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Record W2739723571 · doi:10.1158/1538-7445.am2017-3860

Abstract 3860: Magnetization transfer and T2-weighted MRI studies are useful for visualizing phenotypic presentations of orthotopic, patient-derived xenograft mouse models of glioblastoma

2017· article· en· W2739723571 on OpenAlexaff
Tavarekere N. Nagaraja, Rasha Elmghirbi, Susan M. Irtenkauf, Laura Hasselbach, Baruch Tawil, Stephen L. Brown, Swayamprava Panda, Glauber Cabral, Tom Mikkelsen, James R. Ewing, Ana C. deCarvalho

Bibliographic record

VenueCancer Research · 2017
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsOntario Brain Institute
Fundersnot available
KeywordsMagnetic resonance imagingMagnetization transferPathologyHistologyImmunohistochemistryHistopathologyGlioblastomaH&E stainMedicineNuclear medicineCancer researchRadiology

Abstract

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Abstract Introduction: Patient-derived xenograft (PDX) models for glioblastoma (GBM) from resected tumor tissues replicate several features of the original tumor. They are considered to be representative models to study tumor progression, and to test responses to putative therapies. Longitudinal noninvasive imaging can be useful in such investigations. To that end, we employed magnetic resonance imaging (MRI) to visualize and measure tumor burden in four different PDX models of GBM. Experimental procedures: Four orthotopic mouse PDX models, HF2587, HF2927, HF3077 and HF3253, developed from neurosphere cultures of four different human glioblastoma samples were used in the study. The neurosphere cells were implanted into the right striatum in immunocompromised nude mice (n=5-8 per model) and allowed to grow for 2-8 weeks, depending on their known growth rates from previous studies. They were imaged in a Varian 7T MRI system with the following weightings: T2, T1, magnetization transfer (MT), and contrast enhanced MRI (CE-MRI) with Magnevist as the contrast agent (CA). Following imaging, all the mice were sacrificed and their brains processed for hematoxylin and eosin (H&E) histology and human major histocompatibility complex (MHC) immunohistochemistry. Results: Tumor masses were visible as hyperintense regions on MT and T2-weighted images. The extent of such masses matched the H&E and MHC staining patterns. Ventricle enlargements seen on MRI in several mice were also confirmed by histology. Necrotic cores, when present, were observed on both imaging and on histopathology with good spatial correlations. Surprisingly, post-contrast T1 imaging did not enhance in the tumor mass or peritumorally, except in one mouse in which some intra-tumoral enhancement was observed. In all other instances from the four PDX models tested, enhancement was observed only when the tumor tissue or parts of it were contiguous with pial or dural vasculature. Conclusions: At 7 Tesla, MT-MRI and T2-weighted imaging, rather than CE-MRI, appear to be of better utility in visualizing these PDX models of GBM if MRI is chosen as the imaging modality. Since the parent tumors imaged at lower field strengths showed contrast enhancement, absence of a similar feature in these models needs additional studies to understand their vascular characteristics. Such properties may include low level of vascularization and/or relatively less leaky tumor vasculature. Another possible reason may be that the models tested represent the invasive features of GBM better than the vascular features, e.g. peritumoral ring enhancement, of larger clinical tumors with increased exposure to hypoxia. Citation Format: Tavarekere N. Nagaraja, Rasha Elmghirbi, Susan Irtenkauf, Laura Hasselbach, Baruch Tawil, Stephen L. Brown, Swayamprava Panda, Glauber Cabral, Tom Mikkelsen, James R. Ewing, Ana deCarvalho. Magnetization transfer and T2-weighted MRI studies are useful for visualizing phenotypic presentations of orthotopic, patient-derived xenograft mouse models of glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3860. doi:10.1158/1538-7445.AM2017-3860

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.003

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 head0.149
GPT teacher head0.437
Teacher spread0.289 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2017
Admission routes1
Has abstractyes

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