MRI Multitasking Increases Diagnostic Accuracy and Reliability
By MedImaging International staff writers Posted on 24 Apr 2018 |

Image: Lead author Anthony Christodoulou, PhD (Photo courtesy of Anthony Christodoulou).
A new cardiac magnetic resonance (CMR) imaging technique improves patient comfort and shortens testing time, according to a new study.
Researchers at Cedars-Sinai Medical Center (Los Angeles, CA, USA), the University of California, Los Angeles (UCLA; USA), and Xuanwu Hospital (Beijing, China) conducted a study to examine how the need to reduce CMR imaging artefacts arising from body motion, the beating heart, and blood flow during quantitative imaging could be circumvented in order to make the procedure more reliable. The researchers decided therefore that rather than try to avoid the motion caused by breathing and heartbeats, they would embrace it.
The new technique, which they dubbed CMR Multitasking, abstracts physiological motion and other dynamic processes as time extents, which can be resolved via low-rank tensor imaging, allowing for motion-resolved quantitative CMR in up to four time dimensions. The continuous-acquisition approach, captures--rather than avoids--motion, relaxation, and other dynamics, allowing for T1 mapping, T1/T2 mapping and time-resolved T1mapping of myocardial perfusion without electrocardiography (ECG) information and/or under free-breathing conditions. The study was published on April 9, 2018, in Nature Biomedical Engineering.
“MR Multitasking continuously acquires image data and then, when the test is completed, the program separates out the overlapping sources of motion and other changes into multiple time dimensions,” said lead author Anthony Christodoulou, PhD, of the Cedars-Sinai Biomedical Imaging Research Institute. “If a picture is 2D, then a video is 3D because it adds the passage of time. Our videos are 6D because we can play them back four different ways: We can playback cardiac motion, respiratory motion, and two different tissue processes that reveal cardiac health.”
“It is challenging to obtain good cardiac magnetic resonance images, because the heart is beating incessantly, and the patient is breathing, so the motion makes the test vulnerable to errors,” said Professor Shlomo Melmed, MB, ChB, dean of the Cedars-Sinai medical faculty. “By novel approaches to this longstanding problem, this research team has found a unique solution to improve cardiac care for patients around the world for years to come.”
CMR is a medical imaging technology for the non-invasive assessment of the function and structure of the cardiovascular system, based on the same basic principles as magnetic resonance imaging (MRI), with optimizations that use rapid imaging sequences. As a result, CMR images are currently acquired in steps. Patients breathe in and then hold their breath for each image, then recover before repeating the process for the next image.
Related Links:
Cedars-Sinai Medical Center
University of California, Los Angeles
Xuanwu Hospital
Researchers at Cedars-Sinai Medical Center (Los Angeles, CA, USA), the University of California, Los Angeles (UCLA; USA), and Xuanwu Hospital (Beijing, China) conducted a study to examine how the need to reduce CMR imaging artefacts arising from body motion, the beating heart, and blood flow during quantitative imaging could be circumvented in order to make the procedure more reliable. The researchers decided therefore that rather than try to avoid the motion caused by breathing and heartbeats, they would embrace it.
The new technique, which they dubbed CMR Multitasking, abstracts physiological motion and other dynamic processes as time extents, which can be resolved via low-rank tensor imaging, allowing for motion-resolved quantitative CMR in up to four time dimensions. The continuous-acquisition approach, captures--rather than avoids--motion, relaxation, and other dynamics, allowing for T1 mapping, T1/T2 mapping and time-resolved T1mapping of myocardial perfusion without electrocardiography (ECG) information and/or under free-breathing conditions. The study was published on April 9, 2018, in Nature Biomedical Engineering.
“MR Multitasking continuously acquires image data and then, when the test is completed, the program separates out the overlapping sources of motion and other changes into multiple time dimensions,” said lead author Anthony Christodoulou, PhD, of the Cedars-Sinai Biomedical Imaging Research Institute. “If a picture is 2D, then a video is 3D because it adds the passage of time. Our videos are 6D because we can play them back four different ways: We can playback cardiac motion, respiratory motion, and two different tissue processes that reveal cardiac health.”
“It is challenging to obtain good cardiac magnetic resonance images, because the heart is beating incessantly, and the patient is breathing, so the motion makes the test vulnerable to errors,” said Professor Shlomo Melmed, MB, ChB, dean of the Cedars-Sinai medical faculty. “By novel approaches to this longstanding problem, this research team has found a unique solution to improve cardiac care for patients around the world for years to come.”
CMR is a medical imaging technology for the non-invasive assessment of the function and structure of the cardiovascular system, based on the same basic principles as magnetic resonance imaging (MRI), with optimizations that use rapid imaging sequences. As a result, CMR images are currently acquired in steps. Patients breathe in and then hold their breath for each image, then recover before repeating the process for the next image.
