Posts Tagged MRI

[WEB SITE] Can MRI Brain Scans Help Us Understand Epilepsy?


A massive meta-analysis of global MRI imaging data on epilepsy patients seeks to clarify a complicated and mysterious neurological disorder.

Epilepsy is a neurological disorder characterized by seizures, which can vary from mild and almost undetectable to severe, featuring vigorous shaking. Almost 40 million people worldwide are affected by epilepsy. Epileptic seizures are caused by an abnormally high level of activity in nerve cells in the brain. A small number of cases have been tied to a genetic defect, and major trauma to the brain (such as an injury or stroke) can also induce seizures. However, for the majority of cases, the underlying cause of epilepsy is not known. In many instances, epilepsy can be treated with the use of anti-convulsant medication. Some people will experience an improvement in their symptoms to the point of no longer requiring medication, while others will not respond to medication at all. The variability of the disease with regards to physiology and progression makes it difficult to accurately diagnose.

How Does Epilepsy Affect the Brain?

There are multiple types of epilepsies, some more common than others, which affect different parts of the brain cortex. The disorder has been studied by using techniques such as magnetic resonance imaging (MRI), and analyses of brain tissue. The latter requires post-mortem collection of tissue, as biopsies are not routinely performed on living patients’ brains. A brain scan via MRI imaging can provide detail about pathological markers of epilepsy, but the massive amount of data collected worldwide by imaging has not yet been consolidated and analyzed in a robust manner. Gaining an understanding of distinct or shared disease markers for different forms of epilepsy could help clinicians identify targets for therapy and increase the personalization of treatment.

The ENIGMA Study

A recent study published in the journal BRAIN represents the largest neuroimaging analysis of epilepsy conducted to date.This study, called ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis)summarizes contributions from 24 research centers across 14 countries in Europe, North and South America, Asia, and Australia. Similar wide-ranging studies have revealed structural brain abnormalities in other neurological conditions such as schizophrenia, depression, and obsessive-compulsive disorder. The researchers had several goals in putting this meta-analysis together:

  1. To look at distinct types of epilepsy to see whether they share similar structural abnormalities of the brain.
  2. To analyze a well-known specific type of epilepsy, mesial temporal lobe epilepsy (MTLE) for differences between people afflicted with this disorder on different sides of the brain.
  3. To analyze idiopathic generalized epilepsies (IGE), which are thought to have a genetic component to their cause and aren’t often detectable via MRI.

The researchers compiled imaging data from 2,149 people with epilepsy and 1,727 healthy control subjects. The large sample size allowed them to perform high-powered statistical analysis of the data.

For analysis (1), the results showed that a diverse array of epilepsies showed common structural anomalies across several different regions of the brain. This suggested that distinct disease types share a common neuroanatomical signature.

For analysis (2), they found that people with mesial temporal lobe epilepsy on the right side of the hippocampus did not experience damage to the left side, and vice-versa. However, somewhat unexpectedly, they saw that damage extended to areas outside the hippocampus, suggesting that even a region-specific disorder like mesial temporal lobe epilepsy may be a network disease.

In analysis (3), the researchers found that contrary to many reports of a “normal” MRI for patients with idiopathic generalized epilepsy, several structural irregularities were observable over a large number of samples. These included reduced brain volume and thickness in several regions.

One Step Closer to Understanding Epilepsy

The authors noted some limitations to their study, such as the fact that all results were derived from cross-sectional data, meaning that it was not possible to determine whether certain features were the cause of severe brain damage at one point in time, or whether they were the product of progressive trauma. In addition, this study could not account for the possible contribution of other factors, such as medications, seizure type and frequency, and disease severity. However, this wide-scale meta-analysis represents an important step towards understanding how different types of epilepsies affect the brain, and hopefully can lead to more personalized and effective medical interventions.

Written by Adriano Vissa, PhD

Reference: Whelan CD, et al. Structural brain abnormalities in the common epilepsies assessed in a worldwide ENIGMA study. Brain. 2018; 141(2):391-408


via Can MRI Brain Scans Help Us Understand Epilepsy? – Medical News Bulletin | Health News and Medical Research

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[WEB SITE] MRI brain scans may help clinicians decide between CBT and drug treatment for depression

Researchers from Emory University have found that specific patterns of activity on brain scans may help clinicians identify whether psychotherapy or antidepressant medication is more likely to help individual patients recover from depression.

