Multisite concordance of apparent diffusion coefficient measurements across the NCI quantitative imaging network
Journal of Medical Imaging, ISSN: 2329-4310, Vol: 5, Issue: 1, Page: 011003
2018
- 28Citations
- 4Usage
- 46Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations28
- Citation Indexes26
- 26
- CrossRef9
- Policy Citations2
- 2
- Usage4
- Abstract Views4
- Captures46
- Readers46
- 46
Article Description
Diffusion weighted MRI has become ubiquitous in many areas of medicine, including cancer diagnosis and treatment response monitoring. Reproducibility of diffusion metrics is essential for their acceptance as quantitative biomarkers in these areas. We examined the variability in the apparent diffusion coefficient (ADC) obtained from both postprocessing software implementations utilized by the NCI Quantitative Imaging Network and online scan time-generated ADC maps. Phantom and in vivo breast studies were evaluated for two (ADC) and four (ADC) b-value diffusion metrics. Concordance of the majority of implementations was excellent for both phantom ADC measures and in vivo ADC, with relative biases <0.1% (ADC) and <0.5% (phantom ADC) but with higher deviations in ADC at the lowest phantom ADC values. In vivo ADC concordance was good, with typical biases of ±2% to 3% but higher for online maps. Multiple b-value ADC implementations were separated into two groups determined by the fitting algorithm. Intergroup mean ADC differences ranged from negligible for phantom data to 2.8% for ADC in vivo data. Some higher deviations were found for individual implementations and online parametric maps. Despite generally good concordance, implementation biases in ADC measures are sometimes significant and may be large enough to be of concern in multisite studies.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85032566078&origin=inward; http://dx.doi.org/10.1117/1.jmi.5.1.011003; http://www.ncbi.nlm.nih.gov/pubmed/29021993; https://www.spiedigitallibrary.org/journals/journal-of-medical-imaging/volume-5/issue-01/011003/Multisite-concordance-of-apparent-diffusion-coefficient-measurements-across-the-NCI/10.1117/1.JMI.5.1.011003.full; https://scholar.barrowneuro.org/neurobiology/352; https://scholar.barrowneuro.org/cgi/viewcontent.cgi?article=1351&context=neurobiology; https://dx.doi.org/10.1117/1.jmi.5.1.011003; https://www.spiedigitallibrary.org/access-suspended
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