Modified Visual Magnetic Resonance Scale and Neuropsychometric Corelations in Alzheimer's disease

Year 2020, , 248 - 257, 29.10.2020

Burcu Polat , Nesrin Helvacı Yılmaz , Sabriye Bilgin Lütfü Hanoğlu

https://doi.org/10.21673/anadoluklin.737253

Abstract

Aim: Although more advanced neuroimaging techniques have been developed for research on Alzheimer’s disease (AD), structural magnetic resonance imaging (MRI) remains important in the clinical diagnosis of AD. The relationship between comprehensive MRI visual rating scales evaluating many parameters and cognitive and behavioral appearances of the disease has not been adequately investigated. In this study, we aimed to evaluate the correlation of the 7 sub-sections of the Modified Visual Magnetic Resonance Rating Scale (MVMRRS) with demographic, cognitive, and behavioral characteristics of patients diagnosed with AD.

Materials and Methods: The retrospective study included a total of 42 patients aged 50 years and older whose brain MRI and neuropsychometric test results were available and who were diagnosed with AD according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR) and of the National Institute of Neurological and Communicative Disorders and Stroke & the Alzheimer’s Disease and Related Disorders Association (NINCDS–ADRDA). By use of the Modified Visual Magnetic Resonance Rating Scale (MVMRRS), the brain MRI data were evaluated by a neuroradiologist blinded to the patient age, sex, and diagnosis data. Correlation of MVMRRS data with cognitive and behavioral test results was analyzed.

Results: The mean patient age was 75.19±9.26 (53–92) years and 61.9% of all patients were female. The mean education level was 5.02±4.84 (0–15) years and the mean illness duration was 4.52±2.94 years. The mean Mini-Mental State Examination score was 18.51±5.43 (4–30) while the mean Clinical Dementia Rating (CDR) score was 1.07±0.42 (0.5–2.0). Sulcal atrophy scores were negatively correlated with long-term recall and facial recognition while ventricular atrophy scores were inversely correlated with the learning scores and fruit–human and facial recognition parameters. A significant relationship was observed between the immediate recall, learning score, spontaneous recall, fruit–human, and CDR variables and the medial temporal atrophy variable.

Discussion and Conclusion: In dementia assessment, the use of MRI-based visual rating scales is an inexpensive and practical approach that also improves the diagnostic accuracy. Furthermore, the MVMRRS shows significant correlation with cognitive (executive functions, memory, attention, and language) data. Further studies to evaluate this scale in larger groups of patients with different patterns of cognitive impairment would be of clinical benefit.

Keywords

Neuroimaging scale, dementia, neurocognitive assessment

Modifiye Görsel Manyetik Rezonans Derecelendirme Skalası’nın Alzheimer Hastalığında Kullanımı ve Kognitif Gerileme ile İlişkisi

Abstract

Amaç: Alzheimer hastalığı (AH) araştırmaları için daha ileri nörogörüntüleme teknikleri geliştirilmiş olsa da, yapısal manyetik rezonans görüntüleme (MRG) AH’nin klinik tanısında önemini korumaktadır. Birçok parametreyi değerlendiren kapsamlı görsel MRG derecelendirme ölçeklerinin, hastalığın kognitif ve davranışsal görünümleriyle ilişkisi yeterince araştırılmamıştır. Bu çalışmada, Modifiye Görsel Manyetik Rezonans Derecelendirme Skalası’nın (MGMRDS) 7 alt bölümünün, AH tanısı almış hastaların demografik, kognitif ve davranışsal verileri ile korelasyonunu değerlendirmek amaçlanmıştır.

Gereç ve Yöntemler: Retrospektif çalışmamıza beyin MRG ve nöropsikometrik test (NPT) verileri olan, Ruhsal Bozuklukların Tanısal ve Sayımsal Elkitabı (DSM-IV-TR) ölçütleri ile Ulusal Nörolojik ve İletişimsel Bozukluklar ve İnme Enstitüsü & Alzheimer Hastalığı ve İlişkili Bozukluklar Derneği (NINCDS–ADRDA) kriterleri temelinde AH tanısı almış, 50 yaş ve üzeri toplam 42 hasta dahil edildi. Beyin MRG verileri, hasta yaş, cinsiyet ve tanı verilerine kör bir nöroradyolog tarafından MGMRDS kullanılarak değerlendirildi. MGMRDS verilerinin kognitif ve davranışsal test sonuçlarıyla korelasyonu incelendi.

