Evidence map›Paper›PMID 37767002›Full record

ArticleiScience2023

Focalizing regions of biomarker relevance facilitates biomarker prediction on histopathological images.

Jiefeng Gan, Hanchen Wang, Hui Yu, Zitong He, Wenjuan Zhang, Ke Ma, Lianghui Zhu, Yutong Bai, Zongwei Zhou, Alan Yullie and 13 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in iScience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

23 authors.

Jiefeng GanInstitute of Pathology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Hanchen WangDepartment of Engineering, University of Cambridge, Fitzwilliam House 32 Trumpington Street, Cambridge CB2 1QY, UK.
Hui YuWuhan Children's Hospital, Tongji Medical College, Wuhan, Hubei 430000, China.
Zitong HeDepartment of Computer Science, Johns Hopkins University, 3400 N Charles St, Baltimore, MD 21218, USA.
Wenjuan ZhangDepartment of Pathology, Maternal and Child Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 43000, China.
Ke MaInstitute of Pathology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Lianghui ZhuSchool of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, Hubei 430000, China.
Yutong BaiDepartment of Computer Science, Johns Hopkins University, 3400 N Charles St, Baltimore, MD 21218, USA.
Zongwei ZhouDepartment of Computer Science, Johns Hopkins University, 3400 N Charles St, Baltimore, MD 21218, USA.
Alan YullieDepartment of Computer Science, Johns Hopkins University, 3400 N Charles St, Baltimore, MD 21218, USA.
Xiang BaiInstitute of Pathology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Mingwei WangThe National Center for Drug Screening, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China.
Dehua YangThe National Center for Drug Screening, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China.
Yanyan ChenDepartment of Information Management, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei 430000, China.
Guoan ChenWuhan Blood Center, Wuhan, Hubei 43000, China.
Joan LasenbyDepartment of Engineering, University of Cambridge, Fitzwilliam House 32 Trumpington Street, Cambridge CB2 1QY, UK.
Chao ChengBaylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA.
Jia WuDepartment of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Dr, Palo Alto, CA 94304, USA.
Jianjun ZhangThoracic/Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Xinggang WangSchool of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, Hubei 430000, China.
Yaobing ChenInstitute of Pathology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Guoping WangInstitute of Pathology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Tian XiaInstitute of Pathology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Funding

The molecular and immune evolution in the progression of lung neoplasia to invasive adenocarcinomaR01CA234629 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI ZHANG, JIANJUN · 2019 to 2023
$1.8M
QUANTITATIVE IMAGING BIOMARKERS OF TREATMENT RESPONSE AND PROGNOSIS IN BREAST CANCERR00CA218667 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI WU, JIA · 2020 to 2022
$747k
NCI NIH HHS R00 CA218667NCI NIH HHS R01 CA234629
6 · The paper itself

Abstract

Image-based AI has thrived as a potentially revolutionary tool for predicting molecular biomarker statuses, which aids in categorizing patients for appropriate medical treatments. However, many methods using hematoxylin and eosin-stained (H&E) whole-slide images (WSIs) have been found to be inefficient because of the presence of numerous uninformative or irrelevant image patches. In this study, we introduced the region of biomarker relevance (ROB) concept to identify the morphological areas most closely associated with biomarkers for accurate status prediction. We actualized this concept within a framework called saliency ROB search (SRS) to enable efficient and effective predictions. By evaluating various lung adenocarcinoma (LUAD) biomarkers, we showcased the superior performance of SRS compared to current state-of-the-art AI approaches. These findings suggest that AI tools, built on the ROB concept, can achieve enhanced molecular biomarker prediction accuracy from pathological images.

Indexed as

CancerHistologyMachine learningPathology

Identifiers

PMID37767002
PMCPMC10520807

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.