The study, called PReDICT, randomly assigned patients to 12 weeks of treatment with one of two antidepressant medications or with cognitive behavioral therapy (CBT). At the start of the study, patients underwent a functional MRI brain scan, which was then analyzed to see whether the outcome from CBT or medication depended on the state of the brain prior to starting treatment. The study results are published as two papers in the March 24 online issue of the American Journal of Psychiatry.

The MRI scans identified that the degree of functional connectivity between an important emotion processing center (the subcallosal cingulate cortex) and three other areas of the brain was associated with the treatment outcomes. Specifically, patients with positive connectivity between the brain regions were significantly more likely to achieve remission with CBT, whereas patients with negative or absent connectivity were more likely to remit with antidepressant medication.

“All depressions are not equal and like different types of cancer, different types of depression will require specific treatments. Using these scans, we may be able to match a patient to the treatment that is most likely to help them, while avoiding treatments unlikely to provide benefit,” says Helen Mayberg, MD, who led the imaging study. Mayberg is a Professor of Psychiatry, Neurology and Radiology and the Dorothy C. Fuqua Chair in Psychiatric Imaging and Therapeutics at Emory University School of Medicine.

Mayberg and co- investigators Boadie Dunlop, MD, Director of the Emory Mood and Anxiety Disorders Program, and W. Edward Craighead, PhD, J. Rex Fuqua Professor of Psychiatry and Behavioral Sciences, sought to develop methods for a more personalized approach to treating depression.

Current treatment guidelines for major depression recommend that a patient’s preference for psychotherapy or medication be considered in selecting the initial treatment approach. However, in the PReDICT study patients’ preferences were only weakly associated with outcomes; preferences predicted treatment drop-out but not improvement. These results are consistent with prior studies, suggesting that achieving personalized treatment for depressed patients will depend more on identifying specific biological characteristics in patients rather than relying on their symptoms or treatment preferences. The results from PReDICT suggest that brain scans may offer the best approach for personalizing treatment going forward.

In recruiting 344 patients for the study from across the metro Atlanta area, researchers were able to convene a more diverse group of patients than other previous studies, with roughly half of the participants self-identified as African-American or Hispanic.

“Our diverse sample demonstrated that the evidence-based psychotherapy and medication treatments recommended as first line treatments for depression can be extended with confidence beyond a white, non-Hispanic population,” says Dunlop.

“Ultimately our studies show that clinical characteristics, such as age, gender, etc., and even patients’ preferences regarding treatment, are not as good at identifying likely treatment outcomes as the brain measurement,” adds Mayberg.

Source: MRI brain scans may help clinicians decide between CBT and drug treatment for depression

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[WEB SITE] Understanding the Human Brain – Neuroscience News

Functional magnetic resonance images reflect input signals of nerve cells.

The development of magnetic resonance imaging (MRI) is a success story for basic research. Today medical diagnostics would be inconceivable without it. But the research took time to reach fruition: it has been nearly half a century since physicists first began their investigations that ultimately led to what became known as nuclear magnetic resonance. In 2001, Nikos K. Logothetis and his colleagues at the Max Planck Institute for Biological Cybernetics in Tübingen devised a new methodological approach that greatly deepened our understanding of the principles of functional MRI.

The great advantage of functional magnetic resonance imaging (fMRI) is that it requires no major interventions in the body. In fMRI, the human body is exposed to the action of electromagnetic waves. As far as we know today, the process is completely harmless, despite the fact that fMRI equipment generates magnetic fields that are about a million times stronger than the natural magnetic field of the earth.

The physical phenomenon underlying fMRI is known as nuclear magnetic resonance, and the path to its discovery was paved with several Nobel prizes. The story begins in the first half of the 20th century with the description of the properties of atoms. The idea of using nuclear magnetic resonance as a diagnostic tool was mooted as early as the 1950s. But the method had to be refined before finally being realised in the form of magnetic resonance imaging.

