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Lung | Detection of NSCLC | PD-L1

The first AI solution for PD-L1 to detect and quantify diagnostically relevant cells in non-small-cell lung carcinoma (NSCLC)

The first AI solution for PD-L1 supports cancer experts in the challenging assessment of PD-L1 stained lung tissue. It identifies tumorous and inflammatory cells and quantifies them to support scoring. Mindpeak PD-L1 Quantifier for NSCLC helps to achieve accurate results without the need of manual fine-tuning. It is optimized to account for the typical lab-specific variations and supports tissue slides stained with the most common PD-L1 clones.
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Mindpeak PD-L1 Quantifier is Research Use Only, not for use in diagnostic procedures.
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Detailed information on Mindpeak PD-L1 Quantifier

Quantification/Detection output variables

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Number of positive and negative tumor cells and positive immune cells; Tumor positive score (TPS), Combined positive score (CPS).

Workflow

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Step 1: Open or upload the PD-L1 image / whole-slide image.

Please note that images work best at 20-40x resolution.


Step 2: Select the region of interest for analysis and see that it only takes a couple of seconds to process.


Step 3: Adapt the analysis results to fit your assessment.

You can change the classification of a single cell just clicking on it once and Mindpeak PD-L1 Quantifier will automatically update the result. Double click on a cell or on an empty area to add or remove cells. Select a specific area to analyse and the quantification will only be applied to the selected area.


Step 4: Get your score results on the left side menu.

Architectural model

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Proprietary AI model for cell detection in membrane IHC-stainings based on convolutional neural networks.

System requirements

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Standard personal working machine. Minimum requirements: 32 bit Processor Intel Core i5 or better; 4 GB RAM.

File format capability

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All major whole slide image formats: (tif, mrxs, etc.), png, jpg/jpeg.

Keywords

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Lung, Cell quantification, Cell detection, IHC Membrane, Non-Small Cell Lung Cancer (NSCLC), Membrane Staining, PD-L1, Deep learning, Artificial Intelligence, Image analysis.

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Detection and quantification of relevant cells in NSCLC

Identification & Quantification

Mindpeak PD-L1 Quantifier for NSCLC assists experts in the challenging assessment of PD-L1 stained lung tissue. Our solution identifies and quantifies tumorous cells as well as inflammatory cells to support tissue scoring.

Accurate Results

Our PD-L1 Quantifier for NSCLC provides accurate results even in challenging contexts as it was developed with typical lab-specific variations in mind, such as pre-analytical slide preparation and different staining antibodies.

Easy Integration

It supports most scanners and microscope cameras and can easily be integrated into existing software.

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