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Contrast-Enhanced Ultrasound for Identifying Breast Masses

This study is looking into whether a special type of ultrasound, called Contrast-Enhanced Ultrasound (CEUS), can help tell if breast masses are benign (non-cancerous) or malignant (cancerous). You would receive an intravenous (IV) injection of a contrast agent, either Perflutren Lipid Microspheres (DEFINITY) or Sulfur Hexafluoride Lipid Microspheres (Lumason), before undergoing the CEUS scan. The goal is to see if CEUS can help doctors decide if an ultrasound-guided biopsy is truly needed. Researchers will use computer analysis (machine learning) to analyze the CEUS images. This study is for women aged 18 and older who have newly diagnosed breast masses that are rated as BIRADS 4a, 4b, 4c, or 5 by a regular ultrasound and are recommended for biopsy. The study aims to measure how well this approach can prevent unnecessary biopsies over a period of up to 12 months. The current recruitment status is unclear.

Study design
This is an interventional study involving 100 women. It is not specified if it is randomized or blinded.
What's involved
You would receive an intravenous contrast agent and then undergo a CEUS scan, which takes 60-90 minutes.
Compensation
Not stated in the trial record.
Follow-up
The primary outcomes are measured up to 12 months after the CEUS scan.

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NCT06171607

Contrast Enhanced Ultrasound Medical Imaging for Identifying Breast Masses

Recruiting
PHASE1Ages 18+InterventionalDiagnostic
University of Southern California
~100 participants
Updated 2026-02-02 on ClinicalTrials.gov
What's tested:Contrast-Enhanced UltrasoundPerflutren Lipid MicrospheresSulfur Hexafluoride Lipid Microspheres

At a glance

Recruiting sites
2 of 2 listed sites are recruiting right now
RecruitingSuspended, closed, or not yet open
What they're measuring
Radiomics-based ML-classifier framework
Measured over Up to 12 months
+1 more outcome measured

Conditions

Breast Carcinoma

Explore related trials

Breast Carcinoma

Where it's being run

2 sites across 1 states
California2

Study leadership

  • Bino A Varghese, PhD · PRINCIPAL_INVESTIGATOR · University of Southern California

Who to contact

Janet Jaime
[email protected]
323-865-3205
Email the study team

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Do you actually qualify for this trial?

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Eligibility criteria

Inclusion

Newly diagnosed breast masses assigned as BIRADS 4a, 4b, 4c or 5 by conventional US and recommended for ultrasound guided biopsy
Age \>= 18 years
Female

Exclusion

Contraindications to microbubble contrast: Patients who have a known pulmonary hypertension and any known hypersensitivity to US contrast agent
Women with renal failure or insufficiency (only if patient is receiving CESM scan)
Women with Iodine contrast allergy (only if patient is receiving CESM scan)
Women with the largest side of the mass measuring ≤ 1 cm (only if patient is receiving CEUS scan)
Women who are pregnant, possibly pregnant, or lactating
Women currently undergoing neoadjuvant chemotherapy
Women \< 18 years of age
Patient ≤ 30 years (only if patient is receiving CESM scan)
Masses in the same breast that had prior lumpectomy for cancer
Women with cancer in the same breast will be excluded however, women with cancer in the contralateral breast will be eligible to participate in the study
Women with an allergy to perflutren (only if patient is receiving CEUS scan)
Prior history of biopsy for that specific lesion
Women with breast implants

What this trial measures

  • Radiomics-based ML-classifier frameworkUp to 12 months

    The performance of radiomics-based ML classifier framework will be compared to the performance of the TIC metrics. The joint performance of radiomics and TIC analysis will be compared to their individual performances. The classifier performance will be assessed using the area under curve (AUC). The Z-test will be used to compare the difference between the area under the curves 1) AUCboth versus (vs.) AUCradiomic 2) AUCboth vs. AUCTIC 3) AUCTIC vs. AUCradiomic.

  • Performance of radiomics-based ML approach to prevent unnecessary biopsiesUp to 12 months

    Will assess the percentage of benign cases that can be classified as benign by ML (Specificity) thus been prevented from biopsy. Will select the diagnostic cut-off point based on the ROC curve constructed from the predicted probability. Such a cut-off point will result in a maximal sensitivity (100%). Specificity with 95% Clopper Pearson confidence interval will be obtained.