Feasibility of a real‐time dual energy markerless monitoring of lung tumors using a clinical room‐mounted stereoscopic and monoscopic x‐ray imaging system
Notice bibliographique
Résumé
BACKGROUND: The motion of lung tumors during breathing poses challenges in stereotactic body radiotherapy (SBRT), warranting improved monitoring techniques. Breathing complicates SBRT by creating positional uncertainty in the lungs, traditionally managed with PTV margins, respiratory gating, or breath hold, each with significant drawbacks. While external and implanted markers for tracking have limitations, dual energy (DE) imaging offers a noninvasive, markerless solution that enhances soft tissue contrast and improves real-time tumor localization accuracy and precision. PURPOSE: This study aims to develop a markerless real-time DE tumor localization technique on a clinical room-mounted x-ray image guidance system to allow precise 3D stereoscopic and monoscopic lung tumor motion monitoring during radiotherapy. METHODS: A motorized programmable breathing phantom combined with an anthropomorphic phantom was developed to simulate a lung tumor's respiratory motion, with various asymmetric 3D printed tumor models from lung patients. Tumor sizes ranged between 1.0 and 3.3 cm, with some having varying densities and imaged with varying doses. Real-time images were acquired with a clinical ExacTrac stereoscopic imaging system at a rate of 1.67 Hz with high and low energies (140 and 60 kVp). Weighted logarithmic subtraction and an anti-correlated noise reduction algorithm were used to generate DE images. Conventional single energy images (120 kVp) were acquired for comparison. Digital reconstructed radiographs from x-ray imaging views were created to serve as templates for a template-matching algorithm developed to localize tumor locations on x-ray views. For the stereoscopic case where both imaging views were available, 3D triangulation was performed to localize the tumor. In the monoscopic case, when only one x-ray view was available, the 3D tumor position was estimated using a single 2D localization, combined with a 3D probability density function (PDF) describing tumor motion. RESULTS: Stereoscopic DE techniques demonstrated accurate localizations. The monoscopic view obstructed by the spine showed lower success rates than the view obstructed only by the rib bone. In stereoscopic cases, the localization success rates were similar (>96%) between single and DE techniques for large tumor sizes. As tumor sizes decreased, the localization success rates were higher for DE than the single energy technique showing an improvement of up to 25%. Monoscopic results demonstrated the same trend, with DE localization success rates improvement versus single energy by up to 53% for small tumors. DE showed more successful localization for less dense tumors by up to 60% compared to single energy. Tumors imaged with varying mAs values while remaining at optimal kVp settings showed similar localization success rates between single and DE techniques. CONCLUSION: A real-time markerless tumor monitoring technique was developed utilizing a clinical room-mounted stereoscopic/monoscopic image guidance system. DE increases the accuracy of successful tumor localization as compared to the conventional single energy approach, especially for smaller, less dense tumors. The use of PDFs may be a viable approach to monoscopic estimates when only one view is available.
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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 | 0,001 | 0,001 |
| 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 | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 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 ».