Introduction: It is well known that some patients with Alz-heimer’s disease (AD) have atypical, nonamnestic presentations. While logopenic aphasia and posterior cortical atrophy are well-characterized atypical variants of AD, the behavioral/dysexecutive variant remains a controversial entity, lacking consensus regarding its distinctive clinical and imaging features. Methods: We present a case series of 8 patients with biomarker confirmation of AD (cerebrospinal fluid [CSF] analysis or amyloid positron emission tomography [PET]) and a progressive frontal syndrome, defined as prominent behavioral and/or executive deficits at initial presentation. We characterize the cohort based on clinical features, cognitive performance in 4 domains (memory, visuospatial, executive, and language) as well as behavior on the Dépistage Cognitif de Québec (DCQ), and regional brain metabolism using 18F-fluorodeoxyglucose PET (FDG-PET). We compare these features with 8 age-matched patients diagnosed with the behavioral variant of frontotemporal dementia (bvFTD) and 37 patients with typical amnestic AD. Results: Patients with the behavioral/dysexecutive variant of AD presented with early-onset (mean age: 59 years old) progressive executive and behavioral problems reminiscent of bvFTD, including disinhibition, loss of social conventions, and hyperorality. Patients scored higher on the Memory Index and lower on the Behavioral Index than patients with amnestic AD on the DCQ, yet they were indistinguishable from patients with bvFTD on each of the cognitive indices. Visual analysis of FDG-PET revealed half of patients with behavioral/dysexecutive AD presented with frontal hypometabolism suggestive of bvFTD and only 3/8 (37.5%) presented significant hypometabolism of the posterior cingulate cortex. Group-level analysis of FDG-PET data revealed that the most hypometabolic regions were the middle temporal, inferior temporal, and angular gyri in behavioral/dysexecutive AD and the inferior frontal gyrus, anterior cingulate cortex, caudate nucleus, and insula in bvFTD. Conclusion: The behavioral/dysexecutive variant of AD is a rare, atypical young-onset variant of AD defined clinically by early and prominent impairments in executive and behavioral domains. While behavioral/dysexecutive AD is hardly distinguishable from bvFTD using clinical and cognitive features alone, CSF biomarkers and temporoparietal hypometabolism help predict underlying pathology during life.

While Alzheimer’s disease (AD) is best known as a late-onset progressive disorder of memory, researchers and clinicians have long described young-onset variants with focal language, visuospatial or behavioral impairments, and relative sparing of memory [1-3]. Language (primary progressive aphasia) and visuospatial (posterior cortical atrophy) variants of AD are well recognizedand have dedicated international consensus criteria [4, 5]. The “frontal” variant of AD was first described in 1999 in a case series of 3 patients with disproportionate frontal impairments and higher neurofibrillary tangle (NFT) load in the frontal cortex than typical AD patients [6]. Subsequently, multiple studies reported a proportion of patients clinically diagnosed with the behavioral variant of frontotemporal dementia (bvFTD) who harbored primary AD pathology at autopsy (although not specifically higher in the frontal lobes) [7-17]. The behavioral/dysexecutive variant of AD was incorporated as a modifier of AD diagnosis in the updated National Institute of Aging (NIA) and International Working Group (IWG) criteria [18, 19]. However, it remains poorly studied compared to language and visuospatial variants of AD. In the largest study of behavioral/dysexecutive AD to this date, Ossenkoppele et al. [15] found predominant temporoparietal atrophy and relative sparing of frontal gray matter, hence suggesting labeling the disorder “behavioral/dysexecutive variant of AD” rather than “frontal AD.” However, since AD can be associated with a variety of neuropsychiatric symptoms [20, 21], it remains unclear whether behavioral/dysexecutive AD exists as a distinct clinicopathological entity where AD pathology selectively affects brain networks responsible for executive and behavioral functions, as demonstrated for language and visuospatial variants [2]. In this study, we aimed to provide a clinical, neuropsychological, and biomarker characterization of 8 patients with behavioral/dysexecutive AD seen at a tertiary care memory clinic.

