Dataset Information

A multi-institutional evaluation of machine performance check system on treatment beam output and symmetry using statistical process control.

ABSTRACT: BACKGROUND:The automated and integrated machine performance check (MPC) tool was verified against independent detectors to evaluate its beam uniformity and output detection abilities to consider it suitable for daily quality assurance (QA). METHODS:Measurements were carried out on six linear accelerators (each located at six individual sites) using clinically available photon and electron energies for a period up to 12 months (n = 350). Daily constancy checks on beam symmetry and output were compared against independent devices such as the SNC Daily QA 3, PTW Farmer ionization chamber, and SNC field size QA phantom. MPC uniformity detection of beam symmetry adjustments was also assessed. Sensitivity of symmetry and output measurements were assessed using statistical process control (SPC) methods to derive tolerances for daily machine QA and baseline resets to account for drifts in output readings. I-charts were used to evaluate systematic and nonsystematic trends to improve error detection capabilities based on calculated upper and lower control levels (UCL/LCL) derived using standard deviations from the mean dataset. RESULTS:This study investigated the vendor's method of uniformity detection. Calculated mean uniformity variations were within ± 0.5% of Daily QA 3 vertical symmetry measurements. Mean MPC output variations were within ± 1.5% of Daily QA 3 and ±0.5% of Farmer ionization chamber detected variations. SPC calculated UCL values were a measure of change observed in the output detected for both MPC and Daily QA 3. CONCLUSIONS:Machine performance check was verified as a daily quality assurance tool to check machine output and symmetry while assessing against an independent detector on a weekly basis. MPC output detection can be improved by regular SPC-based trend analysis to measure drifts in the inherent device and control systematic and random variations thereby increasing confidence in its capabilities as a QA device. A 3-monthly MPC calibration assessment was recommended based on SPC capability and acceptability calculations.

SUBMITTER: Binny D

PROVIDER: S-EPMC6414149 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A multi-institutional evaluation of machine performance check system on treatment beam output and symmetry using statistical process control.

Binny Diana D Aland Trent T Archibald-Heeren Ben R BR Trapp Jamie V JV Kairn Tanya T Crowe Scott B SB

Journal of applied clinical medical physics 20190220 3

<h4>Background</h4>The automated and integrated machine performance check (MPC) tool was verified against independent detectors to evaluate its beam uniformity and output detection abilities to consider it suitable for daily quality assurance (QA).<h4>Methods</h4>Measurements were carried out on six linear accelerators (each located at six individual sites) using clinically available photon and electron energies for a period up to 12 months (n = 350). Daily constancy checks on beam symmetry and ...[more]

PMID: 30786139

Similar Datasets

Project description:Tumor markers are used to screen tens of millions of individuals worldwide at annual health check-ups, especially in East Asia. Machine learning (ML)-based algorithms that improve the diagnostic accuracy and clinical utility of these tests can have substantial impact leading to the early diagnosis of cancer. ML-based algorithms, including a cancer screening algorithm and a secondary organ of origin algorithm, were developed and validated using a large real world dataset (RWD) from asymptomatic individuals undergoing routine cancer screening at a Taiwanese medical center between May 2001 and April 2015. External validation was performed using data from the same period from a separate medical center. The data set included tumor marker values, age, and gender from 27,938 individuals, including 342 subsequently confirmed cancer cases. Separate gender-specific cancer screening algorithms were developed. For men, a logistic regression-based algorithm outperformed single-marker and other ML-based algorithms, with a mean area under the receiver operating characteristic curve (AUROC) of 0.7654 in internal and 0.8736 in external cross validation. For women, a random forest-based algorithm attained a mean AUROC of 0.6665 in internal and 0.6938 in external cross validation. The median time to cancer diagnosis (TTD) in men was 451.5, 204.5, and 28 days for the mild, moderate, and high-risk groups, respectively; for women, the median TTD was 229, 132, and 125 days for the mild, moderate, and high-risk groups. A second algorithm was developed to predict the most likely affected organ systems for at-risk individuals. The algorithm yielded 0.8120 sensitivity and 0.6490 specificity for men, and 0.8170 sensitivity and 0.6750 specificity for women. ML-derived algorithms, trained and validated by using a RWD, can significantly improve tumor marker-based screening for multiple types of early stage cancers, suggest the tissue of origin, and provide guidance for patient follow-up.

Project description:Background and purposeA lower proportion of CD8+ tumor infiltrating lymphocytes in mycosis fungoides (MF) patients is associated with worse survival. However, it is not known whether circulating CD4:CD8 ratio is a prognosticator of response to total skin electron beam therapy (TSEBT).Methods and materialsWe identified 126 MF patients treated with TSEBT from 2001 to 20014 at two high-volume academic centers. Circulating CD4:CD8 ratio was obtained within 1 week before TSEBT. TSEBT was delivered with 6-9mEV electrons with low (12 Gy) or conventional (≥12 Gy) doses. Treatment response was assessed with the modified Severity Weighted Assessment Tool (mSWAT). Post-treatment mSWAT decrease of ≥75% was classified as near complete response (CR) while mSWAT decrease of <75% was considered partial response (PR). Receiver operating characteristic analysis determined an optimal CD4:CD8 threshold value to predict TSEBT response in the derivation cohort and was applied to an external validation cohort.Results71.4% and 28.6% of patients achieved CR and PR after TSEBT. Higher CD4:CD8 ratio predicted poorer response: median CD4:CD8 in patients with PR vs. CR was 4.84 vs. 1.97 (p = 0.002). A threshold CD4:CD8 of 4.42 optimally discriminated in the discovery cohort patients with PR vs. XR (sensitivity 90%, specificity 59%, area under curve (AUC) = 0.71; p = 0.002). Within an independent test cohort (n = 32), 73.9% of patients with CD4:CD8 <4.42 achieved CR vs. 33.3% of those with CD4:CD8 ≥4.42 (p = 0.033). Among all patients with CD4:CD8 <4.42 (n = 73), 74% achieved CR with low-dose TSEBT vs. 93% with conventional dose TSEBT (p = 0.02). On multivariable logistic regression, CD4:CD8 remained a significant independent predictor of TSEBT response in all patients (OR = 0.107, 95% CI 0.395-0.290, p < 0.001).ConclusionPeripheral blood CD4:CD8 ratio was a significant independent predictor of TSEBT response of MF patients as validated in an independent cohort at separate academic center. The potential for CD4:CD8 ratio as a biomarker to inform radiation treatment dosing warrants further investigation.

Dataset Information

A multi-institutional evaluation of machine performance check system on treatment beam output and symmetry using statistical process control.

Publications

A multi-institutional evaluation of machine performance check system on treatment beam output and symmetry using statistical process control.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets