Category: mri

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T1-weighted MRI

T1-weighted MRI, also known as T1-MRI, is a type of magnetic resonance imaging (MRI) that is used to create detailed images of internal organs, bones, and other structures inside the body. This imaging technique is particularly useful for visualizing soft tissue structures, such as the brain, spinal cord, and muscles, as well as for detecting certain types of tumors and other abnormalities.

The principle behind T1-weighted MRI is based on the behavior of hydrogen atoms, which are present in large quantities in the body’s water and fat molecules. When a person is placed in a magnetic field, the hydrogen atoms align with the field and emit radiofrequency signals, which are then detected by a receiver coil and used to create an image.

One of the key features of T1-weighted MRI is that it can distinguish between different types of tissue based on their water and fat content. For example, fat appears bright on a T1-weighted image, while water appears dark. This makes it possible to clearly see the boundaries between different structures, such as the brain and spinal cord, or the muscles and tendons.

T1-weighted MRI is also useful for identifying certain types of tumors and other abnormalities. Tumors, for example, tend to have a higher water content than the surrounding tissue, which makes them appear darker on a T1-weighted image. Similarly, certain types of cysts and other fluid-filled structures will also appear dark, making them easy to distinguish from surrounding tissue.

Another advantage of T1-weighted MRI is that it does not use ionizing radiation, which is the type of radiation used in x-rays and CT scans. Instead, it relies on a magnetic field and radiofrequency signals, which are considered to be safer than ionizing radiation. This makes T1-weighted MRI an attractive option for people who are at risk for developing cancer, such as children and pregnant women, as well as for those who have already had a lot of radiation exposure.

Despite its many advantages, T1-weighted MRI is not without its limitations. For example, it is not as good at visualizing certain types of bone and other hard tissue, which can make it difficult to detect certain types of fractures and other injuries. Additionally, some patients may find the procedure uncomfortable or claustrophobic, as they need to lie still inside a narrow tube for several minutes while the images are being taken. Some people also cannot receive an MRI due to implanted medical devices or other conditions.

Overall, T1-weighted MRI is a powerful imaging technique that can provide detailed images of internal organs, bones, and other structures inside the body. Its ability to distinguish between different types of tissue based on their water and fat content, as well as its ability to detect certain types of tumors and other abnormalities, make it a valuable tool for healthcare professionals. Its lack of ionizing radiation also makes it a safer option for certain patients, while the limitations of T1-weighted MRI include difficulty in visualizing certain types of bone and other hard tissue and being uncomfortable for certain patients.

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One in five older adults experience brain network weakening following knee replacement surgery

Gainesville, FL – A new University of Florida study finds that 23 percent of adults age 60 and older who underwent a total knee replacement experienced a decline in activity in at least one region of the brain responsible for specific cognitive functions. Fifteen percent of patients declined across all brain networks the team evaluated.

“In essence, normally synchronized parts of the brain appeared more out of sync after surgery,” said Jared Tanner, Ph.D., the study’s co-lead author and a research assistant professor in the department of clinical and health psychology in the UF College of Public Health and Health Professions, part of UF Health.

Patients who were cognitively weaker before surgery – with worse working memory, slowed mental processing and evidence of brain atrophy as seen in imaging scans – demonstrated the biggest network declines after surgery.

Researchers say they do not yet know if or how patients perceive these network declines. They may contribute to brain “fuzziness” some patients experience right after surgery.

The study, which was published today online ahead of print in the Journal of Alzheimer’s Disease, was conducted to help scientists understand the causes of postsurgical cognitive impairment, which causes memory and thinking problems in about 15 to 30 percent of older adult patients, Tanner said. In most cases, these thinking and memory problems will resolve within six months to a year after surgery.

“Our study builds on 50 years of research into how the aging brain responds to anesthesia and surgery,” Tanner said. “We know older age and cognitive impairment before surgery are risk factors, but the specific causes are not known.”

For the UF study, the team conducted cognitive and brain imaging tests before and after surgery on 48 patients ages 60 and older undergoing a knee replacement. Results were compared with age-matched adults who have knee osteoarthritis, but did not have surgery.

