DNA methylation and the repair of DNA double-strand breaks (DSBs) are important processes for maintaining genomic integrity. Although DSBs can be produced by numerous agents, they also occur spontaneously as endogenous DSBs (EDSBs). In this study, we evaluated the methylation status of EDSBs to determine if there is a connection between DNA methylation and EDSBs. We utilized interspersed repetitive sequence polymerase chain reaction (PCR), ligation-mediated PCR and combined bisulfite restriction analysis to examine the extent of EDSBs and methylation at long interspersed nuclear element-1 (LINE-1) sequences nearby EDSBs. We tested normal white blood cells and several cell lines derived from epithelial cancers and leukemias. Significant levels of EDSBs were detectable in all cell types. EDSBs were also found in both replicating and non-replicating cells. We found that EDSBs contain higher levels of methylation than the cellular genome. This hypermethylation is replication independent and the methylation was present in the genome at the location prior to the DNA DSB. The differences in methylation levels between EDSBs and the rest of the genome suggests that EDSBs are differentially processed, by production, end-modification, or repair, depending on the DNA methylation status.
This work applied statistical process control to establish the control limits of the % gamma pass of patient-specific intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) quality assurance (QA), and to evaluate the efficiency of the QA process by using the process capability index (Cpml). A total of 278 IMRT QA plans in nasopharyngeal carcinoma were measured with MapCHECK, while 159 VMAT QA plans were undertaken with ArcCHECK. Six megavolts with nine fields were used for the IMRT plan and 2.5 arcs were used to generate the VMAT plans. The gamma (3%/3 mm) criteria were used to evaluate the QA plans. The % gamma passes were plotted on a control chart. The first 50 data points were employed to calculate the control limits. The Cpml was calculated to evaluate the capability of the IMRT/VMAT QA process. The results showed higher systematic errors in IMRT QA than VMAT QA due to the more complicated setup used in IMRT QA. The variation of random errors was also larger in IMRT QA than VMAT QA because the VMAT plan has more continuity of dose distribution. The average % gamma pass was 93.7% ± 3.7% for IMRT and 96.7% ± 2.2% for VMAT. The Cpml value of IMRT QA was 1.60 and VMAT QA was 1.99, which implied that the VMAT QA process was more accurate than the IMRT QA process. Our lower control limit for % gamma pass of IMRT is 85.0%, while the limit for VMAT is 90%. Both the IMRT and VMAT QA processes are good quality because Cpml values are higher than 1.0.
The result from any assurance measurement needs to be checked against some limits for acceptability. There are two types of limits; those that define clinical acceptability (action limits) and those that are meant to serve as a warning that the measurement is close to the action limits (tolerance limits). Currently, there is no standard procedure to set these limits. In this work, we propose an operational procedure to set tolerance limits and action limits. The approach to establish the limits is based on techniques of quality engineering using control charts and a process capability index. The method is different for tolerance limits and action limits with action limits being categorized into those that are specified and unspecified. The procedure is to first ensure process control using the I-MR control charts. Then, the tolerance limits are set equal to the control chart limits on the I chart. Action limits are determined using the Cpm process capability index with the requirements that the process must be in-control. The limits from the proposed procedure are compared to an existing or conventional method. Four examples are investigated: two of volumetric modulated arc therapy (VMAT) point dose quality assurance (QA) and two of routine linear accelerator output QA. The tolerance limits range from about 6% larger to 9% smaller than conventional action limits for VMAT QA cases. For the linac output QA, tolerance limits are about 60% smaller than conventional action limits. The operational procedure describe in this work is based on established quality management tools and will provide a systematic guide to set up tolerance and action limits for different equipment and processes.
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