8+ Year Performance of the Gamma Knife Perfexion/Icon Patient Positioning System and Possibilities for Preemptive Fault Detection Using Statistical Process Control. Issue 7 (8th June 2021)

• Record Type: Journal Article
• Authors: Schlesinger, David J.; Sanders, Jason C.; Muller, Donald A.; Nordström, Håkan; Sheehan, Jason P.
• Is Part Of: Medical physics. Volume 48:Issue 7(2021)
• Page Start: 3425
• Page End: 3437
• Publication Date: 2021-06-08
• Subjects: Gamma Knife -- predictive error detection -- statistical process control -- Stereotactic radiosurgery; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1002/mp.14924
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Background: The large fractional doses, steep dose gradients, and small targets found in intracranial radiosurgery require extremely low beam delivery uncertainty. In the case of Gamma Knife radiosurgery (GKRS), this includes minimizing patient positioning system (PPS) positioning uncertainty. Existing QA techniques are recipe based, and feature point in time pass/fail tolerances. However, modern treatment machines, including the Gamma Knife Perfexion/Icon systems, record extensive internal data in treatment logs. These data can be analyzed through statistical process control (SPC) methods which are designed to detect changes in process behavior. The purpose of this study was to characterize the long‐term (8+ year) performance of a Perfexion/Icon unit and use SPC methods to determine if performance changes could be detected at levels lower than existing QA and internal manufacturer performance tolerances. Methods: In‐house software was developed to parse Perfexion/Icon log‐files and store relevant information on shot delivery in a relational database. A last‐in, first‐out (LIFO) queuing algorithm was created to heuristically match messages associated with a given delivered shot. Filtering criteria were developed to filter QA and uncompleted shots. The resulting matched shots were extracted. Achieved versus planned PPS position was determined for each PPS motor as well as for the vector magnitude difference in PPS position. Exponentially weighted moving average (EWMA) control charts were plotted to determine when process behavior changed over time. Results: 53833 shots were delivered over an 8+ year span in the study. The mean vector magnitude PPS difference was 32.7 µm, with 97.5% of all shots within 70.1 µm. Several changes in PPS positioning behavior were observed over time, corresponding with control system faults on several occasions requiring PPS recalibration. EWMA control charts clearly demonstrate that these faults could be identified and possibly predicted as many as 3 years before there were faults beyond control system tolerance. Conclusion: The PPS of Gamma Knife Perfexion/Icon systems has extremely low positioning uncertainties. EWMA control chart method can be utilized to track PPS performance over time and can potentially detect changes in performance that may indicate a component requiring maintenance. This would allow planned service visits to mitigate problems and prevent unplanned downtime.