In a recently published review, radiology researchers from the University of Wisconsin discussed the potential and key considerations for applying accelerated magnetic resonance imaging (MRI) protocols in the assessment of emergent and urgent conditions.
Can abbreviated magnetic resonance imaging (MRI) reduce the number of sequences and overall imaging time without adversely impacting imaging quality in emergent clinical settings?
Sharing insights from the focused abbreviated survey techniques (FAST) they have utilized for rapid MRI protocols at the University of Wisconsin School of Medicine and Public Health, radiology researchers recently published a guide of pertinent considerations with these abbreviated MRI techniques in RadioGraphics.
Here are seven key takeaways from their review.
1. Emphasizing accelerated image acquisition techniques, lower matrices for imaging, phased array coils and innovative reconstruction approaches, the researchers said their FAST MRI protocols target total imaging time of less than 10 minutes and total MRI room time of less than 15 minutes.
2. A core technology utilized for diffusion and perfusion imaging, echo-plantar MRI is an ultrafast technique that enables rapid acquisition of k-space imaging data. However, the study authors pointed out that issues with distorted images and poor quality images can occur due to the technique’s sensitivity to magnetic susceptibility and off-resonance effects. In order to facilitate optimal echo-plantar MRI, the authors recommend a combination of high-performance gradients and the use of techniques such as multi-shot techniques, parallel imaging, and spatial registration to reduce image distortion.
3. While acknowledging that computed tomography (CT) is the ideal first line of imaging for suspicion of large vessel occlusion, the review authors noted that MRI may be preferred in many instances as either initial imaging or as follow-up imaging after initial CT.
“In stroke imaging, the preference for MRI is based largely on the sensitivity of diffusion-weighted imaging to acute brain ischemia, and therefore the prediction of irreversible core infarct, as well as on the ability to sensitively detect blood products and perform whole-brain perfusion-weighted imaging for comprehensive triage with MRI,” wrote lead review author Laura B. Eisenmenger, M.D., an assistant professor of neuroradiology, associate chief of MRI, and medical director of Imaging Services at the Wisconsin Institute for Medical Research at the University of Wisconsin, and colleagues.
4. When intravenous (IV) access is challenging or not an option for patients with acute neurologic deficits, the review authors maintained that their FAST Stroke without contrast protocol is a viable option.
While acknowledging the protocol’s deficiencies with signal intensity and small vessel detection in regard to MR angiography, and an inability to identify enhancing lesions or perfusion, Eisenmenger and colleagues said the protocol allows “fair” radiological assessment of the brain parenchyma, arteries and veins in pediatric patients that may not tolerate IV access without sedation. The inclusion of diffusion-weighted imaging (DWI) and T2-weighted fluid-attenuated inversion-recovery (FLAIR) imaging within the FAST Stroke without contrast protocol may be beneficial in adult patients who have an unknown onset time of stroke.
“T2-weighted FLAIR MRI is sensitive for subarachnoid hemorrhage, and T2-weighted gradient-recalled-echo-plantar imaging is sensitive for acute parenchymal hematomas and older blood products such as remote parenchymal hematomas, microbleeds, and amyloid-related imaging abnormalities in elderly patients,” added Eisenmenger and colleagues.
However, if radiologists see an abnormality that requires further characterization, the review authors said full-length follow-up MRI may be necessary.
(Editor’s note: For related content, see “Spine Radiology Insights on Venous Fistula Localization and Finding Cerebrospinal Fluid Leaks,” “Post-Op MRI Shows New Ischemic Brain Lesions in 65 Percent of Patients After Endovascular Surgery for Intracranial Atherosclerotic Stenosis” and “New MRI Study Examines Impact of Disparities with Childhood Adversity Exposure on Brain Development.”)
5. For situations that require perfusion or robust enhancement characteristics, the review authors emphasized the FAST Brian with contrast protocol. They noted this protocol is a modified version of their FAST stroke protocol that omits the angiography-venography series while offering a more encompassing volumetric series after the use of contrast. Noting that one may employ compressed sensing or parallel imaging techniques to accelerate image acquisition for the FAST Brain with contrast protocol, Eisenmenger and colleagues recommended the MRI protocol for assessment of brain infection in an emergent setting, demyelination, perfusion-diffusion mismatches and in cases of suspected tumors.
6. Emphasizing sagittal T1-weighted three-dimensional (3D) fast-spin echo (FSE) and sagittal two-dimensional short tau inversion-recovery (STIR) images of thoracic, lumbar, and cervical regions, a FAST spine MRI protocol takes 20 minutes to complete in comparison to 90 minutes for traditional total spine MRI, according to the review authors.
“STIR sequences allow identification of edema within the (spinal) cord, osseous spinal column, or paraspinal soft tissues,” noted Eisenmenger and colleagues. “The T1-weighted three-dimensional FSE and STIR sequences combined enable robust detection of disease that causes spinal cord compression that requires emergent decompression.”
7. In regard to the advent of artificial intelligence (AI) in neuroimaging, the review authors noted a “dramatic reduction” in image reconstruction time as well as improvements in spatial resolution and noise reduction. However, Eisenmenger and colleagues noted that some AI reconstructions may not control for motion and in-flow artifacts from synthesized full-contrast reconstructions of T1-weighted sequences could lead to underestimation of contrast enhancement.
“Methods to quantify the risk, reliability, and generalizability of AI models need to be developed; this is particularly important for models trained on a small number of subjects and for deployment into clinical settings,” emphasized Eisenmenger and colleagues.