{"title":"Quantitative characterization of age-related atrophic changes in cerebral hemispheres: A novel “contour smoothing” fractal analysis method","authors":"Nataliia Maryenko, Oleksandr Stepanenko","doi":"10.1016/j.tria.2023.100263","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Quantitatively assessing age-related atrophic changes in cerebral hemispheres remains a crucial challenge, particularly in distinguishing between normal and pathological brain atrophy caused by neurodegenerative diseases. In this study, we introduced a new fractal analysis algorithm, referred to as the “contour smoothing” method, to quantitatively characterize age-related atrophic changes in cerebral hemispheres.</p></div><div><h3>Materials and methods</h3><p>MRI scans from 100 healthy individuals (44 males, 56 females), aged 18–86 (mean age 41.72 ± 1.58), were analyzed. We used two fractal analysis methods: the novel “contour smoothing” method (with stages: 1–6, 1–5, 2–6, 1–4, 2–5) and the classical “box-counting” method to assess cerebral cortex pial surface contours.</p></div><div><h3>Results</h3><p>Fractal dimensions obtained using the “box-counting” method showed weak or statistically insignificant correlations with age. Conversely, fractal dimensions derived from the “contour smoothing” method exhibited significant age-related correlations. The “contour smoothing” method with 1–4 stages proved more suitable for quantifying atrophic changes. The average fractal dimension for 1–4 coronal sections was 1.402 ± 0.005 (minimum 1.266, maximum 1.490), and for all five tomographic sections, it was 1.415 ± 0.004 (minimum 1.278, maximum 1.514). These fractal dimensions exhibited the strongest correlations with age: r = −0.709 (p < 0.001) and r = −0.669 (p < 0.001), respectively.</p></div><div><h3>Conclusion</h3><p>The “contour smoothing” fractal analysis method introduced in this study can effectively examine cerebral hemispheres to detect and quantify age-related atrophic changes associated with normal or pathological aging. This method holds promise for clinical application in diagnosing neurodegenerative disorders, such as Alzheimer's disease.</p></div>","PeriodicalId":37913,"journal":{"name":"Translational Research in Anatomy","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational Research in Anatomy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214854X23000328","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 1
Abstract
Background
Quantitatively assessing age-related atrophic changes in cerebral hemispheres remains a crucial challenge, particularly in distinguishing between normal and pathological brain atrophy caused by neurodegenerative diseases. In this study, we introduced a new fractal analysis algorithm, referred to as the “contour smoothing” method, to quantitatively characterize age-related atrophic changes in cerebral hemispheres.
Materials and methods
MRI scans from 100 healthy individuals (44 males, 56 females), aged 18–86 (mean age 41.72 ± 1.58), were analyzed. We used two fractal analysis methods: the novel “contour smoothing” method (with stages: 1–6, 1–5, 2–6, 1–4, 2–5) and the classical “box-counting” method to assess cerebral cortex pial surface contours.
Results
Fractal dimensions obtained using the “box-counting” method showed weak or statistically insignificant correlations with age. Conversely, fractal dimensions derived from the “contour smoothing” method exhibited significant age-related correlations. The “contour smoothing” method with 1–4 stages proved more suitable for quantifying atrophic changes. The average fractal dimension for 1–4 coronal sections was 1.402 ± 0.005 (minimum 1.266, maximum 1.490), and for all five tomographic sections, it was 1.415 ± 0.004 (minimum 1.278, maximum 1.514). These fractal dimensions exhibited the strongest correlations with age: r = −0.709 (p < 0.001) and r = −0.669 (p < 0.001), respectively.
Conclusion
The “contour smoothing” fractal analysis method introduced in this study can effectively examine cerebral hemispheres to detect and quantify age-related atrophic changes associated with normal or pathological aging. This method holds promise for clinical application in diagnosing neurodegenerative disorders, such as Alzheimer's disease.
期刊介绍:
Translational Research in Anatomy is an international peer-reviewed and open access journal that publishes high-quality original papers. Focusing on translational research, the journal aims to disseminate the knowledge that is gained in the basic science of anatomy and to apply it to the diagnosis and treatment of human pathology in order to improve individual patient well-being. Topics published in Translational Research in Anatomy include anatomy in all of its aspects, especially those that have application to other scientific disciplines including the health sciences: • gross anatomy • neuroanatomy • histology • immunohistochemistry • comparative anatomy • embryology • molecular biology • microscopic anatomy • forensics • imaging/radiology • medical education Priority will be given to studies that clearly articulate their relevance to the broader aspects of anatomy and how they can impact patient care.Strengthening the ties between morphological research and medicine will foster collaboration between anatomists and physicians. Therefore, Translational Research in Anatomy will serve as a platform for communication and understanding between the disciplines of anatomy and medicine and will aid in the dissemination of anatomical research. The journal accepts the following article types: 1. Review articles 2. Original research papers 3. New state-of-the-art methods of research in the field of anatomy including imaging, dissection methods, medical devices and quantitation 4. Education papers (teaching technologies/methods in medical education in anatomy) 5. Commentaries 6. Letters to the Editor 7. Selected conference papers 8. Case Reports