Breast CarcinomaPhase 1NCT06171607
Contrast Enhanced Ultrasound Medical Imaging for Identifying Breast Masses
A Phase 1 study testing Contrast-Enhanced Ultrasound, Perflutren Lipid Microspheres and Sulfur Hexafluoride Lipid Microspheres in people with Breast Carcinoma, run by University of Southern California at 2 sites in United States.
Trial summary
This clinical trial investigates the role of contrast enhanced ultrasound (CEUS) in identifying cystic breast masses as benign or malignant. Ultrasound is a diagnostic imaging test that uses sound waves to make pictures of the body without using radiation (x-rays). Read more about this study
- Who is it for?
- Ages 18 years and older, women only
- Conditions the study is for
- Breast Carcinoma
- What is being tested?
- Contrast-Enhanced Ultrasound, Perflutren Lipid Microspheres and Sulfur Hexafluoride Lipid Microspheres
- Type of treatment
- Injection or infusion, Surgery or procedure
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 100 participants
- Where
- 2 sitesUnited States
- Study dates
- 5 Nov 2020to 5 Nov 2027
- Phase
- Phase 1
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- Women only
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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
Who cannot join
- 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
Show all 13Show fewer
- 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
Trial locations and contacts
2 sites in 1 country. Contact the study team or a site near you to ask about taking part.
United States2 sites, 2 recruiting
- Recruiting
Los Angeles County-USC Medical Center
Los Angeles, California, 90033
Janet Jaime, 323-865-3205, Janet.Jaime@med.usc.edu
Bino A. Varghese, PhD
- Recruiting
USC / Norris Comprehensive Cancer Center
Los Angeles, California, 90033
Janet Jaime, 323-865-3205, Janet.Jaime@med.usc.edu
Bino A. Varghese, PhD
About this study
Official title: Characterizing Breast Masses Using an Integrative Framework of Machine Learning and Radiomics
This clinical trial investigates the role of contrast enhanced ultrasound (CEUS) in identifying cystic breast masses as benign or malignant. Ultrasound is a diagnostic imaging test that uses sound waves to make pictures of the body without using radiation (x-rays). Ultrasounds are widely used to diagnose many diseases in the body. This trial may help researchers learn if using CEUS will help in determining whether or not an ultrasound guided biopsy is necessary.
Read the detailed description
PRIMARY OBJECTIVES:
- To examine and compare the distribution of CEUS parameters in breast masses that were evaluated as Breast Imaging Reporting and Data System (BI-RADS) 4a, 4b, 4c or 5 by conventional ultrasound (US) and were recommended for ultrasound guided biopsy, and to evaluate whether these parameters can be used to classify suspicious cystic-appearing breast masses as benign or malignant.
Ia. To develop a CEUS-based radiomics workflow to extract radiomic metrics (> 1600 features) in classifying breast mass malignancy (Radiomics).
Ib. To develop a systematic and rigorous machine learning (ML)-based framework comprised of classification, cross-validation and statistical analyses to identify the best performing classifier for breast malignancy stratification based on CEUS-derived radiomic metrics (time-intensity curve [TIC] analysis and Radiomics).
Ic. To assess the independent contribution of radiomics classifier and time-intensity curve classifier to the model accuracy in discriminating benign from malignant cases (TIC analysis versus [vs.] Radiomics).
Id. To assess the potential benefit of machine learning classifier in preventing unnecessary biopsy (TIC analysis and Radiomics).
OUTLINE:
Patients receive a contrast agent (Lumason or DEFINITY) intravenously (IV) and then undergo CEUS scan over 60-90 minutes.
- Conditions
- Breast Carcinoma
- Being tested
- Contrast-Enhanced Ultrasound, Perflutren Lipid Microspheres, Sulfur Hexafluoride Lipid Microspheres
- Medical subject headings
- Breast Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Contrast-Enhanced UltrasoundProcedure or surgery
Also called CEUS
Undergo CEUS
Perflutren Lipid MicrospheresDrug
Also called Definity
Given IV
Sulfur Hexafluoride Lipid MicrospheresDrug
Also called Lumason, SF6 Lipid Microspheres, Sulfur Hexafluoride Lipid-type A Microspheres
Given IV
| Study group | Role | What they receive |
|---|---|---|
| Diagnostic (contrast agent, CEUS) | Experimental | Patients receive a contrast tracer (Lumason or DEFINITY) IV and then undergo CEUS scan over 60-90 minutes. Receives: Procedure: Contrast-Enhanced Ultrasound; Drug: Perflutren Lipid Microspheres; Drug: Sulfur Hexafluoride Lipid Microspheres |
What is being measured
The primary outcome is the main question the study is designed to answer.
Radiomics-based ML-classifier framework
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.
Measured: Up to 12 months
Performance of radiomics-based ML approach to prevent unnecessary biopsies
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.
