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A multicenter, pivotal trial of microbubble-enhanced transcranial focused ultrasound (MB-FUS) for plasma-based liquid biopsy in patients with glioblastoma (LIBERATE).

2025· article· en· W4410820588 on OpenAlexaffabout
Manmeet S. Ahluwalia, Ahmad Ozair, Terence Burns, Michael McDermott, Alon Y. Mogilner, Bhavya Shah, Toral Patel, Jordina Rincón-Torroella, Mark V. Mishra, Richard G. Everson, Justin Hilliard, Yarema Bezchlibnyk, Matthew Hibert, Jeffrey S. Weinberg, Christopher P. Cifarelli, Ali R. Rezai, Vibhor Krishna, Nir Lipsman, Graeme F. Woodworth

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineGlioblastomaLiquid biopsyFocused ultrasoundUltrasoundTranscranial DopplerBiopsyGliomaMulticenter trialOncologyRadiologyMulticenter studyPathologyInternal medicineCancer researchRandomized controlled trialCancer

Abstract

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TPS2094 Background: Liquid biopsy in glioblastoma (GBM) is hindered by a lack of requisite circulating tumor (ct) and cell-free (cf) DNA levels in blood due to the blood-brain barrier (BBB). This limits the identification of blood-based tumor biomarkers along with the development and use of biomarker-driven systemic therapies. Low intensity focused ultrasound combined with intravenously administered microbubble oscillators (MB-FUS), leads to non-invasive BBB opening. This trial aims to evaluate the utility of LIFU for bolstering blood ctDNA and cfDNA for enhance liquid biopsy in patients with GBM. Methods: LIBERATE is an ongoing, prospective, multi-center, self-controlled, pivotal trial evaluating safety and technical efficacy of transcranial MR-guided MB-FUS for increasing blood ctDNA and cfDNA levels in adults, aged 18-80 years with GBM. Patients with suspected GBM planned for tumor biopsy or resection at 17 centers in US and Canada are being enrolled. Patients with multifocal tumors or tumors arising from deep midline, thalamus, cerebellum, or brainstem are excluded. Patients are administered IV microbubbles for enhanced sonication, after which MR-guided BBB opening using a 220 kHz device, with 1024-element phased array transducer, is performed with real-time acoustic feedback control for effective cavitation. Pre- and post-procedure, phlebotomy and MRI brain are done. Patients are offered optional 2 nd procedure during adjuvant chemotherapy phase if willing. Primary efficacy endpoint is correlation between biomarker patterns in tumor tissue collected during surgery/biopsy and blood collected following MB-FUS procedure. Confirmatory secondary efficacy endpoint is ratio between greatest yield of cfDNA in blood post-MB-FUS compared to cfDNA level in blood pre-MB-FUS. The primary study hypothesis is that agreement rate on biomarker pattern between resected/biopsied tumor tissue and blood is > 70%. The secondary hypothesis is that MB-FUS BBBO leads to a ≥2-fold rise in blood cfDNA. Assuming the true agreement rate expected is 89%, a sample of N = 50 patients will provide 90% power to meet the primary endpoint (Exact test, Binomial Proportion, one-sided Alpha = 0.025). Exploratory endpoints include (1) sensitivity of detection of known specific somatic mutations in ctDNA from blood samples collected before and after MB-FUS, (2) estimation of ctDNA levels in samples collected at 30-minutes, 1-hour, 2-hour, and 3-hour post-MB-FUS to determine time of greatest yield, (3) correlation of MRI parameters related to grading of BBB opening and ctDNA-based biomarkers from post-MB-FUS blood samples, (4) biomarker correlation between plasma cfDNA sampled during adjuvant chemotherapy phase and tumor tissue harvested at surgery. Patient enrollment commenced in 2022 and is ongoing (NCT05383872). Clinical trial information: NCT05383872 .

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 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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.019
GPT teacher head0.323
Teacher spread0.303 · 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 designNon-randomized trial
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
Published2025
Admission routes2
Has abstractyes

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