Kinetic analysis of dominant intraprostatic lesion of prostate cancer using quantitative dynamic [18F]DCFPyL-PET: comparison to [18F]fluorocholine-PET
Bibliographic record
Abstract
Abstract Purpose Identification of the dominant intraprostatic lesion(s) (DILs) can facilitate diagnosis and treatment by targeting biologically significant intra-prostatic foci. A PSMA ligand, [ 18 F]DCFPyL (2-(3-{1-carboxy-5-[(6-[ 18 F]fluoro-pyridine-3-carbonyl)-amino]-pentyl}-ureido)-pentanedioic acid), is better than choline-based [ 18 F]FCH (fluorocholine) in detecting and localizing DIL because of higher tumour contrast, particularly when imaging is delayed to 1 h post-injection. The goal of this study was to investigate whether the different imaging performance of [ 18 F]FCH and [ 18 F]DCFPyL can be explained by their kinetic behaviour in prostate cancer (PCa) and to evaluate whether DIL can be accurately detected and localized using a short duration dynamic positron emission tomography (PET). Methods 19 and 23 PCa patients were evaluated with dynamic [ 18 F]DCFPyL and [ 18 F]FCH PET, respectively. The dynamic imaging protocol with each tracer had a total imaging time of 22 min and consisted of multiple frames with acquisition times from 10 to 180 s. Tumour and benign tissue regions identified by sextant biopsy were compared using standardized uptake value (SUV) and tracer kinetic parameters from kinetic analysis of time-activity curves. Results For [ 18 F]DCFPyL, logistic regression identified K i and k 4 as the optimal model to discriminate tumour from benign tissue (84.2% sensitivity and 94.7% specificity), while only SUV was predictive for [ 18 F]FCH (82.6% sensitivity and 87.0% specificity). The higher k 3 (binding) of [ 18 F]FCH than [ 18 F]DCFPyL explains why [ 18 F]FCH SUV can differentiate tumour from benign tissue within minutes of injection. Superior [ 18 F]DCFPyL tumour contrast was due to the higher k 4 / k 3 (more rapid washout) in benign tissue compared to tumour tissue. Conclusions DIL was detected with good sensitivity and specificity using 22-min dynamic [ 18 F]DCFPyL PET and avoids the need for delayed post-injection imaging timepoints. The dissimilar in vivo kinetic behaviour of [ 18 F]DCFPyL and [ 18 F]FCH could explain their different SUV images. Clinical Trial Registration NCT04009174 (ClinicalTrials.gov).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".