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Comparison of bone lead measured via portable x-ray fluorescence across and within bones
Environmental Research 172 (2019) 273–278
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Comparison of bone lead measured via portable x-ray fluorescence across and within bones
T
⁎
Aaron J. Specht , Aisha S. Dickerson, Marc G. Weisskopf Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States
A R T I C LE I N FO
A B S T R A C T
Keywords: Heavy metal toxicity Bone Chronic disease Cumulative exposure Biomarkers
Background: Bone lead measured via x-ray fluorescence (XRF) has been used for decades in health studies. A portable XRF device for bone lead measurement is gaining in popularity for its ease of use and shorter measurement times. Previous XRF devices have measured different bone types in order to sample both cortical and trabecular bone, in which lead has different half residence times. Objective: The portable XRF uses lower energy to measure bone lead than previous devices, and, thus, only measures the surface of the bone. Because all bones have a cortical shell, we hypothesized that portable XRF bone lead measurements would be similar regardless of the bone measured. Methods: This study tested differences in portable XRF bone lead measurements across different cortical and trabecular bones in measurements made on 31 cadavers. We also compared tissue thicknesses overlying different bones, which can impact portable XRF measurements. Results: The correlation coefficients found between bones were higher (rho ~0.4) than previous K-shell XRF bone measurements in cortical and trabecular over the same range of values (rho~0.2). The concentrations were shown to vary non-significantly across different bones within individuals.
1. Introduction
are differences between the two approaches. Importantly, the energies that each technique uses are different. Portable XRF uses the L-shell of Pb for measurement at 10.5 and 12.6 keV, much lower energy than the K-shell of Pb at 75, 73, and 84 keV. The lower energy of the portable XRF measurement only allows sampling at a depth of 0.2 mm into the bone (Hubbell and Seltzer, 1982; Todd, 2002b). The low energy also makes L-XRF much more dependent on skin thickness, which, as shown in earlier experimental devices used for in vivo bone Pb measurements, can be difficult to overcome (Todd, 2002b, 2002a; Todd et al., 2002; Rosen et al., 1991). More recent experiments with L-XRF in the form of the portable XRF used in this study, have shown more promise for overcoming some of these critical barriers (Specht et al., 2016, 2018, 2014). In contrast, the higher energy of the KXRF penetrates much deeper into the bone averaging over a large portion of the cross section. Thus, the part of the bone sampled to estimate bone Pb concentration by each approach is different. The different portion of bone sampled by the portable XRF compared with the KXRF may have implications for interpreting the measurement results. Bone Pb analyses have typically measured two different types of bone: more spongy trabecular bone and the harder cortical bone, in which Pb has a half-life on the order of several years vs decades, respectively (Rabinowitz, 1998; Hu et al., 1989; Erkkila et al.,
Bone lead (Pb) has been used for years to assess cumulative Pb exposure levels, which have typically been found to be more strongly associated with many chronic health conditions than more commonly used blood Pb concentrations (Barbosa et al., 2005). The established approach for in vivo bone Pb measurements is K-shell x-ray fluorescence (KXRF) (Chettle et al., 1991; Hu et al., 1989). This technology, however, has disadvantages for use in epidemiological studies mainly related to the need for a radioisotope, resultant facilities approval requirements, lack of portability, and long measurement times. Portable x-ray fluorescence (XRF) is another technology for bone Pb analyses that has become more feasible given advances in detector and other technologies. Advantages of the portable XRF include its portability, a measurement time ten times shorter than KXRF, simpler licensing requirements because it uses an x-ray tube, and the possibility of measuring metals in bone other than Pb. The use of a portable XRF would allow for a much wider undertaking of research on cumulative Pb exposures and so could be tremendously beneficial to clinical and occupational surveillance programs. Work to validate this device in previous studies has proven fairly successful (Specht et al., 2014, 2016). Although both KXRF and portable XRF can measure bone Pb, there ⁎
Correspondence to: 655 Huntington Ave Building 1 Room 1402, Boston, MA 02115, United States. E-mail address: [email protected] (A.J. Specht).
https://doi.org/10.1016/j.envres.2019.02.031 Received 20 November 2018; Received in revised form 19 February 2019; Accepted 20 February 2019 Available online 21 February 2019 0013-9351/ © 2019 Elsevier Inc. All rights reserved.
