Neuroimagen estructural demencias

NEUROIMAGEN ESTRUCTURAL EN
DEMENCIAS
IGNACIO RUEDA MEDINA

NEUROIMAGEN ESTRUCTURAL EN DEMENCIAS
¿DE QUÉ HERRAMIENTAS DISPONEMOS?
¿QUÉ VEMOS?
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RECUERDO ANATÓMICO – RMN CEREBRAL
IMAIOS
2019

ESCALAS VISUALES
NEUROIMAGEN ESTRUCTURAL

ESCALAS VISUALES ATROFIA - NEUROIMAGEN EN DEMENCIAS
ScaleO’Don
Increments4
DisplayT1-we
ReliabilityInter:
Aspartofstudytolook
lishedvisualratingscales
dementiawithLewybodi
opedaratingscaletoasse
markerofGCA.Eachh
enlargementofthelateral
getanoverallvalue.VEn
higherinpatientswithAD
(p<0.003)butsimilarbe
Sensitivityandspecificityo
was94%and40%,respe
versusDLB.
OverviewofGCAscales
Axialslicesprovidethebe
however,specifyingregion
large,generalisedareaisc
ducesexcellentreliability;
estimatesindicatethescale
diagnosis,perhapsduetot
larsizewithinthehealthy
thePasquierscaleismore
thiscomesattheexpense
confoundedbytheinclus
volumeeffects.Simplificati
moregeneralimpression
(figure1)resultedinincrea
munity(table1);however,
acomponentpartofalarg
thelargebrainareaassesse
moreseverelyconfounded
scales,althoughtheirdia
usingage-specificcut-offs.1
VISUALRATINGOFFRON
ScaleDavies(2013)/Kip
Increments5
DisplayT1-weightedcoron
Reliability:Inter/intra:0.62/0
0.64/0.79(posteri
Daviesetal16
devisedas
schemeusedtorateatrop
formedatthelevelofthe
geniculatenucleus,andt
overall(figure2).Thesca
ofpatientsclinicallydiagn
(bvFTD),basedonthe
atrophyscoreshavebetter
Favourableprognosiswas
pendently3yearsafterd
definedasthosewhohad
withinthesametimepe
favourableprognosisw
Discriminantanalysisalso
Table 1 Reliability measures and imaging parameters
Scale Brain region
Scale
increments Imaging plane MR contrast
Reliability*
Citations
Applications
InterRater IntraRater Research Trials Multicentre
Pasquier et al12
Global cortical 4 Axial T2-weighted
FLAIR
>0.6 (Cwκ)12
>0.7 (Cwκ)12
44 35 Y6
Y7
O’Donovan et al13
Ventricular enlargement 4 Axial T1-weighted 0.9 (ICC) 0.92 (ICC) 1 0 N N
Davies et al16
/Kipps et al17
Frontotemporal 5 Coronal T1-weighted >0.7/0.62–0.71 (Cκ) 0.8/0.79–0.83 (Cκ) 90/60 9 N N
Davies et al18
Frontotemporal 5 Coronal T1-weighted 0.71 (Cwκ) 0.75 (Cwκ) 31 3 N N
Ambikairajah et al21
Frontotemporal 5 Coronal T1-weighted 0.91 (Uκ) Not reported 0 0 N N
Chow et al22
Frontotemporal 5 Coronal
Axial
Sagittal
T1-weighted LAC 0.06 and 0.07
LAT 0.2 (kw)
Not reported 0 0 N N
De Leon et al23 24
Medial temporal 4 Axial T1-weighted 0.72 (Uκ)† Not reported 213 0 N N
Scheltens et al29
Medial temporal 5 Coronal T1-weighted 0.72–0.84 (Cwκ)29
0.83–0.94 (Cwκ)29
350 100+ Y8
Y7
Galton et al32
Medial temporal 4‡ Coronal T1-weighted 0.36–0.49 (Fκ)‡ 0.8 (Cκ) 100 13 N N
Urs et al33
/Duara et al34
Medial temporal 5 Coronal T1-weighted 0.75–0.94 (Uκ) 0.84–0.93 (Uκ) 21/59 12 Y9
Y10
Kaneko et al35
Medial temporal 4 Coronal STIR 0.68 (Uκ) 0.79 (Uκ) 0 0 N N
Kim et al36
Medial temporal 5 Axial T1-weighted 0.64 (Uκ) 0.62/0.95 (Uκ) 1 1 N N
Koedam et al38
Posterior 4 Coronal Axial Sagittal T1-weighted FLAIR 0.65–0.84 (Cwκ) 0.93/0.95 (Cwκ) 19 5 N N
*Highest reported values—citation listed if the value is not taken from the original paper.
†Based on CT images.
‡Novel aspect only.
Cwκ, Cohen’s weighted κ; Cκ, Cohen’s κ; Fκ, Fleiss’ κ; ICC, interclass correlation coefficient; KW, Kendall’s W; STIR, short TI inversion time; Uκ, unspecified κ; N, no; Y, yes.
1226HarperL,etal.JNeurolNeurosurgPsychiatry2015
Davies et al18
later developed a more extensive scale
included 15 frontotemporal brain regions contained with
landmark identifiable slices. Specific scale criteria were a
in the basal ganglia and hippocampal region (anterior, m
terior), and the best slice was determined individually f
hemisphere to account for variation in brain orientatio
scale is intended for use in diagnosis and localisation of f
in neurodegenerative diseases and other postoperative o
encephalitic brain abnormalities. Discriminant analysis in
rating of the anterior fusiform distinguished SD from co
while the insula was vital to distinguishing bvFTD. M
regions were reported to be relevant in discriminating A
controls (insula, anterior hippocampus, orbitofrontal g
temporal pole), perhaps reflecting the more diffuse pat
atrophy associated with AD. In a subsequent study, Hor
et al19
reported rating of the orbitofrontal cortex (OF
good discriminator between AD and bvFTD, with
regression analysis demonstrating correct classification in
of patients. Devenney et al20
also used the scale to demo
a lack of atrophy in C9ORF72 mutation carriers.
Scale Ambikairajah et
Increments 5
Display T1-weighted cor
Reliability Inter: 0.91 (unkn
adapted the Davies/Kipps scales16
applied it to patients on an amyotrophic lateral-scleros
continuum.21
They scored four regions: OFC, anterior ci
Harper L, et al. J Neurol Neurosurg Psychiatry 2015;86:1225–1233. doi:10

MEDIAL TEMPORAL LOBE ATROPHY (MTA)
Scheltens scale
■ Ambos temporales – Si asimetría el
de mayor puntuación
■ Evaluación:
– Anchura de cisura coroidea
– Anchura asta temporal
– Altura hipocampo
■ 0-1: No EA
■ 2-4: EA
Figure 3 Example of the five-step
Scheltens scale for medial temporal
atrophy (images from The Radiology
Assistant website—http://www.
radiologyassistant.nl).
Neurodegeneration
JNeurolNeurosurgPsychiatry:firstpublishedas10.1136
Scale Davies et al18
Increments 5
Display T1-weighted coronal
Reliability Inter: 0.71, intra: 0.76 (Cohen’s weighted κ)
Davies et al18
later developed a more extensive scale, which
included 15 frontotemporal brain regions contained within fou
landmark identifiable slices. Specific scale criteria were adopted
in the basal ganglia and hippocampal region (anterior, mid, pos
terior), and the best slice was determined individually for each
hemisphere to account for variation in brain orientation. Th
scale is intended for use in diagnosis and localisation of function
in neurodegenerative diseases and other postoperative or post
encephalitic brain abnormalities. Discriminant analysis indicated
rating of the anterior fusiform distinguished SD from controls
while the insula was vital to distinguishing bvFTD. Multipl
regions were reported to be relevant in discriminating AD from
controls (insula, anterior hippocampus, orbitofrontal gyri and
temporal pole), perhaps reflecting the more diffuse pattern o
atrophy associated with AD. In a subsequent study, Hornberge
et al19
reported rating of the orbitofrontal cortex (OFC) as
good discriminator between AD and bvFTD, with logisti
regression analysis demonstrating correct classification in 71.3%
also used the scale to demonstrat
Scale Ambikairajah et al21
Increments 5
Reliability Inter: 0.91 (unknown κ)
adapted the Davies/Kipps scales16–18
and
applied it to patients on an amyotrophic lateral-sclerosis-FTD
continuum.21
They scored four regions: OFC, anterior cingulat
Harper L, et al. J Neurol Neurosurg Psychiatry 2015;86:1225–1233. doi:10.1136/jn
Materials and methods
The study has been executed in accordance with the principles
Imaging data and visual rating
using either a 1.5- or 3-T MRI, in
weighted gradient echo sequence
Table 1 Details on visual rating
scales of MTA, Koedam score,
CGA, and WMH used in this
study
MTA [14]
Scale rated on coronal T1 images:
Koedam sco
Scale rated i
FLAIR im
0 = normal 0 = no atr
1 = widened choroid fissure 1 = mild
2 = increase of widened fissure, widening of temporal horn,
opening of other sulci
2 = mode
3 = pronounced volume loss of hippocampus 3 = sever
4 = end-stage atrophy
GCA [15]
Scale rated on axial FLAIR images:
WMH [9–11
Scale rated
0 = no atrophy 0 = none
1 = mild atrophy, opening of sulci 1 = multi
2 = moderate atrophy, volume loss of gyri 2 = begin
3 = severe atrophy; knife blade 3 = large
MTA = medial temporal lobe atrophy, GCA = global cortical atrophy, WMH =
Eur Radiol
NEURO
Automatically computed rating scales from MRI for patients
with cognitive disorders
Juha R. Koikkalainen1
& Hanneke F. M. Rhodius-Meester2
& Kristian S. Frederiksen3
& Marie Bruun3
&
3 4 4 5,6 6 6
European Radiology
https://doi.org/10.1007/s00330-019-06067-1
NEURO
& Marie Bruun3
&
Steen G. Hasselbalch3
& Marta Baroni4
& Patrizia Mecocci4
& Ritva Vanninen5,6
& Anne Remes6
& Hilkka Soininen6
&
Mark van Gils7
& Wiesje M. van der Flier2,8
& Philip Scheltens2
& Frederik Barkhof2,9,10
& Timo Erkinjuntti11
&
Jyrki M. P. Lötjönen1
& for the Alzheimer’s Disease Neuroimaging Initiative
Received: 13 September 2018 /Revised: 9 January 2019 /Accepted: 4 February 2019
# European Society of Radiology 2019
European Radiology
https://doi.org/10.1007/s00330-019-06067-1

