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Comparison of the magnetic resonance imaging and acoustocerebrography signals in the assessment of focal cerebral microangiopathic lesions in patients with asymptomatic atrial fibrillation. (Preliminary clinical study results)

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Języki publikacji
EN
Abstrakty
EN
Acoustocerebrography (ACG) is a set of techniques designed to capture states of human brain tissue, and its changes. It is based on noninvasive measurements of various parameters obtained by analyzing an ultrasound pulse emitted through the human’s skull. ACG and Magnetic Resonance Imaging (MRI) results were compared in a clinical study assessment of focal white-matter-lesions (WML) in the brains of patients with asymptomatic atrial fibrillation (AAF). The clinical study included 55 patients (age 66.1 ± 6.7 years). According to MRI data, the patients were assigned into four groups depending on the number of lesions: L0 - 0 to 4 lesions, L5 - 5 to 9 lesions, L10 - 10 to 29 lesions, and L30 - 30 or more lesions. As a result, it has been concluded that the ACG method could clearly differentiate the groups L0 (with 0 ÷ 4 lesions) and L30 (with more than 30 lesions) of WML patients. Fisher’s Exact Test shows that this correlation is highly significant (p < 0.001). ACG seems to be a new, effective, method for detecting WML for patients with AAF and can become increasingly useful in both diagnosing, and in stratifying, them. This, in turn, can be helpful in individualizing their treatment, so that the risk of strokes may become essentially reduced.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
83--92
Opis fizyczny
Bibliogr. 15 poz., rys.
Twórcy
  • District Hospital, Cardiology, Radom, Poland
autor
  • Sonovum AG, Leipzig, Germany
  • Radiology, Military Institute of Medicine, Warsaw, Poland
autor
  • Sonovum AG, Leipzig, Germany
autor
  • Sonomed, Warsaw, Poland
autor
  • Radiology, Military Institute of Medicine, Warsaw, Poland
  • Warsaw Medical University, Warsaw, Poland
autor
  • Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland
autor
  • Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland
Bibliografia
  • [1] Bogdan, M., et al, Computer Aided Multispectral Ultrasound Diagnostics Brain Health Monitoring System based on Acoustocerebrography, Conference Paper submitted for MEDICO 2016, Cyprus, 2016.
  • [2] Cordonnier, C., Al-Shahi Salman, R., Wardlaw, J., Spontaneous brain micro-bleeds: systematic review, subgroup analyses and standards for study design and reporting, Brain,130:1988-2003, 2007.
  • [3] Godin, O., Dufouil, C., Maillard, P., Delcroix, N., Mazoyer, B., Crivello, F., Alperovitch, A., Tzourio, C., White matter lesions as a predictor of depression in the elderly: the 3C-Dijon Study, Biol. Psychiatry,63: 663–666, 2007.
  • [4] Van Dijk, E.J., Prins, N.D., Vrooman, H.A., Hofman, A., Koudstaal, P.J., Breteler, M., Progression of cerebral small vessel disease in relation to risk factors and cognitive consequences - Rotterdam Scan study, Stroke, 39(10):2712-9, 2008.
  • [5] Mazur, R., Dynamics of brain density in the acute phase of ischemic stroke, Udar Mózgu, 4(1), 1-8, 2004.
  • [6] Piszczek M., Rozprawa doktorska: Badanie możliwości monitorowania niedokrwienia mózgu za pomocą pomiaru różnicy fal akustycznych paczek falowych, WAT, Warszawa 2000. In Polish.
  • [7] Stehling, C., Wersching, H., Kloska, S.P., Kirchhof, P., Ring, J., Nassenstein, I., et al., Detection of asymptomatic cerebral microbleeds: a comparative study at 1.5 and 3.0, T. Acad. Radiol., 15: 895-900, 2008.
  • [8] Stoer J., Bulirsch R., Introduction to Numerical Analysis, Springer Science & Business Media, March 1993.
  • [9] Szustakowski, M., et.al., Pomiar zmian prędkości fazowej w cieczy z zastosowaniem cyfrowego przetwarzania sygnału», Molecular & Quantum Acoustics, vol.19, 1998.
  • [10] Tzourio, C., Anderson, C., Blood pressure reduction and risk of dementia in patients with stroke: rationale of the dementia assessment in PROGRESS (Perindopril Protection Against Recurrent Stroke Study), PROGRESS Management Committee, J. Hypertens Suppl., 18:S21–S24, 3, 2000.
  • [11] Wolf, P.A., Abbott, R.D., Kannel, W.B., Atrial fibrillation as an independent risk factor for stroke: the Framingham Study, Stroke, 22: 983–88, 1991.
  • [12] Wrobel, M., Advanced Ultrasonic Interferometer and Method of Non-Linear Classification and Identification of Matter using the same, WO 2007/000047, June 28, 2005.
  • [13] Ylikoski, A., Erkinjuntti, T., Raininko, R., Sarna, S., Sulkava, R., Tilvis, R., White matter hyper-intensities on MRI in the neurologically nondiseased elderly. Analysis of cohorts of consecutive subjects aged 55 to 85 years living at home, Stroke, 26: 1171- 1177, 1995.
  • [14] Wrobel M., Dabrowski A., Kolany A., Olak-Popko A., Olszewski R., Karlowicz P., On ultrasound classification of stroke risk factors from randomly chosen respondents using non-invasive multispectral ultrasonic brain measurements and adaptive profiles, Biocybernetics and Biomedical Engineering, 36(1):18-28, 2015.
  • [15] Miron B. Kursa, Witold R. Rudnicki (2010). Feature Selection with the Boruta Package. Journal of Statistical Software, 36(11), p. 1-13. URL: http://www.jstatsoft.org/v36/i11/.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-3428cf5d-2240-428f-affb-b8c82e2e55ee
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