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Summary

Excerpt

PURPOSE: To determine the variability of lesion size measurements in computed tomography data sets of patients imaged under a “no change” (“coffee break”) condition and to determine the impact of two reading paradigms on measurement variability.

METHOD AND MATERIALS: Using data sets from 32 RIDER Lung CT patients patients and 8 RIDER Pilot patients scanned twice within 15 minutes (“no change”), measurements were performed by five radiologists in two phases: (1) independent reading of each computed tomography dataset (timepoint): (2) a locked, sequential reading of datasets. Readers performed measurements using several sizing methods, including one-dimensional (1D) longest in-slice dimension and 3D semi-automated segmented volume. Change in size was estimated by comparing measurements performed on both timepoints for the same lesion, for each reader and each measurement method. For each reading paradigm, results were pooled across lesions, across readers, and across both readers and lesions, for each measurement method.

RESULTS: The mean percent difference (± SD) when pooled across both readers and lesions for 1D and 3D measurements extracted from contours was 2.8 ± 22.2% and 23.4 ± 105.0%, respectively, for the independent reads. For the locked, sequential reads, the mean percent differences (± SD) reduced to 2.52 ± 14.2% and 7.4 ± 44.2% for the 1D and 3D measurements, respectively.

CONCLUSION: Even under a “no change” condition between scans, there is variation in lesion size measurements due to repeat scans and variations in reader, lesion, and measurement method. This variation is reduced when using a locked, sequential reading paradigm compared to an independent reading paradigm.For additional information please see https://qibawiki.rsna.org/index.php/VolCT_-_Group_1B and the Release Notes from which the following may be specially useful: "Results are described in DICOM SR files, which in turn reference DICOM segmentation files that encode the region as a 3D raster, and presentation states that record the zoom, pan and window levels at the time of measurement" and "Readers are identified by number (from 1 through 5) ... and their actual identity recorded in the SR tree in observer context and worklist descriptions has been removed."

Acknowledgements

  • CoreLab Partners, Inc conducted the reader study component of this investigation. They provided the reading facility, review workstations, software, and logistical support. CoreLab Partners radiologists also participated as readers. Therefore, we acknowledge CoreLab Partners for their support and specifically acknowledge CoreLab Partners radiologists Kevin Byrne, Steven Kaplan, Julie Barudin, Joyce Sherman, Kathy Slazak, George Edeburn, and J. Michael O'Neal for participating as readers in this study.
  • We acknowledge financial support from the RSNA Quantitative Imaging Biomarker Alliance (QIBA) provided by National Institute of Biomedical Imaging and Bioengineering American Recovery and Reinvestment Act of 2009 funds.


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Additional 8 Participants' DICOM not in RIDER Lung CT but rather in RIDER Pilot data (DICOM, XX.X GB)
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activetrue
titleData Access

Data Access

Data TypeDownload all or Query/FilterLicense

Segmentations and Reports (DICOM,

XX.X GB

348 MB)


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urlhttps://wiki.cancerimagingarchive.net/download/attachments/70228818/NBIA-manifest-QIBA%20VolCT%20Group%201B%20Round%202.tcia?api=v2



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urlhttps://public.cancerimagingarchive.net/nbia-search/?MinNumberOfStudiesCriteria=1&CollectionCriteria=RIDER Lung CT&&CollectionCriteria=RIDER Pilot&ThirdPartyCriteria=YES


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Additional Resources for this Dataset

The following external resources have been made available by the data submitters.  These are not hosted or supported by TCIA, but may be useful to researchers utilizing this collection.

  • Spreadsheet of locations or reader results
linked from the 1B page?)Click the Versions tab for more info about data releases.

Collections Used in this Analysis

Below is a list of the Collections used in these analyses:

  • RIDER Lung CT
  • RIDER Pilot - see this link for further detail:

    Source Data TypeDownload or Query/FilterLicense

    Original corresponding images from RIDER Pilot (DICOM, 10.4 GB)


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    urlhttps://wiki.
    nci.nih.gov/display/CIP/RIDER used as with-change distractorsPlease contact help@cancerimagingarchive.net  with any questions regarding usage.
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    Original corresponding images from RIDER Lung CT (DICOM,7.55 GB)


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    For additional information please see https://qibawiki.rsna.org/index.php/VolCT_-_Group_1B

    Localtab
    titleDetailed Description

    Detailed Description

    Image Statistics

    Radiology Image Statistics

    Modalities

    SR, SEG, PR

    Number of Patients

    32 or
    40

    Number of Studies

    323

    Number of Series

    1,508

    ?

    Number of Images

    1508

    Images Size (GB)
    ~350 MB
    0.348

    Please contact TCIA's Helpdesk with any questions regarding usage.and the Release Notes from which the following may be specially useful: "Results are described in DICOM SR files, which in turn reference DICOM segmentation files that encode the region as a 3D raster, and presentation states that record the zoom, pan and window levels at the time of measurement" and "Readers are identified by number (from 1 through 5) ... and their actual identity recorded in the SR tree in observer context and worklist descriptions has been removed."


    Localtab
    titleCitations & Data Usage Policy

    Citations & Data Usage Policy

    tcia-limited-license-4-internationalpolicy

    Info
    titleData Citation

    DOI goes here. Create using Datacite with information from Collection Approval form

    McNitt-Gray, M., Kim, H., Zhao, B., Schwartz, L. H., Clunie, D., Cohen, K., PETRICK, N., Fenimore, C., Lu, Z. Q. J., & Buckler, A. (2020). QIBA VolCT Group 1B Round 2 No Change Size Measurements (QIBA-VolCT-1B) [Data set]. The Cancer Imaging Archive. DOI: https://doi.org/10.7937/tcia.2020.1c3h-vp70  is in draft mode , that is, coming soon.


    Info
    titlePublication Citation

    McNitt-Gray M. F., Hyun Kim G., Zhao B., Schwartz L.H., Clunie D., Cohen K., Petrick N., Fenimore C., Lu Z.Q.J., Buckler A.J. (2015) Determining the Variability of Lesion Size Measurements from CT Patient Data Sets Acquired under “No Change” Conditions. Translational Oncology 8(1):55-64. https://doi.org/10.1016/j.tranon.2015.01.001


    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. (2013).  The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository, . In Journal of Digital Imaging , Volume (Vol. 26, Number Issue 6, December, 2013, pp 1045-1057. DOI: pp. 1045–1057). Springer Science and Business Media LLC. https://doi.org/10.1007/s10278-013-9622-7 PMCID: PMC3824915

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    Localtab
    titleVersions

    Version 1 (Current): Updated

    2020

    2023/

    mm

    05/

    dd

    24


    Data TypeDownload all or Query/Filter
    Images
    License

    Segmentations and Reports (DICOM,

    xx.x GB

    348 MB)


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    labelSearch
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    urlhttps://public.cancerimagingarchive.net/nbia-search/?MinNumberOfStudiesCriteria=1&CollectionCriteria=RIDER Lung CT&&CollectionCriteria=RIDER Pilot&ThirdPartyCriteria=YES


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