The researchers used resting state functional MRI to look at patterns of blood flow in the brain while patients were lying still. Imaging data helped researchers understand how blood flow changes affected connections across brain networks that are responsible for functions such as memories of oneself and others, determining what outside stimuli deserve further attention, and working memory.

Participants who did not have surgery did not demonstrate any changes across the two brain scans, but 23 percent of participants who had knee replacement surgery showed large declines in connectivity in at least one brain network when tested 48 hours after surgery.

“It was surprising to observe such significant effects of orthopedic surgery on the human brain,” said Haiqing Huang, Ph.D., the study’s other lead author, a data manager at the University of Pittsburgh’s Brain Aging & Cognitive Health Lab and a graduate of the biomedical engineering program at the UF Herbert Wertheim College of Engineering.

The investigators say more research is needed to learn if the brain network changes persist.

“Our goals include investigating if patients who have this brain change after surgery continue to show this change later in their recovery, say at three months or one year after the surgery,” said Catherine Price, Ph.D., the study’s senior author and a UF associate professor of clinical and health psychology and anesthesiology.

People with concerns about their attention or memory should discuss them with their surgical team, Tanner said. At UF Health, neuropsychologists and anesthesiologists have established what is believed to be the first clinical service to identify older adults who may be at risk of developing cognitive problems after surgery so that health care providers can intervene to lessen the impact.

“We strongly believe clinicians need to consider preoperative memory and attention abilities in their patients,” said Price, also the co-director of the Perioperative Cognitive and Anesthesia Network, or PeCAN, service. “Across the nation, however, cognition is not routinely assessed prior to surgery.”

There are also actions patients can take on their own, based on previous studies of healthy aging.

“The brain is resilient and there are things we can do to help protect our brains before and after surgery,” Tanner said. “Exercise, following a Mediterranean-style diet (primarily vegetables, fruits and whole grains), remaining mentally and socially active and otherwise striving to stay as healthy as possible – all might help patients’ brains cope with surgery better,” Tanner said.

—

Mingzhou Ding, Ph.D., of the J. Crayton Pruitt Family department of biomedical engineering in the Herbert Wertheim College of Engineering, served as the study’s other senior author. The project is part of a larger investigation involving Thomas Mareci, Ph.D., of the department of biochemistry and molecular biology in the College of Medicine and the Evelyn F. and William L. McKnight Brain Institute; Hari Parvataneni, M.D., of the department of orthopaedics and rehabilitation in the College of Medicine; Ilona Schmalfuss, M.D., of the department of radiology in the College of Medicine; Mark Rice, M.D., and Cynthia Garvan, Ph.D., of the department of anesthesiology in the College of Medicine; and Ann Horgas, Ph.D., of the department of biobehavioral nursing science in the College of Nursing. The research was supported by funding from the National Institutes of Health.

Press release source.

Reference

Huang H, Tanner J, Parvataneni H, Rice M, Horgas A, Ding M, Price C (2018) Impact of Total Knee Arthroplasty with General Anesthesia on Brain Networks: Cognitive Efficiency and Ventricular Volume Predict Functional Connectivity Decline in Older Adults. J Alzheimers Dis 62, 319-333.

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Video Introduction to the Cingulum

I posted this on my neuroimaging blog and thought I should post it here too. This is a video I put together about the cingulum, a prominent white matter fiber track in the brain that is involved in emotion, attention, memory, among many other functions. All images except one from Gray’s Anatomy (the anatomy book, not the T.V. show) were created by me using some fairly advanced imaging techniques. If you are interested about some of the techniques, read my neuroimaging blog.

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Video of my brain

I posted a video of my brain on YouTube just to show the quality of MRI scans we have now (and the fun things we can do with post-processing). The scans were done on a 3T Philips Achieva MR scanner. We acquired 2 T1 scans of my brain (160 1mm slices – 1 mm cubed voxel size) then post-processed the DICOMs using FreeSurfer. The skull-stripped output files (in NIFTI format) were then rendered in 3D in OsiriX. I created a fly-through movie of the brain and exported it as an MP4 movie. If you have any questions about the process, feel free to ask.

