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.
Elsevier, Translational Research in Anatomy, Volume 33, November 2023