Bulgular: Hastaların %61,9’u kadın, yaş ortalaması 75,19±9,26 (53–92) yıl idi. Ortalama eğitim süresi 5,02±4,84 (0–15) yıl, ortalama hastalık süresi 4,52±2,94 yıldı. Ortalama Mini Mental Durum Testi skoru 18,51±5,43 (4–30) iken, ortalama Klinik Demans Derecelendirmesi (KDD) skoru 1,07±0,42 (0,5–2,0) idi. Sulkal atrofi puanları uzun süreli hatırlama ve yüz tanıma ile negatif korele idi; ventriküler atrofi skorları ise öğrenme puanları, meyve–insan ve yüz tanıma değişkenleri ile ters korelasyon gösterdi. Anlık hatırlama, öğrenme puanı, kendiliğinden hatırlama, meyve–insan ve KDD değişkenleri ile mediyal temporal atrofi değişkeni arasında anlamlı ilişki gözlendi.

Tartışma ve Sonuç: Beyin MRG’ye dayalı görsel derecelendirme skalaları kullanmak, demans değerlendirmelerinde tanıyı doğrulayıcı, ucuz ve pratik bir yaklaşımdır. MGMRDS, kognitif (yürütücü işlevler, bellek, dikkat, dil) verilerle de anlamlı korelasyon göstermektedir. Bu ölçeği daha geniş hasta gruplarında değişik kognitif bozukluklarda değerlendirecek çalışmalar klinik açıdan faydalı olacaktır.

