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El patólogo y psiquiatra Alois Alzheimer publicó en 1906 los hallazgos clínicos y neuropatológicos de una paciente, Augusta Deter, que a los 51 años comenzó con un cuadro clínico consistente en pérdida de memoria, desorientación en tiempo y espacio, dificultades en el lenguaje, así como un trastorno de conducta con ideación delirante de perjuicio y celotipia, falleciendo a los 56 años en un estado de demencia avanzada. En un principio, los hallazgos descritos por Alois Alzheimer pasaron inadvertidos para la comunidad científica, hasta que cuatro años más tarde, el psiquiatra Emil Kraepelin en su manual de Psiquiatría, describe nuevamente el descubrimiento de Alzheimer y, establece la enfermedad como una entidad clínico-patológica específica 1 . Inicialmente, la enfermedad de Alzheimer (EA) fue considerada una causa poco frecuente de demencia presenil de predominio no amnésico, a diferencia de la demencia senil, de instauración más tardía y con una clínica preferentemente amnésica que se creía propia del envejecimiento. A finales de los años 60, Sir Martin Roth y sus colaboradores demostraron que la mayoría de los pacientes con demencia senil presentaban en su cerebro los mismos hallazgos neuropatológicos que los pacientes con EA de inicio más joven. Una vez que la separación entre la EA y la demencia senil fue eliminada, se pudo comprobar que la EA era, en realidad, la causa de la mayor parte de las demencias de los pacientes en edades tardías de la vida

Background and purpose: Recommendations for using fluorodeoxyglucose positron emission tomography (FDG-PET) to support the diagnosis of dementing neurodegenerative disorders are sparse and poorly structured. Methods: Twenty-one questions on diagnostic issues and on semi-automated analysis to assist visual reading were defined. Literature was reviewed to assess study design, risk of bias, inconsistency, imprecision, indirectness and effect size. Critical outcomes were sensitivity, specificity, accuracy, positive/negative predictive value, area under the receiver operating characteristic curve, and positive/negative likelihood ratio of FDG-PET in detecting the target conditions. Using the Delphi method, an expert panel voted for/against the use of FDG-PET based on published evidence and expert opinion. Results: Of the 1435 papers, 58 papers provided proper quantitative assessment of test performance. The panel agreed on recommending FDG-PET for 14 questions: diagnosing mild cognitive impairment due to Alzheimer's disease (AD), frontotemporal lobar degeneration (FTLD) or dementia with Lewy bodies (DLB); diagnosing atypical AD and pseudo-dementia; differentiating between AD and DLB, FTLD or vascular dementia, between DLB and FTLD, and between Parkinson's disease and progressive supranuclear palsy; suggesting underlying pathophysiology in corticobasal degeneration and progressive primary aphasia, and cortical dysfunction in Parkinson's disease; using semi-automated assessment to assist visual reading. Panellists did not support FDG-PET use for pre-clinical stages of neurodegenerative disorders, for amyotrophic lateral sclerosis and Huntington disease diagnoses, and for amyotrophic lateral sclerosis or Huntington-disease-related cognitive decline. Conclusions: Despite limited formal evidence, panellists deemed FDG-PET useful in the early and differential diagnosis of the main neurodegenerative disorders, and semi-automated assessment helpful to assist visual reading. These decisions are proposed as interim recommendations.

Background To facilitate population screening and clinical trials of disease-modifying therapies for Alzheimer's disease, supportive biomarker information is necessary. This study was aimed to investigate the association of plasma amyloid-beta (A beta) levels with the presence of pathological accumulation of A beta in the brain measured by amyloid-PET. Both plasma A beta 42/40 ratio alone or combined with an FDG-PET-based biomarker of neurodegeneration were assessed as potential AD biomarkers. Methods We included 39 cognitively normal subjects and 20 patients with mild cognitive impairment from the AB255 Study who had undergone PiB-PET scans. Total A beta 40 and A beta 42 levels in plasma (TP42/40) were quantified using ABtest kits. Subjects were dichotomized as A beta-PET positive or negative, and the ability of TP42/40 to detect A beta-PET positivity was assessed by logistic regression and receiver operating characteristic analyses. Combination of plasma A beta biomarkers and FDG-PET was further assessed as an improvement for brain amyloidosis detection and diagnosis classification. Results Eighteen (30.5%) subjects were A beta-PET positive. TP42/40 ratio alone identified A beta-PET status with an area under the curve (AUC) of 0.881 (95% confidence interval [CI] = 0.779-0.982). Discriminating performance of TP42/40 to detect A beta-PET-positive subjects yielded sensitivity and specificity values at Youden's cutoff of 77.8% and 87.5%, respectively, with a positive predictive value of 0.732 and negative predictive value of 0.900. All these parameters improved after adjusting the model for significant covariates. Applying TP42/40 as the first screening tool in a sequential diagnostic work-up would reduce the number of A beta-PET scans by 64%. Combination of both FDG-PET scores and plasma A beta biomarkers was found to be the most accurate A beta-PET predictor, with an AUC of 0.965 (95% CI = 0.913-0.100). Conclusions Plasma TP42/40 ratio showed a relevant and significant potential as a screening tool to identify brain A beta positivity in preclinical and prodromal stages of Alzheimer's disease.

