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December Highlights

December Cover Art

New method to characterize and correct with sub-µs precision gradient delays in bipolar multispoke RF pulses, by Vincent Gras, Alexandre Vignaud, Alexis Amadon, Franck Mauconduit, Denis Le Bihan and Nicolas Boulant

December Editor’s Picks

Oxidation of [U-13C]glucose in the human brain at 7T under steady state conditions, by Sergey Cheshkov, Ivan E. Dimitrov, Vikram Jakkamsetti, Levi Good, Dorothy Kelly, Karthik Rajasekaran, Ralph J. DeBerardinis, Juan M. Pascual, A. Dean Sherry and Craig R. Malloy

Audioslides

Simultaneous determination of metabolite concentrations, T1 and T2 relaxation times, by Li An, Shizhe Li and Jun Shen

Audioslides: coming soon!

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

Q&A with Hongjiang Wei and Chunlei Liu

By Zahra Hosseini & Phillip Ward

Hongjiang Wei

Recently, we had the pleasure to sit down and have a chat with Dr. Hongjiang Wei and Dr. Chunlei Liu about their editor-selected manuscript entitled “Investigating Magnetic Susceptibility of Human Knee Joint at 7 Tesla.” The conversation took a technical turn right away, when we asked the authors about their chosen technique, quantitative susceptibility mapping (or QSM). Hongjiang explained that, “quantitative susceptibility mapping is an approach to, as the name implies, extract a map of the underlying tissue susceptibility on a pixel-by-pixel basis. QSM computes the magnetic susceptibility from the phase signal of gradient recalled echoes with the assumption that phase shift is mainly due to susceptibility induced field inhomogeneity.” In simple terms, it is a map that demonstrates how tissues interact with the magnetic field of the MRI scanner.

By |November 24th, 2017|Highlights-post, Highlights-QA|Comments Off on Q&A with Hongjiang Wei and Chunlei Liu

Q&A with Kathleen M.Ropella and Douglas C.Noll

By Maria Eugenia Caligiuri

Kathleen M.Ropella

Kathleen Ropella received her Bachelor’s Degree in Biomedical Engineering at Marquette University, and her Master’s Degree at the University of Michigan, where she will defend her PhD thesis this semester (busy times ahead!).

Douglas C. Noll did his PhD in Electrical Engineering with Al Macovski at Stanford, after being introduced by his intramural basketball pals, Dwight Nishimura, Steve Conolly, and Craig Meyer. In 1991, he started his first faculty position at the University of Pittsburgh, working on functional MRI with the first 3T magnet GE ever made. Doug later transitioned to be a professor of biomedical engineering at the University of Michigan – so he’s been in the field of MRI for about 30 years now!

Their paper, “A Regularized, Model-Based Approach to Phase-Based Conductivity Mapping Using MRI,” was focused on two things: first, achieving accurate measurements of conductivity – which describes the ability of a tissue to conduct electric current – at tissue boundaries; and second, the possibility of using non-quadratic regularizers, thanks to advances in compressed sensing.

By |November 17th, 2017|Highlights-post, Highlights-QA|Comments Off on Q&A with Kathleen M.Ropella and Douglas C.Noll

November Highlights

November Cover Art

The ultimate signal-to-noise ratio in realistic body models, by Bastien Guérin, Jorge F. Villena, Athanasios G. Polimeridis, Elfar Adalsteinsson, Luca Daniel, Jacob K. White and Lawrence L. Wald

November Editor’s Picks

Investigating magnetic susceptibility of human knee joint at 7 Tesla, by Hongjiang Wei, Russell Dibb, Kyle Decker, Nian Wang, Yuyao Zhang, Xiaopeng Zong, Weili Lin, Daniel B. Nissman and Chunlei Liu

Audioslides

A regularized, model-based approach to phase-based conductivity mapping using MRI, by Kathleen M. Ropella and Douglas C. Noll

Audioslides: coming soon!

By |November 3rd, 2017|Highlights-post|Comments Off on November Highlights

Q&A with S. Johanna Vannesjo and Klaas Pruessmann

By Ryan Topfer

Johanna Vannesjo

A Highlights Halloween special: For those less than BOLD researchers who remain frightful of Nyquist ghosts, fear not! Johanna and Klaas herein reveal their trick for treating shim and gradient coil-induced field distortions with full cross-term pre-emphasis and, more generally, some tricks of the trade – “How to Make It” in the world of MR engineering research.

By |October 27th, 2017|Highlights-post, Highlights-QA|Comments Off on Q&A with S. Johanna Vannesjo and Klaas Pruessmann

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

 Audioslides

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

Audioslides

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