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The recent commercialisation of the first disease-modifying drugs for Alzheimer's disease emphasises the need for consensus recommendations on the rational use of biomarkers to diagnose people with suspected neurocognitive disorders in memory clinics. Most available recommendations and guidelines are either disease-centred or biomarker-centred. A European multidisciplinary taskforce consisting of 22 experts from 11 European scientific societies set out to define the first patient-centred diagnostic workflow that aims to prioritise testing for available biomarkers in individuals attending memory clinics. After an extensive literature review, we used a Delphi consensus procedure to identify 11 clinical syndromes, based on clinical history and examination, neuropsychology, blood tests, structural imaging, and, in some cases, EEG. We recommend first-line and, if needed, second-line testing for biomarkers according to the patient's clinical profile and the results of previous biomarker findings. This diagnostic workflow will promote consistency in the diagnosis of neurocognitive disorders across European countries.

The recent commercialisation of the first disease-modifying drugs for Alzheimer's disease emphasises the need for consensus recommendations on the rational use of biomarkers to diagnose people with suspected neurocognitive disorders in memory clinics. Most available recommendations and guidelines are either disease-centred or biomarker-centred. A European multidisciplinary taskforce consisting of 22 experts from 11 European scientific societies set out to define the first patient-centred diagnostic workflow that aims to prioritise testing for available biomarkers in individuals attending memory clinics. After an extensive literature review, we used a Delphi consensus procedure to identify 11 clinical syndromes, based on clinical history and examination, neuropsychology, blood tests, structural imaging, and, in some cases, EEG. We recommend first-line and, if needed, second-line testing for biomarkers according to the patient's clinical profile and the results of previous biomarker findings. This diagnostic workflow will promote consistency in the diagnosis of neurocognitive disorders across European countries., The recent commercialisation of the first disease-modifying drugs for Alzheimer's disease emphasises the need for consensus recommendations on the rational use of biomarkers to diagnose people with suspected neurocognitive disorders in memory clinics. Most available recommendations and guidelines are either disease-centred or biomarker-centred. A European multidisciplinary taskforce consisting of 22 experts from 11 European scientific societies set out to define the first patient-centred diagnostic workflow that aims to prioritise testing for available biomarkers in individuals attending memory clinics. After an extensive literature review, we used a Delphi consensus procedure to identify 11 clinical syndromes, based on clinical history and examination, neuropsychology, blood tests, structural imaging, and, in some cases, EEG. We recommend first-line and, if needed, second-line testing for biomarkers according to the patient's clinical profile and the results of previous biomarker findings. This diagnostic workflow will promote consistency in the diagnosis of neurocognitive disorders across European countries.

Introduction Etiological diagnosis of neurocognitive disorders of middle-old age relies on biomarkers, although evidence for their rational use is incomplete. A European task force is defining a diagnostic workflow where expert experience fills evidence gaps for biomarker validity and prioritization. We report methodology and preliminary results. Methods Using a Delphi consensus method supported by a systematic literature review, 22 delegates from 11 relevant scientific societies defined workflow assumptions. Results We extracted diagnostic accuracy figures from literature on the use of biomarkers in the diagnosis of main forms of neurocognitive disorders. Supported by this evidence, panelists defined clinical setting (specialist outpatient service), application stage (MCI-mild dementia), and detailed pre-assessment screening (clinical-neuropsychological evaluations, brain imaging, and blood tests). Discussion The Delphi consensus on these assumptions set the stage for the development of the first pan-European workflow for biomarkers' use in the etiological diagnosis of middle-old age neurocognitive disorders at MCI-mild dementia stages. Highlights Rational use of biomarkers in neurocognitive disorders lacks consensus in Europe. A consensus of experts will define a workflow for the rational use of biomarkers. The diagnostic workflow will be patient-centered and based on clinical presentation. The workflow will be updated as new evidence accrues.

Chronic traumatic encephalopathy (CTE) is associated with a history of repetitive head impacts, such as those sustained through contact sports. Post-mortem assessment has revealed specific neuropathological characteristics related to the condition. The symptoms of CTE typically present several years after exposure and can include mood/behavioural changes, cognitive dysfunction and motor symptoms. The course of CTE can potentially be progressive and debilitating. In this review, we argue, that there is a need for validated neuropathological and clinical criteria in order to detect CTE ante-mortem in the population.

Background: Evidence-based recommendations on the optimal evaluation approach for dementia diagnostics are limited. This impedes a harmonized workup across clinics and nations. Objective: To evaluate the diagnostic performance of a multidisciplinary consensus conference compared to a single clinician approach. Methods: In this prospective study, we enrolled 457 patients with suspected cognitive decline, from two European memory clinics. A diagnostic evaluation was performed at baseline independently in two ways: 1) by a single clinician and 2) at a multidisciplinary consensus conference. A syndrome diagnosis and an etiological diagnosis was made. The confidence in the diagnosis was recorded using a visual analogue scale. An expert panel re-evaluation diagnosis served as reference for the baseline syndrome diagnosis and a 12-24-month follow-up diagnosis for the etiological diagnosis. Results: 439 patients completed the study. We observed 12.5%discrepancy (k=0.81) comparing the baseline syndrome diagnoses of the single clinician to the consensus conference, and 22.3%discrepancy (k=0.68) for the baseline etiological diagnosis. The accuracy of the baseline etiological diagnosis was significantly higher at the consensus conference and was driven mainly by increased accuracy in the MCI group. Confidence in the etiological diagnosis at baseline was significantly higher at the consensus conference (p<0.005), especially for the frontotemporal dementia diagnosis. Conclusion: The multidisciplinary consensus conference performed better on diagnostic accuracy of disease etiology and increased clinicians' confidence. This highlights the importance of a multidisciplinary diagnostic evaluation approach for dementia diagnostics, especially when evaluating patients in the MCI stage.

Chronic traumatic encephalopathy (CTE) is associated with a history of repetitive head impacts, such as those sustained through contact sports. Post-mortem assessment has revealed specific neuropathological characteristics related to the condition. The symptoms of CTE typically present several years after exposure and can include mood/behavioural changes, cognitive dysfunction and motor symptoms. The course of CTE can potentially be progressive and debilitating. In this review, we argue, that there is a need for validated neuropathological and clinical criteria in order to detect CTE ante-mortem in the population.

