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Not yet recruitingNCT07801209Updated Sep 3, 2026

An AI-Assisted Agentic System for Ultrasound Scanning and Diagnosis of Ovarian Lesions

An observational study in Ovarian Mass and Adnexal Mass, sponsored by Women's Hospital School Of Medicine Zhejiang University. Not yet recruiting at 2 sites in China. Open to female participants aged 18 Years to 75 Years. Per ClinicalTrials.gov, last updated 2026-09-03.

Sponsored by Women's Hospital School Of Medicine Zhejiang University · Observational

Study type
Observational
Model
Cohort
Time perspective
Prospective
Enrollment
250
Ages
18 Years to 75 Years
Sex
Female
01

Study summary

Investigators developed an interactive agentic system designed to guide newly qualified sonographers in ovarian lesion scanning and improve their scanning quality and diagnostic performance toward expert-level standards. Our agentic system is capable of capturing key features including the max-diameter plane of ovarian lesions from dynamic ultrasound videos, translating these findings into standardized International Ovarian Tumor Analysis (IOTA) descriptors, and providing multi-turn guidance for subsequent scanning, and ultimately generating an AI-assisted diagnostic assessment based on embedded expert knowledge.

In this multicenter study, participants are asked to undergo gynecological ultrasonography performed by sonographers with less than 3 years of experience with or without AI assistance. Our researchers will compare the performance of operators working with AI against that of operators working without AI, as well as against the performance of expert sonographers, to see whether AI assistance enhances the proficiency of less experienced operators and help them approach the scanning quality and diagnostic accuracy of expert sonographers in real-world clinical scenarios.

Read the detailed description

This multicenter, prospective study will be conducted at tertiary cancer centers and primary healthcare institutions across China. Participants will be recruited from gynecological ultrasound clinics of each site.

Each participant will undergo gynecological ultrasonography under both AI-assisted and unassisted conditions according to their group allocation. Following completion of the study examinations, expert sonographers with more than 10 years of experience, blinded to the scanning and diagnostic results of the junior sonographers, will independently perform a repeat gynecological ultrasound examination of each participant. Based solely on their independent examination, they will issue the final clinical report for each participant. The expert assessments will serve as one reference standard for evaluating scanning completeness, feature interpretation accuracy and diagnostic agreement. Histopathological findings, when available, or clinical follow-up for conservatively managed lesions will serve as the reference standard for evaluating diagnostic accuracy.

02

Conditions studied

  • Ovarian Mass
  • Adnexal Mass
03

Who can participate

Ages eligible
18 Years to 75 Years
Sexes eligible
Female
Accepts healthy volunteers
No
Sampling method
Non-probability sample

Study population

Participants, with suspected ovarian masses identified clinically or by previous imaging examination, will be consecutively recruited from gynecological ultrasound clinics of tertiary cancer centers and primary healthcare institutions across China.

Inclusion criteria

  • Female aged 18-75 years
  • With suspected ovarian masses identified clinically or by previous imaging examination
  • Eligible for and able to undergo transvaginal or transabdominal ultrasonography
  • Agree to provide written informed consent before enrollment

Exclusion criteria

Exclusion Criteria:

  • No ovarian mass identified on ultrasound examination
  • Previous bilateral oophorectomy
  • Previous surgery or chemotherapy for ovarian cancer
  • Previous treatment for other malignant tumors
  • Presence of any psychiatric or psychological disorders that may prevent completion of the study procedures or follow-up
  • Concurrent participation in other clinical trials that may interfere with the outcomes of this study
04

Study design

Observational model
Cohort
Time perspective
Prospective
Enrollment
250 participants (estimated)
Target follow-up
3 Months
Patient registry
Yes

Groups and cohorts

  • Arm A: experimental sequence of non-AI exertion followed by AI-assisted exertion

    The goal is to test the within-operator effect associated with AI assistance by comparing the performance of the same junior sonographer before and after AI guidance, and to compare the performance of both AI-assisted and unaided junior sonographers with that of the standalone AI model.

    Other: non-AI assisted and then AI assisted

  • Arm B: experimental sequence of AI-assisted exertion followed by non-AI exertion

    The goal is to test the clinical utility of AI with minimized potential carry-over effects and recall bias caused by repeated examinations on the same patient, by comparing the performance of one junior sonographer with AI-assisted, with that of independent unaided junior sonographers, and by comparing the performance of both AI-assisted junior sonographers and another unaided ones with that of the standalone AI model.

    Other: AI assisted and then non-AI assisted

Interventions

  • Othernon-AI assisted and then AI assisted

    Participants first undergo ultrasound scanning and diagnosis by a junior sonographer without AI assistance, followed by ultrasound scanning by the same sonographer with AI assistance.

