Parietal atrophy score on magnetic resonance imaging of the brain in normally aging people

Aim: Our intention was to create a simple visual evaluation of parietal atrophy on MRI of the brain useful in identifying neurodegenerative dementias, especially Alzheimer‘s disease. We assessed the changes of the parietal regions dur ing natural aging. Patients and methods: We created a new rat ing scale that we named the Parietal atrophy score. This method is based on semiquantitative scoring of three structures on coronal slices in the entire parietal lobe: parietal gyri, sulcus cingularis posterior and precuneus. Each structure was rated accord ing to the visual classification size as 0 – a normal size without atrophy, 1 – a borderline finding or 2 – a considerable atrophy. These ratings were sum marized into one score for each hemisphere and then these two were integrated into one score for the entire brain. Using a visual rating scale, we clas sified the parietal regions in 74 elderly subjects with a normal Mini-Mental State Examination score (29 ± 1 point) with a wide range of ages between 48–87 years. Results: Increas ing age is as sociated with a mild progression of the parietal lobe atrophy (r = 0.2; p = 0.05). The over all score of the parietal tissue was not as sociated with education, gender or hand dominance. Conclusion: Our new visual rating system of parietal atrophy is an easy and fast method for use in clinical practice. Natural aging is accompanied with negligible parietal atrophic changes. Parietal atrophy score on magnetic resonance imaging of the brain in normally aging people.

  • DOI: 
  • 10.14735/amcsnn2018414

A new MR imaging index for differentiation of progressive supranuclear palsy-parkinsonism from Parkinson's disease

Highlights

  • Distinguishing PSP-P from PD is challenging in the early stages of the disease.
  • Few data exist on the usefulness of MRPI for diagnosing PSP-P patients.
  • MRPI 2.0 is a new version of MRPI which includes the 3rd ventricular width
  • MRPI 2.0 accurately differentiated patients with PSP-P from those with PD.
  • MRPI 2.0 accurately diagnosed PSP-P in the absence of vertical ocular palsy.

Reference: Quattrone A, Morelli M, Nigro S, Quattrone A, Vescio B, Arabia G, Nicoletti G,Nisticò R, Salsone M, Novellino F, Barbagallo G, Le Piane E, Pugliese P, Bosco D, Vaccaro MG, Chiriaco C, Sabatini U, Vescio V, Stanà C, Rocca F, Gullà D, Caracciolo M. A new MR imaging index for differentiation of progressive supranuclear palsy-parkinsonism from Parkinson's disease. Parkinsonism Relat Disord. 2018 Sep;54:3-8. doi: 10.1016/j.parkreldis.2018.07.016

Corpus Callosum Index: A practical method for long-term follow-up in multiple sclerosis

Corpus callosum index


References
Pérez-Álvarez AI, Suárez-Santos P, González-Delgado M, Oliva-Nacarino P. Quantification of brain atrophy in multiple sclerosis using two-dimensional measurements. Neurologia. 2018 Jun 8. pii: S0213-4853(18)30152-X. doi: 10.1016/j.nrl.2018.04.004
Figueira, Fernando Faria Andrade, Santos, Valeria Silva dos, Figueira, Gustavo Medeiros Andrade, & Silva, Ângela Correa Marques da. (2007). Corpus Callosum Index: A practical method for long-term follow-up in multiple sclerosis. Arquivos de Neuro-Psiquiatria, 65(4a), 931-935. https://dx.doi.org/10.1590/S0004-282X2007000600001

A ‘Comprehensive Visual Rating Scale’ for predicting progression to dementia in patients with mild cognitive impairment

Background Numerous efforts have been made to identify biomarkers for predicting the progression of dementia in patients with mild cognitive impairment (MCI), and recently, a comprehensive visual rating scale (CVRS) based on magnetic resonance imaging (MRI) has been validated to assess structural changes in the brain of elderly patients. Based on this, the present study investigated the use of CVRS for predicting dementia and elucidated its association with cognitive change in patients with MCI over a three-year follow-up. Methods We included 340 patients with MCI with more than one follow-up visit. Data were obtained from the Alzheimer’s disease Neuroimaging Initiative study. We assessed all the patients using CVRS and determined their progression to dementia during a follow-up period of over 3 years. The cox proportional hazards model was used to analyze hazard ratios (HRs) of CVRS for disease progression. Further, multiple cognitive measures of the patients over time were fitted using the random effect model to assess the effect of initial CVRS score on subsequent cognitive changes. Results Of 340 patients, 69 (20.2%) progressed to dementia and the median baseline score (interquartile range) of CVRS significantly differed between stable MCI and progressive MCI (9 (5–13) vs 13 (8–17), p<0.001). The initial CVRS score was independently associated with an increased risk of progression to dementia (HR 1.123, 95% confidence interval [CI] 1.059–1.192). From 12 to 24 months, the effect of the interaction between CVRS and interval of follow-up visit on cognitive performance achieved significance (p<0.001). Conclusions Baseline CVRS predicted the progression to dementia in patients with MCI, and was independently associated with longitudinal cognitive decline.
Reference: Jang J-W, Park JH, Kim S, Park YH, Pyun J-M, Lim J-S, et al. (2018) A ‘Comprehensive Visual Rating Scale’ for predicting progression to dementia in patients with mild cognitive impairment. PLoS ONE 13(8): e0201852. https://doi.org/10.1371/journal.pone.0201852

