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Record W4385964276 · doi:10.1093/noajnl/vdad070.049

LMAP-18 ADAPTING LASER INTERSTITIAL THERMAL THERAPY (LITT) FOR TREATMENT OF INTRACRANIAL LESIONS IN CANINES

2023· article· en· W4385964276 on OpenAlexaff
Christopher L. Mariani, Lucas P. Wachsmuth, Laura K. Ruterbories, Vadim Tsvankin, Alexa N. Bramall, Richard Tyc, Peter E. Fecci

Bibliographic record

VenueNeuro-Oncology Advances · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Research and Treatments
Canadian institutionsResearch Manitoba
Fundersnot available
KeywordsMedicineIntracranial pressureAblationStereotaxyRadiologyRadiation therapySkullLesionCatheterSurgeryHaptic technologyComputer science

Abstract

fetched live from OpenAlex

Abstract Malignant gliomas are devastating intracranial tumors with dismal prognoses that impose unique therapeutic challenges. Treatment options include surgical resection, radiation, and chemotherapy, but efficacy is limited and carries associated morbidity. Promise persists for newer modalities, such as immune-based platforms, but the blood-brain barrier (BBB) restricts intracranial therapeutic access, limiting success. Laser interstitial thermal therapy (LITT) is a minimally invasive surgical intervention permitting thermal ablation of brain tumors and other intracranial lesions. During LITT, a laser probe is stereotactically introduced through a small skull burr hole into the lesion. Continuous MRI is used to conduct real-time temperature monitoring via software-based calculation of cumulative thermal dosage zones. LITT is not only capable of ablating neoplastic tissue, but can also open the BBB in peritumoral regions, and thus may synergize with other emerging therapies. We adapted a commercially available LITT system (Monteris Medical) for use in dogs with intracranial lesions. Canine cadavers were used to optimize LITT procedures before employing this platform in live dogs. Our approach consists of 1. obtaining volumetric, T1-weighted, MRI studies to plan trajectories to intracranial targets, 2. fixing canine patients to a surgical bed and registering them for surface matching to a volume rendered image, 3. using an integrated instrument holder (Varioguide, Brainlab) to guide drilling of 4.5 mm skull burr holes for placement of self-tapping titanium “mini-bolts” (Monteris Medical), and 4. introducing the laser catheter probe through the mini-bolts for lesion ablation in the MRI suite. This method allows for rigid stereotaxy, successful neuronavigation, and a minimally invasive approach. We have successfully performed LITT on four canine patients with spontaneously occurring intracranial gliomas and plan to treat additional canine patients with intracranial lesions. Future studies will explore combination therapeutic platforms, including immunotherapy and gold nanoparticles to improve the efficiency and specificity of tumor ablation.

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 score0.314
Threshold uncertainty score0.451

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 head0.045
GPT teacher head0.372
Teacher spread0.327 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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