Measured: Up to 12 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted14 Dec 2023
- Study start5 Nov 2020
- Primary completion5 Nov 2026 (estimated)
- Study completion5 Nov 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Breast CarcinomaStudies of the same condition, open and under way.
- More trials run by University of Southern CaliforniaThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase 1
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 100 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Southern California
- Sponsor type
- University, hospital or other
- Collaborators
- National Cancer Institute (NCI)
- Responsible party
- Sponsor
- Investigators
- Bino A Varghese, PhD, Principal investigator, University of Southern California
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06171607
- Sponsor's protocol ID
- 1B-19-5
- Other IDs
- NCI-2022-03665, 1B-19-5, P30CA014089
- Status last verified
- Jan 2026
- First submitted
- 14 Jul 2022
- Last updated
- 2 Feb 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- Yes
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 2 Feb 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Characterizing Breast Masses Using an Integrative Framework of Machine Learning and Radiomics
- ClinicalTrials.gov ID
- NCT06171607
- Acronym / sponsor ID
- 1B-19-5
- Conditions
- Breast Carcinoma
- Phase
- Phase 1
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 100 participants (estimated)
- Lead sponsor
- University of Southern CaliforniaUniversity, hospital or other
- Collaborators
- National Cancer Institute (NCI)
- Study start
- 5 Nov 2020 (actual)
- Primary completion
- 5 Nov 2026 (estimated)
- Study completion
- 5 Nov 2027 (estimated)
- First posted
- 14 Dec 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This clinical trial investigates the role of contrast enhanced ultrasound (CEUS) in identifying cystic breast masses as benign or malignant. Ultrasound is a diagnostic imaging test that uses sound waves to make pictures of the body without using radiation (x-rays). Ultrasounds are widely used to diagnose many diseases in the body. This trial may help researchers learn if using CEUS will help in determining whether or not an ultrasound guided biopsy is necessary.
Detailed description
PRIMARY OBJECTIVES:
- To examine and compare the distribution of CEUS parameters in breast masses that were evaluated as Breast Imaging Reporting and Data System (BI-RADS) 4a, 4b, 4c or 5 by conventional ultrasound (US) and were recommended for ultrasound guided biopsy, and to evaluate whether these parameters can be used to classify suspicious cystic-appearing breast masses as benign or malignant.
Ia. To develop a CEUS-based radiomics workflow to extract radiomic metrics (> 1600 features) in classifying breast mass malignancy (Radiomics).
Ib. To develop a systematic and rigorous machine learning (ML)-based framework comprised of classification, cross-validation and statistical analyses to identify the best performing classifier for breast malignancy stratification based on CEUS-derived radiomic metrics (time-intensity curve [TIC] analysis and Radiomics).
Ic. To assess the independent contribution of radiomics classifier and time-intensity curve classifier to the model accuracy in discriminating benign from malignant cases (TIC analysis versus [vs.] Radiomics).
Id. To assess the potential benefit of machine learning classifier in preventing unnecessary biopsy (TIC analysis and Radiomics).
OUTLINE:
Patients receive a contrast agent (Lumason or DEFINITY) intravenously (IV) and then undergo CEUS scan over 60-90 minutes.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Diagnostic (contrast agent, CEUS) | Experimental | Procedure: Contrast-Enhanced Ultrasound, Drug: Perflutren Lipid Microspheres, Drug: Sulfur Hexafluoride Lipid MicrospheresPatients receive a contrast tracer (Lumason or DEFINITY) IV and then undergo CEUS scan over 60-90 minutes. |
Who may qualify
- Ages
- 18 years and older
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- 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
Key exclusion criteria (13 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Contrast-Enhanced UltrasoundAlso: CEUSUndergo CEUS | Procedure or surgery | Diagnostic (contrast agent, CEUS) |
| Perflutren Lipid MicrospheresAlso: DefinityGiven IV | Drug | Diagnostic (contrast agent, CEUS) |
| Sulfur Hexafluoride Lipid MicrospheresAlso: Lumason, SF6 Lipid Microspheres, Sulfur Hexafluoride Lipid-type A MicrospheresGiven IV | Drug | Diagnostic (contrast agent, CEUS) |
Primary outcome
Radiomics-based ML-classifier framework
Time frame: Up 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 biopsies
Time frame: Up 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.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 2 Feb 2026.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Bino A Varghese, PhD principal investigator
University of Southern California
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A Phase 1 study testing Contrast-Enhanced Ultrasound, Perflutren Lipid Microspheres and Sulfur Hexafluoride Lipid Microspheres in people with Breast Carcinoma, run by University of Southern California at 2 sites in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 13 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 2 Feb 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
What does this phase mean?
Phase 1 studies test a treatment in a small group of people for the first time or in a new way, mainly to check safety and find the right dose.
Not every study follows the same path, and some studies (observational studies, device studies) have no phase.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Janet Jaime (323-865-3205, Janet.jaime@med.usc.edu), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Radiomics-based ML-classifier framework (time frame: Up to 12 months). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 2 Feb 2026.