Substantiation of threshold values of ventricular-cranial coefficients for the Russian adult population: the retrospective study based on data from adult subjects

Introduction: The diagnosis, treatment, and prevention of neurodegenerative conditions and dementia remain highly important. One of the most common anatomical manifestations of the conditions accompanied by cognitive impairment is ventriculomegaly, which is assessed using ventricular-cranial coefficients. The modern development of information technologies allows estimating the distribution of coefficient values across the general population and clarifying the normal values of these coefficients for patients of different age groups, depending on their gender.

Objective: Тhe study was to use modern AI technologies to evaluate generally accepted indicators of ventriculomegaly in the population as risk factors for various neurodegenerative processes and to determine the normal values of ventricular-cranial coefficients depending on the gender and age of the study subjects.

Materials and methods : A retrospective descriptive epidemiological study was conducted in Moscow for a period of one calendar year — from February 2024 to February 2025. The results of brain CT scans of 121,973 subjects were analyzed, of which 59,079 (48.4%) were men and 62,885 (51.6%) were women. The analysis included the assessment of such indicators as VCR1, VCR2, VCR3, and the width of the third ventricle of the brain and was performed in an automated mode.

Statistics: Data were summarized using descriptive statistics, including the number of non-missing values (N), minimum (Min), maximum (Max), arithmetic mean (M), standard deviation (SD), 95% confidence interval (CI) for the mean, median (Me), and first and third quartiles (Q1, Q3). Analysis of variance (ANOVA) was employed to compare numerical variables. Regression analysis was performed to identify factors significantly correlating with fluctuations in coefficients.

Results: With age, the median of VCR1 increases from 25.0% to 31.0% in the mixed group (men and women), VCR2 from 9.0% to 17.0%, VCR3 from 4.0% to 9.0%, and the width of the third ventricle from 5 mm to 11 mm. An increase in age by one year has a significant impact on the change in these indices in all groups, e.g., the VCR1 increases by 0.15 units for each year of increase in the subject’s age. The dynamics of the VCR1, VCR2, and VCR3 are identical for men and women. The width of the third ventricle in men increases by 10% more than in the female group. According to the regression analysis data, all four assessed indicators are significantly higher on average in men than in women of the same age (p<0.001, confidence intervals: VCR1 – 1.63, 2.0; VCR2 –  1.3, 1.78; VCR3 –  0.41; 1.33; the third ventricle width –  0.95, 1.16). The average VCR1 values in the group of centenarians are more than 0.3 for both sexes.

Discussion: The observed morphometric parameters exhibited population-level variability; however, as we achieved sufficient sample size, our analysis revealed that sexual dimorphism and deviations from normal values significantly correlate with patient age. Reference values for the evaluated morphometric coefficients cannot be identical across sex and age groups. In healthy cohorts, these coefficients are inherently higher in elderly individuals than in younger populations, with males exhibiting higher values than females within the same age group. Deviations from the reference values are critical, particularly among elderly patients and more specifically within the male demographic.

Conclusion: The value of VCR1, VCR2, VCR3, and the width of the third ventricle are statistically significantly higher in men of all age groups than in women of the same age group. With age, the value of VCR1, VCR2, and VCR3 increases synchronously in both sexes, and the width of the third ventricle in men increases at an accelerated rate compared to women (the difference is approximately 10%). New refined normal values of ventricular-cranial coefficients for different age groups of the Russian population depending on gender are proposed.

1. Jalbert J., Daiello L., Lapane K. Dementia of the Alzheimer Type // Epidemiol Rev. 2008. Vol. 30, No. 1. Р. 15–34. doi: 10.1093/epirev/mxn008.

2. Barnes D.E., Yaffe K. The projected effect of risk factor reduction on Alzheimer’s disease prevalence // Lancet Neurol. 2011. Sep; Vol. 10, No. 9. Р. 819–828. doi: 10.1016/S1474-4422(11)70072-2.

