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Record W2887649851 · doi:10.1158/1538-7445.am2018-3199

Abstract 3199: Computational studies show that Tumor Treating Fields can be delivered to the infratentorial brain at therapeutic levels

2018· article· en· W2887649851 on OpenAlexaboutno aff
Shay Levy, Ariel Naveh, Zéev Bomzon, Eilon D. Kirson, Uri Weinberg

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldEngineering
TopicMolecular Communication and Nanonetworks
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBrain tumorGlioblastomaHuman headHuman brainPathologyCancer researchPhysicsAcoustics

Abstract

fetched live from OpenAlex

Abstract TTFields is an antimitotic cancer treatment that utilizes low intensity (1-3 V/cm) alternating electric fields in the intermediate frequency (100-300 kHz), approved by the Food and Drug Administration (FDA) for the treatment of Glioblastoma Multiforme (GBM) located in the supratentorial regions of the brain. A clinical trial testing the efficacy of TTFields for treating brain metastases is currently underway (METIS, NCT02831959). TTFields are delivered using two pairs of transducer arrays placed on the patient's skin in the proximity of the tumor. The electric field generated by the arrays is localized to a region located roughly between the arrays. The standard array layouts used to deliver TTFields involve placement of the arrays on the supratentorial regions of the head. With these array layouts,therapeutic field intensities above 1 V/cm are only achieved within the supratentorial brain. Therefore, treatment with TTFields has been limited to tumors located in the supratentorium. Although Tumors located in the infratentorial brain are rare in adult patients, they are common in the pediatric population. In addition, brain metastases commonly occur in the infratentorium. Hence, there is a need to identify array layouts that can effectively deliver TTFields to the infratentorial brain. Here we present computer simulations designed to identify new array layouts that deliver high field intensities to the infratentorial brain. To simulate delivery of TTFields to the brain, we used realistic computerized head models of an adult human female and an adult human male. Virtual transducer arrays were placed on the models, and boundary conditions were set to simulate delivery of TTFields at 200 kHz. Various array layouts were tested, and field distributions resulting from the layouts were evaluated. In both head models, the highest field intensities were delivered to the infratentorial brain by a layout, in which each array of one pair was laterally placed superficially to the lower region of the occipital lobe, and the two arrays of the second pair were placed on the calvarium and the superior aspect of the neck. In both models, the pair of arrays in which one array was placed on the calvarium and one array on the superior aspect of the neck delivered field intensities above 1.1 V/cm to over 95% of the volume of the infratentorial brain, and the pair of arrays placed on the lateral aspects of the occipital lobe delivered field intensities above 1 V/cm to over 95% of the infratentorial brain. Both pairs of arrays delivered field intensities above 1 V/cm to significant portions of the supratentorial brain. This work shows that TTFields at therapeutic intensities can be delivered to the cerebellum, stem and surrounding regions which are located inferior to the tentorium, suggesting that treatment of tumors within these with TTFields is feasible. Citation Format: Shay Levy, Ariel Naveh, Ze'ev Bomzon, Eilon Kirson, Uri Weinberg. Computational studies show that Tumor Treating Fields can be delivered to the infratentorial brain at therapeutic levels [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3199.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score0.380

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 head0.209
GPT teacher head0.418
Teacher spread0.208 · 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 designNot applicable
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
Published2018
Admission routes1
Has abstractyes

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