GLOBAL CORTICAL ATROPHY (GCA Scale)
■ Evaluación: 13 regiones cerebrales de
ambos hemisferios:
– Frontal, temporal, parieto-occipital y
relación tamaño ventricular
Figure 1 Example of the four-step (generalised) Pasquier scale for global cortical atrophy.
Neurodegeneration
JNeurolNeurosurgPsychiatry:firstpublish
Scale Davies et al18
Increments 5
Davies et al18
included 15 frontotemporal brain regions contained within four
in the basal ganglia and hippocampal region (anterior, mid, pos-
hemisphere to account for variation in brain orientation. The
in neurodegenerative diseases and other postoperative or post-
rating of the anterior fusiform distinguished SD from controls,
while the insula was vital to distinguishing bvFTD. Multiple
temporal pole), perhaps reflecting the more diffuse pattern of
atrophy associated with AD. In a subsequent study, Hornberger
et al19
reported rating of the orbitofrontal cortex (OFC) as a
good discriminator between AD and bvFTD, with logistic
also used the scale to demonstrate
Increments 5
and
continuum.21
They scored four regions: OFC, anterior cingulate
to be 83.6% for bvFTD versus ALS and 75% f
versus ALS. No significant differences in atrophy
found between patients with ALS-FTD and bvFTD
classification calculated as 78.8% between these two
Scale Chow et al22
Increments 5
Display T1-weighted axial, sagittal and
Reliability Inter: 0.06–0.07 (LAC), 0.2 (LAT
Based on previous findings from volumetric an
et al22
adapted the five-point scale of Davies et a
atrophy in the left anterior cingulate (LAC) and
temporal (LAT) regions. Rating was performed on
axial slices, 2 sagittal slices, 1 coronal slice) by fou
scale was applied to a study population of normal
participants and participants with a clinical diagn
(FTD diagnosis was not further categorised). Rater
to give a diagnosis immediately after rating. Based
diagnosis, raters averaged 63% accuracy in correctly
ing AD from FTD and 59.5% accuracy in disting
from controls.
Overview of frontotemporal atrophy scales
Frontotemporal atrophy scales may be useful in th
diagnosis of FTD syndromes, and the scales devel
these regions have been designed and validated sp
this purpose. In particular, the Davies, Kipps and
scales all stem from the same postmortem staging
viding a reliable basis for region selection. Furth
selection is described in detail and reference imag
which probably contributes to the consistently hi
among these scales (table 1). From a usability persp
ence images may be more useful when the ROI is
with a bounding box as in the Ambikairajah study.
Harper L, et al. J Neurol Neurosurg Psychiatry 2015;86:1225–1233. doi:10.1136/jnnp-2014-310090
Materials and methods
The study has been executed in accordance with the principles
of the Declaration of Helsinki. Written informed consent was
obtained from all participants.
Subjects
Imaging data and v
using either a 1.5- or
weighted gradient ech
version recovery (FL
FLAIR images. Image
used (see more details
between 0.4–1.6 × 0.4
1.3 × 0.4–1.3 × 0.6–7.
1 = widened choroid fissure
2 = increase of widened fissure, widening of temporal horn,
opening of other sulci
3 = pronounced volume loss of hippocampus
4 = end-stage atrophy
GCA [15]
0 = no atrophy
1 = mild atrophy, opening of sulci
2 = moderate atrophy, volume loss of gyri
3 = severe atrophy; knife blade
MTA = medial temporal lobe atrophy, GCA = global cortical atro
NEURO
& Marie Bruun3
&
& Marta Baroni4
& Patrizia Mecocci4
& Ritva Vanninen5,6
& Anne Remes6
& Hilkka Soininen6
&
Mark van Gils7
& Philip Scheltens2
&
Abstract
Objectives The aims of this study were to examine whether visual MRI rating scales used in diagnostics of cognitive disorders can
be estimated computationally and to compare the visual rating scales with their computed counterparts in differential diagnostics.
Methods A set of volumetry and voxel-based morphometry imaging biomarkers was extracted from T1-weighted and FLAIR
images. A regression model was developed for estimating visual rating scale values from a combination of imaging biomarkers.
We studied three visual rating scales: medial temporal lobe atrophy (MTA), global cortical atrophy (GCA), and white matter
hyperintensities (WMHs) measured by the Fazekas scale. Images and visual ratings from the Amsterdam Dementia Cohort
(ADC) (N = 513) were used to develop the models and cross-validate them. The PredictND (N = 672) and ADNI (N = 752)
cohorts were used for independent validation to test generalizability.
Results The correlation coefficients between visual and computed rating scale values were 0.83/0.78 (MTA-left), 0.83/0.79
(MTA-right), 0.64/0.64 (GCA), and 0.76/0.75 (Fazekas) in ADC/PredictND cohorts. When performance in differential diagnos-
tics was studied for the main types of dementia, the highest balanced accuracy, 0.75–0.86, was observed for separating different
dementias from cognitively normal subjects using computed GCA. The lowest accuracy of about 0.5 for all the visual and
Data used in the preparation of this article were obtained from the
Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.
loni.usc.edu). As such, the investigators within the ADNI contributed to
the design and implementation of ADNI and/or provided data but did not
participate in the analysis or writing of this report. A complete listing of
ADNI investigators can be found at: https://adni.loni.usc.edu/wp-content/
uploads/how_to_apply/ADNI_Acknowledgement_List.pdf.
European Radiology
https://doi.org/10.1007/s00330-019-06067-1
NEURO
& Marie Bruun3
&
& Marta Baroni4
& Patrizia Mecocci4
& Ritva Vanninen5,6
& Anne Remes6
& Hilkka S
Mark van Gils7
& Philip Scheltens2
& Timo Erkinjuntti
Abstract
Objectives The aims of this study were to examine whether visual MRI rating scales used in diagnostics of cogniti
be estimated computationally and to compare the visual rating scales with their computed counterparts in differen
Methods A set of volumetry and voxel-based morphometry imaging biomarkers was extracted from T1-weigh
images. A regression model was developed for estimating visual rating scale values from a combination of imag
We studied three visual rating scales: medial temporal lobe atrophy (MTA), global cortical atrophy (GCA), a
hyperintensities (WMHs) measured by the Fazekas scale. Images and visual ratings from the Amsterdam D
(ADC) (N = 513) were used to develop the models and cross-validate them. The PredictND (N = 672) and A
Results The correlation coefficients between visual and computed rating scale values were 0.83/0.78 (MTA
(MTA-right), 0.64/0.64 (GCA), and 0.76/0.75 (Fazekas) in ADC/PredictND cohorts. When performance in diffe
tics was studied for the main types of dementia, the highest balanced accuracy, 0.75–0.86, was observed for sep
dementias from cognitively normal subjects using computed GCA. The lowest accuracy of about 0.5 for al
European Radiology
https://doi.org/10.1007/s00330-019-06067-1

