INNV-15. A PIVOTAL, MULTICENTER TRIAL OF FOCUSED ULTRASOUND FOR BLOOD-BRAIN BARRIER DISRUPTION FOR PLASMA-BASED LIQUID BIOPSY IN PATIENTS WITH GLIOBLASTOMA (LIBERATE)
Bibliographic record
Abstract
Abstract BACKGROUND Liquid biopsy in glioblastoma (GBM) is hindered by insufficient requisite circulating-tumor (ct) and cell-free (cf) DNA in blood due to blood-brain barrier (BBB). This limits the identification of blood-based tumor biomarkers along with biomarker-driven systemic therapies. Real-time image-guided low-intensity focused ultrasound (LIFU) plus IV microbubble oscillators, leads to non-invasive BBB disruption. METHODS LIBERATE is an ongoing, prospective, multi-center, self-controlled, pivotal trial investigating safety and technical efficacy of LIFU-based BBB disruption for increasing blood ctDNA and cfDNA levels in adult GBM patients (aged 18-80 years). Patients with suspected GBM planned for biopsy/resection at ten US centers 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 effects, after which MR-guided BBB disruption using 220kHz LIFU device is performed with real-time acoustic-feedback-control for effective microbubble activation. Pre- and post-LIFU, phlebotomy and MRI brain are performed. Primary study endpoint is defined, per subject, as ratio between their blood cfDNA level 1-hour post-LIFU procedure compared to blood cfDNA pre-procedure. Primary study hypothesis is that BBB disruption leads to ≥2-fold rise in blood cfDNA. Secondary hypothesis is that there exists ≥75% agreement between biomarker pattern in blood cfDNA sample obtained 1-hour post-LIFU and biomarker pattern in tumor tissue obtained later. Trial is powered to evaluate both primary and secondary hypotheses. Based on assumed true agreement rate of 91% and one-sided alpha=0.025, an exact test for binomial proportions provides N=50 with 84% power for secondary hypothesis. Exploratory endpoints include (1) sensitivity of detection of specific somatic mutations in ctDNA from blood collected pre- and post-LIFU, (2) ctDNA estimation in samples collected at 30-minutes, 1-hour, 2-hour, and 3-hour post-LIFU to determine time of greatest yield, (3) correlation of MRI parameters related to grading of BBB disruption and ctDNA-based biomarkers from post-LIFU blood samples. Patient enrollment commenced in 2022 and remains ongoing (NCT05383872).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".