GateCT™ surface tracking system for respiratory signal reconstruction in 4DCT imaging
Notice bibliographique
Résumé
PURPOSE: To assess the temporal and spatial accuracy of the GateCT™ system (VisionRT, London, UK), a recently released respiratory tracking system for 4DCT, under both ideal and nonideal respiratory conditions. METHODS: Three experiments were performed by benchmarking and comparing its results with the ground-truth input data and those generated by the widely used Varian RPM™ system (Real-time Position Management, Varian, Palo Alto, CA). The first experiment used 10 sinusoidal breathing patterns (constant amplitude and frequency using sin(6)ωt), 10 "consistent" patient breathing patterns, and 10 "sporadic" patient breathing patterns. Motion was simulated with the quasar™ Programmable Respiratory Motion Platform (MODUS, London, Canada) as the surrogate. The GateCT™ and RPM™ systems were used to track the breathing patterns. The data from both systems were then analyzed in the Fourier domain, to evaluate temporal/phase accuracy, using the Pearson's correlation coefficient (PCC). The analysis correlated the ground-truth input data against the GateCT™ and RPM™ tracking results, respectively. The second experiment used 10 ideal sinusoidal breathing patterns, five of period 2.0 s, and five of period 5.0 s, with varying abdominal amplitudes found in clinical cases (peak-to-peak range: 1.67-10 mm) to test the sensitivity of the system to reconstruct various range of motion. And, the third experiment used 12 consecutive clinical patients to track the abdominal motion simultaneously by the GateCT™ and RPM™ systems. The baseline of the tracking results from both the two systems was analyzed via the mean-position-estimate (MPE) calculations. All experiments were tracked for at least 120 s. RESULTS: In the first experiment, the average PCC values (±SD) of all thirty breathing patterns were 0.9995 ± 0.00035 and 0.9994 ± 0.00041 for the GateCT™ and the RPM™ system, respectively. These nearly identical results demonstrated similar temporal/phase tracking accuracy for the two systems. The results in the second experiment, however, revealed a pattern for the GateCT™ system in which the uncertainty of its mean-position tracking increased as the amplitude of the breathing pattern decreased. For example, a non-negligible baseline drift of up to 29.3% with respect to the peak-to-peak amplitude of 1.67-mm was observed. On the contrary, the RPM™ system displayed a more consistent recording of amplitudes over time with the greatest drift being <7.7%. The third experiment confirmed these findings in the clinical setting. Consistent decrease in PCC values due to the increase in artificial amplitude drifts, as the breathing amplitude decreased, was found. The lowest PCC value was 0.7239 for a patient with 1.57-mm peak-to-peak amplitude. CONCLUSIONS: The GateCT™ system revealed its consistency in temporal/phase tracking but had limitations in accurately tracking the absolute abdominal positions, thus suggesting its appropriateness for phase-sorting of 4DCT rather than amplitude-sorting. In contrast, the RPM™ system demonstrated stable respiratory signal tracking in all ranges and accurately both in phase and amplitude, and is a robust system to use for both phase-sorting and amplitude-sorting techniques. The impact of the observed mean-position drift in the GateCT™ system on the resulting 4DCT image quality, in amplitude-sorting, needs further investigation.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| 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 | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».