ISMRM 23rd Annual Meeting & Exhibition • 30 May - 05 June 2015 • Toronto, Ontario, Canada

Combined Educational & Scientific Session

"Please Hold Still Next Time," Challenges & Solutions in Patient Adherence

SKILL LEVEL: Basic to Intermediate

ORGANIZERS: Ben A. Kennedy, B.App.Sc., Mst. & James G. Pipe, Ph.D.

Wednesday 3 June 2015

Overview
This course will identify the wide variety of methods used to encourage patient adherence in MRI, particulary in reducing unwanted voluntary motion, as well as methods to remove the undesired side effects of this motion. Such methods may range from using external markers or MR navigators to using pads and audio-visual distractions effectively. An emphasis will be given on practical methods for clinical scanning.

Target Audience
Physicians and technologists interested in reducing patient motion, and engineers interested in developing methods for decreasing both motion and motion artifacts.

Educational Objectives
Upon completion of this course, participants should be able to:

• Describe at least three methods for reducing patient motion;
• Articulate the difference between methods used to reduce motion and methods used to correct for motion artifacts; and
• Identify at least three methods that are shown to be effective at increasing patient adherence in clinical scanning.

PROGRAM
Moderators: Jalal B. Andre, M.D., Ryan K. Robison, Ph.D.
10:00   Vendor & Research Solutions
Julian R. Maclaren, Ph.D.
10:24   Imaging in the Trenches: The Technologist's Perspective
Vera K. Kimbrell, B.S., R.T.(R)(MR)
10:48 0583.   
Prospective motion correction with FID-triggered image navigators
Maryna Babayeva1,2, Pavel Falkovskiy1,2, Tom Hilbert1,2, Guillaume Bonnier1,2, Bénédicte Maréchal1,2, Reto Meuli3, Jean-Philippe Thiran2, Rolf Gruetter3,4, Gunnar Krueger1,2, and Tobias Kober1,2
1Siemens ACIT - CHUV Radiology, Siemens Healthcare IM BM PI, & Department of Radiology, University Hospital (CHUV), Lausanne, Switzerland, 2LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, 3Department of Radiology, University Hospital (CHUV), Lausanne, Switzerland, 4CIBM, École Polytechnique Fédérale de Lausanne and University of Geneva, Switzerland

In this work, we propose a method for prospective motion correction in MRI using a novel image navigator module, which is triggered by a free induction decay (FID) navigator. Only when motion occurs, the image navigator is run and new positional information is obtained through image registration. The image navigator was specifically designed to match the impact on the magnetization and the acoustic noise of the host sequence. This detection-correction scheme was implemented for an MP-RAGE sequence and 5 healthy volunteers were scanned at 3T while performing various head movements. The correction performance was demonstrated through automated brain segmentation and an image quality index whose results are sensitive to motion artifacts.

11:00 0584.   Projection-based 2D/3D registration of collapsed FatNav data for prospective motion correction
Enrico Avventi1, Mathias Engström1,2, Ola Norbeck1, Magnus Mårtensson2,3, and Stefan Skare1,2
1Dept. of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden, 2Dept. of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden,3EMEA Research & Collaboration, GE Science Laboratory, GE Healthcare, Stockholm, Sweden

In previous works we developed a novel and promising navigator technique aimed for prospective motion correction: cFatNav (collapsed FatNav). A cFatNav sub-sequence consists of three EPI readouts sampling orthogonal planes in k-space placed between a non space-selective, fat saturation pulse and the host sequence excitation. From each sampled k-space plane, via IFFT, we can obtain a view of the excited volume projected along three orthogonal direction. We have shown that 2D registration applied to cFatNav data produces precise motion estimates when the motion occur mostly along one of the three sampled planes. In this work we present a 2D/3D registration algorithm for cFatNav data that can handle out-of-plane motion. Specifically each of the three collapsed views are matched against a reference 3D volume simultaneously by Gauss-Newton method.

11:12 0585.   A correlation based approach to respiratory self navigation for multi channel non-Cartesian MRI
Gregory R. Lee1,2, Yong Chen3, and Vikas Gulani3,4
1Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States, 2University of Cincinnati, Cincinnati, OH, United States, 3Radiology, University Hospitals Case Medical Center, Cleveland, OH, United States, 4Radiolgoy, Case Western Reserve University, Cleveland, OH, United States

In this work an approach to respiratory self-navigation is proposed that is applicable to non-Cartesian dynamic contrast enhanced MRI sequences that repeatedly sample the k-space center. The approach starts by bandpass filtering to removes slow changes in the signal magnitude & phase due to contrast arrival as well as high frequency noise. Correlations among the complex central k-space point are then evaluated across coils to extract a respiratory waveform. This waveform enables retrospective respiratory binning for motion-compensated image reconstruction. Computation time is negligible and the resulting navigator compares favorably to those acquired with a respiratory bellows or image-domain navigator.

11:24 0586.   
Autofocusing Motion Correction with 3D Image-based Navigators for Abdominal Imaging
Jieying Luo1, Nii Okai Addy1, R. Reeve Ingle1, Joseph Y. Cheng1, Bob S. Hu2, and Dwight G. Nishimura1
1Electrical Engineering, Stanford University, Stanford, California, United States, 2Palo Alto Medical Foundation, Palo Alto, California, United States

An autofocusing nonrigid respiratory motion correction method for abdominal imaging was developed. This technique used motion trajectory candidates estimated from 3D image-based navigators that were acquired with a variable-density 3D cones trajectory. The performance of the proposed autofocusing motion correction was demonstrated with free-breathing scans of the abdominal vasculature.

11:36 0587.   Markerless Motion Correction in MRI
Rasmus Ramsbøl Jensen1,2, Claus Benjaminsen1,2, Adam Espe Hansen2, Rasmus Larsen1, and Oline Vinter Olesen1,2
1DTU Compute, Technical University of Denmark, Lyngby, Copenhagen, Denmark, 2Department of Clinical Physiology, Nuclear Medicine & PET, Rigshospitalet, Copenhagen, Denmark

We propose a method for accurate motion correction in brain MRI through markerless tracking. It is the first time markerless tracking is used to correct MRI images. The method has the potential to seamlessly fit the clinical workflow with no added complexity and no errors related to the generally attached markers. It is based on our Tracoline system; a unique remote surface scanner conveying images through optical fibers. The developed software continuously aligns the surface scans, which allows for accurate motion tracking. In this work, we demonstrate our system on the Siemens mMR with motion correction of an EPI sequence.

11:48 0588.   
Technical Feasibility and Potential Applications of an optical Time-of-Flight camera mounted inside the MR scanner
Guido P. Kudielka1,2, Anne Menini1, Pierre-André Vuissoz2,3, Jacques Felblinger3,4, and Florian Wiesinger1
1GE Global Research, Munich, BY, Germany, 2Imagerie Adaptative Diagnostique et Interventionnelle, Université de Lorraine, Nancy, Lorraine, France,3U947, INSERM, Nancy, Lorraine, France, 4CIC-IT 1433, INSERM, Nancy, Lorraine, France
 
Acquistion of 3D information with dedicated cameras is becoming more popular in healthcare applications for motion and position registration as well as for diagnostic purposes. We present the technical feasibility of such a camera system in a MRI environment. Respiratory movement was acquired by the camera during free-breathing abdominal MRI acquistions. The acquired images were corrected retrospectively with the respiratory belt information, the depth information and intensity amplitude of the camera. The comparison with pneumatic belt data shows strong correlation and motion artifacts were greatly reduced with the camera data.

12:00   Adjournment & Meet the Teachers