Department of Psychology and Psychotherapy, University Witten/Herdecke, Witten, Germany.
Nürtingen-Geislingen University (HfWU), Institute of Research and Development in Art Therapies, Nürtingen, Germany.
J Alzheimers Dis. 2019;68(4):1561-1574. doi: 10.3233/JAD-181029.
The digital tree drawing test (dTDT) is a newly developed screening tool for the early detection of Alzheimer's disease. It is performed with a digitizing pen, recording each pen stroke with temporal and spatial precision. It was hypothesized that movement characteristics recorded during the painting process contribute to the identification of patients with mild cognitive impairment (MCI) and early dementia of the Alzheimer type (eDAT). The study population consisted of 187 participants (67 healthy controls, 64 MCI, and 56 eDAT patients) with a mean age of 68.6±10.6 years. Between-group comparisons of the dTDT-variables were conducted with analysis of variance. The diagnostic power of dTDT variables was analyzed with stepwise logistic regressions and areas under curve (AUC) of receiver operating control curves. Cognitively impaired persons used less colors and line widths and changed them less often than healthy subjects (p-values ≤0.05). Compared to control, eDAT patients had larger not-painting periods, were slower, and their pictures had less contrast, image size, and complexity (p-values ≤0.01). Logistic regression models of stepwise selected dTDT variables resulted in an AUC of 0.84 (95% confidence interval (CI) [0.79, 0.90], sensitivity = 0.78, specificity = 0.77) for discriminating healthy subjects from all cognitive impaired, an AUC of 0.77. (95% CI [0.69; 0.85], sensitivity = 0.56, specificity = 0.83) for discriminating healthy controls from MCI patients and an AUC of 0.90 (95% CI [0.84, 0.96], sensitivity = 0.86, specificity = 0.82) for discriminating controls from eDAT patients. The results suggest that digital recording of pen-stroke data during the drawing process can contribute to the screening of cognitive impaired patients.
数字树图测试（dTDT）是一种新开发的用于早期发现阿尔茨海默病的筛查工具。它使用数字化笔进行，以时间和空间精度记录每个笔触。据推测，在绘画过程中记录的运动特征有助于识别轻度认知障碍（MCI）和早期阿尔茨海默病型痴呆（eDAT）患者。研究人群由 187 名参与者组成（67 名健康对照组，64 名 MCI 和 56 名 eDAT 患者），平均年龄为 68.6±10.6 岁。采用方差分析比较组间 dTDT 变量差异。采用逐步逻辑回归和受试者工作特征曲线下面积（AUC）分析 dTDT 变量的诊断能力。与健康受试者相比，认知障碍者使用的颜色和线宽较少，且变化频率较低（p 值≤0.05）。与对照组相比，eDAT 患者的无绘画期更大，速度更慢，其图像对比度、图像大小和复杂度较小（p 值≤0.01）。逐步选择的 dTDT 变量的逻辑回归模型得出的 AUC 为 0.84（95%置信区间（CI）[0.79，0.90]，敏感性=0.78，特异性=0.77），用于区分健康受试者和所有认知障碍者，AUC 为 0.77（95%CI[0.69；0.85]，敏感性=0.56，特异性=0.83），用于区分健康对照组和 MCI 患者，AUC 为 0.90（95%CI[0.84，0.96]，敏感性=0.86，特异性=0.82），用于区分对照组和 eDAT 患者。结果表明，在绘画过程中数字化记录笔的笔触数据有助于筛选认知障碍患者。
