Progression Modeling of Cognitive Disease Using Temporal Data Mining: Research Landscape, Gaps and Solution Design

Dementia is a cognitive disorder whose diagnosis and progression monitoring is very difficult due to a very slow onset and progression. It is difficult to detect whether cognitive decline is due to ageing process or due to some form of dementia as MRI scans of the brain cannot reliably differentiate between ageing related volume loss and pathological changes. Laboratory tests on blood or CSF samples have also not proved very useful. Alzheimer�s disease (AD) is recognized as the most common cause of dementia. Development of sensitive and reliable tool for evaluation in terms of early diagnosis and progression monitoring of AD is required. Since there is an absence of specific markers for predicting AD progression, there is a need to learn more about specific attributes and their temporal relationships that lead to this disease and determine progression from mild cognitive impairment to full blown AD. Various stages of disease and transitions from one stage to the have be modelled based on longitudinal patient data. This paper provides a critical review of the methods to understand disease progression modelling and determine factors leading to progression of AD from initial to final stages. Then the design of a machine learning based solution is proposed to handle the gaps in current research

Cerebrospinal fluid markers including trefoil factor 3 are associated with neurodegeneration in amyloid-positive individuals.

We aimed to identify cerebrospinal fluid (CSF) biomarkers associated with neurodegeneration in individuals with and without CSF evidence of Alzheimer pathology. We investigated 287 Alzheimer's Disease Neuroimaging Initiative (ADNI) subjects (age=74.9±6.9; 22/48/30% with Alzheimer's disease/mild cognitive impairment/controls) with CSF multiplex analyte data and serial volumetric MRI. We calculated brain and hippocampal atrophy rates, ventricular expansion and Mini Mental State Examination decline. We used false discovery rate corrected regression analyses to assess associations between CSF variables and atrophy rates in individuals with and without amyloid pathology, adjusting in stages for tau, baseline volume, p-tau, age, sex, ApoE4 status and diagnosis. Analytes showing statistically significant independent relationships were entered into reverse stepwise analyses. Adjusting for tau, baseline volume, p-tau, age, sex and ApoE4, 4/83 analytes were significantly independently associated with brain atrophy rate, 1/83 with ventricular expansion and 2/83 with hippocampal atrophy. The strongest CSF predictor for the three atrophy measures was low trefoil factor 3 (TFF3). High cystatin C (CysC) was associated with higher whole brain atrophy and hippocampal atrophy rates. Lower levels of vascular endothelial growth factor and chromogranin A (CrA) were associated with higher whole brain atrophy. In exploratory reverse stepwise analyses, lower TFF3 was associated with higher rates of whole brain, hippocampal atrophy and ventricular expansion. Lower levels of CrA were associated with higher whole brain atrophy rate. The relationship between low TFF3 and increased hippocampal atrophy rate remained after adjustment for diagnosis. We identified a series of CSF markers that are independently associated with rate of neurodegeneration in amyloid-positive individuals. TFF3, a substrate for NOTCH processing may be an important biomarker of neurodegeneration across the Alzheimer spectrum

Reference standard space hippocampus labels according to the EADC-ADNI harmonized protocol: Utility in automated volumetry

BACKGROUND: A harmonized protocol (HarP) for manual hippocampal segmentation on magnetic resonance imaging (MRI) has recently been developed by an international European Alzheimer's Disease Consortium–Alzheimer's Disease Neuroimaging Initiative project. We aimed at providing consensual certified HarP hippocampal labels in Montreal Neurological Institute (MNI) standard space to serve as reference in automated image analyses. METHODS: Manual HarP tracings on the high-resolution MNI152 standard space template of four expert certified HarP tracers were combined to obtain consensual bilateral hippocampus labels. Utility of these reference labels is demonstrated in a simple atlas-based morphometry approach for automated calculation of HarP-compliant hippocampal volumes within SPM software. RESULTS: Individual tracings showed very high agreement among the five expert tracers (pairwise Jaccard indices 0.82–0.87). Automatically calculated hippocampal volumes were highly correlated (rL/R = 0.89/0.91) with gold standard volumes in the HarP benchmark data set (N = 135 MRIs), with a mean volume difference of 9% (standard deviation 7%). CONCLUSION: The consensual HarP hippocampus labels in the MNI152 template can serve as a reference standard for automated image analyses involving MNI standard space normalization

The Rationale and Design of the Reducing Pathology in Alzheimer's Disease through Angiotensin TaRgeting (RADAR) Trial

