2024-03-28T20:29:38Zhttp://repisalud.isciii.es/oai/requestoai:repisalud.isciii.es:20.500.12105/67152022-08-10T08:18:48Zcom_20.500.12105_2053com_20.500.12105_2052com_20.500.12105_2051col_20.500.12105_2054
00925njm 22002777a 4500
dc
Pollan-Santamaria, Marina
author
Llobet, Rafael
author
Miranda-García, Josefa
author
Antón, Joaquín
author
Casals, María
author
Martínez, Inmaculada
author
Palop, Carmen
author
Ruiz-Perales, Francisco
author
Sánchez-Contador, Carmen
author
Vidal, Carmen
author
Perez-Gomez, Beatriz
author
Salas-Trejo, Dolores
author
2013-12
We developed a semi-automated tool to assess mammographic density (MD), a phenotype risk marker for breast cancer (BC), in full-field digital images and evaluated its performance testing its reproducibility, comparing our MD estimates with those obtained by visual inspection and using Cumulus, verifying their association with factors that influence MD, and studying the association between MD measures and subsequent BC risk. Three radiologists assessed MD using DM-Scan, the new tool, on 655 processed images (craniocaudal view) obtained in two screening centers. Reproducibility was explored computing pair-wise concordance correlation coefficients (CCC). The agreement between DM-Scan estimates and visual assessment (semi-quantitative scale, 6 categories) was quantified computing weighted kappa statistics (quadratic weights). DM-Scan and Cumulus readings were compared using CCC. Variation of DM-Scan measures by age, body mass index (BMI) and other MD modifiers was tested in regression mixed models with mammographic device as a random-effect term. The association between DM-Scan measures and subsequent BC was estimated in a case-control study. All BC cases in screening attendants (2007-2010) at a center with full-field digital mammography were matched by age and screening year with healthy controls (127 pairs). DM-Scan was used to blindly assess MD in available mammograms (112 cases/119 controls). Unconditional logistic models were fitted, including age, menopausal status and BMI as confounders. DM-Scan estimates were very reliable (pairwise CCC: 0.921, 0.928 and 0.916). They showed a reasonable agreement with visual MD assessment (weighted kappa ranging 0.79-0.81). DM-Scan and Cumulus measures were highly concordant (CCC ranging 0.80-0.84), but ours tended to be higher (4%-5% on average). As expected, DM-Scan estimates varied with age, BMI, parity and family history of BC. Finally, DM-Scan measures were significantly associated with BC (p-trend=0.005). Taking MD<7% as reference, OR per categories of MD were: OR7%-17%=1.32 (95% CI=0.59-2.99), OR17%-28%=2.28 (95% CI=1.03-5.04) and OR>=29%=3.10 (95% CI=1.35-7.14). Our results confirm that DM-Scan is a reliable tool to assess MD in full-field digital mammograms.
Springerplus. 2013; 2(1):242
2193-1801
http://hdl.handle.net/20.500.12105/6715
23865000
10.1186/2193-1801-2-242
SpringerPlus
Breast density
Computer-assisted tool
Density assessment
Mammographic density
Reliability
Validation of DM-Scan, a computer-assisted tool to assess mammographic density in full-field digital mammograms