3. Breijyeh Z., Karaman R. Comprehensive Review on Alzheimer’s Disease: Causes and Treatment // Molecules. 2020. Vol. 25. Р. 5789. https://doi.org/10.3390/molecules25245789.

4. Revi M. Alzheimer’s Disease Therapeutic Approaches // Adv. Exp. Med. Biol. 2020. Vol. 1195. Р. 105–116. doi: 10.1007/978-3-030-32633-3_15.

5. Todd K.L., Brighton T., Norton E.S. et al. for the Alzheimer’s Disease Neuroimaging Initiative (2018) Ventricular and Periventricular Anomalies in the Aging and Cognitively Impaired Brain // Front. Aging Neurosci. 2017. Vol. 9. Р. 445. doi: 10.3389/fnagi.2017.00445.

6. [Akhmetzyanov B.M., Kremneva E.I., Morozova S.N. et al. Magnetic resonance imaging in evaluation of the cerebrospinal fluid system in norm and with various diseases of the nervous system. REJR, 2018, Vol. 8, No. 1, рр. 145–166 (In Russ.)]. doi: 10.21569/2222-7415-2018-8-1-145-166.

7. [Bogomyakova O.B., Valova G.S., Stankevich Yu.A. et al. Assessment of hemo- and cerebrospinal fluid dynamics disorders in idiopathic normal pressure hydrocephalus according to MRI data: a prospective study. Diagnostic radiology and radiotherapy, 2024, Vol. 15, No. 4, рр. 57–66 (In Russ.)]. https://doi.org/10.22328/2079-5343-2024-15-4-57-66.

8. [Lobzin V.Yu., Kiselev V.N., Fokin V.F. et al. Voxel-based moprhometry in Alzheimer’s disease and vascular cognitive impairment. Bulletin of the Russian Military Medical Academy, 2013, No. 3, pp. 48–54 (In Russ.)].

9. Shook B.A., Lennington J.B., Acabchuk R.L. et al. Ventriculomegaly associated with ependymal gliosis and declines in barrier integrity in the aging human and mouse brain // Aging Cell. 2014. Vol. 2. Р. 340–350. doi: 10.1111/acel.12184.

10. Madsen S.K., Gutman B.A., Joshi S.H. et al. Mapping ventricular expansion onto cortical gray matter in older adults // Neurobiol. Aging. 2015. Vol. 36. Р. S32– S41. doi: 10.1016/s0006-3223(03)00953-3.

11. [Puras J.V., Grigorieva E.V. The neurovisualization methods in diagnostics of head injury. Part 1. Computer tomography and magnetic resonance imaging. Russian journal of neurosurgery, 2014, Vol. 2, рр. 7–16 (In Russ.)]. https://doi.org/10.17650/1683-3295-2014-0-2-7-16.

12. Brix M.K., Westman E., Simmons A. et al. The Evans’ Index revisited: New cut-off levels for use in radiological assessment of ventricular enlargement in the elderly // Eur. J. Radiol. 2017. Oct; Vol. 95. Р. 28–32. doi: 10.1016/j.ejrad.2017.07.013.

13. Jaraj D., Rabiei K., Marlow T. et al. Estimated ventricle size using Evans index: reference values from a population-based sample // Eur. J. Neurol. 2017. Vol. 24, No. 3. P. 468–474.

14. [Murashko M.A., Vankov V.V., Panin A.I. et al. Implementation of artificial intelligence technologies in healthcare in Russia: results of 2024. National Health Care (Russia), 2025, Vol. 6, No. 3, рр. 6–19 (In Russ.)]. https://doi.org/10.47093/2713-069X.2025.6.3.6-19.

15. [Khoruzhaya A.N., Arzamasov K.M., Kodenko M.R. et al. Diagnosis of Intracranial Hemorrhages Based on Brain Computed Tomography with Artificial Intelligence. Digital Diagnostics, 2025, Vol. 6, No. 2, рр. 214–228 (In Russ.)]. doi: 10.17816/DD645364 EDN: RFYVMC.