BACKGROUND: Anti-hypertensives that modify the renin angiotensin system may reduce Alzheimer's disease (AD) pathology and reduce the rate of disease progression. OBJECTIVE: To conduct a phase II, two arm, double-blind, placebo-controlled, randomized trial of losartan to test the efficacy of Reducing pathology in Alzheimer's Disease through Angiotensin TaRgeting (RADAR). METHODS: Men and women aged at least 55 years with mild-to-moderate AD will be randomly allocated 100 mg encapsulated generic losartan or placebo once daily for 12 months after successful completion of a 2-week open-label phase and 2-week placebo washout to establish drug tolerability. 228 participants will provide at least 182 subjects with final assessments to provide 84% power to detect a 25% difference in atrophy rate (therapeutic benefit) change over 12 months at an alpha level of 0.05. We will use intention-to-treat analysis, estimating between-group differences in outcomes derived from appropriate (linear or logistic) multivariable regression models adjusting for minimization variables. RESULTS: The primary outcome will be rate of whole brain atrophy as a surrogate measure of disease progression. Secondary outcomes will include changes to 1) white matter hyperintensity volume and cerebral blood flow; 2) performance on a standard series of assessments of memory, cognitive function, activities of daily living, and quality of life. Major assessments (for all outcomes) and relevant safety monitoring of blood pressure and bloods will be at baseline and 12 months. Additional cognitive assessment will also be conducted at 6 months along with safety blood pressure and blood monitoring. Monitoring of blood pressure, bloods, and self-reported side effects will occur during the open-label phase and during the majority of the post-randomization dispensing visits. CONCLUSION: This study will identify whether losartan is efficacious in the treatment of AD and whether definitive Phase III trials are warranted

Reproducibility of hippocampal atrophy rates measured with manual, FreeSurfer, AdaBoost, FSL/FIRST and the MAPS-HBSI methods in Alzheimer's disease

The purpose of this study is to assess the reproducibility of hippocampal atrophy rate measurements of commonly used fully-automated algorithms in Alzheimer disease (AD). The reproducibility of hippocampal atrophy rate for FSL/FIRST, AdaBoost, FreeSurfer, MAPS independently and MAPS combined with the boundary shift integral (MAPS-HBSI) were calculated. Back-to-back (BTB) 3D T1-weighted MPRAGE MRI from the Alzheimer's Disease Neuroimaging Initiative (ADNI1) study at baseline and year one were used. Analysis on 3 groups of subjects was performed – 562 subjects at 1.5 T, a 75 subject group that also had manual segmentation and 111 subjects at 3 T. A simple and novel statistical test based on the binomial distribution was used that handled outlying data points robustly. Median hippocampal atrophy rates were −1.1%/year for healthy controls, −3.0%/year for mildly cognitively impaired and −5.1%/year for AD subjects. The best reproducibility was observed for MAPS-HBSI (1.3%), while the other methods tested had reproducibilities at least 50% higher at 1.5 T and 3 T which was statistically significant. For a clinical trial, MAPS-HBSI should require less than half the subjects of the other methods tested. All methods had good accuracy versus manual segmentation. The MAPS-HBSI method has substantially better reproducibility than the other methods considered

Cerebral atrophy in mild cognitive impairment and Alzheimer disease: rates and acceleration.

OBJECTIVE: To quantify the regional and global cerebral atrophy rates and assess acceleration rates in healthy controls, subjects with mild cognitive impairment (MCI), and subjects with mild Alzheimer disease (AD). METHODS: Using 0-, 6-, 12-, 18-, 24-, and 36-month MRI scans of controls and subjects with MCI and AD from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, we calculated volume change of whole brain, hippocampus, and ventricles between all pairs of scans using the boundary shift integral. RESULTS: We found no evidence of acceleration in whole-brain atrophy rates in any group. There was evidence that hippocampal atrophy rates in MCI subjects accelerate by 0.22%/year2 on average (p = 0.037). There was evidence of acceleration in rates of ventricular enlargement in subjects with MCI (p = 0.001) and AD (p < 0.001), with rates estimated to increase by 0.27 mL/year2 (95% confidence interval 0.12, 0.43) and 0.88 mL/year2 (95% confidence interval 0.47, 1.29), respectively. A post hoc analysis suggested that the acceleration of hippocampal loss in MCI subjects was mainly driven by the MCI subjects that were observed to progress to clinical AD within 3 years of baseline, with this group showing hippocampal atrophy rate acceleration of 0.50%/year2 (p = 0.003). CONCLUSIONS: The small acceleration rates suggest a long period of transition to the pathologic losses seen in clinical AD. The acceleration in hippocampal atrophy rates in MCI subjects in the ADNI seems to be driven by those MCI subjects who concurrently progressed to a clinical diagnosis of AD

Visual ratings of atrophy in MCI: prediction of conversion and relationship with CSF biomarkers.

