Mathematical models for the diffusion magnetic resonance signal abnormality in patients with prion diseases
In clinical practice signal hyperintensity in the cortex and/or in the striatum on magnetic resonance (MR) diffusion-weighted images (DWIs) is a marker of sporadic Creutzfeldt–Jakob Disease (sCJD). MR diagnostic accuracy is greater than 90%, but the biophysical mechanisms underpinning the signal abn...
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Published in | NeuroImage clinical Vol. 7; no. C; pp. 142 - 154 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
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Elsevier Inc
01.01.2015
Elsevier |
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Online Access | Get full text |
ISSN | 2213-1582 2213-1582 |
DOI | 10.1016/j.nicl.2014.11.017 |
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Abstract | In clinical practice signal hyperintensity in the cortex and/or in the striatum on magnetic resonance (MR) diffusion-weighted images (DWIs) is a marker of sporadic Creutzfeldt–Jakob Disease (sCJD). MR diagnostic accuracy is greater than 90%, but the biophysical mechanisms underpinning the signal abnormality are unknown. The aim of this prospective study is to combine an advanced DWI protocol with new mathematical models of the microstructural changes occurring in prion disease patients to investigate the cause of MR signal alterations. This underpins the later development of more sensitive and specific image-based biomarkers. DWI data with a wide a range of echo times and diffusion weightings were acquired in 15 patients with suspected diagnosis of prion disease and in 4 healthy age-matched subjects. Clinical diagnosis of sCJD was made in nine patients, genetic CJD in one, rapidly progressive encephalopathy in three, and Gerstmann–Sträussler–Scheinker syndrome in two. Data were analysed with two bi-compartment models that represent different hypotheses about the histopathological alterations responsible for the DWI signal hyperintensity. A ROI-based analysis was performed in 13 grey matter areas located in affected and apparently unaffected regions from patients and healthy subjects. We provide for the first time non-invasive estimate of the restricted compartment radius, designed to reflect vacuole size, which is a key discriminator of sCJD subtypes. The estimated vacuole size in DWI hyperintense cortex was in the range between 3 and 10 µm that is compatible with neuropathology measurements. In DWI hyperintense grey matter of sCJD patients the two bi-compartment models outperform the classic mono-exponential ADC model. Both new models show that T2 relaxation times significantly increase, fast and slow diffusivities reduce, and the fraction of the compartment with slow/restricted diffusion increases compared to unaffected grey matter of patients and healthy subjects. Analysis of the raw DWI signal allows us to suggest the following acquisition parameters for optimized detection of CJD lesions: b = 3000 s/mm2 and TE = 103 ms. In conclusion, these results provide the first in vivo estimate of mean vacuole size, new insight on the mechanisms of DWI signal changes in prionopathies and open the way to designing an optimized acquisition protocol to improve early clinical diagnosis and subtyping of sCJD.
•An advanced DWI acquisition scheme was applied to 15 patients with suspected sCJD.•Data fitting with two bi-compartment models outperformed the classic ADC model.•In affected GM T2 values were increased, diffusion was more hindered or restricted.•For the first time an estimate of the restricted compartment radius was provided.•The radius may reflect vacuole size, which is a key discriminator of sCJD subtypes.