16. Zhou X., Xia J. Application of Evans Index in Normal Pressure Hydrocephalus Patients: A Mini Review // Front. Aging Neurosci. 2022. Jan 11; Vol. 13. Р. 783092. doi: 10.3389/fnagi.2021.783092.

17. Espay A.J., Da Prat G.A., Dwivedi A.K. et al. Deconstructing normal pressure hydrocephalus: Ventriculomegaly as early sign of neurodegeneration // Ann. Neurol. 2017. Oct; Vol. 82, No. 4. Р. 503–513. doi: 10.1002/ana.25046.

18. Ambarki K., Israelsson H., Wahlin A. et al. Brain ventricular size in healthy elderly: comparison between Evans index and volume measurement // Neurosurgery. 2010. Vol. 67. Р. 94–99. doi: 10.1227/01.NEU.0000370939.30003.D1.

19. Del B.O., Mera R.M., Gladstone D. et al. Inverse relationship between the evans index and cognitive performance in non-disabled, stroke-free, community-dwelling older adults. A population-based study // Clin. Neurol. Neurosurg. 2018. Vol. 169. Р. 139–143. 10.1016/j.clineuro.2018.03.021.

20. Yamada S., Ishikawa M., Yamamoto K. Optimal diagnostic indices for idiopathic normal pressure hydrocephalus based on the 3D quantitative volumetric analysis for the cerebral ventricle and subarachnoid space // AJNR Am. J. Neuroradiol. 2015. Vol. 362. Р. 2262–2269. doi: 10.3174/ajnr.A4440.

21. Brix M.K., Westman E., Simmons A. et al. The Evans’ Index revisited: new cut-off levels for use in radiological assessment of ventricular enlargement in the elderly // Eur. J. Radiol. 2017. Vol. 95. Р. 28–32. doi: 10.1016/j.ejrad.2017.07.013.

22. Curra A., Pierelli F., Gasbarrone R. et al. The ventricular system enlarges abnormally in the seventies, earlier in men, and first in the frontal horn: a study based on more than 3,000 scans // Aging Neurosci. 2019. Vol. 11. Р. 294. doi: 10.3389/fnagi.2019.00294.

23. Ghorbanlou M., Moradi F., Kazemi-Galougahi M.H., Abdollahi M. In search of subcortical and cortical morphologic alterations of a normal brain through aging: an investigation by computed tomography scan // Anat. Cell Biol. 2024. Mar 31; Vol. 57, No. 1. Р. 45–60. doi: 10.5115/acb.23.219.

24. Dzefi-Tettey K., Edzie E.K.M., Gorleku P.N. et al. Evans index among adult Ghanaians on normal head computerized tomography scan // Heliyon. 2021. May 7; Vol. 7, No. 5. e06982. doi: 10.1016/j.heliyon.2021.e06982.

25. Alomar S.A., Ghoneim A.H. Normative parameters of the Evans Index using Computer Tomography in the Saudi population // Neurosciences (Riyadh). 2024. May; Vol. 29, No. 2. Р. 122–127. doi: 10.17712/nsj.2024.2.20230097.

26. Arun Kumar S., Kumari S.M., Anand M.V. et al. Evaluation of Evan’s index in South Indian population using computed tomography // Int. J. Anat. Radiol. Surg. 2017. Vol. 6, No. 3. Р. RO28–RO31.

27. Hamidu A.U., Olarinoye-Akorede S.A., Ekott D.S. et al. Computerized tomographic study of normal Evans index in adult Nigerians // J. Neurosci Rural. Pract. 2015. Jan; Vol. 6, No. 1. Р. 55–58. doi: 10.4103/0976-3147.143195.

28. Pradhan A., Chalise U., Shrestha A., Dhungana S. Study of Normal Values of Evan’s Index on Brain CT Scan in Individuals attending Nepal Medical College Teaching Hospital, Kathmandu, Nepal // Nepal Medical College Journal. 2021. Vol. 23, No. 1. Р. 41–47. https://doi.org/10.3126/nmcj.v23i1.36227.