ATROPHY POSTERIOR
Koedam Score
NEURO
& Marie Bruun3
&
& Marta Baroni4
& Patrizia Mecocci4
& Ritva Vanninen5,6
& Anne Remes6
& Hilkka Soininen6
&
Mark van Gils7
& Philip Scheltens2
&
Abstract
European Radiology
https://doi.org/10.1007/s00330-019-06067-1
■ Evalúa:
– Surcos cigulado posterior,
precúneo, parieto-occipital
– Cortex parietal
■ Ambos hemisferios
■ Mayor puntuación obtenida para
un área
data and visual ratings The subjects were scanned
Koedam score [8]
Scale rated in sagittal and coronal T1 and axial
FLAIR images:
0 = no atrophy
1 = mild atrophy, opening of sulci
poral horn, 2 = moderate atrophy, volume loss of gyri
3 = severe atrophy; knife blade
WMH [9–11]
0 = none or single (max 3) punctate lesions
1 = multiple (≥ 3) punctate lesions
2 = beginning confluence of lesions
3 = large confluent lesions
l cortical atrophy, WMH = white matter hyperintensities
NEURO
& Marie Bruun3
&
& Marta Baroni4
& Patrizia Mecocci4
& Ritva Vanninen5,6
& Anne Remes6
& Hilkka Soininen6
&
Mark van Gils7
& Philip Scheltens2
&
Abstract
the design and implementation of ADNI and/or provided data but did not
participate in the analysis or writing of this report. A complete listing of
ADNI investigators can be found at: https://adni.loni.usc.edu/wp-content/
uploads/how_to_apply/ADNI_Acknowledgement_List.pdf.
European Radiology
https://doi.org/10.1007/s00330-019-06067-1
H.-R. Kim et al. / Posterior Atrophy in Mild Cognitive Impairment 139
Journal of Alzheimer’s Disease 55 (2017) 137–146
2
1
3
0

ATROPHY POSTERIOR
(Kipps/Davies Scale)
Increments 5
Davies et al18
included 15 frontotemporal brain regions contained within four
in the basal ganglia and hippocampal region (anterior, mid, pos-
hemisphere to account for variation in brain orientation. The
in neurodegenerative diseases and other postoperative or post-
rating of the anterior fusiform distinguished SD from controls,
while the insula was vital to distinguishing bvFTD. Multiple
temporal pole), perhaps reflecting the more diffuse pattern of
atrophy associated with AD. In a subsequent study, Hornberger
et al19
reported rating of the orbitofrontal cortex (OFC) as a
good discriminator between AD and bvFTD, with logistic
also used the scale to demonstrate
Increments 5
and
continuum.21
They scored four regions: OFC, anterior cingulate
classification calculated as 78.8% between these two groups.
Scale Chow et al22
Increments 5
Display T1-weighted axial, sagittal and coronal
Reliability Inter: 0.06–0.07 (LAC), 0.2 (LAT) (Kendall’s W)
Based on previous findings from volumetric analysis, Chow
et al22
adapted the five-point scale of Davies et al18
to assess
atrophy in the left anterior cingulate (LAC) and left anterior
temporal (LAT) regions. Rating was performed on five slices (2
axial slices, 2 sagittal slices, 1 coronal slice) by four raters. The
scale was applied to a study population of normal controls, AD
participants and participants with a clinical diagnosis of FTD
(FTD diagnosis was not further categorised). Raters were asked
to give a diagnosis immediately after rating. Based on the given
diagnosis, raters averaged 63% accuracy in correctly distinguish-
ing AD from FTD and 59.5% accuracy in distinguishing FTD
from controls.
Overview of frontotemporal atrophy scales
Frontotemporal atrophy scales may be useful in the differential
diagnosis of FTD syndromes, and the scales developed around
these regions have been designed and validated specifically for
this purpose. In particular, the Davies, Kipps and Ambikairajah
scales all stem from the same postmortem staging scheme, pro-
viding a reliable basis for region selection. Furthermore, slice
selection is described in detail and reference images provided,
which probably contributes to the consistently high reliability
among these scales (table 1). From a usability perspective, refer-
ence images may be more useful when the ROI is demarcated
with a bounding box as in the Ambikairajah study. The style of
Harper L, et al. J Neurol Neurosurg Psychiatry 2015;86:1225–1233. doi:10.1136/jnnp-2014-310090 1227
on24January2019byguest.Protectedbycopyright.http://jnnp.bmj.com/015.Downloadedfrom
■ Secuencia: T1 coronal
■ Evaluación:
– Puede evalúa hasta 15 regiones en
3 cortes coronales
rence image provided with the second Davies scale, while
ormative, is perhaps somewhat complicated for use in routine
rating scale values ranged between ϕ-κ values of 0.87–0.89.
Using a study cohort of patients with AD, patients with mild
ure 2 Example of the five-step Kipps/Davies scale for frontal atrophy. The posterior temporal lobe reference images were included in the Kipps
y only.
eurodegeneration
JNeurolNeurosurgPsychiatry:firstpublishedas10.1136/jnnp-2014-310090on14April2015.Download
deviation 7.5). An ANOVA showed a significant age effect
across syndromes (F = 5.2, d.f. = 3, p ! 0.01); post hoc
testing showed the bvFTD group to be significantly
younger than either the PNFA (p ! 0.01) or the SD group
(p ! 0.05), but not the controls. The 2 aphasic groups did
not differ significantly in age from each other or from the
controls. The mean symptom duration to scanning was
not significantly different between the groups (F = 2.1,
d.f. = 3, n.s.).
Frontal
Anterior
temporal
Posterior
temporal
0 1 2 3 4
Fig. 2. Array of prerated reference images and rating criteria for
lobar regions. Frontal lobe (on slice I). Stage 0 = Normal appear-
ances; stage 1 = mild atrophy of orbital or supero-medial frontal
cortex – contour of the basal ganglia in the lateral ventricle is
convex, as in controls, but with some prominence of the lateral
ventricle; stage 2 = definite sulcal widening in any cortical sub-
region or flattened profile to basal ganglia; stage 3 = severer cor-
tical atrophy with clear reduction in white matter and reduced
white-grey matter differentiation – stage 3 basal ganglia have
concave profile; stage 4 = cortex reduced to a ribbon and the
basal ganglia virtually indiscernible. Anterior temporal lobe (on
slice I). Stage 0 = Normal appearances; stage 1 = slight promi-
nence of anterior temporal sulci; stage 2 = temporal sulci def-
initely widened; stage 3 = gyri severely atrophic and ribbon-
like – white and grey matter cannot be distinguished (normal
temporal lobe at this level is less substantial than the frontal lobe,
and so the ribbon-like gyri of the stage 3 temporal lobe are simi-
lar to stage 4 frontal gyri); stage 4 = temporal pole has a simple
linear profile or is not seen at all. Posterior temporal lobe (on slice
II). Stage 0 = normal appearances; stage 1 = slight increased
prominence of the lateral ventricle to form a rim around the an-
terior hippocampus – temporal sulci show mild prominence;
stage 2 = lateral ventricle unarguably dilated with subtle reduc-
tion in hippocampal size – the medial temporal gyri may be
atrophic, and there may be prominence of the temporal sulci;
stage 3 = the hippocampus is small and sits at the medial tip of a
greatly expanded temporal horn – sulci are definitely widened;
stage 4 = hippocampus is extremely small – temporal cortex and
white matter show almost complete atrophy.
Imaging Findings in FTD Variants Dement Geriatr Cogn Disord 2007;23:334–342
deviation 7.5). An ANOVA showed a significant age effect
across syndromes (F = 5.2, d.f. = 3, p ! 0.01); post hoc
testing showed the bvFTD group to be significantly
younger than either the PNFA (p ! 0.01) or the SD group
(p ! 0.05), but not the controls. The 2 aphasic groups did
not differ significantly in age from each
controls. The mean symptom duration
not significantly different between the
d.f. = 3, n.s.).
0 1 2 3 4
Fig. 2. Array of prerated reference images and rating criteria for
lobar regions. Frontal lobe (on slice I). Stage 0 = Normal appear-
ances; stage 1 = mild atrophy of orbital or supero-medial frontal
cortex – contour of the basal ganglia in the lateral ventricle is
convex, as in controls, but with some prominence of the lateral
ventricle; stage 2 = definite sulcal widening in any cortical sub-
region or flattened profile to basal ganglia; stage 3 = severer cor-
tical atrophy with clear reduction in white matter and reduced
white-grey matter differentiation – stage 3 basal ganglia have
concave profile; stage 4 = cortex reduced to a ribbon and the
basal ganglia virtually indiscernible. Anterior temporal lobe (on
slice I). Stage 0 = Normal appearances; stage 1 = slight promi-
nence of anterior temporal sulci; stage 2 = temporal sulci def-
initely widened; stage 3 = gyri severely atrophic and ribbon-
like – white and grey matter cannot be distinguished (normal
temporal lobe at this level is less substantial th
and so the ribbon-like gyri of the stage 3 tem
lar to stage 4 frontal gyri); stage 4 = tempor
linear profile or is not seen at all. Posterior tem
II). Stage 0 = normal appearances; stage 1
prominence of the lateral ventricle to form a
terior hippocampus – temporal sulci show
stage 2 = lateral ventricle unarguably dilated
tion in hippocampal size – the medial tem
atrophic, and there may be prominence of
stage 3 = the hippocampus is small and sits a
greatly expanded temporal horn – sulci are
stage 4 = hippocampus is extremely small – t
white matter show almost complete atrophy.

