Breast CancerNCT03706534
Breast Ultrasound Image Reviewed With Assistance of Deep Learning Algorithms
A study testing Ultrasound Image review with CADe, Ultrasound Image review with CADx and Ultrasound Image manual review in people with Breast Cancer and Breast Lesions, run by Samsung Medison at 1 site in United States.
Trial summary
This study evaluates a second review of ultrasound images of breast lesions using an interactive "deep learning" (or artificial intelligence) program developed by Samsung Medical Imaging, to see if this artificial intelligence will help the Radiologist make more accurate diagnoses. Read more about this study
- Who is it for?
- Ages 19 years and olderHealthy volunteers can take part
- Conditions the study is for
- Breast Cancer, Breast Lesions, Breast Mass
- What is being tested?
- Ultrasound Image review with CADe, Ultrasound Image review with CADx and Ultrasound Image manual review
- Type of treatment
- Medical device, Surgery or procedure
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 300 participants
- Where
- 1 siteUnited States
- Study dates
- 20 Sep 2018to 31 Jan 2020
- Phase
- Interventional
- Are there results?
- None posted in the registry
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 19 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
- Inclusion Criteria:
- Adult females or males recommended for ultrasound-guided breast lesion biopsy or ultrasound follow-up with at least one suspicious lesion
- Age > 18 years
- Able to provide informed consent
- Exclusion Criteria:
- Unable to read and understand English
- Unable or unwilling to provide informed consent
- A patient with current or previous diagnosis of breast cancer in the same quadrant
- Unable or unwilling to undergo study procedures
- Subject Characteristics
- Number of Subjects: 300 subjects from 300 separate breast lesions can be acquired. If a subject has more than 1 suspicious lesion, each may be chosen by the radiologist attending as suitable for "second review".
- Gender and Age of Subjects: Adult females or males aged 18 years or older who meet all of the inclusion criteria and none of the exclusion criteria will be considered for enrollment. Minors are excluded as breast cancer is very rare in this age group.
- Racial and Ethnic Origin: There are no enrollment exclusions based on economic status, race, or ethnicity. Based on local and United States census data, the expected ethnic distribution will be approximately 26 Hispanic (approx. 16%) and 134 non-Hispanic people. Furthermore, the expected racial distribution is expected to be approximately 126 White (approx. 79% of the whole study), 21 Black or African America (13%), 8 Asian (5%), and 5 of other categories (3%).
- Vulnerable Subjects: It is unlikely that any UR students or employees will be enrolled unless their primary physician refers them to UR Medicine Breast Imaging at Red Creek for breast ultrasound and a suspicious lesion is found. We do not expect any of these referrals to be from staffs who work directly with the PIs.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Breast Ultrasound Image Reviewed With Assistance of Deep Learning
This study evaluates a second review of ultrasound images of breast lesions using an interactive "deep learning" (or artificial intelligence) program developed by Samsung Medical Imaging, to see if this artificial intelligence will help the Radiologist make more accurate diagnoses.
Read the detailed description
Using ultrasound images prospectively acquired, the purpose of this study entails a second review of ultrasound images with suspicious breast lesions using an interactive "deep learning" (or artificial intelligence) program developed by SamsungMedison Co.,Ltd.
The images will be reviewed by the radiologists twice: first without, and then with assistance of artificial intelligence program by SamsungMedison Co., Ltd.
BIRADS system will be used in this study.
The objectives of the study are twofold: to quantify the statistical equivalence of radiologists' opinion and AI's output (CADe), and to check BIRADS score-based diagnostic accuracy (CADx) that is gained by the Radiologists' use of this interactive tool
- Conditions
- Breast Cancer, Breast Lesions, Breast Mass
- Being tested
- Ultrasound Image review with CADe, Ultrasound Image review with CADx, Ultrasound Image manual review, Biopsy
- Keywords
- Breast cancer, Breast Imaging
- Medical subject headings
- Breast Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Ultrasound Image review with CADeDevice
Also called S-Detect, S-Detect for Breast, CADe, Computer-Assisted Detection Device
This software is a computer-aided detection (CADe) software application, designed to assist radiologist to analyze breast ultrasound images. S-Detect automatically segments and classifies shape, orientation, margin, lesion boundary, echo pattern, and posterior feature characteristics of user-selected region of interest. The device uses deep learning methods to perform tissue segmentation and classification of images.