Background: Patients with dementia have an increased risk of developing epilepsy, es-pecially in patients with vascular dementia and Alzheimer’s disease. In selecting the optimal an-ti-epileptic drug (AED), the possible side effects such as drowsiness and worsening of cognitive function should be taken into consideration, together with co-morbidities and type of epilepsy. Objective: The current systematic review investigates the efficacy, tolerability, and changes in cognitive function after administration of AED in patients with dementia and epilepsy. Methods: We searched six databases, including MEDLINE and CENTRAL, checked reference lists, contacted experts, and searched Google Scholar to identify studies reporting randomized trials. Studies identified were independently screened, data extracted, and quality appraised by two researchers. A narrative synthesis was used to report findings. Results: We included one study with 95 patients with Alzheimer’s disease randomized to either lev-etiracetam, lamotrigine, or phenobarbital. No significant differences were found for efficacy, but patients receiving levetiracetam showed an improvement in mini-mental state examination scores and had fewer adverse events. Conclusion: High-quality evidence in the form of randomized controlled trials to guide clinicians in choosing an AED in patients with dementia and concomitant epilepsy remains scarce. However, levetiracetam has previously been shown to possibly improve cognition in patients with both mild cognitive impairment and Alzheimer’s disease, is better tolerated in the elderly population, and has no clinically relevant interaction with either cholinesterase inhibitors or NMDA receptor antagon-ists. Registration No: The protocol was registered in the PROSPERO database (ID: CRD42020176252).

Background: Evidence-based recommendations on the optimal evaluation approach for dementia diagnostics are limited. This impedes a harmonized workup across clinics and nations. Objective: To evaluate the diagnostic performance of a multidisciplinary consensus conference compared to a single clinician approach. Methods: In this prospective study, we enrolled 457 patients with suspected cognitive decline, from two European memory clinics. A diagnostic evaluation was performed at baseline independently in two ways: 1) by a single clinician and 2) at a multidisciplinary consensus conference. A syndrome diagnosis and an etiological diagnosis was made. The confidence in the diagnosis was recorded using a visual analogue scale. An expert panel re-evaluation diagnosis served as reference for the baseline syndrome diagnosis and a 12-24-month follow-up diagnosis for the etiological diagnosis. Results: 439 patients completed the study. We observed 12.5%discrepancy (k=0.81) comparing the baseline syndrome diagnoses of the single clinician to the consensus conference, and 22.3%discrepancy (k=0.68) for the baseline etiological diagnosis. The accuracy of the baseline etiological diagnosis was significantly higher at the consensus conference and was driven mainly by increased accuracy in the MCI group. Confidence in the etiological diagnosis at baseline was significantly higher at the consensus conference (p<0.005), especially for the frontotemporal dementia diagnosis. Conclusion: The multidisciplinary consensus conference performed better on diagnostic accuracy of disease etiology and increased clinicians' confidence. This highlights the importance of a multidisciplinary diagnostic evaluation approach for dementia diagnostics, especially when evaluating patients in the MCI stage.

Objectives: Mild cognitive impairment (MCI) is associated with an increased risk of further cognitive decline, partly depending on demographics and biomarker status. The aim of the present study was to survey the clinical practices of physicians in terms of biomarker counseling, management, and follow-up in European expert centers diagnosing patients with MCI. Methods: An online email survey was distributed to physicians affiliated with European Alzheimer's disease Consortium centers (Northern Europe: 10 centers; Eastern and Central Europe: 9 centers; and Southern Europe: 15 centers) with questions on attitudes toward biomarkers and biomarker counseling in MCI and dementia. This included postbiomarker counseling and the process of diagnostic disclosure of MCI, as well as treatment and follow-up in MCI. Results: The response rate for the survey was 80.9% (34 of 42 centers) across 20 countries. A large majority of physicians had access to biomarkers and found them useful. Pre- and postbiomarker counseling varied across centers, as did practices for referral to support groups and advice on preventive strategies. Less than half reported discussing driving and advance care planning with patients with MCI. Conclusions: The variability in clinical practices across centers calls for better biomarker counseling and better training to improve communication skills. Future initiatives should address the importance of communicating preventive strategies and advance planning.

Background: Gait analysis with accelerometers is a relatively inexpensive and easy to use method to potentially support clinical diagnoses of Alzheimer's disease and other dementias. It is not clear, however, which gait features are most informative and how these measures relate to Alzheimer's disease pathology. Objective: In this study, we tested if calculated features of gait 1) differ between cognitively normal subjects (CN), mild cognitive impairment (MCI) patients, and dementia patients, 2) are correlated with cerebrospinal fluid (CSF) biomarkers related to Alzheimer's disease, and 3) predict cognitive decline. Methods: Gait was measured using tri-axial accelerometers attached to the fifth lumbar vertebra (L5) in 58 CN, 58 MCI, and 26 dementia participants, while performing a walk and dual task. Ten gait features were calculated from the vertical L5 accelerations, following principal component analysis clustered in four domains, namely pace, rhythm, time variability, and length variability. Cognitive decline over time was measured using MMSE, and CSF biomarkers were available in a sub-group. Results: Linear mixed models showed that dementia patients had lower pace scores than MCI patients and CN subjects (p < 0.05). In addition, we found associations between the rhythm domain and CSF-tau, especially in the dual task. Gait was not associated with CSF Aβ42 levels and cognitive decline over time as measured with the MMSE. Conclusion: These findings suggest that gait-particularly measures related to pace and rhythm-are altered in dementia and have a direct link with measures of neurodegeneration.

INTRODUCTION: An accurate and timely diagnosis for Alzheimer's disease (AD) is important, both for care and research. The current diagnostic criteria allow the use of CSF biomarkers to provide pathophysiological support for the diagnosis of AD. How these criteria should be operationalized by clinicians is unclear. Tools that guide in selecting patients in which CSF biomarkers have clinical utility are needed. We evaluated computerized decision support to select patients for CSF biomarker determination.METHODS: We included 535 subjects (139 controls, 286 Alzheimer's disease dementia, 82 frontotemporal dementia and 28 vascular dementia) from three clinical cohorts. Positive (AD like) and negative (normal) CSF biomarker profiles were simulated to estimate whether knowledge of CSF biomarkers would impact (confidence in) diagnosis. We applied these simulated CSF values and combined them with demographic, neuropsychology and MRI data to initiate CSF testing (computerized decision support approach). We compared proportion of CSF measurements and patients diagnosed with sufficient confidence (probability of correct class ≥0.80) based on an algorithm with scenarios without CSF (only neuropsychology, MRI and APOE), CSF according to the appropriate use criteria (AUC) and CSF for all patients.RESULTS: The computerized decision support approach recommended CSF testing in 140 (26%) patients, which yielded a diagnosis with sufficient confidence in 379 (71%) of all patients. This approach was more efficient than CSF in none (0% CSF, 308 (58%) diagnosed), CSF selected based on AUC (295 (55%) CSF, 350 (65%) diagnosed) or CSF in all (100% CSF, 348 (65%) diagnosed).CONCLUSIONS: We used a computerized decision support with simulated CSF results in controls and patients with different types of dementia. This approach can support clinicians in making a balanced decision in ordering additional biomarker testing. Computer-supported prediction restricts CSF testing to

