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Summary

the outcome of therapy in a patient.
Excerpt

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

Ideally a patient’s response to neoadjuvant chemotherapy could be observed noninvasively, in the first 2-3 weeks of treatment using an imaging to provide feedback related to the effectiveness of the chosen chemotherapy regimen. This capability would permit individuation of patient care by supporting the opportunity to tailor chemotherapy to a each patient’s response. Functional diffusion mapping (fDM), now called Parametric Response Mapping (PRM) has been proposed as an MRI imaging biomarker for quantifying early brain tumor response to therapy [1-3]. This approach quantifies local apparent diffusion coefficient (ADC) changes in tumors using a voxel-based analysis implemented by rigid registration of the patient’s head between interval exams. The RIDER Breast MRI data set extended this approach by demonstrating ADC changes in 3 of 5 primary breast cancer patients measured in response to onset of neoadjuvant chemotherapy from interval exams separated by only 8-11 days.

This ISMRM 2009 poster demonstrates how each of the "coffee break" exams were used as an estimate of each patient's null hypothesis, i.e. distribution associated with no change, and thus supports the estimate of the nulls 97.5 percentile for subsequent estimation of early response to neoadjuvant chemotherapy on an individual patient basis.

 

ISMRM 2009 poster demonstrates how each of the "coffee break" exams were used as an estimate of each patient's null hypothesis, i.e. distribution associated with no change, and thus supports the estimate of the nulls 97.5 percentile for subsequent estimation of early response to neoadjuvant chemotherapy on an individual patient basis. 

Localtab Group
Localtab
activetrue
titleData Access

Data Access

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Localtab
titleDetailed Description

Detailed Description

Collection Statistics

Updated 11/08/2011

Modalities

MR

Number of Patients

5

Number of Studies

10

Number of Series

40

Number of Images

1,500

Image Size (GBMB)401.61

 

A detailed description of the data set is contained in this ISMRM 2009 poster.

 

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
titleRIDER Breast MRI Citation

The Cancer Imaging Archive Team. Data From RIDER Breast MRI. DOI coming soon.

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)

 

Other Publications Using This Data

TCIA maintains a list of publications which leverage our data. At this time we are not aware of any additional publications based on this data. If you have a publication you'd like to add please contact the TCIA Helpdesk.

Localtab
titleVersions

Version 1 (Current): Updated 2011/11/08

Data TypeDownload all or Query/Filter
Images (DICOM, 401MB) Image Removed
ISMRM Poster (PDF)Image Modified