Development of Deep Learning Models for Detection of Neurodegenerative Diseases Using Speech - a Danish Language-based Artificial Intelligence Study (DetectAI)
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 440
- 试验地点
- 2
- 主要终点
- Accuracy of AI model in classifying cognitive impairment vs. unimpaired cognition
研究概览
简要总结
The goal of this observational study is to learn if an artificial intelligence (AI)-based speech analysis tool can identify which patients with memory problems need specialist evaluation at a memory clinic. The main questions it aims to answer are:
Can the AI model accurately distinguish between patients who need referral to a memory clinic (those with dementia or Mild Cognitive Impairment) and patients who don't (those with normal cognition or memory problems from other causes like depression)? Which speech patterns and cognitive test features are most useful for making this distinction?
Researchers will compare speech recordings and cognitive test results from patients diagnosed with dementia or MCI to those from patients with normal cognition or non-neurodegenerative cognitive impairment to see if the AI model can reliably predict who needs specialist dementia care.
Participants will:
Complete standard cognitive tests at the memory clinic Perform structured speech tasks while being audio-recorded Receive their usual clinical evaluation and diagnosis from memory clinic specialists
The results of this study will help develop a tool that can assist doctors in making faster, more accurate decisions about which patients need specialist dementia evaluation, potentially leading to earlier diagnosis and better patient outcomes.
详细描述
Background Dementia is a growing public health challenge, and early and accurate diagnosis is essential for effective care and potential future disease-modifying treatments. Current diagnostic pathways are resource-intensive and associated with long waiting times. Speech reflects cognitive functioning, and recent international studies have shown that machine learning models can detect dementia-related patterns in speech recordings with promising accuracy. This study aims to develop a speech-based deep learning model in a Danish setting, providing a non-invasive and scalable screening tool for use in primary care.
Study Design and Sampling Methods
This is an observational, cross-sectional study. Participants are recruited using two different sampling strategies corresponding to two artificial intelligence (AI) model development tracks:
Track A (Model A) - Retrospective case-control sampling:
This track addresses a focused diagnostic task: identification of Mild Cognitive Impairment (MCI). Participants are patients with a recent diagnosis from the memory clinic at Region Zealand University Hospital (ZUH). Sampling uses convenience sampling prioritizing patients who live close to the hospital, as data collection occurs during home visits. Patients with more recent diagnoses are prioritized to minimize the risk that participants have progressed to a new disease stage since diagnosis (e.g., from MCI to dementia).
研究设计
- 研究类型
- Observational
- 观察模型
- Other
- 时间视角
- Cross Sectional
入排标准
- 年龄范围
- 50 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Model A (patient participants)
- •Age > 50 years
- •Fluent in Danish
- •Minimum of 7 years of schooling
- •A diagnosis of either MCI or AD, given at the SUH memory clinic within 6 months before enrollment
- •Model A (cognitively healthy controls)
- •Age > 50 years
- •Fluent in Danish
- •Minimum of 7 years of schooling
- •Age > 50 years
- •Fluent in Danish
- •Minimum of 7 years of schooling
排除标准
- •Significantly impaired vision or hearing (to the extent that the patient cannot participate in the AI analysis)
- •MMSE score < 16
- •Concomitant diagnoses which are expected to influence cognitive impairment (eg. depression)
- •Patients unable to give consent
- •Patients with alcohol consumption >21 standard alcohol units per week
- •Any history of speech or language impairment predating the current condition
- •Cognitively healthy controls:
- •Significantly impaired vision or hearing (to the extent that the patient cannot participate in the AI analysis)
- •MMSE < 26 and ACE < 90
- •Clinical, laboratory, or neuroradiological findings that could affect cognitive functions
- •Known diseases which are expected to impair cognitive functions
- •Any history of speech or language impairment predating the current condition
- •Patients with alcohol consumption >21 standard alcohol units per week.
- •Significantly impaired vision or hearing (to the extent that the patient cannot participate in the AI analysis)
- •MMSE score < 16
- •Patients unable to give consent
- •Patients with concomitant psychosis or severe psychiatric comorbidities other than depression
- •Any history of speech or language impairment predating the current condition
研究组 & 干预措施
Cognitively Healthy Control Participants for Model A
We seek to enroll 40 age-matched cognitively healthy control participants for the training of model A.
干预措施: Mini-mental State Examination (Diagnostic Test)
Cognitively Healthy Control Participants for Model A
We seek to enroll 40 age-matched cognitively healthy control participants for the training of model A.
干预措施: Addenbrooke's Cognitive Examination (Diagnostic Test)
Cognitively Healthy Control Participants for Model A
We seek to enroll 40 age-matched cognitively healthy control participants for the training of model A.
干预措施: Speech Task - Picture Description (Other)
Cognitively Healthy Control Participants for Model A
We seek to enroll 40 age-matched cognitively healthy control participants for the training of model A.
干预措施: Speech Task - Picture Recall (Other)
Cognitively Healthy Control Participants for Model A
We seek to enroll 40 age-matched cognitively healthy control participants for the training of model A.
