Hypoxia Detection in Infiltrative Astrocytoma: Ferumoxytol-based Quantitative BOLD MRI with Intraoperative and Histologic Validation
Bibliographic record
Abstract
Purpose To validate ferumoxytol-based quantitative blood oxygenation level–dependent (BOLD) MRI for mapping oxygenation of human infiltrative astrocytomas by using intraoperative measurement of tissue oxygen tension and histologic staining. Materials and Methods Fifteen patients with infiltrative astrocytomas were recruited into this prospective multicenter study between July 2014 and December 2016. Prior to treatment, participants underwent preoperative quantitative BOLD MRI with ferumoxytol to generate tissue oxygen saturation (StO2) maps. Two intratumoral sites were identified, one with low StO2 and one with high StO2. Neuronavigation was used to locate sites intraoperatively for insertion of oxygen-sensing probes to measure local tissue oxygen tension (PtO2). Biopsies from both sites were taken and stained for markers of hypoxia (hypoxia-inducible factor 1α, carbonic anhydrase IX) and neoangiogenesis (vascular endothelial growth factor, endoglin [CD105]). Spearman correlation and nonparametric sign-rank tests were used to analyze data. Results Ten patients with median age of 58.5 years (interquartile range, 25 years; four men and six women) completed the study. Because there is no linear relationship between StO2 and PtO2, the ratios of low to high StO2 versus low to high PtO2 in each patient were compared and a significant correlation was found (r = 0.73; P = .01). Pathologic analyses revealed differences between carbonic anhydrase IX (P = .03) for sites of low StO2 versus high StO2. CD105 displayed a similar trend but was not significant (P = .09). Conclusion Ferumoxytol-based quantitative blood oxygenation level–dependent MRI can potentially be used as a noninvasive surrogate for oxygenation mapping in infiltrative astrocytomas. This technique can potentially be integrated in treatment planning for aggressive targeting of hypoxic areas in tumors. © RSNA, 2018
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".