Kinetic modeling of 68Ga-PSMA-11 and validation of simplified methods for quantification in primary prostate cancer patients
Bibliographic record
Abstract
Abstract Background The positron emission tomography (PET) ligand 68 Ga-Glu-urea-Lys(Ahx)-HBED-CC ( 68 Ga-PSMA-11) targets the prostate-specific membrane antigen (PSMA), upregulated in prostate cancer cells. Although 68 Ga-PSMA-11 PET is widely used in research and clinical practice, full kinetic modeling has not yet been reported nor have simplified methods for quantification been validated. The aims of our study were to quantify 68 Ga-PSMA-11 uptake in primary prostate cancer patients using compartmental modeling with arterial blood sampling and to validate the use of standardized uptake values (SUV) and image-derived blood for quantification. Results Fifteen patients with histologically proven primary prostate cancer underwent a 60-min dynamic 68 Ga-PSMA-11 PET scan of the pelvis with axial T1 Dixon, T2, and diffusion-weighted magnetic resonance (MR) images acquired simultaneously. Time-activity curves were derived from volumes of interest in lesions, normal prostate, and muscle, and mean SUV calculated. In total, 18 positive lesions were identified on both PET and MR. Arterial blood activity was measured by automatic arterial blood sampling and manual blood samples were collected for plasma-to-blood ratio correction and for metabolite analysis. The analysis showed that 68 Ga-PSMA-11 was stable in vivo. Based on the Akaike information criterion, 68 Ga-PSMA-11 kinetics were best described by an irreversible two-tissue compartment model. The rate constants K 1 and k 3 and the net influx rate constants K i were all significantly higher in lesions compared to normal tissue ( p < 0.05). K i derived using image-derived blood from an MR-guided method showed excellent agreement with K i derived using arterial blood sampling (intraclass correlation coefficient = 0.99). SUV correlated significantly with K i with the strongest correlation of scan time-window 30–45 min (rho 0.95, p < 0.001). Both K i and SUV correlated significantly with serum prostate specific antigen (PSA) level and PSA density. Conclusions 68 Ga-PSMA-11 kinetics can be described by an irreversible two-tissue compartment model. An MR-guided method for image-derived blood provides a non-invasive alternative to blood sampling for kinetic modeling studies. SUV showed strong correlation with K i and can be used in routine clinical settings to quantify 68 Ga-PSMA-11 uptake.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".