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Additional Resources for this Dataset<\/strong><\/p>\n The following external resources have been made available by the data submitters.\u00a0 These are not hosted or supported by TCIA, but may be useful to the researchers utilizing this collection:<\/p>\n Expensive and lengthy clinical trials delay regulatory evaluation of innovative medical technologies affecting patient access to high-quality medical products. Sophisticated simulation tools are increasingly being used in device development, but are rarely used in regulatory applications. We investigate a new paradigm for evaluating digital breast tomosynthesis (DBT) as a replacement for digital mammography (DM), using exclusively in-silico methods.<\/p> A total of 2986 subjects, with breast sizes and radiographic densities representative of a screening population and compressed thicknesses from 3.5 to 6 cm, were simulated and imaged on in-silico versions of DM and DBT systems using fast Monte Carlo x-ray transport. Images were interpreted by a computational reader detecting the presence of lesions. The in-silico trial (VICTRE) was designed to replicate a comparative trial from a previous regulatory submission. The endpoint was the difference in area under the receiver-operating-characteristic curve between modalities (delta-AUC) for lesion detection. Using a fully-crossed design, VICTRE was sized for a standard error (SE) of 0.01 in delta-AUC, half the uncertainty seen in the comparative trial.\u00a0A 1-hour summary presentation of the project and findings was given at the FDA Grand Rounds on 3\/14\/2019 and can be found\u00a0<\/span>here<\/a>.<\/span><\/p> A systematic exploration of the trial parameters including lesion types and sizes is also possible and greatly facilitated by the availability of open-source, free software tools available at\u00a0https:\/\/github.com\/DIDSR\/VICTRE<\/a>.Summary<\/span><\/h1>