Quantitative characterization of age-related atrophic changes in cerebral hemispheres: A novel “contour smoothing” fractal analysis method

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.