Filaria Journal Comparison of IgG4 assays using whole parasite extract and BmR1 recombinant antigen in determining antibody prevalence in brugian filariasis

Rahmah Noordin email@example.com
Institute for Research in Molecular Medicine
Universiti Sains Malaysia
11800PenangMalaysia

Sitti Wahyuni firstname.lastname@example.com
Dept. of Parasitology
Hasanuddin University
Jalan Perintis Kemerdekaan KM 10 Tamalanrea 90245MakassarIndonesia

Department of Parasitology
Leiden University Medical Centre
P.O Box 96002300 RCLeidenThe Netherlands

Andarias Mangali email@example.com
Dept. of Parasitology
Hasanuddin University
Jalan Perintis Kemerdekaan KM 10 Tamalanrea 90245MakassarIndonesia

Lim Boon Huat
Institute for Research in Molecular Medicine
Universiti Sains Malaysia
11800PenangMalaysia

Maria Yazdanbakhsh
Department of Parasitology
Leiden University Medical Centre
P.O Box 96002300 RCLeidenThe Netherlands

Erliyani Sartono
Department of Parasitology
Leiden University Medical Centre
P.O Box 96002300 RCLeidenThe Netherlands

Maria Yazdanbakhsh
-M Yazdanbakhsh@lumc
; Nl
Sartono -E Erliyani
Sartono@lumc
Nl
Filaria Journal Comparison of IgG4 assays using whole parasite extract and BmR1 recombinant antigen in determining antibody prevalence in brugian filariasis
10.1186/1475-2883-3-8BioMed Central Page 1 of 6 (page number not for citation purposes) Research * Corresponding author
Background: Brugia malayi is endemic in several Asian countries with the highest prevalence in Indonesia. Determination of prevalence of lymphatic filariasis by serology has been performed by various investigators using different kinds of antigen (either soluble worm antigen preparations or recombinant antigens). This investigation compared the data obtained from IgG4 assays using two different kinds of antigen in a study on prevalence of antibodies to B. malayi.Methods: Serum samples from a transmigrant population and life long residents previously tested with IgG4 assay using soluble worm antigen (SWA-ELISA), were retested with an IgG4 assay that employs BmR1 recombinant antigen (BmR1 dipstick [Brugia Rapid™]). The results obtained with the two antigens were compared, using Pearson chi-square and McNemar test.Results: There were similarities and differences in the results obtained using the two kinds of antigen (SWA and BmR1). Similarities included the observation that assays using both antigens demonstrated an increasing prevalence of IgG4 antibodies in the transmigrant population with increasing exposure to the infection, and by six years living in the area, antibody prevalence was similar to that of life-long residents. With regards to differences, of significance is the demonstration of similar antibody prevalence in adults and children by BmR1 dipstick whereas by SWA-ELISA the antibody prevalence in adults was higher than in children.Conclusions:Results and conclusions made from investigations of prevalence of anti-filarial IgG4 antibody in a population would be affected by the assay employed in the study.

Background

Lymphatic filariasis affects approximately 120 million people worldwide. Ten percent of these infections are attributed to Brugia malayi and Brugia timori [1]. Thick blood smear examination is the routine parasitological method used for diagnosis and prevalence studies in the Brugia endemic countries of Malaysia and Indonesia [2,3]. This diagnostic method depends on the detection of microfilariae in the peripheral blood, and due to the nocturnal periodicity of microfilaremia in these areas, requires nighttime collection and survey, which is often unpopular with the local population. Furthermore, this method is relatively insensitive [4] and difficult to perform accurately and with consistency in field situations.

Conversely, serological diagnostic methods exhibit better sensitivity than detection of microfilaria by thick blood smear, allow the detection of amicrofilaraemic infections among "endemic normals" and afford daytime fingerprick blood sampling (thus overcoming the inconveniences associated with night blood sampling, thereby encouraging greater cooperation with the local population and facilitate field work) [5].

However, reports on antigen detection test for brugian filariasis have not demonstrated high levels of sensitivity [6,7]. Thus in the absence of a good antigen detection test for Brugia infection, anti-filarial IgG4 assay may be the next best alternative for detection of brugian filariasis [8]. Anti-filarial IgG4 levels have been demonstrated to be elevated in active filarial infection [9][10][11][12][13] and decline posttreatment [14][15][16][17]. Detection of anti-filarial IgG4 antibodies has also been used for epidemiological assessment of filariasis [13,18,19].

Studies assessing antibody prevalence of lymphatic filariasis have employed assays that use either soluble worm antigens or recombinant antigens [12,13,[18][19][20][21]. These antigens may not bind to the same set of anti-filarial antibodies and probably display different cross-reactivities to antibodies against other infections. Thus differences in the antigens employed may be expected to affect the results of antibody prevalence studies. Therefore, the present study aimed to make direct comparison of two antigens i.e. soluble adult worm antigen (SWA) and a recombinant antigen (BmR1), in IgG4 assays on the same set of serum samples.