Today, MRI not only produces images of the inside of our bodies; it also provides information on the functional state of certain tissues. The breakthrough for fMRI came in the 1980s when researchers discovered that MRI can also be used to detect changes in the oxygen saturation of blood, a principle known as BOLD (blood oxygen level dependent) imaging. There is a 20 percent difference between the magnetic sensitivity of oxygenated arterial blood and that of deoxygenated venous blood. Unlike oxygenated haemoglobin, deoxygenated haemoglobin amplifies the strength of a magnetic field in its vicinity. This difference can be seen on an MRI image.

Resuscitation of the brain after a 15-minute cardiac arrest in fMRI: The pictorial representation provides information about the degree of damage of the brain as well as a detailed analysis of the recovery curve. The top three rows are examples of successful and the bottom row for an unsuccessful resuscitation. The comparison with the concentration images of ATP, glucose and lactate shows that the MR images are in fact closely related to the biochemical changes. Based on such studies, the course of cerebral infarction and the success of various therapeutic measures can be documented. Credit Max Planck Institute.

fMRI has given us new insights into the brain, especially in neurobiology. However, the initial phase of euphoria was followed by a wave of scepticism among scientists, who questioned how informative the “coloured images” really are. Although fMRI can in fact generate huge volumes of data, there is often a lack of background information or basic understanding to permit a meaningful interpretation. As a result, there is a yawning gap between fMRI measurements of brain activity and findings in animals based on electrophysiological recordings.

This is due mainly to technical considerations: interactions between the strong MRI field and currents being measured at the electrodes made it impossible to apply the two methods simultaneously to bridge the gap between animal experiments and findings in humans.

fMRT shows input signals

In 2001, Nikos Logothetis and his colleagues at the Max Planck Institute for Biological Cybernetics in Tübingen were the first to overcome this barrier. With the help of special electrodes and sophisticated data processing, they showed unambiguously that BOLD fMRI actually does measure changes in the activity of nerve cells. They also discovered that BOLD signals correlate to the arrival and local processing of data in an area of the brain rather than to output signals that are transmitted to other areas of the brain. Their paper was a milestone in our understanding of MRI and has been cited over 2500 times worldwide.

Their novel experimental setup enabled the Tübingen scientists to study various aspects of nerve cell activity and to distinguish between action potentials and local field potentials. Action potentials are electrical signals that originate from single nerve cells or a relatively small group of nerve cells. They are all-or-nothing signals that occur only if the triggering stimulus exceeds a certain threshold. Action potentials therefore reflect output signals. These signals are detected by electrodes located in the immediate vicinity of the nerve cells. By contrast, local field potentials generate slowly varying electrical potentials that reflect signals entering and being processed in a larger group of nerve cells.

Applying these three methods simultaneously, the Max Planck researchers examined the responses to a visual stimulus in the visual cortex of anaesthetized monkeys. Comparison of the measurements showed that fMRI data relate more to local field potentials than to single-cell and multi-unit potentials. This means that changes in blood oxygen saturation are not necessarily associated with output signals from nerve cells; instead, they reflect the arrival and processing of signals received from other areas of the brain.

Another important discovery the Tübingen researchers made was that, because of the large variability of vascular reactions, BOLD fMRI data have a much lower signal-to-noise ratio than electrophysiological recordings. Because of this, conventional statistical analyses of human fMRI data underestimate the extent of activity in the brain. In other words, the absence of an fMRI signal in an area of the brain does not necessarily mean that no information is being processed there. Doctors need to take this into account when interpreting fMRI data.


Contact: Christina Beck – Max Planck Institute
Source: Max Planck Institute press release
Image Source: The image is credited to Max Planck Institute and is adapted from the press release

Source: Understanding the Human Brain – Neuroscience News

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[ARTICLE] Comparison of Magnetic Resonance Imaging and Stress Radiographs in the Evaluation of Chronic Lateral Ankle Instability – Full Text

In patients who develop chronic ankle instability, clinicians often obtain magnetic resonance imaging (MRI) as part of the evaluation prior to operative referral. The purpose of this study was to analyze the diagnostic efficacy of MRI in the diagnosis of chronic lateral ankle instability. Our hypothesis was that magnetic resonance imaging would not be a specific diagnostic tool in the evaluation of chronic lateral ankle instability.