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AbstractList | In clinical practice signal hyperintensity in the cortex and/or in the striatum on magnetic resonance (MR) diffusion-weighted images (DWIs) is a marker of sporadic Creutzfeldt–Jakob Disease (sCJD). MR diagnostic accuracy is greater than 90%, but the biophysical mechanisms underpinning the signal abnormality are unknown. The aim of this prospective study is to combine an advanced DWI protocol with new mathematical models of the microstructural changes occurring in prion disease patients to investigate the cause of MR signal alterations. This underpins the later development of more sensitive and specific image-based biomarkers. DWI data with a wide a range of echo times and diffusion weightings were acquired in 15 patients with suspected diagnosis of prion disease and in 4 healthy age-matched subjects. Clinical diagnosis of sCJD was made in nine patients, genetic CJD in one, rapidly progressive encephalopathy in three, and Gerstmann–Sträussler–Scheinker syndrome in two. Data were analysed with two bi-compartment models that represent different hypotheses about the histopathological alterations responsible for the DWI signal hyperintensity. A ROI-based analysis was performed in 13 grey matter areas located in affected and apparently unaffected regions from patients and healthy subjects. We provide for the first time non-invasive estimate of the restricted compartment radius, designed to reflect vacuole size, which is a key discriminator of sCJD subtypes. The estimated vacuole size in DWI hyperintense cortex was in the range between 3 and 10 µm that is compatible with neuropathology measurements. In DWI hyperintense grey matter of sCJD patients the two bi-compartment models outperform the classic mono-exponential ADC model. Both new models show that T
2
relaxation times significantly increase, fast and slow diffusivities reduce, and the fraction of the compartment with slow/restricted diffusion increases compared to unaffected grey matter of patients and healthy subjects. Analysis of the raw DWI signal allows us to suggest the following acquisition parameters for optimized detection of CJD lesions: b = 3000 s/mm
2
and TE = 103 ms. In conclusion, these results provide the first in vivo estimate of mean vacuole size, new insight on the mechanisms of DWI signal changes in prionopathies and open the way to designing an optimized acquisition protocol to improve early clinical diagnosis and subtyping of sCJD.
•
An advanced DWI acquisition scheme was applied to 15 patients with suspected sCJD.
•
Data fitting with two bi-compartment models outperformed the classic ADC model.
•
In affected GM T
2
values were increased, diffusion was more hindered or restricted.
•
For the first time an estimate of the restricted compartment radius was provided.
•
The radius may reflect vacuole size, which is a key discriminator of sCJD subtypes. AbstractIn clinical practice signal hyperintensity in the cortex and/or in the striatum on magnetic resonance (MR) diffusion-weighted images (DWIs) is a marker of sporadic Creutzfeldt–Jakob Disease (sCJD). MR diagnostic accuracy is greater than 90%, but the biophysical mechanisms underpinning the signal abnormality are unknown. The aim of this prospective study is to combine an advanced DWI protocol with new mathematical models of the microstructural changes occurring in prion disease patients to investigate the cause of MR signal alterations. This underpins the later development of more sensitive and specific image-based biomarkers. DWI data with a wide a range of echo times and diffusion weightings were acquired in 15 patients with suspected diagnosis of prion disease and in 4 healthy age-matched subjects. Clinical diagnosis of sCJD was made in nine patients, genetic CJD in one, rapidly progressive encephalopathy in three, and Gerstmann–Sträussler–Scheinker syndrome in two. Data were analysed with two bi-compartment models that represent different hypotheses about the histopathological alterations responsible for the DWI signal hyperintensity. A ROI-based analysis was performed in 13 grey matter areas located in affected and apparently unaffected regions from patients and healthy subjects. We provide for the first time non-invasive estimate of the restricted compartment radius, designed to reflect vacuole size, which is a key discriminator of sCJD subtypes. The estimated vacuole size in DWI hyperintense cortex was in the range between 3 and 10 µm that is compatible with neuropathology measurements. In DWI hyperintense grey matter of sCJD patients the two bi-compartment models outperform the classic mono-exponential ADC