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Leukoaraiosis and Lacunes – A Very Brief Overview

As people age, it is common for their brain white matter to change. These changes often appear as bright white spots on T2-weighted MR scans. These areas or spots of hyperintensity (i.e., white matter hyperintensities {WMH}) are also called leukoaraiosis (LA). Researchers are still investigating the exact nature and pathology of these abnormalities but our understanding of them is increasing. They most often seem to start around the lateral ventricles and spread from there, although it is possible to have punctate WMH throughout the brain white matter (i.e., WMH that are not connected to other regions). WMH on brain MRIs represent rarefaction of the white matter, including swelling, demyelination, and damage, although the exact nature and combination of the white matter changes is not known. These WMH can interfere with normal cognitive functioning, including processing speed, attention, inhibition, as well as global executive functioning (although these claims are still being investigated).

Other damage to white matter includes lacunes, which are little holes in the brain, much like the holes in Swiss cheese. They are caused by mini infarcts, or strokes, or other processes. Most of the time they are due to “silent strokes”, or strokes that are small enough that the person does not have any noticeable stroke symptoms. These lacunes can have similar impact on cognition as WMH. Both WMH and lacunes are related to vascular risk factors, such as hyper- or hypo-tension, diabetes, etc.

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Moral Development and the Brain

Moral reasoning is the ability a person has to reason in and through social, ethical, and emotional situations. One component of moral reasoning is moral behavior, which is the intentional and voluntary acting in a prosocial manner (Walker, 2004). Moral behavior and reasoning are the foundation for “many human social and cultural institutions such as family structures, legal and political government systems that affect the lives of virtually every person” (Eslinger, Flaherty-Craig, & Benton, 2004, p. 100). Often situations in life are morally ambiguous and involve a choice between two actions that both have consequences that may or may not be in opposition to each other. Some researchers, such as Lawrence Kohlberg, believe that people will reason through these situations at varying levels or stages, with some in a very concrete and egotistic manner and others in an abstract and universal manner.

Lawrence Kohlberg was the first researcher to come up with a major testable theory of moral development. He formulated six stages of development, with most adults reaching stage four, a few five, and very few stage six. The first two stages are at the pre-conventional level (typically self-centered and concrete reasoning), stages three and four are at the conventional level (recognition of social norms and laws), and the last two stages at the post-conventional level (recognition of universal rights and responsibilities). While Kohlberg’s theory of moral development is a stage model, the progression through the stages is not necessarily viewed as invariant. This means that people reach them at different rates and do not always reason at a particular stage with any given dilemma. There is significant variability within and between people in moral reasoning abilities. Most research focuses on between-person variability.

Continue reading “Moral Development and the Brain”

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MedINRIA MRI Visualization and Processing

I just ran across a site that has a few medical imaging software packages. One of them is MedINRIA.

“MedINRIA aims at providing to clinicians state-of-the-art algorithms dedicated to medical image processing and visualization. Efforts have been made to simplify the user interface, while keeping high-level algorithms. Each application is called a module, and can be loaded dynamically from a single main window. MedINRIA is available for Microsoft Windows XP/Vista, Linux Fedora Core, MacOSX, and is fully multithreaded.”

Link to a description and download.

MedINRIA screenshot

I have not tried the software yet – my MRI analysis software is FSL – but this software looks promising. Plus it runs natively on Windows, Linux (Fedora Core), and Mac OS X (FSL only runs natively in OS X and Linux – it’s a little tricky to run in Windows). Not that running in Windows is necessarily a perk – our preferred MRI processing workstation is a Mac – but many people are using Windows. If I get around to installing the software, I’ll post a review of it later. I’m always looking to user-friendly ways to analyze MRI data. Best of all, like FSL, it is free. It is based, in part, on the open-source and excellent ITK and VTK packages.