Related Links:
Cedars-Sinai Medical Center
University of California, Los Angeles
Xuanwu Hospital
Latest MRI News
- Cutting-Edge MRI Technology to Revolutionize Diagnosis of Common Heart Problem
- New MRI Technique Reveals True Heart Age to Prevent Attacks and Strokes
- AI Tool Predicts Relapse of Pediatric Brain Cancer from Brain MRI Scans
- AI Tool Tracks Effectiveness of Multiple Sclerosis Treatments Using Brain MRI Scans
- Ultra-Powerful MRI Scans Enable Life-Changing Surgery in Treatment-Resistant Epileptic Patients
- AI-Powered MRI Technology Improves Parkinson’s Diagnoses
- Biparametric MRI Combined with AI Enhances Detection of Clinically Significant Prostate Cancer
- First-Of-Its-Kind AI-Driven Brain Imaging Platform to Better Guide Stroke Treatment Options
- New Model Improves Comparison of MRIs Taken at Different Institutions
- Groundbreaking New Scanner Sees 'Previously Undetectable' Cancer Spread
- First-Of-Its-Kind Tool Analyzes MRI Scans to Measure Brain Aging
- AI-Enhanced MRI Images Make Cancerous Breast Tissue Glow
- AI Model Automatically Segments MRI Images
- New Research Supports Routine Brain MRI Screening in Asymptomatic Late-Stage Breast Cancer Patients
- Revolutionary Portable Device Performs Rapid MRI-Based Stroke Imaging at Patient's Bedside
- AI Predicts After-Effects of Brain Tumor Surgery from MRI Scans
Channels
Radiography
view channel
AI Improves Early Detection of Interval Breast Cancers
Interval breast cancers, which occur between routine screenings, are easier to treat when detected earlier. Early detection can reduce the need for aggressive treatments and improve the chances of better outcomes.... Read more
World's Largest Class Single Crystal Diamond Radiation Detector Opens New Possibilities for Diagnostic Imaging
Diamonds possess ideal physical properties for radiation detection, such as exceptional thermal and chemical stability along with a quick response time. Made of carbon with an atomic number of six, diamonds... Read moreUltrasound
view channel.jpeg)
AI-Powered Lung Ultrasound Outperforms Human Experts in Tuberculosis Diagnosis
Despite global declines in tuberculosis (TB) rates in previous years, the incidence of TB rose by 4.6% from 2020 to 2023. Early screening and rapid diagnosis are essential elements of the World Health... Read more
AI Identifies Heart Valve Disease from Common Imaging Test
Tricuspid regurgitation is a condition where the heart's tricuspid valve does not close completely during contraction, leading to backward blood flow, which can result in heart failure. A new artificial... Read moreNuclear Medicine
view channel
Novel Radiolabeled Antibody Improves Diagnosis and Treatment of Solid Tumors
Interleukin-13 receptor α-2 (IL13Rα2) is a cell surface receptor commonly found in solid tumors such as glioblastoma, melanoma, and breast cancer. It is minimally expressed in normal tissues, making it... Read more
Novel PET Imaging Approach Offers Never-Before-Seen View of Neuroinflammation
COX-2, an enzyme that plays a key role in brain inflammation, can be significantly upregulated by inflammatory stimuli and neuroexcitation. Researchers suggest that COX-2 density in the brain could serve... Read moreGeneral/Advanced Imaging
view channel
AI-Based CT Scan Analysis Predicts Early-Stage Kidney Damage Due to Cancer Treatments
Radioligand therapy, a form of targeted nuclear medicine, has recently gained attention for its potential in treating specific types of tumors. However, one of the potential side effects of this therapy... Read more
CT-Based Deep Learning-Driven Tool to Enhance Liver Cancer Diagnosis
Medical imaging, such as computed tomography (CT) scans, plays a crucial role in oncology, offering essential data for cancer detection, treatment planning, and monitoring of response to therapies.... Read moreImaging IT
view channel
New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible
Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Global AI in Medical Diagnostics Market to Be Driven by Demand for Image Recognition in Radiology
The global artificial intelligence (AI) in medical diagnostics market is expanding with early disease detection being one of its key applications and image recognition becoming a compelling consumer proposition... Read moreIndustry News
view channel
GE HealthCare and NVIDIA Collaboration to Reimagine Diagnostic Imaging
GE HealthCare (Chicago, IL, USA) has entered into a collaboration with NVIDIA (Santa Clara, CA, USA), expanding the existing relationship between the two companies to focus on pioneering innovation in... Read more
Patient-Specific 3D-Printed Phantoms Transform CT Imaging
New research has highlighted how anatomically precise, patient-specific 3D-printed phantoms are proving to be scalable, cost-effective, and efficient tools in the development of new CT scan algorithms... Read more
Siemens and Sectra Collaborate on Enhancing Radiology Workflows
Siemens Healthineers (Forchheim, Germany) and Sectra (Linköping, Sweden) have entered into a collaboration aimed at enhancing radiologists' diagnostic capabilities and, in turn, improving patient care... Read more