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| ID | Type | Description | Link |
|---|---|---|---|
| CIV-22-06-039726 | Other Identifier | Medical Products Agency of Sweden (Läkemedelsverket) |
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| Name | Class |
|---|---|
| Blekinge Institute of Technology | OTHER |
| Blekinge County Council Hospital | OTHER |
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Two devices will be tested in this research:
Worldwide, millions of people are affected by neurodegenerative diseases (e.g., Alzheimer's disease, dementia). Those diseases are having a tremendous socio-economic impact on our society. The cost associated with treating and caring for those diseases is enormous. Overwhelming evidence indicates how selective lifestyle changes (e.g., reducing exposure to known risk factors) can sometimes significantly decrease the probability of developing the disease or delay its onset. However, the diseases must be diagnosed early for them to be effective. There is a lack of accessible, inexpensive, and non-invasive practices that would allow for an early diagnosis of different diseases, even at the primary physician's office. Mantis Photonics and Blekinge Tekniska Högskola (Institustionen för Hälsa) aim to fill this urgent unmet medical need.
Strong indications of the possibility of classifying Alzheimer's status based on hyperspectral scans of the retina have been published by different researchers. These results were obtained based on images taken with hyperspectral cameras with a different working principle than the Mantis Photonics camera. The working principle of the Mantis Photonics camera allows making a hyperspectral retinoscopy with the same spectral range and comparable or better spectral resolution with a machine that is more modular and lower in cost. There is thus reason to hypothesize retinal scans taken with the Mantis Photonics camera can be used for the same classification task.
Previous studies on the automated tablet computer cognitive test CoGNIT have established validity, reliability and sensitivity for testing patients with Normal Pressure Hydrocephalus (NPH) . Recently feasibility of testing in Mild Cognitive Impairment (MCI) was affirmed (Behrens, Berglund, & Anderberg, CoGNIT Automated Tablet Computer Cognitive Testing in Patients With Mild Cognitive Impairment: Feasibility Study, 2022). In NPH patients, CoGNIT was more sensitive to cognitive impairment at baseline and cognitive improvement after shunt surgery than the Mini-Mental State Examination (MMSE).
Blood tests for amyloid-β and other biomarkers related to Alzheimer's disease are being investigated for clinical practice, but the technique is not accepted as a standard test. Research has shown that renal function influences amyloid-β clearance from the body. Also, analytical errors influence test results. Therefore, one can question the influence of normal repeatability of the blood test result.
The aim of this investigation is the evaluation, (further) development and comparison of non-invasive techniques for the evaluation of patients suffering mild cognitive impairment, in particular, the Mantis Photonics hyperspectral camera with classification machine learning model in combination with the CoGNIT test of Dr Behrens (Blekinge Tekniska Högskola). These techniques will be compared to the result of cerebrospinal fluid analysis (CSF), the reference biological diagnostic technique for Alzheimer's disease.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Subjects | Experimental | On all subjects included in the study (see inclusion / exclusion criteria and informed consent) both procedures will be performed. The result of these procedures (retinal scan, result from cognitive test and blood sample) will be used to build diagnostic classification models. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| non-invasive hyperspectral retinoscopy | Procedure | The Principal Investigator or a trained medical nurse (under the supervision of the principal investigator) will take an image of the retina of the patient with the Mantis Photonics hyperspectral retinoscopy camera. |
| Measure | Description | Time Frame |
|---|---|---|
| Accuracy (Statistical metric) retinal image classification model | Performance metric of the retinal image classification model: model accuracy [percent] | within 2 months after last patient procedure |
| Area under the Curve (statistical metrics) retinal image classification model | Performance metric of the retinal image classification model: Area under the Curve (AuC) [0 < AuC < 1] | within 2 months after last patient procedure |
| Sensitivity (Statistical metric) retinal image classification model | Performance metrics of the retinal image classification model: Sensitivity [percent] | within 2 months after last patient procedure |
| CoGNIT test diagnostic accuracy | Accuracy [percent] of diagnosis based on the CoGNIT test data | within 2 months after last patient procedure |
| Measure | Description | Time Frame |
|---|---|---|
| Accuracy: Metrics combination model | A combination model of both non-invasive techniques will be evaluated based on the same metrics as the single-technique model (see primary objectives) and evaluated based on the comparison of said metrics: accuracy [percent] for the optimal choice of threshold. | within 3 months after last patient procedure |
| Measure | Description | Time Frame |
|---|---|---|
| Adverse effect | Measurement: Percentage [percent] of patients who report adverse effects such as transient 'imprint' of the flash or other adverse effects. | Immediately after the retinoscopy procedure |
| Serious adverse effect |
Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Anders Behrens, MD, PhD | Contact | +460702034496 | anders.behrens@regionblekinge.se | |
| Jan Alexander, Master | Contact | 0478779156 | jan.alexander@mantis-photonics.com |
| Name | Affiliation | Role |
|---|---|---|
| Anders Behrens, MD, PhD | Blekinge Tekniska Högskola | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Blekinge Tekniska Högskola | Karlskrona | Blekine Län | 37141 | Sweden |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 35275064 | Background | Behrens A, Berglund JS, Anderberg P. CoGNIT Automated Tablet Computer Cognitive Testing in Patients With Mild Cognitive Impairment: Feasibility Study. JMIR Form Res. 2022 Mar 11;6(3):e23589. doi: 10.2196/23589. | |
| 25279138 | Background | Behrens A, Eklund A, Elgh E, Smith C, Williams MA, Malm J. A computerized neuropsychological test battery designed for idiopathic normal pressure hydrocephalus. Fluids Barriers CNS. 2014 Sep 25;11:22. doi: 10.1186/2045-8118-11-22. eCollection 2014. |
| Label | URL |
|---|---|
| World Alzheimer Report 2022 - Alzheimer's disease international | View source |
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No Individual Participant Data (IPD) sharing to third parties. Data of individual participants will be used for this study only.
