PD-L1 (CAL10) IHC digital slide (left) with Lung PD-L1 AI markup (right) identifying negative tumor cells (cyan), and positive tumor cells (magenta).

Lunit SCOPE PD-L1 CAL10 NSCLC

Lunit SCOPE is an artificial intelligence (AI)-based digital pathology image analysis software that empowers researchers to improve accuracy, scoring agreement, and workflow efficiency. Lunit SCOPE PD-L1 CAL10 NSCLC assists in the detection and quantification of PD-L1 expression in non-small cell lung cancer (NSCLC) tissue stained with Leica Biosystems’ PD-L1 (CAL10) primary antibody.

Lunit SCOPE PD-L1 CAL10 NSCLC automates tumor proportion score (TPS) calculations and marks up images with tumor detection and cell phenotyping based on PD-L1 (CAL10) staining. The AI-powered algorithm seamlessly integrates with Leica Biosystems’ staining and digital pathology ecosystem to streamline workflows.

Activate AI Now

Lunit SCOPE PD-L1 CAL10 NSCLC is For Research Use Only. Not for use in diagnostic procedures.

Lunit SCOPE PD-L1 CAL10 NSCLC is accessed via the Aperio HALO AP image management system.

Lunit-SCOPE-PD-L1-CAL10-NSCLC-PDL-1-1x-Scanned-tissue-for-workflow

Lunit-SCOPE-PD-L1-CAL10-NSCLC-PDL-1-Results-window

Lunit-SCOPE-PD-L1-CAL10-NSCLC-PDL-1-1x-Mask-Image-for-workslow

Lunit-SCOPE-PD-L1-CAL10-NSCLC-PDL-1-Cell-Counts-for-Workflow

Lunit-SCOPE-PD-L1-CAL10-NSCLC-PDL-1-1x-Scanned-tissue-for-workflow

Zoom image

Step 1: Lung PD-L1 IHC Image

Lunit SCOPE PD-L1 CAL10 NSCLC algorithm can be launched by a user directly in the viewer or configured to automatically run for every Lung PD-L1 image in Aperio HALO AP image management system.

Lunit-SCOPE-PD-L1-CAL10-NSCLC-PDL-1-Results-window

Zoom image

PD-L1 Scoring Metrics

Lunit SCOPE PD-L1 CAL10 NSCLC generates the following metrics as output for within the tumor regions across the image:

Tumor proportion score (TPS)
Total tumor cells
PD-L1 positive tumor cells
PD-L1 negative tumor cells
TPS cutoff maps

Lunit-SCOPE-PD-L1-CAL10-NSCLC-PDL-1-1x-Mask-Image-for-workslow

Zoom image

Step 2: PD-L1 TPS Cutoff Map

An image analysis TPS cutoff map mask is generated for each slide, denoting regions within the sample that express PD-L1.

Prior to this step, image analysis pre-processing excludes artifacts, benign epithelial tissue, and macrophages.

The TPS cutoff map offers visual identification of PD-L1 expression into three cutoff classifications (>50%, 1-49%, and <1%) for deeper understanding on intra-tumoral heterogeneity.

Lunit-SCOPE-PD-L1-CAL10-NSCLC-PDL-1-Cell-Counts-for-Workflow

Zoom image

Step 3: PD-L1 Cell Classification

Lunit SCOPE PD-L1 CAL10 NSCLC generates an image mask for every cancer cell within the tumor region, denoting the following cell classes:

Positive PD-L1 Tumor Cell: Magenta
Negative PD-L1 Tumor Cell : Cyan

Consistent Scoring for PD-L1 Research

AI/ML-Based Scoring: The application utilizes robust artificial intelligence and machine learning algorithms, trained on a broad spectrum of PD-L1 (CAL10) stained tissue samples. This ensures accurate TPS quantification, particularly around critical cutoffs (1% and 50%), addressing common interpretation challenges such as borderline cases, macrophage staining, and human subjectivity.
Automated TPS Scoring: By automating TPS scoring, the application saves valuable reading time, especially for complex cases. This efficiency allows researchers to focus on higher-value tasks and enhances productivity.
Seamless Digital Pathology Integration: Designed for the Leica Biosystems digital pathology ecosystem across digital slide scanner, image management, and AI image analysis. Researchers benefit from streamlined workflow integration that enables reproducibility across multiple study sites.

Lunit SCOPE PD-L1 CAL10 NSCLC Demonstration in Aperio HALO AP Image Management System

Explore the future of pathology with Lunit SCOPE PD-L1 CAL10 NSCLC. The PD-L1 image analysis algorithm is designed for intuitive use within the Aperio digital pathology environment. The algorithm automatically identifies regions of interest and applies AI-powered image analysis to calculate the tumor proportion score (TPS), presenting analysis in a clear, interactive dashboard.

Specifications

Scanner:	Compatible file types include Leica Biosystems (.svs), Philips (.iSyntax, .tiff), 3D Histech (.mrxs), Hamamatsu (.ndpi) and other scanners at x40 magnification
IMS:	Leica Biosystems’ Aperio HALO AP
Algorithm:	Lunit SCOPE PD-L1 CAL10 NSCLC

Assay:	Leica Biosystems PD-L1 CAL10
Tissue Type:	NSCLC
Scoring:	TPS
Regulatory status:	Research Use Only (RUO)