Comparative evaluation of a surface-based respiratory monitoring system against a pressure sensor for 4DCT image reconstruction in phantoms

• Verfasst von: Qubala, Abdallah [VerfasserIn]
• Verfasst von: Shafee, Jehad [VerfasserIn]
• Verfasst von: Batista, Vania [VerfasserIn]
• Verfasst von: Liermann, Jakob [VerfasserIn]
• Verfasst von: Winter, Marcus [VerfasserIn]
• Verfasst von: Piro, Daniel [VerfasserIn]
• Verfasst von: Jäkel, Oliver [VerfasserIn]
• Titel: Comparative evaluation of a surface-based respiratory monitoring system against a pressure sensor for 4DCT image reconstruction in phantoms
• Verf.angabe: Abdallah Qubala, Jehad Shafee, Vania Batista, Jakob Liermann, Marcus Winter, Daniel Piro, Oliver Jäkel
• E-Jahr: 2024
• Jahr: February 2024
• Umfang: 14 S.
• Illustrationen: Illustrationen
• Fussnoten: Online veröffentlicht: 10. Oktober 2023 ; Gesehen am 05.12.2023
• Titel Quelle: Enthalten in: Journal of applied clinical medical physics
• Ort Quelle: Reston, Va. : ACMP, 2000
• Jahr Quelle: 2024
• Band/Heft Quelle: 25(2024), 2, Artikel-ID e14174, Seite 1-14
• ISSN Quelle: 1526-9914
• DOI: doi:10.1002/acm2.14174
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: 4DCT reconstruction
• Sach-SW: breathing detection
• Sach-SW: breathing surrogate
• Sach-SW: commissioning
• Sach-SW: mobile tumors
• Sach-SW: motion artifacts
• Sach-SW: respiratory monitoring system
• Sach-SW: Surface-guided radiotherapy
• K10plus-PPN: 187191972X

Abstract

Four-dimensional computed tomography (4DCT), which relies on breathing-induced motion, requires realistic surrogate information of breathing variations to reconstruct the tumor trajectory and motion variability of normal tissues accurately. Therefore, the SimRT surface-guided respiratory monitoring system has been installed on a Siemens CT scanner. This work evaluated the temporal and spatial accuracy of SimRT versus our commonly used pressure sensor, AZ-733 V. A dynamic thorax phantom was used to reproduce regular and irregular breathing patterns acquired by SimRT and Anzai. Various parameters of the recorded breathing patterns, including mean absolute deviations (MAD), Pearson correlations (PC), and tagging precision, were investigated and compared to ground-truth. Furthermore, 4DCT reconstructions were analyzed to assess the volume discrepancy, shape deformation and tumor trajectory. Compared to the ground-truth, SimRT more precisely reproduced the breathing patterns with a MAD range of 0.37 ± 0.27 and 0.92 ± 1.02 mm versus Anzai with 1.75 ± 1.54 and 5.85 ± 3.61 mm for regular and irregular breathing patterns, respectively. Additionally, SimRT provided a more robust PC of 0.994 ± 0.009 and 0.936 ± 0.062 for all investigated breathing patterns. Further, the peak and valley recognition were found to be more accurate and stable using SimRT. The comparison of tumor trajectories revealed discrepancies up to 7.2 and 2.3 mm for Anzai and SimRT, respectively. Moreover, volume discrepancies up to 1.71 ± 1.62% and 1.24 ± 2.02% were found for both Anzai and SimRT, respectively. SimRT was validated across various breathing patterns and showed a more precise and stable breathing tracking, (i) independent of the amplitude and period, (ii) and without placing any physical devices on the patient's body. These findings resulted in a more accurate temporal and spatial accuracy, thus leading to a more realistic 4DCT reconstruction and breathing-adapted treatment planning.