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Record W2416237333

Scatter and attenuation correction for brain SPECT using attenuation distributions inferred from a head atlas.

2000· article· en· W2416237333 on OpenAlexaff
Robert Z. Stodilka, Brad Kemp, Frank S. Prato, Andrew Kertesz, Don Kuhl, R.L. Nicholson

Bibliographic record

VenuePubMed · 2000
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsDefence Research and Development CanadaSt Joseph's Health CareSt Joseph's Health Centre
Fundersnot available
KeywordsCorrection for attenuationNuclear medicineCerebral blood flowAtlas (anatomy)CollimatorAttenuationVoxelMedicinePhysicsPositron emission tomographyOpticsRadiologyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

UNLABELLED: Sequential transmission scanning (TS)/SPECT is impractical for neurologically impaired patients who are unable to keep their heads motionless for the extended duration of the combined scans. To provide an alternative to TS, we have developed a method of inferring-attenuation distributions (IADs), from SPECT data, using a head atlas and a registration program. The validity of replacing TS with IAD was tested in 10 patients with mild dementia. METHODS: TS was conducted with each patient using a collimated 99mTc line source and fanbeam collimator; this was followed by hexamethyl propyleneamine oxime-SPECT. IAD was derived by deformably registering the brain component of a digital head atlas to a preliminary SPECT reconstruction and then applying the resulting spatial transformation to the full head atlas. SPECT data were reconstructed with scatter and attenuation correction. Relative regional cerebral blood flow was quantified in 12 threshold-guided anatomic regions of interest, with cerebellar normalization. SPECT reconstructions using IAD were compared with those using TS (which is the "gold standard") in terms of these regions of interest. RESULTS: When we compared all regions of interest across the population, the correlation between IAD-guided and TS-guided SPECT scans was 0.92 (P < 0.0001), whereas the mean absolute difference between the scans was 7.5%. On average, IAD resulted in slight underestimation of relative regional cerebral blood flow; however, this underestimation was statistically significant for only the left frontal and left central sulcus regions (P = 0.001 and 0.002, respectively). Error analysis indicated that approximately 10.0% of the total error was caused by IAD scatter correction, 36.6% was caused by IAD attenuation correction, 27.0% was caused by discrepancies in region-of-interest demarcation from quantitative errors in IAD-guided reconstructions, and 26.5% was caused by patient motion throughout the imaging procedure. CONCLUSION: SPECT reconstructions guided by IAD are sufficiently accurate to identify regional cerebral blood flow deficits of 10%, which are typical in moderate and advanced dementia.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.884
Threshold uncertainty score0.381

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.050
GPT teacher head0.317
Teacher spread0.267 · 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
GenreEmpirical

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

Citations29
Published2000
Admission routes1
Has abstractyes

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