An AI-Ready Multiplex Staining Dataset for Reproducible and Accurate Characterization of Tumor Immune Microenvironment

by   Parmida Ghahremani, et al.
Memorial Sloan Kettering Cancer Center
Moffitt Cancer Center

We introduce a new AI-ready computational pathology dataset containing restained and co-registered digitized images from eight head-and-neck squamous cell carcinoma patients. Specifically, the same tumor sections were stained with the expensive multiplex immunofluorescence (mIF) assay first and then restained with cheaper multiplex immunohistochemistry (mIHC). This is a first public dataset that demonstrates the equivalence of these two staining methods which in turn allows several use cases; due to the equivalence, our cheaper mIHC staining protocol can offset the need for expensive mIF staining/scanning which requires highly-skilled lab technicians. As opposed to subjective and error-prone immune cell annotations from individual pathologists (disagreement > 50 immune and tumor cell annotations via mIF/mIHC restaining for more reproducible and accurate characterization of tumor immune microenvironment (e.g. for immunotherapy). We demonstrate the effectiveness of this dataset in three use cases: (1) IHC quantification of CD3/CD8 tumor-infiltrating lymphocytes via style transfer, (2) virtual translation of cheap mIHC stains to more expensive mIF stains, and (3) virtual tumor/immune cellular phenotyping on standard hematoxylin images. The dataset is available at <>.


page 2

page 4

page 5

page 7

page 8


CRC-ICM: Colorectal Cancer Immune Cell Markers Pattern Dataset

Colorectal Cancer (CRC) is the second most common cause of cancer death ...

The Detection of Thoracic Abnormalities ChestX-Det10 Challenge Results

The detection of thoracic abnormalities challenge is organized by the De...

Hybrid Window Attention Based Transformer Architecture for Brain Tumor Segmentation

As intensities of MRI volumes are inconsistent across institutes, it is ...

Real-time Bayesian personalization via a learnable brain tumor growth model

Modeling of brain tumor dynamics has the potential to advance therapeuti...

Segmentation of the veterinary cytological images for fast neoplastic tumors diagnosis

This paper shows the machine learning system which performs instance seg...

Inferring clonal evolution of tumors from single nucleotide somatic mutations

High-throughput sequencing allows the detection and quantification of fr...

GANDA: A deep generative adversarial network predicts the spatial distribution of nanoparticles in tumor pixelly

Intratumoral nanoparticles (NPs) distribution is critical for the diagno...

Please sign up or login with your details

Forgot password? Click here to reset