Electromagnetic Navigation Bronchoscopy-Guided Fiducial Placement for Robotic Stereotactic Radiosurgery of Lung Tumors

Anantham, Devanand; Feller‐Kopman, David; Shanmugham, L.N.; Berman, Stuart M.; DeCamp, Malcolm M.; Gangadharan, Sidhu P.; Eberhardt, Ralf; Herth, Felix J.F.; Ernst, Armin

doi:10.1378/chest.07-0522

Cited by 141 publications

(87 citation statements)

References 14 publications

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“…Additionally, a pair of orthogonal x-rays tubes image the patient to monitor the location and orientation of several seeds implanted in or near the tumor. 10,19,20,26,30 Three flashpoint cameras continually track the external LEDs and the data are recorded at a frequency of 26 Hz. X-rays are taken by the operators (usually radiation therapist) using the CyberKnife control panel on an approximately per-beam basis, depending on user settings and treatment plan details.…”

Section: Iia Data Sourcementioning

confidence: 99%

“…This motion can occur in all anatomic directions and inhibits the accurate delivery of radiation. 3 It is reported that 42.9% of motion is in the superior-inferior direction (SI), 30.5% is in the anterior-posterior direction (AP), and 26.6% is in the lateral direction (LAT). 3 The International Commission on Radiation Units and Measurements (ICRU) recommends that margins be added to the tumor position to compensate for the geometric uncertainties brought about by this motion and tumor rotations.…”

Section: Introductionmentioning

confidence: 99%

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Correlation and prediction uncertainties in the CyberKnife Synchrony respiratory tracking system

et al. 2011

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Purpose: The CyberKnife uses an online prediction model to improve radiation delivery when treating lung tumors. This study evaluates the prediction model used by the CyberKnife radiation therapy system in terms of treatment margins about the gross tumor volume (GTV). Methods: From the data log files produced by the CyberKnife synchrony model, the uncertainty in radiation delivery can be calculated. Modeler points indicate the tracked position of the tumor and Predictor points predict the position about 115 ms in the future. The discrepancy between Predictor points and their corresponding Modeler points was analyzed for 100 treatment model data sets from 23 de-identified lung patients. The treatment margins were determined in each anatomic direction to cover an arbitrary volume of the GTV, derived from the Modeler points, when the radiation is targeted at the Predictor points. Each treatment model had about 30 min of motion data, of which about 10 min constituted treatment time; only these 10 min were used in the analysis. The frequencies of margin sizes were analyzed and truncated Gaussian normal functions were fit to each direction's distribution. The standard deviation of each Gaussian distribution was then used to describe the necessary margin expansions in each signed dimension in order to achieve the desired coverage. In this study, 95% modeler point coverage was compared to 99% modeler coverage. Two other error sources were investigated: the correlation error and the targeting error. These were added to the prediction error to give an aggregate error for the CyberKnife during treatment of lung tumors. Results: Considering the magnitude of 2r from the mean of the Gaussian in each signed dimension, the margin expansions needed for 95% modeler point coverage were 1.2 mm in the lateral (LAT) direction and 1.7 mm in the anterior-posterior (AP) direction. For the superior-inferior (SI) direction, the fit was poor; but empirically, the expansions were 3.5 mm. For 99% modeler point coverage, the AP margin was 3.6 mm and the lateral margin was 2.9 mm. The SI margins for 99% modeler point coverage were highly variable. The aggregate error at 95% was 6.9 mm in the SI direction, 4.6 mm in the AP direction, and 3.5 in the lateral direction. Conclusions: The Predictor points follow the Modeler points closely. Margins were found in each clinical direction that would provide 95% modeler point coverage for 95% of the models reviewed in this study. Similar margins were found in two clinical directions for 99% modeler point coverage in 95% of models. These results can offer guidance in the selection of CTV margins for treatment with the CyberKnife.

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Section: Iia Data Sourcementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Correlation and prediction uncertainties in the CyberKnife Synchrony respiratory tracking system

et al. 2011

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“…Similarly a small series described no pneumothorax in 8 patients who underwent electromagnetic navigation bronchoscopy for endobronchial implantation of 39 fiducial markers (10). Also, retention of implanted fiducial markers in lung tissue varies by marker type.…”

Section: Fiducial Placementmentioning

confidence: 90%

CyberKnife Stereotactic Ablative Radiotherapy for Lung Tumors

Gibbs

Loo

2010

Technol Cancer Res Treat

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Stereotactic ablative radiotherapy (SABR) has emerged as a promising treatment for early stage non-small cell lung cancer, particularly for patients unable to tolerate surgical resection. High rates of local tumor control have been demonstrated with acceptable toxicity and the practical advantage of a short course of treatment. The CyberKnife image-guided robotic radiosurgery system has unique technical characteristics that make it well suited for SABR of tumors that move with breathing, including lung tumors. We review the qualities of the CyberKnife platform for lung tumor SABR, and provide a summary of clinical data using this system specifically.

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“…Stereotactic radiotherapy may require fiducial markers to track respiration cycle and compensate for the changing tumor position (16), while reducing irradiation to the surrounding healthy lung. Fiducials can be inserted into intrathoracic tumors with different modalities: transthoracic, intravascular, and bronchoscopic ( Figure 3).…”

Section: To Help Stereotactic Radiosurgerymentioning

confidence: 99%

Endobronchial treatment of peripheral tumors: ongoing development and perspectives

et al. 2018

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Abstract:The expanded possibilities to explore the lung deeper with new tools such as electromagnetic navigation bronchoscopy (ENB) or radial probe endobronchial ultrasonography (radial EBUS), combined with miniaturization of traditional local therapies such as radiofrequency ablation (RFA), radiotherapy, cryotherapy or photodynamic therapy, let the bronchoscopists hope for new ways of endoscopic treatments.This challenge could change the practice in the upcoming decades but raise some physical and technical issues. Safety and efficacy need to be solidly established to face the serious concurrence of stereotactic radiotherapy (SBRT) or percutaneous RFA. Here we describe ongoing development and perspectives for endobronchial treatment of peripheral lung tumors.

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Electromagnetic Navigation Bronchoscopy-Guided Fiducial Placement for Robotic Stereotactic Radiosurgery of Lung Tumors

Cited by 141 publications

References 14 publications

Correlation and prediction uncertainties in the CyberKnife Synchrony respiratory tracking system

Correlation and prediction uncertainties in the CyberKnife Synchrony respiratory tracking system

CyberKnife Stereotactic Ablative Radiotherapy for Lung Tumors

Endobronchial treatment of peripheral tumors: ongoing development and perspectives

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