AI ultrasound could revolutionize childhood cancer diagnosis
NCT ID NCT07549425
First seen Jun 27, 2026 · Last updated Jun 27, 2026
Summary
This study aims to create an intelligent ultrasound system that can better diagnose and classify neuroblastoma tumors in children. Researchers will use ultrasound images and medical data from 300 children to train a computer model to identify tumor types, predict risk, and guide treatment. The goal is to make diagnosis faster and more accurate, helping doctors choose the best care for each child.
This is an AI summary of the original study and may miss details. Read our disclaimer.
Study facts
What this study's own registry entry says, in plain language.
- Participants
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About 300 people
The number the study aims to enrol. It can still change while the study runs.
- Started
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Jan 2026
- Expected to finish
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Sep 2026
An estimate. End dates often move.
- Lead sponsor
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Other sponsor
The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.
Who can take part
This study's own entry requirements. Only the study team can say for certain whether you qualify.
Who is studied
Patients diagnosed with NTs at the Children's Hospital of Zhejiang University School of Medicine, the Children's Hospital Affiliated to Soochow University, the Children's Hospital of Kunming City, and Anhui Provincial Children's Hospital from January 2015 to February 2025.
- Ages
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Up to 18 years
- Sex
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Anyone
- Healthy volunteers
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Not accepted
This study is not open to healthy volunteers. The entry requirements below say who it is open to.
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Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.
Inclusion Criteria: 1. 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. 2. Age ≤ 18 years old, with no gender restrictions. 3. There are complete abdominal (or primary site) ultrasound images archived, in original DICOM or JPG format, with image quality meeting the analysis requirements. 4. Complete clinical and pathological data relevant to the research purpose are available. Exclusion Criteria: 1. The patient has previously undergone surgical resection treatment in another hospital, but the tumor recurred or remained after the operation. 2. 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. 3. Severe data deficiency: Key clinical pathological data or imaging data are missing, making it impossible to extract and analyze the required information.
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Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
Contacts and locations
Locations
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Anhui Provincial Children's Hospital
Hefei, Anhui, 230041, China
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Kunming Children's Hospital
Kunming, Yunnan, 650100, China
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The Children's Hospital Affiliated to Soochow University
Suzhou, Jiangsu, 215008, China
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The Children's Hospital of Zhejiang University School of Medicine
Hangzhou, Zhejiang, 310000, China
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Wenling Institute of Medical Big Data and Artificial Intelligence
Wenling, Zhejiang, 317500, China
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Zhejiang Cancer Hospital
Hangzhou, Zhejiang, 310000, China
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Other studies related to the condition(s) this trial covers.