Abstract

Background. Vascular diseases of the brain, which lead to encephalopathy, are a significant medical and social problem. The main clinical tool for diagnosing cognitive impairments is a neuropsychological testing. Its disadvantages are a big number of different tests, which are used in clinical institutions, and thus, make it extremely complicated to compare the data; in monitoring studies, patients can learn answers, which somewhat distorts the results; there is also a possibility of a non-objective doctor’s impact on the results of the conducted test. Therefore, the development of methods for assessing the neuropsychological and cognitive state of patients based on objective data is an urgent task. Besides, to this date, it is not completely known which segments of the brain directly or indirectly affect this or that cognitive function. Purpose – to develop a methodology for assessing the scores of neuropsychological testing (NPT) in patients with atherosclerotic hypertensive encephalopathy (ATHE) based on data from single-photon emission computed tomography (SPECT) with perfusion radiopharmaceuticals (RPh). Materials and Methods. NPT and SPECT data of twenty patients with clinical diagnosis of atherosclerotic hypertensive encephalopathy were analyzed. The principal scales used during the study were the following: Montgomery – Asberg Depression Rating Scale (MADRS), Hamilton Anxiety Rating Scale (HARS), Schulte Table, O. Luria. Tomographic images of the brain were obtained on the gamma camera «E. Cam» (Siemens) using perfusion lipophilic radiopharmaceutical 99mTc-hexamethylpropyleneamineoxime (99mTc-HMPAO). Processing and analysis of the scintigraphic images were conducted in the original software «ScintiBrain», which is implemented in the Matlab-2018 environment. The quantitative characteristics of accumulation and spatial distribution of RPh in the brain were: specific accumulation of RPh (Upt) and parameter of intrahemispheric symmetry (IHS) of perfusion in the brain segments. Based on machine learning method, which can be attributed to regression methods, NPT data were compared with the ratio of Upt and IHS between different segments of the brain Results. As a result of the analysis (machine learning) of 190 Upt and IHS ratios between different segments of the brain with NPT values, the most informative ratios in terms of regression analysis were highlighted. The independence of Upt and IHS makes it possible to increase the accuracy of calculations of NPT values by algebraic averaging of calculations by Upt and IHS ratios.
 Machine learning results by both Upt and IHS values had one order of correlation and a mean squared error in the tests. The correlation coefficient of linear approximation of values between the SPECT and NPT data was in the range of 0.75–0.93 (p < 0.01), which corresponded to the average relative error in calculations of test values from 7–22%. Conclusions. For the first time, a method of quantitative assessment of the neuropsychological and cognitive state of patients was developed on the basis of an objective research method, namely SPECT. The average relative error in calculations of equivalent values of NPT was in the range of 7 – 22%. At the same time, it was shown that the neuropsychological and cognitive state of patients, in particular patients with ATHE, according to the analysis of effective brain perfusion, didn’t correspond to one specific segment of the brain, but instead to a group of three interrelations of RPh accumulation in the highlighted regions of interest. The presence of a sufficiently high correlation between the NPT data and the indicators of the specific accumulation of RPh and the IHS in the brain segments showed that the neuropsychological and cognitive state of the patient depended not only on the level of accumulation of RPh in segments, but also on its spatial distribution.

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