干预措施: MRI (Diagnostic Test)
Cognitively Healthy Control Participants for Model A
We seek to enroll 40 age-matched cognitively healthy control participants for the training of model A.
干预措施: blood sampling (Diagnostic Test)
Cognitively Healthy Control Participants for Model A
We seek to enroll 40 age-matched cognitively healthy control participants for the training of model A.
干预措施: Depression screening (Diagnostic Test)
Cognitively Healthy Control Participants for Model A
We seek to enroll 40 age-matched cognitively healthy control participants for the training of model A.
干预措施: Somatic- and neurological examination (Other)
Cognitively Healthy Control Participants for Model A
We seek to enroll 40 age-matched cognitively healthy control participants for the training of model A.
干预措施: Speech Task - Picture Narrative (Other)
Patient Participants for Model A
We seek to retrospectively enroll patients from the ZUH memory clinic with a diagnosis of either Alzheimer's Disease (AD, n=50) or MCI (n=50), made within 6 months prior to enrollment. These participants will be used for the training of model A.
干预措施: Mini-mental State Examination (Diagnostic Test)
Patient Participants for Model A
We seek to retrospectively enroll patients from the ZUH memory clinic with a diagnosis of either Alzheimer's Disease (AD, n=50) or MCI (n=50), made within 6 months prior to enrollment. These participants will be used for the training of model A.
干预措施: Addenbrooke's Cognitive Examination (Diagnostic Test)
Patient Participants for Model A
We seek to retrospectively enroll patients from the ZUH memory clinic with a diagnosis of either Alzheimer's Disease (AD, n=50) or MCI (n=50), made within 6 months prior to enrollment. These participants will be used for the training of model A.
干预措施: Speech Task - Picture Description (Other)
Patient Participants for Model A
We seek to retrospectively enroll patients from the ZUH memory clinic with a diagnosis of either Alzheimer's Disease (AD, n=50) or MCI (n=50), made within 6 months prior to enrollment. These participants will be used for the training of model A.
干预措施: Speech Task - Picture Recall (Other)
Patient Participants for Model A
We seek to retrospectively enroll patients from the ZUH memory clinic with a diagnosis of either Alzheimer's Disease (AD, n=50) or MCI (n=50), made within 6 months prior to enrollment. These participants will be used for the training of model A.
干预措施: Speech Task - Picture Narrative (Other)
Patient Participants for Model B
We will prospectively recruit newly referred patients for the memory clinic at ZUH. Enrollment happens at first patient visit. At this time, diagnosis is not yet known, but assumed present.
干预措施: Mini-mental State Examination (Diagnostic Test)
Patient Participants for Model B
We will prospectively recruit newly referred patients for the memory clinic at ZUH. Enrollment happens at first patient visit. At this time, diagnosis is not yet known, but assumed present.
干预措施: Addenbrooke's Cognitive Examination (Diagnostic Test)
Patient Participants for Model B
We will prospectively recruit newly referred patients for the memory clinic at ZUH. Enrollment happens at first patient visit. At this time, diagnosis is not yet known, but assumed present.
干预措施: Speech Task - Picture Description (Other)
Patient Participants for Model B
We will prospectively recruit newly referred patients for the memory clinic at ZUH. Enrollment happens at first patient visit. At this time, diagnosis is not yet known, but assumed present.
干预措施: Speech Task - Picture Recall (Other)
Patient Participants for Model B
We will prospectively recruit newly referred patients for the memory clinic at ZUH. Enrollment happens at first patient visit. At this time, diagnosis is not yet known, but assumed present.
干预措施: Speech Task - Picture Narrative (Other)
结局指标
主要结局
Accuracy of AI model in classifying cognitive impairment vs. unimpaired cognition
时间窗: At baseline (speech recording)
Measured by sensitivity, specificity, AUR-ROC of AI predictions compared to clinical consensus diagnosis, using baseline speech recordings from participants. Model performance will be measured after database lock at study completion.
次要结局
- Accuracy for dementia vs. depression(At baseline (speech recording))
- Sub-classification of Mild Cognitive Impairment (MCI) into progressive vs. non-progressive(At baseline (speech recording) and up to 12 months after enrollment (to determine progression))
- Classification of dementia subtypes (AD, VaD, LBD, FTD)(At baseline (speech recording))
- Comparison with established biomarkers(At baseline, or at time of biomarker testing if performed after baseline)
- Feature importance analysis(At baseline (speech recording))
- Accuracy for dementia vs. depression(At baseline (speech recording))
- Sub-classification of Mild Cognitive Impairment (MCI) into progressive vs. non-progressive(At baseline (speech recording) and up to 12 months after enrollment (to determine progression))
- Classification of dementia subtypes (AD, VaD, LBD, FTD)(At baseline (speech recording))
- Comparison with established biomarkers(At baseline, or at time of biomarker testing if performed after baseline)
- Feature importance analysis(At baseline (speech recording))