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Record W3012014097 · doi:10.1186/s13014-020-01506-6

Indications, feasibility, safety, and efficacy of CyberKnife radiotherapy for the treatment of olfactory groove meningiomas: a single institutional retrospective series

2020· article· en· W3012014097 on OpenAlexaff
Jianmin Liu, Rafael Rojas, Fred C. Lam, Farhan A. Mirza, Anand Mahadevan, Ekkehard M. Kasper

Bibliographic record

VenueRadiation Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicMeningioma and schwannoma management
Canadian institutionsMcMaster UniversityHamilton General Hospital
Fundersnot available
KeywordsMedicineRadiosurgeryCyberknifeRadiation therapyStereotactic radiotherapyRetrospective cohort studySurgeryRadiology

Abstract

fetched live from OpenAlex

Abstract Purpose To assess the safety and efficacy of CyberKnife® radiotherapy (CKRT) for the treatment of olfactory groove meningiomas (OGMs). Methods A retrospective review was performed of 13 patients with OGM treated with CKRT from September 2005 to May 2018 at our institution. Nine patients were treated primarily with CKRT, 3 for residual disease following resection, and 1 for disease recurrence. Results Five patients were treated with stereotactic radiosurgery (SRS), 6 with hypofractionated stereotactic radiotherapy (HSRT), and 2 with fractionated stereotactic radiotherapy (FSRT). The median tumor volume was 8.12 cm 3 . The median prescribed dose was 14.8 Gy for SRS, 27.3 Gy for HSRT, and 50.2 Gy for FSRT. The median maximal dose delivered was 32.27 Gy. Median post treatment follow-up was 48 months. Twelve of 13 patients yielded a 100% regional control rate with a median tumor volume reduction of 31.7%. Six of the 12 patients had reduced tumor volumes while the other 6 had no changes. The thirteenth patient had significant radiation-induced edema requiring surgical decompression. Twelve patients were alive and neurologically stable at the time of the review. One patient died from pneumonia unrelated to his CKRT treatment. Conclusions CKRT appears to be safe and effective for the treatment of OGMs.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
Threshold uncertainty score0.300

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 head0.058
GPT teacher head0.325
Teacher spread0.267 · 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 designObservational
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

Citations6
Published2020
Admission routes1
Has abstractyes

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