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Record W2045205384 · doi:10.2967/jnumed.112.115782

Exploratory Evaluation of MR Permeability with <sup>18</sup>F-FDG PET Mapping in Pediatric Brain Tumors: A Report from the Pediatric Brain Tumor Consortium

2013· article· en· W2045205384 on OpenAlexaff
Katherine Zukotynski, Frederic H. Fahey, Sridhar Vajapeyam, Sarah S. Ng, Mehmet Koçak, Sridharan Gururangan, Larry E. Kun, Tina Young Poussaint

Bibliographic record

VenueJournal of Nuclear Medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
FundersNational Cancer Institute
KeywordsNuclear medicineMedicineGliomaWhite matterBrain tumorMedulloblastomaMagnetic resonance imagingPathologyRadiology

Abstract

fetched live from OpenAlex

UNLABELLED: The purpose of this study was to develop a method of registering (18)F-FDG PET with MR permeability images for investigating the correlation of (18)F-FDG uptake, permeability, and cerebral blood volume (CBV) in children with pediatric brain tumors and their relationship with outcome. METHODS: Twenty-four children with brain tumors in a phase II study of bevacizumab and irinotecan underwent brain MR and (18)F-FDG PET within 2 wk. Tumor types included supratentorial high-grade astrocytoma (n = 7), low-grade glioma (n = 9), brain stem glioma (n = 4), medulloblastoma (n = 2), and ependymoma (n = 2). There were 33 cases (pretreatment only [n = 12], posttreatment only [n = 3], and both pretreatment [n = 9] and posttreatment [n = 9]). (18)F-FDG PET images were registered to MR images from the last time point of the T1 perfusion time series using mutual information. Three-dimensional regions of interest (ROIs) drawn on permeability images were automatically transferred to registered PET images. The quality of ROI registration was graded (1, excellent; 2, very good; 3, good; 4, fair; and 5, poor) by 3 independent experts. Spearman rank correlations were used to assess correlation of maximum tumor permeability (Kps(max)), maximum CBV (CBV(max)), and maximum (18)F-FDG uptake normalized to white matter (T/W(max)). Cox proportional hazards models were used to investigate associations of these parameters with progression-free survival (PFS). RESULTS: The quality of ROI registration between PET and MR was good to excellent in 31 of 33 cases. There was no correlation of baseline Kps(max) with CBV(max) (Spearman rank correlation = 0.018 [P = 0.94]) or T/W(max) (Spearman rank correlation = 0.07 [P = 0.76]). Baseline CBV(max) was correlated with T/W(max) (Spearman rank correlation = 0.47 [P = 0.036]). Baseline Kps(max), CBV(max), and T/W(max) were not significantly associated with PFS (P = 0.42, hazard ratio [HR] = 0.97, 95% confidence interval [CI] = 0.90-1.045, and number of events [n(events)] = 15 for Kps(max); P = 0.41, HR = 0.989, 95% CI = 0.963-1.015, and n(events) = 14 for CBV(max); and P = 0.17, HR = 1.49, 95% CI = 0.856-2.378, and n(events) = 15 for T/W(max)). CONCLUSION: (18)F-FDG PET and MR permeability images were successfully registered and compared across a spectrum of pediatric brain tumors. The lack of correlation between metabolism and permeability may be expected because these parameters characterize different molecular processes. The correlation of CBV and tumor metabolism may be related to an association with tumor grade. More patients are needed for a covariate analysis of these parameters and PFS by tumor histology.

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)0.004
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.039
GPT teacher head0.286
Teacher spread0.247 · 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.

Study designObservational
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

Citations22
Published2013
Admission routes1
Has abstractyes

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