Engineering topics

Chan, K

Publications and source records attributed to Chan, K.

4 records

DOE OSTI2016

SU-F-T-489: 4-Years Experience of QA in TomoTherapy MVCT: What Do We Look Out For?

Purpose: To evaluate the QA results of TomoTherapy MVCT from March 2012 to February 2016, and to identify issues that may affect consistency in HU numbers and reconstructed treatment dose in MVCT. Methods: Monthly QA was performed on our TomoHD system. Phantom with rod inserts of various mass densities was imaged in MVCT and compared to baseline to evaluate HU number consistency. To evaluate treatment dose reconstructed by delivered sinogram and MVCT, a treatment plan was designed on a humanoid skull phantom. The phantom was imaged with MVCT and treatment plan was delivered to obtain the sinogram. The dose reconstructed with the Planned Adaptive software was compared to the dose in the original plan. The QA tolerance for HU numbers was ±30 HU, and ±2% for discrepancy between original plan dose and reconstructed dose. Tolerances were referenced to AAPM TG148. Results: Several technical modifications or maintenance activities to the system have been identified which affected QA Results: 1) Upgrade in console system software which added a weekly HU calibration procedure; 2) Linac or MLC replacement leading to change in Accelerator Output Machine (AOM) parameters; 3) Upgrade in planning system algorithm affecting MVCT dose reconstruction. These events caused abrupt changes in QA results especially for the reconstructed dose. In the past 9 months, when no such modifications were done to the system, reconstructed dose was consistent with maximum deviation from baseline less than 0.6%. The HU number deviated less than 5HU. Conclusion: Routine QA is essential for MVCT, especially if the MVCT is used for daily dose reconstruction to monitor delivered dose to patients. Several technical events which may affect consistency of this are software changes, linac or MLC replacement. QA results reflected changes which justify re-calibration or system adjustment. In normal circumstances, the system should be relatively stable and quarterly QA may be sufficient.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-J-231: Comparison of Delineation Variability of Soft Tissue Volume and Position in Head-And-Neck Between Two T1-Weighted Pulse Sequences Using An MR-Simulator with Immobilization

Purpose: There is growing interests in applying MR-simulator(MR-sim) in radiotherapy but MR images subject to hardware, patient and pulse sequence dependent geometric distortion that may potentially influence target definition. This study aimed to evaluate the influence on head-and-neck tissue delineation, in terms of positional and volumetric variability, of two T1-weighted(T1w) MR sequences on a 1.5T MR-sim Methods: Four healthy volunteers were scanned (4 scans for each on different days) using both spin-echo (3DCUBE, TR/TE=500/14ms, TA=183s) and gradient-echo sequences (3DFSPGR, TE/TR=7/4ms, TA=173s) with identical coverage, voxel-size(0.8×0.8×1.0mm3), receiver-bandwidth(62.5kHz/pix) and geometric correction on a 1.5T MR-sim immobilized with personalized thermoplastic cast and head-rest. Under this setting, similar T1w contrast and signal-to-noise ratio were obtained, and factors other than sequence that might bias image distortion and tissue delineation were minimized. VOIs of parotid gland(PGR, PGL), pituitary gland(PIT) and eyeballs(EyeL, EyeR) were carefully drawn, and inter-scan coefficient-of-variation(CV) of VOI centroid position and volume were calculated for each subject. Mean and standard deviation(SD) of the CVs for four subjects were compared between sequences using Wilcoxon ranksum test. Results: The mean positional(<4%) and volumetric(<7%) CVs varied between tissues, majorly dependent on tissue inherent properties like volume, location, mobility and deformability. Smaller mean volumetric CV was found in 3DCUBE, probably due to its less proneness to tissue susceptibility, but only PGL showed significant difference(P<0.05). Positional CVs had no significant differences for all VOIs(P>0.05) between sequences, suggesting volumetric variation might be more sensitive to sequence-dependent delineation difference. Conclusion: Although 3DCUBE is considered less prone to tissue susceptibility-induced artifact and distortion, our preliminary data showed that both sequences had insignificant differences on positional and volumetric CV in most head-and-neck tissues except for PGL. This study is majorly limited in its small sample size. Influences of image contrasts(T1w v.s. T2w) and inter-observer difference have to be further investigated.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

TH-C-9A-01: Lean Tools and Methods

Lean thinking has revolutionized the manufacturing industry. Toyota has pioneered and leveraged this aspect of Lean thinking. Application of Lean thinking and Lean Six Sigma techniques into Healthcare and in particular in Radiation Oncology has its merits and challenges. To improve quality, safety and patient satisfaction with available resources or reducing cost in terms of time, staff and resources is demands of today's healthcare. Radiation oncology treatment involves many processes and steps, identifying and removing the non-value added steps in a process can significantly improve the efficiency. Real projects undertaken in radiation oncology department in cutting down the procedure time for MRI guided brachytherapy to 40% less using lean thinking will be narrated. Simple Lean tools and techniques such as Gemba walk, visual control, daily huddles, standard work, value stream mapping, error-proofing, etc. can be applied with existing resources and how that improved the operation in a Radiation Oncology department's two year experience will be discussed. Lean thinking focuses on identifying and solving the root-cause of a problem by asking “Why” and not “Who” and this requires a culture change of no blame. Role of leadership in building lean culture, employee empowerment and trains and develops lean thinkers will be presented. Why Lean initiatives fail and how to implement lean successfully in your clinic will be discussed. Learning Objectives: Concepts of lean management or lean thinking. Lean tools and techniques applied in Radiation Oncology. Implement no blame culture and focus on system and processes. Leadership role in implementing lean culture. Challenges for Lean thinking in healthcare.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

SU-E-J-117: Verification Method for the Detection Accuracy of Automatic Winston Lutz Test

Purpose: Winston Lutz test (WLT) has been a standard QA procedure performed prior to SRS treatment, to verify the mechanical iso-center setup accuracy upon different Gantry/Couch movements. Several detection algorithms exist,for analyzing the ball-radiation field alignment automatically. However, the accuracy of these algorithms have not been fully addressed. Here, we reveal the possible errors arise from each step in WLT, and verify the software detection accuracy with the Rectilinear Phantom Pointer (RLPP), a tool commonly used for aligning treatment plan coordinate with mechanical iso-center. Methods: WLT was performed with the radio-opaque ball mounted on a MIS and irradiated onto EDR2 films. The films were scanned and processed with an in-house Matlab program for automatic iso-center detection. Tests were also performed to identify the errors arise from setup, film development and scanning process. The radioopaque ball was then mounted onto the RLPP, and offset laterally and longitudinally in 7 known positions ( 0, ±0.2, ±0.5, ±0.8 mm) manually for irradiations. The gantry and couch was set to zero degree for all irradiation. The same scanned images were processed repeatedly to check the repeatability of the software. Results: Miminal discrepancies (mean=0.05mm) were detected with 2 films overlapped and irradiated but developed separately. This reveals the error arise from film processor and scanner alone. Maximum setup errors were found to be around 0.2mm, by analyzing data collected from 10 irradiations over 2 months. For the known shift introduced using the RLPP, the results agree with the manual offset, and fit linearly (R{sup 2}>0.99) when plotted relative to the first ball with zero shift. Conclusion: We systematically reveal the possible errors arise from each step in WLT, and introduce a simple method to verify the detection accuracy of our in-house software using a clinically available tool.

60 APPLIED LIFE SCIENCES↗