PUNTOS DE CORTE - ESCALAS ATROFIA CORTICAL
e4 noncarriers’ refers to AD patients with a disease onset
before 65 years of age and who do not carry the ApoE e4
allele
MTA GCA-F PA
Heterogeneous group
45–64 years ≥1.5 ≥1 ≥1
65–74 years ≥1.5 ≥1 ≥1
75–84 years ≥2 ≥1 ≥1
85–94 years ≥2.5 ≥1 ≥1
Early-onset ApoE e4 non-carriers
45–64 years ≥2 ≥1 –
65–74 years ≥2 ≥1 –
75–84 years ≥3 ≥2 –
85–94 years ≥3 ≥2 –
MTA, medial temporal atrophy; GCA-F, frontal lobe
atrophy (from the global cortical atrophy scale); PA,
posterior atrophy; AD, Alzheimer’s disease; ApoE e4,
apolipoprotein E e4 allele.
doi: 10.1111/joim.12358
Practical cut-offs for visual rating scales of medial
temporal, frontal and posterior atrophy in Alzheimer’s
disease and mild cognitive impairment
D. Ferreira1
, L. Cavallin2,3
, E.-M. Larsson4
, J.-S. Muehlboeck1
, P. Mecocci5
, B. Vellas6
, M. Tsolaki7
,
I. Kłoszewska8
, H. Soininen9
, S. Lovestone10
, A. Simmons11,12,13
, L.-O. Wahlund1
, E. Westman1
& for the AddNeuroMed
consortium and the Alzheimer’s Disease Neuroimaging Initiative*
From the 1
Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Clinical Geriatrics; 2
Department
of Clinical Science, Intervention and Technology, Division of Medical Imaging and Technology, Karolinska Institutet; 3
Department of
Radiology, Karolinska University Hospital, Stockholm; 4
Department of Radiology, Oncology and Radiation Science, Uppsala University,
Uppsala, Sweden; 5
Institute of Gerontology and Geriatrics, University of Perugia, Perugia, Italy; 6
INSERM U 558, University of Toulouse,
Toulouse, France; 7
3rd Department of Neurology, Aristoteleion Panepistimeion Thessalonikis, Thessaloniki, Greece; 8
Medical University of
Lodz, Lodz, Poland; 9
University of Eastern Finland, University Hospital of Kuopio, Kuopio, Finland; 10
Department of Psychiatry, Warneford
Hospital, University of Oxford, Oxford; 11
Institute of Psychiatry, King’s College London; 12
NIHR Biomedical Research Centre for Mental
Health; and 13
NIHR Biomedical Research Unit for Dementia, London, UK
Abstract. Ferreira D, Cavallin L, Larsson E-M,
Muehlboeck J-S, Mecocci P, Vellas B, Tsolaki M,
Kloszewska I, Soininen H, Lovestone S, Simmons A,
Wahlund L-O, Westman E; for the AddNeuroMed
consortium and the Alzheimer’s Disease
Neuroimaging Initiative (Karolinska Institutet,
Stockholm; Karolinska Institutet, Stockholm;
Karolinska University Hospital, Stockholm; Uppsala
University, Uppsala, Sweden; Institute of Gerontology
and Geriatrics, University of Perugia, Perugia, Italy;
INSERM U 558, University of Toulouse, Toulouse,
France; Aristoteleion Panepistimeion Thessalonikis,
Thessaloniki,Greece;MedicalUniversityofLodz,Lodz,
Poland; University of Eastern Finland, University
Hospital of Kuopio, Kuopio, Finland; University of
Oxford, Oxford, Institute of Psychiatry, King’s College
London, London; NIHR Biomedical Research Centre
forMentalHealth,London;NIHRBiomedicalResearch
Unit for Dementia, London, UK). Practical cut-offs for
visual rating scales of medial temporal, frontal and
posterior atrophy in Alzheimer’s disease and mild
cognitive impairment. J Intern Med 2015; 278: 277–
290.
Background. Atrophy in the medial temporal lobe,
frontal lobe and posterior cortex can be measured
withvisualratingscalessuchasthemedialtemporal
atrophy (MTA), global cortical atrophy – frontal
subscale (GCA-F) and posterior atrophy (PA) scales,
respectively.However,practicalcut-offsareurgently
needed, especially now that different presentations
of Alzheimer’s disease (AD) are included in the
revised diagnostic criteria.
Aims. The aim of this study was to generate a list of
practical cut-offs for the MTA, GCA-F and PA
scales, for both diagnosis of AD and determining
prognosis in mild cognitive impairment (MCI), and
to evaluate the influence of key demographic and
clinical factors on these cut-offs.
Methods. AddNeuroMed and ADNI cohorts were com-
binedgivinga totalof1147participants(322patients
with AD, 480 patients with MCI and 345 control
subjects). The MTA, GCA-F and PA scales were
applied and a broad range of cut-offs was evaluated.
Results. The MTA scale showed better diagnostic and
predictive performances than the GCA-F and PA
scales. Age, apolipoprotein E (ApoE) e4 status and
age at disease onset influenced all three scales. For
the age ranges 45–64, 65–74, 75–84 and 85–
94 years, the following cut-offs should be used.
MTA: ≥1.5, ≥1.5, ≥2 and ≥2.5; GCA-F, ≥1, ≥1, ≥1
and ≥1; and PA, ≥1, ≥1, ≥1 and ≥1, respectively,
with an adjustment for early-onset ApoE e4 non-
carrier AD patients (MTA: ≥2, ≥2, ≥3 and ≥3; and
GCA-F: ≥1, ≥1, ≥2 and ≥2, respectively).
Conclusions. If successfully validated in clinical set-
tings, the list of practical cut-offs proposed here
might be useful in clinical practice. Their use might
also (i) promote research on atrophy subtypes, (ii)
*Data used in the preparation of this article were obtained from
the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database
(adni.loni.usc.edu). As such, the investigators within the ADNI
contributed to the design and implementation of ADNI and/or
provided data but did not participate in the analysis or writing of
this report. A complete listing of the ADNI investigators can be
found at: http://adni.loni.usc.edu/wp-content/uploads/how_-
to_apply/ADNI_Acknowledgement_List.pdf.
ª 2015 The Association for the Publication of the Journal of Internal Medicine 277
Original Article
Stockholm; Karolinska Institutet, Stockholm;
Karolinska University Hospital, Stockholm; Uppsala
University, Uppsala, Sweden; Institute of Gerontology
and Geriatrics, University of Perugia, Perugia, Italy;
INSERM U 558, University of Toulouse, Toulouse,
France; Aristoteleion Panepistimeion Thessalonikis,
Thessaloniki,Greece;MedicalUniversityofLodz,Lodz,
Poland; University of Eastern Finland, University
Hospital of Kuopio, Kuopio, Finland; University of
Oxford, Oxford, Institute of Psychiatry, King’s College
London, London; NIHR Biomedical Research Centre
forMentalHealth,London;NIHRBiomedicalResearch
Unit for Dementia, London, UK). Practical cut-offs for
visual rating scales of medial temporal, frontal and
posterior atrophy in Alzheimer’s disease and mild
cognitive impairment. J Intern Med 2015; 278: 277–
290.
Background. Atrophy in the medial temporal lobe,
frontal lobe and posterior cortex can be measured
withvisualratingscalessuchasthemedialtemporal
atrophy (MTA), global cortical atrophy – frontal
Aims. The aim of this study was to generate a list of
practical cut-offs for the MTA, GCA-F and PA
scales, for both diagnosis of AD and determining
prognosis in mild cognitive impairment (MCI), and
to evaluate the influence of key demographic and
clinical factors on these cut-offs.
Methods. AddNeuroMed and ADNI cohorts were com-
binedgivinga total of1147participants(322patients
with AD, 480 patients with MCI and 345 control
subjects). The MTA, GCA-F and PA scales were
applied and a broad range of cut-offs was evaluated.
Results. The MTA scale showed better diagnostic and
predictive performances than the GCA-F and PA
scales. Age, apolipoprotein E (ApoE) e4 status and
age at disease onset influenced all three scales. For
the age ranges 45–64, 65–74, 75–84 and 85–
94 years, the following cut-offs should be used.
MTA: ≥1.5, ≥1.5, ≥2 and ≥2.5; GCA-F, ≥1, ≥1, ≥1
and ≥1; and PA, ≥1, ≥1, ≥1 and ≥1, respectively,
with an adjustment for early-onset ApoE e4 non-
carrier AD patients (MTA: ≥2, ≥2, ≥3 and ≥3; and
GCA-F: ≥1, ≥1, ≥2 and ≥2, respectively).
Conclusions. If successfully validated in clinical set-
tings, the list of practical cut-offs proposed here
might be useful in clinical practice. Their use might
also (i) promote research on atrophy subtypes, (ii)
*Data used in the preparation of this article were obtained from
the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database
(adni.loni.usc.edu). As such, the investigators within the ADNI
contributed to the design and implementation of ADNI and/or
provided data but did not participate in the analysis or writing of
this report. A complete listing of the ADNI investigators can be
found at: http://adni.loni.usc.edu/wp-content/uploads/how_-
to_apply/ADNI_Acknowledgement_List.pdf.
ª 2015 The Association for the Publication of the Journal of Internal Medicine 277