BACKGROUND: To facilitate population screening and clinical trials of disease-modifying therapies for Alzheimer's disease, supportive biomarker information is necessary. This study was aimed to investigate the association of plasma amyloid-beta (Aß) levels with the presence of pathological accumulation of Aß in the brain measured by amyloid-PET. Both plasma Aß42/40 ratio alone or combined with an FDG-PET-based biomarker of neurodegeneration were assessed as potential AD biomarkers. METHODS: We included 39 cognitively normal subjects and 20 patients with mild cognitive impairment from the AB255 Study who had undergone PiB-PET scans. Total Aß40 and Aß42 levels in plasma (TP42/40) were quantified using ABtest kits. Subjects were dichotomized as Aß-PET positive or negative, and the ability of TP42/40 to detect Aß-PET positivity was assessed by logistic regression and receiver operating characteristic analyses. Combination of plasma Aß biomarkers and FDG-PET was further assessed as an improvement for brain amyloidosis detection and diagnosis classification. RESULTS: Eighteen (30.5%) subjects were Aß-PET positive. TP42/40 ratio alone identified Aß-PET status with an area under the curve (AUC) of 0.881 (95% confidence interval [CI] = 0.779-0.982). Discriminating performance of TP42/40 to detect Aß-PET-positive subjects yielded sensitivity and specificity values at Youden's cutoff of 77.8% and 87.5%, respectively, with a positive predictive value of 0.732 and negative predictive value of 0.900. All these parameters improved after adjusting the model for significant covariates. Applying TP42/40 as the first screening tool in a sequential diagnostic work-up would reduce the number of Aß-PET scans by 64%. Combination of both FDG-PET scores and plasma Aß biomarkers was found to be the most accurate Aß-PET predictor, with an AUC of 0.965 (95% CI = 0.913-0.100). CONCLUSIONS: Plasma TP42/40 ratio showed a relevant and significant potential as a screening tool to identify brain Aß positivity in preclinical and prodromal stages of Alzheimer's disease.

Background: Hypofractionated radiation therapy is a feasible and safe treatment option in elderly and frail patients with glioblastoma. The aim of this study was to evaluate the effectiveness of hypofractionated radiation therapy with concurrent temozolomide in terms of feasibility and disease control in primary glioblastoma patients with poor prognostic factors other than advanced age, such as post-surgical neurological complications, high tumor burden, unresectable or multifocal lesions, and potential low treatment compliance due to social factors or rapidly progressive disease. Material and methods: GTV included the surgical cavity plus disease visible in T1WI-MRI, FLAIR-MRI and in the MET-uptake. The CTV was defined as the GTV plus 1.5-2 cm margin; the PTV was the CTV+0.3 cm margin. Forty, fourty-five, and fifty grays in 15 fractions were prescribed to 95% of PTV, CTV, and GTV, respectively. Treatment was delivered using IMRT or the VMAT technique. Simultaneously, 75 mg/m2/day of temozolomide were administered. Results: Between January 2010 and November 2017, we treated a total of 17 patients. The median age at diagnosis was 68-years; median KPS was 50-70%. MGMT-methylation status was negative in 5 patients, and 8 patients were IDH-wildtype. Eight of 18 patients were younger than 65-years. Median tumor volume was 26.95cc; median PTV volume was 322cc. Four lesions were unresectable; 6 patients underwent complete surgical resection. Median residual volume was 1.14cc. Progression-free survival was 60% at 6 months, 33% at 1-year and 13% at 2-years (median OS = 7 months). No acute grade 3-5 toxicities were documented. Symptomatic grade 3 radiation necrosis was observed in one patient. Conclusions: Patients with poor clinical factors other than advanced age can be selected for hypofractionated radiotherapy. The OS and PFS rates obtained in our series are similar to those in patients treated with standard fractionation, assuring good treatment adherence, low rates of toxicity and probable improved cost-effectiveness.