Patient Selection

The Clinique Interdisciplinaire de Mémoire (CIME) du CHU de Québec is a tertiary care memory clinic in Québec City, Québec, Canada. All patients are assessed according to the recommendations of the fourth Canadian Consensus Conference on the Diagnosis and Treatment of Dementia [22]. A typical consultation includes history taking, neurological examination, cognitive screening (Mini-Mental State Examination [MMSE] [23] and Montreal Cognitive Assessment [MoCA] [24]), targeted cognitive evaluation using Dépistage Cognitif de Québec (DCQ) [25] and/or other specific cognitive tests, basic blood work (complete blood count, electrolytes, TSH, B12, and screening for syphilis), and magnetic resonance imaging (MRI) – dementia protocol (which includes a 3D-T1 and susceptibility-weighted imaging). If the diagnosis remains unclear, patients can be referred to further neuropsychological and speech/language pathology testing as well as 18F-fluorodeoxyglucose positron emission tomography (FDG-PET). When the diagnosis remains unclear, clinicians can order amyloid PET imaging or a lumbar puncture with cerebrospinal fluid (CSF) analysis of total tau (t-tau), tau phosphorylated at threonine 181 (p-tau181), and amyloid β 1–42 (Aβ1–42) peptide (for an algorithm, see Laforce et al. [26]).

We searched our clinical database for patients with a diagnosis of “frontal AD” or “behavioral/dysexecutive AD” who had biomarker confirmation of AD pathophysiology (amyloid-PET imaging or CSF analysis) and FDG-PET. Eight patients corresponded to our search criteria. Of these, 6 patients had participated in our research project on the DCQ cognitive test, offering basic neurocognitive characterization. We then searched our clinical database for patients with a diagnosis of bvFTD according to consensus criteria [27] who had a biomarker confirmation of the absence of AD pathophysiology and an FDG-PET. We selected 8 bvFTD patients corresponding to those criteria. Finally, we searched our database for patients with typical amnestic AD who had a biomarker confirmation of AD pathology and an FDG-PET. We found 10 patients corresponding to those criteria.

Clinical Definitions

The updated consensus diagnostic criteria were used for patients with AD [18] and FTD [27]. For the diagnosis of the behavioral/dysexecutive variant of AD, we adapted the diagnostic criteria used in the largest cohort to this date [15]. Our criteria were as follows: (1) in vivo evidence of amyloid pathology on PET or CSF; (2) clinical diagnosis of possible behavioral variant FTD, suggested by a combination of behavioral symptoms (disinhibition, apathy, loss of empathy, and hyperorality) [27], prominent executive dysfunction, and frontal hypometabolism on metabolic imaging (FDG-PET). All cases were discussed over interdisciplinary meetings (neurologists, geriatricians, neuropsychiatrists, neuropsychologists, and other allied health professionals).

Neurocognitive Characterization

The DCQ is a cognitive screening tool that was designed by a group of behavioral neurologists and clinical neuropsychologists (R.L., R.B., and C.H.) to target 5 relevant domains, referred to as DCQ indexes [25, 28]. The DCQ’s questionnaire, administration guidelines, and normative data are available free of charge at www.dcqtest.org. The Memory Index assesses basic attention using the forward digit span, a short-term recall task of 8 words with delayed recall after 15 min, and a recognition task. The Visuospatial Index tests visual recognition of overlapping figures and spatial rotation (the subject is asked to recognize an image from a scene, representing his viewing angle, which is changed throughout the task). This index also includes a geometric figure drawing test. The Executive Index includes backward digit span, months backward test, an alternating graphic sequence test, a two-item verbal abstraction task, phonemic fluency (letter A, 60 s), and a modified Stroop test. The Language Index comprises a scene description task to assess spontaneous speech, a naming and single-word writing task, a multisentence writing test, assessment of comprehension through a sentence – picture matching test, a semantic verbal fluency task, and a task requiring the participant to repeat short as well as long and complex sentences. Finally, the Behavioral Index explores 10 domains (depression, anxiety, delusions, hallucinations, irritability and aggression, apathy, disinhibition and impaired judgment, perseverations and compulsions, loss of empathy/sympathy, and self-criticism) as reported by a significant other. Psychometric properties of the screening tool have been validated in a cohort of 410 healthy aged individuals [28]. As part of a validation study on clinical populations, the DCQ was administered to patients seen at the memory clinic by trained psychometricians, blind to clinical diagnosis. Twenty-one of the patients included in this study (6 behavioral/dysexecutive AD, 7 bvFTD, and 8 typical amnestic AD) performed the DCQ.

Metabolic Imaging Using FDG-PET

All FDG-PET scans were acquired between 2015 and 2018 under common standardized FDG-PET acquisition protocols described elsewhere [29]. For the image analysis, dementias were classified mainly by visual rating according to generally accepted criteria: for a recent review, see Brown et al. [30]. For quantitative analysis, FDG-PET images were analyzed using the MIMneuro® software (MIM, Cleveland, OH, USA). FDG-PET images were coregistered to brain CT for anatomic segmentation. Then, FDG-PET was normalized to whole-brain activity and compared against a normal database to determine the presence of hypometabolism based on standardized uptake values (SUV). The MIM database of cognitively healthy subjects consists of brain FDG-PET scans from 43 male and female subjects with a mean age of 63 ± 10 years and an age range of 41–80 years. Subjects did not have histories of primary brain neoplasms, brain metastases, head/neck radiation, chemotherapy, medications that could affect cerebral glucose metabolism, head trauma, stroke, substance abuse, leukemia, renal failure, severe heart failure, severe chronic obstructive pulmonary disease, uncontrolled diabetes, or immune suppression. All volunteers in the normal control group had MMSE scores of 25 or higher and Memory Impairment Screen scores of 6 or higher. Regional SUV was converted to z-scores for defining FDG metabolism in 70 regions of interest (ROIs).