model. Both new models show that T 2 relaxation times significantly increase, fast and slow diffusivities reduce, and the fraction of the compartment with slow/restricted diffusion increases compared to unaffected grey matter of patients and healthy subjects. Analysis of the raw DWI signal allows us to suggest the following acquisition parameters for optimized detection of CJD lesions: b = 3000 s/mm 2 and TE = 103 ms. In conclusion, these results provide the first in vivo estimate of mean vacuole size, new insight on the mechanisms of DWI signal changes in prionopathies and open the way to designing an optimized acquisition protocol to improve early clinical diagnosis and subtyping of sCJD. In clinical practice signal hyperintensity in the cortex and/or in the striatum on magnetic resonance (MR) diffusion-weighted images (DWIs) is a marker of sporadic Creutzfeldt–Jakob Disease (sCJD). MR diagnostic accuracy is greater than 90%, but the biophysical mechanisms underpinning the signal abnormality are unknown. The aim of this prospective study is to combine an advanced DWI protocol with new mathematical models of the microstructural changes occurring in prion disease patients to investigate the cause of MR signal alterations. This underpins the later development of more sensitive and specific image-based biomarkers. DWI data with a wide a range of echo times and diffusion weightings were acquired in 15 patients with suspected diagnosis of prion disease and in 4 healthy age-matched subjects. Clinical diagnosis of sCJD was made in nine patients, genetic CJD in one, rapidly progressive encephalopathy in three, and Gerstmann–Sträussler–Scheinker syndrome in two. Data were analysed with two bi-compartment models that represent different hypotheses about the histopathological alterations responsible for the DWI signal hyperintensity. A ROI-based analysis was performed in 13 grey matter areas located in affected and apparently unaffected regions from patients and healthy subjects. We provide for the first time non-invasive estimate of the restricted compartment radius, designed to reflect vacuole size, which is a key discriminator of sCJD subtypes. The estimated vacuole size in DWI hyperintense cortex was in the range between 3 and 10 µm that is compatible with neuropathology measurements. In DWI hyperintense grey matter of sCJD patients the two bi-compartment models outperform the classic mono-exponential ADC model. Both new models show that T2 relaxation times significantly increase, fast and slow diffusivities reduce, and the fraction of the compartment with slow/restricted diffusion increases compared to unaffected grey matter of patients and healthy subjects. Analysis of the raw DWI signal allows us to suggest the following acquisition parameters for optimized detection of CJD lesions: b = 3000 s/mm2 and TE = 103 ms. In conclusion, these results provide the first in vivo estimate of mean vacuole size, new insight on the mechanisms of DWI signal changes in prionopathies and open the way to designing an optimized acquisition protocol to improve early clinical diagnosis and subtyping of sCJD. •An advanced DWI acquisition scheme was applied to 15 patients with suspected sCJD.•Data fitting with two bi-compartment models outperformed the classic ADC model.•In affected GM T2 values were increased, diffusion was more hindered or restricted.•For the first time an estimate of the restricted compartment radius was provided.•The radius may reflect vacuole size, which is a key discriminator of sCJD subtypes. [Display omitted] In clinical practice signal hyperintensity in the cortex and/or in the striatum on magnetic resonance (MR) diffusion-weighted images (DWIs) is a marker of sporadic Creutzfeldt-Jakob Disease (sCJD). MR diagnostic accuracy is greater than 90%, but the biophysical mechanisms underpinning the signal abnormality are unknown. The aim of this prospective study is to combine an advanced DWI protocol with new mathematical models of the microstructural changes occurring in prion disease patients to investigate the cause of MR signal alterations. This underpins the later development of more sensitive and specific image-based biomarkers. DWI data with a wide a range of echo times and diffusion weightings were acquired in 15 patients with suspected diagnosis of prion disease and in 4 healthy age-matched subjects. Clinical diagnosis of sCJD was made in nine patients, genetic CJD in one, rapidly progressive encephalopathy in three, and Gerstmann-Sträussler-Scheinker syndrome in two. Data were analysed with two bi-compartment models that represent different hypotheses about the histopathological alterations responsible