Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
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.
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:
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.
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Screening cohort | Women aged 45-75 who underwent routine mammographic screening within the "Prevenzione Serena" program at ASL CN2 between September 2023 and May 2024. Breast density (BI-RADS A-D) will be evaluated, along with recall rates, false-positive findings, and comparisons of automated breast-density assessment (Insight BD) with radiologist readings. No interventions are administered; data are collected retrospectively from clinical records. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| No intervention is administered. | Other | No intervention is administered. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Recall Rate for Second-Level Examinations by BI-RADS Breast Density Category | Percentage of women recalled for second-level diagnostic examinations among all women undergoing mammographic screening, calculated separately for each BI-RADS density category (A, B, C, D) and for the dichotomized groups A-B versus C-D. | September 2023 - May 2024 |
| Measure | Description | Time Frame |
|---|---|---|
| Technical Performance of Insight BD: Accuracy and Repeatability on Breast Density Phantom | Evaluation of the volumetric breast density percentage produced by Insight BD on a standardized phantom, assessing measurement accuracy compared with the reference phantom values and repeatability across repeated acquisitions. | September 2023 - May 2024 |
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
The study will include women aged 45 to 75 years who participated in the "Prevenzione Serena" mammography screening program and underwent screening mammography at ASL CN2 using a Siemens MAMMOMAT Revelation mammography system between September 25, 2023, and May 3, 2024.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Francesco Lucio, Principal Investigator | Contact | +39.0172.1408486 | flucio@aslcn2.it |
Not provided
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| SSD Fisica Sanitaria - Ospedale Michele e Pietro Ferrero di Verduno (CN) - ASL CN2 | Recruiting | Verduno | Italy/CN | 12060 | Italy |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 25615746 | Background | 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. | |
| 27814815 | Background | 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. |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| ID | Term |
|---|---|
| D004194 | Disease |
| D001943 | Breast Neoplasms |
| ID | Term |
|---|---|
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
Not provided
Not provided
Not provided
Not provided
Not provided
| Concordance Between Insight BD BI-RADS Classification and Radiologist Assessment | Diagnostic agreement between Insight BD BI-RADS breast density classification and radiologist assessments. The outcome includes:
| September 2023 - May 2024 |
| Recall Rate for Second-Level Examinations in Negative Mammographic Screens by BI-RADS Density | Proportion of women recalled for second-level diagnostic examinations among those with a negative screening mammogram, stratified by BI-RADS breast density categories (A, B, C, D) and by dichotomized density groups (A-B vs C-D). | September 2023 - May 2024 |
| Distribution of Breast Density by Menopausal Status, Hormonal Therapy, and Family History | Proportion of participants in each BI-RADS breast density category (A, B, C, D), and in dichotomized density groups (A-B vs C-D), stratified by: menopausal status (pre/post-menopause), use of hormonal therapy (yes/no), family history of breast cancer (yes/no). | September 2023 - May 2024 |
| 26514436 | Background | 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. |
| 32493654 | Background | 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. |
| 35348987 | Background | 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. |
| 32455643 | Background | 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. |
| 26392955 | Background | 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. |
| 25720749 | Background | 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. |
| 25239205 | Background | Eng A, Gallant Z, Shepherd J, McCormack V, Li J, Dowsett M, Vinnicombe S, Allen S, dos-Santos-Silva I. Digital mammographic density and breast cancer risk: a case-control study of six alternative density assessment methods. Breast Cancer Res. 2014 Sep 20;16(5):439. doi: 10.1186/s13058-014-0439-1. |
| 27011371 | Background | Sartor H, Lang K, Rosso A, Borgquist S, Zackrisson S, Timberg P. Measuring mammographic density: comparing a fully automated volumetric assessment versus European radiologists' qualitative classification. Eur Radiol. 2016 Dec;26(12):4354-4360. doi: 10.1007/s00330-016-4309-3. Epub 2016 Mar 24. |
| 27598536 | Background | Jeffers AM, Sieh W, Lipson JA, Rothstein JH, McGuire V, Whittemore AS, Rubin DL. Breast Cancer Risk and Mammographic Density Assessed with Semiautomated and Fully Automated Methods and BI-RADS. Radiology. 2017 Feb;282(2):348-355. doi: 10.1148/radiol.2016152062. Epub 2016 Sep 5. |
| D001941 | Breast Diseases |
| D012871 | Skin Diseases |
| D017437 | Skin and Connective Tissue Diseases |