Ultrasound Image review with CADxDevice
Also called S-Detect, S-Detect for Breast, CADx, Computer-Assisted Diagnostic Device
This software is also a computer-assisted diagnostic(CADx) software application, designed to assist a medical doctor in determining diagnosis by presenting whether a lesion is malignant in a breast ultrasound image obtained from an ultrasound imaging device.
Ultrasound Image manual reviewDevice
Also called Convetional Ultrasound image
The images will be reviewed by the radiologists using BIRADS scheme without any assistance of artificial assistance. This review will be done off-line using a separate program in entirely manual mode. During this review, BIRADS descriptor choices by each radiologist and the time it takes for the radiologist to make such decision will be stored.
BiopsyProcedure or surgery
Suspicious lesions found on breast ultrasound are then followed either by ultrasound guided biopsy or ultrasound imaging every 6 months for two years. For those who undergo biopsy, ultrasound provides images which are used to localize the lesion and guide the placement of the biopsy needle. The sample is sent to pathology for diagnosis, while the ultrasound guidance images are stored. For those who have imaging follow-up, ultrasound images of the breast mass are obtained, digitally stored and interpreted by the radiologist typically using BIRADS scheme.
| Study group | Role | What they receive |
|---|---|---|
| Manual review | Active comparator | The images will be reviewed by the radiologists using BIRADS scheme without any assistance of artificial assistance. This review will be done off-line using a separate program in entirely manual mode. During this review, BIRADS descriptor choices by each radiologist and the time it takes for the radiologist to make such decision will be stored. Radiologists also make assessment decision without any intervention from artificial intelligence. 10 radiologists review manually. Receives: Device: Ultrasound Image review with CADe; Device: Ultrasound Image review with CADx; Device: Ultrasound Image manual review; Procedure: Biopsy |
| Review by S-Detect for Breast | Experimental | The same images will be separately processed by the artificial intelligence system (S-Detect for Breast) by Samsung. The two results, one by the radiologists and the other by artificial intelligence system, will be compared to statistically quantify equivalence (CADe). Receives: Device: Ultrasound Image review with CADe; Device: Ultrasound Image manual review |
| Review with assistance of S-Detect for Breast | Experimental | Second, the images will be reviewed by the radiologists with the help of artificial intelligence system, which is an interactive tool automatically providing recommendations on BIRADS descriptor choices that can be modified by the radiologists. The radiologists, after selecting all the descriptors of BIRADS, will decide the assessment categories. These decisions will be compared with the ground truths generated from the biopsy results or a 24-month follow-up (CADx). Receives: Device: Ultrasound Image review with CADx; Device: Ultrasound Image manual review; Procedure: Biopsy |
What is being measured
The primary outcome is the main question the study is designed to answer.
Concordance rate
Breast Imaging Reporting and Data System descriptors suggested by S-Detect for Breast are in good agreement with those selected by experts. In other words, the Breast Imaging Reporting and Data System Lexicon values generated by S-Detect for Breast are not statistically different from the consensus of experts.
Breast Imaging Reporting and Data System Assessment Category Score: The user makes the final decision on the Assessment Category Score. Using this Score, S-Detect displays the assessment description.
Category 0: Incomplete - Need Additional Imaging Evaluation Category 1: Negative Category 2: Benign Category 3: Probably Benign Category 4a: Low suspicion for malignancy Category 4b: Moderate suspicion for malignancy Category 4c: High suspicion for Malignancy Category 5: Highly Suggestive of Malignancy Category 6: Known Biopsy-Proven Malignancy
Measured: 2 days
Secondary outcomes (6)
Reporting time
Measure reporting time of Breast Imaging Reporting and Data System Lexicon value in Breast imaging by radiologists without S-Detect for Breast and also measured report time by radiologists with S-Detect for Breast.
Measured: 2 day
Consensus
Evaluate the consensus between manually reading of Breast Imaging without assistance and Automatically detection results(Breast Imaging Reporting and Data System Lexicons). Average of consensus is evaluated in both of Expert group and non-expert group.
Measured: 2 day
Accuracy
Comparing to the Breast Biopsy results, The accuracy of Breast Imaging results by radiologists with CADx will be evaluated.
Measured: 7 day
Sensitivity
Comparing to the Breast Biopsy results, The sensitivity of Breast Imaging results by radiologists with CADx will be evaluated.