LESIONES SUSTANCIA BLANCA
ESCALA FAZEKAS
White matter hyperintensi
impairment and dementia
Niels D. Prins and Philip Scheltens
Abstract | White matter hyperintensities (WMHs) in the brain a
disease, and can easily be detected on MRI. Over the past thre
presence and extent of white matter hyperintense signals on M
of cognitive and functional impairment. Large, longitudinal pop
have confirmed a dose-dependent relationship between WMHs
a causal link between large confluent WMHs and dementia an
assessment and management is of the utmost importance in
incipient cognitive impairment. Novel imaging techniques such
damage before it is visible on standard MRI. Even in Alzheimer
caused by amyloid, vascular pathology, such as small vessel d
amyloid itself in terms of influencing the disease course, espe
factors for small vessel disease could be an important therape
interventions is still lacking. Here, we provide a timely Review
cognitive decline and dementia.
Prins, N. D. & Scheltens, P. Nat. Rev. Neurol. 11, 157–165 (2015); published onl
Introduction
barrier permeab
to leakage of ma
activation.4
Alte
proposed. Aβ de
layers of mening
lead to obstructio
of vascular smoo
cerebral autoregu
implicated in th
genous thickenin
draining veins.71
been attributed t
Given that WM
vessel disease are
recurring questi
AD pathology in
Group of the M
Function and A
no association b
increased burden
people.73
The sam
protein E (APOE
factor for AD, wa
pathology but no
than CAA.74
This
WMHs correlate
carriers but not i
the latter individ
effects of WMHs
WMHs on MR
found to indepe
tracts, as measu
in line with ima
Nature Reviews | Neurology
Fazekas 1 Fazekas 2 Fazekas 3
Figure 2 | Axial fluid-attenuated inversion recovery images illustrating the Fazekas
scores. The scoring system is outlined in Box 1.
REVIEWS

LESIONES SUSTANCIA BLANCA
ESCALA SCHELTENS
White matter hyperintensities, cognitive
impairment and dementia: an update
Niels D. Prins and Philip Scheltens
Abstract | White matter hyperintensities (WMHs) in the brain are the consequence of cerebral small vessel
disease, and can easily be detected on MRI. Over the past three decades, research has shown that the
presence and extent of white matter hyperintense signals on MRI are important for clinical outcome, in terms
of cognitive and functional impairment. Large, longitudinal population-based and hospital-based studies
have confirmed a dose-dependent relationship between WMHs and clinical outcome, and have demonstrated
a causal link between large confluent WMHs and dementia and disability. Adequate differential diagnostic
assessment and management is of the utmost importance in any patient, but most notably those with
incipient cognitive impairment. Novel imaging techniques such as diffusion tensor imaging might reveal subtle
damage before it is visible on standard MRI. Even in Alzheimer disease, which is thought to be primarily
caused by amyloid, vascular pathology, such as small vessel disease, may be of greater importance than
amyloid itself in terms of influencing the disease course, especially in older individuals. Modification of risk
factors for small vessel disease could be an important therapeutic goal, although evidence for effective
interventions is still lacking. Here, we provide a timely Review on WMHs, including their relationship with
cognitive decline and dementia.
Prins, N. D. & Scheltens, P. Nat. Rev. Neurol. 11, 157–165 (2015); published online 17 February 2015; doi:10.1038/nrneurol.2015.10
REVIEWS

PROTOCOLO DE RMN EN DEMENCIAS
NEURODEGENERATIVAS
■ Secuencia T1 axial, sagital y coronal
■ Secuencia FLAIR axial
■ Secuencia spin eco axial
■ Secuencia ecogradiente axial
INFORME RADIOLÓGICO EN ESTUDIO
PROTOCOLIZADO
DE RMN CEREBRAL DEMENCIA
■ Escala MTA con descripción
■ Escala GCA con descripción
■ Tamaño ventricular
■ Escala Fazekas con descripción
■ Localización y tamaño lesiones
vasculares
■ Comparación con estudios previos
– Grado de atrofia
– Carga lesional vascular
■ Otras lesiones asociadas
■ Correlación de hallazgos con clínica y
otras pruebas diagnósticas: LCR O PET
PICTORIAL REVIEW
Imaging biomarkers of dementia: recommended visual rating
scales with teaching cases
Lars-Olof Wahlund1
& Eric Westman1
& Danielle van Westen2,3
& Anders Wallin4
&
Sara Shams5,6
& Lena Cavallin5,6
& Elna-Marie Larsson7
& From the Imaging
Cognitive Impairment Network (ICINET)
Received: 5 May 2016 /Revised: 1 September 2016 /Accepted: 19 September 2016 /Published online: 21 December 2016
# The Author(s) 2016. This article is published with open access at Springerlink.com
Abstract
The diagnostic work up of dementia may benefit from struc-
tured reporting of CT and/or MRI and the use of standardised
visual rating scales. We advocate a more widespread use of
standardised scales as part of the workflow in clinical and
research evaluation of dementia. We propose routine clinical
use of rating scales for medial temporal atrophy (MTA), glob-
al cortical atrophy (GCA) and white matter hyperintensities
(WMH). These scales can be used for evaluation of both CT
and MRI and are efficient in routine imaging assessment in
dementia, and may improve the accuracy of diagnosis. Our
review provides detailed imaging examples of rating
increments in each of these scales and a separate teaching file.
The radiologist should relate visual ratings to the clinical as-
sessment and other biomarkers to assist the clinician in the
diagnostic decision.
Teaching points
• Clinical dementia diagnostics would benefit from structured
radiological reporting.
• Standardised rating scales should be used in dementia
assessment.
• It is important to relate imaging findings to the clinically
suspected diagnosis.
Keywords Dementia .Imaging .Alzheimer’sdisease .MRI .
CT
Introduction
The prevalence of dementia is increasing due to longer life
expectancy, including a large increase of populations aged 80-
years and older. A thorough investigation of suspected demen-
tia and pre-dementia stages is of high importance for early
diagnosis, caretaking and, if possible, treatment. Brain imag-
ing is included among the basic investigations in the work-up
of dementia in many countries. Knowledge on dementia and
particularly Alzheimer’s disease has increased significantly in
recent years, especially with regard to imaging methods and
their impact on differential diagnosis. Nevertheless, this
knowledge has not been fully implemented in clinical radio-
logical routine work, most likely due to lack of communica-
tion between academia and clinical practice. In this paper,we
describe how changes characteristic of common dementia dis-
orders can be assessed in a structured way using computed
tomography (CT) and magnetic resonance imaging (MRI).
Electronic supplementary material The online version of this article
(doi:10.1007/s13244-016-0521-6) contains supplementary material,
which is available to authorized users.
* Sara Shams
sara.shams@ki.se
From the Imaging Cognitive Impairment Network (ICINET)
1
Division of Clinical Geriatrics, Department of Neurobiology, Care
Sciences, and Society, Karolinska Institutet, Stockholm, Sweden
2
Diagnostic Radiology, Clinical Sciences, Lund University,
Lund, Sweden
3
Imaging and Function, Skåne University Hospital, Lund, Sweden
4
Institute of Neuroscience and Physiology, Sahlgrenska Academy at
University of Gothenburg, Gothenburg, Sweden
5
Department of Clinical Science, Intervention, and Technology,
Division of Medical Imaging and Technology, Karolinska Institutet,
Stockholm, Sweden
6
Department of Radiology, Karolinska University Hospital,
SE-14186 Stockholm, Sweden
7
Department of Surgical Sciences, Radiology, Uppsala University,
Uppsala, Sweden
Insights Imaging (2017) 8:79–90
DOI 10.1007/s13244-016-0521-6
PICTORIAL REVIEW
Lars-Olof Wahlund1
& Eric Westman1
& Anders Wallin4
&
Sara Shams5,6
& Lena Cavallin5,6
& From the Imaging
Abstract
Teaching points
assessment.
Keywords Dementia .Imaging .Alzheimer’sdisease .MRI .Electronic supplementary material The online version of this article
DOI 10.1007/s13244-016-0521-6

