Diagnosis and Survival Prediction of Pancreatic Cancer by Machine Learning of Image Data

NCT ID: NCT05313854

Last Updated: 2022-04-06

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Total Enrollment

1000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-01-01

Study Completion Date

2023-12-31

Brief Summary

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This prospective cohort study is designed to investigate the diagnostic ability and prediction accuracy of pancreatic cancer by radiomics data and clinical data.

Detailed Description

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In this study, investigators aimed to investigate the diagnostic performance and prediction accuracy of pancreatic cancer by radiomics data and clinical data, which include CT scan, MRI, PET-CT, PET-MR, ultrasound, and clinical data.

Conditions

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Pancreatic Cancer

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Eligibility Criteria

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Inclusion Criteria

Clinical diagnosis of pancreatic tumor; Must have CT / MRI / ultrasound data and pathology diagnosis

Exclusion Criteria

Have other tumors along with pancreatic tumor; Clinical information missing
Minimum Eligible Age

18 Years

Maximum Eligible Age

90 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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RenJi Hospital

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Tao Chen, Dr

Role: PRINCIPAL_INVESTIGATOR

Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University

Locations

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Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University

Shanghai, , China

Site Status RECRUITING

Countries

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China

Central Contacts

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Xinsen Xu, Dr

Role: CONTACT

+86-21-68383713

Tao Chen, Dr

Role: CONTACT

+86-21-68383713

Facility Contacts

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Tao Chen, MD.

Role: primary

References

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Xu X, Qu J, Zhang Y, Qian X, Chen T, Liu Y. Development and validation of an MRI-radiomics nomogram for the prognosis of pancreatic ductal adenocarcinoma. Front Oncol. 2023 Feb 24;13:1074445. doi: 10.3389/fonc.2023.1074445. eCollection 2023.

Reference Type DERIVED
PMID: 36910599 (View on PubMed)

Other Identifiers

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RA-2020-455

Identifier Type: -

Identifier Source: org_study_id

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