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1992; Eswaran et al., 2006). Often KXRF measurements are done on both the patella (mostly trabecular) and tibia (mostly cortical) bones (Hu et al., 1989; Erkkila et al., 1992). Trabecular and cortical bones have different mechanisms of uptake for Pb and other metals, which influence their respective use in exposure assessment studies (Hu et al., 1996; Nilsson et al., 1991; O'Flaherty, 1998; Pemmer et al., 2013; Nie, 2005; Leggett, 1993). However, all bones are encased in a cortical shell (Gray et al., 2005). For example, the predominantly trabecular patella bone thickness averages about 2.5 cm, but with a cortical shell that ranges in thickness from 0.2 to 0.6 mm (Gray et al., 2005). Thus, it is likely that the vast majority of bone sampled when measuring any bone with the portable XRF is in fact cortical bone given the penetration depth of the portable XRF energy. Little is known about how using the bone surface as a biomarker may differ epidemiologically from traditional KXRF measurements. The bone surface has been shown to incorporate and turnover bone at a different rate (Leggett, 1993; O'Flaherty, 1998). Characterizations of the structural differences have shown parallel differences in quantification of surface sections in the bone (Pemmer et al., 2013; Bellis et al., 2009; Zhang et al., 2005; Zoeger et al., 2005). However, little is known on the potential of surface bone for impacting health and how the shift from KXRF to portable XRF may influence future epidemiological health studies and exposure comparability to previous studies of bone Pb. In this study, we compared bone Pb concentrations across different bones and within bones in cadavers measured using the portable XRF. We hypothesized that measurement of any bone type with the portable XRF should give readings reflective of cortical bone measurements. We compared correlations of portable XRF measures between different bone sites to correlations of standard KXRF measures in previous studies to identify how the change of biomarker may influence future studies. We also took several measurements along the tibial shaft and skull to determine the variability of measurements along a single bone type.
Fig. 1. Lead beta peak spectrum from an individual with 3 mm of soft tissue thickness.
with the portable XRF reported here are equivalent to µg/g of dry weight bone, which is 1.5 times lower than typical KXRF measurements, which are µg/g of bone mineral. All references to previous KXRF measurements have been labeled as µg/g bone mineral, whereas all other units of µg/g are ug of Pb/g of dry weight bone, unless otherwise noted. Previous works identified the detection limit for the portable XRF used in this study to range between 2 and 11 µg/g dry weight bone for tissue thicknesses ranging from 1 to 5 mm respectively (Specht et al., 2014, 2018). The raw spectra from the bone Pb measurements were fitted for the Pb beta signal as done in our previous works (Specht et al., 2019, 2016, 2014). Briefly, the beta peak from Pb (12.6 keV) was fitted using a Gaussian function combined with an exponential function to fit the background counts using Matlab (Release 2014 A). We used the net counts from Pb and a function of the tissue thickness effect on net counts of Pb derived from our calibration standards to identify the concentration of bone Pb from each individual. A typical lead peak for our spectra is shown in Fig. 1. Measurements were made at the tibia, patella, skull, ankle, and index finger bones. Due to rigor mortis in cadavers, we deviated from typical measurement positioning. Soft tissue was intact on each cadaver, and we believe these measurements should be identical to those expected from typical in vivo measurements. Patella measurements were made with the leg straight, which may have increased the soft tissue thickness overlying the bone and resultant uncertainty compared with patella measurements done on a flexed leg. Finger bone measurements were made at the middle phalanx of the index finger with the finger slightly bent, depending on the cadaver and how they were positioned before rigor mortis. In eight of the cadavers we made multiple measurements of the tibia and skull. Measurements from proximal to distal tibia were made at four equal intervals down the tibia shaft with one extra measurement at mid-tibia level. The skull was measured in 3 locations, one measurement at each temporal plate and one measurement of the frontal plate. The mid-tibia and frontal plate skull measurements were used for the comparisons between bone sites among all 31 cadavers.
