| Title |
Validation of DM-Scan, a computer-assisted tool to assess mammographic density in full-field digital mammograms
|
|---|---|
| Published in |
SpringerPlus, May 2013
|
| DOI | 10.1186/2193-1801-2-242 |
| Pubmed ID | |
| Authors |
Marina Pollán, Rafael Llobet, Josefa Miranda-García, Joaquín Antón, María Casals, Inmaculada Martínez, Carmen Palop, Francisco Ruiz-Perales, Carmen Sánchez-Contador, Carmen Vidal, Beatriz Pérez-Gómez, Dolores Salas-Trejo |
| Abstract |
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. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 3% |
| Unknown | 34 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 17% |
| Student > Master | 4 | 11% |
| Student > Ph. D. Student | 3 | 9% |
| Other | 2 | 6% |
| Student > Doctoral Student | 2 | 6% |
| Other | 10 | 29% |
| Unknown | 8 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 13 | 37% |
| Computer Science | 4 | 11% |
| Psychology | 3 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 6% |
| Nursing and Health Professions | 2 | 6% |
| Other | 4 | 11% |
| Unknown | 7 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 July 2013.
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#14,753,796
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Outputs from SpringerPlus
#834
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#115,628
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Outputs of similar age from SpringerPlus
#43
of 98 outputs
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