Previously, an ELISA employing soluble adult worm antigen (SWA-ELISA) had been performed to determine prevalence of anti-filarial IgG4 antibodies on a set of serum samples from Indonesia. These samples were collected from:

1. A transmigrant population that migrated from a nonfilarial endemic region to an area endemic for Brugian filariasis and;

2. Life-long residents of the Brugian endemic area [22].

In the present study a rapid test based on B. malayi recombinant antigen (BmR1 dipstick [Brugia Rapid™]) and detection of IgG4 antibodies were evaluated using the same set of serum samples. The BmR1 dipstick test has previously been shown to be highly specific and sensitive for the detection of brugian filariasis. In a study involving four international laboratories, the BmR1 dipstick was found to be 93% sensitive and 100% specific when tested with 535 serum samples from patients with various infections and healthy controls [8]. In another multicenter validation study, 97% sensitivity and 99% specificity were recorded when the BmR1 dipstick was tested with 753 serum samples [23].

The present study demonstrated that interpretations of some aspects of the seroepidemiology of filarial infection are affected by the kind of antigen employed in the assay. Thus this study, which utilized the same set of serum samples on assays using two kinds of antigens, highlights the role of the kind of antigen employed in the comparison of results of prevalence studies.

Materials and methods

Sera and study population

The details on the sera and study population are as described previously [22]. Briefly, serum samples were collected cross-sectionally from a total of 247 transmigrants and 133 life-long residents (LLR) from Budongbudong, a district of Mamuju Regency in South-Sulawesi, Indonesia, which is endemic for nocturnal-periodic B. malayi [24,25]. The samples from the transmigrant population are valuable as they could help determine the pattern of acquisition of infection with increasing length of exposure to Brugian filariasis. The transmigrant population had traveled to their new homesteads in groups; they came from the same village or region in Bali or Lesser Sunda islands as part of the government-sponsored relocation programme. Each year a new settlement was founded close to the former one (between 10 and 20 kilometers) which accommodated groups of transmigrants from 2-3 different regions together with migrants from Polmas, an over-populated area in South Sulawesi, to promote integration of different tribes. Transmigrants were grouped together according to the year of arrival in the new settlement. A total of 6 transmigrant units, settled between several months and 6 years prior to the survey, were included in the study together with 2 villages of indigenous Sulawesians (LLR), which were situated closely to the transmigrant areas. Those aged ≤ 15 years were classified as children, while adults were classified as those aged 16 years and older. The mean age of children in transmigrant population and LLR population was 10.2 years and that of adults was 32.6 years.

Soluble worm antigen (SWA)

Adult B. malayi worms were purchased from TRS labs, Athens, Georgia, USA. Female worms were freeze dried, ground to powder, dissolved in phosphate buffered saline (PBS), homogenized and slowly stirred overnight at 4°C. The protein concentration was determined by 2,2'-biquinoline-4,4'-dicarboxylic acid disodium salt hydrate (BCA) method before storage at -20°C.

BmR1 dipstick

Statistical Analysis

The results obtained with BmR1 dipstick were compared to the results obtained previously with SWA-ELISA. The similarities and differences in the results were analyzed by comparing proportion of related samples using McNemar test; and comparing proportions of unrelated samples by using Pearson Chi-square (if indicated Fischer exact test was used instead). Figure 1 shows the antibody prevalence to B. malayi, as determined by BmR1 dipstick assay and SWA-ELISA, in the transmigrant population who had resided for various lengths of time in the endemic area and the antibody prevalence in the LLR population. The first detection of IgG4 antibody by the BmR1 dipstick was recorded at 3 years post-exposure, the antibody prevalence increased from 0% in the new arrivals (≤ 1 month and 2-4 months) to 7.4%, 11.1%, 39.1% and 42 % in populations exposed to the infection for 3, 4, 5 and 6 years respectively. Comparison of IgG4 assays using the two kinds of antigen demonstrated similarities in three areas. First, using both SWA-ELISA and BmR1 dipstick, the total prevalence of specific IgG4 in the transmigrant population was found to increase with increasing length of residence in the endemic area. Thus the BmR1 dipstick test confirmed the previously reported finding which demonstrated that the development of anti-filarial IgG4 correlated with the duration of exposure in previously unexposed population [22]. Second, after a period of 5-6 years of being exposed to the filaria infection, anti-filarial IgG4 prevalence by BmR1 dipstick in the transmigrant population (42%) was comparable (p = 0.763) to the antibody prevalence in the LLR population (39.8%); this finding was also previously reported with SWA-ELISA [22]. Thus the results with BmR1 dipstick is in agreement with the previous finding that approximately 5-6 years of exposure is required for the anti-filarial IgG4 in the transmigrant population to reach levels comparable to life-long residents. This is also reported to be the period needed for the detection of microfilaria in the peripheral blood [22]. Third, the overall prevalence of anti-filarial IgG4 was found to be higher in males than in females, by both BmR1 dipstick (p = 0.019) and by SWA-ELISA (p = 0.001).

Results and Discussion

Differences between the two kinds of antigen were also observed ( Figure 1  year 6, p = 0.061; LLR, p = 0.074). Using SWA-ELISA, except for early transmigrant settlers (2-4 months residents), the IgG4 prevalence in the transmigrant population was reported to be significantly higher in adults than in children [22]; however in the LLR population, antibody prevalence in children was not significantly higher than in adults (p = 0.316).

Thus the BmR1 dipstick test demonstrated that the establishment of anti-filarial IgG4 in the children and adults of the transmigrant population occur at comparable rates; this is not in agreement with the previous finding, using SWA-ELISA, that demonstrated IgG4 was established more rapidly in the adult population than in children [22]. The above observations may be due to a mixture of filarial antigens in SWA, some of which may recognize antibodies produced by exposed but not infected individuals, and/or by individuals who have cleared the infection either due to treatment or spontaneous death of worms. Although IgG4 detection significantly increases the specificity of antibody assays in brugian filariasis [12] the specificity of parasite extract-based assays and recombinant antigen-based assays may not be the same. In a recent study in a non-filaria endemic area in Brazil, the presence of Strongyloides antibody responses was found to be associated with higher antifilarial IgG4 responses in assay that uses crude filaria extract as compared to assay that uses B. malayi Bm14 recombinant antigen [26].

The discrepancy between the results of SWA-ELISA and BmR1 dipstick may also be partly due to the greater sensitivity of the former as compared to the latter. Out of 120 (of 381) discrepant results, 111 were positive by SWA-ELISA but negative by BmR1 dipstick. Out of these 111 samples, 38 had low ELISA titers (cut-off value > 4.02 but < 4.5). If the stringency of the cut-off value of the SWA-ELISA is increased from 4.02 to 4.5, then the discrepancy can be considerably reduced to 88 (of 381), with 73 positive by SWA-ELISA but negative by BmR1 dipstick. On the other hand, since BmR1 dipstick test has been reported to be highly specific [8,23], it is unclear why there were eight individuals who were positive by BmR1 dipstick but negative by SWA-ELISA.

Due to the problem of maintaining the antigenicity of the BmR1 antigen when shipped from Malaysia to Netherlands, the dipstick (immunochromatography) assay, which can be transported at room temperature, was employed to test the BmR1 antigen. However the difference in the assay formats is unlikely to be the reason for the lower overall antibody prevalence levels seen with the latter. This is because we have previously shown that ELISA using BmR1 was less sensitive (albeit equally specific) than BmR1 dipstick test [27] in detecting B. malayi infection. Thus in this study if the ELISA format had been used to determine prevalence of IgG4 antibodies to BmR1 instead of the dipstick format, the SWA-ELISA would still be detecting significantly more positives than the BmR1-ELISA.

Differences between the two antigens were also observed in the pattern of IgG4 antibody prevalence in children (Figure 2a &2b). Using BmR1 dipstick, positivity of the test in children was first demonstrated at 3 years (2 of 35, 5.7%), followed by no positive child detected at year 4 (0 of 17), positive antibody prevalence at year 5 (3 of 8; 37.5%) which is significantly greater than at year 3 (p = 0.011). This is followed by a nonsignificant decrease (p = 0.589) in antibody prevalence by year 6 (6 of 22; 27.3%). IgG4 prevalence at year 6 and LLR (30 of 87; 34.5%) was also found to be not significantly different (p = 0.542). After year 4, the IgG4 prevalence in children seemed to achieve a stable level that was similar to the antibody prevalence in the LLR population children. In adults, infection was also initially detected at year 3 and there appeared to be a pattern of increasing antibody prevalence with increasing time of residence (9.1% at 3 years; 16.7% at year 4, 40% at year 5; 53.6 % at year 6). Furthermore, the detection rate at year 6 was not significantly different (p = 0.766) from that seen in the LLR population adults (50%). Thus using the BmR1 dipstick, the increasing total IgG4 prevalence with exposure to brugian filariasis was mostly due to the increasing positive cases in the adult population. It is tempting to speculate that the differences in the pattern observed in children and adults are due to the greater rate of aborted infections and/or spontaneous clearance of the infection in children than in adults. The overall lower worm burden in children, due to physiological differences, may enable higher rate of spontaneous clearance of infections in children than in adults. The difference in physiology between adults and children has been demonstrated by the greater number of natural killer cells, and T-and B-lymphocytes in children as compared to middle aged people [28]. In addition CD4/CD8 T-cells have also been reported to decline from a young age onwards [29,30]. However, since this is a cross-sectional study in which data for each period of residence were obtained from different groups of individuals, this hypothesis could not be confirmed.