Background: Several factors may play a role in the ability of patients with Alzheimer’s disease to perform activities of daily living (ADL). The aim of this study was to examine the impact of different aspects of physical performance and cognitive functions on ADL in patients suffering from mild-to-moderate Alzheimer’s disease. Methods: We conducted secondary analyses on cross-sectional baseline data from the randomized controlled multicentre study “Preserving quality of life, physical health and functional ability in Alzheimer’s Disease: The effect of physical exercise” (ADEX). In total, 185 AD patients (76 women and 109 men), with a mean age on 70,4 years, were included. Data from physical performance tests (Astrand cycle test, Timed up & Go (TUG), Sit to Stand test (STS)) and cognitive tests (Mini Mental Status Examination (MMSE), Symbol Digit Modalities Test (SDMT), Stroop Color and Word test (Stroop)) were used. Their associations with ADL, measured on the ADCS-ADL scale was assessed in multivariable regression analyses. Results: SDMT and MMSE had significant, moderate correlations with total ADL (SDMT: r = 0.33, MMSE: r = 0.42) and instrumental ADL (SDMT: r = 0.31, MMSE: r = 0.42), but not with basic ADL. Adjusting for age and sex, the associations between SDMT and MMSE to total ADL and instrumental ADL persisted. No significant associations were found between Astrand, TUG, STS or Stroop and total ADL, basic ADL or instrumental ADL. Conclusion: Total ADL and instrumental ADL are associated with cognitive functions, including executive function. No significant association between examined physical performance parameters and ADL functions was observed, and consequently does not support an impact of physical function on ADL functions in patients with mild-to-moderate Alzheimer’s disease and relatively well-preserved physical function. Strategies aimed to improve cognition may be better suited to improve ADL function in patients with mild-to-moderate Alzhei

INTRODUCTION: An accurate and timely diagnosis for Alzheimer's disease (AD) is important, both for care and research. The current diagnostic criteria allow the use of CSF biomarkers to provide pathophysiological support for the diagnosis of AD. How these criteria should be operationalized by clinicians is unclear. Tools that guide in selecting patients in which CSF biomarkers have clinical utility are needed. We evaluated computerized decision support to select patients for CSF biomarker determination.METHODS: We included 535 subjects (139 controls, 286 Alzheimer's disease dementia, 82 frontotemporal dementia and 28 vascular dementia) from three clinical cohorts. Positive (AD like) and negative (normal) CSF biomarker profiles were simulated to estimate whether knowledge of CSF biomarkers would impact (confidence in) diagnosis. We applied these simulated CSF values and combined them with demographic, neuropsychology and MRI data to initiate CSF testing (computerized decision support approach). We compared proportion of CSF measurements and patients diagnosed with sufficient confidence (probability of correct class ≥0.80) based on an algorithm with scenarios without CSF (only neuropsychology, MRI and APOE), CSF according to the appropriate use criteria (AUC) and CSF for all patients.RESULTS: The computerized decision support approach recommended CSF testing in 140 (26%) patients, which yielded a diagnosis with sufficient confidence in 379 (71%) of all patients. This approach was more efficient than CSF in none (0% CSF, 308 (58%) diagnosed), CSF selected based on AUC (295 (55%) CSF, 350 (65%) diagnosed) or CSF in all (100% CSF, 348 (65%) diagnosed).CONCLUSIONS: We used a computerized decision support with simulated CSF results in controls and patients with different types of dementia. This approach can support clinicians in making a balanced decision in ordering additional biomarker testing. Computer-supported prediction restricts CSF testing to

Background: Several factors may play a role in the ability of patients with Alzheimer’s disease to perform activities of daily living (ADL). The aim of this study was to examine the impact of different aspects of physical performance and cognitive functions on ADL in patients suffering from mild-to-moderate Alzheimer’s disease. Methods: We conducted secondary analyses on cross-sectional baseline data from the randomized controlled multicentre study “Preserving quality of life, physical health and functional ability in Alzheimer’s Disease: The effect of physical exercise” (ADEX). In total, 185 AD patients (76 women and 109 men), with a mean age on 70,4 years, were included. Data from physical performance tests (Astrand cycle test, Timed up & Go (TUG), Sit to Stand test (STS)) and cognitive tests (Mini Mental Status Examination (MMSE), Symbol Digit Modalities Test (SDMT), Stroop Color and Word test (Stroop)) were used. Their associations with ADL, measured on the ADCS-ADL scale was assessed in multivariable regression analyses. Results: SDMT and MMSE had significant, moderate correlations with total ADL (SDMT: r = 0.33, MMSE: r = 0.42) and instrumental ADL (SDMT: r = 0.31, MMSE: r = 0.42), but not with basic ADL. Adjusting for age and sex, the associations between SDMT and MMSE to total ADL and instrumental ADL persisted. No significant associations were found between Astrand, TUG, STS or Stroop and total ADL, basic ADL or instrumental ADL. Conclusion: Total ADL and instrumental ADL are associated with cognitive functions, including executive function. No significant association between examined physical performance parameters and ADL functions was observed, and consequently does not support an impact of physical function on ADL functions in patients with mild-to-moderate Alzheimer’s disease and relatively well-preserved physical function. Strategies aimed to improve cognition may be better suited to improve ADL function in patients with mild-to-moderate Alzhei

Introduction: Animal models of Alzheimer's disease show that exercise may modify β-amyloid (Aβ) deposition. We examined the effect of a 16-week exercise intervention on cortical Aβ in patients with mild-to-moderate Alzheimer's disease. Methods: Thirty-six patients with Alzheimer's disease were randomized to either one hour of aerobic exercise three times weekly for 16 weeks or usual care. Pre and post intervention, 11Carbon-Pittsburgh compound B positron emission tomography was carried out to assess cortical Aβ, and quantified using standardized uptake value rations (SUVRs). Results: The intervention showed no effect on follow-up SUVRs in a covariance analysis with group allocation, baseline intervention SUVR, age, sex, and baseline Mini–Mental State Examination as predictors. Change in SUVRs did not correlate with changes in measures of physical or aerobic fitness. Discussion: The present findings do not support an effect of exercise on Aβ. However, the relatively short intervention period may account for a lack of efficacy. Further studies should test earlier and longer interventions.

