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ADC

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Q&A with Michael Dieckmeyer and Dimitrios Karampinos

By Jessica McKay

Michael Dieckmeyer

This month we talked to Michael Dieckmeyer and Dimitrios (Dimitris) Karampinos about their work to measure apparent diffusion coefficient (ADC) values in bone marrow. Michael has a very diverse education that includes a master’s degree in mathematics, and he is currently completing his final year of medical school. His mentor Dimitris leads a multidisciplinary research team in Munich that focuses on the development of quantitative MRI, targeting musculoskeletal diseases and metabolic diseases like obesity and diabetes. In this paper, they use modeling to overcome some of the challenges of ADC quantification in the presence of fat. By including the proton density fat fraction (PDFF) and the T2 of water, they can reduce the bias in the ADC measurements that is introduced by residual fat.

13 October 2017, 09:50 PDT|Categories: Highlights-post, Highlights-QA|Tags: , , , , , |

Q&A with Dariya Malyarenko and Tom Chenevert

The March Editor’s Pick features Dr. Dariya Malyarenko and Dr. Tom Chenevert, from the University of Michigan. With a background in solid-state NMR and signal processing for biomarker discovery from cancer proteomics data, Dariya started in MRI as an NIH T32 trainee four years ago. Tom began his work in MRI 25 years ago at the University of Michigan. In their paper they perform a multicenter study to thoroughly characterize the sources of technical bias in quantitative diffusion weighted imaging (DWI), and identify gradient non-linearity as a major contributor.

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