Diagnostic Accuracy of MRI and Additional [ 18 F]FDG-PET for Behavioral Variant Frontotemporal Dementia in Patients with Late Onset Behavioral Changes

Abstract

Background: Neuroimaging has a reasonable accuracy to differentiate behavioral variant frontotemporal dementia (bvFTD) from other neurodegenerative disorders, its value for the differentiation of bvFTD among subjects with acquired behavioral disturbances is unknown.

Objective: To determine the diagnostic accuracy of MRI, additional [¹⁸F]FDG-PET, and their combination for bvFTD among subjects with late onset behavioral changes.

Methods: Patients with late onset behavioral changes referred to a memory clinic or psychiatric services were included. At baseline, 111 patients had a brain MRI scan and 74 patients received an additional [¹⁸F]FDG-PET when the MRI was inconclusive. The consensus diagnosis after two-year-follow-up was used as the gold standard to calculate sensitivity and specificity for baseline neuroimaging.

Results: 27 patients had probable/definite bvFTD and 84 patients had a non-bvFTD diagnosis (primary psychiatric diagnosis or other neurological disorders). MRI had a sensitivity of 70% (95% CI 52–85%) with a specificity of 93% (95% CI 86–97%). Additional [¹⁸F]FDG-PET had a sensitivity of 90% (95% CI 66–100%) with a specificity of 68% (95% CI 56–79%). The sensitivity of combined neuroimaging was 96% (95% CI 85–100%) with a specificity of 73% (95% CI 63–81%). In 66% of the genetic FTD cases, MRI lacked typical frontotemporal atrophy. 40% of cases with a false positive [¹⁸F]FDG-PET scan had a primary psychiatric diagnosis.

Conclusion: A good diagnostic accuracy was found for MRI and additional [¹⁸F]FDG-PET for bvFTD in patients with late onset behavioral changes. Caution with the interpretation of neuroimaging results should especially be taken in cases with a genetic background and in cases with a primary psychiatric differential diagnosis where [¹⁸F]FDG-PET is the only abnormal investigation.

Keywords

Behavior diagnostic accuracy frontotemporal dementia MRI neuropsychology psychiatric disorders

INTRODUCTION

In clinical practice, behavioral variant frontotemporal dementia (bvFTD) has a broad and heterogeneous differential diagnosis including both neurodegenerative diseases and primary psychiatric disorders. Identifying the specific cause of late-onset behavioral changes represents a major challenge [1 –3] and will be increasingly important when disease-specific treatments become available.

As described in the international consensus criteria for bvFTD (FTDC), the presence of frontotemporal abnormalities on neuroimaging is considered as a biomarker for bvFTD, and is mandatory for the diagnosis probable bvFTD [4]. However, the diagnostic accuracy of magnetic resonance imaging (MRI) and [¹⁸F]-fluorodeoxyglucose-positron emission tomography ([¹⁸F]FDG-PET) for bvFTD varies across different studies [5 –9]. Generally, these studies have measured the diagnostic accuracy of frontotemporal changes on neuroimaging for bvFTD among cohorts of patients with neurodegenerative disorders.

Several studies have reported evidence of changes in frontotemporal regions on MRI and [¹⁸F]FDG-PET-scan in mood disorders and schizophrenia [10 –15], primary psychiatric disorders that may also present with behavioral changes. This might affect the diagnostic accuracy of neuroimaging for bvFTD. In other words, the value of neuroimaging for the differentiation of bvFTD among subjects with an acquired behavioral changes is unknown.

Therefore, the aim of this study was to measure the diagnostic accuracy of MRI and additional [¹⁸F]FDG-PET for bvFTD in a large and clinically relevant cohort, consisting of subjects with late-onset behavioral changes [16].

MATERIALS AND METHODS

Patients

We selected patients of the Late Onset Frontal lobe (LOF) study, which is a multi-center observational and prospective follow-up study [17]. In the LOF study, 137 patients were prospectively included with a presentation of behavioral changes consisting of apathy, disinhibition, and/or compulsive/stereotypical behavior emerging between 45 and 75 years of age. The patients had been referred to the VU medical center Alzheimer Center and the Department of Old Age Psychiatry of the GGZInGeest, Amsterdam, the Netherlands, between April 2011 and June 2013 [18]. Patients were included in the study when behavioral complaints dominated the presentation and when they had a score of≥11 on the Frontal Behavioural Inventory (FBI) [19] or a score of≥10 on the Stereotypy Rating Inventory (SRI) [20]. All patients received full neurological and psychiatric examination at baseline and at two-year-follow-up. Cognitive screening tests included the Mini-Mental State Examination (MMSE) [21] and the Frontal Assessment Battery (FAB) [22]. Psychiatric evaluation included applying the Montgomery Aberg Depression Rating Scale (MADRS) [23] for depressive symptoms, the positive and negative symptom scale for psychotic symptoms (PANSS) [24], and the MINI-PLUS Diagnostic interview [25] to assess primary psychiatric disorders. Additional information of the assessment is described in the LOF study design [17]. The local institutional review board approved this study and a written informed consent was obtained from all participants.

