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Frontotemporal dementia (FTD) is one of the main causes of dementia in people under 65, accounting for nearly 20% of neurodegenerative dementia
.
The clinical symptoms of FTD overlap with other types of dementia, mental illness, or Parkinson's disease
Alzheimer's disease (AD) is the most common type of dementia and is often difficult to distinguish from FTD, especially in the early stages
Currently, there is no disease-modifying therapy for FTD
.
Acetylcholinesterase inhibitors, which are widely used in AD patients, may worsen the symptoms of FTD patients
diagnosis
Structural magnetic resonance imaging (sMRI) is a common non-invasive test used to diagnose dementia
.
Compared with computed tomography, positron emission tomography and advanced MRI sequences, sMRI has the advantages of being widely used, no ionizing radiation or nuclear radiation, objective observation of brain atrophy, and good tissue contrast
In clinical practice, neurologists and radiologists use various visual scales to assess the degree of brain atrophy in MR images
.
Although it is convenient to implement, visual scoring is highly subjective and relies on experience, which can easily lead to misdiagnosis and missed diagnosis in practice
Recently, people have conducted a lot of research on automatic brain segmentation, quantitative analysis and machine learning of neurodegenerative diseases
.
However, a large number of machine learning-based classifications are highly dependent on limited training data and lack of basic clinical reasons
Secondly, most studies are based on samples from a single center.
Due to the heterogeneity of diagnostic criteria, imaging parameters, and sociodemographic characteristics of patients, they may not be able to be transformed into studies of other centers
.
Finally, many studies only focus on the difference between AD and behavioral variant frontotemporal dementia (bvFTD)
But in fact, due to the presence of mild or overlapping language barriers, AD with language barriers may also be confused with subtypes of FTD, such as primary progressive aphasia (PPA), including semantic variant PPA (svPPA) and Non-fluency variability PPA (nfvPPA)
.
Therefore, if AD can be distinguished from FTD spectrum disorders, it is desirable in theory and meaningful in practice
Therefore, if AD can be distinguished from FTD spectrum disorders, it is desirable in theory and meaningful in practice
In this study, the data came from three different databases, including 47 FTD patients, 47 AD patients, and 47 normal controls in the NACC database; 50 AD patients in the ADNI database; and 50 AD patients in the FTLDNI database.
FTD patients
.
The MRI images of all subjects were automatically segmented, and AccuBrain® was used to quantify brain atrophy, including AD-RAI
.
A new MRI index is named Frontotemporal Dementia Index (FTDI), which is the ratio of the weighted sum of the volume index of the "FTD-dominant" structure and the volume index of the "AD-dominant" structure
.
The identification of weights and "FTD/AD dominant" structure is obtained through statistical analysis of NACC data
.
Using independent data from ADNI and FTLDNI databases verifies the distinguishing performance of FTDI
.
Result
.
AD-RAI is a mature biomarker of imaging, which can identify AD and FTD from NC, and its value is significantly higher than our previous report (p <0.
001, AUC = 0.
88), but there is no obvious difference between AD and FTD The difference (p = 0.
647)
.
FTDI showed excellent accuracy in identifying FTD from AD (AUC=0.
90; SEN=89%, SPE=75%, threshold=1.
08)
.
Validation using independent data from the ADNI and FTLDNI datasets also confirmed the efficacy of FTDI (AUC=0.
93; SEN=96%, SPE=70%, threshold=1.
08)
.
The important significance of this study lies in the discovery: AD, FTD and normal elderly brain atrophy show different patterns
.
In addition to AD-RAI, which aims to detect abnormal brain atrophy in dementia, a new index specifically for FTD has also been proposed and verified
.
AD, FTD and normal elderly brain atrophy show different patterns
Original source: the National Alzheimer's Coordinating Center, the Alzheimer's Disease Neuroimaging Initiative, the Frontotemporal Lobar Degeneration Neuroimaging Initiative, Yu Q, et al.
An MRI-based strategy for differentiation of frontotemporal dementia and Alzheimer's disease.
Alz Res Therapy .
2021;13( 1):23.
doi:10.
1186/s13195-020-00757-5
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