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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.

By |October 13th, 2017|Highlights-post, Highlights-QA|Comments Off on Q&A with Michael Dieckmeyer and Dimitrios Karampinos

October Highlights

October Cover Art

7 Tesla 22-channel wrap-around coil array for cervical spinal cord and brainstem imaging, by Bei Zhang, Alan C. Seifert, Joo-won Kim, Joseph Borrello and Junqian Xu

October Editor’s Picks

ADC Quantification of the Vertebral Bone Marrow Water Component: Removing the Confounding Effect of Residual Fat, by Michael Dieckmeyer, Stefan Ruschke, Holger Eggers, Hendrik Kooijman, Ernst J. Rummeny, Jan S. Kirschke, Thomas Baum and Dimitrios C. Karampinos


Gradient and shim pre-emphasis by inversion of a linear time-invariant system model, by S. Johanna Vannesjo, Yolanda Duerst, Laetitia Vionnet, Benjamin E. Dietrich, Matteo Pavan, Simon Gross, Christoph Barmet and Klaas P. Pruessmann

Audioslides: coming soon!

By |October 6th, 2017|Highlights-post|Comments Off on October Highlights

QA with Stephen Cauley and Lawrence Wald

By Nikola Stikov

Stephen Cauley

 The Martinos center in Boston recently brought us wave-CAIPI, an accelerated 3D imaging technique that uses helixes in k-space to encode information and speed up MRI acquisition. However, differences in the calibration of the gradient systems made it difficult to generalize the wave-CAIPI technique and deploy it on any clinical scanner. This is where the Editor’s Pick for September comes in; Stephen Cauley and his colleagues proposed a joint optimization approach to estimate k-space trajectory discrepancies simulataneously with the underlying image. We asked Steve and senior author Larry Wald to tell us the story of autocallibrated wave-CAIPI.

By |September 29th, 2017|Highlights-post, Highlights-QA|Comments Off on QA with Stephen Cauley and Lawrence Wald

QA with Dmitry Kurzhunov and Michael Bock

By Nikola Stikov, Atef Badji

Dmitry Kurzhunov in Toronto for ISMRM in 2015

This September brings us an Editor’s pick from Freiburg, where Dmitry Kurzhunov and his colleagues used Oxygen-17 (17O) to quantify the cerebral metabolic rate of oxygen consumption (CMRO2) on a 3T clinical MRI system. While positron emission tomography (PET) remains the gold standard for measuring CMRO2, Dmitry and senior author Michael Bock give us several reasons why 17O might be the way to go.

By |September 15th, 2017|Highlights-post, Highlights-QA|Comments Off on QA with Dmitry Kurzhunov and Michael Bock

September Highlights

September Cover Art

In memoriam: Sir Peter Mansfield (1933–2017), by Richard W. Bowtell

September Editor’s Picks

Autocalibrated wave-CAIPI reconstruction; Joint optimization of k-space trajectory and parallel imaging reconstruction, by Stephen F. Cauley, Kawin Setsompop, Berkin Bilgic, Himanshu Bhat, Borjan Gagoski and Lawrence L. Wald


Quantification of oxygen metabolic rates in Human brain with dynamic 17O MRI: Profile likelihood analysis, by Dmitry Kurzhunov,  Robert Borowiak, Helge Hass, Philipp Wagner, Axel Joachim Krafft, Jens Timmer and Michael Bock

Audioslides: coming soon!


By |September 1st, 2017|Highlights-post|Comments Off on September Highlights

Q&A with Bernhard Strasser and Wolfgang Bogner

 By Blake Dewey

Bernhard Strasser

  This week we gathered across multiple continents (as I feel we always do!) to discuss the ins and outs of spectroscopic imaging with Bernhard Strasser and Wolfgang Bogner, two authors of “(2 + 1)D-CAIPIRINHA accelerated MR spectroscopic imaging of the brain at 7T”, one of the MRM Editor’s Picks for August 2017. In this paper, Bernhard and his colleagues propose a new method of acceleration for magnetic resonance spectroscopic imaging (MRSI) that combines 2D CAIPIRINHA with simultaneous multi-slice (SMS) to accelerate imaging in all three spatial dimensions.