Neuroimaging

All patients received a brain MR (3T Signa HDxt whole-body MRI system GE Medical Systems Milwaukee, WI, USA) using an 8-channel head coil with foam padding to restrict head motion. Image acquisition included an established standard MRI protocol for memory clinic patients [17]. A sagittal 3D heavily T1-weighted gradient-echo sequence with coronal reformats, a sagittal 3D T2-weighted fluid-attenuated inversion-recovery (FLAIR) fast spin-echo with axial reformats, a transverse T2-weighted fast spin-echo, a transverse T2^* susceptibility sequence, and diffusion weighted imaging/EPI. All sequences were performed using 3 mm slices/reformats with 1 mm in-plane resolution and provided whole brain coverage [18]. An experienced neuroradiologist (FB or MPW), unblinded for the study design and age but blinded to the patients’ symptoms and medical history, evaluated the images with respect to global cortical atrophy (GCA) using a 4-point scale (0 = no cortical atrophy; 1 = mild atrophy, opening of sulci; 2 = moderate atrophy, volume loss of gyri; 3 = severe atrophy, ‘knife blade’ atrophy), medial temporal lobe atrophy (MTA) using a 5-point scale (0 = no atrophy; 1 = only widening of choroid fissure, 2 = also widening of temporal horn of lateral ventricle; 3 = moderate loss of hippocampal volume; 4 = severe volume loss of hippocampus), and white matter hyperintensities (WMH) (Fazekas) using 4 point scale (0 = None or a single punctate WMH lesion; 1 = Multiple punctate lesions; 2 = Beginning confluences of lesions; 3 = Large confluent lesions), according to established and validated visual rating scales [26 –28]. In addition, the neuroradiologist was asked to classify the MRI as consistent with frontotemporal dementia or not. When frontal and/or anterior temporal atrophy on MRI was present and discrepant with global cortical atrophy, this was considered as consistent with frontotemporal dementia.

In case of normal MRI findings or doubt on the interpretation of the abnormalities being explanatory for the behavioral changes, an [¹⁸F]FDG-PET-scan was made. [¹⁸F]FDG-PET-scans were made on an ECAT EXACT HR+ scanner (Siemens/CTI, Knoxville, USA). 185 MBq [¹⁸F]FDG was injected after subjects rested for ten minutes with minimal noise and eyes closed in a dimly lit room. PET scans were acquired 45 min after injection during 15 min (3 frames of 5 min). [¹⁸F]FDG-PET-scans were assessed visually and interpreted by an experienced nuclear medicine physician (BB) on frontal and/or anterior temporal hypometabolism based on the summed images of all the frames, unblinded for the study design and age, blinded to the patients’ symptoms, complaints, and medical history.

Diagnostic procedure

A consensus diagnosis between the neurologist and the psychiatrist was made based upon the relevant clinical information and additional investigations, including results of cerebrospinal fluid biomarkers, MRI and [¹⁸F]FDG-PET at baseline. All patients with a positive family history for early-onset dementia were referred for clinical genetic counseling. If deemed appropriate, genetic screening included the MAPT, GRN, PSEN1, and APP genes. In all subjects of whom DNA was available (n = 137) C9orf72 repeat expansion was tested. After two years of follow-up, neuropsychiatric examination, neuropsychological examination, and the brain MRI were repeated, followed by establishment of the final multidisciplinary diagnosis. Diagnoses were based on the published consensus guidelines for dementia and the primary psychiatric diagnoses were based on current psychiatric criteria [4 , 29–33]. Based on the follow-up diagnosis, patients were divided into two groups: having bvFTD (defined as probable and definite bvFTD) or not having bvFTD (non-bvFTD). All probable bvFTD patients at follow-up had neuroimaging consistent with FTD. Subsequently the sensitivity and specificity of the baseline MRI and additional [¹⁸F]FDG-PET were calculated, using the follow-up diagnosis as the gold standard. From the original LOF cohort of 137 cases, a total of 26 patients were excluded. Three patients were excluded from the final analysis with a two-year follow-up diagnosis of possible bvFTD, whereas three patients died without postmortem verification or a clear clinical diagnosis. Fifteen patients were lost to follow-up, whereby most of these participants withdrew from the study. Five cases were excluded based on insufficient quality of their baseline MRI that had been performed elsewhere.

Statistical analysis

Data analysis was performed using IBM SPSS statistics version 20.0 (IBM SPSS Statistics, Armonk, NY). Independent samples t-test for continuous measures, Chi-square tests for categorical variables and Mann-Whitney U test for variables that are not normally distributed were performed to compare age, gender, duration of onset symptoms at presentation, education in years, MMSE, FAB, FBI, SRI, and MADRS between the two groups. MRI visual rating scores comparison was done with the Chi-square test for trend. Sensitivities and specificities for the MRI scans of the brain and [¹⁸F]FDG-PET-scans were calculated with cross tables with 95% confidence interval. The statistical significance was set to p-value <0.05.