2. Materials and methods 2.1. Cadavers We used 31 cadavers in this study from the Anatomical Gift Program of Harvard Medical School. The age of death ranged from 52 to 100 years with a median (interquartile range) of 86 (13) years. There were 15 females and 16 males who all died of natural diseases. The anatomical gift program partnered with Brigham and Women's Hospital and Partners Health Care and received ethical approval from the human subjects research internal review board (IRB) at Brigham and Women's Hospital. Harvard T.H. Chan School of Public Health ceded IRB review to Brigham and Women's Hospital. 2.2. Portable XRF We used a commercially available portable XRF (Niton XL3t GOLDD +, Thermo Fisher Scientific Inc., Billerica, MA) with customizable x-ray tube voltage, current, and filtration to perform this study. We used an xray tube voltage of 50 keV and current of 40 uA with a filter of silver and iron, and 3-min real-time measurements for this study. These are the parameters used previously with a similar device in studies with living humans and lab samples (Specht et al., 2016, 2017, 2014). The device was calibrated for bone Pb in previous work using Pb doped plaster-of-Paris (PP) phantoms at 0, 5, 10, 15, 30, 50, and 100 µg/g PP and soft tissue phantoms made of Lucite (Specht et al., 2014). Although calibration is done on phantoms in unit of µg/g PP, measurements made with the portable XRF have units of µg/g dry bone as shown in our previous work comparing bone measurements using inductively coupled plasma mass spectrometry, KXRF, and portable XRF bone Pb measurements (Specht et al., 2019, 2018). All Pb measurements made
2.3. Statistical analysis The uncertainty values for the portable XRF measurements were determined as in previous studies using counting statistics in the fitted area for Pb (Specht et al., 2017). The uncertainty (σ ) of each measurement was calculated using the following equation,
C× σ=
BKG + Gross t
Net
(1)
where c is the concentration, BKG is the background counts as estimated by our Matlab fitting, Gross is gross counts over the area of the fitted peak, t is measurement time, and Net is the net Pb counts from the 274
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Gaussian function from our Matlab spectral fitting. This gives an uncertainty estimate equivalent to one standard deviation (σ) change from the calculated concentration. This uncertainty value, and the device limit of detection, is different from standard counting error values, which generally underestimate the actual error. Our value is a more conservative estimate to account for the added uncertainty of our tissue thickness calculation, which will have the greatest impact on the associated uncertainty and limit of detection of the device, which was demonstrated in our previous work (Specht et al., 2014). We weighted the analysis on the uncertainty values to utilize the information gained from our Matlab analysis fitting for each measurement, even values lower than the limit of detection, which would normally result in censored data. Hence, negative values are left as such because they represent the point estimate of concentration with uncertainty in the measurement. If an individual measurement is close to zero. To reduce the likelihood of bias from artificial variance reduction, we include the negative point estimate of the measurements in our analysis instead of assigning other values or censoring any data. This has been shown to the most appropriate analysis procedure for in vivo bone Pb analyses in previous studies over other potential methods (Kim et al., 1995). For the measurements of different bone sites, we wanted to determine whether each subject's bone measurements differed based on the location on the bone measured. We performed a repeated-measures multivariate ANOVA to assess the variation in measured Pb concentration across sites on a single bone and across different bones in the body. Each ANOVA analysis was adjusted for subject variation, and the assumption of sphericity was met in each case. The ANOVA had four degrees of freedom for the main analysis as we had 5 measures of bone lead per cadaver. A pairwise correlation matrix was used to show the relationship between bone types of each individual. The correlations were weighted based on the uncertainty of the bone with the greatest average uncertainty value. For example, the correlation between tibia and patella was weighted based on the squared inverse of the uncertainty in the patella lead measurements, since the uncertainty in patella (13.7 μg/g) was greater than tibia (6.3 