for the DWI signal hyperintensity. A ROI-based analysis was performed in 13 grey matter areas located in affected and apparently unaffected regions from patients and healthy subjects. We provide for the first time non-invasive estimate of the restricted compartment radius, designed to reflect vacuole size, which is a key discriminator of sCJD subtypes. The estimated vacuole size in DWI hyperintense cortex was in the range between 3 and 10 µm that is compatible with neuropathology measurements. In DWI hyperintense grey matter of sCJD patients the two bi-compartment models outperform the classic mono-exponential ADC model. Both new models show that T2 relaxation times significantly increase, fast and slow diffusivities reduce, and the fraction of the compartment with slow/restricted diffusion increases compared to unaffected grey matter of patients and healthy subjects. Analysis of the raw DWI signal allows us to suggest the following acquisition parameters for optimized detection of CJD lesions: b = 3000 s/mm(2) and TE = 103 ms. In conclusion, these results provide the first in vivo estimate of mean vacuole size, new insight on the mechanisms of DWI signal changes in prionopathies and open the way to designing an optimized acquisition protocol to improve early clinical diagnosis and subtyping of sCJD.In clinical practice signal hyperintensity in the cortex and/or in the striatum on magnetic resonance (MR) diffusion-weighted images (DWIs) is a marker of sporadic Creutzfeldt-Jakob Disease (sCJD). MR diagnostic accuracy is greater than 90%, but the biophysical mechanisms underpinning the signal abnormality are unknown. The aim of this prospective study is to combine an advanced DWI protocol with new mathematical models of the microstructural changes occurring in prion disease patients to investigate the cause of MR signal alterations. This underpins the later development of more sensitive and specific image-based biomarkers. DWI data with a wide a range of echo times and diffusion weightings were acquired in 15 patients with suspected diagnosis of prion disease and in 4 healthy age-matched subjects. Clinical diagnosis of sCJD was made in nine patients, genetic CJD in one, rapidly progressive encephalopathy in three, and Gerstmann-Sträussler-Scheinker syndrome in two. Data were analysed with two bi-compartment models that represent different hypotheses about the histopathological alterations responsible for the DWI signal hyperintensity. A ROI-based analysis was performed in 13 grey matter areas located in affected and apparently unaffected regions from patients and healthy subjects. We provide for the first time non-invasive estimate of the restricted compartment radius, designed to reflect vacuole size, which is a key discriminator of sCJD subtypes. The estimated vacuole size in DWI hyperintense cortex was in the range between 3 and 10 µm that is compatible with neuropathology measurements. In DWI hyperintense grey matter of sCJD patients the two bi-compartment models outperform the classic mono-exponential ADC model. Both new models show that T2 relaxation times significantly increase, fast and slow diffusivities reduce, and the fraction of the compartment with slow/restricted diffusion increases compared to unaffected grey matter of patients and healthy subjects. Analysis of the raw DWI signal allows us to suggest the following acquisition parameters for optimized detection of CJD lesions: b = 3000 s/mm(2) and TE = 103 ms. In conclusion, these results provide the first in vivo estimate of mean vacuole size, new insight on the mechanisms of DWI signal changes in prionopathies and open the way to designing an optimized acquisition protocol to improve early clinical diagnosis and subtyping of sCJD. In clinical practice signal hyperintensity in the cortex and/or in the striatum on magnetic resonance (MR) diffusion-weighted images (DWIs) is a marker of sporadic Creutzfeldt-Jakob Disease (sCJD). MR diagnostic accuracy is greater than 90%, but the biophysical mechanisms underpinning the signal abnormality are unknown. The aim of this prospective study is to combine an advanced DWI protocol with new mathematical models of the microstructural changes occurring in prion disease patients to investigate the cause of MR signal alterations. This underpins the later development of more sensitive and specific image-based biomarkers. DWI data with a wide a range of echo times and diffusion weightings were acquired in 15 patients with suspected diagnosis of prion disease and in 4 healthy age-matched subjects. Clinical diagnosis of sCJD was made in nine patients, genetic CJD in one, rapidly progressive encephalopathy in