Menu
Recruiting NCT07415499

Breast Density Impact on Mammographic Screening for Breast Cancer Diagnosis

Observational Breast Cancer Screening Breast Cancer Screening and Diagnosis

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: No intervention is administered..
Who it may be relevant to
Registry conditions: Breast Cancer Screening, Breast Cancer Screening and Diagnosis. Basic parameters: 45 years — 75 years · Female.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
Italy
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Official title

Retrospective Study on Patients Undergoing Mammographic Screening to Evaluate the Impact of Breast Density on Breast Cancer Diagnosis

Overview

This retrospective, observational study aims to evaluate how breast density affects the accuracy and outcomes of mammographic screening for breast cancer within the regional screening program "Prevenzione Serena". Breast density is an important factor because dense breast tissue can make it more difficult to detect breast cancer on a mammogram. Dense tissue and tumors both appear white on a mammogram, which may hide abnormalities and lead to missed cancers or false-positive results. Women aged 45 to 75 years who underwent routine mammographic screening at ASL CN2 between September 2023 and May 2024 will be included. Breast density will be classified using the BI-RADS system (categories A-D), and the study will assess whether women with dense breasts (categories C and D) experience higher rates of recalls for second-level examinations such as ultrasound, MRI, etc). The study also includes an internal validation of Insight BD, an automated breast-density measurement software used at ASL CN2. The software will be evaluated using a mammography phantom (to verify technical accuracy) and by comparing its BI-RADS density classifications with readings from two radiologists (one expert and one less experienced). This will help determine whether the software can support radiologists, especially in evaluating dense breast tissue. Additional factors such as menopausal status, family history of breast cancer, and hormone therapy will also be examined to understand how they relate to breast density and screening outcomes. The study aims to quantify the frequency of false-positive recalls-cases in which additional tests are recommended but cancer is not found-because these events can increase patient anxiety and healthcare workload. Ultimately, this research seeks to provide evidence that may inform future screening guidelines and support more personalized approaches, particularly for women with dense breasts.

Detailed description

This retrospective, monocentric, observational study investigates the impact of breast density on mammographic screening performance in the regional program "Prevenzione Serena," implemented at ASL CN2 (Piedmont, Italy). The primary objective is to evaluate the association between BI-RADS breast-density categories and the frequency of recalls for second-level diagnostic examinations among women aged 45-75 undergoing screening mammography between 25 September 2023 and 3 May 2024.

Breast density is a known factor that can reduce the sensitivity of mammography. Dense fibroglandular tissue appears radiopaque and may mask suspicious lesions, leading to false-negative or false-positive examinations. Women with dense breasts (BI-RADS categories C-D) also have an independently increased risk of breast cancer. For these reasons, the study aims to characterize how breast density influences recall rates, diagnostic appropriateness, and overall screening performance in a real-world population.

A secondary goal is the internal validation of Insight BD, an automated breast-density assessment software integrated into the Siemens Mammomat Revelation mammography system used at ASL CN2. The validation includes:

1. Technical validation using a dedicated mammographic phantom with known density values to determine measurement accuracy and repeatability; 2. Diagnostic validation through comparison between the BI-RADS density category assigned by the software and those assigned by two radiologists (one expert, one non-expert).

The study will also examine associations between breast density and key clinical factors, including menopausal status, family history of breast cancer, and systemic hormone therapy. Furthermore, the frequency of false-positive recalls (additional testing without a final diagnosis of cancer) will be assessed, given their clinical, psychological, and organizational implications.

The study aims to characterize density-related patterns in screening performance, quantify false-positive recalls, and contribute evidence to support future updates to breast-screening guidelines and potential personalized screening strategies, especially for women with dense breast tissue.

Interventions

  • Other No intervention is administered.
    No intervention is administered.

