Development of the quantitative PET prostate phantom (Q3P) for improved quality assurance of <sup>18</sup>F‐PSMA PET imaging in metastatic prostate cancer
Notice bibliographique
Résumé
Abstract Background Phantoms are commonly used to evaluate and compare the performance of imaging systems given the known ground truth. Positron emission tomography (PET) scanners are routinely validated using the NEMA image quality phantom, in which lesions are modeled using 10 to 37 mm fillable spheres. The NEMA phantom neglects, however, to model focal (3–10‐mm), high‐uptake lesions that are increasingly observed in prostate‐specific membrane antigen (PSMA) PET images. PSMA‐targeting radiopharmaceuticals allow for enhanced detection of metastatic prostate cancers. As such, there is significant need to develop an updated phantom which considers both the quantitative and lesion detectability of this new paradigm in oncological PET imaging. Purpose In this work, we present the Quantitative PET Prostate Phantom (Q3P); a portable and modular phantom that can be used to improve and harmonize imaging protocols for 18F‐PSMA PET scans. Methods A one‐piece cylindrical phantom was designed effectively in two halves, which we call modules. Module 1 was designed to mimic lesions in the presence of background, and Module 2 mimicked very high contrast conditions (i.e., very low background) that can be observed in 18F‐PSMA PET scans. Shell‐less radioactive spheres (3–16‐mm) were cast using epoxy resin mixed with sodium‐22 (22Na), a long half‐life positron emitter with positron range similar to 18F. To establish realistic lesion contrast, the 22Na spheres were mounted in a cylindrical chamber that can be filled with an 18F background (module 1). Thirteen exchangeable spherical cavity inserts (3–37‐mm) were machined in two parts and solvent welded together, and filled with 18F (50 kBq/mL) to model lesions with very high contrast (module 2). Five 2.5‐min PET scans were acquired on a 5‐ring GE Discovery MI PET/CT scanner (General Electric, USA). Lesions were segmented using 41% of SUVmax fixed thresholding (41% FT) and recovery coefficients (RCs) were computed from 5 noise realizations. Results The manufactured phantom is portable (5.7 kg) and scan preparation takes less than 40 min. The total 22Na activity is 250 kBq, allowing it to be shipped as an exempt package under International Atomic Energy Agency (IAEA) regulations. Recovery coefficients, computed using PSF modeling and no post‐reconstruction smoothing, were 130.3% (16 mm), 147.1% (10 mm), 87.2% (6 mm), and 7.0% (3 mm) for RCmax, which decreased to 91.1% (16 mm), 90.6% (10 mm), 53.2% (6 mm), and 3.6% (3 mm) for RCmean in the 22Na spheres. Comparatively, 18F sphere recovery was 110.7% (17 mm), 123.6% (10 mm), 106.5% (7 mm), and 23.3% (3 mm) for RCmax, which was reduced to 76.7% (17 mm), 77.7% (10 mm), 66.8% (7 mm), and 13.5% (3 mm), for RCmean. Conclusions A standardized imaging phantom was developed for lesion quantification assessment in 18F‐PSMA PET images. The phantom is configurable, providing users with the opportunity to modify background activity levels or sphere sizes according to clinical demands. Distributed to the community, the Q3P phantom has the potential to enable better assessment of lesion quantification and harmonization of 18F‐PSMA PET imaging, which may lead to more robust predictive metrics and better outcome prediction in metastatic prostate cancer.
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 | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».