Statistical Analyses

All statistical analyses were performed using SAS 9.3 (SAS Institute Inc.). The significance level was set at p < 0.05. Analyses of variance (ANOVA) and χ2 analyses were used to compare groups on quantitative continuous and on categorical demographic/cognitive variables, respectively. Quantitative analyses of FDG-PET data were performed using MIMneuro® software (MIM, Cleveland, OH, USA). For each patient, a z-score of metabolic activity (in comparison with reference values of 43 normal controls) was calculated for 70 ROIs. We calculated mean z-scores of metabolism for each ROI in the behavioral/dysexecutive AD and bvFTD groups. We subtracted mean z-scores in each group to determine the ROIs showing the highest discrepancy between the groups (presented in Table 4).

We included 8 patients with a diagnosis of behavioral/dysexecutive AD, 8 patients with a diagnosis of bvFTD, and 10 patients with typical amnestic AD. Patients with behavioral/dysexecutive AD were significantly younger than patients with amnestic AD (59.5 years old vs. 74 years old at the clinical presentation on average, p < 0.05) and bvFTD (64 years old on average; p > 0.05). All patients had biomarker confirmation of amyloid positivity (behavioral/dysexecutive AD) or negativity (bvFTD) based on amyloid PET (3 patients, visual read of 18F-NAV4694 PET) or CSF analysis (13 patients, Aβ-42 <550 pg/mL). Cohorts were otherwise similar for sex, education, and disease stage measured by MMSE (p > 0.05; see Table 1). All patients underwent FDG-PET and CSF measurement of AD biomarkers, and most patients performed detailed cognitive screening with DCQ.

Table 1.

Patients’ characteristics

Patients’ characteristics
Patients’ characteristics

Clinical Features

Among the 8 patients included with a clinical diagnosis of behavioral/dysexecutive AD, 4 had a primarily dysexecutive phenotype (patients 1, 5, 6, and 8) and 4 had a primarily behavioral phenotype (patients 2, 3, 4, and 7). In patients with a behavioral phenotype, the most common FTD features were apathy, disinhibition, ritualistic behaviors, and hyperorality, and every patient fulfilled clinical criteria for bvFTD (see Table 2). All patients had “positive” frontal lobe features such as disinhibition, loss of social conventions, or inappropriate social conduct. Interestingly, many patients reported marked diet changes similar to what is described in patients with bvFTD. For instance, patient 2 had an increased taste for sweets, eating as many as 12 small cakes a night. The positive frontal lobe symptoms were generally less severe than in patients with bvFTD. Patients with a dysexecutive phenotype showed aspontaneity and disorganization, which were perceived as more limiting than impairments in memory. Cognitive testing revealed predominant executive dysfunction at examination, with relative preservation of episodic memory.

Table 2.

Cognitive and behavioral symptoms of behavioral/dysexecutive AD patients

Cognitive and behavioral symptoms of behavioral/dysexecutive AD patients
Cognitive and behavioral symptoms of behavioral/dysexecutive AD patients

Cognitive Screening

Patients with behavioral/dysexecutive AD, bvFTD, and typical amnestic AD were in a similar disease stage, as suggested by similar MMSE (22.3/30, 22.1/30, and 23.5/30, respectively, p > 0.05). Compared to patients with typical amnestic AD, those with behavioral/dysexecutive AD had a significantly higher score on the memory index (19.3/30 vs. 14.1/30) and lower score on the behavioral index (9.0/20 vs. 14.8/30; p < 0.05). Interestingly, however, patients with behavioral/dysexecutive AD were indistinguishable from those with bvFTD on each of the 5 cognitive indexes, including the Memory (19.3/30 vs. 20.3/30), Visuospatial (5.6/7 vs. 4.8/7), Executive (4.4/10 vs. 4.4/10), Language (26.9/33 vs. 25.4/33), and Behavioral (9.0/20 vs. 9.0/20) (all p > 0.05; See Table 3).

Table 3.