■ Secuencia T1 axial, sagital y coronal
■ Secuencia FLAIR axial
■ Secuencia spin eco axial
■ Secuencia ecogradiente axial
PICTORIAL REVIEW
Lars-Olof Wahlund1
& Eric Westman1
& Anders Wallin4
&
Sara Shams5,6
& Lena Cavallin5,6
& From the Imaging
Abstract
Teaching points
assessment.
Keywords Dementia .Imaging .Alzheimer’sdisease .MRI .
CT
Introduction
The prevalence of dementia is increasing due to longer life
expectancy, including a large increase of populations aged 80-
Electronic supplementary material The online version of this article
(doi:10.1007/s13244-016-0521-6) contains supplementary material,
which is available to authorized users.
* Sara Shams
sara.shams@ki.se
From the Imaging Cognitive Impairment Network (ICINET)
DOI 10.1007/s13244-016-0521-6
PICTORIAL REVIEW
Lars-Olof Wahlund1
& Eric Westman1
& Anders Wallin4
&
Sara Shams5,6
& Lena Cavallin5,6
& From the Imaging
Abstract
DOI 10.1007/s13244-016-0521-6S14 M. P. Wattjes
Table 1. Example of a multisequence MRI protocol for patients presenting to a memory clinic
3D-T1 with MPR Assessment of the medial temporal lobe on oblique coronal
reconstructions according to the axis of the hippocampus
Axial FLAIR (preferably 3D dataset) Assessment of vascular white matter changes, global and focal
cortical atrophy
Axial T2-(T)SE Assessment of vascular changes in deep gray matter structures
(e.g. lacunar infarctions of the thalamus)
Axial T2∗
-GE Detection of microbleeds and macrohemorrhages
Axial DWI Detection of areas with restricted diffusion (e.g. acute stroke,
Creutzfeld–Jakob disease, Herpes encephalitis)
D = dimensional; DWI = diffusion-weighted imaging; FLAIR = fluid-attenuated inversion recovery; MPR =
multiplanar reconstructions; TSE = turbo spin echo; GE = gradient echo.
Table 2. Overview of the most established visual rating scales for the assessment of
cortical atrophy, hippocampal atrophy (medial temporal lobe atrophy, MTA) and white matter
hyperintensities (WMH)
CORTICAL ATROPHY MTA WMH
PASQUIER SCALE SCHELTENS SCALE FAZEKAS SCALE
.......................................................................................................................................................................................................................................................................................
PROTOCOLO DE RMN EN DEMENCIAS NEURODEGENERATIVAS
International Psychogeriatrics (2011), Vol. 23, Supplement 2, S13–S24 C⃝ International Psychogeriatric Association 2011
doi:10.1017/S1041610211000913
Structural MRI
.........................................................................................................................................................................................................................................................................................................................................................................
Mike P. Wattjes
Alzheimer Center Amsterdam, Department of Radiology, VU University Medical Center, Amsterdam, The Netherlands
ABSTRACT
Clinical neuroimaging is increasingly being used in the diagnosis of neurodegenerative diseases and has become
one of the most important paraclinical tools in the diagnosis of dementia. According to current guidelines,
neuroimaging, preferably magnetic resonance imaging (MRI), should be performed at least once during the
diagnostic work-up of patients with suspected or definite dementia. MRI is helpful in identifying or excluding
potentially treatable causes of dementia; however, these account only for a small proportion of dementias.
In addition, MRI is able to support the clinical diagnosis in a memory clinic setting by identifying certain
patterns of atrophy and vascular damage. Visual rating scales are well-established methods in the clinical
routine for the assessment and quantification of regional/global cortical atrophy, hippocampal atrophy and
vascular damage. In addition, MRI is able to detect certain aspects of pathology associated with dementia,
such as cerebral microbleeds which are related to cerebral amyloid angiopathy and Alzheimer pathology. This
review paper aims to give an overview of the application of structural MRI in the diagnostic procedure for
memory clinic patients in terms of excluding and supporting the diagnosis of various diseases associated with
dementia.
Key words: dementia, neuroimaging, magnetic resonance imaging, Alzheimer’s disease
Introduction
Clinical neuroimaging is increasingly being used in
the diagnostic work-up of patients presenting to a
memory clinic. Structural neuroimaging methods
such as computed tomography (CT) and, more
sensitively, magnetic resonance imaging (MRI)
are well suited to exclude possibly (surgically)
and vascular changes) and has therefore been
established as a valuable method for efficacy and
safety monitoring in clinical treatment trials (Frisoni
et al., 2010). As a consequence, this has led to the
incorporation of clinical neuroimaging into current
diagnostic guidelines of dementia, which state that
neuroimaging should be performed at least once
International Psychogeriatrics (2011), Vol. 23, Supplement 2, S13–S24 C⃝ Inter
Structural MRI
........................................................................................................................................................................................................................................................................................
Mike P. Wattjes
Alzheimer Center Amsterdam, Department of Radiology, VU University Medical Center, Amsterdam, The Netherlands
ABSTRACT
Clinical neuroimaging is increasingly being used in the diagnosis of neurodegenerativ
one of the most important paraclinical tools in the diagnosis of dementia. Accord
neuroimaging, preferably magnetic resonance imaging (MRI), should be performe
diagnostic work-up of patients with suspected or definite dementia. MRI is helpful
potentially treatable causes of dementia; however, these account only for a small
In addition, MRI is able to support the clinical diagnosis in a memory clinic set
patterns of atrophy and vascular damage. Visual rating scales are well-establishe
routine for the assessment and quantification of regional/global cortical atrophy,
vascular damage. In addition, MRI is able to detect certain aspects of pathology
such as cerebral microbleeds which are related to cerebral amyloid angiopathy and

PATRONES NEUROIMAGEN
ESTRUCTURAL

ENFERMEDAD DE ALZHEIMER
■ Síndrome amnésico típico: atrofia hipocampal y precúneo
■ EA comienzo tardío y polimorfismo APOE4: atrofia hipocampal predominante
■ EA comienzo precoz: presenta más atrofia cortical posterior
■ Variante logopénica afasia progresiva primaria: atrofia inicial unión temporoparietal
■ EA asociada a síndrome corticobasal: atrofia parietal predominante
changes lead to neuronal dysfunction and death, with subse-
quent atrophy of selectively vulnerable brain networks and
emergent clinical features, including cognitive impairment.4
Dependingonthebrainregionsandnetworksthat areaffected,
AD can present with a multitude of clinical syndromes,
including, but not limited to, the classic amnestic syndrome,
posterior cortical atrophy (PCA), a frontal/dysexecutive syn-
drome, and the logopenic variant of primary progressive
aphasia (discussed in the Primary Progressive Aphasia sec-
tion). Substantial research efforts aimed at studying biomar-
kers of AD, including the large-scale Alzheimer’s Disease
Neuroimaging Initiative (ADNI) and the Imaging Dementia-
Evidence for Amyloid Scanning (IDEAS) studies, have shown
that neuroimaging biomarkers improve clinical diagnosis in
emission tomography (PET) scan] of underlying AD pathol-
ogy.6
Additionally, AD pathology often co-exists with other
pathologies, such as synucleinopathies and vascular disease,
that contribute to cognitive deficits, raising uncertainty about
direct causality between specific underlying pathology and
predominant clinical syndrome.7
MRI
Although the earliest site of AD pathology is often phospho-
tau accumulation in brainstem nuclei,8,9
the earliest atrophy
on magnetic resonance imaging (MRI) is detected in the
cerebrum.10
In the classic amnestic AD syndrome, early
atrophy can be appreciated in the hippocampi and precuneus
(►Fig. 1).10
Interestingly, however, hippocampal atrophy is
Downloadedby:HOSP.VIRGENDELASALUD.Copyrightedmaterial.
Fig. 1 T1 imaging in amyloid-PET confirmed AD variants. (A) LOAD 75-year-old female (MMSE: 17) with hippocampal atrophy on axial and coronal planes.
Precuneus atrophy canbeappreciatedon sagittal imaging, along with some mild frontal atrophy. (B) EOAD 59-year-old female with cognitiveimpairments in
multiple domains including memory and executive functioning (MMSE: 23; MOCA: 15). Prominent biparietal atrophy can be observed on sagittal and
coronal planes, with relatively preserved medial temporal lobes on axial reconstruction compared with LOAD. (C) lvPPA female with lvPPA (MMSE: 28).
Atrophy is lateralized to the left, primarily in the left temporoparietal region as seen on axial and coronal images. The precuneal atrophy observed on the
sagittal images is typical of AD pathology. (D) PCA patient (MMSE: 18) with significant occipital and parietal atrophy, shown by arrows on all three planes.
Ã
Non-neurologic orientation (right is right). Ã
Abbreviations:MMSE, mini-mental state examination; MoCA, Montreal Cognitive Assessment; LOAD, late onset
Alzheimer’s disease; EOAD, early onset Alzheimer’s disease; PCA, posterior cortical atrophy.
Seminars in Neurology Vol. 37 No. 5/2017

