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Summary

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.

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.

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.

Excerpt

Researchers studying radiomics will be able to evaluate features for robustness across a variety of scanners. Features can be calculated using the researchers own software or third party software such as IBEX (imaging biomarker explorer).

Related publications: http://journals.lww.com/investigativeradiology/Abstract/2015/11000/Measuring_Computed_Tomography_Scanner_Variability.3.aspx                 

The following paper was generated on different imaging modalities but the same phantom, this is a related but independent paper with a different set of authors:  http://tinyurl.com/zm7tr7p

This data set was provided to TCIA by Authors: Mackin, Dennis; Fave, Xenia; Zhang, Lifei; Fried, David; Yang, Jinzhong; Taylor, Brian; Rodriguez-Rivera, Edgardo; Dodge, Cristina; Jones, Aaron Kyle; and Court, Laurence.  

 

 A 1-hour summary presentation of the project and findings was given at the FDA Grand Rounds on 3/14/2019 and can be found here.

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 https://github.com/DIDSR/VICTRE.


Localtab Group



Localtab
activetrue
titleData Access

Data Access

Choosing the Download option will provide you with a file to launch the TCIA Download Manager to download the entire collection. If you want to browse or filter the data to select only specific scans/studies please use the Search By Collection optionClick the  Download button to save a ".tcia" manifest file to your computer, which you must open with the NBIA Data Retriever. Click the Search button to open our Data Portal, where you can browse the data collection and/or download a subset of its contents.


Data TypeDownload all or Query/Filter
Images (DICOM, 1.
33 GB
03 TB)
Software (Github)


Click the Versions tab for more info about data releases.




Localtab
titleDetailed Description

Detailed Description


Collection Statistics

Updated

2017/05/01

Modalities

CT, RTSRUCT
MG

Number of

Patients

Participants

17

2994

Number of Studies

17

8749

Number of Series

51

8749

Number of Images

2672

217913

Image Size (
GB
TB)1.
33

Supporting Documentation and Metadata

Acquisition parameters for the phantom scans in this Collection:

Scan

Manufacturer

Model

Kernel

Type

Slice Thickness (mm)

Pixel (mm)

Spiral Pitch Factor

kVp

Effective mAs

CTDIvol (mGy)

CCR1-GE1

GE

Discovery CT750 HD

standard

helical

2.5

0.49

0.98

120

81

6.19

CCR1-GE2

GE

Discovery CT750 HD

standard

axial

2.5

0.70

1.00

120

300

 

CCR1-GE3

GE

Discovery CT750 HD

standard

helical

2.5

0.78

0.98

120

122

9.3

CCR1-GE4

GE

Discovery ST

standard

helical

2.5

0.98

1.35

120

143

16.3

CCR1-GE5

GE

LightSpeed RT

standard

helical

2.5

0.98

0.75

120

1102

53.6

CCR1-GE6

GE

LightSpeed RT16

standard

helical

2.5

0.98

0.94

120

367

18.8

CCR1-GE7

GE

LightSpeed VCT

standard

helical

2.5

0.74

0.98

120

82

 

CCR1-P1

Philips

Brilliance Big Bore

B

helical

3.0

0.98

0.94

120

320

17.8

CCR1-P2

Philips

Brilliance Big Bore

C

helical

3.0

0.98

0.94

120

369

15.8

CCR1-P3

Philips

Brilliance Big Bore

B

helical

3.0

1.04

0.81

120

320

19.9

CCR1-P4

Philips

Brilliance Big Bore

B

helical

3.0

1.04

0.81

120

369

19.9

CCR1-P5

Philips

Brilliance 64

B

helical

3.0

0.98

0.67

120

372

16.4

CCR1-S1

Siemens

Sensation Open

B31s

axial

3.0

0.54

1.00

120

26 - 70

1.5

CCR1-S2

Siemens

SOMATOM Definition Flash

['I70f', '2']

helical

2.0

0.52

0.60

120

17 - 28

 

CCR1-T1

Toshiba

Aquilion

FC18

helical

3.0

0.63

1.11

120

135

4.0

CCR1-T2

Toshiba

Aquilion

FC18

helical

3.0

0.63

1.11

120

135

3.8

CCR1-T3

Toshiba

Aquilion ONE

FC18

helical

3.0

0.98

0.99

120

151

13.5

03






Mackin, Dennis; Fave, Xenia; Zhang, Lifei; Fried, David; Yang, Jinzhong; Taylor, Brian; Rodriguez-Rivera, Edgardo; Dodge, Cristina; Jones, Aaron Kyle; and Court, Laurence. (2017). Data From Credence Cartridge Radiomics Phantom CT Scans. The Cancer Imaging Archive. http://doi.org/10.7937/K9/TCIA.2017.zuzrml5b

Localtab
titleCitations & Data Usage Policy

Citations & Data Usage Policy 

This collection is freely available to browse, download, and use for commercial, scientific and educational purposes as outlined in the Creative Commons Attribution 3.0 Unported License.  See TCIA's Data Usage Policies and Restrictions for additional details. Questions may be directed to help@cancerimagingarchive.net.

Please be sure to include the following citations in your work if you use this data set:

Info
titleData Citation
Public collection license

Info
titleDataset Citation

Badano A, Graff CG, Badal A, Sharma D, Zeng R, Samuelson FW, Glick S, Myers KJ. The VICTRE Trial: Open-Source, In-Silico Clinical Trial for Evaluating Digital Breast Tomosynthesis. 2018. DOI:  10.7937/TCIA.2019.ho23nxaw .




Info
titlePublication Citation

Badano A, Graff CG, Badal A, Sharma D , Zeng R, Samuelson FW, Glick SJ, Myers KJ. Evaluation of Digital Breast Tomosynthesis as Replacement of Full-Field Digital Mammography Using an In Silico Imaging Trial. JAMA Netw Open. 2018;1(7):e185474. DOI: 10.1001/jamanetworkopen.2018.5474.




Info
titleTCIA Citation

Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M, Tarbox L, Prior F. The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, Journal of Digital Imaging, Volume 26, Number 6, December, 2013, pp 1045-1057. (paper)

 

DOI: 10.1007/s10278-013-9622-7.



Other Publications Using This Data

TCIA maintains a list of publications which leverage our data. If you have a  publication  you'd like to add please  contact the TCIA Helpdesk .




Localtab
titleVersions

Version 1 (Current): Updated

2017

03/

07

08/

28

2019


Data TypeDownload all or Query/Filter
Images (DICOM, 1.
33 GB
03 TB)