Perfusion Magnetic Resonance Imaging in Psychiatry
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Bibliographic record
Abstract
INTRODUCTION: Cerebral perfusion imaging using magnetic resonance imaging (MRI) is widely used in the research and clinical fields to assess the profound changes in blood flow related to ischemic events such as acute stroke, chronic steno-occlusive disease, vasospasm, and abnormal vessel formations from congenital conditions or tumoral neovascularity. With continuing improvements in the precision of MRI-based perfusion techniques, it is increasingly feasible to use this tool in the study of the subtle brain perfusion changes occurring in psychiatric illnesses. This article aims to review the existing literature on applications of perfusion MRI in psychiatric disorder and substance abuse research. The article also provides a brief introductory overview of dynamic susceptibility contrast MRI and arterial spin labeling techniques. An outlook of necessary steps to bring perfusion MRI into the realm of clinical psychiatry as a diagnostic tool is brought forth. Opportunities for research in unexplored disorders and with higher field strengths are briefly examined. METHODS: PubMed, ISI Web of Knowledge & Scopus were used to search the literature and cross reference several neuropsychiatric disorders with a search term construct, including "magnetic resonance imaging," "dynamic susceptibility contrast," "arterial spin labeling," perfusion or "cerebral blood flow" or "cerebral blood volume" or "mean transit time." The list of disorders used in the search included schizophrenia, depression and bipolar disorder, dementia and Alzheimer's disease, Parkinson's disease, posttraumatic stress disorder, autism, Asperger disease, attention deficit, Tourette syndrome, obsessive-compulsive disorder, Huntington's disease, bulimia nervosa, anorexia nervosa, and substance abuse. For each disorder for which perfusion MRI studies were found, a brief overview of the disorder symptoms, treatment, prevalence, and existing models is provided, and previous findings from nuclear medicine-based perfusion imaging are overviewed. Findings of perfusion MRI studies are then summarized, and overlap of findings are discussed. Overarching conclusions are made, or an outlook for future work in the area is offered, where appropriate. RESULTS: Despite the now fairly broad availability of perfusion MRI, only a limited number of studies were found using this technology. The search produced 13 studies of schizophrenia, 7 studies in major depression, 12 studies in Alzheimer's disease, and 2 studies in Parkinson's disease. Drug abuse and other disorders have mainly been studied with nuclear medicine-based perfusion imaging. The literature concerning the use of perfusion imaging in psychiatry has not been reviewed in the last 5 years or more. The use of MRI for perfusion measurements in psychiatry has not been reviewed in 10 years. CONCLUSIONS: Although MRI-based perfusion imaging in psychiatry has mainly been used as a research tool, a path is progressively being cleared for its application in clinical diagnostic and treatment monitoring. The precision of perfusion MRI methods now rivals that of nuclear medicine-based perfusion imaging techniques. Because of their noninvasive nature, arterial spin labeling methods have gained popularity in studies of neuropsychiatric disorders such as schizophrenia, depression, Alzheimer's, and Parkinson's diseases. Perfusion imaging measurements have yet to be included within the diagnostic criteria of neuropsychiatric disorders despite having shown to have great discriminant power in specific disorders. As this young methodology continues to improve and research studies demonstrate the correlation of measured perfusion abnormalities to microcirculatory abnormalities and neuropsychiatric symptomatology, the idea of including such a test within diagnostic criteria for certain mental illnesses becomes increasingly plausible.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it