All slides were scanned with a Zeiss Axio Scan Z.1 digital slide scanner at 20x. Semi-automated, quantitative analysis was performed for scanned slides using HALO v2.2 software (Indica Labs). All analyses were performed by a technician blinded to experimental group. User-defined thresholds for positive staining were identical across all slides stained under the same conditions. The automated CytoNuclear FL v1 algorithm was used to identify and count positively stained cells. Positive cells were counted as number of cells displaying colocalization of BrdU and nuclear stain. Counted cells met user-set parameters including size limits and intensity thresholds that were applied uniformly across all experimental groups. The number of BrdU positive cells were calculated, and values were expressed as % proliferation (BrdU+DAPI+ cells).
Halo v2
Manufactured by Indica Labs
Sourced in United States
The HALO v2.2 is a comprehensive image analysis software platform developed by Indica Labs. It provides a suite of tools for processing, visualizing, and analyzing digital pathology images. The core function of HALO v2.2 is to enable researchers and clinicians to perform quantitative analysis on a wide range of biological samples, such as histological slides and tissue microarrays.
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Lab products found in correlation
2 protocols using halo v2
1
Quantitative Analysis of Cell Proliferation
2
Multispectral Imaging of Tumor Microenvironment
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Slides were imaged using the Vectra 3.0 and multispectral fluorescent images visualised in Phenochart v.1.0.8 (AKOYA Biosciences). High-resolution images (20×) were captured of the entire tumour and surrounding peritumoural regions. Images were spectrally unmixed in inForm v.2.4.1 (AKOYA Biosciences), and the individual 20× images stitched into a single multispectral image for each tumour specimen for analysis in HALO v.2.2 (Indica Labs, Albuquerque, NM, USA). The Random Forest tissue classifier algorithm was trained to recognise tumour and peritumour based on the presence or absence of SOX10. Positivity for each individual marker was determined by optimised thresholds based on the staining intensity.
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