Keywords

demans, nörogörüntüleme skalası, nörokognitif testler

References

• 1. Frisoni GB, Fox NC, Jack CR Jr, Scheltens P, Thompson PM. The clinical use of structural MRI in Alzheimer disease. Nat Rev Neurol. 2010;6(2):67–77.
• 2. Harper L, Barkhof F, Scheltens P, Schott JM, Fox NC. An algorithmic approach to structural imaging in dementia. J Neurol Neurosurg Psychiatry. 2014;85(6):692–8.
• 3. Scheltens P, Leys D, Barkhof F, Huglo D, Weinstein HC, Vermersch P, ve ark. Atrophy of medial temporal lobes on MRI in “probable” Alzheimer’s disease and normal ageing: diagnostic value and neuropsychological correlates. J Neurol Neurosurg Psychiatry. 1992;55(10):967–72.
• 4. Reiman EM, Brinton RD, Katz R, Petersen RC, Negash S, Mungas D, ve ark. Considerations in the design of clinical trials for cognitive aging. J Gerontol A Biol Sci Med Sci. 2012;67(7):766–72.
• 5. Dickerson BC, Goncharova I, Sullivan MP, Forchetti C, Wilson RS, Bennett DA, ve ark. MRI-derived entorhinal and hippocampal atrophy in incipient and very mild Alzheimer’s disease. Neurobiol Aging. 2001;22(5):747–54.
• 6. de Toledo-Morrell L, Stoub TR, Bulgakova M, Wilson RS, Bennett DA, Leurgans S, ve ark. MRI-derived entorhinal volume is a good predictor of conversion from MCI to AD. Neurobiol Aging. 2004;25(9):1197–203.
• 7. Du AT, Schuff N, Kramer JH, Rosen HJ, Gorno-Tempini ML, Rankin K, ve ark. Different regional patterns of cortical thinning in Alzheimer’s disease and frontotemporal dementia. Brain. 2007;130(4):1159–66.
• 8. Dallaire-Théroux C, Callahan BL, Potvin O, Saikali S, Duchesne S. Radiological–pathological correlation in Alzheimer’s disease: systematic review of antemortem magnetic resonance imaging findings. J Alzheimers Dis. 2017;57(2):575–601.
• 9. Capizzano AA, Ación L, Bekinschtein T, Furman M, Gomila H, Martínez A, ve ark. White matter hyperintensities are significantly associated with cortical atrophy in Alzheimer’s disease. J Neurol Neurosurg Psychiatry. 2004;75(6):822–7.
• 10. Chandra A, Dervenoulas G, Politis M, Alzheimer’s Disease Neuroimaging Initiative. Magnetic resonance imaging in Alzheimer’s disease and mild cognitive impairment. J Neurol. 2019;266(6):1293–302.
• 11. Fazekas F, Chawluk JB, Alavi A, Hurtig HI, Zimmerman RA. MR signal abnormalities at 1.5 T in Alzheimer’s dementia and normal aging. AJR Am J Roentgenol. 1987;149(2):351–6.
• 12. Scheltens P, Weinstein HC, Leys D. Neuro-imaging in the diagnosis of Alzheimer’s disease. I. Computer tomography and magnetic resonance imaging. Clin Neurol Neurosurg. 1992;94(4):277–89.
• 13. Yue NC, Arnold AM, Longstreth WT Jr, Elster AD, Jungreis CA, O’Leary DH, ve ark. Sulcal, ventricular, and white matter changes at MR imaging in the aging brain: data from the cardiovascular health study. Radiology. 1997;202(1):33–9.
• 14. Verhagen MV, Guit GL, Hafkamp GJ, Kalisvaart K. The impact of MRI combined with visual rating scales on the clinical diagnosis of dementia: a prospective study. Eur Radiol. 2016;26(6):1716–22.
• 15. Harper L, Fumagalli GG, Barkhof F, Scheltens P, O’Brien JT, Bouwman F, ve ark. MRI visual rating scales in the diagnosis of dementia: evaluation in 184 post-mortem confirmed cases. Brain. 2016;139(4):1211–25.
• 16. Harper L, Barkhof F, Fox NC, Schott JM. Using visual rating to diagnose dementia: a critical evaluation of MRI atrophy scales. J Neurol Neurosurg Psychiatry. 2015;86:1225–33.
• 17. Wahlund LO, Westman E, van Westen D, Wallin A, Shams S, Cavallin L, ve ark. Imaging biomarkers of dementia: recommended visual rating scales with teaching cases. Insights Imaging. 2017;8(1):79–90.
• 18. Jang JW, Park SY, Park YH, Baek MJ, Lim JS, Youn YC, ve ark. A comprehensive visual rating scale of brain magnetic resonance imaging: application in elderly subjects with Alzheimer’s disease, mild cognitive impairment, and normal cognition. J Alzheimers Dis. 2015;44(3):1023–34.
• 19. Jang JW, Park JH, Kim S, Park YH, Pyun JM, Lim JS, ve ark. A “Comprehensive Visual Rating Scale” for predicting progression to dementia in patients with mild cognitive impairment. PLoS One. 2018;13(8):e0201852.
• 20. Yalciner BZ, Kandemir M, Taskale S, Tepe SM, Unay D. Modified visual magnetic resonance rating scale for evaluation of patients with forgetfulness. Can J Neurol Sci. 2019;46(1):71–8.
• 21. Fillenbaum GG, Unverzagt FW, Ganguli M, Welsh-Bohmer KA, Heyman A. The CERAD Neuropsychological Battery: performance of representative community and tertiary care samples of African American and European American elderly. In: Ferraro FR (ed.), Minority and Cross-cultural Aspects of Neuropsychological Assessment. Lisse, Hollanda: Swets & Zeitlinger; 2002:45–62.