Background: Diagnosing frontotemporal dementia may be challenging. New methods for analysis of regional brain atrophy patterns on magnetic resonance imaging (MRI) could add to the diagnostic assessment. Therefore, we aimed to develop automated imaging biomarkers for differentiating frontotemporal dementia subtypes from other diagnostic groups, and from one another. Methods: In this retrospective multicenter cohort study, we included 1213 patients (age 67 ± 9, 48% females) from two memory clinic cohorts: 116 frontotemporal dementia, 341 Alzheimer's disease, 66 Dementia with Lewy bodies, 40 vascular dementia, 104 other dementias, 229 mild cognitive impairment, and 317 subjective cognitive decline. Three MRI atrophy biomarkers were derived from the normalized volumes of automatically segmented cortical regions: 1) the anterior vs. posterior index, 2) the asymmetry index, and 3) the temporal pole left index. We used the following performance metrics: area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. To account for the low prevalence of frontotemporal dementia we pursued a high specificity of 95%. Cross-validation was used in assessing the performance. The generalizability was assessed in an independent cohort (n = 200). Results: The anterior vs. posterior index performed with an AUC of 83% for differentiation of frontotemporal dementia from all other diagnostic groups (Sensitivity = 59%, Specificity = 95%, positive likelihood ratio = 11.8, negative likelihood ratio = 0.4). The asymmetry index showed highest performance for separation of primary progressive aphasia and behavioral variant frontotemporal dementia (AUC = 85%, Sensitivity = 79%, Specificity = 92%, positive likelihood ratio = 9.9, negative likelihood ratio = 0.2), whereas the temporal pole left index was specific for detection of semantic variant primary progressive aphasia (AUC = 85%, Sensitivity = 82%, Specificity = 80%, positive likelihood ratio = 4.1, negative

BACKGROUND: In clinical practice, it is often difficult to predict which patients with cognitive complaints or impairment will progress or remain stable. We assessed the impact of using a clinical decision support system, the PredictND tool, to predict progression in patients with subjective cognitive decline (SCD) and mild cognitive impairment (MCI) in memory clinics.METHODS: In this prospective multicenter study, we included 429 patients with SCD (n = 230) and MCI (n = 199) (female 54%, age 67 ± 9, MMSE 28 ± 2) and followed them for at least 12 months. Based on all available patient baseline data (demographics, cognitive tests, cerebrospinal fluid biomarkers, and MRI), the PredictND tool provides a comprehensive overview of the data and a classification defining the likelihood of progression. At baseline, a clinician defined an expected follow-up diagnosis and estimated the level of confidence in their prediction using a visual analogue scale (VAS, 0-100%), first without and subsequently with the PredictND tool. As outcome measure, we defined clinical progression as progression from SCD to MCI or dementia, and from MCI to dementia. Correspondence between the expected and the actual clinical progression at follow-up defined the prognostic accuracy.RESULTS: After a mean follow-up time of 1.7 ± 0.4 years, 21 (9%) SCD and 63 (32%) MCI had progressed. When using the PredictND tool, the overall prognostic accuracy was unaffected (0.4%, 95%CI - 3.0%; + 3.9%; p = 0.79). However, restricting the analysis to patients with more certain classifications (n = 203), we found an increase of 3% in the accuracy (95%CI - 0.6%; + 6.5%; p = 0.11). Furthermore, for this subgroup, the tool alone showed a statistically significant increase in the prognostic accuracy compared to the evaluation without tool (6.4%, 95%CI 2.1%; 10.7%; p = 0.004). Specifically, the negative predictive value was high. Moreover, confidence in the prediction increased significantly (∆VAS = 4%, p

Background: Diagnosing frontotemporal dementia may be challenging. New methods for analysis of regional brain atrophy patterns on magnetic resonance imaging (MRI) could add to the diagnostic assessment. Therefore, we aimed to develop automated imaging biomarkers for differentiating frontotemporal dementia subtypes from other diagnostic groups, and from one another. Methods: In this retrospective multicenter cohort study, we included 1213 patients (age 67 ± 9, 48% females) from two memory clinic cohorts: 116 frontotemporal dementia, 341 Alzheimer's disease, 66 Dementia with Lewy bodies, 40 vascular dementia, 104 other dementias, 229 mild cognitive impairment, and 317 subjective cognitive decline. Three MRI atrophy biomarkers were derived from the normalized volumes of automatically segmented cortical regions: 1) the anterior vs. posterior index, 2) the asymmetry index, and 3) the temporal pole left index. We used the following performance metrics: area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. To account for the low prevalence of frontotemporal dementia we pursued a high specificity of 95%. Cross-validation was used in assessing the performance. The generalizability was assessed in an independent cohort (n = 200). Results: The anterior vs. posterior index performed with an AUC of 83% for differentiation of frontotemporal dementia from all other diagnostic groups (Sensitivity = 59%, Specificity = 95%, positive likelihood ratio = 11.8, negative likelihood ratio = 0.4). The asymmetry index showed highest performance for separation of primary progressive aphasia and behavioral variant frontotemporal dementia (AUC = 85%, Sensitivity = 79%, Specificity = 92%, positive likelihood ratio = 9.9, negative likelihood ratio = 0.2), whereas the temporal pole left index was specific for detection of semantic variant primary progressive aphasia (AUC = 85%, Sensitivity = 82%, Specificity = 80%, positive likelihood ratio = 4.1, negative

BACKGROUND: In clinical practice, it is often difficult to predict which patients with cognitive complaints or impairment will progress or remain stable. We assessed the impact of using a clinical decision support system, the PredictND tool, to predict progression in patients with subjective cognitive decline (SCD) and mild cognitive impairment (MCI) in memory clinics.METHODS: In this prospective multicenter study, we included 429 patients with SCD (n = 230) and MCI (n = 199) (female 54%, age 67 ± 9, MMSE 28 ± 2) and followed them for at least 12 months. Based on all available patient baseline data (demographics, cognitive tests, cerebrospinal fluid biomarkers, and MRI), the PredictND tool provides a comprehensive overview of the data and a classification defining the likelihood of progression. At baseline, a clinician defined an expected follow-up diagnosis and estimated the level of confidence in their prediction using a visual analogue scale (VAS, 0-100%), first without and subsequently with the PredictND tool. As outcome measure, we defined clinical progression as progression from SCD to MCI or dementia, and from MCI to dementia. Correspondence between the expected and the actual clinical progression at follow-up defined the prognostic accuracy.RESULTS: After a mean follow-up time of 1.7 ± 0.4 years, 21 (9%) SCD and 63 (32%) MCI had progressed. When using the PredictND tool, the overall prognostic accuracy was unaffected (0.4%, 95%CI - 3.0%; + 3.9%; p = 0.79). However, restricting the analysis to patients with more certain classifications (n = 203), we found an increase of 3% in the accuracy (95%CI - 0.6%; + 6.5%; p = 0.11). Furthermore, for this subgroup, the tool alone showed a statistically significant increase in the prognostic accuracy compared to the evaluation without tool (6.4%, 95%CI 2.1%; 10.7%; p = 0.004). Specifically, the negative predictive value was high. Moreover, confidence in the prediction increased significantly (∆VAS = 4%, p