RESULTS

Clinical and demographical characteristics

The two-year-follow-up multidisciplinary diagnoses consisted of probable/definite bvFTD in 27 patients (24%) and non-bvFTD in 84 patients (Table 1). Of the 27 patients in probable/definite bvFTD group, 4 patients were diagnosed with definite bvFTD consisting of two C9orf72 hexanucleotide repeat expansion, one progranulin mutation and a histopathological-confirmed tauopathy. The non-bvFTD group consisted of patients diagnosed with other types of dementia (n = 28, 25%), primary psychiatric disorders (n = 44, 40%), and other neurological diseases (n = 7, 6%). The most common neurodegenerative diagnoses were Alzheimer’s disease (AD) (n = 7), vascular cognitive impairment (n = 6), progressive supranuclear palsy (n = 4), and dementia with Lewy bodies (n = 4). The most common primary psychiatric diagnoses were major depression (n = 11) and bipolar disorder (n = 6). Other neurological disorders were Parkinson’s disease (n = 2), multiple sclerosis (n = 2), histopathologically-confirmed limbic encephalitis (n = 1), and post-anoxic encephalopathy (n = 1). Their clinical and demographical characteristics are shown in Table 2. The patients with bvFTD diagnosis after two-year-follow-up were more often male and presented more often with stereotypical symptoms than the non-bvFTD group.

Procedure neuroimaging

The included 111 cases all received an MRI scan at baseline and 74 cases received additional [¹⁸F]FDG-PET-scan. Of the 74 cases with a additional [¹⁸F]FDG-PET-scan, nine cases had MRI scans with borderline abnormalities consistent with bvFTD, whereas 64 were considered as inconclusive (no abnormalities). Of the 37 patients without an [¹⁸F]FDG-PET-scan, sixteen MRI scans showed abnormalities consistent with bvFTD, and in nineteen cases the MRI findings were inconclusive, however the patient refused or there were technical problems with the [¹⁸F]FDG-PET-scanner. In two patients the MRI scan showed findings suggestive of an alternative clinical diagnosis (multiple sclerosis and vascular cognitive impairment).

Neuroimaging for probable/definite bvFTD

Of the 27 patients with a diagnosis of probable/definite bvFTD at two-year-follow-up, 19 patients had MRI features consistent with bvFTD at baseline and 10 patients revealed frontotemporal hypometabolism on the additional [¹⁸F]FDG-PET-scan at baseline. Of these 10 patients, 8 patients showed no clear abnormalities on MRI at baseline and these were considered as inconclusive. Two out of the 27 patients with probable/definite bvFTD at two-year-follow-up had abnormalities consistent with bvFTD on MRI and on [¹⁸F]FDG-PET at baseline. The MRI visual ratings scores at baseline are described in Table 3, showing a significantly higher MTA and GCA scores in bvFTD compared to the non-FTD group. For probable/definite bvFTD patients, on inspection changes on MRI and the additional [¹⁸F]FDG-PET were found predominantly on the right side of the brain and more often in the temporal lobe than in the frontal lobe.

Sensitivity and specificity of MRI and additional [¹⁸F]FDG-PET-scan

The sensitivity of frontotemporal atrophy on the baseline MRI for bvFTD was 70% (95% CI 52–85%) and the specificity was 93% (95% CI 86–97%). This yielded positive and negative predictive values of 76% (95% CI 57–90%) and 91% (95% CI 84–96%). The sensitivity for the additional [¹⁸F]FDG-PET-scan at baseline was 90% (95% CI 66–100%) and the specificity 68% (95% CI 56–79%). This yielded positive and negative predictive values of 33% (95% CI 18–51%) and 98% (95% CI 90–100%). The sensitivity of combined neuroimaging in bvFTD, MRI and additional [¹⁸F]FDG-PET-scan together, was 96% (95% CI 85–100%) and the specificity was 73% (95% CI 63–81%). The positive and negative predictive values of neuroimaging in a cohort with behavioral changes for bvFTD were 53% (95% CI 40–67%) and 98% (95% CI 93–100%).

False negative cases

Eight patients showed no frontotemporal atrophy on the MRI at baseline, but were diagnosed with probable/definite bvFTD at two-year-follow-up. Among these patients, 3 patients were diagnosed with definite bvFTD; the first patient had a progranulin mutation with asymmetric atrophy in the right temporoparietal region on the MRI, reported as more consistent with AD. Another patient with a C9orf72 expansion hexanucleotide repeat showed mild hippocampal atrophy only on the left side (MTA grade 1) and no global atrophy (See Fig. 1C). The third patient with autopsy-based definite bvFTD, had generalized frontoparietal atrophy (GCA grade 1) and asymmetric atrophy of the temporal lobe right more than left, reported also more consistent with AD. The other five patients were diagnosed with probable bvFTD, of whom in 3 cases the neuroradiologist reported that the MRI was more consistent with another type of dementia (AD or vascular cognitive impairment) and two patients had no atrophy or GCA grade 1. For [¹⁸F]FDG-PET, one patient diagnosed with probable bvFTD had no hypometabolism on the [¹⁸F]FDG-PET-scan at baseline.

