Breast Cancer DiagnosisAICAMAMMELLANCT05858762
Artificial Intelligence for Automated Diagnosis of Breast Cancer
An observational study of Breast Cancer Diagnosis, run by Regina Elena Cancer Institute at 2 sites in Italy.
Trial summary
Mammography is a two-dimensional imaging technique which involves the tissues overlapping under the projective image; dense glandular tissue above or below the lesion can reduce the visibility of the lesion. Read more about this study
- Who is it for?
- Ages 18 years and older, women only
- Conditions the study is for
- Breast Cancer Diagnosis
- What is being tested?
- Breast digital tomosynthesis
- How many people
- 200 participants
- Where
- 2 sitesItaly
- Study dates
- 20 Oct 2020to 31 Dec 2023
- How long will I take part?
- 24 Months
- Phase
- Observational
- 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 18 years and older
- Women only
- No healthy volunteers
- Adult, Older adult
Study population: Women undergoing mammography
Who may be able to join
- Patients who refer to the Regina Elena for diagnostic mammography tests
- Informed consent
Who cannot join
- presence of prostheses, artifacts, outcomes of a study in the breast intervention under the study
Trial locations and contacts
2 sites in 1 country.
Italy2 sites, 2 recruiting
- Recruiting
Università degli Studi di Napoli Federico II
Naples, 80138
Giovanni Mettivier
- Recruiting
"Regina Elena" National Cancer Institute
Rome, 00144
About this study
Official title: Study of an Artificial Intelligence Algorithm for the Classification of Digital Tomosynthesis Breast Images for Automated Breast Cancer Diagnosis
Mammography is a two-dimensional imaging technique which involves the tissues overlapping under the projective image; dense glandular tissue above or below the lesion can reduce the visibility of the lesion.
The trouble could be the interpretation of the image obtained which may lead to the inability to visualize a fist stage cancer and the probability that to a healthy person will be diagnosed a pathology that is not present (false positive). The introduction of an almost three-dimensional technique imaging called breast digital tomosynthesis (DBT) can overcome most limitations. In the last 5 years image analysis methods based on Artificial Intelligence (, AI) have also been massively introduced in breast cancer detection. The study is a prospective observational study based on Artificial intelligence whose the mail goal is to develop a method to identify a lesion.
- Conditions
- Breast Cancer Diagnosis
- Being tested
- Breast digital tomosynthesis
- Medical subject headings
- Breast Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Breast digital tomosynthesisDiagnostic test
Introduction of an almost three-dimensional imaging technique called breast digital tomosynthesis
What is being measured
The primary outcome is the main question the study is designed to answer.
Artificial Intelligence system to detect a lesion
Lesion detction is based on breast density, case type, BIRADS assessment categories, mammographic appearance, size and pathological profile of malignant lesions
Measured: 12 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted15 May 2023
- Study start20 Oct 2020
- Primary completion25 Nov 2022
- Study completion31 Dec 2023 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Breast Cancer DiagnosisStudies 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
- Observational
- Observational model
- Other
- Time perspective
- Prospective
- Enrolment
- 200 participants (estimated)
- Target duration
- 24 Months
Sponsor and investigators
- Lead sponsor
- Regina Elena Cancer Institute
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05858762
- Sponsor's protocol ID
- RS1414/20
- Acronym
- AICAMAMMELLA
- Status last verified
- Mar 2023
- First submitted
- 28 Mar 2023
- Last updated
- 15 May 2023
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 15 May 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Study of an Artificial Intelligence Algorithm for the Classification of Digital Tomosynthesis Breast Images for Automated Breast Cancer Diagnosis
- ClinicalTrials.gov ID
- NCT05858762
- Acronym / sponsor ID
- AICAMAMMELLA / RS1414/20
- Conditions
- Breast Cancer Diagnosis
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 200 participants (estimated)
- Lead sponsor
- Regina Elena Cancer InstituteUniversity, hospital or other
- Study start
- 20 Oct 2020 (actual)
- Primary completion
- 25 Nov 2022 (actual)
- Study completion
- 31 Dec 2023 (estimated)
- First posted
- 15 May 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.
Mammography is a two-dimensional imaging technique which involves the tissues overlapping under the projective image; dense glandular tissue above or below the lesion can reduce the visibility of the lesion.
The trouble could be the interpretation of the image obtained which may lead to the inability to visualize a fist stage cancer and the probability that to a healthy person will be diagnosed a pathology that is not present (false positive). The introduction of an almost three-dimensional technique imaging called breast digital tomosynthesis (DBT) can overcome most limitations. In the last 5 years image analysis methods based on Artificial Intelligence (, AI) have also been massively introduced in breast cancer detection. The study is a prospective observational study based on Artificial intelligence whose the mail goal is to develop a method to identify a lesion.
Study design
- Observational model
- Other
- Time perspective
- Prospective
- Target follow-up
- 24 Months
Who may qualify
- Ages
- 18 years and older
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Women undergoing mammography
Key inclusion criteria (2 listed)
- Patients who refer to the Regina Elena for diagnostic mammography tests
- Informed consent
Key exclusion criteria (1 listed)
- presence of prostheses, artifacts, outcomes of a study in the breast intervention under the study
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 |
|---|---|---|
| Breast digital tomosynthesisIntroduction of an almost three-dimensional imaging technique called breast digital tomosynthesis | Diagnostic test | – |
Primary outcome
Artificial Intelligence system to detect a lesion
Time frame: 12 months
Lesion detction is based on breast density, case type, BIRADS assessment categories, mammographic appearance, size and pathological profile of malignant lesions
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 May 2023.
- Individual participant dataSharing planned: Undecided
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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.
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Breast Cancer Diagnosis, run by Regina Elena Cancer Institute at 2 sites in Italy.
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 2 inclusion and 1 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: status not confirmed, as of the sponsor's last update on 15 May 2023. 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 Italy. 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?
Contact Valeria Landoni (+39 06 52665602, valeria.landoni@ifo.it), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Artificial Intelligence system to detect a lesion (time frame: 12 months). 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 15 May 2023.