Background: Diagnosing frontotemporal dementia may be challenging. New methods for analysis of regional brain atrophy patterns on magnetic resonance imaging (MRI) could add to the diagnostic assessment. Therefore, we aimed to develop automated imaging biomarkers for differentiating frontotemporal dementia subtypes from other diagnostic groups, and from one another. Methods: In this retrospective multicenter cohort study, we included 1213 patients (age 67 ± 9, 48% females) from two memory clinic cohorts: 116 frontotemporal dementia, 341 Alzheimer's disease, 66 Dementia with Lewy bodies, 40 vascular dementia, 104 other dementias, 229 mild cognitive impairment, and 317 subjective cognitive decline. Three MRI atrophy biomarkers were derived from the normalized volumes of automatically segmented cortical regions: 1) the anterior vs. posterior index, 2) the asymmetry index, and 3) the temporal pole left index. We used the following performance metrics: area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. To account for the low prevalence of frontotemporal dementia we pursued a high specificity of 95%. Cross-validation was used in assessing the performance. The generalizability was assessed in an independent cohort (n = 200). Results: The anterior vs. posterior index performed with an AUC of 83% for differentiation of frontotemporal dementia from all other diagnostic groups (Sensitivity = 59%, Specificity = 95%, positive likelihood ratio = 11.8, negative likelihood ratio = 0.4). The asymmetry index showed highest performance for separation of primary progressive aphasia and behavioral variant frontotemporal dementia (AUC = 85%, Sensitivity = 79%, Specificity = 92%, positive likelihood ratio = 9.9, negative likelihood ratio = 0.2), whereas the temporal pole left index was specific for detection of semantic variant primary progressive aphasia (AUC = 85%, Sensitivity = 82%, Specificity = 80%, positive likelihood ratio = 4.1, negative

BACKGROUND: In clinical practice, it is often difficult to predict which patients with cognitive complaints or impairment will progress or remain stable. We assessed the impact of using a clinical decision support system, the PredictND tool, to predict progression in patients with subjective cognitive decline (SCD) and mild cognitive impairment (MCI) in memory clinics.METHODS: In this prospective multicenter study, we included 429 patients with SCD (n = 230) and MCI (n = 199) (female 54%, age 67 ± 9, MMSE 28 ± 2) and followed them for at least 12 months. Based on all available patient baseline data (demographics, cognitive tests, cerebrospinal fluid biomarkers, and MRI), the PredictND tool provides a comprehensive overview of the data and a classification defining the likelihood of progression. At baseline, a clinician defined an expected follow-up diagnosis and estimated the level of confidence in their prediction using a visual analogue scale (VAS, 0-100%), first without and subsequently with the PredictND tool. As outcome measure, we defined clinical progression as progression from SCD to MCI or dementia, and from MCI to dementia. Correspondence between the expected and the actual clinical progression at follow-up defined the prognostic accuracy.RESULTS: After a mean follow-up time of 1.7 ± 0.4 years, 21 (9%) SCD and 63 (32%) MCI had progressed. When using the PredictND tool, the overall prognostic accuracy was unaffected (0.4%, 95%CI - 3.0%; + 3.9%; p = 0.79). However, restricting the analysis to patients with more certain classifications (n = 203), we found an increase of 3% in the accuracy (95%CI - 0.6%; + 6.5%; p = 0.11). Furthermore, for this subgroup, the tool alone showed a statistically significant increase in the prognostic accuracy compared to the evaluation without tool (6.4%, 95%CI 2.1%; 10.7%; p = 0.004). Specifically, the negative predictive value was high. Moreover, confidence in the prediction increased significantly (∆VAS = 4%, p

Introduction: Apolipoprotein E (APOE) epsilon 4 is the major genetic risk factor for Alzheimer's disease (AD), but its prevalence is unclear because earlier studies did not require biomarker evidence of amyloid beta(A beta) pathology. Methods: We included 3451 A beta+ subjects (853 AD-type dementia, 1810 mild cognitive impairment, and 788 cognitively normal). Generalized estimating equation models were used to assess APOE epsilon 4 prevalence in relation to age, sex, education, and geographical location. Results: The APOE epsilon 4 prevalence was 66% in AD-type dementia, 64% in mild cognitive impairment, and 51% in cognitively normal, and it decreased with advancing age in A beta+ cognitively normal and A beta+ mild cognitive impairment (P <.05) but not in A beta+ AD dementia (P =.66). The prevalence was highest in Northern Europe but did not vary by sex or education. Discussion: The APOE E4 prevalence in AD was higher than that in previous studies, which did not require presence of A beta pathology. Furthermore, our results highlight disease heterogeneity related to age and geographical location. (C) 2018 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Introduction: Apolipoprotein E (APOE) epsilon 4 is the major genetic risk factor for Alzheimer's disease (AD), but its prevalence is unclear because earlier studies did not require biomarker evidence of amyloid beta(A beta) pathology. Methods: We included 3451 A beta+ subjects (853 AD-type dementia, 1810 mild cognitive impairment, and 788 cognitively normal). Generalized estimating equation models were used to assess APOE epsilon 4 prevalence in relation to age, sex, education, and geographical location. Results: The APOE epsilon 4 prevalence was 66% in AD-type dementia, 64% in mild cognitive impairment, and 51% in cognitively normal, and it decreased with advancing age in A beta+ cognitively normal and A beta+ mild cognitive impairment (P <.05) but not in A beta+ AD dementia (P =.66). The prevalence was highest in Northern Europe but did not vary by sex or education. Discussion: The APOE E4 prevalence in AD was higher than that in previous studies, which did not require presence of A beta pathology. Furthermore, our results highlight disease heterogeneity related to age and geographical location. (C) 2018 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Introduction: Apolipoprotein E (APOE) epsilon 4 is the major genetic risk factor for Alzheimer's disease (AD), but its prevalence is unclear because earlier studies did not require biomarker evidence of amyloid beta(A beta) pathology. Methods: We included 3451 A beta+ subjects (853 AD-type dementia, 1810 mild cognitive impairment, and 788 cognitively normal). Generalized estimating equation models were used to assess APOE epsilon 4 prevalence in relation to age, sex, education, and geographical location. Results: The APOE epsilon 4 prevalence was 66% in AD-type dementia, 64% in mild cognitive impairment, and 51% in cognitively normal, and it decreased with advancing age in A beta+ cognitively normal and A beta+ mild cognitive impairment (P <.05) but not in A beta+ AD dementia (P =.66). The prevalence was highest in Northern Europe but did not vary by sex or education. Discussion: The APOE E4 prevalence in AD was higher than that in previous studies, which did not require presence of A beta pathology. Furthermore, our results highlight disease heterogeneity related to age and geographical location. (C) 2018 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Introduction: Apolipoprotein E (APOE) epsilon 4 is the major genetic risk factor for Alzheimer's disease (AD), but its prevalence is unclear because earlier studies did not require biomarker evidence of amyloid beta(A beta) pathology. Methods: We included 3451 A beta+ subjects (853 AD-type dementia, 1810 mild cognitive impairment, and 788 cognitively normal). Generalized estimating equation models were used to assess APOE epsilon 4 prevalence in relation to age, sex, education, and geographical location. Results: The APOE epsilon 4 prevalence was 66% in AD-type dementia, 64% in mild cognitive impairment, and 51% in cognitively normal, and it decreased with advancing age in A beta+ cognitively normal and A beta+ mild cognitive impairment (P <.05) but not in A beta+ AD dementia (P =.66). The prevalence was highest in Northern Europe but did not vary by sex or education. Discussion: The APOE E4 prevalence in AD was higher than that in previous studies, which did not require presence of A beta pathology. Furthermore, our results highlight disease heterogeneity related to age and geographical location. (C) 2018 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Introduction: We studied, using a data-driven approach, how different combinations of diagnostic tests contribute to the differential diagnosis of dementia.Methods: In this multicenter study, we included 356 patients with Alzheimer's disease, 87 frontotemporal dementia, 61 dementia with Lewy bodies, 38 vascular dementia, and 302 controls. We used a classifier to assess accuracy for individual performance and combinations of cognitive tests, cerebrospinal fluid biomarkers, and automated magnetic resonance imaging features for pairwise differentiation between dementia types.Results: Cognitive tests had good performance in separating any type of dementia from controls. Cerebrospinal fluid optimally contributed to identifying Alzheimer's disease, whereas magnetic resonance imaging features aided in separating vascular dementia, dementia with Lewy bodies, and frontotemporal dementia. Combining diagnostic tests increased the accuracy, with balanced accuracies ranging from 78% to 97%.Discussion: Different diagnostic tests have their distinct roles in differential diagnostics of dementias. Our results indicate that combining different diagnostic tests may increase the accuracy further.

