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Modified Visual Magnetic Resonance Rating Scale for Evaluation of Patients with Forgetfulness

  • Betul Z. Yalciner (a1), Melek Kandemir (a1), Sencan Taskale (a2), Savas M. Tepe (a3) and Devrim Unay (a4)...

Abstract

Background

As cognitive impairment increases with age, sulcal atrophy (SA) and the enlargement of the ventricles also increase. Considering the measurements on the previously proposed visual scales, a new scale is proposed in this study that allows us to evaluate the atrophy, white matter hyperintensities (WMHs), basal ganglia infarct (BGI), and infratentorial infarct (ITI) together. Our aim of this study is to propose a practical and standardized MRI for the clinicians to be used in daily practice.

Methods

A total of 97 patients older than 60 years and diagnosed with depression or Alzheimer’s disease (AD) are included. Cranial MRI, Mini Mental State Examination (MMSE), detailed neuropsychometric tests, and depression scales are applied to all patients. The SA, ventricular atrophy (VA), medial temporal lobe atrophy (MTA), periventricular WMH (PWMH), subcortical WMH (SCWMH), BGI, and ITI are scored according to the scale. The total score is also recorded.

Results

The average age of the patients was 74.53, and the mean MMSE score was 22.7 in the degenerative group and 27.8 in the non-degenerative group. Among the patients, 50 were diagnosed with AD. All parameters significantly increased with age. In the degenerative group, SA, VA, MTA, PWMH, SCWMH, and total scores were found to be significantly higher. Sensitivities of VA, PWMH, SCWMH, and total scores, as well as both sensitivity and specificities of MTA score, were observed to be high. When they were combined, sensitivities and specificities were found to be high.

Conclusion

The scale is observed to be predictive in discriminating degenerative and non-degenerative processes. This discrimination is important, particularly in depressive patients complaining of forgetfulness.

Modifier une échelle d’évaluation visuelle dans le cas de patients présentant des pertes de mémoire et soumis à une IRM.

Contexte

Dans la mesure où les manifestations de déficience cognitive ont tendance à augmenter avec le vieillissement, on constate aussi une augmentation de l’atrophie des sillons du cortex cérébral et de l’élargissement des ventricules cérébraux. En tenant compte des mesures propres à des échelles visuelles utilisées antérieurement, cette étude entend proposer une nouvelle échelle nous permettant d’évaluer en même temps des cas d’atrophie ainsi que la présence d’hyperdensités de la substance blanche, d’anomalies des ganglions de la base et d’infarctus affectant l’étage sus-tentoriel (infratentorial infarcts). L’objectif de cette étude est donc de proposer un examen d’IRM pratique et standardisé pouvant être utilisé quotidiennement par les cliniciens.

Méthodes

Nous avons inclus dans cette étude 97 patients âgés de plus de 60 ans qui étaient soit atteints de dépression, soit de la maladie d’Alzheimer. Tous les patients recrutés ont été soumis à des examens d’IRM crâniens, au test de Folstein (ou MMSE), à un ensemble de tests neuro-psychométriques approfondis et à des échelles diagnostiques permettant d’évaluer la dépression. L’incidence de l’atrophie des sillons du cortex cérébral, de la région ventriculaire, du lobe temporal médian, des régions péri-ventriculaire et sous-corticale et de la substance blanche qu’elles contiennent, d’anomalies affectant les ganglions de base et d’infarctus à l’étage sus-tentoriel a été ainsi mesurée selon notre échelle. Le score total obtenu a aussi été enregistré.

Résultats

L’âge moyen des patients était de 74,53 ans. Leur score moyen au test de Folstein était de 22,7 dans le cas du groupe de patients atteints d’une maladie dégénérative et de 27,8 dans le cas du groupe de patients n’étant pas atteints par ce type de maladie. Fait à noter, cinquante patients avaient reçu un diagnostic de maladie d’Alzheimer. Tous les paramètres évalués ont augmenté de façon notable avec l’âge. Ainsi, tant les scores obtenus dans le cas de l’atrophie des sillons du cortex cérébral, de celle affectant le lobe temporal médian, la région ventriculaire, la région péri-ventriculaire, la région sous-corticale que les scores totaux se sont révélés nettement plus élevés au sein du groupe de patients atteints d’une maladie dégénérative. La sensibilité des scores totaux et des scores évaluant l’atrophie des régions vasculaire, péri-vasculaire et sous-corticale, de même que la sensibilité et la spécificité des scores évaluant l’atrophie du lobe temporal médian, se sont révélées élevées. Lorsque combinées, la sensibilité et la spécificité sont apparues élevées.