Primary outcome measures

  • Recall Rate for Second-Level Examinations by BI-RADS Breast Density Category [Time frame: September 2023 - May 2024]
Secondary outcome measures (4)
  • Technical Performance of Insight BD: Accuracy and Repeatability on Breast Density Phantom [Time frame: September 2023 - May 2024]
  • Concordance Between Insight BD BI-RADS Classification and Radiologist Assessment [Time frame: September 2023 - May 2024]
  • Recall Rate for Second-Level Examinations in Negative Mammographic Screens by BI-RADS Density [Time frame: September 2023 - May 2024]
  • Distribution of Breast Density by Menopausal Status, Hormonal Therapy, and Family History [Time frame: September 2023 - May 2024]

Eligibility criteria

Inclusion criteria

  • Women aged 45 to 75 years who participated in the "Prevenzione Serena" mammography screening program and underwent screening mammography at ASL CN2 between September 25, 2023, and May 3, 2024.
  • Signed informed consent or equivalent substitute declaration, when applicable.

Exclusion criteria

  • Women with a history of mastectomy.
  • Women with breast implants.
  • Women with cardiac implantable devices, such as pacemakers or loop recorders.
  • Cases in which the Insight BD software cannot be applied due to compression thickness below 15 mm.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Observational model
Cohort

Study locations

Italy · 1 center
  • SSD Fisica Sanitaria - Ospedale Michele e Pietro Ferrero di Verduno (CN) - ASL CN2 — Verduno

Publications

  • Ray KM, Price ER, Joe BN. Breast density legislation: mandatory disclosure to patients, alternative screening, billing, reimbursement. AJR Am J Roentgenol. 2015 Feb;204(2):257-60. doi: 10.2214/AJR.14.13558. PMID 25615746
  • Dehkordy SF, Carlos RC. Dense Breast Legislation in the United States: State of the States. J Am Coll Radiol. 2016 Nov;13(11S):R53-R57. doi: 10.1016/j.jacr.2016.09.027. PMID 27814815
  • Damases CN, Brennan PC, Mello-Thoms C, McEntee MF. Mammographic Breast Density Assessment Using Automated Volumetric Software and Breast Imaging Reporting and Data System (BIRADS) Categorization by Expert Radiologists. Acad Radiol. 2016 Jan;23(1):70-7. doi: 10.1016/j.acra.2015.09.011. Epub 2015 Oct 26. PMID 26514436
  • Pesce K, Tajerian M, Chico MJ, Swiecicki MP, Boietti B, Frangella MJ, Benitez S. Interobserver and intraobserver variability in determining breast density according to the fifth edition of the BI-RADS(R) Atlas. Radiologia (Engl Ed). 2020 Nov-Dec;62(6):481-486. doi: 10.1016/j.rx.2020.04.006. Epub 2020 May 31. English, Spanish. PMID 32493654
  • Sheehan J. Brain fragments: Leksell's autobiography newly translated to English. J Neurooncol. 2022 Apr;157(2):383. doi: 10.1007/s11060-022-03968-y. Epub 2022 Mar 29. No abstract available. PMID 35348987
  • Martinez-Navarro B, Sanchis R, Asedegbega-Nieto E, Solsona B, Ivars-Barcelo F. (Ag)Pd-Fe3O4 Nanocomposites as Novel Catalysts for Methane Partial Oxidation at Low Temperature. Nanomaterials (Basel). 2020 May 21;10(5):988. doi: 10.3390/nano10050988. PMID 32455643
  • Zimri K, Hesseling AC, Godfrey-Faussett P, Schaaf HS, Seddon JA. Why do child contacts of multidrug-resistant tuberculosis not come to the assessment clinic? Public Health Action. 2012 Sep 21;2(3):71-5. doi: 10.5588/pha.12.0024. PMID 26392955
  • Oliver A, Tortajada M, Llado X, Freixenet J, Ganau S, Tortajada L, Vilagran M, Sentis M, Marti R. Breast Density Analysis Using an Automatic Density Segmentation Algorithm. J Digit Imaging. 2015 Oct;28(5):604-12. doi: 10.1007/s10278-015-9777-5. PMID 25720749

Identifiers

NCT: NCT07415499 · SINATRA

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