Comparison of clinical types of Wilson's disease and glucose metabolism in extrapyramidal motor brain regions

Hermann, W.; Barthel, Henryk; Hesse, Swen; Grahmann, F.; Kühn, H.; Wagner, A.; Villmann, Thomas

doi:10.1007/s00415-002-0756-7

Cited by 33 publications

(29 citation statements)

References 21 publications

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“…The data from this study demonstrated age-dependent changes of 64 Cu accumulation in the brains of Atp7b −/− knockout mice, which are encouraging and support further investigation of age-dependent changes of copper metabolism in WD patients who suffer from psychiatric and neurological symptoms, using [ 64 Cu]CuCl 2 -PET/CT imaging in conjunction with [ 18 F]FDG PET [34, 35] and MRI [35, 36]. Delineation of age-dependent changes of copper metabolism in WD patients is expected to contribute to a better understanding of molecular mechanism of neurodegeneration in WD.…”

Section: Discussionsupporting

confidence: 64%

Age-dependent changes of cerebral copper metabolism in Atp7b −/− knockout mouse model of Wilson’s disease by [64Cu]CuCl2-PET/CT

Xie

Pascual

et al. 2017

Metab Brain Dis

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Copper is a nutritional metal required for brain development and function. Wilson’s disease (WD), or hepatolenticular degeneration, is an inherited human copper metabolism disorder caused by mutation of ATP7B gene. Many WD patients present with variable neurological and psychiatric symptoms, which may be related to neurodegeneration secondary to copper metabolism imbalance. The objective of this study is to explore feasibility and use of copper-64 chloride ([64C]CuCl2) as a tracer for noninvasive assessment of age-dependence changes of cerebral copper metabolism in WD using an Atp7b−/− knockout mouse model of WD and a positron emission tomography/computed tomography (PET/CT) scanner. Continuing from recent study of biodistribution and radiation dosimetry of [64C]CuCl2 in Atp7b−/− knockout mice, PET quantitative analysis revealed low 64Cu radioactivity in the brains of Atp7b−/− knockout mice at 7th week of age, compared with the 64Cu radioactivity in the brains of age and gender-matched wild type C57BL/6 mice, at 24 hour (h) post intravenous injection of [64C]CuCl2 as a tracer. Furthermore, age-dependent increase of 64Cu radioactivity was detected in the brains of Atp7b−/− knockout mice from 13th to 21th week of age, using the data derived from a longitudinal [64C]CuCl2-PET/CT study of Atp7b−/− knockout mice with orally administered [64Cu]CuCl2 as a tracer. The findings of this study support the use of [64Cu]CuCl2-PET/CT as a tool for noninvasive assessment of age-dependent changes of cerebral copper metabolism in WD patients presenting with variable neurological and psychiatric symptoms.

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Section: Discussionsupporting

confidence: 64%

Age-dependent changes of cerebral copper metabolism in Atp7b −/− knockout mouse model of Wilson’s disease by [64Cu]CuCl2-PET/CT

Xie

Pascual

et al. 2017

Metab Brain Dis

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“…The severity of neurological deficits was assessed using an established semiquantitative scale: 0 (no deficits), 1 (only dysarthrophonia), 2 (mild deficits) , 3 (moderate deficits), 4 (severe deficits) and 5 (very severe deficits) [8].…”

Section: Methodsmentioning

confidence: 99%

Profound midbrain atrophy in patients with Wilson’s disease and neurological symptoms?

et al. 2006

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Wilson's disease (WD) is characterized by impaired hepatic copper secretion and subsequent copper accumulation in many organs predominantly liver and brain, secondary to loss of function mutations in the copper transport protein ATP7B. If the disease is recognized too late or treatment is not adequate, brain copper accumulation leads to progressive neurodegeneration with a variety of clinical symptoms. The nigrostriatal dopaminergic system seems rather vulnerable. Midbrain atrophy, however, has not been recognized as one of the prime features of patients with WD. Here we report quantification of midbrain diameter in 41 patients with WD. Data were correlated to the severity of neurological symptoms and the integrity of dopaminergic neurons measured via dopamine transporter binding. For control, we measured midbrain diameter in 18 patients with no evidence for brainstem dysfunction and 5 patients with progressive supranuclear palsy (PSP). Patients with WD had a reduced midbrain diameter (15.5 +/- 0.4 mm) compared to controls (18.5 +/- 0.2 mm). WD patients without neurological symptoms had midbrain diameter that were not different from controls (18.0 +/- 0.3 mm), while patients with neurological symptoms showed midbrain atrophy similar to patients with PSP (14.4 +/- 0.3 mm versus 14.1 +/- 0.3). There was a strong and significant correlation between midbrain atrophy and the severity of neurological symptoms (r= -0.68, p < 0.001) while midbrain atrophy and dopamine transporter binding correlated significantly but was less pronounced (r=0.46, p < 0.001). In summary, we were able to show, that midbrain diameter is an easy to perform quantification of neurodegeneration induced by brain copper accumulation and that other structures than substantia nigra dopaminergic neurons seem to contribute to midbrain atrophy in WD.

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“…For the latter case one can further differentiate between pseudo-sclerotic (PS) and pseudo-parkinsonian (PP) cases according to their fine-motoric disturbances caused by the neurological impairments [47]. Frequently, a merged type (MT) between them is considered, which can be seen neurologically belonging to PP [51].…”

Section: Exemplary Application -Classification Of Morbus Wilsonmentioning

confidence: 98%

Precision-Recall-Optimization in Learning Vector Quantization Classifiers for Improved Medical Classification Systems

Villmann

Kaden

Lange

et al. 2014

2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM)

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Classification and decision systems in data analysis are mostly based on accuracy optimization. This criterion is only a conditional informative value if the data are imbalanced or false positive/negative decisions cause different costs. Therefore more sophisticated statistical quality measures are favored in medicine, like precision, recall etc. . Otherwise, most classification approaches in machine learning are designed for accuracy optimization. In this paper we consider variants of learning vector quantizers (LVQs) explicitly optimizing those advanced statistical quality measures while keeping the basic intuitive ingredients of these classifiers, which are the prototype based principle and the Hebbian learning. In particular we focus in this contribution particularly to precision and recall as important measures for use in medical applications. We investigate these problems in terms of precision-recall curves as well as receiver-operating characteristic (ROC) curves well-known in statistical classification and test analysis. With the underlying more general framework, we provide a principled alternatives traditional classifiers, such that a closer connection to statistical classification analysis can be drawn.

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Comparison of clinical types of Wilson's disease and glucose metabolism in extrapyramidal motor brain regions

Cited by 33 publications

References 21 publications

Age-dependent changes of cerebral copper metabolism in Atp7b −/− knockout mouse model of Wilson’s disease by [64Cu]CuCl2-PET/CT

Age-dependent changes of cerebral copper metabolism in Atp7b −/− knockout mouse model of Wilson’s disease by [64Cu]CuCl2-PET/CT

Profound midbrain atrophy in patients with Wilson’s disease and neurological symptoms?

Precision-Recall-Optimization in Learning Vector Quantization Classifiers for Improved Medical Classification Systems

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