Conclusions

Notre échelle possède un caractère prédictif en ce qu’elle permet d’établir une distinction entre les processus dégénératifs et les processus non-dégénératifs. Cette capacité est particulièrement importante dans le cas de patients dépressifs qui se plaignent de perte de mémoire.

Copyright

Corresponding author

Correspondence to: M. Kandemir, Department of Neurology, Bayindir Icerenoy Hospital, Ali Nihat Tarlan Cad. Ertas Sok. No: 17, Atasehir 34752, Istanbul, Turkey. Email: melekkandemir@gmail.com

References

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1. Hafkemeijer, A, van der Grond, J, Rombouts, SA. Imaging the default mode network in aging and dementia. Biochim Biophys Acta. 2012;1822(3):431-441.10.1016/j.bbadis.2011.07.008
2. Yue, NC, Arnold, AM, Longstreth, WT, et al. Sulcal, ventricular, and white matter changes at MR imaging in the aging brain: data from the cardiovascular health study. Radiology. 1997;202(1):33-39.10.1148/radiology.202.1.8988189
3. Jack, CR Jr, Shiung, MM, Gunter, JL, et al. Comparison of different MRI brain atrophy rate measures with clinical disease progression in AD. Neurology. 2004;62(4):591-600.10.1212/01.WNL.0000110315.26026.EF
4. Nestor, SM, Rupsingh, R, Borrie, M, et al. Ventricular enlargement as a possible measure of Alzheimer’s disease progression validated using the Alzheimer’s disease neuroimaging initiative database. Brain. 2008;131(Pt 9):2443-2454.
5. Liu, T, Wen, W, Zhu, W, et al. The relationship between cortical sulcal variability and cognitive performance in the elderly. Neuroimage. 2011;56(3):865-873.10.1016/j.neuroimage.2011.03.015
6. Liu, T, Lipnicki, DM, Zhu, W, et al. Cortical gyrification and sulcal spans in early stage Alzheimer’s disease. PLoS One. 2012;7(2):e31083.10.1371/journal.pone.0031083
7. Visser, PJ, Verhey, FR, Hofman, PA, et al. Medial temporal lobe atrophy predicts Alzheimer’s disease in patients with minor cognitive impairment. J Neurol Neurosurg Psychiatry. 2002;72(4):491-497.
8. Erkinjuntti, T, Gao, F, Lee, DH, et al. Lack of difference in brain hyperintensities between patients with early Alzheimer’s disease and control subjects. Arch Neurol. 1994;51(3):260-268.
9. Longstreth, WT, Manolio, TA, Arnold, A, et al. Clinical correlates of white matter findings on cranial magnetic resonance imaging of 3301 elderly people. The Cardiovascular Health Study. Stroke. 1996;27(8):1274-1282.10.1161/01.STR.27.8.1274
10. Barber, R, Scheltens, P, Gholkar, A, et al. White matter lesions on magnetic resonance imaging in dementia with Lewy bodies, Alzheimer’s disease, vascular dementia, and normal aging. J Neurol Neurosurg Psychiatry. 1999;67(1):66-72.
11. Debette, S, Markus, HS. The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ. 2010;341:c3666.10.1136/bmj.c3666
12. Thomas, AJ, Perry, R, Kalaria, RN, et al. Neuropathological evidence for ischemia in the white matter of the dorsolateral prefrontal cortex in late-life depression. Int J Geriatr Psychiatry. 2003;18(1):7-13.10.1002/gps.720
13. Debette, S, Bombois, S, Bruandet, A, et al. Subcortical hyperintensities are associated with cognitive decline in patients with mild cognitive impairment. Stroke. 2007;38(11):2924-2930.
14. Wardlaw, JM, Valdés Hernández, MC, Muñoz-Maniega, S. What are white matter hyperintensities made of? Relevance to vascular cognitive impairment. J Am Heart Assoc. 2015;4(6):001140.
15. Fazekas, F, Chawluk, JB, Alavi, A, et al. MR signal abnormalities at 1.5 T in Alzheimer’s dementia and normal aging. AJR Am J Roentgenol. 1987;149(2):351-356.