False-positive cases

Six patients of the non-FTD group demonstrated frontotemporal atrophy on the baseline MRI. These patients had bipolar disorder (n = 2), Parkinson’s disease (n = 1), post-anoxic encephalopathy (n = 1), semantic dementia (n = 1), and behavioral changes due to relational problems (n = 1). This group had predominantly lower visual rating scores at baseline; a description is shown in Table 3. Twenty patients with frontal, anterior temporal, or frontotemporal hypometabolism on the baseline [¹⁸F]FDG-PET-scan were diagnosed with a different disorder than probable/definite bvFTD. This group consisted of twelve patients with a primary psychiatric disorder; the alternative diagnosis was minor/major depressive disorder (n = 5) (MDD) (see Fig. 1A), personality disorders (n = 3), bipolar disorder (n = 1), schizophrenia (n = 1), and relational problems (n = 2). These patients with primary psychiatric disorders had mainly decreased uptake in the frontal and temporal lobe, mostly bilaterally. Some patients also showed parietal hypometabolism mainly on the right side. Six patients were diagnosed with dementia other than bvFTD, including patients with AD (n = 1), semantic dementia (n = 3), progressive supranuclear palsy (n = 1), and cortical basal syndrome (n = 1). The patient with AD showed predominately hypometabolism of the left temporal and frontal lobe, with less hypometabolism in the posterior cingulate cortex. Other AD patients (n = 4) showed mainly hypometabolism in bilateral parietal lobe with no or less frontotemporal hypometabolism. Diagnoses at two-year-follow-up for patients with positive and negative neuroimaging are presented in Table 4.

DISCUSSION

We found a sensitivity of frontotemporal changes on MRI for bvFTD of 70% with a specificity of 93%. The additional [¹⁸F]FDG-PET, when the MRI was inconclusive, had a sensitivity of 90% at the cost of a lower specificity of 68%. The combination of MRI and [¹⁸F]FDG-PET-scan, had a sensitivity of 96% and a specificity of 73%.

The current study found a moderate sensitivity for frontotemporal changes on MRI for bvFTD among patients with acquired behavioral changes. This finding is predominately driven by the absence of structural abnormalities with respect to visual rating scales on baseline MRI in patients with probable bvFTD [34]. Moreover, 3 cases with a definite bvFTD had atypical findings on MRI [35, 36]. In a previous study including clinical frontotemporal lobar degeneration syndrome cases, it was found that only 50% had abnormalities on the MRI at presentation using postmortem confirmed diagnosis as gold standard [6, 8]. Assessing frontotemporal changes in a memory clinic population, 53% of the bvFTD patients had an abnormal MRI at presentation [6]. One study among patients with a C9orf72 hexanucleotide repeat expansion reported a very low sensitivity of 13% for frontotemporal changes on MRI [37]. Our results seem to be more consistent with a sensitivity of 72% of MRI in a different cohort of patients carrying a C9orf72 hexanucleotide repeat expansion [38] and a sensitivity of 75% in clinically defined bvFTD [39]. Overall, the sensitivity for MRI abnormalities varies and is moderate in different studies. Our findings suggest that the current clinical consensus criteria for bvFTD might be modified, and include the atrophy patterns described in known pathogenic mutations. Furthermore, the absence of atrophy on MRI in the early stage of bvFTD stresses the need for more sensitive biomarkers for bvFTD.

In contrast, we found a high specificity of MRI for bvFTD, indicating that frontotemporal atrophy on MRI is suggestive of a neurodegenerative cause. Moreover, this result is consistent with the visual rating scores of global cortical atrophy and especially hippocampal atrophy in this study, which were significantly higher in the true-positive group and false-negative group compared to the non-FTD group. In addition, the current findings also seem in line with previous studies that found higher MTA scores in FTD [40 –42]. Taken together, MTA and GCA scores appear to be a good indicator for a neurodegenerative disorder in a late-onset behavioral change cohort, and in this study for bvFTD. However, these visual rating scores cannot be applied in the differentiation between bvFTD and AD. Biomarkers aiming at detecting underlying amyloid pathology, such as amyloid PET imaging [43, 44] and cerebrospinal fluid amyloid beta [45] could serve this goal.

Frontotemporal changes on [¹⁸F]FDG-PET had a high sensitivity for bvFTD, similar to previous studies [5, 46]. An explanation for these results might by the early synaptic dysfunction in the frontal and temporal regions in bvFTD [47], which is measured by [¹⁸F]FDG-PET [48]. In contrast, other studies found lower sensitivities for [¹⁸F]FDG-PET in patients with a C9orf72 hexanucleotide repeat expansion [37, 38]. This might be due to the atypical slow progression of this phenotype of bvFTD [49]. In addition, we found that a group of bvFTD patients without MRI changes had metabolism changes on the [¹⁸F]FDG-PET-scan. This finding is an argument for the suggestion that absence of sufficient atrophy could be an early stage of the disease. Therefore, [¹⁸F]FDG-PET seems a sensitive marker for early detection of bvFTD.

However, in our clinically representative cohort of patients presenting with behavioral changes, we found that the specificity of [¹⁸F]FDG-PET was relatively low due to false positive scans in the primary psychiatric cases and cases with various other types of dementia. Moreover, 40% of the falsely positive rated scans were of patients with primary psychiatric disorders. This also may be explained by the synaptic dysfunction in primary psychiatric disorders in similar anatomic regions as bvFTD [10 –15]. Our findings indicate that the interpretation of frontotemporal hypometabolism on [¹⁸F]FDG-PET should always be accompanied by a thorough clinical evaluation, such as a psychiatric and neurological examination.

Another finding of the present study was the high sensitivity and a suboptimal specificity for the combination of MRI and additional [¹⁸F]FDG-PET-scan. The combined neuroimaging causes an increase in the diagnostic accuracy for bvFTD compared with the both individual imaging technics. Conclusively, these results support the notion of clinical practice to perform MRI investigation first in patients with a behavioral changes and clinically bvFTD, and if inconclusive for bvFTD, to perform an additional [¹⁸F]FDG-PET-scan. Moreover, coverage by Centers for Medicare en Medicaid Services for [¹⁸F]FDG-PET for dementia requires diagnostic structural imaging first.