• 22. Samtani MN, Farnum M, Lobanov V, Yang E, Raghavan N, Dibernardo A, ve ark. An improved model for disease progression in patients from the Alzheimer’s disease neuroimaging initiative. J Clin Pharmacol. 2012;52(5):629–44.
• 23. Baxter LC, Sparks DL, Johnson SC, Lenoski B, Lopez JE, Connor DJ, ve ark. Relationship of cognitive measures and gray and white matter in Alzheimer’s disease. J Alzheimers Dis. 2006;9(3):253–60.
• 24. Erkinjuntti T, Sipponen JT, Iivanainen M, Ketonen L, Sulkava R, Sepponen RE. Cerebral NMR and CT imaging in dementia. J Comput Assist Tomogr. 1984;8(4):614–8.
• 25. Güngen C, Ertan T, Eker E, Yaşar R, Engin F. Standardize Mini Mental Test’in Türk toplumunda hafif demans tanısında geçerlik ve güvenilirliği. Türk Psikiyatri Derg. 2002;13(4):273–81.
• 26. Morris J. The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology. 1993;43:2412–4.
• 27. Akça-Kalem Ş, Hanağası H, Cummings CL, Gurvit H. Validation study of the Turkish translation of the Neuropsychiatric Inventory (NPI). In: The 21st International Conference of Alzheimer’s Disease International Bildiri Kitabı. İstanbul: 2005:58.
• 28. Ertan T, Eker E, Şar V. Geriatrik Depresyon Ölçeği’nin Türk yaşlı nüfusunda geçerlilik ve güvenilirliği. Nöropsikiyatri Arşivi. 1997;33(2):62–71.
• 29. Soylu AE, Cangoz B. Adaptation and norm determination study of the Boston Naming Test for healthy Turkish elderly. Arch Neuropsychiatry. 2018;55(4):341–8.
• 30. Tanör ÖÖ. Öktem Sözel Bellek Süreçleri Testi (Öktem–SBST) El Kitabı, 2. ed. Ankara: Türk Psikologlar Derneği Yayınları; 2016.
• 31. Karakaş S, Eski R, Başar E. Türk kültürü için standardizasyonu yapılmış nöropsikolojik testler topluluğu: BİLNOT Bataryası. In: 32. Ulusal Nöroloji Kongresi Kitabı. İstanbul: 1996:43–70.
• 32. Icellioglu S, Bingol A, Kurt E, Yeni SN. The effects of computer-based rehabilitation on the cognitive functions of epilepsy patients. Dusunen Adam. 2017;30:354–63.
• 33. Cangöz B, Karakoç E, Selekler K. Saat çizme testinin 50 yaş üzeri Türk yetişkin ve yaşlı örneklemi üzerindeki norm belirleme ve geçerlilik–güvenilirlik çalışmaları. Türk Geriatri Derg. 2006;9(3):136–42.
• 34. Keskinkılıç C. Benton Yüz Tanıma Testi’nin Türk toplumu normal yetişkinler üzerindeki standardizasyonu. Türk Nöroloji Derg. 2008;14(3):179–90.
• 35. Bingol A, Yildiz S, Topcular B, Tutuncu M, Demirci NO. Brief Repeatable Battery (BRB)–Turkish normative data. Eur J Neurol. 2012;19(ek 1):558.
• 36. Başkaya O, Kandemir M, Tepe MS, Acar M, Ünal G, Yalçıner ZB, ve ark. Inter-hemispheric atrophy better correlates with expert ratings than hemispheric cortical atrophy. In: The 2012 20th Signal Processing and Communications Applications Conference (SIU) Bildiri Kitabı. Muğla: 2012:1–4.
• 37. Nestor SM, Rupsingh R, Borrie M, Smith M, Accomazzi V, Wells JL, ve ark. Ventricular enlargement as a possible measure of Alzheimer’s disease progression validated using the Alzheimer’s disease neuroimaging initiative database. Brain. 2008;131(9):2443–54.
• 38. Ezekiel F, Chao L, Kornak J. Comparisons between global and focal brain atrophy rates in normal aging and Alzheimer’s disease. Alzheimer Dis Assoc Disord. 2004;18:196–201.
• 39. Stout JC, Bondi MW, Jernigan TL, Archibald SL, Delis DC. Regional cerebral volume loss associated with verbal learning and memory in dementia of the Alzheimer type. Neuropsychology. 1999;(13)2:188–97.
• 40. Mungas D, Reed BR, Haan MN, González H. Spanish and English neuropsychological assessment scales: relationship to demographics, language, cognition, and independent function. Neuropsychology. 2005;19(4):466–75.
• 41. Evans MC, Barnes J, Nielsen C, Kim LG, Clegg SL, Blair M, ve ark. Volume changes in Alzheimer’s disease and mild cognitive impairment: cognitive associations. Eur Radiol. 2010;20(3):674–82.
• 42. Murray AD. Imaging approaches for dementia. AJNR Am J Neuroradiol. 2012;33(10):1836–44.
• 43. Sato N, Morishita R. Brain alterations and clinical symptoms of dementia in diabetes: Aβ/Tau-dependent and independent mechanisms. Front Endocrinol. 2014;5:143.
• 44. Banerjee G, Jang H, Kim HJ, Kim ST, Kim JS, Lee JH, ve ark. Total MRI small vessel disease burden correlates with cognitive performance, cortical atrophy, and network measures in a memory clinic population. J Alzheimers Dis. 2018;63:1485–97.
• 45. Ferreira D, Verhagen C, Hernandez-Cabrera JA, Cavallin L, Guo CJ, Ekman U, ve ark. Distinct subtypes of Alzheimer’s disease based on patterns of brain atrophy: longitudinal trajectories and clinical applications. Sci Rep. 2017;7:46263.
• 46. Persson K, Barca ML, Cavallin L, Brækhus A, Knapskog AB, Selbæk G, ve ark. Comparison of automated volumetry of the hippocampus using NeuroQuant® and visual assessment of the medial temporal lobe in Alzheimer’s disease. Acta Radiol. 2018;59(8):997–1001.