AI reads PET scans to guide treatment for head and neck cancer
Checks an AI tool's predictions from PET scans in adults with head and neck cancer.
Plain-language title generated from the registry record
Registry title: Artificial Intelligence in Functional Imaging for Individualized Treatment of Head and Neck Squamous Cell Carcinoma Patients
Key facts
- Where
- Berlin, GermanySee the site
AI summary: who the study is looking for
From the trial's eligibility criteria. Machine-read from the registry text on this page, so it can be wrong. The registry text below and the trial team decide who can take part.
The trial is looking for adults with head and neck squamous cell carcinoma who start treatment meant to remove all of the disease, either radiation with or without chemotherapy, or surgery. All must have had an FDG PET scan before treatment.
- Age
- Older than 18 years
- Sex
- All sexes can join
- Disease stage
- Head and neck squamous cell carcinoma (HNSCC) that can be treated with the aim of removing all of the disease
- Earlier treatment
- Must have had an FDG PET scan before treatment starts. The treatment is either radiation with or without chemotherapy, or surgery, alone or combined.
Main reasons for not taking part
- HNSCC that cannot be treated with the aim of removing all of the disease
- Unable to have an FDG PET scan before treatment starts
- Has withdrawn consent to the study
Read by machine on 9 November 2026.
Where in Germany
- Department of Radiooncology and Radiotherapy, Charité - Universitätsmedizin Berlin, Campus Virchow KlinikumBerlin, GermanyTaking people
Questions to ask the study team
- How often do I need to come in, and for how long each time?
- Are travel costs paid?
- Can I keep my own doctor?
- What happens if I want to stop?
Trial details
- Who runs it
- Charite University, Berlin, Germany
- Trial code
- NCT05192655
- Record updated
- 7 February 2024
- Original description
The two curative treatment modalities for patients with HNSCC - primary chemoradiation (CRT) or primary surgery (often combined with postoperative (C)RT) - are both associated with serious side effects for which reason further stratification, optimization and personalization of treatment is urgently needed. As novel quantitative image analyses are a promising tool for further risk stratification, the investigators training a three-dimensional Convolutional Neural Network on 18F-Fluorodesoxyglucose (FDG) positron emission tomography (PET) imaging and clinical / histopathological data of a multicentric, retrospective cohort of 1200 patients treated with primary CRT and 800 patients treated with primary surgery at Charité and cooperation institutes in order to predict individual treatment-specific outcomes and identify patients with excellent outcome after primary CRT or primary surgery or unfavorable outcome for both. The trained algorithm of the artificial intelligence will be validated in a prospective trial to see if predicted loco-regional control and recommended treatment strategies are reliable. In total 250 curative HNSCC patients, treated with CRT or primary surgery, will be enrolled on this prospective validation trial with observational character, while biomarker, clinical and FDG-PET data are collected from these patients and follow-up visits will be concluded.Read full original descriptionShow less
Künstliche Intelligenz (KI) in Der Funktionellen Bildgebung Zur Individualisierten Behandlung Von Kopf-Hals-Plattenepithelkarzinom-Patienten Artificial Intelligence in Functional Imaging for Individualized Treatment of Head and Neck Squamous Cell Carcinoma Patients
The two curative treatment modalities for patients with HNSCC - primary chemoradiation (CRT) or primary surgery (often combined with postoperative (C)RT) - are both associated with serious side effects for which reason further stratification, optimization and personalization of treatment is urgently needed. As novel quantitative image analyses are a promising tool for further risk stratification, the investigators training a three-dimensional Convolutional Neural Network on 18F-Fluorodesoxyglucose (FDG) positron emission tomography (PET) imaging and clinical / histopathological data of a multicentric, retrospective cohort of 1200 patients treated with primary CRT and 800 patients treated with primary surgery at Charité and cooperation institutes in order to predict individual treatment-specific outcomes and identify patients with excellent outcome after primary CRT or primary surgery or unfavorable outcome for both. The trained algorithm of the artificial intelligence will be validated in a prospective trial to see if predicted loco-regional control and recommended treatment strategies are reliable. In total 250 curative HNSCC patients, treated with CRT or primary surgery, will be enrolled on this prospective validation trial with observational character, while biomarker, clinical and FDG-PET data are collected from these patients and follow-up visits will be concluded.
Inclusion: All patients older than 18 years with diagnosed HNSCC, attending the Department of Radiooncology and Radiotherapy or the Department of Oral and Maxillofacial Surgery at Charité for a treatment with curative intension ( R(C)T or primary surgery / combined); All patients received as pretherapeutic diagnostic method a 18F-Fluorodesoxyglucose (FDG) positron emission tomography (PET) imaging.
Exclusion: Patients with HNSCC who cannot be treated in a curative approach; Patients with HNSCC treated in a curative approach but unable to receive FDG PET imaging before start of treatment; Data from patients who have withdrawn their study consent.