In recent years there has been an increasing focus on the relation between cerebrovascular health, physical exercise and Alzheimer's disease. The aim of the current study was to determine the effect of moderate-to-high-intensity aerobic exercise on cerebral blood flow in patients with mild to moderate Alzheimer's disease. Fifty-one patients were randomized to either usual care or moderate-to-high intensity aerobic exercise for 16 weeks. Exercise had no consistent effect on whole brain or regional cerebral blood flow. Sixteen weeks of exercise are, therefore, not sufficient to produce a consistent increase in cerebral blood flow in a relatively small sample of Alzheimer's patients.

Introduction: Apolipoprotein E (APOE) epsilon 4 is the major genetic risk factor for Alzheimers disease (AD), but its prevalence is unclear because earlier studies did not require biomarker evidence of amyloid beta(A beta) pathology. Methods: We included 3451 A beta+ subjects (853 AD-type dementia, 1810 mild cognitive impairment, and 788 cognitively normal). Generalized estimating equation models were used to assess APOE epsilon 4 prevalence in relation to age, sex, education, and geographical location. Results: The APOE epsilon 4 prevalence was 66% in AD-type dementia, 64% in mild cognitive impairment, and 51% in cognitively normal, and it decreased with advancing age in A beta+ cognitively normal and A beta+ mild cognitive impairment (P amp;lt;.05) but not in A beta+ AD dementia (P =.66). The prevalence was highest in Northern Europe but did not vary by sex or education. Discussion: The APOE E4 prevalence in AD was higher than that in previous studies, which did not require presence of A beta pathology. Furthermore, our results highlight disease heterogeneity related to age and geographical location. (C) 2018 the Alzheimers Association. Published by Elsevier Inc. All rights reserved., Funding Agencies|AXA Research Fund; Fondation Universite Pierre et Marie Curie; "Fondation pour la Recherche sur Alzheimer", Paris, France; program "Investissements davenir" [ANR-10-IAIHU-06]; National Institutes of Health [P50 AG005133, RF1 AG025516, PO1 AG025204]; Marie Curie FP7 International Outgoing Fellowship [628812]; Instituto de Salud Carlos III (Fondo de InvestigaciOn Sanitario) [PI08/0139, PI12/02288, PI16/01652]; NIH/NIA [RF1 AG057570, AG035137, AG032554, AG022374, AG13616, AG12101, AG08051, NIH-HLB HL111724]; Instituto de Salud Carlos III (CIBERNED program)

Introduction: We studied, using a data-driven approach, how different combinations of diagnostic tests contribute to the differential diagnosis of dementia.Methods: In this multicenter study, we included 356 patients with Alzheimer's disease, 87 frontotemporal dementia, 61 dementia with Lewy bodies, 38 vascular dementia, and 302 controls. We used a classifier to assess accuracy for individual performance and combinations of cognitive tests, cerebrospinal fluid biomarkers, and automated magnetic resonance imaging features for pairwise differentiation between dementia types.Results: Cognitive tests had good performance in separating any type of dementia from controls. Cerebrospinal fluid optimally contributed to identifying Alzheimer's disease, whereas magnetic resonance imaging features aided in separating vascular dementia, dementia with Lewy bodies, and frontotemporal dementia. Combining diagnostic tests increased the accuracy, with balanced accuracies ranging from 78% to 97%.Discussion: Different diagnostic tests have their distinct roles in differential diagnostics of dementias. Our results indicate that combining different diagnostic tests may increase the accuracy further.

In recent years there has been an increasing focus on the relation between cerebrovascular health, physical exercise and Alzheimer's disease. The aim of the current study was to determine the effect of moderate-to-high-intensity aerobic exercise on cerebral blood flow in patients with mild to moderate Alzheimer's disease. Fifty-one patients were randomized to either usual care or moderate-to-high intensity aerobic exercise for 16 weeks. Exercise had no consistent effect on whole brain or regional cerebral blood flow. Sixteen weeks of exercise are, therefore, not sufficient to produce a consistent increase in cerebral blood flow in a relatively small sample of Alzheimer's patients.

