Sie befinden Sich nicht im Netzwerk der Universität Paderborn. Der Zugriff auf elektronische Ressourcen ist gegebenenfalls nur via VPN oder Shibboleth (DFN-AAI) möglich. mehr Informationen...
Ergebnis 21 von 27
IEEE transactions on biomedical engineering, 2010-01, Vol.57 (1), p.103-113
2010
Volltextzugriff (PDF)

Details

Autor(en) / Beteiligte
Titel
Improved Volumetric MR-HIFU Ablation by Robust Binary Feedback Control
Ist Teil von
  • IEEE transactions on biomedical engineering, 2010-01, Vol.57 (1), p.103-113
Ort / Verlag
United States: IEEE
Erscheinungsjahr
2010
Quelle
IEEE Electronic Library Online
Beschreibungen/Notizen
  • Volumetric high-intensity focused ultrasound (HIFU) guided by multiplane magnetic resonance (MR) thermometry has been shown to be a safe and efficient method to thermally ablate large tissue volumes. However, the induced temperature rise and thermal lesions show significant variability, depending on exposure parameters, such as power and timing, as well as unknown tissue parameters. In this study, a simple and robust feedback-control method that relies on rapid MR thermometry to control the HIFU exposure during heating is introduced. The binary feedback algorithm adjusts the durations of the concentric ablation circles within the target volume to reach an optimal temperature. The efficacy of the binary feedback control was evaluated by performing 90 ablations in vivo and comparing the results with simulations. Feedback control of the sonications improved the reproducibility of the induced lesion size. The standard deviation of the diameter was reduced by factors of 1.9, 7.2, 5.0, and 3.4 for 4-, 8-, 12-, and 16-mm lesions, respectively. Energy efficiency was also improved, as the binary feedback method required less energy to create the desired lesion. These results show that binary feedback improves the quality of volumetric ablation by consistently producing thermal lesions of expected size while reducing the required energy as well.

Weiterführende Literatur

Empfehlungen zum selben Thema automatisch vorgeschlagen von bX