Comprehensive SPECT/CT system characterization and calibration for 177Lu quantitative SPECT (QSPECT) with dead-time correction
Notice bibliographique
Résumé
Abstract Background Personalization of 177Lu-based radionuclide therapy requires implementation of dosimetry methods that are both accurate and practical enough for routine clinical use. Quantitative single-photon emission computed tomography/computed tomography (QSPECT/CT) is the preferred scanning modality to achieve this and necessitates characterizing the response of the camera, and calibrating it, over the full range of therapeutic activities and system capacity. Various methods to determine the camera calibration factor (CF) and the deadtime constant (τ) were investigated, with the aim to design a simple and robust protocol for quantitative 177Lu imaging. Methods The SPECT/CT camera was equipped with a medium energy collimator. Multiple phantoms were used to reproduce various attenuation conditions: rod sources in air or water-equivalent media, as well as a Jaszczak phantom with inserts. Planar and tomographic images of a wide range of activities were acquired, with multiple energy windows for scatter correction (double or triple energy window technique) as well as count rate monitoring over a large spectrum of energy. Dead time was modelled using the paralysable model. CF and τ were deduced by curve fitting either separately in two steps (CF determined first using a subset of low-activity acquisitions, then τ determined using the full range of activity) or at once (both CF and τ determined using the full range of activity). Total or segmented activity in the SPECT field of view was computed. Finally, these methods were compared in terms of accuracy to recover the known activity, in particular when planar-derived parameters were applied to the SPECT data. Results The SPECT camera was shown to operate as expected on a finite count rate range (up to ~ 350 kcps over the entire energy spectrum). CF and τ from planar (sources in air) and SPECT segmented Jaszczak data yielded a very good agreement (CF < 1% and τ < 3%). Determining CF and τ from a single curve fit made dead-time-corrected images less prone to overestimating recovered activity. Using triple-energy window scatter correction while acquiring one or more additional energy window(s) to enable wide-spectrum count rate monitoring (i.e. ranging 55–250 or 18–680 keV) yielded the most consistent results across the various geometries. The final, planar-derived calibration parameters for our system were a CF of 9.36 ± 0.01 cps/MBq and a τ of 0.550 ± 0.003 μs. Using the latter, the activity in a Jaszczak phantom could be quantified by QSPECT with an accuracy of 0.02 ± 1.10%. Conclusions Serial planar acquisitions of sources in air using an activity range covering the full operational capacity of the SPECT/CT system, with multiple energy windows for wide-spectrum count rate monitoring, and followed by simultaneous determination of CF and τ using a single equation derived from the paralysable model, constitutes a practical method to enable accurate dead-time-corrected QSPECT imaging in a post-177Lu radionuclide therapy setting.
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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 | 0,003 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| 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 ».