Jan 4th – Structural MRI can accurately and non-invasively predict cerebral spinal fluid (CSF) total tau to beta-amyloid ratios in patients with neurodegenerative disease.
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Image: PD/NIH. Healthy (left) vs Alzheimer’s (right)
1. Structural MRI can accurately and non-invasively predict cerebral spinal fluid (CSF) total tau to beta-amyloid ratios in patients with neurodegenerative disease.Â
2. This method may be sufficient to distinguish between Alzheimer disease and frontotemporal lobar degeneration in patients with unclear clinical presentation.
This study demonstrates that structural MRI may predict CSF tau (tt) to beta-amyloid (βA) (tt/βA) ratios with considerable accuracy relative to actual measurement of these biomarkers in patients with Alzheimer disease and frontotemporal lobar degeneration. Moreover, regional decreases in gray matter density can accurately differentiate AD from FTLD based on predicted CSF tt/βA. As the current method of diagnosis (lumbar puncture) is invasive, painful and carries multiple risks, particularly in an elderly population, a non-invasive test is highly desirable when evaluating a patient presenting with dementia not clearly distinguishable based on clinical characteristics alone.
This study is limited primarily by its design, as the algorithm is being retrofitted to known data. Validation of the model on independent data will be a crucial next step in demonstrating its clinical usefulness. That said, the model shows great promise as a non-invasive diagnostic tool, which may be useful both in the clinical and trial settings in the future.
Click to read the study in NeurologyÂ
Click to read an accompanying editorial in Neurology
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Image:Â PD/NIH. Healthy (left) vs Alzheimer’s (right)
1. Structural MRI can accurately and non-invasively predict cerebral spinal fluid (CSF) total tau to beta-amyloid ratios in patients with neurodegenerative disease.Â
2. This method may be sufficient to distinguish between Alzheimer disease and frontotemporal lobar degeneration in patients with unclear clinical presentation.
Study author, Dr. Corey T. McMillan, PhD, talks to 2 Minute Medicine: Department of Neurology, University of Pennsylvania
“Alzheimer’s disease (AD) and frontotemporal dementia (FTD) affect over 30 million individuals worldwide. However, since these patients may have overlapping clinical features it can be difficult to determine the root cause of these dementias in a clinical evaluation. To date, cerebrospinal fluid (CSF) obtained by a lumbar puncture procedure provides the most accurate diagnosis but patients may be resistant to having this procedure performed. In this paper we use MRI, a non-invasive and readily available method, in an effort to predict the protein levels measured using CSF. We observed that protein levels predicted with MRI were highly correlated with protein levels measured with CSF. We achieved 75% accuracy of identifying the source of dementia in individual subjects and suggest that for the remaining 25% of patients the more precise CSF method may be necessary. Future work is needed to validate this approach in a novel group of patients before it can be used for clinical evaluation”.
Primer: Alzheimer disease (AD) is the most common form of dementia, affecting an estimated 26.6 million patients worldwide in 2006. Frontotemporal lobar degeneration (FTLD) is a less common cause of dementia characterized by degeneration of the frontal and temporal lobes. Both disorders present similarly, particularly during the early stages of disease, which makes clinical diagnosis difficult. Currently, cerebrospinal fluid (CSF) analysis for the ratio of total tau (tt) to beta-amyloid (βA) is the preferred diagnostic test. However, lumbar puncture is invasive and carries numerous risks, particularly in an elderly population who may be on chronic anticoagulation therapies.
Structural magnetic resonance imaging (MRI) does not play a large role in the routine diagnosis of either disorder. However, regional atrophy seen on MRI has been used as a threshold criterion for entrance into clinical trials for AD and FTLD, which suggests that this modality may be sensitive to pathologic changes in both conditions. In the present study, the authors examine the potential use of MRI as a tool for differentiating AD from FTLD instead of invasive CSF sampling via traditional lumbar puncture.
Background reading:
- Cerebrospinal fluid biomarkers in the differential diagnosis of Alzheimer’s disease from other cortical dementias.
- Frontotemporal lobar degeneration: Epidemiology, pathophysiology, diagnosis and management.
- CSF biomarkers in frontotemporal lobar degeneration with known pathology.
This [cross-sectional] study: Patients with AD (n=88) and FTLD (n=97), diagnosed by clinical presentation and CSF tt/βA ratio, were given structural brain MRIs. These scans were analyzed for gray matter density (GMD) at numerous locations throughout the brain. Density values were processed via an algorithm to predict CSF tt/βA ratios. On regression analysis, ‘MRI-predicted’ and ‘actual’ CSF tt/βA ratios were significantly correlated (p<0.0001). Moreover, further regression analyses demonstrated significant correlations between lower actual CSF tt/βA (consistent with FTLD) and decreased GMD in several specified areas of the brain, as well as significant correlations between increased actual CSF tt/βA ratios (consistent with AD) and decreased GMD in other specified areas in the brain.  Also of note, in a subset of 32 patients, four false diagnoses were made based on structural MRI for each disease.
In sum: This study demonstrates that structural MRI may predict CSF tau (tt) to beta-amyloid (βA) (tt/βA) ratios with considerable accuracy relative to actual measurement of these biomarkers in patients with Alzheimer disease and frontotemporal lobar degeneration. Moreover, regional decreases in gray matter density can accurately differentiate AD from FTLD based on predicted CSF tt/βA. As the current method of diagnosis (lumbar puncture) is invasive, painful and carries multiple risks, particularly in an elderly population, a non-invasive test is highly desirable when evaluating a patient presenting with dementia not clearly distinguishable based on clinical characteristics alone.
This study is limited primarily by its design, as the algorithm is being retrofitted to known data. Validation of the model on independent data will be a crucial next step in demonstrating its clinical usefulness. That said, the model shows great promise as a non-invasive diagnostic tool, which may be useful both in the clinical and trial settings in the future.
Click to read the study in NeurologyÂ
Click to read an accompanying editorial in NeurologyÂ
By [JD] and [RR]
More from this author: Intracranial pressure monitoring does not increase survival in patients with traumatic brain injury, PET imaging findings may precede cognitive impairment in patients at high risk for Alzheimer’s disease,Initial dexamethasone improves long-term survival in acute bacterial meningitis, Elevated systolic blood pressure linked to white matter brain damage in young adults
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John Prendergass:Â John is a 2nd year M.D. candidate at New Jersey Medical School.
Rif Rahman:Â Rif is a 4th year M.D. candidate at Harvard Medical School, currently completing a research year investigating the use of conventional and advanced imaging techniques to assess treatment response of high grade gliomas.
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