Cerebral cortex thinning and cerebral blood flow (CBF) reduction are typically observed during normal healthy aging. However, imaging-based age prediction models have primarily used morphological features of the brain. Complementary physiological CBF information might result in an improvement in age estimation. In this study, T1-weighted structural magnetic resonance imaging and arterial spin labeling CBF images were acquired in 146 healthy participants across the adult life span. Sixty-eight cerebral cortex regions were segmented, and the cortical thickness and mean CBF were computed for each region. Linear regression with age was computed for each region and data type, and laterality and correlation matrices were computed. Sixteen predictive models were trained with the cortical thickness and CBF data alone as well as a combination of both data types. The age explained more variance in the cortical thickness data (average R2 of 0.21) than in the CBF data (average R2 of 0.09). All 16 models performed significantly better when combining both measurement types and using feature selection, and thus, we conclude that the inclusion of CBF data marginally improves age estimation.

中文翻译：

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脑血流量和皮质厚度的年龄相关差异在年龄预测中的应用

大脑皮层变薄和脑血流量 (CBF) 减少通常在正常健康老龄化期间观察到。然而，基于成像的年龄预测模型主要使用大脑的形态特征。补充生理 CBF 信息可能会导致年龄估计的改进。在这项研究中，T1 加权结构磁共振成像和动脉自旋标记 CBF 图像在 146 名成年健康参与者中获得。分割了 68 个大脑皮层区域，并计算了每个区域的皮质厚度和平均 CBF。为每个区域和数据类型计算随年龄的线性回归，并计算侧向性和相关性矩阵。仅使用皮质厚度和 CBF 数据以及两种数据类型的组合对 16 个预测模型进行了训练。与 CBF 数据（平均 R2 为 0.09）相比，年龄解释了皮质厚度数据（平均 R2 为 0.21）的更多差异。在结合两种测量类型和使用特征选择时，所有 16 个模型的表现都明显更好，因此，我们得出结论，包含 CBF 数据略微改善了年龄估计。