Breast CancerCOMPRESSNCT06469606
Study on Female Patients' Mammographic Texture Features
A study testing AI tool in people with Breast Cancer and Artificial Intelligence, run by Tampere University Hospital at 1 site in Finland.
Trial summary
Mammography is the most common method for breast imaging, and it provides information for model building and analysis. Radiomics applied to mammography has the potential to revolutionize clinical decision-making by providing valuable insights into risk assessment and disease detection. Read more about this study
- Who is it for?
- Ages 18 years and older, women only
- Conditions the study is for
- Breast Cancer, Artificial Intelligence, Mammography
- What is being tested?
- AI tool
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 200 participants
- Where
- 1 siteFinland
- Study dates
- 17 Jun 2024to 15 Dec 2038
- Phase
- Interventional
- 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
- Candidate is a biological female aged 18 years or above;
- Candidate is willing and able to give informed consent and gives their written consent for the participation in the study;
- There is a clinical indication for a uni- or bilateral mastectomy
Who cannot join
- Candidate lacks the capacity to provide informed consent;
- Candidate has breast implants
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Finland1 site, 1 recruiting
- Recruiting
Wellbeing Services County of Pirkanmaa
Tampere
About this study
Official title: A Cohort Study on feMale Patients' mammogRaphic texturE featureS: the COMPRESS Trial
Mammography is the most common method for breast imaging, and it provides information for model building and analysis. Radiomics applied to mammography has the potential to revolutionize clinical decision-making by providing valuable insights into risk assessment and disease detection. Despite this, the influence of imaging parameters and clinical and biological factors on radiological texture features remains poorly understood. There is a pressing need to overcome the obstacle of system-inherent effects on mammographic images to facilitate the translation of radiological texture features into routine clinical practice by enabling reliable and robust AI-based or AI-aided decision-making. Furthermore, understanding the relationship between imaging parameters, textural features, and clinical and biological information supports the clinical use of AI. The objective of this study is to evaluate AI methods for clinical practice and to study how it relates to clinical factors and biological features.
- Conditions
- Breast Cancer, Artificial Intelligence, Mammography
- Being tested
- AI tool
- Medical subject headings
- Breast Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI toolDevice
Both the arms will undergo the use of "AI tool" developed in the group. The tool will be trained to detect outcomes.
| Study group | Role | What they receive |
|---|---|---|
| Participant diagnosed with breast cancer | Experimental | Participants diagnosed with breast cancer who will undergo a mastectomy operation Receives: Device: AI tool |
| Participant not diagnosed with breast cancer | Experimental | Participants who will undergo a mastectomy operation for a non-breast cancer related clinical indication Receives: Device: AI tool |
What is being measured
The primary outcome is the main question the study is designed to answer.
Mammographic texture features
Aim: to evaluate how imaging parameters affect the mammographic texture features
Measured: Through study completion, an average of 5 year
Secondary outcomes (1)
Biological features
Aim: To evaluate whether there is an interplay between mammographic texture feature parameters and pathological and biological features (e.g., breast cancer biomarkers)
Measured: through study completion, an average of 10 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted21 Jun 2024
- Study start17 Jun 2024
- Primary completion15 Dec 2035 (estimated)
- Study completion15 Dec 2038 (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
- Diagnosis
- Allocation
- Non-randomised
- Intervention model
- Single group
- Masking
- Single blind
- Who is masked
- Participant
- Enrolment
- 200 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Tampere University Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- Tampere University, Kuopio University Hospital, University of Eastern Finland, University of Turku, University of Oulu
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06469606
- Sponsor's protocol ID
- R23077
- Acronym
- COMPRESS
- Status last verified
- Jul 2026
- First submitted
- 30 May 2024
- Last updated
- 5 Aug 2026
- 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 5 Aug 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Cohort Study on feMale Patients' mammogRaphic texturE featureS: the COMPRESS Trial
- ClinicalTrials.gov ID
- NCT06469606
- Acronym / sponsor ID
- COMPRESS / R23077
- Conditions
- Breast Cancer, Artificial Intelligence, Mammography
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 200 participants (estimated)
- Lead sponsor
- Tampere University HospitalUniversity, hospital or other
- Collaborators
- Tampere University, Kuopio University Hospital, University of Eastern Finland, University of Turku, University of Oulu
- Study start
- 17 Jun 2024 (actual)
- Primary completion
- 15 Dec 2035 (estimated)
- Study completion
- 15 Dec 2038 (estimated)
- First posted
- 21 Jun 2024 (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 the most common method for breast imaging, and it provides information for model building and analysis. Radiomics applied to mammography has the potential to revolutionize clinical decision-making by providing valuable insights into risk assessment and disease detection. Despite this, the influence of imaging parameters and clinical and biological factors on radiological texture features remains poorly understood. There is a pressing need to overcome the obstacle of system-inherent effects on mammographic images to facilitate the translation of radiological texture features into routine clinical practice by enabling reliable and robust AI-based or AI-aided decision-making. Furthermore, understanding the relationship between imaging parameters, textural features, and clinical and biological information supports the clinical use of AI. The objective of this study is to evaluate AI methods for clinical practice and to study how it relates to clinical factors and biological features.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Non-randomised
- Intervention model
- Single group
- Masking
- Single blind (participant)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Participant diagnosed with breast cancer | Experimental | Device: AI toolParticipants diagnosed with breast cancer who will undergo a mastectomy operation |
| Participant not diagnosed with breast cancer | Experimental | Device: AI toolParticipants who will undergo a mastectomy operation for a non-breast cancer related clinical indication |
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)
- Candidate is a biological female aged 18 years or above;
- Candidate is willing and able to give informed consent and gives their written consent for the participation in the study;
- There is a clinical indication for a uni- or bilateral mastectomy
Key exclusion criteria (2 listed)
- Candidate lacks the capacity to provide informed consent;
- Candidate has breast implants
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 |
|---|---|---|
| AI toolBoth the arms will undergo the use of "AI tool" developed in the group. The tool will be trained to detect outcomes. | Device | Participant diagnosed with breast cancer, Participant not diagnosed with breast cancer |
Primary outcome
Mammographic texture features
Time frame: Through study completion, an average of 5 year
Aim: to evaluate how imaging parameters affect the mammographic texture features
1 secondary outcome
Biological features
Time frame: through study completion, an average of 10 year
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 5 Aug 2026.
- 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.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI tool in people with Breast Cancer and Artificial Intelligence, run by Tampere University Hospital at 1 site in Finland.
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 2 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 5 Aug 2026. 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 Finland. 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?
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 Otso Arponen, MD, PhD (+3583311611, otso.arponen@tuni.fi), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Mammographic texture features (time frame: Through study completion, an average of 5 year). 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 5 Aug 2026.