By |August 25th, 2017|Highlights-post, Highlights-QA|Comments Off on Q&A with Bernhard Strasser and Wolfgang Bogner

Q&A with Xiao-Yong Zhang and Zhongliang Zu

By Mathieu Boudreau

Xiao-Yong Zhang

The August 2017 Editor’s Pick is from Xiao-Yong Zhang and Zhongliang Zu, researchers at Vanderbilt University in Nashville. Their paper presents a newly discovered Nuclear Overhauser Effect (NOE) signal at -1.6 ppm from water. They measured this signal in normal rat brains at 9.4 T, and found that it changed significantly in a rodent tumor model. Using reconstituted phospholipids and cultured cell experiments, they hypothesize that this signal may originate from membrane choline phospholipids. We recently spoke with Xiao-Yong and Zhongliang Zu about their work. 

By |August 18th, 2017|Highlights-post, Highlights-QA|Comments Off on Q&A with Xiao-Yong Zhang and Zhongliang Zu

August Highlights

August Cover Art

A dedicated neonatal brain imaging system, by Emer J. Hughes, Tobias Winchman, Francesco Padormo, Rui Teixeira, Julia Wurie, Maryanne Sharma, Matthew Fox, Jana Hutter, Lucilio Cordero-Grande, Anthony N. Price, Joanna Allsop, Jose Bueno-Conde, Nora Tusor, Tomoki Arichi, A. D. Edwards, Mary A. Rutherford, Serena J. Counsell and Joseph V. Hajnal

August Editor’s Picks

(2 + 1)D-CAIPIRINHA accelerated MR spectroscopic imaging of the brain at 7T, by B. Strasser, M. Považan, G. Hangel, L. Hingerl, M. Chmelik, S. Gruber, S. Trattnig and W. Bogner

audioslides : coming soon !

MR imaging of a novel NOE-mediated magnetization transfer with water in rat brain at 9.4 T, by Xiao-Yong Zhang, Feng Wang, Tao Jin, Junzhong Xu, Jingping Xie, Daniel F. Gochberg, John C. Gore and Zhongliang Zu


By |August 11th, 2017|Highlights-post|Comments Off on August Highlights

Q&A with Patrick Schuenke and Moritz Zaiss

                                                               By Brian Chung

Patrick Schuenke

This week we ventured across continents to speak with Drs. Patrick Schünke and Moritz Zaiss, two primary authors of a recent paper from the German Cancer Research Center (DKFZ) in Heidelberg, Germany titled: “Adiabatically Prepared Spin-Lock Approach for T1ρ-Based Dynamic Glucose Enhanced MRI at Ultrahigh Fields.” In this paper, the authors developed an NMR method for imaging glucose using an ultrahigh field MR scanner and a spin-lock approach to gain sensitivity to chemical exchange. At ultrahigh field strengths, distinct artifacts appear predominantly resulting from RF field inhomogeneities. Thus, adiabatic pulses were implemented to enable the application of spin-lock MRI at fields such as 7T. This adiabatic spin-lock approach is explained, its feasibility for application in vivo at 7T is verified, the technique’s sensitivity to glucose is investigated, and a first proof of concept of spin-lock based glucose imaging for the detection of cancer in humans is presented.

By |July 28th, 2017|Highlights-post, Highlights-QA|Comments Off on Q&A with Patrick Schuenke and Moritz Zaiss

Q&A with Zhe Liu and Pascal Spincemaille

Zhe Liu

By Pinar Ozbay

It is our pleasure to present one of the Editor’s picks for July, Preconditioned Total Field Inversion (TFI) Method for Quantitative Susceptibility Mapping (QSM), from Cornell University. In this work Zhe Liu, Pascal Spincemaille and colleagues proposed an algorithm which allows mapping of tissue magnetic susceptibility in regions with large dynamic susceptibility ranges, such as cavities, bones, and hemorrhages in the head. There are two main steps in QSM algorithm which are removal of background fields to calculate the local field, and solving the local field-to-susceptibility problem. The latter is an ill-posed problem by nature, hence is mainly referred to as the step of inverse problem in the literature of QSM. Their method calculates susceptibility maps via ‘total field inversion’, which generalizes those two steps as one optimization problem, and further employs preconditioning to achieve fast convergence.

By |July 14th, 2017|Highlights-post, Highlights-QA|Comments Off on Q&A with Zhe Liu and Pascal Spincemaille