Deep Learning-based Classification and Prediction of Radiation Dermatitis in Head and Neck Patients

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

300 participants

Study Classification

OBSERVATIONAL

Study Start Date

2022-07-01

Study Completion Date

2025-06-30

Brief Summary

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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.

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Detailed Description

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1. 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.
2. Grading evaluation Each image was individually graded by three experienced radiotherapy experts according to the RD criteria of RTOG
3. 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

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Radiation Dermatitis Head and Neck Cancer

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Eligibility Criteria

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Inclusion Criteria

* Age ≥ 18 years old.
* Histologically or cytologically confirmed head and neck carcinoma confirmed by pathology.
* Receive radical radiotherapy including neck area
* Informed consent.