P03.27.B FLUID-SUPPRESSED APTW IMAGING BEFORE AND AFTER SURGERY IN GLIOBLASTOMA: A PROOF-OF-CONCEPT FOR DETECTING INFILTRATIVE AND RESIDUAL TUMOR BEYOND CONTRAST ENHANCEMENT
Bibliographic record
Abstract
Abstract BACKGROUND In glioblastoma (GBM), the presence of residual tumor on postoperative imaging is strongly associated with patient survival. Thus, the standard of care involves maximal safe resection of contrast-enhancing tumor tissue. However, tumor infiltration often extends beyond these margins into non-enhancing peritumoral brain regions that are not visible on conventional MRI. Amide Proton Transfer-weighted (APTw) imaging has demonstrated potential for visualizing tumor-related metabolic activity beyond the contrast-enhancing zone. However, conventional APT imaging might be limited due to fluid-related artifacts following surgery, particularly from the resection cavity. In this study, we employ fluid-suppressed APTw imaging to improve both pre- and postoperative visualization and to offer a novel approach for more specific identification of residual tumor volume. METHODS In this prospective study 10 patients with histologically confirmed glioblastoma underwent fluid-suppressed APT imaging at 3T, both before and after surgical resection. APT maps were co-registered with conventional anatomical and contrast-enhanced MRI sequences. We evaluated peritumoral and postoperative regions for APT signal abnormalities and compared the findings with those from standard imaging. RESULTS Preoperatively, fluid-suppressed APTw imaging consistently revealed elevated signals extending beyond the gadolinium-enhancing tumor margins, consistent with suspected infiltrative tumor. Postoperatively, the technique effectively reduced fluid-related signal contamination within and around the resection cavity, thereby improving image interpretability. Additionally, APTw imaging identified residual areas of high signal intensity in non-enhancing regions, suggesting the presence of metabolically active tumor tissue not detectable by conventional MRI. CONCLUSION Fluid-suppressed APTw imaging enhances the detection of infiltrative tumor beyond contrast-enhancing margins in preoperative scans and reveals residual disease not visible on conventional MRI postoperatively. These findings support further investigation of this technique’s potential role in surgical planning and treatment monitoring.
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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 | 0.001 | 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) | 0.002 | 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".