Objective: This study aims to quantify the uncertainties of CyberKnife Synchrony fiducial tracking for liver stereotactic body radiation therapy (SBRT) cases, and evaluate the required planning target volume (PTV) margins.
Methods: A total of 11 liver tumor patients with a total of 57 fractions, who underwent SBRT with synchronous fiducial tracking, were enrolled for the present study. The correlation/prediction model error, geometric error, and beam targeting error were quantified to determine the patient-level and fraction-level individual composite treatment uncertainties. The composite uncertainties and multiple margin recipes were compared for scenarios with and without rotation correction during treatment.
Results: The correlation model error-related uncertainty was 4.3±1.8, 1.4±0.5 and 1.8±0.7 mm in the superior-inferior (SI), left-right, and anterior-posterior directions, respectively. These were the primary contributors among all uncertainty sources. The geometric error significantly increased for treatments without rotation correction. The fraction-level composite uncertainties had a long tail distribution. Furthermore, the generally used 5-mm isotropic margin covered all uncertainties in the left-right and anterior-posterior directions, and only 75% of uncertainties in the SI direction. In order to cover 90% of uncertainties in the SI direction, an 8-mm margin would be needed. For scenarios without rotation correction, additional safety margins should be added, especially in the superior-inferior and anterior-posterior directions.
Conclusion: The present study revealed that the correlation model error contributes to most of the uncertainties in the results. Most patients/fractions can be covered by a 5-mm margin. Patients with large treatment uncertainties might need a patient-specific margin.
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http://dx.doi.org/10.1007/s11596-023-2717-6 | DOI Listing |
Adv Sci (Weinh)
December 2024
Department of Bioengineering, Department of Electrical and Computer Engineering, Beckman Institute for Advanced Science and Technology, Cancer Center at Illinois, University of Illinois Urbana-Champaign, Urbana, IL, 61801, USA.
High-resolution optical microscopy, particularly super-resolution localization microscopy, requires precise real-time drift correction to maintain constant focus at nanoscale precision during the prolonged data acquisition. Existing methods, such as fiducial marker tracking, reflection monitoring, and bright-field image correlation, each provide certain advantages but are limited in their broad applicability. In this work, a versatile and robust drift correction technique is presented for single-molecule localization-based super-resolution microscopy.
View Article and Find Full Text PDFHardwareX
December 2024
School of Electrical Engineering and Computer Science, The Pennsylvania State University, University Park, 16802, PA, USA.
Honey bee foraging is a complex behavior because it involves tens of thousands of organisms making decisions about where to collect pollen and nectar based on the quality of resources and the distance to flowers. Studying this aspect of their biology is possible through direct observations but the large number of individuals involved in this behavior makes the implementation of technologies ideal to scale up this type of study. Consequently, there is a need for instruments that can facilitate accurate assessments of honey bee foraging at the colony level.
View Article and Find Full Text PDFInt J Med Robot
December 2024
Department of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, South Korea.
Background: Cable-driven continuum manipulators (CDCMs) enable scar-free procedures but face limitations in workspace and control accuracy due to hysteresis.
Methods: We introduce an extensible CDCM with a semi-active mechanism (SAM) and develop a real-time hysteresis compensation control algorithm using a temporal convolution network (TCN) based on data collected from fiducial markers and RGBD sensing.
Results: Performance validation shows the proposed controller significantly reduces hysteresis by up to 69.
Front Oncol
November 2024
Department of Oncology, The First Hospital of Hebei Medical University, Shijiazhuang, China.
Objective: This study investigates the impact of non-standard positioning on the accuracy of 6D-skull tracking using dual-panel imaging systems. It explores whether positioning patients' heads at various angles during intracranial lesion treatment affects the accuracy of the CyberKnife 6D-skull tracking system.
Materials And Methods: A heterogeneous density skull phantom was used to simulate various patient skull positioning angles.
ISA Trans
November 2024
Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle, Ministry of Education, School of Electrical Engineering, Southwest Jiaotong University, Chengdu, 610031, China. Electronic address:
With the growing size of the system, this distributed Kalman filter (DKF) is widely used in multi-sensor networks. However, it is difficult for DKF to accurately estimate state values in non-Gaussian noise environments. In this paper, a regression equation is first constructed to contain all sensor node information.
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