three, and Gerstmann-Sträussler-Scheinker syndrome in two. Data were analysed with two bi-compartment models that represent different hypotheses about the histopathological alterations responsible for the DWI signal hyperintensity. A ROI-based analysis was performed in 13 grey matter areas located in affected and apparently unaffected regions from patients and healthy subjects. We provide for the first time non-invasive estimate of the restricted compartment radius, designed to reflect vacuole size, which is a key discriminator of sCJD subtypes. The estimated vacuole size in DWI hyperintense cortex was in the range between 3 and 10 µm that is compatible with neuropathology measurements. In DWI hyperintense grey matter of sCJD patients the two bi-compartment models outperform the classic mono-exponential ADC model. Both new models show that T2 relaxation times significantly increase, fast and slow diffusivities reduce, and the fraction of the compartment with slow/restricted diffusion increases compared to unaffected grey matter of patients and healthy subjects. Analysis of the raw DWI signal allows us to suggest the following acquisition parameters for optimized detection of CJD lesions: b = 3000 s/mm(2) and TE = 103 ms. In conclusion, these results provide the first in vivo estimate of mean vacuole size, new insight on the mechanisms of DWI signal changes in prionopathies and open the way to designing an optimized acquisition protocol to improve early clinical diagnosis and subtyping of sCJD. In clinical practice signal hyperintensity in the cortex and/or in the striatum on magnetic resonance (MR) diffusion-weighted images (DWIs) is a marker of sporadic Creutzfeldt–Jakob Disease (sCJD). MR diagnostic accuracy is greater than 90%, but the biophysical mechanisms underpinning the signal abnormality are unknown. The aim of this prospective study is to combine an advanced DWI protocol with new mathematical models of the microstructural changes occurring in prion disease patients to investigate the cause of MR signal alterations. This underpins the later development of more sensitive and specific image-based biomarkers. DWI data with a wide a range of echo times and diffusion weightings were acquired in 15 patients with suspected diagnosis of prion disease and in 4 healthy age-matched subjects. Clinical diagnosis of sCJD was made in nine patients, genetic CJD in one, rapidly progressive encephalopathy in three, and Gerstmann–Sträussler–Scheinker syndrome in two. Data were analysed with two bi-compartment models that represent different hypotheses about the histopathological alterations responsible for the DWI signal hyperintensity. A ROI-based analysis was performed in 13 grey matter areas located in affected and apparently unaffected regions from patients and healthy subjects. We provide for the first time non-invasive estimate of the restricted compartment radius, designed to reflect vacuole size, which is a key discriminator of sCJD subtypes. The estimated vacuole size in DWI hyperintense cortex was in the range between 3 and 10 µm that is compatible with neuropathology measurements. In DWI hyperintense grey matter of sCJD patients the two bi-compartment models outperform the classic mono-exponential ADC model. Both new models show that T2 relaxation times significantly increase, fast and slow diffusivities reduce, and the fraction of the compartment with slow/restricted diffusion increases compared to unaffected grey matter of patients and healthy subjects. Analysis of the raw DWI signal allows us to suggest the following acquisition parameters for optimized detection of CJD lesions: b = 3000 s/mm2 and TE = 103 ms. In conclusion, these results provide the first in vivo estimate of mean vacuole size, new insight on the mechanisms of DWI signal changes in prionopathies and open the way to designing an optimized acquisition protocol to improve early clinical diagnosis and subtyping of sCJD. |
Author | Figini, Matteo Grisoli, Marina Bizzi, Alberto Tagliavini, Fabrizio Alexander, Daniel C. Fasano, Fabrizio Gambetti, Pierluigi Baselli, Giuseppe Redaelli, Veronica |
AuthorAffiliation | b Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy c Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom d Neuropathology, Fondazione IRCCS Istituto Neurologico, Parma, Italy g Neuroradiology, Humanitas Research Hospital IRCCS, Rozzano, Milano, Italy e Department of Neuroscience, Università degli Studi di Parma, Parma, Italy a Neuroradiology, Fondazione IRCCS Istituto Neurologico “Carlo Besta”, Milano, Italy f National Prion Disease Pathology Surveillance Center, Department of Pathology, Case Western Reserve University, Cleveland, OH, USA |
