Detection of clinically significant prostate cancer with 18F-DCFPyL (PSMA) PET/MR compared to mpMR alone: preliminary results of a prospective trial
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,017 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,004 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,004 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».