It could be discussed that semantic dementia (n = 3), progressive supranuclear palsy (n = 1), and cortical basal syndrome (n = 1) patients had false positive neuroimaging, since these disorders are all part of the frontotemporal lobar degeneration spectrum and have partially overlapping atrophy and hypometabolism patterns [50, 51]. This is mainly related to our study design, that was specifically aimed at detecting bvFTD according to the neuroradiologist’s visual rating. From a clinical perspective, we might therefore have underestimated the specificity of MRI and [¹⁸F]FDG-PET-scan. Even when including these patients as FTD cases, specificity of MRI would not have surpassed 93% and for the [¹⁸F]FDG-PET-scan 74%.

Considerable strengths of our study are the large and clinically well-phenotyped cohort and its study design. Patients were included based on their symptoms, thereby closely resembling daily practice in neuropsychiatric clinics. Another important strength is the blinding of the neuroimaging raters, although they were aware of the study design. Thus, we have attempted to avoid over-interpretation of the neuroimaging investigations.

A limitation of this study is the rather limited number of cases with a definite FTD diagnosis based on autopsy and genetic testing. For the gold standard definition, we had to rely on the clinical consensus diagnosis and additional investigations at two-year-follow-up. We acknowledge that excluding 3 cases with a two-year-follow-up diagnosis of possible bvFTD could have influenced our results. However, we consider possible bvFTD not as a final diagnosis, which is corresponding to the study design of the LOF study. Moreover, 76% of the patients included in the LOF study met the criteria for possible bvFTD and most patients did not have bvFTD. So, although an alternative psychiatric diagnosis was lacking at two years of follow-up, it remains questionable whether these 3 cases have bvFTD. These patients with a two-year-follow-up diagnose of possible bvFTD might be considered as benign bvFTD phenocopy syndrome; however, due to the open discussion on this issue, we had even more reason to exclude these patients. Furthermore, one of the weaknesses of our study is the potential selection bias for the patients undergoing additional [¹⁸F]FDG-PET-scan, because of refusal in 20%. However, because of the equal diagnostic distribution in these cases (9 neurodegenerative disorders, 8 primary psychiatric disorders, and 2 neurological disorders), we do not expect a large effect on the results of our study. Another source of uncertainty is the reliability of visual rating of the MRI and [¹⁸F]FDG-PET, in combination with the lacking data on interrater variability and interrater agreement of the assessment of the neuroimaging. This limits the accuracy of the present results to a certain degree, and it gives a possible explanation of the finding that the correctly assessed scans in our study were with vast atrophy and high visual rating grades and the false positive scans showed less atrophy and lower visual rating grades. Although clinical classification of neuroimaging can be poor [52], in the majority of studies visual rating is reliable and correlates with atrophy of the dementia pathology [53].

Our study shows that atypical MRI atrophy patterns should not preclude genetic testing in case of suspected bvFTD. On the other hand, a positive [¹⁸F]FDG-PET-scan scan does not exclude a primary psychiatric disorder and should not be overinterpretated toward bvFTD. Therefore, genetic testing and long-term follow-up, by a neurologist and psychiatrist, are of high relevance in the diagnosis of bvFTD. Nevertheless, the search for additional and disease specific biomarkers might further increase the diagnostic specificity of bvFTD.

Footnotes

ACKNOWLEDGMENTS

E.G.B. Vijverberg had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

E.G.B. Vijverberg is supported by the VUmc Alzheimer center. The Alzheimer Center receives unrestricted funding from various sources through the VUmc Fonds. The funding sources had no role in design and conduct of the study, data collection, data analysis, data interpretation, or in writing or approval of this report.

Authors’ disclosures available online ().

References

Gossink

, Dols

, Kerssens

, Krudop

, Kerklaan

, Scheltens

, Stek

, Pijnenburg

YAL

(2016) Psychiatric diagnoses underlying the phenocopy syndrome of behavioural variant frontotemporal dementia. J Neurol Neurosurg Psychiatry 87, 64–68.

Ducharme

, Price

, Larvie

, Dougherty

, Dickerson

(2015) Clinical approach to the differential diagnosis between behavioral variant frontotemporal dementia and primary psychiatric disorders. Am J Psychiatry 172, 827–837.

Woolley

, Khan

, Murthy

, Miller

, Rankin

(2011) The diagnostic challenge of psychiatric symptoms in neurodegenerative disease. J Clin Psychiatry 72, 126–133.

Rascovsky

, Hodges

, Knopman

, Mendez

, Kramer

, Neuhaus

, Van Swieten

, Seelaar

, Dopper

EGP

, Onyike

, Hillis

, Josephs

, Boeve

, Kertesz

, Seeley

, Rankin

, Johnson

, Gorno-Tempini

M-L

, Rosen

, Prioleau-Latham

, Lee

, Kipps

, Lillo

, Piguet

, Rohrer

, Rossor

, Warren

, Fox

, Galasko

, Salmon

, Black

, Mesulam

, Weintraub

, Dickerson

, Diehl-Schmid

, Pasquier

, Deramecourt

, Lebert

, Pijnenburg

, Chow

, Manes

, Grafman

, Cappa

, Freedman

, Grossman

, Miller

(2011) Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia. Brain 134, 2456–2477.