In recent years there has been an increasing focus on the relation between cerebrovascular health, physical exercise and Alzheimer's disease. The aim of the current study was to determine the effect of moderate-to-high-intensity aerobic exercise on cerebral blood flow in patients with mild to moderate Alzheimer's disease. Fifty-one patients were randomized to either usual care or moderate-to-high intensity aerobic exercise for 16 weeks. Exercise had no consistent effect on whole brain or regional cerebral blood flow. Sixteen weeks of exercise are, therefore, not sufficient to produce a consistent increase in cerebral blood flow in a relatively small sample of Alzheimer's patients.

Background: Studies of physical exercise in patients with Alzheimer’s disease (AD) are few and results have been inconsistent. Objective: To assess the effects of a moderate-to-high intensity aerobic exercise program in patients with mild AD. Methods: In a randomized controlled trial, we recruited 200 patients with mild AD to a supervised exercise group (60-min sessions three times a week for 16 weeks) or to a control group. Primary outcome was changed from baseline in cognitive performance estimated by Symbol Digit Modalities Test (SDMT) in the intention-to-treat (ITT) group. Secondary outcomes included changes in quality of life, ability to perform activities of daily living, and in neuropsychiatric and depressive symptoms. Results: The ITT analysis showed no significant differences between intervention and control groups in change from baseline of SDMT, other cognitive tests, quality of life, or activities of daily living. The change from baseline in Neuropsychiatric Inventory differed significantly in favor of the intervention group (mean: –3.5, 95% confidence interval (CI) –5.8 to –1.3, p = 0.002). In subjects who adhered to the protocol, we found a significant effect on change from baseline in SDMT as compared with the control group (mean: 4.2, 95% CI 0.5 to 7.9, p = 0.028), suggesting a dose-response relationship between exercise and cognition. Conclusions: This is the first randomized controlled trial with supervised moderate-to-high intensity exercise in patients with mild AD. Exercise reduced neuropsychiatric symptoms in patients with mild AD, with possible additional benefits of preserved cognition in a subgroup of patients exercising with high attendance and intensity.

Cerebral amyloid-β aggregation is an early pathological event in Alzheimer disease (AD), starting decades before dementia onset. Estimates of the prevalence of amyloid pathology in persons without dementia are needed to understand the development of AD and to design prevention studies.

BackgroundAn international Delphi panel has defined a harmonized protocol (HarP) for the manual segmentation of the hippocampus on MR. The aim of this study is to study the concurrent validity of the HarP toward local protocols, and its major sources of variance.MethodsFourteen tracers segmented 10 Alzheimer's Disease Neuroimaging Initiative (ADNI) cases scanned at 1.5 T and 3T following local protocols, qualified for segmentation based on the HarP through a standard web-platform and resegmented following the HarP. The five most accurate tracers followed the HarP to segment 15 ADNI cases acquired at three time points on both 1.5 T and 3T.ResultsThe agreement among tracers was relatively low with the local protocols (absolute left/right ICC 0.44/0.43) and much higher with the HarP (absolute left/right ICC 0.88/0.89). On the larger set of 15 cases, the HarP agreement within (left/right ICC range: 0.94/0.95 to 0.99/0.99) and among tracers (left/right ICC range: 0.89/0.90) was very high. The volume variance due to different tracers was 0.9% of the total, comparing favorably to variance due to scanner manufacturer (1.2), atrophy rates (3.5), hemispheric asymmetry (3.7), field strength (4.4), and significantly smaller than the variance due to atrophy (33.5%, P < .001), and physiological variability (49.2%, P < .001).ConclusionsThe HarP has high measurement stability compared with local segmentation protocols, and good reproducibility within and among human tracers. Hippocampi segmented with the HarP can be used as a reference for the qualification of human tracers and automated segmentation algorithms.

Alzheimer's disease is responsible for 40-50% of dementia cases. Future treatment may include disease-modifying compounds unlikely to be efficient if administered late in the course, thus necessitating early diagnosis. Furthermore, revised diagnostic research criteria that include biomarkers of pathological accumulation of cortical beta-amyloid (decreased beta-amyloid in cerebrospinal fluid and amyloid imaging) and neurodegeneration (structural MRI and 18F-FDG-PET), have been published. Future research is needed to determine specific evidence-based application of these biomarkers in the clinic as well as discovery of novel biomarkers.

BACKGROUND: An international Delphi panel has defined a harmonized protocol (HarP) for the manual segmentation of the hippocampus on MR. The aim of this study is to study the concurrent validity of the HarP toward local protocols, and its major sources of variance.METHODS: Fourteen tracers segmented 10 Alzheimer's Disease Neuroimaging Initiative (ADNI) cases scanned at 1.5 T and 3T following local protocols, qualified for segmentation based on the HarP through a standard web-platform and resegmented following the HarP. The five most accurate tracers followed the HarP to segment 15 ADNI cases acquired at three time points on both 1.5 T and 3T.RESULTS: The agreement among tracers was relatively low with the local protocols (absolute left/right ICC 0.44/0.43) and much higher with the HarP (absolute left/right ICC 0.88/0.89). On the larger set of 15 cases, the HarP agreement within (left/right ICC range: 0.94/0.95 to 0.99/0.99) and among tracers (left/right ICC range: 0.89/0.90) was very high. The volume variance due to different tracers was 0.9% of the total, comparing favorably to variance due to scanner manufacturer (1.2), atrophy rates (3.5), hemispheric asymmetry (3.7), field strength (4.4), and significantly smaller than the variance due to atrophy (33.5%, P < .001), and physiological variability (49.2%, P < .001).CONCLUSIONS: The HarP has high measurement stability compared with local segmentation protocols, and good reproducibility within and among human tracers. Hippocampi segmented with the HarP can be used as a reference for the qualification of human tracers and automated segmentation algorithms.

OBJECTIVES: Physical exercise may modulate neuropathology and symptoms of Alzheimer's disease (AD). This pilot study assessed the feasibility of conducting a study of moderate-to-high intensity aerobic exercise in home-dwelling patients with mild AD.METHODS: An uncontrolled preintervention-postintervention test design with a single group receiving the same intervention. A total of eight patients with mild to moderate AD from the Copenhagen Memory clinic were included in the study. The intervention lasted for 14 weeks and consisted of supervised, 1-h sessions of aerobic exercise three times per week (50-60% of heart rate reserve for a two-week adaptation period and 70-80 % of heart rate reserve for the remaining 12 weeks) Feasibility was assessed based on acceptability, including attendance and drop-out, safety, and patients' and caregivers' attitudes towards the intervention as well as other relevant parameters.RESULTS: Attendance (mean, range: 90 %, 70-100 %) and retention (seven out of eight) rates were very high. No serious adverse events were observed. In general, patients and caregivers were positive towards the intervention.CONCLUSION: This study shows that it is feasible to conduct moderate-to-high intensity aerobic exercise in community-dwelling patients with mild AD. Our findings indicate that aspects such as a longer adaptation period, information about injury prevention, and need for involvement and support from caregivers should be addressed when planning an exercise intervention in an AD population.

