Morphometric analysis of the frontal horns of the lateral ventricles using normal computed tomographic images

The ventricular system is altered by the normal aging process and various pathological conditions such as Alzheimer’s, schizophrenia, hydrocephalus, and tumors. This study aimed at establishing the normal baseline data regarding the dimensions of the frontal horns of the lateral ventricles in adults Nigerians. This retrospective observational study evaluated CT brain images stored in a Radiology unit in Delta State, Nigeria. Ethical clearance was sought from the Hospital’s ethics board. Images of 202 patients, aged 18 years and above, were included. Measurements of frontal horn length and width were conducted using a standardized digital caliper approach. The data were analyzed based on gender and age groups, employing statistical methods such as t-tests and Pearson correlation. A p-value of < 0.05 in the inferential statistics was deemed statistically significant. The length of the bilateral frontal horns and distance between their tips were significantly higher in males than in females (p<0.05). The left frontal horn length was consistently larger than the right. Both lengths and widths exhibited significant variations across age groups and had a positive correlation with age (p<0.05). The study provides standard reference values for clinicians in the study center to consider during neuroimaging and diagnostic assessments. The gender-, age- and side-related findings enhance the understanding of the normal anatomical diversity, which has crucial clinical implications.

Authors

Publication Details

Journal
European Journal of Anatomy
Published
2024-09-01
DOI
https://doi.org/10.52083/bvbf3444
Citations
1
Primary Topic
Advanced Neuroimaging Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.40
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article

Morphometric analysis of the frontal horns of the lateral ventricles using normal computed tomographic images

Beryl S. Ominde, Patrick Sunday Igbigbi, Joyce Ekeme Ikubor, Orovwoghene Faithful Omoro et al.
1 citations
European Journal of Anatomy
Advanced Neuroimaging Techniques and Applications
0.40
article

Morphometric analysis of the frontal horns of the lateral ventricles using normal computed tomographic images

Beryl S. Ominde, Patrick Sunday Igbigbi, Joyce Ekeme Ikubor, Orovwoghene Faithful Omoro, Emmanuel C. Ogbolu
article en
1 citations

Abstract

The ventricular system is altered by the normal aging process and various pathological conditions such as Alzheimer’s, schizophrenia, hydrocephalus, and tumors. This study aimed at establishing the normal baseline data regarding the dimensions of the frontal horns of the lateral ventricles in adults Nigerians. This retrospective observational study evaluated CT brain images stored in a Radiology unit in Delta State, Nigeria. Ethical clearance was sought from the Hospital’s ethics board. Images of 202 patients, aged 18 years and above, were included. Measurements of frontal horn length and width were conducted using a standardized digital caliper approach. The data were analyzed based on gender and age groups, employing statistical methods such as t-tests and Pearson correlation. A p-value of < 0.05 in the inferential statistics was deemed statistically significant. The length of the bilateral frontal horns and distance between their tips were significantly higher in males than in females (p<0.05). The left frontal horn length was consistently larger than the right. Both lengths and widths exhibited significant variations across age groups and had a positive correlation with age (p<0.05). The study provides standard reference values for clinicians in the study center to consider during neuroimaging and diagnostic assessments. The gender-, age- and side-related findings enhance the understanding of the normal anatomical diversity, which has crucial clinical implications.

European Journal of AnatomyVol. 28(5)
Openalex Percentile: Top 35%
Advanced Neuroimaging Techniques and Applications
0.40
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Morphometric analysis of the frontal horns of the lateral ventricles using normal computed tomographic images — Beryl S. Ominde, Patrick Sunday Igbigbi, et al. · European Journal of Anatomy (2024) | TGRS Research Map | TGRS