DEMENCIA FRONTOTEMPORAL – Variante conductual
www.thelancet.com Vol 386 October 24, 2015 1677
Frontotemporal lobar degeneration-tau accounts for
36–50% of all cases of frontotemporal lobar degeneration
according to different pathological series.36–38
The most
common subtypes of frontotemporal lobar degeneration-
tau are Pick’s disease, corticobasal degeneration, and
progressive supranuclear palsy. Pick’s disease constitutes
5% of all dementia cases and up to 30% of frontotemporal
Frontotemporal lobar degeneration-TDP
Frontotemporal lobar degeneration-TDP accounts for
about 50% of all cases of frontotemporal lobar
degeneration.37,38
Three major subtypes of frontotemporal
lobar degeneration-TDP (types A, B, and C) are recognised
on the basis of the patterns of cytoplasmic or intranuclear
pathology, and cortical association (figure 2E–G and
A B C D
E F G H
Figure 2: Neuropathology in FTLD-tau and FTLD-TDP
FTLD-tau (A) Pick bodies in Pick’s disease; (B) atufted astrocyte in progressive supranuclear palsy; (C) an astrocytic plaque in corticobasal degeneration; FTLD-TDP (E)
small compact or crescentic neuronal cytoplasmic inclusions and short,then neuropilthreads in FTLD-TDPtypeA; (F) diffuse or granular neuronal cytoplasmic inclusions
(with a relative paucity of neuropilthreads) in FTLD-TDPtype B; and (G) long,tortuous dystrophic neurites in FTLD-TDPtypeC.TDP can be seen withinthe nucleus in
neurons lacking inclusions but mislocalisestothe cytoplasm and forms inclusions in FTLD-TDP.The remaining FTLD cases are characterised by FUS-immunoreactive
inclusionsthat stain negatively fortau andTDP-43; a vermiform neuronal nuclear inclusion in a dentate gyrus granule cell is shown (D);this neuron contains an ovoid
cytoplasmic inclusion. In patients with hexanucleotide expansions in C9orf72, small juxtanuclear ubiquitin-positive,TDP-negative inclusions (H) are pathognomonic for
the disorder.These inclusions contain dipeptide repeat proteinstranslated fromtheGGGGCC repeat in one of six reading frames. Immunostains are 3-repeattau (A),
phospho-tau (B andC), FUS (D),TDP-43 (E–G) and ubiquitin (H). Sections are counterstained with haematoxylin. Scale bar appliesto all panels and represents 50 µm
inA, B,C, and H; 12 µm in D; and 100 µm in E andG. FTLD=frontotemporal lobar degeneration.TDP=TAR DNA-binding protein. FUS=fused-in-sarcoma.
■ Atrofia:
– Frontotemporal incluida
ínsula
– Cingulado anterior
– Lóbulo temporal anterior
– Estriado
– Amígdala
– Tálamo
NEUROPATOLOGÍA
GENÉTICA
Series
Non-Alzheim
Frontotemp
Jee Bang*, Salvatore Spina*,
Frontotemporal deme
characterised by progr
common type of deme
disorders because of th
frontotemporal demen
and temporal cortices
imaging, and molecul
allowing for the accura
molecular basis for fro
Introduction
Frontotemporal dem
degenerative clinica
progressive deficits i
and language. The dis
form of dementia
Alzheimer’s disease a
and is a leading type o
description of a patien
was made by Arnold
aphasia, lobar atroph
1911, Alois Alzheime
association with P
Lancet 2015; 386: 1672–82
See Editorial page 1600
This is the first in a Series
of three papers about
Non-Alzheimer’s dementia
*These authors contributed
equally
Memory and Aging Center,
University of California,
San Francisco, San Francisco,
CA, USA (J Bang MD, S Spina MD,
Prof B L Miller MD)
Correspondence to:
Prof Bruce L Miller, Memory and
Aging Center, University of
California, San Francisco School
of Medicine, Sandler
Neurosciences Center,
San Francisco, CA 94158, USA
bruce.miller@ucsf.edu

■ (3R) Enfermedad Pick
– Atrofia frontoinsular
asimétrica extendida
a temporal anterior
■ (4R) - PSP■ (4R) DCB
– Atrofia más posterior
– Respeta área
frontoinsular
■ DFT - Tau
25% of suspected corticobasal degeneration cases, and a
small proportion of behavioural-variant frontotemporal
dementia cases with or without motor neuron disease,
whereas frontotemporal lobar degeneration-TDP type B
accounts for about two-thirds of frontotemporal
dementia–motor neuron disease cases and 25% of
behavioural-variant frontotemporal dementia cases.
Frontotemporal lobar degeneration-TDP type C accounts
for about 90% of all cases of semantic-variant primary
progressive aphasia (left) or temporal-variant behavioural-
variant frontotemporal dementia (right).
Frontotemporal lobar degeneration-FUS
Behavioural-variant frontotemporal dementia associated
with frontotemporal lobar degeneration-FUS accounts
sometimes psychosis
behavioural abnormal
linguistic deficits. P
immunoreactive inclu
dentate gyrus (figure 2
Genetics
A family history of dem
cases of frontotempor
clear autosomal domin
cases.47
Mutations in
account for about 6
frontotemporal lobar de
be considered in patie
with a strong family
A B C
cases of non-fluent variant primary progressive aphasia,
onset frontotemporal dementia with severe disinhibition,
sometimes psychosis, and other psychiatric and
behavioural abnormalities in the absence of motor or
linguistic deficits. Patients show distinctive FUS-
immunoreactive inclusions that are abundant in the
dentate gyrus (figure 2D), and severe striatal atrophy.46
Genetics
A family history of dementia is reported in up to 40% of
cases of frontotemporal lobar degeneration, although a
clear autosomal dominant history accounts for only 10% of
cases.47
Mutations in C9orf72, MAPT, and GRN genes
account for about 60% of all cases of inherited
frontotemporal lobar degeneration.48
Genetic testing should
be considered in patients with frontotemporal dementia
with a strong family history of autosomal dominant
A B C
sometimes psychosis, and other psychiatric and
behavioural abnormalities in the absence of motor or
linguistic deficits. Patients show distinctive FUS-
immunoreactive inclusions that are abundant in the
dentate gyrus (figure 2D), and severe striatal atrophy.46
Genetics
A family history of dementia is reported in up to 40% of
cases of frontotemporal lobar degeneration, although a
clear autosomal dominant history accounts for only 10% of
cases.47
Mutations in C9orf72, MAPT, and GRN genes
account for about 60% of all cases of inherited
frontotemporal lobar degeneration.48
Genetic testing should
be considered in patients with frontotemporal dementia
with a strong family history of autosomal dominant
A B C
Series
N
Fr
Jee B
FroLancet 2015; 386: 1672–82
degeneration.37,38
A B C D
E F G H