A retrospective chart review of 187 consecutive patients (190 ankles) was performed. Inclusion criteria for the study group required a primary complaint of instability that required operative repair or reconstruction, a documented clinical evaluation consistent with instability, stress radiographs, and MRI. Stress radiographs and clinical examinations for the study group and a control group were reviewed independently by both a musculoskeletal radiologist and a board-certified orthopaedic foot and ankle surgeon. Predictive values in terms of sensitivity, specificity, and prevalence were performed. In total, 112 patients (115 ankles) were identified who underwent an operative reconstruction of their lateral ligaments with a history, physical examination, and stress radiographs consistent with lateral ankle instability. A control group was selected consisting of 75 patients seen in the foot and ankle clinic with a diagnosis other than lateral ankle instability. Thirty-seven of the patients in the control group had stress radiographs performed in the clinic to rule out instability as part of their evaluation, and this allowed for an evaluation of the efficacy of stress radiographs in addition to MRI. Statistical analysis was performed using predictive values from sensitivity, specificity, and prevalence.

The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) in regards to MRI in the evaluation of patients found to have clinical lateral ankle instability and those who did not had statistical significance. Sensitivity of MRI was 82.6%, specificity was 53.3%, NPV was 66.7%, and PPV was 73%. Since 37 patients in the control group also had stress radiographs, a subanalysis was performed to identify the same values with stress radiographs. Sensitivity, specificity, NPV, and PPV were 66%, 97%, 48%, and 98.7%, respectively. The overall accuracy within this study was 71% for MRI and 74% for stress radiographs.

This study demonstrated that MRI has high sensitivity but low specificity in the evaluation of clinical ankle instability. While MRI has value as a screening tool for concomitant ankle pathology, it should not be considered diagnostic in terms of lateral ankle instability.

Figure 1. In conducting the anterolateral drawer, the examiner applies slight internal rotation force and stabilizes the tibia with one hand while grasping the heel with the other hand and applying anteriorly directed force on the heel.

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Continue —> Comparison of Magnetic Resonance Imaging and Stress Radiographs in the Evaluation of Chronic Lateral Ankle Instability – Jan 06, 2017

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[Educational] Central Nervous System – Visual Perspectives


Central Nervous System – Visual Perspectives illustrates the spatial dimension of the human brain and stimulates interaction with the object being studied, something which is not a standard feature of illustrations and atlases. The information from the interactive animation will ease retention and incorporation of knowledge structures as a resource for mental model construction of the human brain and spinal cord. We hope that the use of Central Nervous System: Visual Perspectives will enhance motivation of the students, increase their comprehension of the content, and facilitate learning such a complex structure as the human CNS.

It is a demanding task to study the anatomy of the human brain. The complexity can be simplified by approaching the study of the brain from the dual perspectives of its spatial and functional anatomy. CNS-Visualperspectives examines the relations between different brain structures and defines major divisions. Functional anatomy describes the role of the structures and points out structures that work together to accomplish particular tasks…

Anna Josephson
MD; PhD, Dept. of Neuroscience
Karolinska Institutet


Source: Central Nervous System – Visual Perspectives

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[ARTICLE] Does stroke location predict walk speed response to gait rehabilitation? – Full Text PDF/HTML



Recovery of independent ambulation after stroke is a major goal. However, which rehabilitation regimen best benefits each individual is unknown and decisions are currently made on a subjective basis. Predictors of response to specific therapies would guide the type of therapy most appropriate for each patient. Although lesion topography is a strong predictor of upper limb response, walking involves more distributed functions. Earlier studies that assessed the cortico-spinal tract (CST) were negative, suggesting other structures may be important.

Experimental Design: The relationship between lesion topography and response of walking speed to standard rehabilitation was assessed in 50 adult-onset patients using both volumetric measurement of CST lesion load and voxel-based lesion–symptom mapping (VLSM) to assess non-CST structures. Two functional mobility scales, the functional ambulation category (FAC) and the modified rivermead mobility index (MRMI) were also administered. Performance measures were obtained both at entry into the study (3–42 days post-stroke) and at the end of a 6-week course of therapy. Baseline score, age, time since stroke onset and white matter hyperintensities score were included as nuisance covariates in regression models.

