Detection and delineation of intraprostatic lesions (IPLs) using multiparametric magnetic resonance imaging (mpMRI) and prostate specific membrane antigen positron emission tomography (PSMA PET) for patients with prostate cancer: A systematic review and meta-analysis.
Notice bibliographique
Résumé
287 Background: External beam radiation therapy (EBRT) is a common treatment used for patients with prostate cancer, however, isolated local failures (ILFs) can occur in up to 13% of patients receiving EBRT. Most ILFs occur at the location of the previously known intraprostatic lesions (IPLs). The FLAME trial has shown improved cancer outcomes for patients treated with EBRT who receive a focal radiation boost to their IPL. Both mpMRI and PSMA PET can be used to localize IPL for these patients. Methods: A systematic review and meta-analysis was conducted for the use of mpMRI and PSMA PET for the detection and delineation of IPLs for patients with localized prostate cancer. Trials were included if patients received either mpMRI, PSMA PET, or both, prior to radical prostatectomy (RP). IPLs on RP specimens were used as the reference standard. The quality of the co-registration between imaging and histopathology was assessed as high or low for each study included in the systematic review. Outcomes that were recorded include sensitivity and specificity, among others. A meta-analysis was conducted using a bivariate model to determine the sensitivity, specificity, and area under the receiver operating curve (AUROC) of mpMRI, PSMA PET, and their combination. This systematic review was registered through PROSPERO (CRD42023389092). Results: After exclusions, 20 studies were incorporated into the bivariate meta-analysis. In total, there were 13 studies using mpMRI (n = 541 patients), 12 studies that used PSMA PET (n = 327), and 5 studies that used a combination (n = 180). The pooled sensitivity (95% CI), specificity (95% CI) and AUROC for mpMRI were 64.7% (50.2% – 76.9%), 86.4% (79.7% - 91.1%), and 0.852; the pooled outcomes for PSMA PET were 75.7% (64.0% - 84.5%), 87.1% (80.2% - 91.9%), and 0.889; for their combination, the pooled outcomes were 70.3% (64.1% - 75.9%), 81.9% (71.9% - 88.8%), and 0.796. When reviewing studies with a high-quality co-registration between imaging and histopathology, IPL delineation recommendations included using a 1-2 mm margin when delineating on mpMRI, using a SUV max threshold of 20-30% for PSMA PET, and using the union of mpMRI and PSMA PET when using both modalities. Conclusions: In this study, we conducted a meta-analysis of studies that used mpMRI, PSMA PET or their combination prior to RP for patients with localized prostate cancer. The pooled sensitivity and specificity for each modality had overlapping 95% confidence intervals, suggesting the modalities have similar accuracy in detecting IPLs on RP specimens. There were different delineation recommendations based on the imaging modalities used in studies with a high-quality co-registration of imaging and histopathology.
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 | 0,011 | 0,030 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,014 | 0,028 |
| Bibliométrie | 0,006 | 0,007 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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 ».