Purpose: To develop a simple software tool to help determine whether a fiducial placement meets the Spacing and Collinearity criteria for CyberKnife 6D target tracking. Methods: An Excel spreadsheet has been developed for this purpose. The spreadsheet calculates distances and angles for all possible combinations of fiducial triplets based on the fiducial coordinates entered. In general, a group of 4 fiducials forms 4 triplets; a group of 6 fiducials forms 20 triplets. Distance between any two points in 3D space can be calculated easily. Angles formed by lines joining a fiducial triplet are calculated by using the law of cosines. Calculations using scalar product of vectors method are also implemented and used as a redundancy check. Fiducial placement and CyberKnife treatment data from 78 prostate patients were analyzed. Results: The spreadsheet checks each fiducial triplet against the Spacing & Collinearity Thresholds. Distances or angles failed to meet the thresholds are flagged. If none of the fiducial triplets meet the criteria, extra fiducials need to be implanted. Of the 78 patients studied, most patients were implanted with 4 fiducials; seven patients had 3, and twenty patients had 6 fiducials. A total of the 345 fiducials and 600+ triplets were analyzed. The study showed that 72% of the fiducial distances exceeded the 20‐mm Spacing Threshold, and 99% of the fiducial angles exceeded the 15‐degree Collinearity Threshold. Conclusions: We have developed an Excel spreadsheet to verify that a fiducial placement meets the Cyberknife 6D tracking criteria before patient treatment. Analyzing past patient data helps provide guidance on how fiducial placement may be improved. It is important that least one of the fiducial triplets exceed both Spacing and Collinearity Thresholds, as the study has found that there were cases where a fiducial triplet met the Spacing criteria but failed Collinearity criteria, and vice versa.
Purpose: During the setup of Cyberknife patients with extracranial tumors, it is always a challenge to tell the angles of misalignment (roll, yaw and pitch) from the two digital reconstructed radiographs (DRRs) and the radiographs from two X‐ray cameras. Most of the cases, software handles the problem, but in some cases, software fails, it is because of fiducial migration or not enough fiducials to give 6D information (fiducial), or fiducial motion due to tumor motion (synchrony), or the angles are too large for the software to handle (skeletal structure tracking). When this happens, the operator needs to make the right decision fast, in order to shorten the setup time and to deliver the correct dose to the tumor. We decided to write a program to help people in this situation. This program can generate DRRs before and after each transformation. It will be a great learning tool; new users can practice how to set up a patient from a random starting position; we can't practice the setup on a live patient. Experienced users can use it to study setup, learn how the positions of different structures change relative to different rotations. Method and Materials: Java programming was chosen to build the software. The DRRs were reconstructed from a series of CT images according to Cyberknife X‐ray sources and screens configuration. Results: A graphic user interface (GUI) with two DRRs will be presented to the user, user can choose to translate and rotate the patient, two more DRRs will be generated; and a CT slice will also show up on the GUI. The user can identify the features that have the most change in each transformation. Conclusions: This program works as expected. It also demonstrates to the medical physics community that we can easily write programs to manipulate images.
Purpose: To find out the dose difference on targets and organs at risk for the treatment of acoustic schwannoma if the inhomogeneity correction (Convolution algorithm) is applied. Methods: Images of patients treated for acoustic schwannoma with Gamma Knife using TMR 10 algorithm were retrieved from database and replanned with Convolution and TMR 10 algorithm respectively. These patients were treated using a preplan scheme in following: (1) Before the actual treatment day, using the MRI image that was taken without a head frame on the patient's skull, a pre‐treatment plan was made based on the default skull coordinates in the Gamma Knife treatment planning system (LGP); (2) then on treatment day, a head frame was placed on the patient's skull, and a CT image was taken. The CT image with head frame was registered and fused with the completed preplan; (3) the treatment plan was finalized and the treatment was delivered. To find out the dosimetry impact of inhomogeneity correction, we used the retrieved CT images to replan the treatment using Convolution algorithm in LGP software version 10.1.1. The dose distributions and the dose volume histograms for targets and OARs were compared for these two dose calculation algorithms. Results: The dose calculated with the Convolution algorithm in general is slightly lower than the one from TMR 10 around the boney area. The effect from the inhomogeneity correction is observable but not significant, and varies with the location of the tumor. Conclusion: Inhomogeneity correction slightly improve the dose accuracy for acoustic schwannoma Gamma Knife treatments although the correction may not be very significant. Our Result provides evidence for dose prescription adjustment to treat acoustic schwannoma. The actual clinical outcome of switching from using TMR10 to using Convolution needs to be further investigated.
Purpose: Varian MLC leaf travel is limited to 14.5 cm. For large PTV, an IMRT field will be split into two or three sub‐fields. Thus a 9‐beam head‐and‐neck plan may end up with 18 or more treatment fields. The purpose of this study is to develop a non‐split IMRT planning technique and compare the quality of non‐split plans with beam‐split counterparts. Method: Varian Eclipse user can choose fixed‐jaws and set field‐size less than 14.5 cm so that IMRT field will not split. A small part of the PTV may be blocked by x‐jaws in a particular beam, but the missing dose from one beam can be covered by other beams at different gantry angles. We compared our previously treated 9‐beam‐split‐18‐field head‐and‐neck IMRT plans with corresponding non‐split plans of 9, 11, and 15 gantry angles. Plan DVH and IMRT QA results were analyzed. Results: Non‐split plans produced the same dose coverage as beam‐split plans. DVH curves of PTV for split and non‐split plans almost overlapped with each other. DVH of organs‐at‐risk were slightly different. Total treatment MU were about the same for all the plans. All IMRT QA plans delivered on a Varian Trilogy passed physics QA criteria, with non‐split plans showing slightly better passing scores. Conclusions: Creating IMRT plans without beam‐splitting is encouraged. Non‐split IMRT plans can be as good as beam‐split plans, but use only half of the number of beams. Quality of non‐split plans improves with increasing number of beams. The amount of improvement was larger for the number of beams going from 9 to 11 than that from 13 to 15, demonstrating a balance of costs and benefits. Cutting the number of beams by half may result in a number of benefits: more accurate dose delivery, shorter treatment time, and increased machine throughput and productivity.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.