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Abstract #4765

Retrospective ADC correction of gradient nonlinearity errors in multi-center breast DWI trials: ACRIN6698 multi-platform feasibility study

Dariya Malyarenko1, David C Newitt2, Lisa J Wilmes2, Ek Tsoon Tan3, Luca Marinelli4, Ajit Devaraj5, Johannes M Peeters6, Shivraman Giri7, Axel vom Endt8, Nola Hylton2, Savannah Partridge9, and Thomas L Chenevert1
1Radiology, University of Michigan, Ann Arbor, MI, United States, 2Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States, 3Hospital for Special Surgery, New York, NY, United States, 4GE Global Research, Niskayuna, NY, United States, 5Philips Research North America, Cambridge, MA, United States, 6Philips MR Clinical Science, Best, Netherlands, 7Siemens Medical Solutions, Boston, MA, United States, 8Siemens Healthcare GmbH, Erlangen, Germany, 9Radiology, University of Washington, Seattle, WA, United States

Multi-site, multi-platform clinical oncology trials seek to enhance quantitative utility of the apparent diffusion coefficient (ADC) metric by reducing technical cross-platform variability due to systematic gradient nonlinearity (GNL). Here we test feasibility of retrospective GNL correction implementation for a representative subset of subjects and systems from the ACRIN6698 breast cancer therapy response trial. GNL ADC correction based on previously developed formalism is demonstrated for trace-DWI DICOM using system-specific gradient-channel fields derived from vendor-provided spherical harmonic tables. Implemented correction substantially improves precision and removes ADC bias for DWI QC phantoms, and markedly changes ADC histogram percentiles for solid breast tumors.

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