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The behavioural variant of frontotemporal dementia (bvFTD) is a frequent cause of early-onset dementia. The diagnosis of bvFTD remains challenging because of the limited accuracy of neuroimaging in the early disease stages and the absence of molecular biomarkers, and therefore relies predominantly on clinical assessment. BvFTD shows significant symptomatic overlap with non-degenerative primary psychiatric disorders including major depressive disorder, bipolar disorder, schizophrenia, obsessive-compulsive disorder, autism spectrum disorders and even personality disorders. To date, ∼50% of patients with bvFTD receive a prior psychiatric diagnosis, and average diagnostic delay is up to 5-6 years from symptom onset. It is also not uncommon for patients with primary psychiatric disorders to be wrongly diagnosed with bvFTD. The Neuropsychiatric International Consortium for Frontotemporal Dementia was recently established to determine the current best clinical practice and set up an international collaboration to share a common dataset for future research. The goal of the present paper was to review the existing literature on the diagnosis of bvFTD and its differential diagnosis with primary psychiatric disorders to provide consensus recommendations on the clinical assessment. A systematic literature search with a narrative review was performed to determine all bvFTD-related diagnostic evidence for the following topics: bvFTD history taking, psychiatric assessment, clinical scales, physical and neurological examination, bedside cognitive tests, neuropsychological assessment, social cognition, structural neuroimaging, functional neuroimaging, CSF and genetic testing. For each topic, responsible team members proposed a set of minimal requirements, optimal clinical recommendations, and tools requiring further research or those that should be developed. Recommendations were listed if they reached a ≥ 85% expert consensus based on an online survey among all consortium participants. New recommendations include performing at least one formal social cognition test in the standard neuropsychological battery for bvFTD. We emphasize the importance of 3D-T1 brain MRI with a standardized review protocol including validated visual atrophy rating scales, and to consider volumetric analyses if available. We clarify the role of 18F-fluorodeoxyglucose PET for the exclusion of bvFTD when normal, whereas non-specific regional metabolism abnormalities should not be over-interpreted in the case of a psychiatric differential diagnosis. We highlight the potential role of serum or CSF neurofilament light chain to differentiate bvFTD from primary psychiatric disorders. Finally, based on the increasing literature and clinical experience, the consortium determined that screening for C9orf72 mutation should be performed in all possible/probable bvFTD cases or suspected cases with strong psychiatric features.

IntroductionTimely diagnosis of behavioral variant frontotemporal dementia (bvFTD) remains challenging because it depends on clinical expertise and potentially ambiguous diagnostic guidelines. Recent recommendations highlight the role of multimodal neuroimaging and machine learning methods as complementary tools to address this problem.MethodsWe developed an automatic, cross-center, multimodal computational approach for robust classification of patients with bvFTD and healthy controls. We analyzed structural magnetic resonance imaging and resting-state functional connectivity from 44 patients with bvFTD and 60 healthy controls (across three imaging centers with different acquisition protocols) using a fully automated processing pipeline, including site normalization, native space feature extraction, and a random forest classifier.ResultsOur method successfully combined multimodal imaging information with high accuracy (91%), sensitivity (83.7%), and specificity (96.6%).DiscussionThis multimodal approach enhanced the system's performance and provided a clinically informative method for neuroimaging analysis. This underscores the relevance of combining multimodal imaging and machine learning as a gold standard for dementia diagnosis.

Background: The behavioral variant of frontotemporal dementia (bvFTD) is very heterogeneous in pathology, genetics, and disease course. Unlike Alzheimer's disease, reliable biomarkers are lacking and sporadic bvFTD is often misdiagnosed as a primary psychiatric disorder (PPD) due to overlapping clinical features. Current efforts to characterize and improve diagnostics are centered on the minority of genetic cases. Objective: The multi-center study DIPPA-FTD aims to develop diagnostic and prognostic algorithms to help distinguish sporadic bvFTD from late-onset PPD in its earliest stages. Methods: The prospective DIPPA-FTD study recruits participants with late-life behavioral changes, suspect for bvFTD or late-onset PPD diagnosis with a negative family history for FTD and/or amyotrophic lateral sclerosis. Subjects are invited to participate after diagnostic screening at participating memory clinics or recruited by referrals from psychiatric departments. At baseline visit, participants undergo neurological and psychiatric examination, questionnaires, neuropsychological tests, and brain imaging. Blood is obtained to investigate biomarkers. Patients are informed about brain donation programs. Follow-up takes place 10-14 months after baseline visit where all examinations are repeated. Results from the DIPPA-FTD study will be integrated in a data-driven approach to develop diagnostic and prognostic models. Conclusions: DIPPA-FTD will make an important contribution to early sporadic bvFTD identification. By recruiting subjects with ambiguous or prodromal diagnoses, our research strategy will allow the characterization of early disease stages that are not covered in current sporadic FTD research. Results will hopefully increase the ability to diagnose sporadic bvFTD in the early stage and predict progression rate, which is pivotal for patient stratification and trial design. [ABSTRACT FROM AUTHOR]

Background: Sporadic bvFTD is often misdiagnosed as a primary psychiatric disorder (PPD) due to overlapping clinical features and lack of reliable biomarkers. The multi‐centre study DIPPA‐FTD aims to develop diagnostic‐ and prognostic‐algorithms that can distinguish sporadic bvFTD from late‐onset PPD. The aim of the retrospective DIPPA‐FTD study was to identify the strongest clinical discriminators. Method: DIPPA‐FTD has compiled a retrospective database with 508 sporadic bvFTD and 152 late‐onset PPD cases from five cohorts, making it the largest sporadic FTD cohort to date. Logistic regression models and ROC curve analysis were applied to determine discriminative value per clinical marker in separate subsets; (i) neuropsychological features, (ii) visual brain atrophy rating scales and (iii) serum NfL+GFAP. A global (backward stepwise) logistic regression was also conducted in the most optimal subset that had all markers per modality available. All models were adjusted for age, sex and education when indicated. Result: For marker (i) (bvFTD n = 217, PPD n = 75) higher scores of letter fluency (OR:1.47, p<0.001), global cognitive screening (OR:1.72, p = 0.01) and lower attention scores (OR:0.77, p = 0.05) were significantly associated with increased likelihood of PPD and reached an AUC of 0.77. Marker (ii) visual atrophy rating composite score (bvFTD n = 211, PPD n = 112) reached diagnostic accuracy of 79% and fronto‐insula was the most useful discriminator (AUC 0.80). Analysis of marker (iii) NfL+GFAP (bvFTD n = 275, PPD n = 82) showed that NfL and GFAP levels were significantly higher in bvFTD. Combination of NfL+GFAP yielded highest AUC value (0.88). The combined dataset with all markers variables available (bvFTD n = 120, PPD n = 40) reached an AUC of 0.89. Higher NfL (OR:1.09, p<0.01), more atrophy in fronto‐insula (OR:2.38, p = 0.02) and enlarged mean ventricular space (OR:3.84, p = 0.05) were significant predictors for sporadic bvFTD. Conclusion: Global cognition, letter fluency and attention scores, fronto‐insula brain atrophy and NfL+GFAP have a significant role in discriminating sporadic bvFTD from PPD. Combination of markers can increase diagnostic accuracy in clinical setting. Promising markers identified in this retrospective study will be validated in the prospective DIPPA‐FTD study and integrated in a data‐driven approach to develop diagnostic and prognostic tools, enabling early‐stage diagnosis sporadic bvFTD which is required for trial enrolment. [ABSTRACT FROM AUTHOR]