Measured: 7 day
Specificity
Comparing to the Breast Biopsy results, The specificity of Breast Imaging results by radiologists with CADx will be evaluated.
Measured: 7 day
Area Under Curve
Comparing to the Breast Biopsy results, Area Under Curve (ROC analysis) of Breast Imaging results by radiologists with CADx will be evaluated.
Measured: 7 day
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted16 Oct 2018
- Study start20 Sep 2018
- Primary completion30 Nov 2019 (estimated)
- Study completion31 Jan 2020 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Breast CancerStudies of the same condition, open and under way.
- 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 N/A
- Primary purpose
- Device feasibility
- Allocation
- Randomised
- Intervention model
- Crossover
- Model description
- This clinical study performed by multiple reader multiple case (MRMC) study design, where as set of clinical readers evaulate under multiple reading condition. All Interpreting physician(reader) independently read all of the cases. (fully-crossed design).
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 300 participants (actual)
Sponsor and investigators
- Lead sponsor
- Samsung Medison
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- University of Rochester
- Responsible party
- Sponsor
- Investigators
- Avice O'Connell, Principal investigator, Department of Imaging Sciences, University of RochesterKevin Parker, Principal investigator, Department of Electrical & Computer Engineering, University of Rochester
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03706534
- Sponsor's protocol ID
- 300.08-2018-Samsungmedison-S
- Status last verified
- Oct 2019
- First submitted
- 11 Oct 2018
- Last updated
- 29 Oct 2019
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 29 Oct 2019. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Breast Ultrasound Image Reviewed With Assistance of Deep Learning
- ClinicalTrials.gov ID
- NCT03706534
- Acronym / sponsor ID
- 300.08-2018-Samsungmedison-S
- Conditions
- Breast Cancer, Breast Lesions, Breast Mass
- Keywords
- Breast cancer, Breast Imaging
- Study type
- Interventional
- Recruitment status
- Unknown status
- Enrolment
- 300 participants (actual)
- Lead sponsor
- Samsung MedisonIndustry (pharma, biotech, devices)
- Collaborators
- University of Rochester
- Study start
- 20 Sep 2018 (actual)
- Primary completion
- 30 Nov 2019 (estimated)
- Study completion
- 31 Jan 2020 (estimated)
- First posted
- 16 Oct 2018 (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 study evaluates a second review of ultrasound images of breast lesions using an interactive "deep learning" (or artificial intelligence) program developed by Samsung Medical Imaging, to see if this artificial intelligence will help the Radiologist make more accurate diagnoses.
Detailed description
Using ultrasound images prospectively acquired, the purpose of this study entails a second review of ultrasound images with suspicious breast lesions using an interactive "deep learning" (or artificial intelligence) program developed by SamsungMedison Co.,Ltd.
The images will be reviewed by the radiologists twice: first without, and then with assistance of artificial intelligence program by SamsungMedison Co., Ltd.
BIRADS system will be used in this study.
The objectives of the study are twofold: to quantify the statistical equivalence of radiologists' opinion and AI's output (CADe), and to check BIRADS score-based diagnostic accuracy (CADx) that is gained by the Radiologists' use of this interactive tool
Study design
- Primary purpose
- Device feasibility
- Allocation
- Randomised
- Intervention model
- Crossover
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 3
- Model description
- This clinical study performed by multiple reader multiple case (MRMC) study design, where as set of clinical readers evaulate under multiple reading condition. All Interpreting physician(reader) independently read all of the cases. (fully-crossed design).
