The Nightingale Centre
Manchester, M23 9LT, United Kingdom
NCT Number: NCT05796219
Breast cancer (BC) is the commonest cause of death in young women. Breast screening in women aged 35-45, at increased risk due to their family history, has been shown to improve survival. However, 80% of women who develop BC do not have a family history. Numerous studies have shown that high mammographic density (MD) is one of the strongest risk factors for BC development. Full field digital mammography (FFDM) can be used to assess MD, however it is not recommended for population BC screening in those <40 years of age due to the concerns about the use of ionising radiation. Safe and accurate high throughput methods to quantify MD in young women are thus required to improve risk prediction and reduce BC mortality. This study aims to develop a low dose mammogram, with quantification of density using artificial intelligence, to facilitate high throughput risk assessment in young women. 600 women aged 30-45, previously identified as being at increased risk of BC and attending for annual mammography at The Nightingale Centre will be recruited. Participants will undergo FFDM of the right breast as usual, however, following acquisition of the craniocaudal (CC) view, the breast will remain compressed and the mammogram dose reduced by 90% to deliver a LD mammogram. This process will be repeated for the right medio-lateral oblique (MLO) view. The left breast FFDM will proceed as normal. It is estimated that each extra exposure will take 1-2 minutes only. Deep machine learning methods will be used to define the relationship between standard FFDM views and their low dose counterparts and determine which view (CC vs MLO) provides the best correlation to be taken forward to the next stage of the research.
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Notify Me30 year–45 year
Female
Interventional
Not applicable
Manchester, M23 9LT, United Kingdom
The more prolonged compression of the breast required to acquire the LD images may cause some additional breast discomfort. However, in a similar study in The Netherlands only 1% of women could not tolerate the procedure.
Participants will receive an extra dose of ionising radiation amounting to 20% of the radiation dose of a single FFDM view (of which 4 are usually taken, 2 on each breast). The risks associated with this are described in section B and entered into the PIS.
The research question for this study is whether an automated, low dose mammogram can be developed to provide an accurate assessment of mammographic density, and thus breast cancer risk, in women aged 30-45.
The two key objectives are:
Breast cancer is the commonest of all causes of death in young women. Currently the only factor triggering referral to risk assessment clinics is the presence of a family history. Although this is known to confer increased risk, only 20% of young women who develop BC actually have such a family history of the disease. Thus 80% of cases come 'out of the blue' and methods to assess risk in the general population are required if we are to improve survival (screening in those at increased risk aged 35-45 has been shown to reduce mortality). High mammographic density has been shown in multiple studies to confer significantly increased risk of BC, however population screening with full field digital mammograms is not recommended in those <40 primarily due to the reduced sensitivity and use of a moderate doses of ionising radiation. There is thus an urgent need for safe, high throughput, techniques to accurately define mammographic density in young women - the purpose of this study. Following consent and initial Case Report Form (CRF) completion, mammography will commence as standard. The right breast craniocaudal (CC) view will be performed first and the steps below followed:
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Low dose mammogram
Time frame: The low dose mammogram will be taken immediately after the full dose exposure, under the same breast compression.
Full dose and Low dose mammograms will be analysed using an established AI technique, the predicted Visual Analogue Score (pVAS), to determine the percent mammographic density (%MD). Correlation between the full and low dose image derived %MD across the whole study population will be assessed using Pearson correlation coefficient.
Manchester University NHS Foundation Trust
Other Gov
Technical Development of Automated Low Dose Risk Assessment Mammography (ALDRAM) in Women Attending for Annual Mammography Through a Family History Clinic
Acronym: ALDRAM
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