Actively Recruiting
Predicting Esophageal Cancer Borders Using PET-Imaging
Led by University Hospital Heidelberg · Updated on 2026-03-10
30
Participants Needed
1
Research Sites
213 weeks
Total Duration
On this page
AI-Summary
What this Trial Is About
The study examines the diagnostic precision of endosonography, mpMRI and PET/CT in defining tumor boundaries and tumor spread before and after neoadjuvant therapy and definitive surgery.
CONDITIONS
Official Title
Predicting Esophageal Cancer Borders Using PET-Imaging
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Histologically confirmed adenocarcinoma or squamous cell carcinoma of the esophagus, including AEG I and AEG II tumors in the primary situation
- Planned surgical treatment of esophageal carcinoma
- Possible staging advantage through FAPI PET/CT diagnostics
- Patient information and written consent
- KI 60% or ECOG 0/1 (at least: self-sufficiency)
- Age �318 years
You will not qualify if you...
- Previous radiation therapy in the tumor region
- Previous tumor disease with less than 5 years of remission
- Surgical therapy is not functionally or technically possible
- Distant metastasis
- Patient is not capable of giving consent
- Concurrent participation in another clinical trial that could affect the results of this trial or the other trial
- Illnesses that do not allow the person concerned to assess the nature and scope as well as possible consequences of the clinical study
- Pregnant or breastfeeding women
- Signs that the person taking part is unlikely to comply with the therapy (e.g. unwillingness to cooperate)
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Trial Site Locations
Total: 1 location
1
Department of Radiotherapy, University of Heidelberg
Heidelberg, Germany, 69120
Actively Recruiting
Research Team
C
Christoph Fink, MD
CONTACT
How is the study designed?
Study Type
INTERVENTIONAL
Masking
NONE
Allocation
NON_RANDOMIZED
Model
PARALLEL
Primary Purpose
TREATMENT
Number of Arms
3
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