesis testing. The focus of this tool is to quantify spatial intratumoral heterogeneity (ITH), and the interactions between different cell phenotypes and noncellular constituents. Specifically, we foresee applications in phenotyping cells within tumor microenvironments, recognizing tumor boundaries, identifying degrees of immune infiltration and epithelial/stromal separation, and identification of heterotypic signaling networks underlying microdomains. The THRIVE platform provides an integrated workflow for analyzing whole-slide immunofluorescence images and tissue microarrays, including algorithms for segmentation, quantification, and heterogeneity analysis. THRIVE promotes flexible deployment, a maintainable code base using open-source libraries, and an extensible framework for customizing algorithms with ease. THRIVE was designed with highly multiplexed immunofluorescence images in mind, and, by providing a platform to efficiently analyze high-dimensional immunofluorescence signals, we hope to advance these data toward mainstream adoption in cancer research. .
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1538-7445
1538-7445
DOI:10.1158/0008-5472.CAN-17-0676