AuthorAffiliation_xml | – name: d Neuropathology, Fondazione IRCCS Istituto Neurologico, Parma, Italy – name: f National Prion Disease Pathology Surveillance Center, Department of Pathology, Case Western Reserve University, Cleveland, OH, USA – name: b Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy – name: c Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom – name: e Department of Neuroscience, Università degli Studi di Parma, Parma, Italy – name: a Neuroradiology, Fondazione IRCCS Istituto Neurologico “Carlo Besta”, Milano, Italy – name: g Neuroradiology, Humanitas Research Hospital IRCCS, Rozzano, Milano, Italy |
Author_xml | – sequence: 1 givenname: Matteo surname: Figini fullname: Figini, Matteo organization: Neuroradiology, Fondazione IRCCS Istituto Neurologico “Carlo Besta”, Milano, Italy – sequence: 2 givenname: Daniel C. surname: Alexander fullname: Alexander, Daniel C. organization: Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom – sequence: 3 givenname: Veronica surname: Redaelli fullname: Redaelli, Veronica organization: Neuropathology, Fondazione IRCCS Istituto Neurologico, Parma, Italy – sequence: 4 givenname: Fabrizio surname: Fasano fullname: Fasano, Fabrizio organization: Department of Neuroscience, Università degli Studi di Parma, Parma, Italy – sequence: 5 givenname: Marina surname: Grisoli fullname: Grisoli, Marina organization: Neuroradiology, Fondazione IRCCS Istituto Neurologico “Carlo Besta”, Milano, Italy – sequence: 6 givenname: Giuseppe surname: Baselli fullname: Baselli, Giuseppe organization: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy – sequence: 7 givenname: Pierluigi surname: Gambetti fullname: Gambetti, Pierluigi organization: National Prion Disease Pathology Surveillance Center, Department of Pathology, Case Western Reserve University, Cleveland, OH, USA – sequence: 8 givenname: Fabrizio surname: Tagliavini fullname: Tagliavini, Fabrizio organization: Neuropathology, Fondazione IRCCS Istituto Neurologico, Parma, Italy – sequence: 9 givenname: Alberto surname: Bizzi fullname: Bizzi, Alberto email: alberto.bizzi@humanitas.it organization: Neuroradiology, Humanitas Research Hospital IRCCS, Rozzano, Milano, Italy |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/25610776$$D View this record in MEDLINE/PubMed |
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Keywords | ADC Prion disease MPRAGE PrPSc Biophysical models CNR EEG GSS RPE SS-SE FOV ROI TE PrPC TI Spongiform degeneration DWI Diffusion MRI CJD BIC Creutzfeldt–Jakob disease TR EPI sCJD inversion time diffusion weighted imaging PrP C PrP Sc contrast to noise ratio sporadic Creutzfeldt–Jakob disease apparent diffusion coefficient magnetization-prepared rapid acquisition gradient-echo prion protein scrapie echo time rapidly progressive encephalopathy Gerstmann–Sträussler–Scheinker syndrome single shot spin-echo repetition time field of view electroencephalogram region of interest echo-planar imaging prion protein cellular Bayesian information criterion PrPC, prion protein cellular FOV, field of view TR, repetition time DWI, diffusion weighted imaging EEG, electroencephalogram CJD, Creutzfeldt–Jakob disease RPE, rapidly progressive encephalopathy ADC, apparent diffusion coefficient ROI, region of interest CNR, contrast to noise ratio sCJD, sporadic Creutzfeldt–Jakob disease TE, echo time GSS, Gerstmann–Sträussler–Scheinker syndrome SS-SE, single shot spin-echo BIC, Bayesian information criterion EPI, echo-planar imaging PrPSc, prion protein scrapie MPRAGE, magnetization-prepared rapid acquisition gradient-echo TI, inversion time |
Language | English |
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Snippet | In clinical practice signal hyperintensity in the cortex and/or in the striatum on magnetic resonance (MR) diffusion-weighted images (DWIs) is a marker of... AbstractIn clinical practice signal hyperintensity in the cortex and/or in the striatum on magnetic resonance (MR) diffusion-weighted images (DWIs) is a marker... |
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SubjectTerms | Adult Aged Aged, 80 and over Biophysical models Brain - pathology Brain Mapping - methods Creutzfeldt–Jakob disease Diffusion Magnetic Resonance Imaging Diffusion MRI Female Humans Image Interpretation, Computer-Assisted - methods Male Middle Aged Models, Theoretical Prion disease Prion Diseases - pathology Radiology Regular Spongiform degeneration |
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Title | Mathematical models for the diffusion magnetic resonance signal abnormality in patients with prion diseases |
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