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Record W2159161559 · doi:10.1186/alzrt200

Role of emerging neuroimaging modalities in patients with cognitive impairment: a review from the Canadian Consensus Conference on the Diagnosis and Treatment of Dementia 2012

2013· review· en· W2159161559 on OpenAlexafffundabout
Amer M. Burhan, Robert Bartha, Christian Bocti, Michael Borrie, Robert Laforce, Pedro Rosa‐Neto, Jean‐Paul Soucy

Bibliographic record

VenueAlzheimer s Research & Therapy · 2013
Typereview
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsDouglas CollegeParkwood InstituteUniversité de SherbrookeUniversité LavalMontreal Neurological Institute and HospitalSt Joseph's Health CareWestern University
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchAlzheimer's Association
KeywordsNeuroimagingDementiaPositron emission tomographyModalitiesMagnetic resonance imagingCognitionMedicinePsychologyMedical physicsDiseasePsychiatryRadiologyPathology

Abstract

fetched live from OpenAlex

The Fourth Canadian Consensus Conference on the Diagnosis and Treatment of Dementia (CCCDTD4) was held 3 to 4 May 2012 in Montreal, Quebec, Canada. A group of neuroimaging experts were assigned the task of reviewing and summarizing the literature on clinical and research applications of different neuroimaging modalities in cognitive disorders. This paper summarizes the literature and recommendations made to the conference regarding the role of several emerging neuroimaging modalities in cognitive disorders. Functional magnetic resonance imaging (MRI), magnetic resonance spectroscopy, and diffusion tensor imaging are discussed in detail within this paper. Other emergent neuroimaging modalities such as positron emission tomography with novel ligands, high-field MRI, arterial spin labeling MRI and noncerebral blood flow single-photon emission computerized tomography are only discussed briefly. Neuroimaging modalities that were recommended at the CCCDTD4 for both clinical and research applications such as amyloid and flurodeoxyglucose positron emission tomography, computerized tomography and structural MRI are discussed in a separate paper by the same authors. A literature search was conducted using the PubMed database including articles in English that involved human subjects and covered the period from the last CCCDTD publication (CCCDTD3; January 2006) until April 2012. Search terms included the name of the specific modality, dementia, Alzheimer's disease, and mild cognitive impairment. A separate search used the same parameters but was restricted to review articles to identify recent evidence-based reviews. Case studies and small case series were not included. Papers representing current evidence were selected, reviewed, and summarized, and the results were presented at the CCCDTD4 meeting with recommendations regarding the utility of various neuroimaging modalities in cognitive disorders. The evidence was graded according to the Oxford Centre for Evidence Based Medicine guidelines. Due to the limitations of current evidence, the neuroimaging modalities discussed in this paper were not recommended for clinical investigation of patients presenting with cognitive impairment. However, in the research setting, each modality provides a unique contribution to the understanding of basic mechanisms and neuropathological markers of cognitive disorders, to the identification of markers for early detection and for the risk of conversion to dementia in the at-risk populations, to the differentiation between different types of cognitive disorders, and to the identification of treatment targets and indicators of treatment response. In conclusion, for all of the neuroimaging modalities discussed in this paper, further studies are needed to establish diagnostic utility such as validity, reliability, and predictive and prognostic value. More multicenter studies are therefore needed with standardized image acquisition, experimental protocols, definition of the clinical population studied, larger numbers of participants, and longer duration of follow-up to allow generalizability of the results to the individual patient.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.333
GPT teacher head0.452
Teacher spread0.119 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations24
Published2013
Admission routes3
Has abstractyes

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