ESPECTRO DFT - Tau
■ Dilatación marcada de III ventrículo
■ Atrofia mesencefálica dorsal
■ Adelgazamiento pedúnculos
cerebelosos superiores
■ Atrofia tálamo, ganglios basales,
córtex frontal.
is 18
F-AV1451. Very few studies have been conducted in
bvFTD at this point. In a few case studies of patients with
the MAPT mutation, in vivo tracer binding occurs in the
expected frontotemporal distribution.109–111
A caveat is
that the specificity of some tau tracers has been questioned,
as one leading tracer, 18F
-THK5351, has been shown to bind
monoamine oxidase B (MAO-B) as well as PHFs.112
Corticobasal Syndrome
Consensus diagnostic criteria define CBS by early asymme-
trical cortical symptoms including limb rigidity, dystonia or
myoclonus, oral buccal or limb apraxia, cortical sensory
deficit, and/or alien limb phenomenon.113
CBS can include
language and speech disturbances or begin as a bvFTD
syndrome.114
Atrophy in CBS is typically located in dorsal
GM and WM of the posteromedial frontal and perirolandic
cortices,88
as well as the basal ganglia and brainstem.115
A difficulty in interpreting the historical literature on
imaging findings in CBS is that much was based on cases
without pathologically confirmed diagnoses. We now know
Neuroimaging in Dementia Staffaroni et al. 517
terial.
is 18
F-AV1451. Very few studies have been conducted in
bvFTD at this point. In a few case studies of patients with
the MAPT mutation, in vivo tracer binding occurs in the
expected frontotemporal distribution.109–111
A caveat is
that the specificity of some tau tracers has been questioned,
as one leading tracer, 18F
-THK5351, has been shown to bind
monoamine oxidase B (MAO-B) as well as PHFs.112
Corticobasal Syndrome
Consensus diagnostic criteria define CBS by early asymme-
trical cortical symptoms including limb rigidity, dystonia or
myoclonus, oral buccal or limb apraxia, cortical sensory
deficit, and/or alien limb phenomenon.113
CBS can include
language and speech disturbances or begin as a bvFTD
syndrome.114
Atrophy in CBS is typically located in dorsal
GM and WM of the posteromedial frontal and perirolandic
cortices,88
as well as the basal ganglia and brainstem.115
A difficulty in interpreting the historical literature on
imaging findings in CBS is that much was based on cases
without pathologically confirmed diagnoses. We now know
that CBS can be caused by different pathological entities,
each with its own imaging findings, and CBD pathology can
present with several clinical phenotypes other than CBS,
such as bvFTD, nfvPPA, PSPS, and PCA.116
In our own center’s
review of 40 pathologically confirmed cases of CBS, we found
at least four common pathologic substrates for this syn-
drome, including CBD (35%), AD (23%), PSP (13%), and FTLD-
TDP (13%);15
other centers have shown as many as 50% of CBS
patients to have PSP pathology on autopsy.117
Pathologically confirmed CBD pathology is generally asso-
ciated with bilateral cortical atrophy in the dorsolateral pre-
frontal cortex, supplementary motor area (SMA), perirolandic
cortex, striatum, and brainstem.15
CBD pathology, however,
can manifest as several syndromes, each with different neu-
roimaging signatures that generally adhere to that syndrome’s
Fig. 5 Neuroimaging in progressive supranuclear palsy syndrome
(PSPS). (A,B) Sagittal and (C) coronal T1-weighted images from a 61-
Neuroimaging in Dementia Staffaroni et al. 517
y:HOSP.VIRGENDELASALUD.Copyrightedmaterial.
berrant WM changes in the left frontal lobes,
nt of subcortical tracts and the uncinate
0
In one study, when DTI metrics were com-
tical thickness, nfvPPA (n ¼ 13) and svPPA
be distinguished from each other with a
92 and specificity of 0.85.161
lvPPA patients,
broad, bilateral front-temporo-parietal WM
3,159
that are similar to those seen in classic
e small number of subjects in these studies,
ire validation in larger cohorts.
with Lewy Bodies and Parkinson’s
mentia
ndromes are often associated with cognitive
t can progress to dementia. PDD and demen-
bodies (DLB) are among the most common
ive diseases in older adults.162–164
PDD and
y symptoms, and many consider these dis-
ng a spectrum, although some have argued
orders affect different anatomical path-
hologically, DLB and PDD are characterized
al α-synuclein “Lewy body” inclusions in
ortex, brainstem, and substantia nigra.162,168
ferentiating feature between PDD and DLB is
symptom emergence: onset of cognitive
e or within the same year as onset of motor
ants a diagnosis of DLB, and motor symptoms
gnitive decline by at least a year warrant a
62,165
The central feature of DLB is progres-
ecline in executive and visuospatial functions
er in the disease, memory. Other core and
increases with above age 65. In light of the increased pre-
valence of mixed pathologies in elderly, distinguishing DLB
from other conditions is complicated by the prevalence of
copathologies, with several pathology studies suggesting
that 66% to 77% of clinically diagnosed DLB cases have
comorbid DLB and AD pathology (DLB þ AD).169–173
Brain MRI of patients with DLB may not be diagnostically
informative, as patients often have diffuse mild cortical
atrophy with no distinct regional pattern. A pathologically
confirmed study of 42 DLB cases found that in cases of DLB
pathology with low-to-intermediate likelihood of comorbid
AD and Braak NFT stage IV (n ¼ 20), global atrophy on MRI
was not significantly different than controls, with no identi-
fied regional patterns, and atrophy was minimal compared
with both DLB þ AD and AD. In 22 patients with mixed
DLB þ AD pathology, the spatial distribution of atrophy on
MRI generally mapped onto the same areas atrophied in AD
and correlated with Braak NFT stage, suggesting that AD
pathology drives atrophy in these patients.174
These findings
are in contrast to those of clinically-, rather than pathologi-
cally-, diagnosed patients. For example, one voxel-based
morphometry (VBM) meta-analysis of 218 DLB clinically
diagnosed patients showed reduced right lateral temporal/
insular and left lenticular nucleus/insular GM compared with
219 healthy controls.175
When clinically diagnosed DLB and
AD have been compared using VBM analysis, no consistent
regions of atrophy differentiated the two, with the possible
exception of relatively preserved medial temporal lobe
volume in DLB compared with AD.176–179
Structural MRI findings in PDD have beenvariable, though a
lackof autopsy-confirmed studies on this topic raises concerns
about pathological confounds. A meta-analysis of GM VBM
Downloadedby:HOSP.VIRGENDELAS
PARÁLISIS SUPRANUCLEAR PROGRESIVA
■ DFT - Tau
lobar degeneration are frontotemporal lobar degeneration-
tau, frontotemporal lobar degeneration-TDP, and fronto-
temporal lobar degeneration-FUS. A few cases of
frontotemporal lobar degeneration have ubiquitin-only or
p62-only positive inclusions, or no inclusions at all.33
Frontotemporal lobar degeneration-tau
The most
Progressive supranuclear palsy is associated with atrophy
of the frontal convexity, milder than in corticobasal
degeneration.42
Subcortical atrophy is severe at the level of
the globus pallidus, subthalamic nucleus, and brainstem
nuclei. Microscopically, neuronal granular inclusions,
tufted astrocytes, and globose tangles are seen (figure 2B).40
degeneration.37,38
A B C D
E F G H

■ DFT - TDP
■ TDP-43 A
– Asociada mutación gen
PGRN
– Atrofia asimétrica
■ TDP-43 B
– Asociada a enfermedad
de motoneurona
– Atrofia simétrica insular y
temporal anteromedial
D E F
Figure 3: Patterns of brain atrophy in FTLD pathologies
D E F
Figure 3: Patterns of brain atrophy in FTLD pathologies
Series
Non-Alzheimer’s dementi
Frontotemporal dementia
Jee Bang*, Salvatore Spina*, Bruce L Miller
Frontotemporal dementia is an umbrella clinicaLancet 2015; 386: 1672–82
The most
degeneration.37,38
A B C D
E F G H

■ DFT - FUS
■ Atrofia severa caudado
■ Además de frontotemporal
The most
degeneration.37,38
A B C D
E F G H
FTLD-TAU cases (P = 0.02). Frontal lobe grey mat-
ter volumes (Fig. 4B) were similar across both groups
(P = 0.12). The total grey matter volumes were largest
in the FTLD-TAU group and smallest in the FTLD-
TDP group (P = 0.02) (Fig. 4C). Caudate volume
whereas frontal grey matter vol
proportion of total grey matter v
similar across all groups (P = 0.
expressed as a proportion of fronta
was lower in FTLD-FUS (Fig
Figure 3 Axial T
in the FTLD-TAU group and smallest in the FTLD-
TDP group (P = 0.02) (Fig. 4C). Caudate volume
expressed as a proportion of frontal grey matter volume
was lower in FTLD-FUS (Fig. 4F) compared to
Figure 3 Axial T1-weighted MRI scans
show that the caudate in our three
FTLD-FUS cases (left panel) are visually
smaller than the caudate in two represen-
tative FTLD-TDP cases (right panel);
despite the times from onset to MRI scan.
Note one of the FTLD-TDP cases was
6 years from onset at the time of the MRI
scan with relatively preserved caudate
volume.
Ó 2010 The Author(s)
Journal compilation Ó 2010 EFNS European Journal of Neurology 17, 969–975

■ C9orf72
■ Atrofia simétrica:
– Frontotemporal, talámica, parietal
y cerebelosa
■ PGRN
■ MAPT
■ Menor afectación frontomedial que en
forma esporádica
■ Atrofia asimétrica:
– Frontotemporal que puede
extenderse a nivel parietal
■ Respeta cerebelo
■ Atrofia severa temporal

DEMENCIA FRONTOTEMPORAL - Variante conductual
Fig. 4 Neuroimaging in pathologically conﬁrmed frontotemporal dementia (FTD) patients. T1 MRI images in genetic and pathological forms
of FTD, highlighting pathological propensities toward symmetry and regional predilections. Figure used with permission from: Gordon E, Rohrer
Neuroimaging in Dementia Staffaroni et al.516
atrophy in addition to frontotemporal involve
Genetic Variants and Imaging
Each genetic variant of bvFTD generally is ass
neuroimaging phenotype. bvFTD patients
mutation have a variable age of onset (20s–8
present with psychiatric features including
C9orf72 carriers are less likely to present w
ﬁndings than PGRN and MAPT carriers. M
usually shows symmetric frontotemporal, thal
and cerebellar atrophy, with less medial fronta
than in sporadic bvFTD.93,95
Patients with PG
usually manifest symptoms around age 60,96
an
range of clinical phenotypes, including bvFT
CBS.97
In contrast to C9orf72 patients, ima
patients typically shows asymmetric frontot
phy extending into the parietal lobes with s
cerebellum.95,98
Patients with MAPT mutation
earlier symptom onset, often before age 50
temporal lobe atrophy.99,100
Mutations in FU
ALS, but may rarely cause bvFTD.101

DEMENCIA FRONTOTEMPORAL
atrophy in addition to frontotemporal involve
Genetic Variants and Imaging
Each genetic variant of bvFTD generally is ass
neuroimaging phenotype. bvFTD patients
mutation have a variable age of onset (20s–8
present with psychiatric features including
C9orf72 carriers are less likely to present w
ﬁndings than PGRN and MAPT carriers. M
usually shows symmetric frontotemporal, thal
and cerebellar atrophy, with less medial fronta
than in sporadic bvFTD.93,95
Patients with PG
usually manifest symptoms around age 60,96
an
range of clinical phenotypes, including bvFT
CBS.97
In contrast to C9orf72 patients, ima
patients typically shows asymmetric frontot
phy extending into the parietal lobes with s
cerebellum.95,98
Patients with MAPT mutation
earlier symptom onset, often before age 50
temporal lobe atrophy.99,100
Mutations in FU
ALS, but may rarely cause bvFTD.101
Seminars in Neurology Vol. 37 No. 5/2017Fig. 4 Neuroimaging in pathologically conﬁrmed frontotemporal dementia (FTD) patients. T1 MRI images in genetic and pathological forms
of FTD, highlighting pathological propensities toward symmetry and regional predilections. Figure used with permission from: Gordon E, Rohrer
Neuroimaging in Dementia Staffaroni et al.516

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