Mendez

, Shapira

, McMurtray

, Licht

, Miller

(2007) Accuracy of the clinical evaluation for frontotemporal dementia. Arch Neurol 64, 830–835.

Pijnenburg

YAL

, Mulder

, Van Swieten

, Uitdehaag

BMJ

, Stevens

, Scheltens

, Jonker

(2008) Diagnostic accuracy of consensus diagnostic criteria for frontotemporal dementia in a memory clinic population. Dement Geriatr Cogn Disord 25, 157–164.

Kipps

, Davies

, Mitchell

, Kril

, Halliday

, Hodges

(2007) Clinical significance of lobar atrophy in frontotemporal dementia: Application of an MRI visual rating scale. Dement Geriatr Cogn Disord 23, 334–342.

Knopman

, Boeve

, Parisi

, Dickson

, Smith

, Ivnik

, Josephs

, Petersen

(2005) Antemortem diagnosis of frontotemporal lobar degeneration. Ann Neurol 57, 480–488.

Kerklaan

, van Berckel

BNM

, Herholz

, Dols

, van der Flier

, Scheltens

, Pijnenburg

YAL

(2014) The added value of 18-fluorodeoxyglucose-positron emission tomography in the diagnosis of the behavioral variant of frontotemporal dementia. Am J Alzheimers Dis Other Demen 29, 607–613.

10.

Kimbrell

, Ketter

, George

, Little

, Benson

, Willis

, Herscovitch

, Post

(2002) Regional cerebral glucose utilization in patients with a range of severities of unipolar depression. Biol Psychiatry 51, 237–252.

11.

van Haren

NEM

, Schnack

, Cahn

, van den Heuvel

, Lepage

, Collins

, Evans

, Hulshoff Pol

, Kahn

(2011) Changes in cortical thickness during the course of illness in schizophrenia. Arch Gen Psychiatry 68, 871–880.

12.

Sheline

, Wang

, Gado

, Csernansky

, Vannier

(1996) Hippocampal atrophy in recurrent major depression. Proc Natl Acad Sci U S A 93, 3908–3913.

13.

Ellison-Wright

, Bullmore

(2010) Anatomy of bipolar disorder and schizophrenia: A meta-analysis. Schizophr Res 117, 1–12.

14.

van Tol

M-J

, van der Wee

NJA

, van den Heuvel

, Nielen

MMA

, Demenescu

, Aleman

, Renken

, van Buchem

, Zitman

, Veltman

(2010) Regional brain volume in depression and anxiety disorders. Arch Gen Psychiatry 67, 1002–1011.

15.

Hosokawa

, Momose

, Kasai

(2009) Brain glucose metabolism difference between bipolar and unipolar mood disorders in depressed and euthymic states. Prog Neuropsychopharmacol. Biol Psychiatry 33, 243–250.

16.

Krudop

, Kerssens

, Dols

, Prins

, Möller

, Schouws

, van der Flier

, Scheltens

, Sikkes

, Stek

, Pijnenburg

YAL

(2015) Identifying bvFTD within the wide spectrum of late onset frontal lobe syndrome: A clinical approach. Am J Geriatr Psychiatry 23, 1056–1066.

17.

Krudop

, Kerssens

, Dols

, Prins

, Möller

, Schouws

, van der Flier

, Scheltens

, Sikkes

, Stek

, Pijnenburg

YAL

(2013) Building a new paradigm for the early recognition of behavioral variant frontotemporal dementia: Late onset frontal lobe syndrome study. Am J Geriatr Psychiatry 22, 1–6.

18.

van der Flier

, Pijnenburg

YAL

, Prins

, Lemstra

, Bouwman

, Teunissen

, van Berckel

BNM

, Stam

, Barkhof

, Visser

, van Egmond

, Scheltens

(2014) Optimizing patient care and research: The Amsterdam Dementia Cohort. J Alzheimers Dis 41, 313–327.

19.

Kertesz

, Davidson

, Fox

(2000) The Frontal Behavioral Inventory in the differential diagnosis of frontotemporal dementia. J Int Neuropsychol Soc 6, 460–468.

20.

Shigenobu

, Ikeda

, Fukuhara

, Maki

, Hokoishi

, Nebu

, Yasuoka

, Komori

, Tanabe

(2002) The Stereotypy Rating Inventory for frontotemporal lobar degeneration. Psychiatry Res 110, 175–187.

21.

Folstein

, Folstein

, McHugh

(1975) “Mini-mental state”: A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 12, 189–198.

22.

Dubois

, Slachevsky

, Litvan

, Pillon

(2000) The FAB: A Frontal Assessment Battery at bedside. Neurology 55, 1621–1626.

23.

Montgomery

, Asberg

(1979) A new depression scale designed to be sensitive to change. Br J Psychiatry 134, 382–389.

24.

Kay

, Fiszbein

, Opler

(1987) The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophr Bull 13, 261–276.

25.

Sheehan

, Lecrubier

, Sheehan

(1998) The Mini-International Neuropsychiatric Interview (MINI): The development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry 59, 22–33.

26.