| Arm | Type | Receives |
|---|---|---|
| Manual review | Active comparator | Device: Ultrasound Image review with CADe, Device: Ultrasound Image review with CADx, Device: Ultrasound Image manual review, Procedure: BiopsyThe images will be reviewed by the radiologists using BIRADS scheme without any assistance of artificial assistance. This review will be done off-line using a separate program in entirely manual mode. During this review, BIRADS descriptor choices by each radiologist and the time it takes for the radiologist to make such decision will be stored. Radiologists also make assessment decision without any intervention from artificial intelligence. 10 radiologists review manually. |
| Review by S-Detect for Breast | Experimental | Device: Ultrasound Image review with CADe, Device: Ultrasound Image manual reviewThe same images will be separately processed by the artificial intelligence system (S-Detect for Breast) by Samsung. The two results, one by the radiologists and the other by artificial intelligence system, will be compared to statistically quantify equivalence (CADe). |
| Review with assistance of S-Detect for Breast | Experimental | Device: Ultrasound Image review with CADx, Device: Ultrasound Image manual review, Procedure: BiopsySecond, the images will be reviewed by the radiologists with the help of artificial intelligence system, which is an interactive tool automatically providing recommendations on BIRADS descriptor choices that can be modified by the radiologists. The radiologists, after selecting all the descriptors of BIRADS, will decide the assessment categories. These decisions will be compared with the ground truths generated from the biopsy results or a 24-month follow-up (CADx). |
Who may qualify
- Ages
- 19 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
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 |
|---|---|---|
| Ultrasound Image review with CADeAlso: S-Detect, S-Detect for Breast, CADe, Computer-Assisted Detection DeviceThis software is a computer-aided detection (CADe) software application, designed to assist radiologist to analyze breast ultrasound images. S-Detect automatically segments and classifies shape, orientation, margin, lesion boundary, echo pattern, and posterior feature characteristics of user-selected region of interest. The device uses deep learning methods to perform tissue segmentation and classification of images. | Device | Manual review, Review by S-Detect for Breast |
| Ultrasound Image review with CADxAlso: S-Detect, S-Detect for Breast, CADx, Computer-Assisted Diagnostic DeviceThis software is also a computer-assisted diagnostic(CADx) software application, designed to assist a medical doctor in determining diagnosis by presenting whether a lesion is malignant in a breast ultrasound image obtained from an ultrasound imaging device. | Device | Manual review, Review with assistance of S-Detect for Breast |
| Ultrasound Image manual reviewAlso: Convetional Ultrasound imageThe images will be reviewed by the radiologists using BIRADS scheme without any assistance of artificial assistance. This review will be done off-line using a separate program in entirely manual mode. During this review, BIRADS descriptor choices by each radiologist and the time it takes for the radiologist to make such decision will be stored. | Device | Manual review, Review by S-Detect for Breast, Review with assistance of S-Detect for Breast |
| BiopsySuspicious lesions found on breast ultrasound are then followed either by ultrasound guided biopsy or ultrasound imaging every 6 months for two years. For those who undergo biopsy, ultrasound provides images which are used to localize the lesion and guide the placement of the biopsy needle. The sample is sent to pathology for diagnosis, while the ultrasound guidance images are stored. For those who have imaging follow-up, ultrasound images of the breast mass are obtained, digitally stored and interpreted by the radiologist typically using BIRADS scheme. | Procedure or surgery | Manual review, Review with assistance of S-Detect for Breast |
Primary outcome
Concordance rate
Time frame: 2 days
Breast Imaging Reporting and Data System descriptors suggested by S-Detect for Breast are in good agreement with those selected by experts. In other words, the Breast Imaging Reporting and Data System Lexicon values generated by S-Detect for Breast are not statistically different from the consensus of experts. Breast Imaging Reporting and Data System Assessment Category Score: The user makes the final decision on the Assessment Category Score. Using this Score, S-Detect displays the assessment description. Category 0: Incomplete - Need Additional Imaging Evaluation Category 1: Negative Category 2: Benign Category 3: Probably Benign Category 4a: Low suspicion for malignancy Category 4b: Moderate suspicion for malignancy Category 4c: High suspicion for Malignancy Category 5: Highly Suggestive of Malignancy Category 6: Known Biopsy-Proven Malignancy
6 secondary outcomes
Reporting time
Time frame: 2 day
Consensus
Time frame: 2 day
Accuracy
Time frame: 7 day
Sensitivity
Time frame: 7 day
Specificity
Time frame: 7 day
Area Under Curve
Time frame: 7 day
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 29 Oct 2019.
- Individual participant dataSharing planned: No
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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. This study is not recruiting at the moment.
Avice O'Connell principal investigator
Department of Imaging Sciences, University of Rochester
Kevin Parker principal investigator
Department of Electrical & Computer Engineering, University of Rochester
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Ultrasound Image review with CADe, Ultrasound Image review with CADx and Ultrasound Image manual review in people with Breast Cancer and Breast Lesions, run by Samsung Medison at 1 site 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?
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: status not confirmed, as of the sponsor's last update on 29 Oct 2019. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site 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.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Concordance rate (time frame: 2 days). 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 29 Oct 2019; AzTrials last refreshed its copy on 6 Nov 2026.