Evidence map›Paper›PMID 40425893›Full record

ReviewMedical oncology (Northwood, London, England)2025

Radiomics applications in the modern management of esophageal squamous cell carcinoma.

Liqiang Shi, Xipeng Wang, Chengqiang Li, Yaya Bai, Yajie Zhang, Hecheng Li

Abstract readReview
PubMed Publisher
In one paragraph

Review in Medical oncology (Northwood, London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

6 authors.

Liqiang ShiDepartment of Thoracic Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China.
Xipeng WangDepartment of Thoracic Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China.
Chengqiang LiDepartment of Thoracic Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China.
Yaya BaiDepartment of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
Yajie ZhangDepartment of Thoracic Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China. 13817163025@163.com.
Hecheng LiDepartment of Thoracic Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China. lihecheng2000@hotmail.com.

Funding

National Natural Science Foundation of China 82072557
6 · The paper itself

Abstract

Esophageal cancer ranks among the most lethal malignancies globally, with China accounting for more than half of worldwide esophageal squamous cell carcinoma (ESCC) cases. Late-stage diagnosis frequently precludes surgical intervention, contributing to poor outcomes. While precise clinical assessment is essential for treatment planning, therapeutic responses and prognosis exhibit substantial inter-patient heterogeneity, underscoring the urgent need for reliable biomarkers to enhance prognostic accuracy and guide personalized therapeutic strategies. Radiomics, an emerging field that extracts high-dimensional features from medical images, provides non-invasive approaches to improve diagnostic accuracy, predict survival, monitor adverse events, detect recurrence, and optimize treatment strategies. Radiomics has shown promising potential in the modern management of ESCC. Here, we review the critical contributions of radiomics to ESCC research and clinical practice, examining its workflow, applications, strengths, and limitations. Radiomics represents a compelling frontier with substantial potential to advance precision medicine for ESCC patients.

Indexed as

Esophageal NeoplasmsEsophageal Squamous Cell CarcinomaImage Processing, Computer-AssistedHumansPrecision MedicinePrognosisRadiomicsApplicationsArtificial intelligenceBiomarkersEsophageal squamous cell carcinomaPrediction modelRadiomics

Identifiers

What OpenQuestion holds

Textmetadata
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.