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MRI Quenching

I learned something new this week. Modern MRI scanners produce high-strength magnetic fields (typically 1.5T up to about 20T – scanners for use with humans max out at about 7T right now {those are very rare though, 1.5T and 3T are more common). To produce these fields the scanners need to have strong electric currents. In order to handle large currents, scanners use superconductors cooled with liquid helium. In cases of serious malfunction or emergency the MRI scanner can be quenched, which releases all of the liquid helium. The helium turns into a gaseous state rapidly and expands to fill the room. The quench will make a loud sound like a jet engine or a pop. If the room is small enough, all of the air can be pushed out as the helium expands and increases the pressure. Most MRI rooms have fail-safe systems that release the helium outside, which prevents the occupants from suffocating.MRI Quench

Image from here.

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Diffusion Tensor Imaging and High Angular Resolution Diffusion Imaging

I attended an interesting lecture this week. The professor who spoke talked about Diffusion Tensor Imaging (DTI) as well as about a newer technology they are trying to help develop – High Angular Resolution Diffusion Imaging (HARDI). DTI is based on tensor mathematics and physics. The tensor in DTI is basically a 3×3 matrix (x, y, and z planes) of numbers that represent the diffusion per voxel in the brain. A voxel is a volumetric pixel – a 3D portion of the brain in MR imaging. The highest resolution we can typically get with clinical MR scanners is a cubic mm voxel. So with DTI we have a tensor, a matrix, that describes the diffusion of water molecules within each voxel in the brain. Diffusion in a jar of water or in the ventricles of the brain tends to be fast and spherical. It is less spherical in the gray matter and even less so in the white matter. In fact, the diffusion of water is highly directional in white matter (the myelinated axons of neurons). This means that the water molecules tend to diffuse somewhat parallel to the length of the axon. The movements of these water molecules are picked up by the MR scanner (which is technically “focusing” on the hydrogen atoms in water).
The diffusion per voxel can be quantified by measures of fractional anisotropy (how directional is the movement), Mean Diffusivity (total diffusion within the voxel), and by the eigenvalues of the matrix (basically how far the molecules moved in the direction of the eigenvector).
Back to HARDI. HARDI improves upon DTI by allowing for more directions of the white matter fibers to be separated out than is possible with DTI. There are some areas of the brain where there are a lot of crossing fibers and these areas show up as dark spots on DTI (which looks like a hole in the brain). With HARDI, you can see that the fibers are just more complex than is possible to calculate with DTI.
Both of these methods are useful for measuring the overall integrity (and potentially connectivity) of the white matter in the brain.

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The 3D brain

Technology Review has an interesting article about “new” 3D brain imaging software being developed at Thomas Jefferson University Hospital in Philadelphia, PA (I put “new” in quotation marks because there are other similar programs out there; they might not be as polished but some are even open source). Their software fuses MRI, fMRI, and DTI together to create a fairly comprehensive view of the brain: “The fusion of these different images produces a 3-D display that surgeons can manipulate: they can navigate through the images at different orientations, virtually slice the brain in different sections, and zoom in on specific sections.”

The software looks like it is aimed more at neurosurgeons than researchers (i.e., it probably isn’t free like a lot of MRI image processing software). It does produce amazing images (view the images here) and looks like it could be a very useful tool for at least a qualitative approach to brain imaging.

DTI fibers near a tumor

The software is focused a lot on DTI (diffusion tensor imaging) and how the white matter fibers in the brain interact with lesions or tumors. I think that one researcher’s word of caution is important:

“Bruce Fischl, an assistant in neuroscience at Massachusetts General Hospital, says that the idea is ‘interesting’ but cautions that there are a number of levels of ambiguity when talking about connectivity in imaging. ‘Just because you live next to the Mass Pike doesn’t mean that there is an exit,’ he says.”

In other words, don’t get too caught up in the fact that fibers are right by a tumor, they may not really have anything to do with the part of the brain the tumor is most affecting.

In any case, I think that the idea behind this software is amazing. The graphics renderings are impressive (but they are just the pretty pictures – the rendering details may be beneficial in clinical surgery settings but they are not particularly useful in research situations, other than producing nice pictures to go in your publication). This software is very similar to something that I envisioned using a few years ago and I’m glad to see it being developed.

Image credit: Song Lai, Thomas Jefferson University Hospital (borrowed via technologyreview.com)

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