OBJECTIVES: Physical exercise may modulate neuropathology and symptoms of Alzheimer's disease (AD). This pilot study assessed the feasibility of conducting a study of moderate-to-high intensity aerobic exercise in home-dwelling patients with mild AD.METHODS: An uncontrolled preintervention-postintervention test design with a single group receiving the same intervention. A total of eight patients with mild to moderate AD from the Copenhagen Memory clinic were included in the study. The intervention lasted for 14 weeks and consisted of supervised, 1-h sessions of aerobic exercise three times per week (50-60% of heart rate reserve for a two-week adaptation period and 70-80 % of heart rate reserve for the remaining 12 weeks) Feasibility was assessed based on acceptability, including attendance and drop-out, safety, and patients' and caregivers' attitudes towards the intervention as well as other relevant parameters.RESULTS: Attendance (mean, range: 90 %, 70-100 %) and retention (seven out of eight) rates were very high. No serious adverse events were observed. In general, patients and caregivers were positive towards the intervention.CONCLUSION: This study shows that it is feasible to conduct moderate-to-high intensity aerobic exercise in community-dwelling patients with mild AD. Our findings indicate that aspects such as a longer adaptation period, information about injury prevention, and need for involvement and support from caregivers should be addressed when planning an exercise intervention in an AD population.

Background: The PredictAD tool integrates heterogeneous data such as imaging, cerebrospinal fluid biomarkers and results from neuropsychological tests for compact visualization in an interactive user interface. This study investigated whether the software tool could assist physicians in the early diagnosis of Alzheimer's disease. Methods: Baseline data from 140 patients with mild cognitive impairment were selected from the Alzheimer's Disease Neuroimaging Study. Three clinical raters classified patients into 6 categories of confidence in the prediction of early Alzheimer's disease, in 4 phases of incremental data presentation using the software tool. A 5th phase was done with all available patient data presented on paper charts. Classifications by the clinical raters were compared to the clinical diagnoses made by the Alzheimer's Disease Neuroimaging Initiative investigators. Results: A statistical significant trend (p <0.05) towards better classification accuracy (from 62.6 to 70.0%) was found when using the PredictAD tool during the stepwise procedure. When the same data were presented on paper, classification accuracy of the raters dropped significantly from 70.0 to 63.2%. Conclusion: Best classification accuracy was achieved by the clinical raters when using the tool for decision support, suggesting that the tool can add value in diagnostic classification when large amounts of heterogeneous data are presented.

Cross-sectional studies have suggested that corpus callosum (CC) atrophy is related to impairment in global cognitive function, mental speed, and executive functions in the elderly. Longitudinal studies confirming these findings have been lacking. We investigated whether CC tissue loss is associated with change in cognitive performance over time in subjects with age-related white matter lesions (WML). Two-hundred-fifty-three subjects, aged 65-84 years, were evaluated by using repeated MRI and neuropsychological evaluation at baseline and after 3 years. The effect of overall and regional CC tissue loss on cognitive decline was analyzed with hierarchical linear regression models. After controlling for age, sex, education, and baseline cognitive performance, the rates of tissue loss in the total CC area, and in rostrum/genu and midbody subregions were significantly associated with decline in a compound measure of cognitive speed and motor control, but not in those of executive functions, memory, or global cognitive function. Total CC area and midbody remained significant predictors of speed also after adjusting for baseline WML volume, WML progression, and global brain atrophy. However, the relationship between anterior CC and speed performance was mediated by WML volume. In conclusion, the overall and regional rate of CC tissue loss parallels longitudinal slowing of psychomotor performance. The adverse effect of CC tissue loss on psychomotor function may be driven by altered interhemispheric information transfer between homologous cortical areas.

Background: The PredictAD tool integrates heterogeneous data such as imaging, cerebrospinal fluid biomarkers and results from neuropsychological tests for compact visualization in an interactive user interface. This study investigated whether the software tool could assist physicians in the early diagnosis of Alzheimer's disease. Methods: Baseline data from 140 patients with mild cognitive impairment were selected from the Alzheimer's Disease Neuroimaging Study. Three clinical raters classified patients into 6 categories of confidence in the prediction of early Alzheimer's disease, in 4 phases of incremental data presentation using the software tool. A 5th phase was done with all available patient data presented on paper charts. Classifications by the clinical raters were compared to the clinical diagnoses made by the Alzheimer's Disease Neuroimaging Initiative investigators. Results: A statistical significant trend (p <0.05) towards better classification accuracy (from 62.6 to 70.0%) was found when using the PredictAD tool during the stepwise procedure. When the same data were presented on paper, classification accuracy of the raters dropped significantly from 70.0 to 63.2%. Conclusion: Best classification accuracy was achieved by the clinical raters when using the tool for decision support, suggesting that the tool can add value in diagnostic classification when large amounts of heterogeneous data are presented.

Cross-sectional studies have suggested that corpus callosum (CC) atrophy is related to impairment in global cognitive function, mental speed, and executive functions in the elderly. Longitudinal studies confirming these findings have been lacking. We investigated whether CC tissue loss is associated with change in cognitive performance over time in subjects with age-related white matter lesions (WML). Two-hundred-fifty-three subjects, aged 65-84 years, were evaluated by using repeated MRI and neuropsychological evaluation at baseline and after 3 years. The effect of overall and regional CC tissue loss on cognitive decline was analyzed with hierarchical linear regression models. After controlling for age, sex, education, and baseline cognitive performance, the rates of tissue loss in the total CC area, and in rostrum/genu and midbody subregions were significantly associated with decline in a compound measure of cognitive speed and motor control, but not in those of executive functions, memory, or global cognitive function. Total CC area and midbody remained significant predictors of speed also after adjusting for baseline WML volume, WML progression, and global brain atrophy. However, the relationship between anterior CC and speed performance was mediated by WML volume. In conclusion, the overall and regional rate of CC tissue loss parallels longitudinal slowing of psychomotor performance. The adverse effect of CC tissue loss on psychomotor function may be driven by altered interhemispheric information transfer between homologous cortical areas.

To examine the impact of corpus callosum (CC) tissue loss on the development of global cognitive and motor impairment in the elderly.

To examine the impact of corpus callosum (CC) tissue loss on the development of global cognitive and motor impairment in the elderly.