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The diagnosis of Amyloidosis (biomarker of Alzheimer's disease) is made based on the normal patient care consisting of the neurologist assessment and the Cerebro-Spinal Fluid analysis.
This diagnosis is used as golden standard for the model based on retinal images and cognitive test results.
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| blood sample | Procedure | The Principle Investigator or a trained medical nurse (under the supervision of the Principal Investigator) will draw a small blood sample according to the standard medical procedures for drawing blood samples. |
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| Test of cognitive ability on tablet computer with CoGNIT software | Diagnostic Test | The Principle Investigator or a trained medical nurse (under the supervision of the Principal Investigator) will give the patient to perform the digital cognitive test on a commercial tablet computer. The Principal Investigator or the medical nurse will be available for the patient to ask questions while the test is ongoing. |
|
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| Area Under the Curve: Metrics combination model | A combination model of both non-invasive techniques will be evaluated based on the same metrics as the single-technique model (see primary objectives) and evaluated based on the comparison of said metrics: Area Under the Curve [0](streamdown:incomplete-link) | within 3 months after last patient procedure |
| Sensitivity: Metrics combination model | A combination model of both non-invasive techniques will be evaluated based on the same metrics as the single-technique model (see primary objectives) and evaluated based on the comparison of said metrics: sensitivity [percent] for the optimal choice of threshold. | within 3 months after last patient procedure |
| Non invasive test variability compared to reference | The variability [relative and normalized: percent] between the first and the second hyperspectral retinoscopy result will be compared to the variability between the blood analysis at the first and the second appointment [relative and normalized: percent]. The blood test variability will be used as a reference in this study. | within 3 months after last patient procedure |
Occurence of serious adverse effects due to the procedure.
Any patient who suffers serious harm due to the procedure is a study outcome and a study endpoint.
| Immediately after the retinoscopy procedure |
| Blekinge Hospital | Karlskrona | Blekinge County | 37141 | Sweden |
|
| 30738407 | Background | Behrens A, Elgh E, Leijon G, Kristensen B, Eklund A, Malm J. The Computerized General Neuropsychological INPH Test revealed improvement in idiopathic normal pressure hydrocephalus after shunt surgery. J Neurosurg. 2019 Feb 8;132(3):733-740. doi: 10.3171/2018.10.JNS18701. Print 2020 Mar 1. |
| 31843944 | Background | Budelier MM, Bateman RJ. Biomarkers of Alzheimer Disease. J Appl Lab Med. 2020 Jan 1;5(1):194-208. doi: 10.1373/jalm.2019.030080. |
| 31530809 | Background | Hadoux X, Hui F, Lim JKH, Masters CL, Pebay A, Chevalier S, Ha J, Loi S, Fowler CJ, Rowe C, Villemagne VL, Taylor EN, Fluke C, Soucy JP, Lesage F, Sylvestre JP, Rosa-Neto P, Mathotaarachchi S, Gauthier S, Nasreddine ZS, Arbour JD, Rheaume MA, Beaulieu S, Dirani M, Nguyen CTO, Bui BV, Williamson R, Crowston JG, van Wijngaarden P. Non-invasive in vivo hyperspectral imaging of the retina for potential biomarker use in Alzheimer's disease. Nat Commun. 2019 Sep 17;10(1):4227. doi: 10.1038/s41467-019-12242-1. |
| 31920420 | Background | Rasmussen J, Langerman H. Alzheimer's Disease - Why We Need Early Diagnosis. Degener Neurol Neuromuscul Dis. 2019 Dec 24;9:123-130. doi: 10.2147/DNND.S228939. eCollection 2019. |
| 34838239 | Background | Teunissen CE, Verberk IMW, Thijssen EH, Vermunt L, Hansson O, Zetterberg H, van der Flier WM, Mielke MM, Del Campo M. Blood-based biomarkers for Alzheimer's disease: towards clinical implementation. Lancet Neurol. 2022 Jan;21(1):66-77. doi: 10.1016/S1474-4422(21)00361-6. Epub 2021 Nov 24. |
| 41153055 | Derived | Dallora AL, Alexander J, Palesetti PP, Guenot D, Selvander M, Berglund JS, Behrens A. Hyperspectral retinal imaging to detect Alzheimer's disease in a memory clinic setting. Alzheimers Res Ther. 2025 Oct 28;17(1):232. doi: 10.1186/s13195-025-01887-4. |
| ID | Term |
|---|---|
| D000544 | Alzheimer Disease |
| D060825 | Cognitive Dysfunction |
| ID | Term |
|---|---|
| D003704 | Dementia |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
| D024801 | Tauopathies |
| D019636 | Neurodegenerative Diseases |
| D019965 | Neurocognitive Disorders |
| D001523 | Mental Disorders |
| D003072 | Cognition Disorders |
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| ID | Term |
|---|---|
| D001800 | Blood Specimen Collection |
| ID | Term |
|---|---|
| D013048 | Specimen Handling |
| D019411 | Clinical Laboratory Techniques |
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
| D011677 | Punctures |
| D013514 | Surgical Procedures, Operative |
| D008919 | Investigative Techniques |
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