16. Scheltens, P, Barkhof, F, Leys, D, et al. A semiquantitative rating scale for the assessment of signal hyperintensities on magnetic resonance imaging. J Neurol Sci. 1993;114(1):7-12.10.1016/0022-510X(93)90041-V
17. de Groot, JC, de Leeuw, FE, Oudkerk, M, et al. Cerebral white matter lesions and cognitive function: The Rotterdam Scan Study. Ann Neurol. 2000;47(2):145-151.
18. DeCarli, C, Fletcher, E, Ramey, V, et al. Anatomical mapping of white matter hyperintensities (WMH). Exploring the relationships between periventricular WMH, deep WMH, and total WMH burden. Stroke. 2005;36(1):50-55.
19. Fazekas, F, Kleinert, R, Offenbacher, H, et al. Pathologic correlates of incidental MRI white matter signal hyperintensities. Neurology. 1993;43(9):1683-1689.10.1212/WNL.43.9.1683
20. Scheltens, P, Leys, D, Barkhof, F, et al. 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):967-972.10.1136/jnnp.55.10.967
21. Scheltens, P, Erkinjunti, T, Leys, D, et al. White matter changes on CT and MRI: an overview of visual rating scales. European Task Force on age-related white matter changes. Eur Neurol. 1998;39(2):80-89.
22. Breteler, MM, van Amerongen, NM, van Swieten, JC, et al. Cognitive correlates of ventricular enlargement and cerebral white matter lesions on magnetic resonance imaging. The Rotterdam Study. Stroke. 1994;25(6):1109-1115.10.1161/01.STR.25.6.1109
23. Whitwell, JL, Peterson, RC, Negash, S, et al. Patterns of atrophy differ among specific subtypes of mild cognitive impairment. Arch Neurol. 2007;64(8):1130-1138.
24. Wahlund, LO, Barkhof, F, Fazekas, F, et al. A new rating scale for age-related white matter changes applicable to MRI and CT. Stroke. 2001;32(6):1318-1322.
25. Bombois, S, Debette, S, Delbeuck, X, et al. Prevalence of subcortical vascular lesions and association with executive function in mild cognitive impairment subtypes. Stroke. 2007;38(9):2595-2597.10.1161/STROKEAHA.107.486407
26. Bombois, S, Debette, S, Bruandet, A, et al. Vascular subcortical hyperintensities predict conversion to vascular and mixed dementia in MCI patients. Stroke. 2008;39(7):2046-2051.10.1161/STROKEAHA.107.505206
27. Baskaya, O, Acar, M, Kandemir, M, et al. Inter-hemispheric atrophy better correlates with expert ratings than hemispheric cortical atrophy. SIU’12. 2012:1-4, https://doi.org/10.1109/SIU.2012.6204783.
28. Iheme, LO, Baskaya, O, Sennaz, A, et al. Atrophy measurement biomarkers using structural MRI for Alzheimer’s disease. Workshop on novel imaging biomarkers for Alzheimer’s Disease and related disorders (NIBAD) MICCAI’12, 2012.
29. Schmidt, R, Fazekas, F, Kleinert, G, et al. Magnetic resonance imaging signal hyperintensities in the deep and subcortical white matter: a comparative study between stroke patients and normal volunteers. Arch Neurol. 1992;49(8):825-827.10.1001/archneur.1992.00530320049011
30. van der Flier, WM, van Straaten, ECW, Barkhof, F, et al. Medial temporal lobe atrophy and white matter hyperintensities are associated with mild cognitive deficits in non-disabled elderly people: The LADIS Study. J Neurol Neurosurg Psychiatry. 2005;76(11):1497-1500.10.1136/jnnp.2005.064998
31. van der Flier, WM, van Straaten, ECW, Barkhof, F, et al. Small vessel disease and general cognitive function in nondisabled elderly. The LADIS Study. Stroke. 2005;36(10):2116-2120.10.1161/01.STR.0000179092.59909.42
32. Wu, RH, Feng, C, Xu, Y, Hua, T, et al. Late-onset depression in the absence of stroke: associated with silent brain infarctions, microbleeds and lesion locations. Int J Med Sci. 2014;11(6):587-592.

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