Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

10.1K
Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
10.1K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Characterization of low-level water addition for preparative chiral SFC.

Journal of chromatography. A·2026
Same author

Standardized End Point Definitions for Clinical Trials in Thoracic Aortic Repair: A Consensus Report From the ARCH-Academic Research Consortium.

Circulation·2026
Same author

Development of a population based patient cancer data warehouse from multiple electronic health record systems.

Health informatics journal·2026
Same author

Two hundred years of historical spawning and nursery data for coregonine fishes in the Laurentian Great Lakes.

Scientific data·2026
Same author

Sentence-Level Cross-Referencing Improves Comprehension and Confidence in AI-Generated Patient-Friendly Radiology Reports: Design for Understanding.

Journal of the American College of Radiology : JACR·2026
Same author

Deep reinforcement learning for automatic anatomic CT landmark localization in Stanford Type B aortic dissection.

Radiology advances·2026
Same journal

Rosai-Dorfman Disease: Imaging and Updates.

Radiographics : a review publication of the Radiological Society of North America, Inc·2026
Same journal

Spectrum of Breast Sarcomas with Radiologic-Pathologic Correlation.

Radiographics : a review publication of the Radiological Society of North America, Inc·2026
Same journal

Postdeployment Monitoring and Surveillance Methods, Guidelines, and Possibilities for AI in Radiology.

Radiographics : a review publication of the Radiological Society of North America, Inc·2026
Same journal

Pediatric Sacroiliac Joint: Normal Development and Pathologic Disorders.

Radiographics : a review publication of the Radiological Society of North America, Inc·2026
Same journal

US of the Postprocedure Uterus: Long-term Findings with Correlative Imaging.

Radiographics : a review publication of the Radiological Society of North America, Inc·2026
Same journal

Imaging of the Three-Piece Inflatable Penile Prosthesis.

Radiographics : a review publication of the Radiological Society of North America, Inc·2026
See all related articles

Related Experiment Video

Updated: Mar 9, 2026

Author Spotlight: Optimized Lung MRI Protocol with Computationally Efficient Reconstruction Methods
05:07

Author Spotlight: Optimized Lung MRI Protocol with Computationally Efficient Reconstruction Methods

Published on: September 6, 2024

822

Reducing Functional MR Imaging Acquisition Times by Optimizing Workflow.

Wilson B Chwang1, Michael Iv1, Jason Smith1

  • 1From the Department of Radiology, Stanford Health Care, Lucas Center for Imaging, 1201 Welch Rd, Room P271, Stanford, CA 94305.

Radiographics : a Review Publication of the Radiological Society of North America, Inc
|January 12, 2017
PubMed
Summary
This summary is machine-generated.

Functional MRI acquisition times were reduced by optimizing workflow and implementing targeted interventions. This improved scheduling efficiency and patient satisfaction while maintaining diagnostic quality.

More Related Videos

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain
10:06

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

Published on: May 10, 2012

13.5K
Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
09:30

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease

Published on: December 18, 2016

20.2K

Related Experiment Videos

Last Updated: Mar 9, 2026

Author Spotlight: Optimized Lung MRI Protocol with Computationally Efficient Reconstruction Methods
05:07

Author Spotlight: Optimized Lung MRI Protocol with Computationally Efficient Reconstruction Methods

Published on: September 6, 2024

822
High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain
10:06

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

Published on: May 10, 2012

13.5K
Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
09:30

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease

Published on: December 18, 2016

20.2K

Area of Science:

  • Neurology
  • Radiology
  • Medical Imaging

Background:

  • Functional magnetic resonance imaging (fMRI) is crucial for assessing hemispheric language lateralization.
  • Current fMRI protocols can be lengthy, posing scheduling challenges and impacting patient experience.
  • Optimizing fMRI workflow is essential for efficient clinical practice.

Purpose of the Study:

  • To reduce functional MRI acquisition times by enhancing workflow efficiency.
  • To implement quality improvement tools to streamline the fMRI examination process.
  • To improve patient comfort and satisfaction through reduced scan durations.

Main Methods:

  • A multidisciplinary team retrospectively reviewed fMRI examinations (January 2013 - August 2015).
  • Key drivers for lengthy acquisition times were identified: protocols, patient monitoring, stimuli, understanding, and motion.
  • Interventions included eliminating contrast, reducing paradigm repeats, updating checklists, and improving visual/audio stimuli.

Main Results:

  • Mean fMRI acquisition time decreased from 76.3 to 53.2 minutes.
  • Routine scheduling time for fMRI was reduced from 2 hours to 1 hour.
  • Diagnostic quality of fMRI examinations was maintained throughout the optimization process.

Conclusions:

  • Workflow optimization significantly reduces functional MRI acquisition and scheduling times.
  • Streamlined fMRI protocols enhance patient comfort and satisfaction.
  • This quality improvement project offers a transferable model for other fMRI practices.