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Peer-reviewedCC BY-NC-ND 4.0Alzheimer's Research & Therapy

MemTrax as a scalable digital triage tool for mild cognitive impairment screening: primary validation in Alzheimer’s disease and exploratory analysis in Parkinson’s disease

  • Xinchong Shi1
  • Haifan Kong2
  • Weineng Chen2
  • Lishan Lin2
  • Kang Yuan2
  • Fengjuan Su2
  • Yating Wang2
  • Ya Zhang2
  • Jiayi Zhou2
  • Xianbo Zhou3,4
  • Curtis B. Ashford5
  • Feng Li6
5 more authors
  • J Wesson Ashford7
  • Michael F. Bergeron8
  • Zhong Pei2
  • Yifan Zheng2
  • Wenbiao Xian2
8 affiliations
  1. 1Department of Nuclear Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
  2. 2Department of Neurology, The First Affiliated Hospital, Guangdong Provincial Key Laboratory of Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Sun Yat-sen University, No.58 Zhongshan Road 2, Guangzhou, 510080 China
  3. 3Center for Alzheimer’s Research, Washington Institute of Clinical Research, Vienna, VA USA
  4. 4AstraNeura, Co., Ltd, Shanghai, China
  5. 5MemTrax, LLC, Redwood City, CA USA
  6. 6Kunming Escher Technology Co. Ltd, Kunming, Yunnan China
  7. 7Department of Psychiatry & Behavioral Sciences, War Related Illness & Injury Study Center, VA Palo Alto Health Care System, Stanford University, Palo Alto, CA USA
  8. 8Department of Health Sciences, University of Hartford, West Hartford, CT USA
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Abstract

Background: Alzheimer’s disease (AD) and Parkinson’s disease (PD) pose escalating global health challenges, with early detection of mild cognitive impairment (MCI) being critical for timely intervention. The 2023 Delphi consensus highlights the need for scalable tools suitable for primary care. This study aimed to validate the MemTrax as a rapid memory-focused triage tool against consensus-recommended cognitive assessments, including the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA), for detecting MCI due to Alzheimer’s disease (AD-MCI) as the primary objective, and to explore its performance in MCI due to Parkinson’s disease (PD-MCI) as an exploratory aim, evaluating its utility as a rapid, accessible digital tool.

Methods: We conducted a cross-sectional study enrolling 222 participants: 74 with AD-MCI, 73 healthy controls (HCs; primary cohort); 42 PD patients with normal cognition (PD-NC), 33 with PD-MCI (exploratory cohort). All participants underwent MMSE, MoCA and MemTrax testing. Diagnostic accuracy, optimal cut‑offs, and correlations between MemTrax parameters (percent correct [MTx‑%C], reaction time [MTx‑RT], composite score [MTx‑Cp]) and standard cognitive measures were evaluated.

Results: In the primary AD cohort, MTx-%C showed an area under the curve (AUC) of 0.876 (95% CI: 0.813–0.926) for discriminating AD-MCI from HCs, comparable to MoCA (AUC = 0.879) and MMSE (AUC = 0.916). At a cut-off of ≤ 80%, MTx-%C achieved a sensitivity of 70.3% and specificity of 90.4%. In the exploratory PD cohort, MTx-%C (AUC = 0.808) showed similar discrimination to MMSE (AUC = 0.694) in differentiating PD-MCI from PD-NC (DeLong’s test, p = 0.142). Multivariate analysis of MTx-%C, MTx-RT, and MTx-Cp demonstrated significant separation between MCI and cognitively normal groups in both the AD and PD cohorts. MTx-%C showed significant correlations with MMSE in AD (r = 0.709) and PD (r = 0.340), and with MoCA in AD (r = 0.601) and PD (r = 0.608). MemTrax metrics correlated significantly with distinct domain-level associations reflecting disease-specific cognitive profiles.

Conclusions: MemTrax demonstrates good diagnostic accuracy comparable to established cognitive screening tools for AD-MCI (primary cohort), supporting its use as a rapid, scalable, and culturally neutral digital memory-focused triage tool. Exploratory findings in PD-MCI are promising but require confirmatory studies. Its brevity and automation support practical implementation in primary care and community settings, potentially facilitating earlier detection and stratification of cognitive impairment.

Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s13195-026-02153-x.

