Radiation DermatitisNCT05607225
Deep Learning-based Classification and Prediction of Radiation Dermatitis in Head and Neck Patients
An observational study of Radiation Dermatitis and Head and Neck Cancer, run by Cancer Institute and Hospital, Chinese Academy of Medical Sciences at 2 sites in China.
Trial summary
to develop a deep learning-based model to grade the severity of radiation dermatitis (RD) and predict the severity of radiation dermatitis in patients with head and neck cancer undergoing radiotherapy, so as to provide support for doctors' diagnosis and prediction. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Radiation Dermatitis, Head and Neck Cancer
- How many people
- 300 participants
- Where
- 2 sitesChina
- Study dates
- 1 Jul 2022to 30 Jun 2025
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: patients with head and neck cancer who will receive radical radiotherapy
Who may be able to join
- Age ≥ 18 years old.
- Histologically or cytologically confirmed head and neck carcinoma confirmed by pathology.
- Receive radical radiotherapy including neck area
- Informed consent.
Who cannot join
- unable to cooperate with image acquisition
Trial locations and contacts
2 sites in 1 country.
China2 sites, 2 recruiting
- Recruiting
Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College
Beijing, 100080
Ye Zhang, MD
- Recruiting
Shenzhen Cancer Hospital, Chinese Academy of Medical Sciences
Shenzhen, Guangdong, 518116
Li Ma, MD, +86-755-66618168
About this study
Official title: Deep Learning-based Classification and Prediction of Radiation Dermatitis in Head and Neck
to develop a deep learning-based model to grade the severity of radiation dermatitis (RD) and predict the severity of radiation dermatitis in patients with head and neck cancer undergoing radiotherapy, so as to provide support for doctors' diagnosis and prediction.
Read the detailed description
- Image acquisition The images of the neck area were collected from the enrolled patients one week before and every week during radiotherapy. The photographs were taken from three angles (front, left and right oblique) of the neck area.
- Grading evaluation Each image was individually graded by three experienced radiotherapy experts according to the RD criteria of RTOG
- Data analysis Construct a dermatitis grading model basing on deep learning. Evaluate the performance of model using accuracy, precision, recall, F1-measure, dice value.
- Conditions
- Radiation Dermatitis, Head and Neck Cancer
- Medical subject headings
- Radiodermatitis, Head and Neck Neoplasms
What is being measured
The primary outcome is the main question the study is designed to answer.
Accuracy
Evaluate the rate of deep learning based rating model in accordance with experts' assessment.
Measured: July 1, 2022 to June 30, 2025
Precision
The proportion of positive samples in the positive prediction result
Measured: July 1, 2022 to June 30, 2025
Recall
The proportion of positive samples that were predicted to be positive
Measured: July 1, 2022 to June 30, 2025
F1-measure
The harmonic average of precision and recall
Measured: July 1, 2022 to June 30, 2025
ROC curve
Measured: July 1, 2022 to June 30, 2025
Secondary outcomes (1)
dice value
Ratio of overlap and distance between artificial and automatic neck segmentation regions
Measured: July 1, 2022 to June 30, 2025
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted7 Nov 2022
- Study start1 Jul 2022
- Primary completion30 Jun 2025 (estimated)
- Study completion30 Jun 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Radiation DermatitisStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 300 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Cancer Institute and Hospital, Chinese Academy of Medical Sciences
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, YE ZHANG, Cancer Institute and Hospital, Chinese Academy of Medical Sciences
- Investigators
- Ye Zhang, MD, Principal investigator, Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical CollegeLi Ma, MD, Principal investigator, Shenzhen Cancer Hospital, Chinese Academy of Medical Sciences
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05607225
- Sponsor's protocol ID
- JS2022-62
- Status last verified
- Oct 2022
- First submitted
- 24 Oct 2022
- Last updated
- 7 Nov 2022
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 7 Nov 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Deep Learning-based Classification and Prediction of Radiation Dermatitis in Head and Neck
- ClinicalTrials.gov ID
- NCT05607225
- Acronym / sponsor ID
- JS2022-62
- Conditions
- Radiation Dermatitis, Head and Neck Cancer
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 300 participants (estimated)
- Lead sponsor
- Cancer Institute and Hospital, Chinese Academy of Medical SciencesUniversity, hospital or other
- Study start
- 1 Jul 2022 (actual)
- Primary completion
- 30 Jun 2025 (estimated)
- Study completion
- 30 Jun 2025 (estimated)
- First posted
- 7 Nov 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
to develop a deep learning-based model to grade the severity of radiation dermatitis (RD) and predict the severity of radiation dermatitis in patients with head and neck cancer undergoing radiotherapy, so as to provide support for doctors' diagnosis and prediction.
Detailed description
- Image acquisition The images of the neck area were collected from the enrolled patients one week before and every week during radiotherapy. The photographs were taken from three angles (front, left and right oblique) of the neck area.
- Grading evaluation Each image was individually graded by three experienced radiotherapy experts according to the RD criteria of RTOG
- Data analysis Construct a dermatitis grading model basing on deep learning. Evaluate the performance of model using accuracy, precision, recall, F1-measure, dice value.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- patients with head and neck cancer who will receive radical radiotherapy
Key inclusion criteria (4 listed)
- Age ≥ 18 years old.
- Histologically or cytologically confirmed head and neck carcinoma confirmed by pathology.
- Receive radical radiotherapy including neck area
- Informed consent.
Key exclusion criteria (1 listed)
- unable to cooperate with image acquisition
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Accuracy
Time frame: July 1, 2022 to June 30, 2025
Evaluate the rate of deep learning based rating model in accordance with experts' assessment.
Precision
Time frame: July 1, 2022 to June 30, 2025
The proportion of positive samples in the positive prediction result
Recall
Time frame: July 1, 2022 to June 30, 2025
The proportion of positive samples that were predicted to be positive
F1-measure
Time frame: July 1, 2022 to June 30, 2025
The harmonic average of precision and recall
ROC curve
Time frame: July 1, 2022 to June 30, 2025
1 secondary outcome
dice value
Time frame: July 1, 2022 to June 30, 2025
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 7 Nov 2022.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Ye Zhang, MD principal investigator
Cancer Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College
Li Ma, MD principal investigator
Shenzhen Cancer Hospital, Chinese Academy of Medical Sciences
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Radiation Dermatitis and Head and Neck Cancer, run by Cancer Institute and Hospital, Chinese Academy of Medical Sciences at 2 sites in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 7 Nov 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Li Ma, MD (86-755-66618168, ml_1990@126.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Accuracy (time frame: July 1, 2022 to June 30, 2025). The study lists 5 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 7 Nov 2022.