Summary

The RIDER Lung CT collection was constructed as part of a study to evaluate the variability of tumor unidimensional, bidimensional, and volumetric measurements on same-day repeat computed tomographic (CT) scans in patients with non–small cell lung cancer.

Thirty-two patients with non–small cell lung cancer, each of whom underwent two CT scans of the chest within 15 minutes by using the same imaging protocol, were included in this study. Three radiologists independently measured the two greatest diameters of each lesion on both scans and, during another session, measured the same tumors on the first scan. In a separate analysis, computer software was applied to assist in the calculation of the two greatest diameters and the volume of each lesion on both scans. Concordance correlation coefficients (CCCs) and Bland-Altman plots were used to assess the agreements between the measurements of the two repeat scans (reproducibility) and between the two repeat readings of the same scan (repeatability).

The reproducibility and repeatability of the three radiologists' measurements were high (all CCCs, ≥0.96). The reproducibility of the computer-aided measurements was even higher (all CCCs, 1.00). The 95% limits of agreements for the computer-aided unidimensional, bidimensional, and volumetric measurements on two repeat scans were (−7.3%, 6.2%), (−17.6%, 19.8%), and (−12.1%, 13.4%), respectively. Chest CT scans are well reproducible. Changes in unidimensional lesion size of 8% or greater exceed the measurement variability of the computer method and can be considered significant when estimating the outcome of therapy in a patient.


About the RIDER project

The Reference Image Database to Evaluate Therapy Response (RIDER) is a targeted data collection used to generate an initial consensus on how to harmonize data collection and analysis for quantitative imaging methods applied to measure the response to drug or radiation therapy.  The National Cancer Institute (NCI) has exercised a series of contracts with specific academic sites for collection of repeat "coffee break," longitudinal phantom, and patient data for a range of imaging modalities (currently computed tomography [CT] positron emission tomography [PET] CT, dynamic contrast-enhanced magnetic resonance imaging [DCE MRI], diffusion-weighted [DW] MRI) and organ sites (currently lung, breast, and neuro). The methods for data collection, analysis, and results are described in the new Combined RIDER White Paper Report (Sept 2008):

The long term goal is to provide a resource to permit harmonized methods for data collection and analysis across different commercial imaging platforms to support multi-site clinical trials, using imaging as a biomarker for therapy response. Thus, the database should permit an objective comparison of methods for data collection and analysis as a national and international resource as described in the first RIDER white paper report (2006):




Data Access

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Data TypeDownload all or Query/Filter
Images (DICOM, 7.55GB)

 

DICOM Metadata Digest (CSV)
Lesion Notes (XLS)


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Third Party Analyses of this Dataset

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Detailed Description


Collection Statistics


Modalities

CT

Number of Participants

32

Number of Studies

46

Number of Series

63

Number of Images

15,419

Image Size (GB)7.55






Citations & Data Usage Policy 

Zhao, Binsheng, Schwartz, Lawrence H, & Kris, Mark G. (2015). Data From RIDER_Lung CT. The Cancer Imaging Archive. DOI: 10.7937/K9/TCIA.2015.U1X8A5NR




Zhao, B., James, L. P., Moskowitz, C. S., Guo, P., Ginsberg, M. S., Lefkowitz, R. A.,Qin, Y. Riely, G.J., Kris, M.G., Schwartz, L. H. (2009, July). Evaluating Variability in Tumor Measurements from Same-day Repeat CT Scans of Patients with Non–Small Cell Lung Cancer 1 . Radiology. Radiological Society of North America (RSNA). DOI: 10.1148/radiol.2522081593 (paper)




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.  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.

  1. Radiomics of Lung Nodules: A Multi-Institutional Study of Robustness and Agreement of Quantitative Imaging Features.  DOI:10.18383/j.tom.2016.00235
  2. Textural Analysis of Tumour Imaging: A Radiomics Approach. https://lib.ugent.be/catalog/rug01:002367219




Version 2 (Current): Updated 2014/11/14


Data TypeDownload all or Query/Filter
Images (DICOM, 7.55GB)

 

DICOM Metadata Digest (CSV)


It was brought to our attention that the  RIDER-8509201188 patient contained 2 identical image series rather than the correct secondary/repeat series. The duplicate series has been removed (UID: 1.3.6.1.4.1.9328.50.1.64033480205396366773922006817138551096), but we are unable to obtain the correct series at this point.

Version 1: Updated 2012/10/18

Initial upload of data set.