Neuropsychological differences between bvFTD, behavioral/dysexecutive AD, and amnestic AD

Neuropsychological differences between bvFTD, behavioral/dysexecutive AD, and amnestic AD
Neuropsychological differences between bvFTD, behavioral/dysexecutive AD, and amnestic AD

18F-Fluorodeoxyglucose Positron Emission Tomography

All patients included in the study with a diagnosis of behavioral/dysexecutive AD or bvFTD underwent FDG-PET with visual and quantitative characterization (see Fig. 1). On visual reads, frontal hypometabolism suggestive of bvFTD on FDG-PET was present in 50% of patients (4/8, mostly dysexecutive phenotype), with the remaining patients presenting predominant temporoparietal hypometabolism with occasional mild frontal involvement (mostly behavioral phenotype). Posterior cingulate cortex hypometabolism was present in only 3 patients at visual inspection (37.5%). On group-level quantitative analyses of 70 ROIs, the regions better distinguishing behavioral/dysexecutive AD from typical amnestic AD were the orbitofrontal cortex, middle orbital gyrus, lateral orbital gyrus, and middle temporal gyrus and those better distinguishing behavioral/dysexecutive AD from bvFTD were the middle temporal, inferior temporal, and angular gyri (see Table 4). Conversely, regions better distinguishing bvFTD from behavioral/dysexecutive AD were pars opercularis of the inferior frontal gyrus, insula, anterior cingulate gyrus, and caudate nucleus. However, none of these differences reached a significance level of p < 0.05.

Table 4.

FDG-PET differences between bvFTD and behavioral/dysexecutive AD

FDG-PET differences between bvFTD and behavioral/dysexecutive AD
FDG-PET differences between bvFTD and behavioral/dysexecutive AD
Fig. 1.

3D-SSP projections of FDG-PET in behavioral/dysexecutive AD and bvFTD. Images represent lateral and axial 3D-SSP projections of FDG-PET scans in patients with FTD and AD. FDG-PET, 18F-fluorodeoxyglucose positron emission tomography; AD, Alzheimer’s disease; bvFTD, behavioral variant of frontotemporal dementia; L, left; R, right.

Fig. 1.

3D-SSP projections of FDG-PET in behavioral/dysexecutive AD and bvFTD. Images represent lateral and axial 3D-SSP projections of FDG-PET scans in patients with FTD and AD. FDG-PET, 18F-fluorodeoxyglucose positron emission tomography; AD, Alzheimer’s disease; bvFTD, behavioral variant of frontotemporal dementia; L, left; R, right.

Close modal

Although “frontal” or “dysexecutive” variants of AD are now included in updated NIA and IWG criteria, the evidence acknowledging behavioral/dysexecutive AD as a distinct clinicopathological entity remains scarce. In this study, we present a case series of 8 patients diagnosed with behavioral/dysexecutive AD, providing clinical, neuropsychological, and FDG-PET characterization. We compared the cohort with 8 patients with bvFTD and 10 patients with typical AD. Since the first description of “frontal” AD in 1999 in 3 patients with disproportionate frontal impairments and higher NFT load in the frontal cortex [6], AD pathology was consistently found at autopsy in about 5–20% of patients with a diagnosis of bvFTD during life [7-15, 17]. This clinical overlap creates diagnostic confusion and argues in favor of the clinical use of in vivo amyloid biomarkers in early-onset dementia with behavioral presentations [31]. Two studies analyzed the frequency of clinical features of frontal dementia caused by AD versus FTLD pathology, as well as the sensitivity and specificity of consensus diagnostic criteria for bvFTD [12, 16] (see Fig. 1). Mendez et al. [12] showed that concomitant memory or visuospatial dysfunction argues for a diagnosis of behavioral/dysexecutive AD, whereas personality change is more consistent with bvFTD. Similarly, Vijverberg et al. [16] showed that while disinhibition, apathy, and empathy loss are sensitive for FTLD pathology, perseverative behavior, hyperorality, and dysexecutive-predominant cognitive profile have higher specificity. Nevertheless, our case series highlights that AD can also present with prominent behavioral changes generally associated with FTLD pathology (disinhibition, loss of social conventions, hyperorality, etc.). Moreover, in our cohort, clinical features and neuropsychological testing of the main cognitive domains was indistinguishable between behavioral/dysexecutive AD and bvFTD, suggesting that clinical evaluation alone is not sufficient to distinguish both entities. Quantitative analysis of regional brain metabolism on FDG-PET highlighted regions whose hypometabolism may suggest FTLD pathology (ACC, insula, caudate, and inferior frontal gyrus) or behavioral/dysexecutive AD (inferior and middle temporal gyri and angular gyrus); however, on visual examination, half of the FDG-PET scans of patients subsequently diagnosed with behavioral/dysexecutive AD presented alterations suggestive of bvFTD. Likewise, in a previous study, nearly 50% of the behavioral/dysexecutive AD FDG-PET was rated as having frontal-predominant atrophy suggestive of bvFTD at MRI [15]. Interestingly, the posterior cingulate gyrus, a region that is widely used to distinguish AD from FTLD pathologies [30, 32-34], was not part of the 3 most discriminant regions between behavioral/dysexecutive AD and bvFTD, neither at visual nor quantitative analysis. These findings suggest that the usefulness of anterior (frontal lobes, anterior cingulate cortex, and anterior temporal lobe) to posterior (posterior association cortex and posterior cingulate cortex) metabolic gradient to distinguish AD from FTLD pathologies [35, 36] also applies to patients with a behavioral/dysexecutive profile. These results are also consistent with the largest study of behavioral/dysexecutive AD to this date, which showed temporoparietal-predominant atrophy rather than the expected frontal-predominant pattern [15]. This brought authors to rename the so-called “frontal variant AD” to “behavioral/dysexecutive variant AD,” as this atypical variant may not involve the frontal lobes as much as previously thought. Likewise, Whitwell et al. [37] had also shown that temporoparietal atrophy at MRI was indicative of AD regardless of the clinical variant – including a behavioral syndrome. Interestingly, group-level analyses of FDG-PET data revealed that many of the ROIs showing the more discrepancy between behavioral/dysexecutive AD and typical amnestic AD were located in the frontal (orbitofrontal region, orbital gyrus, etc.) and temporal lobes (middle temporal gyrus and inferior temporal gyrus). This finding suggests that behavioral/dysexecutive AD is a distinct clinicoanatomical variant of AD with selective vulnerability of frontotemporal brain networks [1, 2].