Principal Observations: CST damage independently predicted response to therapy for FAC and MRMI, but not for walk speed. However, using VLSM the latter was predicted by damage to the putamen, insula, external capsule and neighbouring white matter.


Walk speed response to rehabilitation was affected by damage involving the putamen and neighbouring structures but not the CST, while the latter had modest but significant impact on everyday functions of general mobility and gait.

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Continue HTML —> Does stroke location predict walk speed response to gait rehabilitation? – Simon Jones – 2015 – Human Brain Mapping – Wiley Online Library

Figure 1. Lesion overlap map from the 50 participants overlaid on a standard MNI space brain after the right-sided lesions had been flipped to the left side (see Methods section), and projected onto the whole set of axial slices from the canonical normal subject T1-weighted MRI in Montreal Neurological Institute (MNI) space. The number of participants in each pixel is shown on the pseudo-colour scale on the right. The maximum number of participants with a lesion for any voxel was 24 (red colour) and involved the striato-capsular area and corona radiata. [Color figure can be viewed in the online issue, which is available at]

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Neurology Image Library | Internet Stroke Center

Neurology Image Library

View CT, MRI, and Angiogram case studies by diagnosis

This library illustrates a variety of stroke related diagnoses through deidentified case studies. Use keyword searches to narrow down to specific cases of interest and select a diagnosis to view images.

Goto —> Neurology Image Library

Source: Neurology Image Library | Internet Stroke Center

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[WEB SITE] Brain Imaging: Advance Aims for Epilepsy’s Hidden Hot Spots


GluCEST signal

GluCEST imaging of the brain of a person with drug-resistant epilepsy, showing the hippocampi (highlighted) with signal for high glutamate (red). Credit: Reddy Lab, University of Pennsylvania

For many of the 65 million people around the world with epilepsy, modern medications are able to keep the seizures under control. When medications fail, as they do in about one-third of people with epilepsy, surgery to remove affected brain tissue without compromising function is a drastic step, but offers a potential cure. Unfortunately, not all drug-resistant patients are good candidates for such surgery for a simple reason: their brains appear normal on traditional MRI scans, making it impossible to locate precisely the source(s) of the seizures.

Now, in a small study published in Science Translational Medicine [1], NIH-funded researchers report progress towards helping such people. Using a new MRI method, called GluCEST, that detects concentrations of the nerve-signaling chemical glutamate in brain tissue [2], researchers successfully pinpointed seizure-causing areas of the brain in four of four volunteers with drug-resistant epilepsy and normal traditional MRI scans. While the findings are preliminary and must be confirmed by larger studies, researchers are hopeful that GluCEST, which takes about 30 minutes, may open the door to new ways of treating this type of epilepsy.

To understand why glutamate might be a useful marker for epilepsy, it’s useful to note that this molecule serves as the brain’s main excitatory nerve signal. In healthy people, when neurons fire off a stimulatory signal, they release short bursts of glutamate to relay the signal onward. Support cells then rapidly clear the glutamate. But in some people with epilepsy, glutamate seems to build up outside of brain cells, triggering continuous overstimulation and potential seizures.

The challenge has been finding these suspected glutamate hot spots, to see if they correlate with seizures. In the study, led by Ravinder Reddy and Kathryn Davis of the University of Pennsylvania, the researchers turned to GluCEST to image hot spots specifically in people with drug-resistant epilepsy localized to the brain’s temporal lobe. This includes the left and right hippocampi, which are parts of the brain that help to consolidate short-term thought into long-term memory, play a role in spatial navigation, and, importantly, are a frequent site of seizures.

While conventional MRI works by using strong magnets and radio waves to study water molecules directly in living tissue, GluCEST takes advantage of special chemical properties of glutamate that influence water to visualize and quantify it at high resolution. Reddy and Davis found in the study that their GluCEST images could detect an increase in glutamate in the hippocampi. In every case, glutamate levels were elevated on the side of the brain in which the participant’s seizures were found to originate, based on brain wave recordings during a seizure. In contrast to the people with epilepsy, GluCEST scans of 11 healthy volunteers didn’t show any consistent differences in glutamate levels on one side of the brain versus the other.