Conversely, results of the SWA-ELISA demonstrated initial antibody positivity in children at 2-4 months, followed by increasing antibody prevalence with time of residence. IgG4 prevalence at year 6 was found to be significantly lower than the antibody prevalence in children of the LLR population (p = 0.007). In the adult population, except for the earlier initial detection, a similar pattern was observed with the results of the BmR1 dipstick i.e. increasing rate of antibody prevalence in the transmigrants with exposure; and the IgG4 prevalence at year 6 is not signifi-cantly different (p = 0.430) than the antibody prevalence in the LLR adult population.

Conclusions

This study highlights that assays using both BmR1 and SWA antigens demonstrate an increasing prevalence of specific IgG4 antibodies in the transmigrant population with increasing length of residence in an area endemic for brugian filariasis, and, by six years residency that the antibody prevalence was similar to that observed in the LLR population. This study also documented three main differences in results derived from assays using two antigens i.e.

1. Earlier detection and higher rate of antibody prevalence by SWA-ELISA as compared to the results demonstrated by BmR1 dipstick;

2. Similar rate of acquisition of antibody prevalence in children and adults by BmR1 dipstick; whereas by SWA-ELISA adults were found to become antibody positive faster than in children;

3. By BmR1 dipstick the increasing total prevalence of IgG4 with exposure was primarily due to the adult population, whereas by SWA-ELISA this was attributed to both children and adult populations.

This study demonstrates that some aspects of seroepidemiology of Brugia malayi infection may vary with the kind of antigen used in the assay. Thus comparison of results of different studies must take into account the kind of antigen employed, especially if one study uses native antigen and another uses recombinant antigen. It would be interesting to compare seroepidemiological data of IgG4 assays using two different recombinant antigens on the same population.

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This BmR1 dipstick (Brugia Rapid™) was performed as described previously and according to the instructions of the manufacturer [16, Malaysian Bio Diagnostics Research Sdn. Bhd., Bangi, Selangor, Malaysia]. The BmR1 recombinant antigen was expressed from Bm17DIII DNA sequence, GenBank accession no. AF225296. Southern blot hybridization assays performed on cDNA libraries of L3, L4, mf, adult male and adult female B. malayi demonstrated that the DNA sequence is present in all of the five kinds of libraries (Rahmah et al., unpublished data). Preliminary immunohistological studies suggest that the expressed antigen is found in the epithelial membranes of the adult female uterus (Rahmah et al., unpublished data).

). First, except for year 5 transmigrants (p = 0.146), the percent antibody prevalence recorded in the transmigrant population and in the LLR population by BmR1 dipstick were significantly lower than that detected by the SWA-ELISA i.e. year 3, p = 0.00; year 4, p = 0.00; year 6, p = 0.041; LLR, p = 0.00. Second, using SWA-ELISA, anti-filarial IgG4 was first detected at 2-4 months post-exposure in the population of transmigrants, while using BmR1 dipstick the first detection of IgG4IgG4 antibody prevalence in transmigrant population who resided in B. malayi endemic areas for various lengths of time and in life-long residents (LLR), as determined by BmR1 dip-stick and SWA-ELISA Figure 1 IgG4 antibody prevalence in transmigrant population who resided in B. malayi endemic areas for various lengths of time and in life-long residents (LLR), as determined by BmR1 dipstick and SWA-ELISA. recorded after three years of residence in the endemic area.

Figure 2a
2aand 2b shows the IgG4 antibody prevalence among children and adult populations as determined by BmR1 dipstick and SWA-ELISA respectively. There was no significant difference detected in antibody prevalence between adults and children in the transmigrant population and in the LLR population when BmR1 dipstick was used (year 3, p = 0.594; year 4, p = 0.066; year 5, p = 0.907;

IgG4 antibody prevalence in transmigrant adult and children populations who resided in B. malayi endemic areas for vari-ous lengths of time and in life-long residents (LLR) Figure 2 IgG4 antibody prevalence in transmigrant adult and children populations who resided in B. malayi endemic areas for various lengths of time and in life-long residents (LLR). a (top) IgG4 antibody prevalence as determined by BmR1 dipstick assay. b (bottom) IgG4 antibody prevalence as determined by SWA-ELISA. (Note: Previously published in Parasitology 2001; 122, pg. 636 [Reproduced with permission]).