Our study has limitations. First, the absence of clear consensus criteria for behavioral/dysexecutive AD creates heterogeneity in clinician’s perception of this entity from a center to another, and even among clinicians within a given center. For example, the distinction between AD with early neuropsychiatric symptoms and behavioral/dysexecutive AD is difficult, and it is still unclear whether frontal-predominant atrophy/hypometabolism should be considered supportive of a diagnosis of behavioral/dysexecutive AD. Second, use of in vivo biomarker confirmation of AD pathophysiology (amyloid PET or CSF analysis) – rather than autopsy – does not exclude the possibility of dual pathologies, with primary FTLD pathology and incidental age-related amyloid pathology [38-41]. Nevertheless, autopsy studies of patients diagnosed with bvFTD during life consistently report a proportion of patients with primary AD pathology, without evidence of FTLD pathology [7-10, 13, 17]. Moreover, patients with behavioral/dysexecutive AD were very young (<60 years old on average); hence, incidental age-related amyloid pathology is less likely [38, 41]. Third, our study had a low sample size and hence observed group-level differences in regional hypometabolism between bvFTD, behavioral/dysexecutive AD, and amnestic AD did not reach statistical significance. Since our study was descriptive and not specifically intended to evaluate diagnostic properties of FDG-PET, our results should be considered preliminary evidence suggesting usefulness of FDG-PET to predict underlying pathology in patients with a frontal lobe syndrome.

A proportion of patients with a progressive frontal lobe syndrome have positive in vivo amyloid biomarkers, hence generally receive a diagnosis of behavioral/dysexecutive AD. Our case series of 8 biomarker-confirmed cases of behavioral/dysexecutive AD adds to previous reports in defining a subset of patients with AD with clinical features strikingly reminiscent of bvFTD. Cognitive screening of the main domains did not us allow to distinguish behavioral/dysexecutive AD from bvFTD, and group-level analysis of regional hypometabolism at FDG-PET suggested potential “signature” regions helping to distinguish both entities. More research is needed to validate clinical and imaging features helping clinicians to predict the underlying pathology of patients presenting with a progressive frontal lobe syndrome. Assessment of social cognition may represent a promising avenue [42, 43] and is currently tested at our institution.

The research was conducted ethically in accordance with the World Medical Association Declaration of Helsinki. The study protocol was approved by the institute’s committee on human research. The study used retrospective data from the CIME research database. All patients provided written consent to participate in the research database for retrospective studies.

The authors do not have any conflicts of interest to disclose.

The authors wish to thank the Canadian Institutes of Health Research (CIHR) Vanier Graduate Scholarship Program.

David Bergeron gathered the data, performed statistical analyses, and drafted the initial version of the manuscript. All authors contributed to study design, data interpretation, and provided input to the redaction of the manuscript.