Scheltens

, Launer

, Barkhof

, Weinstein

, van Gool

(1995) Visual assessment of medial temporal lobe atrophy on magnetic resonance imaging: Interobserver reliability. J Neurol 242, 557–560.

27.

Koedam

ELGE

, Lehmann

, van der Flier

, Scheltens

, Pijnenburg

YAL

, Fox

, Barkhof

, Wattjes

(2011) Visual assessment of posterior atrophy development of a MRI rating scale. Eur Radiol 21, 2618–2625.

28.

Fazekas

, Chawluk

, Alavi

, Hurtig

, Zimmerman

(1987) MR signal abnormalities at 1.5 T in Alzheimer’s dementia and normal aging. AJR Am J Roentgenol 149, 351–356.

29.

Gorno-Tempini

, Hillis

, Weintraub

, Kertesz

, Mendez

, Cappa

, Ogar

, Rohrer

, Black

, Boeve

, Manes

, Dronkers

, Vandenberghe

, Rascovsky

, Patterson

, Miller

, Knopman

, Hodges

, Mesulam

, Grossman

(2011) Classification of primary progressive aphasia and its variants. Neurology 76, 1006–1014.

30.

McKhann

, Knopman

, Chertkow

, Hyman

, Jack

Jr , Kawas

, Klunk

, Koroshetz

, Manly

, Mayeux

, Mohs

, Morris

, Rossor

, Scheltens

, Carrillo

, Thies

, Weintraub

, Phelps

(2011) 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 7, 263–269.

31.

Roman

, Tatemichi

, Erkinjuntti

, Cummings

, Masdeu

, Garcia

, Amaducci

, Orgogozo

, Brun

, Hofman

(1993) Vascular dementia: Diagnostic criteria for research studies. Report of the NINDS-AIREN International Workshop. Neurology 43, 250–260.

32.

McKeith

, Dickson

, Lowe

, Emre

, O’Brien

, Feldman

, Cummings

, Duda

, Lippa

, Perry

, Aarsland

, Arai

, Ballard

, Boeve

, Burn

, Costa

, Del Ser

, Dubois

, Galasko

, Gauthier

, Goetz

, Gomez-Tortosa

, Halliday

, Hansen

, Hardy

, Iwatsubo

, Kalaria

, Kaufer

, Kenny

, Korczyn

, Kosaka

, Lee

VM-Y

, Lees

, Litvan

, Londos

, Lopez

, Minoshima

, Mizuno

, Molina

, Mukaetova-Ladinska

, Pasquier

, Perry

, Schulz

, Trojanowski

, Yamada

, Consortium on DLB (2005) Diagnosis and management of dementia with Lewy bodies: Third report of the DLB Consortium. Neurology 65, 1863–1872.

33.

American Psychiatric Association (2000) Diagnostic and Statistical Manual of Mental Disorders, 4th edition Text Revision (DSM-IV-TR), American Psychiatric Association, Washington, DC.

34.

Gregory

, Serra-Mestres

, Hodges

(1999) Early diagnosis of the frontal variant of frontotemporal dementia: How sensitive are standard neuroimaging and neuropsychologic tests? Neuropsychiatry Neuropsychol Behav Neurol 12, 128–135.

35.

Beck

, Rohrer

, Campbell

, Isaacs

, Morrison

, Goodall

, Warrington

, Stevens

, Revesz

, Holton

, Al-Sarraj

, King

, Scahill

, Warren

, Fox

, Rossor

, Collinge

, Mead

(2008) A distinct clinical, neuropsychological and radiological phenotype is associated with progranulin gene mutations in a large UK series. Brain 131, 706–720.

36.

Whitwell

, Boeve

, Weigand

, Senjem

, Gunter

, Baker

, DeJesus-Hernandez

, Knopman

, Wszolek

, Petersen

, Rademakers

, Jack

Jr , Josephs

(2015) Brain atrophy over time in genetic and sporadic frontotemporal dementia: A study of 198 serial magnetic resonance images. Eur J Neurol 22, 745–752.

37.

Devenney

, Hornberger

, Irish

, Mioshi

, Burrell

, Tan

, Kiernan

, Hodges

(2014) Frontotemporal dementia associated with the C9ORF72 mutation: A unique clinical profile. JAMA Neurol 71, 331–339.

38.

Solje

, Aaltokallio

, Koivumaa-Honkanen

, Suhonen

, Moilanen

, Kiviharju

, Traynor

, Tienari

, Hartikainen

, Remes

(2015) The phenotype of the C9ORF72 expansion carriers according to revised criteria for bvFTD. PLoS One 10, e0131817–e0131819.

39.

Kipps

, Davies

, Mitchell

, Kril

, Halliday

, Hodges

(2007) Clinical significance of lobar atrophy in frontotemporal dementia: Application of an MRI visual rating scale. Dement Geriatr Cogn Disord 23, 334–342.

40.

van de Pol

, Hensel

, van der Flier

, Visser

P-J

, Pijnenburg

YAL

, Barkhof

, Gertz

, Scheltens

(2006) Hippocampal atrophy on MRI in frontotemporal lobar degeneration and Alzheimer’s disease. J Neurol Neurosurg Psychiatry 77, 439–442.

41.

