Construction and Validation of an Intelligent Ultrasound Diagnostic System for the Spectrum of Ne… (NCT07549425) | Clinical Trial Compass
Active — Not RecruitingNot Applicable
Construction and Validation of an Intelligent Ultrasound Diagnostic System for the Spectrum of Neuroblastoma in Children
China300 participantsStarted 2026-01-01
Plain-language summary
The goal of this observational study is to build an intelligent ultrasound diagnostic system that integrates pathological typing, risk stratification and prognosis assessment. The main question it aims to answer is:
1. Can the prediction model of neuroblastoma tumors (NTs) in children based on ultrasound images distinguish each pathological subtype?
2. Can the multimodal fusion model established based on clinical and pathological features identify high-risk patients, predict bone marrow metastasis, and estimate the therapeutic effect?
3. Can this ultrasound diagnostic system achieve a systematic and intelligent assessment of NTs patients to assist in clinical risk stratification and individualized treatment decisions?
Who can participate
Age range
18 Years
Sex
ALL
See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Inclusion criteria
. The diagnosis of NTs was confirmed by surgical resection or biopsy with histopathological examination, and the type was classified as NB, GNB or GN according to the INPC standard.
. Age ≤ 18 years old, with no gender restrictions.
. There are complete abdominal (or primary site) ultrasound images archived, in original DICOM or JPG format, with image quality meeting the analysis requirements.
. Complete clinical and pathological data relevant to the research purpose are available.
Exclusion criteria
. The patient has previously undergone surgical resection treatment in another hospital, but the tumor recurred or remained after the operation.
Questions worth asking your doctor
Bring these to your next appointment. They're a starting point for a shared conversation — not a sign you qualify or a recommendation to enrol.
1Based on my diagnosis and history, is this trial worth exploring for me — or is there a standard treatment we should try first?
2What does this trial's phase tell us about how much is already known about its safety and benefit?
3What would taking part actually involve for me — visits, tests, time, and travel?
4What are the known and possible risks or side effects I should weigh, and how would they be monitored?
5If this trial isn't the right fit, what other options or trials would you suggest I look into?
Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.
Questions for the trial coordinator
The trial coordinator is the person who runs the study day to day. These cover the practical side — logistics, costs, and what taking part would actually mean for your life. The study team confirms whether you meet the criteria; these are questions to ask, not a sign you qualify.
1What does taking part actually involve week to week — how many visits, where, and how long does each one take?
2What costs are covered by the study, and what might I have to pay for myself, including travel, parking, or time off work?
3What happens during screening, and what happens if the study team confirms I don't meet the criteria after those tests?
4Who pays for the scans, blood work, and other tests the trial requires — the study, my insurance, or me?
5How will being in the trial affect my regular care, and will my own doctor stay informed and involved?
6Can I leave the trial at any point if I change my mind, and what would happen to my care if I do?
A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
What they're measuring
1
F1 score
Timeframe: Within one week after the model training is completed, calculations are conducted respectively on the internal validation set and the independent external validation set.
2
accuracy rate
Timeframe: Within one week after the model training is completed, performance tests are conducted respectively on the internal validation set and the independent external validation set.
3
specificity
Timeframe: Within one week after the model training is completed, calculations are conducted respectively on the internal validation set and the independent external validation set.
4
sensitivity
Timeframe: Within one week after the model training is completed, calculations are conducted respectively on the internal validation set and the independent external validation set.
Trial details
NCT IDNCT07549425
SponsorThe Children's Hospital of Zhejiang University School of Medicine
. Poor quality of ultrasound images: There are artifacts that seriously affect the identification of tumor contours or feature extraction, image blurring, or incomplete display of the lesion.
. Severe data deficiency: Key clinical pathological data or imaging data are missing, making it impossible to extract and analyze the required information.