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AcknowledgementsCompeting interestsRahmah Noordin is the inventor of the commercialized BmR1 dipstick test (Brugia Rapid™)Authors' contributionsRN drafted the paper and supplied the BmR1 dipstick test; SW & AM supplied the sera and edited the paper; LBH performed most of the statistical analysis; ES and MY conceived the study and contributed significantly in editing of the paper: In addition ES performed the BmR1 dipstick test and some statistical analysis. All authors read and approved the final manuscript.
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Initial investigation using statistical process control for quality control of accelerator beam steering

Charles M Able
Carnell J Hampton
Alan H Baydush
Michael T Munley
Initial investigation using statistical process control for quality control of accelerator beam steering
R E S E A R C H Open Access
Background: This study seeks to increase clinical operational efficiency and accelerator beam consistency by retrospectively investigating the application of statistical process control (SPC) to linear accelerator beam steering parameters to determine the utility of such a methodology in detecting changes prior to equipment failure (interlocks actuated). Methods: Steering coil currents (SCC) for the transverse and radial planes are set such that a reproducibly useful photon or electron beam is available. SCC are sampled and stored in the control console computer each day during the morning warm-up. The transverse and radial -positioning and angle SCC for photon beam energies were evaluated using average and range (Xbar-R) process control charts (PCC). The weekly average and range values (subgroup n = 5) for each steering coil were used to develop the PCC. SCC from September 2009 (annual calibration) until two weeks following a beam steering failure in June 2010 were evaluated. PCC limits were calculated using the first twenty subgroups. Appropriate action limits were developed using conventional SPC guidelines. Results: PCC high-alarm action limit was set at 6 standard deviations from the mean. A value exceeding this limit would require beam scanning and evaluation by the physicist and engineer. Two low alarms were used to indicate negative trends. Alarms received following establishment of limits (week 20) are indicative of a non-random cause for deviation (Xbar chart) and/or an uncontrolled process (R chart). Transverse angle SCC for 6 MV and 15 MV indicated a high-alarm 90 and 108 days prior to equipment failure respectively. A downward trend in this parameter continued, with high-alarm, until failure. Transverse position and radial angle SCC for 6 and 15 MV indicated low-alarms starting as early as 124 and 116 days prior to failure, respectively. Conclusion: Radiotherapy clinical efficiency and accelerator beam consistency may be improved by instituting SPC methods to monitor the beam steering process and detect abnormal changes prior to equipment failure.

I. Background

Radiation beam uniformity is one of a number of characteristics required for high energy x-ray beams to be useful in radiation therapy treatment. Verification of radiation beam uniformity in a plane perpendicular to the direction of the beam is particularly important for linear accelerators [1]. Uniformity must be maintained independent of the orientation or direction of the beam. Uniformity can be evaluated using various methods depending on the accelerator manufacturer's specifications. Typically the largest field size is evaluated at a particular depth in water and uniformity is specified over the central 80% of the beam. Figure 1 is an idealized two dimensional plot of radiation beam intensity across a typical accelerator photon beam. Beam uniformity is specified in terms of flatness and symmetry. Acceptable beam flatness and symmetry is produced by the combination of proper beam steering and a carefully designed filter. The accelerated electron beam is steered to a specific location (position) and exit orientation (angle) as it strikes the target ( Figure 2). Beam steering is accomplished using two sets of steering coils. One set is located on the solenoid of the waveguide ( Figure 2) and the second set is located in the electron beam transport section prior to the beam striking the target (not shown in Figure 2 [2].

The accelerator system evaluates beam uniformity internally using the ion chambers located below the flattening filter. The beam current measured in each Figure 1 Idealized radiation beam intensity profile of a typical accelerator produced photon beam. Beam flatness is the maximum plus and minus variation from the mean beam intensity within the central 80% area of full width half maximum intensity and linear symmetry is defined as the maximum variation of points symmetric to the central axis. quadrant is compared and any asymmetry exceeding the specification results in a system interlock. An active system interlock takes the accelerator out of service until the problem is resolved. This interlock system prevents hazards that can cause serious injury to the patient or damage to the equipment. While the interlock system is extremely important, major interlocks disrupt workflow and retard clinical efficiency by forcing machine down time where patients can not be treated.

In this study we seek to characterize the process of medical linear accelerator beam steering and demonstrate, retrospectively, the ability to provide a level of control using the statistical process control (SPC) methodology [3][4][5][6][7][8][9][10][11]. For a generalized system, process performance data varies naturally. The information in the variation of a process is important for an understanding of how the process is performing. SPC is primarily a tool for understanding normal and abnormal variations [3,4]. SPC is used globally in manufacturing and business management to provide an ongoing evaluation of the stability and/or variability of a process [3,4]. Its success rests upon the fact that any process can be mapped by a series of inputs and outputs. Our ability to measure and effectively evaluate the variation of a critical subset of these inputs and outputs can provide an objective basis for timely intervention to maintain a high quality product -the desired beam flatness and symmetry for a medical linear accelerator. The work reported here test the hypothesis that SPC can ensure consistency of beam uniformity and indicate when intervention is required to correct non-uniformity prior to the actuation of a system interlock (thus saving valuable machine down time).

