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Record W2055069465 · doi:10.2967/jnumed.107.048330

Design and Implementation of an Automated Partial Volume Correction in PET: Application to Dopamine Receptor Quantification in the Normal Human Striatum

2008· article· en· W2055069465 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Nuclear Medicine · 2008
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute on Drug AbuseNational Institutes of HealthNational Institute of Neurological Disorders and StrokeNational Institute of Mental HealthNational Institute on Alcohol Abuse and AlcoholismJohns Hopkins University
KeywordsRaclopridePutamenNuclear medicineStriatumReproducibilityCaudate nucleusHuman brainChemistryNuclear magnetic resonancePartial volumeDopamineBiomedical engineeringMathematicsMedicinePhysicsNeuroscienceChromatographyPsychologyInternal medicine

Abstract

fetched live from OpenAlex

UNLABELLED: The considerable effort and potential lack of reproducibility of human-driven PET quantification and partial volume correction (PVC) can be alleviated by use of atlas-based automatic analysis. The present study examined the application of a new algorithm designed to automatically define 3-dimensional regions of interest (ROIs) and their effect on dopamine receptor quantification in the normal human brain striatum, both without and with PVC. METHODS: A total of 90 healthy volunteers (age range, 18-46 y) received a single injection of (11)C-raclopride, and automatic segmentation of concomitant structural MR images was performed using a maximum-probability atlas in combination with a trained neural network. For each identified tissue segment considered homogeneous for the tracer (or volumes of interest [VOIs]), an a priori criterion based on minimum axial recovery coefficient (RC(zmin) = 50%, 75%, and 90%) was used to constrain the extent of each ROI. RESULTS: With ROIs essentially overlapping the entire VOI volume (obtained with RC(zmin) = 50%), the binding potential (BP(ND)) of (11)C-raclopride was found to be around 2.2 for caudate and 2.9 for putamen, an underestimation by 35% and 28%, respectively, according to PVC values. At increased RC(zmin), BP(ND) estimates of (11)C-raclopride were increased by 12% and 21% for caudate and 8% and 15% for putamen when the associated ROIs decreased to around 65% and 43% of total tissue volume (VOI) for caudate and 67% and 31% for putamen. After PVC, we observed relative increases in BP(ND) variance of 12% for caudate and 20% for putamen, whereas estimated BP(ND) values all increased to 3.4 for caudate and 4.0 for putamen, regardless of ROI size. Dopamine receptor concentrations appeared less heterogeneous in the normal human striatum after PVC than they did without PVC: the 25%-30% difference in BP(ND) estimates observed between caudate and putamen remained significant after PVC but was reduced to slightly less than 20%. Furthermore, the results were comparable with those obtained with a manual method currently in use in our laboratory. CONCLUSION: The new algorithm allows for traditional PET data extraction and PVC in an entirely automatic fashion, thus avoiding labor-intensive analyses and potential intra- or interobserver variability. This study also offers the first, to our knowledge, large-scale application of PVC to dopamine D(2)/D(3) receptor imaging with (11)C-raclopride in humans.

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.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score0.215

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.037
GPT teacher head0.370
Teacher spread0.333 · 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