Clinical Application of MR-PET in Non-small Cell Lung Cancer: Diagnosis, Treatment Outcome, and Prognosis Prediction

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National Taiwan University

Status

Unknown

Conditions

Non-small Cell Lung Cancer

Treatments

Radiation: MR/PET

Study type

Interventional

Funder types

Other

Identifiers

NCT03053804
201501073RINA

Details and patient eligibility

About

It is a study that hypothesize that MR/PET can have better information than current CT image study, about the medical or surgical treatment outcome of lung cancer

Full description

The investigators analyze tumor size、ADCmean、ADCmin、DCE、SUVmax、SUVmin、etc in MR/PET study,to compare its efficacy with other image studies in tumor malignancy grade, systemic involvement detection, treatment outcome after medical target therapy and treatment outcome after surgery.

Enrollment

75 estimated patients

Sex

All

Ages

20 to 100 years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  • Age: > 20 years old.
  • Patients have confirmed lung cancer by histopathological methods (fiber, bronchoscopy, lung biopsy, open chest biopsy, pleural effusion exfoliated cells, sputum exfoliated cells)
  • Patients voluntarily to join this study and signed informed consents.

Exclusion criteria

  • Any body metal implants (pacemaker implantation, nerve stimulator, vascular stent, aneurysm clip, eye foreign body, the inner metal prosthesis) or artificial heart valves
  • Patients with claustrophobia to MRI examination
  • Patients who are reluctant to comply with follow-up and subsequent examination
  • The other condition that do not meet the inclusion criteria.
  • Pregnancy.
  • Age < 20 years old.

Trial design

Primary purpose

Diagnostic

Allocation

N/A

Interventional model

Single Group Assignment

Masking

None (Open label)

75 participants in 1 patient group

MR/PET
Experimental group
Description:
hypothesize that MR/PET can have better information than current CT image study
Treatment:
Radiation: MR/PET

Trial contacts and locations

0

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Central trial contact

Yu-Sen Huang; Yeun-Chung Chang

Data sourced from clinicaltrials.gov

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