Frisoni

, Laakso

, Beltramello

, Geroldi

, Bianchetti

, Soininen

, Trabucchi

(1999) Hippocampal and entorhinal cortex atrophy in frontotemporal dementia and Alzheimer’s disease. Neurology 52, 91–91.

42.

Galton

, Gomez-Anson

, Antoun

(2001) Temporal lobe rating scale: Application to Alzheimer’s disease and frontotemporal dementia. J Neurol 70, 165–173.

43.

Kobylecki

, Langheinrich

, Hinz

, Vardy

ERLC

, Brown

, Martino

, Haense

, Richardson

, Gerhard

, Anton-Rodriguez

, Snowden

, Neary

, Pontecorvo

, Herholz

(2015) 18F-Florbetapir PET in patients with frontotemporal dementia and Alzheimer disease. J Nucl Med 56, 386–391.

44.

Rabinovici

, Furst

, O’Neil

, Racine

, Mormino

, Baker

, Chetty

, Patel

, Pagliaro

, Klunk

, Mathis

, Rosen

, Miller

, Jagust

(2007) 11C-PIB PET imaging in Alzheimer disease and frontotemporal lobar degeneration. Neurology 68, 1205–1212.

45.

Schoonenboom

NSM

, Reesink

, Verwey

, Kester

, Teunissen

, van de Ven

, Pijnenburg

YAL

, Blankenstein

, Rozemuller

, Scheltens

, van der Flier

(2012) Cerebrospinal fluid markers for differential dementia diagnosis in a large memory clinic cohort. Neurology 78, 47–54.

46.

Foster

, Heidebrink

, Clark

, Jagust

, Arnold

, Barbas

, DeCarli

, Scott Turner

, Koeppe

, Higdon

, Minoshima

(2007) FDG-PET improves accuracy in distinguishing frontotemporal dementia and Alzheimer’s disease. Brain 130, 2616–2635.

47.

Lipton

, Cullum

, Satumtira

, Sontag

, Hynan

, White

, Bigio

(2001) Contribution of asymmetric synapse loss to lateralizing clinical deficits in frontotemporal dementias. Arch Neurol 58, 1233–1239.

48.

Kadekaro

, Crane

, Sokoloff

(1985) Differential effects of electrical stimulation of sciatic nerve on metabolic activity in spinal cord and dorsal root ganglion in the rat. Proc Natl Acad Sci U S A 82, 6010–6013.

49.

Khan

, Yokoyama

, Takada

, Sha

, Rutherford

, Fong

, Karydas

, Wu

, Ketelle

, Baker

, Hernandez

, Coppola

, Geschwind

, Rademakers

, Lee

, Rosen

, Rabinovici

, Seeley

, Rankin

, Boxer

, Miller

(2012) Atypical, slowly progressive behavioural variant frontotemporal dementia associated with C9ORF72 hexanucleotide expansion. J Neurol Neurosurg Psychiatry 83, 358–364.

50.

Cairns

, Bigio

, Mackenzie

IRA

, Neumann

, Lee

VMY

, Hatanpaa

, White

, Schneider

, Grinberg

, Halliday

, Duyckaerts

, Lowe

, Holm

, Tolnay

, Okamoto

, Yokoo

, Murayama

, Woulfe

, Munoz

, Dickson

, Ince

, Trojanowski

, Mann

DMA

(2007) Neuropathologic diagnostic and nosologic criteria for frontotemporal lobar degeneration: Consensus of the Consortium for Frontotemporal Lobar Degeneration. Acta Neuropathol 114, 5–22.

51.

Mackenzie

IRA

, Neumann

, Bigio

, Cairns

, Alafuzoff

, Kril

, Kovacs

, Ghetti

, Halliday

, Holm

, Ince

, Kamphorst

, Revesz

, Rozemuller

AJM

, Kumar-Singh

, Akiyama

, Baborie

, Spina

, Dickson

, Trojanowski

, Mann

DMA

(2009) Nomenclature and nosology for neuropathologic subtypes of frontotemporal lobar degeneration: An update. Acta Neuropathol 119, 1–4.

52.

Suárez

, Tartaglia

, Vitali

, Erbetta

, Neuhaus

, Laluz

, Miller

(2009) Characterizing radiology reports in patients with frontotemporal dementia. Neurology 73, 1073–1074.

53.

Harper

, Fumagalli

, Barkhof

, Scheltens

, O’Brien

, Bouwman

, Burton

, Rohrer

, Fox

, Ridgway

, Schott

(2016) MRI visual rating scales in the diagnosis of dementia: Evaluation in 184 post-mortem confirmed cases. Brain 139(Pt 4), 1211–1225.

Diagnostic Accuracy of MRI and Additional [ 18 F]FDG-PET for Behavioral Variant Frontotemporal Dementia in Patients with Late Onset Behavioral Changes

Abstract

Keywords

INTRODUCTION

MATERIALS AND METHODS

Patients

Neuroimaging

Diagnostic procedure

Statistical analysis

RESULTS

Clinical and demographical characteristics

Procedure neuroimaging

Neuroimaging for probable/definite bvFTD

Sensitivity and specificity of MRI and additional [18F]FDG-PET-scan

False negative cases

False-positive cases

DISCUSSION

Footnotes

ACKNOWLEDGMENTS

References

Sensitivity and specificity of MRI and additional [¹⁸F]FDG-PET-scan