BACKGROUND: Easily accessible biomarkers are needed for the early identification of individuals at risk of developing Alzheimer's disease (AD) in large population screening strategies. OBJECTIVES: This study evaluated the potential of plasma ß-amyloid (Aß) biomarkers in identifying early stages of AD and predicting cognitive decline over the following two years. DESIGN: Total plasma Aß42/40 ratio (TP42/40) was determined in 83 cognitively normal individuals (CN) and 145 subjects with amnestic mild cognitive impairment (a-MCI) stratified by an FDG-PET AD-risk pattern. RESULTS: Significant lower TP42/40 ratio was found in a-MCI patients compared to CN. Moreover, a-MCIs with a high-risk FDG-PET pattern for AD showed even lower plasma ratio levels. Low TP42/40 at baseline increased the risk of progression to dementia by 70%. Furthermore, TP42/40 was inversely associated with neocortical amyloid deposition (measured with PiB-PET) and was concordant with the AD biomarker profile in cerebrospinal fluid (CSF). CONCLUSIONS: TP42/40 demonstrated value in the identification of individuals suffering a-MCI, in the prediction of progression to dementia, and in the detection of underlying AD pathology revealed by FDG-PET, Amyloid-PET and CSF biomarkers, being, thus, consistently associated with all the well-established indicators of AD.

Alzheimer's disease (AD) is a neurodegenerative condition characterized by progressive cognitive decline and memory loss, and is the most common form of dementia. Amyloid plaques with neurofibrillary tangles are a neuropathological hallmark of AD that produces synaptic dysfunction and culminates later in neuronal loss. Amyloid PET is a useful, available and non-invasive technique that provides in vivo information about the cortical amyloid burden. In the latest revised criteria for the diagnosis of AD biomarkers were defined and integrated: pathological and diagnostic biomarkers (increased retention on fibrillar amyloid PET or decreased A beta(1-42) and increased T-Tau or P-Tau in CSF) and neurodegeneration or topographical biomarkers (temporoparietal hypometabolism on F-18-FDG PET and temporal atrophy on MRI). Recently specific recommendations have been created as a consensus statement on the appropriate use of the imaging biomarkers, including amyloid PET: early-onset cognitive impairment/dementia, atypical forms of AD, mild cognitive impairment with early age of onset, and to differentiate between AD and other neurodegenerative diseases that occur with dementia. Amyloid PET is also contributing to the development of new therapies for AD, as well as in research studies for the study of other neurodegenerative diseases that occur with dementia where the deposition of A beta amyloid is involved in its pathogenesis. In this paper, we review some general concepts and study the use of amyloid PET in depth and its relationship with neurodegenerative diseases and other diagnostic techniques. (C) 2018 Sociedad Espanola de Medicina Nuclear e Imagen Molecular. Published by Elsevier Espana, S.L.U. All rights reserved.

Aim: To evaluate the incremental value of FDG-PET over clinical tests in: (i) diagnosis of amyotrophic lateral sclerosis (ALS); (ii) picking early signs of neurodegeneration in patients with a genetic risk of Huntington's disease (HD); and detecting metabolic changes related to cognitive impairment in (iii) ALS and (iv) HD patients. Methods: Four comprehensive literature searches were conducted using the PICO model to extract evidence from relevant studies. An expert panel then voted using the Delphi method on these four diagnostic scenarios. Results: The availability of evidence was good for FDG-PET utility to support the diagnosis of ALS, poor for identifying presymptomatic subjects carrying HD mutation who will convert to HD, and lacking for identifying cognitive-related metabolic changes in both ALS and HD. After the Delphi consensual procedure, the panel did not support the clinical use of FDG-PET for any of the four scenarios. Conclusion: Relative to other neurodegenerative diseases, the clinical use of FDG-PET in ALS and HD is still in its infancy. Once validated by disease-control studies, FDG-PET might represent a potentially useful biomarker for ALS diagnosis. FDG-PET is presently not justified as a routine investigation to predict conversion to HD, nor to detect evidence of brain dysfunction justifying cognitive decline in ALS and HD

Parkinson’s disease (PD) is a neurodegenerative disease which is difficult to diagnose at an early stage. Brain imaging techniques like [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) may aid to identify disease-related changes in cerebral glucose metabolism. The scaled subprofile model with principal component analysis (SSM/PCA) is applied to FDG-PET data to extract features and corresponding patterns of glucose metabolism which can be used to distinguish PD subjects from healthy controls. From a previous study, the decision tree (DT) classifier’s performance to separate the PD group from healthy controls was below chance level. This could be attributed to the small number of subjects in the dataset, combined with the early disease progression. In this study, we make use of an additional PD dataset, consisting of subject brain images obtained at a later disease stage. The features m extracted by the SSM/PCA method are used for distinguishing PD subjects from healthy controls using three classification methods, that is, decision trees, Generalized Matrix Learning Vector Quantization (GMLVQ), and Support Vector Machine (SVM) with linear kernel. The classifiers are validated to determine their capability of classification given new subject data. We compare the classifiers performances on the distinct early-stage and late-stage datasets, as well on the combined datasets. We also use the early and late-stage datasets interchangeably for training and testing the classifiers. We find that the DT classification performance on the late-stage dataset is considerably better than in the previous study, where we used early-stage data. For early-stage patients, the application of the GMLVQ and SVM classifiers gives a significant improvement as compared to the DT classifier.