TRIBVN has been developping a solution for
Tissue Micro Array (TMA) which allows to perform quantitavtive studies on TMA virtual slides produced by a
or a digital scanner.
The solution enables researchers to identify and score TMA cores and to analyze them with a dedicated algorithm.
Cores automatic identification:
the manual identification is often tiresome and cause of mistakes. Thanks to the Crop function,
the TRIBVN solution uses the file from Arrayer to automatically detect
crop and identify cores even on slides with high density and with damaged or distorted grid.
Cores annotation: The Score function
allows you to define a structured reading grid
adapted to your TMA and to browse from cores to cores to score very quickly your slide.
You can display several cores or several slides in the same time and synchronize them for a
comparison or an accelarated scoring. Each core is read at the magnification of your choice
with the same functions of annotation and browsing used for virtual slides.
Automatic cores quantification: All the TRIBVN image
analysis macros can be used on TMA cores, and notably Immuno.
After manual or automatic determination of the regions of analysis, the quantification macro is automatically
applied to certain or all of the cores on one slide or on a serie of identical slides.
The retrieval and quantification of nuclear, cytoplasmic and membrane staining becomes automatic,
reliable and robust. Thus, you have an efficient and standardized solution for high throughput screening.
Export of cores' annotation and quantification results: All the results generated around cores are exportable within Excel for a
quantitative and statistic processing. Thus you have reliable datas for your studies in clinical biostatistic.
Datas storage: All the images and datas produced during your TMA work are stored in the TRIBVN database linked to the initial virtual slide and raw data.
You can then perform powerful queries looking for slides or cores based on specimen identification, pathology exam number, technical,
and even on the results from manual annotation or automatic quantification.