Role of intravoxel incoherent motion parameters in gastroesophageal cancer: relationship with 18F-FDG-positron emission tomography, computed tomography perfusion and magnetic resonance perfusion imaging parameters
Bibliographic record
Abstract
BACKGROUND: Identification of pretherapeutic predictive markers in gastro-esophageal cancer is essential for individual-oriented treatment. This study evaluated the relationship of multimodality parameters derived from intravoxel incoherent motion method (IVIM), 18F-FDG-positron emission tomography (PET), computed tomography (CT) perfusion and dynamic contrast enhanced magnetic resonance imaging (MRI) in patients with gastro-esophageal cancer and investigated their histopathological correlation. METHODS: Thirty-one consecutive patients (28 males; median age 63.9 years; range 37-84 years) with gastro-esophageal adenocarcinoma (N.=22) and esophageal squamous cell carcinoma (N.=9) were analyzed. IVIM parameters: pseudodiffusion (D*), perfusion fraction (fp), true diffusion (D) and the threshold b-value (bval); PET-parameters: SUVmax, metabolic tumor volume (MTV) and total lesion glycolysis (TLG); CT perfusion parameters: blood flow (BF), blood volume (BV) and mean transit time (MTT); and MR perfusion parameters: time to enhance, positive enhancement integral, time-to-peak (TTP), maximum-slope-of-increase, and maximum-slope-of-decrease were determined, and correlated to each other and to histopathology. RESULTS: IVIM and PET parameters showed significant negative correlations: MTV and bval (rs =-0.643, P=0.002), TLG and bval (rs=-0.699, P<0.01) and TLG and fp (rs=-0.577, P=0.006). Positive correlation was found for TLG and D (rs=0.705, P=0.000). Negative correlation was found for bval and staging (rs=0.590, P=0.005). Positive correlation was found for positive enhancement interval and BV (rs=0.547, P=0.007), BF and regression index (rs=0.753, P=0.005) and for time-to-peak and staging (rs=0.557, P=0.005). CONCLUSIONS: IVIM parameters (bval, fp, D) provide quantitative information and correlate with PET parameters (MTV, TLG) and staging. IVIM might be a useful tool for additional characterization of gastro-esophageal cancer.
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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 | 0.000 | 0.002 |
| 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) | 0.001 | 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 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".