1.
Warren
JD
,
Fletcher
PD
,
Golden
HL
.
The paradox of syndromic diversity in Alzheimer disease
.
Nat Rev Neurol
.
2012 Aug
;
8
(
8
):
451
64
. .
2.
Bergeron
D
,
Bensaïdane
R
,
Laforce
R
.
Untangling Alzheimer’s disease clinicoanatomical heterogeneity through selective network vulnerability: an effort to understand a complex disease
.
Curr Alzheimer Res
.
2016
;
13
(
5
):
589
96
. .
3.
Dickerson
BC
,
McGinnis
SM
,
Xia
C
,
Price
BH
,
Atri
A
,
Murray
ME
, et al
Approach to atypical Alzheimer’s disease and case studies of the major subtypes
.
CNS Spectr
.
2017 Dec
;
22
(
6
):
1
11
. .
4.
Gorno-Tempini
ML
,
Hillis
AE
,
Weintraub
S
,
Kertesz
A
,
Mendez
M
,
Cappa
SF
, et al
Classification of primary progressive aphasia and its variants
.
Neurology
.
2011 Mar 15
;
76
(
11
):
1006
14
. .
5.
Crutch
SJ
,
Schott
JM
,
Rabinovici
GD
,
Murray
M
,
Snowden
JS
,
van der Flier
WM
, et al
Consensus classification of posterior cortical atrophy
.
Alzheimers Dement
.
2017 Aug
;
13
(
8
):
870
84
. .
6.
Johnson
JK
,
Head
E
,
Kim
R
,
Starr
A
,
Cotman
CW
.
Clinical and pathological evidence for a frontal variant of Alzheimer disease
.
Arch Neurol
.
1999 Oct
;
56
(
10
):
1233
9
. .
7.
Kertesz
A
,
McMonagle
P
,
Blair
M
,
Davidson
W
,
Munoz
DG
.
The evolution and pathology of frontotemporal dementia
.
Brain
.
2005 Sep
;
128
(
Pt 9
):
1996
2005
. .
8.
Knopman
DS
,
Boeve
BF
,
Parisi
JE
,
Dickson
DW
,
Smith
GE
,
Ivnik
RJ
, et al
Antemortem diagnosis of frontotemporal lobar degeneration
.
Ann Neurol
.
2005 Apr
;
57
(
4
):
480
8
. .
9.
Shi
J
,
Shaw
CL
,
Du Plessis
D
,
Richardson
AM
,
Bailey
KL
,
Julien
C
, et al
Histopathological changes underlying frontotemporal lobar degeneration with clinicopathological correlation
.
Acta Neuropathol
.
2005 Nov
;
110
(
5
):
501
12
. .
10.
Forman
MS
,
Farmer
J
,
Johnson
JK
,
Clark
CM
,
Arnold
SE
,
Coslett
HB
, et al
Frontotemporal dementia: clinicopathological correlations
.
Ann Neurol
.
2006 Jun
;
59
(
6
):
952
62
. .
11.
Snowden
JS
,
Thompson
JC
,
Stopford
CL
,
Richardson
AM
,
Gerhard
A
,
Neary
D
, et al
The clinical diagnosis of early-onset dementias: diagnostic accuracy and clinicopathological relationships
.
Brain
.
2011 Sep
;
134
(
Pt 9
):
2478
92
. .
12.
Mendez
MF
,
Joshi
A
,
Tassniyom
K
,
Teng
E
,
Shapira
JS
.
Clinicopathologic differences among patients with behavioral variant frontotemporal dementia
.
Neurology
.
2013 Feb 5
;
80
(
6
):
561
8
. .
13.
Chare
L
,
Hodges
JR
,
Leyton
CE
,
McGinley
C
,
Tan
RH
,
Kril
JJ
, et al
New criteria for frontotemporal dementia syndromes: clinical and pathological diagnostic implications
.
J Neurol Neurosurg Psychiatry
.
2014 Aug
;
85
(
8
):
865
70
. .
14.
Leger
GC
,
Banks
SJ
.
Neuropsychiatric symptom profile differs based on pathology in patients with clinically diagnosed behavioral variant frontotemporal dementia
.
Dement Geriatr Cogn Disord
.
2014
;
37
(
1–2
):
104
12
.
15.
Ossenkoppele
R
,
Pijnenburg
YA
,
Perry
DC
,
Cohn-Sheehy
BI
,
Scheltens
NM
,
Vogel
JW
, et al
The behavioural/dysexecutive variant of Alzheimer’s disease: clinical, neuroimaging and pathological features
.
Brain
.
2015 Sep
;
138
(
Pt 9
):
2732
49
. .
16.
Vijverberg
EG
,
Dols
A
,
Krudop
WA
,
Peters
A
,
Kerssens
CJ
,
