Certified into the record
The exact text we saved
This is the version exactly as it was saved, character for character. The SHA-256 hash below is a 64-character code worked out from that text. Run the same text through SHA-256 and you get the same code; change a single letter and the code comes out completely different. Each version also stores the previous version’s hash, which chains them together so no version can be swapped out quietly.
TRUVACE RECORD VERSION record: TRV-2026-2401 version: 1 kind: certified reason: Certified into the record timestamp: 2026-11-06T18:01:47.809641Z status: published lens: g_space sector: health headline: Intraoperative Tumor-Tissue Discrimination and Histology-Defined Glioma Grading Using Combined Fluorescence and Diffuse Reflectance Spectroscopy dek: Background Maximal safe glioma resection requires distinguishing infiltrative tumor from surrounding brain. Visible 5-aminolevulinic acid (5-ALA)-induced protoporphyrin IX (PpIX) fluorescence guides surgery, but low or heterogeneous PpIX accumulation and optical attenuation limit sensitivity. We tested whether combined fluorescence spectroscopy (FS) and diffuse reflectance spectroscopy (DRS) could improve tumor-tissue discrimination beyond visible fluorescence. Methods Thirty-three patients with historically cla… gain_title: In a study of 33 glioma patients, a handheld probe with machine learning raised tumor detection sensitivity by 34.3 percentage points over visible 5-ALA fluorescence and found tumor the dye did not show. problem_title: (none) trace_subject: (none) gain_reading: In a study of 33 glioma patients, a handheld probe with machine learning raised tumor detection sensitivity by 34.3 percentage points over visible 5-ALA fluorescence and found tumor the dye did not show. gain_evidence: Compared with visible fluorescence, FS+DRS increased sensitivity by 34.3 percentage points | Combined FS+DRS improved tumor detection and identified histology-positive tumor not visible with standard fluorescence. problem_reading: (none) problem_evidence: (none) quick_read: A study of 33 glioma patients tested a handheld probe that combines fluorescence and diffuse reflectance spectroscopy during 5-ALA-guided surgery. Across 212 sites, the combined approach reached 85.82% sensitivity, 74.36% specificity and 0.81 AUROC for telling tumor from non-tumor tissue. Compared with visible fluorescence alone, sensitivity rose by 34.3 percentage points (95% CI, 19.3-47.5). The combined signal also identified histology-positive tumor that standard fluorescence did not show, a gap that matters because low or uneven dye accumulation limits visible guidance. The work does not yet show that surgeons make better decisions or that patients do better. The authors call for prospective multicenter testing with a locked model, molecularly classified cohorts, prespecified clinical endpoints and spatial registration. limitation: The study has not shown that the added signal improves surgical decisions or patient outcomes; the authors call for prospective multicenter evaluation with a locked model and molecularly classified cohorts. tag: Evidence-backed gain key_points: Thirty-three patients with low-grade, high-grade or recurrent glioma had 5-ALA-guided surgery, and a handheld bimodal probe took in vivo readings. | Readings came from biopsy-paired sites and navigation-defined presumed non-tumor sites, 212 sites in total. | Fluorescence plus reflectance reached 80.09% balanced accuracy, versus 73.16% for fluorescence alone and 66.17% for reflectance alone. | A light-transport model estimated optical properties and corrected the fluorescence signal before machine learning was applied. | Models were validated with leave-one-patient-out cross-validation, and patient-clustered bootstrapping compared the combined method with visible fluorescence. | The study also tested sequential classification of low-grade versus high-grade glioma. rundown: Surgeons aim for maximal safe resection of glioma, which requires separating infiltrating tumor from surrounding brain. Visible fluorescence from 5-ALA-induced protoporphyrin IX guides this, but low or heterogeneous accumulation and optical attenuation limit its sensitivity. The researchers built a handheld probe that captures both fluorescence and diffuse reflectance spectra. A light-transport model estimated tissue optical properties and corrected the fluorescence, and five predictor representations were tested with supervised machine learning. Evaluation used patient-grouped leave-one-patient-out cross-validation across 212 sites. The combined approach outperformed either modality alone and visible fluorescence, including by 34.3 percentage points in sensitivity. The authors recommend prospective multicenter evaluation to determine whether the added signal improves intraoperative decisions and patient outcomes. sources: - peer_reviewed | Neuro-Oncology | https://doi.org/10.1093/neuonc/noag274 | 2026-11-02 prev: 0000000000000000000000000000000000000000000000000000000000000000
- SHA-256 hash
- b408e2eef7ef1e2489707dbe382cd1585f504420d3c0631daf20270543d6db38
- Previous version’s hash
- 0000000000000000000000000000000000000000000000000000000000000000
How to check it yourself, without trusting this page
Download any version from /api/record/TRV-2026-2401 and hash its canonical field yourself, for example with shasum -a 256. You should get its content_hash. Each version’s text also ends with prev:and the hash of the version before it (version 1 points to 64 zeros). If anyone had changed a single character of any version after it was saved, those hashes wouldn’t line up.
ace