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Record W4289878828 · doi:10.1093/noajnl/vdac078.058

LOCL-16 IMPACT OF MGMT PROMOTER METHYLATION STATUS ON TUMOR DYNAMICS DURING WEEKLY ADAPTIVE RADIOTHERAPY FOR GLIOBLASTOMA

2022· article· en· W4289878828 on OpenAlexaff
John M. Hudson, James Stewart, Kang Zeng, Hanbo Chen, Mark Ruschin, Hany Soliman, Chia‐Lin Tseng, Sten Myrehaug, Zain Husain, Arjun Sahgal, Jay Detsky

Bibliographic record

VenueNeuro-Oncology Advances · 2022
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsTemozolomideNuclear medicineFluid-attenuated inversion recoveryGlioblastomaMedicineRadiation therapyMethylationChemoradiotherapyO-6-methylguanine-DNA methyltransferaseMethyltransferaseMagnetic resonance imagingInternal medicineCancer researchRadiologyBiology

Abstract

fetched live from OpenAlex

Abstract PURPOSE Adaptive MRI-guided radiotherapy (RT) on a 1.5T-MR-Linac using reduced clinical target volumes (CTV) of 5mm instead of the 15mm standard for glioblastoma (GBM) is currently being evaluated on the UNITED clinical trial (NCT04726397). We explored the morphological changes that occur during adaptive RT with concurrent temozolomide between tumors with MGMT promotor methylation (MGMT-m) vs. unmethylation (MGMT-um). METHODS Thirty patients with IDH-wildtype GBMs were treated with 60Gy in 30 (n=12) or 40Gy in 15 fractions (n=18) (Fx). The CTV included a 5mm expansion on the gross tumor volume (GTV) +/- FLAIR hyperintense areas-at-risk and a 3mm planning target volume. Planning was performed on a pre-treatment reference MRI (FxRef) followed by weekly on-line adaptive re-planning at Fx1, Fx6, etc. acquired on the MR-Linac. Interim fractions were image-guided by pre-beam-on onboard MRI. The GTV/CTVs were quantified by their absolute volumes, volumes relative to the FxRef and the maximum linear distance from the edges of the reference contour to the weekly adapted contours (migration distance, dmig). MGMT promoter methylation status was explored as a fixed effect in a linear mixed statistical model. RESULTS Weekly median changes in GTV relative to FxRef in MGMT-um tumors (n=12) were 10.3%, 9.2%, 10.6%, 14.5%, 18.0% and 17.3%, respectively, while for MGMT-m (n=18) were 3.4%, 0.0%, -8.6%, -11.3%, -11.3% and -5.6% (p=0.021). Between FxRef and Fx1, the GTV increased by over 10% in 58% of MGMT-um tumors vs. 33% of MGMT-m tumors. Similar significant trends were observed with the CTVs. MGMT-um tumors had significantly larger dmig compared to tumors with MGMT-m (median 9.6mm vs. 5.8mm, respectively (p=0.018)). CONCLUSIONS MGMT-um GBM exhibited significant changes in morphology and migration distance between the time of treatment planning to the first treatment fraction, as well as throughout a course of RT. In this population, our results support a greater frequency of imaging and plan adaptation when applying personalized reduced CTV margins.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.266
Threshold uncertainty score0.704

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 head0.013
GPT teacher head0.319
Teacher spread0.306 · 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 designBench or experimental
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

Citations3
Published2022
Admission routes1
Has abstractyes

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