| 1. |
- Weinstein, John N., et al.
(author)
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The cancer genome atlas pan-cancer analysis project
- 2013
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:10, s. 1113-1120
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Research review (peer-reviewed)abstract
- The Cancer Genome Atlas (TCGA) Research Network has profiled and analyzed large numbers of human tumors to discover molecular aberrations at the DNA, RNA, protein and epigenetic levels. The resulting rich data provide a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages. The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA. Analysis of the molecular aberrations and their functional roles across tumor types will teach us how to extend therapies effective in one cancer type to others with a similar genomic profile. © 2013 Nature America, Inc. All rights reserved.
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| 2. |
- van Schie, Guido, et al.
(author)
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Mass detection in reconstructed digital breast tomosynthesis volumes with a computer-aided detection system trained on 2D mammograms
- 2013
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In: Medical physics (Lancaster). - : Wiley. - 0094-2405. ; 40:4, s. 041902-
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Journal article (peer-reviewed)abstract
- Purpose: To develop a computer-aided detection (CAD) system for masses in digital breast tomosynthesis (DBT) which can make use of an existing CAD system for detection of breast masses in full-field digital mammography (FFDM). This approach has the advantage that large digital screening databases that are becoming available can be used for training. DBT is currently not used for screening which makes it hard to obtain sufficient data for training. Methods: The proposed CAD system is applied to reconstructed DBT volumes and consists of two stages. In the first stage, an existing 2D CAD system is applied to slabs composed of multiple DBT slices, after processing the slabs to a representation similar to that of the FFDM training data. In the second stage, the authors group detections obtained in the slabs that detect the same object and determine the 3D location of the grouped findings using one of three different approaches, including one that uses a set of features extracted from the DBT slabs. Experiments were conducted to determine performance of the CAD system, the optimal slab thickness for this approach and the best method to establish the 3D location. Experiments were performed using a database of 192 patients (752 DBT volumes). In 49 patients, one or more malignancies were present which were described as a mass, architectural distortion, or asymmetry. Free response receiver operating characteristic analysis and bootstrapping were used for statistical evaluation. Results: Best performance was obtained when slab thickness was in the range of 1-2 cm. Using the feature based 3D localization procedure developed in the study, accurate 3D localization could be obtained in most cases. Case sensitivities of 80% and 90% were achieved at 0.35 and 0.99 false positives per volume, respectively. Conclusions: This study indicates that there may be a large benefit in using 2D mammograms for the development of CAD for DBT and that there is no need to exclusively limit development to DBT data.
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| 3. |
- Wallis, Matthew G., et al.
(author)
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Two-View and Single-View Tomosynthesis versus Full-Field Digital Mammography : High-Resolution X-Ray Imaging Observer Study
- 2012
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In: Radiology. - : Radiological Society of North America (RSNA). - 0033-8419 .- 1527-1315. ; 262:3, s. 788-796
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Journal article (peer-reviewed)abstract
- Purpose: To compare the diagnostic accuracy of two-dimensional (2D) full-field digital mammography with that of two-view (mediolateral and craniocaudal) and single-view (mediolateral oblique) tomosynthesis in an observer study involving two institutions. Materials and Methods: Ethical committee approval was obtained. All participating women gave informed consent. Two hundred twenty women (mean age, 56.3; range, 40-80 years) with breast density of 2-4 according to American College of Radiology criteria were recruited between November 2008 and September 2009 and underwent standard treatment plus tomosynthesis with a prototype photon-counting machine. After exclusion criteria were met, this resulted in a final test set of 130 women. Ten accredited readers classified the 130 cases (40 cancers, 24 benign lesions, and 66 normal images) using 2D mammography and two-view tomosynthesis. Another 10 readers reviewed the same cases using 2D mammography but single-view tomosynthesis. The multireader, multicase receiver operating characteristic (ROC) method was applied. The significance of the observed difference in accuracy between 2D mammography and tomosynthesis was calculated. Results: For diagnostic accuracy, 2D mammography performed significantly worse than two-view tomosynthesis (average area under ROC curve [AUC] = 0.772 for 2D, AUC = 0.851 for tomosynthesis, P = .021). Significant differences were found for both masses and microcalcification (P = .037 and .049). The difference in AUC between the two modalities of 20.110 was significant (P = .03) only for the five readers with the least experience (<10 years of reading); with AUC of 20.047 for the five readers with 10 years or more experience (P = .25). No significant difference (P = .79) in reader performance was seen when 2D mammography (average AUC = 0.774) was compared with single-view tomosynthesis (average AUC = 0.775). Conclusion: Two-view tomosynthesis outperforms 2D mammography but only for readers with the least experience. The benefits were seen for both masses and microcalcification. No differences in classification accuracy was seen between and 2D mammography and single-view tomosynthesis.
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| 4. |
- Zanca, Federica, et al.
(author)
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Diagnostic accuracy of digital mammography versus tomosynthesis : effect of radiologists' experience
- 2012
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In: Medical Imaging 2012. - International Society for Optics and Photonics : SPIE. - 9780819489678 ; , s. 83180-83180
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Conference paper (peer-reviewed)abstract
- Purpose: To investigate whether readers' experience affects performance in a study comparing 2D digital mammography (2D) with 2-view (CC and MLO) or 1-view (MLO) tomosynthesis. Materials and Methods: One-hundred-thirty 2D cases were collected from screening assessment and referral clinics; 64 of the cases had verified abnormalities and the remaining were confirmed normal. Two-view tomosynthesis images were obtained from the same patients. Ten accredited readers (5 with ≥ 10 years experience in mammography and 5 with < 10 years) classified the cases in terms of malignancy (rate 0-5), and recall (yes/no), for both modalities. A second experiment was performed with the same cases, with 10 other readers (again 5 experienced / 5 less experienced), but using 2D and 1-view tomosynthesis as the two modalities. The multi-reader-multi-case ROC method was applied and the significance of diagnostic accuracy difference of 2D vs tomosynthesis was calculated, as a function of experience and for each experiment. Recall rate (RR) on malignant and benign cases was also calculated, along with reading time. Results: No significant difference was reached between 2D and 2-view tomosynthesis for experienced readers (pvalue= 0.25); for less experienced readers the p-value was significant (0.03). No significant difference was found between 2D and 1-view tomosynthesis, independent of readers' experience. RR for benign cases decreased for tomosynthesis (for booth 1- and 2-view), independent of experience. Average reading time per case was 79 s (range 65- 91 s) and 134 s (range 119-158 s) for experienced readers; 56 s (range 46-67 s) and 115s (range 97-142 s) for nonexperienced, for 2D and 2-view tomosynthesis respectively. Reading time was 74 s (range 43-98 s) and 99 s (range 73- 117 s) for experienced readers; 74 s (range 62-85 s) and 94 s (range 82-137 s) for non-experienced, for 2D and 1-view tomosynthesis respectively. Conclusions: For experienced readers, there is no evidence of improved diagnostic accuracy when using 2-view or 1- view tomosynthesis, while less experienced readers perform better with 2-view tomosynthesis than 2D images. Tomosynthesis reduces the number of recall of benign cases, without hindering cancer detection.
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