van Berckel
BN
, et al
Diagnostic accuracy of the frontotemporal dementia consensus criteria in the late-onset frontal lobe syndrome
.
Dement Geriatr Cogn Disord
.
2016
;
41
(
3–4
):
210
9
. .
17.
Perry
DC
,
Brown
JA
,
Possin
KL
,
Datta
S
,
Trujillo
A
,
Radke
A
, et al
Clinicopathological correlations in behavioural variant frontotemporal dementia
.
Brain
.
2017 Dec 1
;
140
(
12
):
3329
45
. .
18.
McKhann
GM
,
Knopman
DS
,
Chertkow
H
,
Hyman
BT
,
Jack
CR
 Jr
,
Kawas
CH
, et al
The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease
.
Alzheimers Dement
.
2011 May
;
7
(
3
):
263
9
. .
19.
Dubois
B
,
Feldman
HH
,
Jacova
C
,
Hampel
H
,
Molinuevo
JL
,
Blennow
K
, et al
Advancing research diagnostic criteria for Alzheimer’s disease: the IWG-2 criteria
.
Lancet Neurol
.
2014 Jun
;
13
(
6
):
614
29
. .
20.
Zhao
QF
,
Tan
L
,
Wang
H-F
,
Jiang
T
,
Tan
MS
,
Tan
L
, et al
The prevalence of neuropsychiatric symptoms in Alzheimer’s disease: systematic review and meta-analysis
.
J Affect Disord
.
2016 Jan 15
;
190
:
264
71
. .
21.
Poulin
SP
,
Bergeron
D
,
Dickerson
BC
.
Alzheimer’s disease neuroimaging I. Risk factors, neuroanatomical correlates, and outcome of neuropsychiatric symptoms in Alzheimer’s disease
.
J Alzheimers Dis
.
2017
;
60
(
2
):
483
93
.
22.
Gauthier
S
,
Patterson
C
,
Chertkow
H
,
Gordon
M
,
Herrmann
N
,
Rockwood
K
, et al
Recommendations of the 4th Canadian consensus conference on the diagnosis and treatment of dementia (CCCDTD4)
.
Can Geriatr J
.
2012 Dec
;
15
(
4
):
120
6
. .
23.
Folstein
MF
,
Folstein
SE
,
McHugh
PR
.
“Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician
.
J Psychiatr Res
.
1975 Nov
;
12
(
3
):
189
98
.
24.
Nasreddine
ZS
,
Phillips
NA
,
Bédirian
V
,
Charbonneau
S
,
Whitehead
V
,
Collin
I
, et al
The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment
.
J Am Geriatr Soc
.
2005 Apr
;
53
(
4
):
695
9
. .
25.
Sellami
L
,
Meilleur-Durand
S
,
Chouinard
AM
,
Bergeron
D
,
Verret
L
,
Poulin
S
, et al
The Depistage Cognitif de Quebec: a new clinician’s tool for early recognition of atypical dementia
.
Dement Geriatr Cogn Disord
.
2018
;
46
(
5–6
):
310
21
.
26.
Laforce
R
 Jr
,
Soucy
JP
,
Sellami
L
,
Dallaire-Théroux
C
,
Brunet
F
,
Bergeron
D
, et al
Molecular imaging in dementia: past, present, and future
.
Alzheimers Dement
.
2018 Nov
;
14
(
11
):
1522
52
. .
27.
Rascovsky
K
,
Hodges
JR
,
Knopman
D
,
Mendez
MF
,
Kramer
JH
,
Neuhaus
J
, et al
Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia
.
Brain
.
2011 Sep
;
134
(
Pt 9
):
2456
77
. .
28.
Laforce
R
 Jr
,
Sellami
L
,
Bergeron
D
,
Paradis
A
,
Verret
L
,
Fortin
MP
, et al
Validation of the Depistage Cognitif de Quebec: a new cognitive screening tool for atypical dementias
.
Arch Clin Neuropsychol
.
2018 Feb 1
;
33
(
1
):
57
65
.
29.
Bergeron
D
,
Beauregard
JM
,
Guimond
J
,
Fortin
MP
,
Houde
M
,
Poulin
S
, et al
Clinical impact of a second FDG-PET in atypical/unclear dementia syndromes
.
J Alzheimers Dis
.
2016
;
49
(
3
):
695
705
. .
30.
Brown
RK
,
Bohnen
NI
,
Wong
KK
,
Minoshima
S
,
Frey
KA
.
Brain PET in suspected dementia: patterns of altered FDG metabolism
.
Radiographics
.
2014 May–Jun
;
34
(
3
):
684
701
. .
31.
Bensaidane
MR
,
Beauregard
JM
,
Poulin
