Detection of clinically significant prostate cancer with 18F-DCFPyL (PSMA) PET/MR compared to mpMR alone: preliminary results of a prospective trial
Bibliographic record
Abstract
1574 Objectives: The workup of patients with clinical suspicion of prostate cancer (PCa) includes TRUS-guided systematic biopsies and if these are negative, multiparametric pelvic MR (mpMR), interpreted using a 5-point scoring scale (PI-RADS-v2). For focal lesions on mpMR, MR-US fusion biopsies can be performed. Although PSMA-ligand PET imaging (=PET) is increasingly being used for staging and restaging of prostate cancer, its role in the detection of clinically significant PCa (csPCa) is still uncertain. The purpose of the current study is to assess the incremental value of PSMA- ligand (18F-DCFPyL) PET/mpMR as compared to mpMR alone in detecting csPCa. Methods: This is a preliminary analysis of the first 22 men enrolled on a prospective single arm study. Inclusion criteria were clinical suspicion of prostate cancer with negative TRUS-guided biopsy, clinically discordant low-risk prostate cancer (suspicion of more extensive or aggressive disease), or potential candidates for focal treatment. Initially mpMR and PET images were interpreted separately and all lesions with PI-RADS score ≥ 3 on MR1 and molecular imaging PSMA (miPSMA) expression score ≥ 1 on PET2 were recorded. A combined PET/mpMR interpretation was done according to recently suggested interpretation criteria (Prostate Cancer Molecular Imaging Standardized Evaluation; PROMISE), with equivocal lesions considered positive. All focal lesions on mpMR, PET and PET/mpMR were biopsied using PET/MR-US fusion targeted biopsy. csPCa was defined as tumors with a Gleason score ≥ 3+4. The performance of mpMR in detecting csPCa, using lesions with score 4 or 5 as positive as per PI-RADS v2, was compared to PET/mpMR using the PROMISE interpretation criteria, considering equivocal lesions as positive. Results: There were 50 prostate lesions detected in 22 men. These lesions were identified on MR alone (n=13), on PET alone (n=19) or both (n=18). There were no lymph nodes or distant metastasis in any of the patients. For csPCa, the sensitivity, specificity, and overall accuracy of mpMR and PET/mpMR were 64.3%, 86.1% and 80% & 85.7%, 75% and 78%, respectively. csPCa was more often detected in mpMR equivocal lesions (PIRADS category 3) when any focal PSMA uptake was detected 3/6 (50%), compared to those with no appreciable PSMA uptake 2/11 (18%). Conclusions: Interpretation of PSMA PET with mpMR improved the sensitivity of mpMR alone in detecting csPCa but did not improve specificity. Furthermore, equivocal mpMR lesions were more likely malignant when also associated with PSMA uptake. However, these findings need to be confirmed in a larger patient population.Figure: 57y old man with PSA 10.3 and a biopsy proven Gleason score 6 (3+3) on TRUS-guided systematic biopsy. On follow-up mpMR he had small equivocal lesion (PI-RADS 3) with low T2 signal (a) and mild restricted diffusion (b) in the left posterior base peripheral zone. On PSMA PET there was mild uptake (SUVmax- 3.2) corresponded to the same lesion (c,d). A repeat PET/MR-US fusion targeted biopsy revealed a Gleason score 7 (3+4) lesion.
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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 | 0.017 | 0.010 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".