Although the new study represents a very small number of patients, it suggests that GluCEST might stand to improve patient care and quality of life in people with epilepsy who now have very limited treatment options. The researchers say they’ve reported their early findings in hopes that they can be validated in more people with epilepsy by researchers at other medical centers. The GluCEST technique requires powerful 7 Tesla MRI scanners, which are already in regular use for research purposes at some medical centers around the country, and special software, which the researchers intend to make freely available.

As for the UPenn team, they’re working to expand and improve upon the GluCEST method to produce images and data in three dimensions and over a wider swath of the brain. If they are successful, this new tool could yield important insights into epilepsy and a variety of other neurological disorders in which glutamate is thought to play an important role, including schizophrenia, Alzheimer’s disease, Parkinson’s disease, and maybe even autism.


[1] Glutamate imaging (GluCEST) lateralizes epileptic foci in nonlesional temporal lobe epilepsy. Davis KA, Nanga RP, Das S, Chen SH, Hadar PN, Pollard JR, Lucas TH, Shinohara RT, Litt B, Hariharan H, Elliott MA, Detre JA, Reddy R. Sci Transl Med. 2015 Oct 14;7(309):309ra161.

[2] Magnetic resonance imaging of glutamate. Cai K, Haris M, Singh A, Kogan F, Greenberg JH, Hariharan H, Detre JA, Reddy R. Nat Med. 2012 Jan 22;18(2):302-306.


Epilepsy Information Page (National Institute of Neurological Disorders and Stroke/NIH)

Magnetic Resonance Imaging (National Institute of Biomedical Imaging and Bioengineering/NIH)

Center For Magnetic Resonance And Optical Imaging (Perelman School of Medicine, University of Pennsylvania, Philadelphia)

Kathryn Davis (Perelman School of Medicine)

Ravinder Reddy (Perelman School of Medicine)

NIH Support: National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke

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[WEB SITE] Role of MRI in Epilepsy – Radiology Assistant


Role of MRI in Epilepsy

Laurens De Cocker, Felice D’Arco and Philippe Demaerel and Robin Smithuis


.In many patients with epilepsy antiepileptic drug treatment is unable to control the seizures.
Using a dedicated MRI-protocol, it is possible to detect an epileptogenic lesion in 80 percent of these patients.
Resection of these lesions can lead to seizure freedom in many patients.
We will discuss the MRI protocol and the typical findings in the most common epilepsy-associated diseases.

Common causes of Epilepsy

The illustration summarizes the most common causes of seizures in patients with medically uncontrollable epilepsy.
Some of these lesions are readily identifiable.
Meso temporal sclerosis and focal cortical dysplasia are the most common causes and can only be depicted with a dedicated protocol.

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Continue —> The Radiology Assistant : Role of MRI in Epilepsy.

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[WEB SITE] What to Expect from an MRI


MRI MachineWhat Exactly is an MRI?

Magnetic resonance imaging (MRI) uses magnetic resonance to take detailed, high resolution images of your body that other procedures such as X-rays are not able to detect. An MRI does not produce a photo but rather a map of specific parts of your body which are highly valuable to your prognosis, diagnosis, and future treatment plan.

I recently had my first MRI during a yearly follow-up with my provider to monitor scoliosis issues with my spine. Below is the information I learned during the MRI process including reasons your doctor may recommend the procedure, questions you should ask, benefits vs. risks, preparing for the procedure, what you should expect during the scan, and following up with your provider afterwards.

Reasons Your Provider may Recommend an MRI:

  • To get a more accurate picture of your body.
  • To identify specific abnormalities.
  • To recommend the most appropriate treatment plan.
  • To determine if further tests or procedures are required.
  • To defer or more accurately recommended surgery.

Questions You Should Ask before the Scan

If your doctor has recommended an MRI scan, below are some questions you should ask and ensure you fully understand prior to undergoing the procedure:

  • Will the scan be covered by my insurance?

Your provider may not be able to answer this question, but he or she can direct you to the billing department and the right people who can get you the financial answers you need.

  • Is this absolutely necessary or are there alternatives?

As with any recommended procedure, it’s important to ask your doctor if this is the right treatment, necessary to move forward with your care, and if there are any alternatives you should consider.

Continue —->  What to Expect from an MRI.

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