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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