  • OtherAI assisted and then non-AI assisted

    Participants first undergo ultrasound scanning and diagnosis by a junior sonographer with AI assistance, followed by ultrasound scanning by another junior sonographer without AI assistance. The two junior sonographers are blinded to each other's scanning and assessment results.

05

What researchers measure

Primary outcomes

  1. Completeness of ultrasound feature acquisition

    The completeness of ultrasound feature acquisition will be assessed with reference to national authoritative quality-control standards. After each examination, all stored ultrasound images and videos will be labeled according to their intended purpose. A feature will be considered adequately acquired when at least one stored image or video provides sufficient visual evidence for assessment of that feature. The proportion of required features successfully acquired will be calculated. The proportion of redundant stored images will also be recorded as an additional indicator of acquisition quality.

    Time frame: Up to 7 days from completion of the study

  2. Accuracy of interpretation of individual ultrasound features

    The accuracy of interpretation of ultrasound features will be assessed by comparing the assessments made by junior sonographers under AI-assisted and unassisted conditions with the findings independently acquired and interpreted by expert sonographers during a separate repeat ultrasound examination. The accuracy rate for each feature will be calculated.

    Time frame: Up to 7 days from completion of the study

  3. Agreement between junior and expert sonographers in ultrasound diagnosis

    Agreement between junior and expert sonographers will be assessed for the final diagnosis of ovarian lesions. The assessments made by junior sonographers under AI-assisted and unassisted conditions will be compared with the corresponding diagnoses independently obtained by expert sonographers during a separate repeat ultrasound examination, which will then be quantified using appropriate agreement statistics.

    Time frame: Up to 7 days from completion of the study

  4. Diagnostic accuracy of ovarian tumors

    Diagnostic accuracy will be assessed against histopathological diagnosis as the golden reference standard. This outcome will be evaluated only in participants who undergo surgical treatment and have definitive histopathological findings based on paraffin-embedded surgical specimens.

    Time frame: Within 3 months after the ultrasonography examination

  5. Diagnostic performance of ovarian tumors

    Area under curve will be assessed against histopathological diagnosis as the golden reference standard. This outcome will be evaluated only in participants who undergo surgical treatment and have definitive histopathological findings based on paraffin-embedded surgical specimens.

    Time frame: Within 3 months after the ultrasonography examination

  6. Diagnostic performance of ovarian tumors

    Diagnostic sensitivity and specificity will be assessed against histopathological diagnosis as the golden reference standard. This outcome will be evaluated only in participants who undergo surgical treatment and have definitive histopathological findings based on paraffin-embedded surgical specimens.

    Time frame: Within 3 months after the ultrasonography examination

  7. Diagnostic performance of ovarian tumors

    Diagnostic F1-score will be assessed against histopathological diagnosis as the golden reference standard. This outcome will be evaluated only in participants who undergo surgical treatment and have definitive histopathological findings based on paraffin-embedded surgical specimens.

    Time frame: Within 3 months after the ultrasonography examination

Secondary outcomes

  1. Confidence in ultrasound feature acquisition and diagnosis

    Sonographers' confidence in the completeness and adequacy of feature acquisition and in their final diagnostic assessment will be evaluated using a predefined rating scale as follows: 5 = very confident, 4 = confident, 3 = uncertain, 2 = less confident, and 1 = not confident at al.

    Time frame: Up to 7 days from completion of the study

06

Study locations

2 sites
  • Women's Hospital School Of Medicine Zhejiang University
    Hangzhou, Zhejiang 310006, China
  • Shaoxing Maternity and Child Health Care Hospital
    Shaoxing, Zhejiang 311800, China
    • Hua Yuan, Chief physician in ultrasound · Contact · yh0464@163.com · +86 0575-88211352
    • Xuezhen Lou, Attending physician · Contact · 505571621@qq.com
07

References and documents

Individual participant data

Plan to share: No

No publications or documents are linked to this record.

08

Registry details

Key details

Study ID
NCT07801209
Lead sponsor
Women's Hospital School Of Medicine Zhejiang University
Collaborators
Shaoxing Maternity and Child Health Care Hospital
Responsible party
Jiale Qin (Professor/Chief Physician in Ultrasound, M.D., Women's Hospital School Of Medicine Zhejiang University) — Principal investigator
First posted
Sep 3, 2026
Start date
Aug 19, 2026 (estimated)
Primary completion
Mar 31, 2027 (estimated)
Completion
Mar 31, 2027 (estimated)
Last update
Sep 3, 2026

Study contacts

Jiale Qin, Prof., Professor
Contact
qinjiale@zju.edu.cn
+86 0571-89998869
Ruixia Dai, Ph.D. student
Contact
12418399@zju.edu.cn

Oversight

Data monitoring committee
Yes
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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