II. Materials and Methods

Monitoring of radiation beam flatness and symmetry is critical to the quality of external beam radiation treatment delivery. It is possible to produce a beam with flatness that is within ± 3% of the central axis dose and has symmetry that does not exceed 2% across the central 80% of the defined field dimensions ( Figure 1) [12]. Various manufacturers define flatness and symmetry differently. One common definition (Varian Medical Systems, Palo Alto, CA) of beam flatness is the maximum plus and minus variation from the mean beam intensity within the central 80% area of full width half maximum intensity. Likewise, linear symmetry is defined as the maximum variation of points symmetric to the central axis [13]. Modern linear accelerators utilize interlock systems to determine if predefined limits have been exceeded and will not allow the system to continue to operate once these limits are reached. The accelerator system used in this study, a 21 EX Varian C-series linac (Varian Medical Systems, Palo Alto, CA), performs a self-diagnostic test and creates Morning Checkout (MC) files during the initial warm-up at the start of each treatment day. Morning warm-up measurements are typically made at a single standard gantry angle and the accelerator feedback system is designed to maintain this setting as the gantry angle varies. The MC files are stored on the console computer but are not used for any specific analysis. Steering coil currents (amperes) for the transverse and radial plane position and angle steering coil currents are stored in the MC files.

The Varian 21EX at one of our regional affiliates experienced down time related to a water leak in the gantry stand. A fine crack in the water circulation tube dripped water on the electrical harness. This leak had persisted for months based on the amount of water found in the bottom of the stand and the fact that our records did not indicate any notable change in the water level. The leak was detected when there was an EXQT (total asymmetry exceeds 2% of symmetrical adjustment) interlock fault that would not clear. This interlock is an indication that the beam symmetry is outside specifications. Following repair, all beams were scanned and adjusted to ensure beam flatness, symmetry, and absolute dose outputs were within operating specifications.

Data from September 2009 (annual medical linear accelerator calibration) until two weeks following the beam steering failure in June 2010 were evaluated. The steering coil current (SCC) data were downloaded and manually extracted to Excel file format. The transverse and radial -positioning and angle SCC for photon beam energies were evaluated using average and range (Xbar-R) process behavior charts (Mintab v16, Minitab, Inc., State College, PA). The evaluation was limited to 6 MV and 15 MV photon beam data only.

A. Process Control Charts (PCC)

To monitor a process, typically two control charts are created: 1) an average chart for subgroup averages, x, and 2) a range chart for subgroup ranges, R. The centerline for the subgroup average chart is x, which is the average of all the subgroup averages. The centerline for the range chart is R, which is the average of all the subgroup ranges. The daily recorded SCC (transverse angle, transverse position, radial angle, and radial position) values were regrouped into nominal weekly values (subgroup of size n = 5 days/week). Values from the first 20 weeks were used to calculate the limits (upper control limit (UCL) and lower control limit (LCL)). The average chart will have an upper threshold (A u ), centerline (A c ) and lower threshold (A l ) [6,7] defined as
A u = x + 6 R d 2 √ n = UCL(1)A c = x = d t t=1....T /T
where T = 20 and d t = mean SCC for treatment week number (t)
A l = x − 6 R d 2 √ n = LCL
where the factor '6' sets the number of standard deviations for the limit margins and n is equal to 5. Similarly, the range chart will have an upper threshold (R u ), centerline (R c ) and lower threshold (R l ) [6,7] defined as
R u = 1 + 6 d 3 d 2 R = UCL (2) R c = R = [( R t ) t=1.....T ]/T where R t = d tmax − d tmin
where T = 20 and d tmax and d tmin = maximum and minimum SCC for treatment week number (t)
R l = 1 − 6 d 3 d 2 R = LCL
The quantities d 2 and d 3 are correction factors that reflect the non-normality of the distribution of range values and also depend on the subgroup size n. The range limits have an asymmetric distribution about the mean range because the range is a positively skewed value and cannot be less than zero. It can be seen from equations (1) and (2) that only the quantities x, R and √n need to be computed to set action thresholds for the process control charts. The implication of exceeding the average or range chart limits on the process is thoroughly presented in SPC literature and an extensive review is beyond the scope of this work [3][4][5][6][7]. In general, data that exceeds the average chart limits suggest a special or non-random cause and/or an uncontrolled process, while exceeding the range chart limits indicates a process that is uncontrolled.

