Javascript must be enabled to continue!
Stereotactic Cones in a 6MV Flattening Filter-free Beam: A Dosimetric Comparison of Varian Cones on TrueBeam versus CyberKnife Cones
View through CrossRef
Purpose:
Dosimetric comparison of conical collimator (CC) supplied by Varian Medical System on a TrueBeam (TB) for 6MV-flattening filter-free (FFF) beams versus CC on CyberKnife-G4 (CK) by Accuray Inc.
Methods:
5 cones with nominal diameters of 5 mm, 7.5 mm, 10 mm, 12.5 mm, and 15 mm were considered in our study. Percentage depth dose (PDD), off-axis ratio (OAR), tissue maximum ratio (TMR), and output factor (OF) were presented and compared.
Results:
PDD comparisons between TB and CK cones show good agreement across the range of cones; the mean difference of the % dose values, for all cones, was − 0.9% ±1.2% across the five considered depths along the curve. The agreement between CK and TB cones is poorer for TMR; the discrepancies between CK and TB values increase with depth and lightly decrease with increased cone size. OAR profiles are in agreement, although CK cones tend to overestimate the dose between 80% and 5% dose; consequently, the FHWM (full width at half maximum) for CK cones is slightly larger. Except for the 5-mm cone with a difference percentage of −3.7% between CK and Varian cones, CK cones show the largest output factors, with a maximum difference percentage was 1.9% for the 7.5-mm cone.
Conclusion:
CK and TB cones show similar dosimetric characteristics. The observed differences suggest that the 6MV-FFF beams from TB cones would be slightly “softer” than the 6MV-FFF beams from CK cones; Varian cones may potentially provide better sparing of organs at risk.
Ovid Technologies (Wolters Kluwer Health)
Title: Stereotactic Cones in a 6MV Flattening Filter-free Beam: A Dosimetric Comparison of Varian Cones on TrueBeam versus CyberKnife Cones
Description:
Purpose:
Dosimetric comparison of conical collimator (CC) supplied by Varian Medical System on a TrueBeam (TB) for 6MV-flattening filter-free (FFF) beams versus CC on CyberKnife-G4 (CK) by Accuray Inc.
Methods:
5 cones with nominal diameters of 5 mm, 7.
5 mm, 10 mm, 12.
5 mm, and 15 mm were considered in our study.
Percentage depth dose (PDD), off-axis ratio (OAR), tissue maximum ratio (TMR), and output factor (OF) were presented and compared.
Results:
PDD comparisons between TB and CK cones show good agreement across the range of cones; the mean difference of the % dose values, for all cones, was − 0.
9% ±1.
2% across the five considered depths along the curve.
The agreement between CK and TB cones is poorer for TMR; the discrepancies between CK and TB values increase with depth and lightly decrease with increased cone size.
OAR profiles are in agreement, although CK cones tend to overestimate the dose between 80% and 5% dose; consequently, the FHWM (full width at half maximum) for CK cones is slightly larger.
Except for the 5-mm cone with a difference percentage of −3.
7% between CK and Varian cones, CK cones show the largest output factors, with a maximum difference percentage was 1.
9% for the 7.
5-mm cone.
Conclusion:
CK and TB cones show similar dosimetric characteristics.
The observed differences suggest that the 6MV-FFF beams from TB cones would be slightly “softer” than the 6MV-FFF beams from CK cones; Varian cones may potentially provide better sparing of organs at risk.
Related Results
CyberKnife for Recurrent Malignant Gliomas: A Systematic Review and Meta-Analysis
CyberKnife for Recurrent Malignant Gliomas: A Systematic Review and Meta-Analysis
Background and ObjectivePossible treatment strategies for recurrent malignant gliomas include surgery, chemotherapy, radiotherapy, and combined treatments. Among different reirradi...
Monte Carlo simulation of the Varian TrueBeam flattened-filtered beams using a surrogate geometry in PRIMO
Monte Carlo simulation of the Varian TrueBeam flattened-filtered beams using a surrogate geometry in PRIMO
Abstract
Background: Monte Carlo simulation of radiation transport for medical linear accelerators (linacs) requires accurate knowledge of the geometrical description of th...
Monte Carlo simulation of the Varian TrueBeam flattened-filtered beams using a surrogate geometry in PRIMO
Monte Carlo simulation of the Varian TrueBeam flattened-filtered beams using a surrogate geometry in PRIMO
Abstract
Background
Monte Carlo simulation of radiation transport for medical linear accelerators (linacs) requires accurate knowledge of the geomet...
Karakteristik Covid-19 Varian Delta dan Varian Omicron pada Anak
Karakteristik Covid-19 Varian Delta dan Varian Omicron pada Anak
Abstract: To date, COVID-19 has mutated into several types or variants. The variants of this virus, Delta and Omicron, become noticable and spread in all ages including children wo...
Evaluation of the Varian TrueBeam™ 6 MV phase-space files for the Monte Carlo simulation in small field dosimetry
Evaluation of the Varian TrueBeam™ 6 MV phase-space files for the Monte Carlo simulation in small field dosimetry
Background: The Monte Carlo (MC) simulation is an effective tool for determining the absorbed dose in small field sizes. To calculate accurate results, the MC simulation requires p...
The Clinical Outcome of Hypofractionated Stereotactic Radiotherapy With CyberKnife Robotic Radiosurgery for Perioptic Pituitary Adenoma
The Clinical Outcome of Hypofractionated Stereotactic Radiotherapy With CyberKnife Robotic Radiosurgery for Perioptic Pituitary Adenoma
Stereotactic radiation technique including single fraction radiosurgery and conventional fractionated stereotactic radiotherapy is widely reported as an effective treatment of pitu...
Penyebaran sistem vokal DMP di Yaha
Penyebaran sistem vokal DMP di Yaha
Kajian ini dilakukan bertujuan melihat ciri linguistik bagi setiap varian yang wujud di Yaha. Bentuk vokal dilihat dari segi kesejajaran dan penyebarannya dalam ruang geografi, sam...
Dose prediction of CyberKnife Monte Carlo plan for lung cancer patients based on deep learning: robust learning of variable beam configurations
Dose prediction of CyberKnife Monte Carlo plan for lung cancer patients based on deep learning: robust learning of variable beam configurations
Abstract
Background
Accurate calculation of lung cancer dose using the Monte Carlo (MC) algorithm in CyberKnife is essential for precise planning. We aim to employ deep le...