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Cite

BibTeXRIS
BibTeX
@article{shi2026memtrax,
  title = {{MemTrax as a scalable digital triage tool for mild cognitive impairment screening: primary validation in Alzheimer’s disease and exploratory analysis in Parkinson’s disease}},
  author = {Xinchong Shi and Haifan Kong and Weineng Chen and Lishan Lin and Kang Yuan and Fengjuan Su and Yating Wang and Ya Zhang and Jiayi Zhou and Xianbo Zhou and Curtis B. Ashford and Feng Li and J Wesson Ashford and Michael F. Bergeron and Zhong Pei and Yifan Zheng and Wenbiao Xian},
  journal = {Alzheimer's Research \& Therapy},
  year = {2026},
  month = aug,
  doi = {10.1186/s13195-026-02153-x},
  url = {https://doi.org/10.1186/s13195-026-02153-x},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - MemTrax as a scalable digital triage tool for mild cognitive impairment screening: primary validation in Alzheimer’s disease and exploratory analysis in Parkinson’s disease
AU  - Xinchong Shi
AU  - Haifan Kong
AU  - Weineng Chen
AU  - Lishan Lin
AU  - Kang Yuan
AU  - Fengjuan Su
AU  - Yating Wang
AU  - Ya Zhang
AU  - Jiayi Zhou
AU  - Xianbo Zhou
AU  - Curtis B. Ashford
AU  - Feng Li
AU  - J Wesson Ashford
AU  - Michael F. Bergeron
AU  - Zhong Pei
AU  - Yifan Zheng
AU  - Wenbiao Xian
PY  - 2026
DA  - 2026/08/08
JO  - Alzheimer's Research & Therapy
DO  - 10.1186/s13195-026-02153-x
UR  - https://doi.org/10.1186/s13195-026-02153-x
AB  - Background: Alzheimer’s disease (AD) and Parkinson’s disease (PD) pose escalating global health challenges, with early detection of mild cognitive impairment (MCI) being critical for timely intervention. The 2023 Delphi consensus highlights the need for scalable tools suitable for primary care. This study aimed to validate the MemTrax as a rapid memory-focused triage tool against consensus-recommended cognitive assessments, including the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA), for detecting MCI due to Alzheimer’s disease (AD-MCI) as the primary objective, and to explore its performance in MCI due to Parkinson’s disease (PD-MCI) as an exploratory aim, evaluating its utility as a rapid, accessible digital tool.  Methods: We conducted a cross-sectional study enrolling 222 participants: 74 with AD-MCI, 73 healthy controls (HCs; primary cohort); 42 PD patients with normal cognition (PD-NC), 33 with PD-MCI (exploratory cohort). All participants underwent MMSE, MoCA and MemTrax testing. Diagnostic accuracy, optimal cut‑offs, and correlations between MemTrax parameters (percent correct [MTx‑%C], reaction time [MTx‑RT], composite score [MTx‑Cp]) and standard cognitive measures were evaluated.  Results: In the primary AD cohort, MTx-%C showed an area under the curve (AUC) of 0.876 (95% CI: 0.813–0.926) for discriminating AD-MCI from HCs, comparable to MoCA (AUC = 0.879) and MMSE (AUC = 0.916). At a cut-off of ≤ 80%, MTx-%C achieved a sensitivity of 70.3% and specificity of 90.4%. In the exploratory PD cohort, MTx-%C (AUC = 0.808) showed similar discrimination to MMSE (AUC = 0.694) in differentiating PD-MCI from PD-NC (DeLong’s test, p = 0.142). Multivariate analysis of MTx-%C, MTx-RT, and MTx-Cp demonstrated significant separation between MCI and cognitively normal groups in both the AD and PD cohorts. MTx-%C showed significant correlations with MMSE in AD (r = 0.709) and PD (r = 0.340), and with MoCA in AD (r = 0.601) and PD (r = 0.608). MemTrax metrics correlated significantly with distinct domain-level associations reflecting disease-specific cognitive profiles.  Conclusions: MemTrax demonstrates good diagnostic accuracy comparable to established cognitive screening tools for AD-MCI (primary cohort), supporting its use as a rapid, scalable, and culturally neutral digital memory-focused triage tool. Exploratory findings in PD-MCI are promising but require confirmatory studies. Its brevity and automation support practical implementation in primary care and community settings, potentially facilitating earlier detection and stratification of cognitive impairment.  Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s13195-026-02153-x.
SN  - 1758-9193
ER  -