The control limits (UCL and LCL) were set using ± 6 standard deviations from the mean (equations 1 and 2). The chance of a random normal value exceeding the limits is extremely small. Typically limits are set using 3 standard deviations encompassing 99.7% of the normal distribution [4,6,8]. The cost of intervention (machine downtime, physics and engineering man-hours, scanning equipment, etc.) is considerable and a higher threshold limit appeared to be reasonable. Setting the limits at ± 6 standard deviations encompasses 99.9999998% of the normal distribution. The probability of a Type I error (a signal indicating an alarm incorrectly) is reduced and therefore the cost of unwarranted intervention is reduced as well. While there is an increase in the probability of a Type II error (a signal indicating there is no alarm when in fact a problem exist), this risk is balanced and offset by the existence of the interlock system. The data analysis was also performed using the 3 standard deviation control limits to gather a baseline understanding of how changing the limits may impact the investigation of or intervention in the process.

There are a number of standard tests other than the UCL and LCL that can be applied to PCC that assist in detecting a change in the process resulting from special causes or conditions [3,4], a. k number of points in a row, on the same side of the center line b. k number of points in a row, all increasing or decreasing c. k number of points in a row, alternating up and down d. k out of k+1 points,> 2 standard deviations from the center line on the same side e. k out of k+1 points > 1 standard deviation from the center line on the same side f. k number of points in a row within 1 standard deviation from the center line on either side g. k number of points in a row > 1 standard deviation from the center line on either side These can be considered as low-alarm or warning indicators. Low-alarm indicators represent a trend with a specific probability. Determining which low-alarm indicators to apply can be decided by using historical data to create a run chart. A run chart is simply a plot of individual or subgroup data points which allows the investigator to broadly characterize the process data. Reviewing the characteristics of the process data sampled can assist in determining which low alarm indicators may be most useful.

Two low-alarm indicators (a & d) were used in this study: 1) the observation of nine consecutive weekly samples on one side of the mean and 2) the observation of two out of three consecutive weekly samples greater than two standard deviations from the mean but not exceeding the UCL or LCL. For the first low-alarm indicator, the probability of a single value on one side of the mean but not exceeding the limit is 0.5. The probability of nine in a row is (0.5) 9 or~0.002. The chance of this occurring is similar to a single value exceeding 3 standard deviations. For the second low-alarm indicator, the probability of a single value on one side of the mean being less than two standard deviations from the mean is 0.475. Also the probability of a single value on one side of the mean being greater than two standard deviations from the mean is 0.025. The probability for this low-alarm is then (0.475 × 0.025 × 0.025) or 0.0003. This alarm indicates a lack of process control and an acute shift in the mean. It is a powerful warning indicator whose probability of occurrence is smaller than that of a single value exceeding 3 standard deviations.   Figure 7 and show the number of days prior to failure that an alarm was triggered.  Comparison of PCC using control limits of 3 standard deviations versus 6 standard deviations primarily indicates:

III. Results and discussion

a. Low alarms are changed to high alarms requiring intervention. b. There is an increase in the number of Type I errors observed.

The result of the comparison supports the use of 6 standard deviation control limits for monitoring the beam steering process.

Subsequent to the repair, continued monitoring using SPC requires the calculation of new limits based on the newly established operating SCC. The first twenty subgroups would be used to determine new limits and SPC then continues to monitor and evaluate process variation.

These results indicate that evaluation of beam steering currents using SPC would have provided an early indication of deviations in the current values prior to the actuation of the interlock and required unscheduled downtime. Results of the 6 MV transverse angle SCC results show the first low-alarm (5 -two out of three points greater than two standard deviations) on March 15, which was 104 days prior to failure with a highalarm two weeks later. The low-alarm was fifteen weeks prior to actuation of the system interlock. The 15 MV transverse angle SCC show the first low-alarm (5-two out of three points greater than two standard deviations) on March 3, which was 116 days prior to failure, followed by a high-alarm one week later. These alarms confirm the diagnosis that the water leak and resulting damage persisted for a relatively long period of time. Investigation of this alarm would have initiated sixteen weeks prior to the actuation of the system interlock. The radial angle and radial position low-alarms gave the earliest warnings (124 days). In addition, the low-alarm indicators were effective in signaling a change in the established operating SCC of both energies. Overall, the low-alarm indicating two out of three points greater than two standard deviations was most effective in predicting a "permanent" shift in the mean SCC values. Further study of additional low-alarm indicators may establish which alarms are most predictive of a clinically significant change in beam steering.

Typically, standard control limits are calculated using three standard deviations to balance the cost-benefit as well as the Type I and II error probability. The use of six standard deviations for calculating the control chart limits was particularly economical in our study. The physics and engineering effort required to investigate a Type I error is significant. We believe a high threshold for action is desirable compared to current cost of unwarranted intervention or investigation.