S
,
Buteau
FA
,
Guimond
J
,
Bergeron
D
, et al
Clinical utility of amyloid PET imaging in the differential diagnosis of atypical dementias and its impact on caregivers
.
J Alzheimers Dis
.
2016 Apr 18
;
52
(
4
):
1251
62
.
32.
Minoshima
S
,
Giordani
B
,
Berent
S
,
Frey
KA
,
Foster
NL
,
Kuhl
DE
.
Metabolic reduction in the posterior cingulate cortex in very early Alzheimer’s disease
.
Ann Neurol
.
1997 Jul
;
42
(
1
):
85
94
. .
33.
Silverman
DH
,
Small
GW
,
Chang
CY
,
Lu
CS
,
Kung De Aburto
MA
,
Chen
W
, et al
Positron emission tomography in evaluation of dementia: regional brain metabolism and long-term outcome
.
JAMA
.
2001 Nov 7
;
286
(
17
):
2120
7
. .
34.
Nestor
PJ
,
Altomare
D
,
Festari
C
,
Drzezga
A
,
Rivolta
J
,
Walker
Z
, et al
Clinical utility of FDG-PET for the differential diagnosis among the main forms of dementia
.
Eur J Nucl Med Mol Imaging
.
2018 May 7
;
45
(
9
):
1509
25
.
35.
Foster
NL
,
Heidebrink
JL
,
Clark
CM
,
Jagust
WJ
,
Arnold
SE
,
Barbas
NR
, et al
FDG-PET improves accuracy in distinguishing frontotemporal dementia and Alzheimer’s disease
.
Brain
.
2007 Oct
;
130
(
Pt 10
):
2616
35
. .
36.
Womack
KB
,
Diaz-Arrastia
R
,
Aizenstein
HJ
,
Arnold
SE
,
Barbas
NR
,
Boeve
BF
, et al
Temporoparietal hypometabolism in frontotemporal lobar degeneration and associated imaging diagnostic errors
.
Arch Neurol
.
2011 Mar
;
68
(
3
):
329
37
. .
37.
Whitwell
JL
,
Jack
CR
 Jr
,
Przybelski
SA
,
Parisi
JE
,
Senjem
ML
,
Boeve
BF
, et al
Temporoparietal atrophy: a marker of AD pathology independent of clinical diagnosis
.
Neurobiol Aging
.
2011 Sep
;
32
(
9
):
1531
41
. .
38.
Ossenkoppele
R
,
Jansen
WJ
,
Rabinovici
GD
,
Knol
DL
,
van der Flier
WM
,
van Berckel
BN
, et al
Prevalence of amyloid PET positivity in dementia syndromes: a meta-analysis
.
JAMA
.
2015 May 19
;
313
(
19
):
1939
49
. .
39.
Naasan
G
,
Rabinovici
GD
,
Ghosh
P
,
Elofson
JD
,
Miller
BL
,
Coppola
G
, et al
Amyloid in dementia associated with familial FTLD: not an innocent bystander
.
Neurocase
.
2016
;
22
(
1
):
76
83
. .
40.
Mesulam
MM
,
Dickerson
BC
,
Sherman
JC
,
Hochberg
D
,
Gonzalez
RG
,
Johnson
KA
, et al
Case 1-2017. A 70-year-old woman with gradually progressive loss of language
.
N Engl J Med
.
2017 Jan 12
;
376
(
2
):
158
67
. .
41.
Bergeron
D
,
Ossenkoppele
R
,
Laforce
R
 Jr
.
Evidence-based interpretation of amyloid-beta PET results: a clinician’s tool
.
Alzheimer Dis Assoc Disord
.
2018 Jan–Mar
;
32
(
1
):
28
34
.
42.
Bertoux
M
,
de Souza
LC
,
O’Callaghan
C
,
Greve
A
,
Sarazin
M
,
Dubois
B
, et al
Social cognition deficits: the key to discriminate behavioral variant frontotemporal dementia from Alzheimer’s disease regardless of amnesia?
J Alzheimers Dis
.
2016
;
49
(
4
):
1065
74
. .
43.
Mariano
LI
,
Caramelli
P
,
Guimarães
HC
,
Gambogi
LB
,
Moura
MVB
,
Yassuda
MS
, et al
Can social cognition measurements differentiate behavioral variant frontotemporal dementia from Alzheimer’s disease regardless of apathy?
J Alzheimers Dis
.
2020
;
74
(
3
):
817
27
. .
Copyright / Drug Dosage / Disclaimer
Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher.
Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug.
Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.