Evidence map›Paper›PMID 36865274›Full record

ArticlebioRxiv : the preprint server for biology2023

Dual-modality imaging of immunofluorescence and imaging mass cytometry for whole slide imaging with accurate single-cell segmentation.

Eun Na Kim, Phyllis Zixuan Chen, Dario Bressan, Monika Tripathi, Ahmad Miremadi, Massimiliano di Pietro, Lisa M Coussens, Gregory J Hannon, Rebecca C Fitzgerald, Lizhe Zhuang and 1 more

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 3 countries.

Eun Na KimDepartment of Biomedical Engineering and Computational Biology Program, Oregon Health and Science University, Portland, OR, USA.
Phyllis Zixuan ChenEarly Cancer Institute, University of Cambridge, Cambridge, UK.
Dario BressanCancer Research UK Cambridge Institute and Department of Oncology, Li Ka Shing Centre, University of Cambridge, Cambridge, UK.
Monika TripathiEarly Cancer Institute, University of Cambridge, Cambridge, UK.
Ahmad MiremadiEarly Cancer Institute, University of Cambridge, Cambridge, UK.
Massimiliano di PietroEarly Cancer Institute, University of Cambridge, Cambridge, UK.
Lisa M CoussensDepartment of Cell, Developmental and Cancer Biology, Oregon Health and Science University, Portland, OR, USA.
Gregory J HannonCancer Research UK Cambridge Institute and Department of Oncology, Li Ka Shing Centre, University of Cambridge, Cambridge, UK.
Rebecca C FitzgeraldEarly Cancer Institute, University of Cambridge, Cambridge, UK.
Lizhe ZhuangEarly Cancer Institute, University of Cambridge, Cambridge, UK.
Young Hwan ChangDepartment of Biomedical Engineering and Computational Biology Program, Oregon Health and Science University, Portland, OR, USA.
University of Cambridge · GBOregon Health & Science University · US

Funding

Understanding the Impact of Microscale and Nanoscale Heterogeneity and ResistanceU54CA209988 · NCI · OREGON HEALTH & SCIENCE UNIVERSITY · PI DEMIR, EMEK, HEISER, LAURA MADELINE · 2017 to 2021
$10.3M
Omic and Multidimensional Spatial Atlas of Metastatic Breast CancerU2CCA233280 · NCI · OREGON HEALTH & SCIENCE UNIVERSITY · PI GOECKS, JEREMY · 2018 to 2023
$9.7M
Integrative single cell analyses of inflammation-derived circulating hybrid cells to identify aggressive diseaseR01CA253860 · NCI · OREGON HEALTH & SCIENCE UNIVERSITY · PI CHANG, YOUNG HWAN, WONG, MELISSA H. · 2021 to 2025
$3.0M
Comparative analysis between patient-derived models of pancreatic ductal adenocarcinomas and matched tumor specimensU01CA224012 · NCI · OREGON HEALTH & SCIENCE UNIVERSITY · PI BRODY, JONATHAN, COUSSENS, LISA M. · 2019 to 2023
$2.9M
NCI NIH HHS R01 CA253860NCI NIH HHS U01 CA224012NCI NIH HHS U2C CA233280NCI NIH HHS U54 CA209988Wellcome Trust
6 · The paper itself

Abstract

Imaging mass cytometry (IMC) is a powerful multiplexed tissue imaging technology that allows simultaneous detection of more than 30 makers on a single slide. It has been increasingly used for singlecell-based spatial phenotyping in a wide range of samples. However, it only acquires a small, rectangle field of view (FOV) with a low image resolution that hinders downstream analysis. Here, we reported a highly practical dual-modality imaging method that combines high-resolution immunofluorescence (IF) and high-dimensional IMC on the same tissue slide. Our computational pipeline uses the whole slide image (WSI) of IF as a spatial reference and integrates small FOVs IMC into a WSI of IMC. The high-resolution IF images enable accurate single-cell segmentation to extract robust high-dimensional IMC features for downstream analysis. We applied this method in esophageal adenocarcinoma of different stages, identified the single-cell pathology landscape via reconstruction of WSI IMC images, and demonstrated the advantage of the dual-modality imaging strategy. Motivation: Highly multiplexed tissue imaging allows visualization of the spatially resolved expression of multiple proteins at the single-cell level. Although imaging mass cytometry (IMC) using metal isotope-conjugated antibodies has a significant advantage of low background signal and absence of autofluorescence or batch effect, it has a low resolution that hampers accurate cell segmentation and results in inaccurate feature extraction. In addition, IMC only acquires mm

Identifiers

PMID36865274
PMCPMC9980062
OpenAlexW4321605270

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.