The use of digital control systems in medical linear accelerators make them ideal for the incorporation of a SPC subsystem that can use the performance data generated to monitor consistency of operation. Quality of patient treatment delivery can be improved by ensuring consistent operating parameters relative to the baseline values determined at the time of accelerator commissioning [14]. The use of an SPC subsystem is non-invasive and simply samples data already generated by the accelerator. While SPC could be used to alert the physicist and service engineer to a change in operating parameters, any use as an active control system would need to have FDA clearance provided by the manufacturer.

IV. Conclusion

The results of this study suggest that the use of the investigated SPC methodology with a six standard deviation high-alarm action limit would have prompted an investigation of the beam steering process prior to a significant change in beam flatness and symmetry and made detection of the water leak responsible for changes in SCC performance more likely. The impact of machine downtime on clinical operational efficiency would be minimized by the scheduling of planned maintenance to be performed without interruption of the clinic treatment schedule.

System interlocks provide an important safety function to safeguard the equipment from catastrophic failure and prevent unsafe clinical use when operating specifications are exceeded. SPC could be used to detect nonstandard functioning of beam flatness and symmetry prior to these measurements creating beam interrupts and altering treatment times and schedules. This early warning alert could ultimately improve treatment delivery and clinical operational efficiency. The use of SPC to evaluate the operating parameters of critical accelerator systems has the potential to improve the quality of accelerator maintenance, treatment delivery and ultimately patient safety. SPC could be expanded to help provide a "smart-accelerator" system that communicates non-standard functioning of systems directly to the local service representative and physicist if automated.

Authors' contributions CMA designed the study, performed the data analysis and is the lead editor of the manuscript. CJH assisted in study design, data analysis as well as insight into the application of statistical process control methods. AHB performed the data capture and processing prior to the application of statistical process control and editing of the manuscript. MTM provided institutional support and played a pivotal role in manuscript editing for intellectual content. All the authors have read and approved the final manuscript.

Figure 2
2Schematic diagram of a typical medical linear accelerator. (reproduced from Van Dyk, J. The modern technology of radiation oncology Madison, WI, USA: Medical Physics Publishing; 1999. p1073.)

Figure 3 5 Figure 3
353and 4 are the SPC results of the transverse angle SCC for the 6 MV and 15 MV beams, respectively. The high-alarm action limit is indicated by a 1 below a red data point. The low-alarms are indicated by a 2 [nine weekly samples on one side of the mean] or a Process control charts (average and range charts) for 6 MV photon beam transverse angle steering coil current. Note: Red data points indicate an alarm has been signaled. Valid alarms occur after the first 20 data points which establish the calculated control limits.

Figure 4
4Process control charts (average and range charts) for 15 MV photon beam transverse angle steering coil current. Note: Red data points indicate an alarm has been signaled. Valid alarms occur after the first 20 data points which establish the calculated control limits. out of three consecutive weekly samples greater than two standard deviations from the mean] below a red data point respectively. SPC analysis of transverse angle SCC for 6 MV and 15 MV indicated a high-alarm on April 14 th and March 13 th -90 and 108 days prior to failure, respectively. In each case, a downward trend in this parameter continued, with high-alarm, until failure. Transverse position(Figure 5 and 6) and radial angle SCC for both energies indicated a low-alarm starting in March or April. Transverse position SCC results show sensitivity similar to the transverse angle results. Analysis of the SCC in the radial plane did not indicate the same sensitivity as early as the SCC in the transverse plane. All the results are summarized in

Figure 5
5Process control charts (average and range charts) for 6 MV photon beam transverse position steering coil current. Note: Red data points indicate an alarm has been signaled. Valid alarms occur after the first 20 data points which establish the calculated control limits.

Figure 6 Figure 7
67Process control charts (average and range charts) for 15 MV photon beam transverse position steering coil current. Note: Red data points indicate an alarm has been signaled. Valid alarms occur after the first 20 data points which establish the calculated control limits. Process control chart warning results. Bars indicate the number of days prior to failure that an action level threshold was first triggered for each of the monitored steering coil parameters. A -High Alarm triggered indicating parameters exceeding ± 6 standard deviations of the mean weekly sample value. B -Low alarm indicating the observation of nine consecutive weekly samples on one side of the mean. C -Low alarm indicating the observation of two out of three consecutive weekly samples greater than two standard deviations from the mean but not exceeding the high alarm limit.
Able et al. Radiation Oncology 2011, 6:180 http://www.ro-journal.com/content/6/1/180
Able et al. Radiation Oncology 2011, 6:180 http://www.ro-journal.com/content/6/1/180 Page 4 of 9
Competing interestsThis project was partially supported by a grant from Varian Medical Systems, Inc.
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Initial investigation using statistical process control for quality control of accelerator beam steering. Able, Radiation Oncology. 6180Cite this article asCite this article as: Able et al.: Initial investigation using statistical process control for quality control of accelerator beam steering. Radiation Oncology 2011 6:180.