New MRI visual rating scales

Six visual rating scales, three alreary described: medial temporal, posterior, anterior temporal and three new/addapted: orbito-frontal, anterior cingulate and fronto-insula) were assessed in this study

Time to perform visual rating
Mean time to perform and record all six visual rating scales based on three raters assessing the subset study population ( n = 80) was 2.9 ± 1.3 min. Individual rater means and standard deviations were 2.7 ± 1.1, 2.4 ± 1.0 and 3.6 ± 1.6 min.

Inter-rater reliability of visual rating scores
Single measure and average measure ICC results for each scale are shown in Supplementary Table 1 . For the single measures ICC values, representing the reliability of each scale at the level of the individual rater, the MTA scale performed best overall, with very similar results achieved with two raters assessing all 257 scans, and four raters scoring 80 scans [ICC(2,1) ≥ 0.79]. The PA, OF and FI scales also demonstrated good reliability [ICC(2,1) ≥0.71] based on two raters assessing the total study population; reliability was slightly reduced when performed by four raters in the subset population [ICC(2,1) ≥ 0.58]. The reliability of the AC scale was lowest overall [ICC(2,1) range = 0.49–0.62]. As expected, the reliability based on mean rater scores was consistently greater for all scales [ICC(2,k) ≥ 0.73]. There were no material differences in reliability based on the larger or smaller population samples for any scale with the exception of the AT and AC scales, which were less reliable in the larger population sample.

Correlation of grey matter volume with visual rating scores
Voxel-based morphometry analysis revealed a negative partial correlation of higher visual rating score with lower grey matter density for all visual rating scales. 

Reference:
Lorna Harper, Giorgio G. Fumagalli, Frederik Barkhof, Philip Scheltens, John T. O’Brien, Femke Bouwman, Emma J. Burton, Jonathan D. Rohrer, Nick C. Fox, Gerard R. Ridgway, Jonathan M. Schott; MRI visual rating scales in the diagnosis of dementia: evaluation in 184 post-mortem confirmed cases. Brain 2016; 139 (4): 1211-1225. doi: 10.1093/brain/aww005https://academic.oup.com/brain/article-lookup/doi/10.1093/brain/aww005

Methods used for measuring atrophy in Multiple Sclerosis


Location/generic methodologyMethodAdvantagesDisadvantages
Brain/linear and regional measuresThird ventricle widthEasy to implement; rapid analysis; standard acquisition methods; enables targeting of eloquent regionsLimited anatomical scope; may miss subtle effects; may exhibit user bias; high user input
Third ventricle volume
Brain width
Corpus callosum width
Volume on central brain slices
Stereology
Brain/whole brain segmentation approachesCSF volumesIncreased automation reduces user bias and user input; generally higher measurement precisionComplex analysis methods; possibly more complex acquisition schemes
BPF
WBR
BICCR
Fuzzy connectedness
Probabilistic segmentation (SPM)
TDS
SIENAX
Brain/registration‐based methodsMIDASRegional atrophy may become apparentComplex analysis methods; limited application to multiple sclerosis to date
Voxel‐based morphometry
SIENA
Spinal cordManual outliningStraightforwardPossible user bias; high user input
Semi‐automated outline of 3D axial imagesPrecise
Automated whole cord volume measurementLittle user inputComplex analysis methods; limited application to date
Optic nerveManual outliningStraightforwardPossible user bias; high user input
Semi‐automated outline of 3D axial imagesPrecise
Automated whole nerve volume measurementLittle user inputComplex analysis methods; limited application to date
TDS = template‐driven segmentation; MIDAS = Medical Image Display and Analysis Software.

Source: David H. Miller, Frederik Barkhof, Joseph A. Frank, Geoffrey J. M. Parker, Alan J. Thompson. Measurement of atrophy in multiple sclerosis: pathological basis, methodological aspects and clinical relevance . Brain 2002. DOI: http://dx.doi.org/10.1093/brain/awf177