Medial temporal lobe atrophy (MTA) and cerebrospinal fluid (CSF) markers of Alzheimer's disease (AD) pathology may aid the early detection of AD in mild cognitive impairment (MCI). However, the relationship between structural and pathological markers is not well understood. Furthermore, while posterior atrophy (PA) is well recognized in AD, its value in predicting conversion from late-onset amnestic MCI to AD is unclear. In this study we used visual ratings of MTA and PA to assess their value in predicting conversion to AD in 394 MCI patients. The relationship of atrophy patterns with CSF Aβ1-42, tau, and p-tau(181) was further investigated in 114 controls, 192 MCI, and 99 AD patients. There was a strong association of MTA ratings with conversion to AD (p < 0.001), with a weaker association for PA ratings (p = 0.047). Specific associations between visual ratings and CSF biomarkers were found; MTA was associated with lower levels of Aβ1-42 in MCI, while PA was associated with elevated levels of tau in MCI and AD, which may reflect widespread neuronal loss including posterior regions. These findings suggest both that posterior atrophy may predict conversion to AD in late-onset MCI, and that there may be differential relationships between CSF biomarkers and regional atrophy patterns

Automated cross-sectional and longitudinal hippocampal volume measurement in mild cognitive impairment and Alzheimer's disease.

Volume and change in volume of the hippocampus are both important markers of Alzheimer's disease (AD). Delineation of the structure on MRI is time-consuming and therefore reliable automated methods are required. We describe an improvement (multiple-atlas propagation and segmentation (MAPS)) to our template library-based segmentation technique. The improved technique uses non-linear registration of the best-matched templates from our manually segmented library to generate multiple segmentations and combines them using the simultaneous truth and performance level estimation (STAPLE) algorithm. Change in volume over 12months (MAPS-HBSI) was measured by applying the boundary shift integral using MAPS regions. Methods were developed and validated against manual measures using subsets from Alzheimer's Disease Neuroimaging Initiative (ADNI). The best method was applied to 682 ADNI subjects, at baseline and 12-month follow-up, enabling assessment of volumes and atrophy rates in control, mild cognitive impairment (MCI) and AD groups, and within MCI subgroups classified by subsequent clinical outcome. We compared our measures with those generated by Surgical Navigation Technologies (SNT) available from ADNI. The accuracy of our volumes was one of the highest reported (mean(SD) Jaccard Index 0.80(0.04) (N=30)). Both MAPS baseline volume and MAPS-HBSI atrophy rate distinguished between control, MCI and AD groups. Comparing MCI subgroups (reverters, stable and converters): volumes were lower and rates higher in converters compared with stable and reverter groups (p< or =0.03). MAPS-HBSI required the lowest sample sizes (78 subjects) for a hypothetical trial. In conclusion, the MAPS and MAPS-HBSI methods give accurate and reliable volumes and atrophy rates across the clinical spectrum from healthy aging to AD

Sledování průběhu patologie podobné Alzheimerově chorobě v transgenním potkaním modelu TgF344-AD

Alzheimer's disease (AD) is a progressive neurodegenerative disorder affecting dominantly the elderly and it is the most common cause of dementia. AD is characterized by many pathological events such as amyloid plaques, neurofibrillary tangles, inflammation, neurotransmitter dysregulation and many others. These disruptive processes ultimately lead to synaptic and cell loss which human brain. According to literaure, cell loss in AD is apparent especially in the cortex and hippocampus. However, it is unclear at which timepoint the loss becomes significant and in which other structures. There are many other important structures such as olfactory bulbs or entorhinal cortex where the cell loss has not been fully quantified. With new methods like isotropic fractionator it has become possible for scientists to quantify large number of structures more quickly. Since human brains are not easy to obtain shortly after death, use of transgenic animal models, mostly rodents, is a good way to obtain more information about cell and especially neuronal loss occurring in AD. Key words: Alzheimer's disease, cell loss, isotropic fractionator, hippocampus, neurofibrillary tangles, beta amyloidAlzheimerova choroba je progresivní neurodegenerativní onemocnění postihující zejména starší populaci a je nejčastější příčinou demence. Je charakterizované mnoha patologickými událostmi jako jsou amyloidové plaky, neurofibrilární klubíčka, zánět, deregulace neurotransmiterů a mnoho dalších. Tyto disruptivní procesy v konečném důsledku vedou ke ztrátě synapsí a buněk. Podle literatury jsou buněčné ztráty pozorovatelné především v kortexu a hipokampu. Není jasné, v jakém časovém bodě je ztráta buněk signifikantní a v jakých dalších strukturách. Je mnoho dalších důležitých struktur jako jsou čichové laloky nebo entorhinální kortex, kde ztráta buněk nebyla dostatečně kvantifikována. S novými metodami jako je izotropní frakcionace je nyní možné kvantifikovat větší počet struktur mnohem rychleji. Vzhledem k tomu, že není jednoduché získat lidský mozek ihned po smrti, použití transgenních animálních modelů, zejména hlodavčích, je dobrý způsob, jak získat více informací o buněčném a především neuronálním úbytku u Alzheimerovy choroby. Klíčová slova: Alzheimerova choroba, ztráta buněk, izotropní frakcionátor, hippocampus, neurofibrilární klubíčka, beta amyloidDepartment of PhysiologyKatedra fyziologiePřírodovědecká fakultaFaculty of Scienc