μg/g) (Table 1). Since the goal of the analysis was to identify differences between bones measured with portable XRF, we ran a simulation to assess our power to detect differences given the uncertainties in these measures. We simulated 1000 data sets for 31 cadavers assuming they had portable XRF Pb measurements from five bones each. Two of the five bones were simulated as trabecular (slightly higher bone Pb) and the other three bones were simulated as cortical (slightly lower bone Pb) on an individual basis. This simulated dataset was created based on the distributions found in our measured cadavers using the portable XRF. This should reflect the variance observed from portable XRF measurements from bone lead, which takes into account both the variance of the bone lead between individuals and the uncertainty in the measurements from the portable XRF itself. We found that we would have 86.7% power to detect an average individual difference of 5 μg/g (or a 0.8 standard deviation difference) between bones using our repeated-measures ANOVA adjusted for within and between subject variance. This is
equivalent to less than half of the within person difference seen between tibia, mostly cortical, and patella, mostly trabecular, bone measures in the Normative Aging Study, which was 11.6 μg/g (Weisskopf et al., 2007). All Pb measurements from the cadavers were normally distributed in our samples and checked at each analysis step. The aforementioned statistical analysis was done using R statistical software, version 3.0.3 (Foundation for Statistical Computing, Vienna, Austria). Additionally, since many previous environmental epidemiologic studies use tibia Pb measurements when assessing associations between Pb exposures and health outcomes, tibia measurements were further compared to measurements of other bones using generalized estimating equations (GEE) with repeated measures to verify our results using ANOVA. The GEE used tibia as the reference group, as tibia was shown to be > 90% cortical bone. Using this comparison, we would compare other bones with high percentage of trabecular bone to tibia with a high percentage of cortical bone. The GEE was conducted using an identity link function and an unstructured covariance matrix for within and between subject measurements. Then the GEE model was weighted based on the uncertainty of the bone lead measurements. This portion of the statistical analysis was done using SAS Version 9.4 statistical software (SAS Institute Inc., Cary, NC, USA).
3. Results 3.1. Bone Pb results from different bones In Table 1, we show a summary of the results for the measurements, uncertainties, and tissue thicknesses of mid-tibia, patella, frontal plate, ankle, and finger bones for each cadaver. Results from repeated measures ANOVA found non-significant differences between each bone measurement (mid-tibia, patella, frontal plate of the skull, ankle, and finger) with a p-value of 0.12 and F-ratio of 1.85. There was no significant relationship between age and bone Pb in our population. This analysis was adjusted for within and between subject variances. The average detection limit across all measurements was 12.6 μg/g, which is equivalent to previous studies using in vivo KXRF measurements. We also did a sensitivity analysis excluding measurements with tissue thicknesses greater than 5 mm, which has been shown to substantially increase the detection limit and uncertainty. Results for this analysis still showed non-significant differences between bones (p-value=0.40) with F-ratio of 1.03. We show the correlation matrix comparing the pairwise correlations between bones of individuals in Table 2. Results from the GEEs are presented in Table 3. In the unadjusted models, patella Pb estimates were lower than tibia measures (β = -3.00; 95% CI: -13.37, 7.37). The expected difference of patella measures compared to tibia measures became almost zero after adjustment and weighting for uncertainty (β = 0.86; 95% CI: -3.92, 5.63). Mean ankle measures were 8.57 µg/g higher with marginal significance (p = 0.05), though the mean decreased to 0.45 µg/g and significance diminished (p = 0.89) after weighting for uncertainty. Additionally, finger, and skull measures were slightly higher than tibia measures in crude analyses, but essentially no different in weighted models. All differences in measurements between bones were far from statistically significant.
Table 1 Summary of bone Pb (ug/g) measurements of the different bones and the uncertainties (sigma) associated with measurement for each bone.
Tibia Patella Ankle Finger Skull
Bone Pb (µg/g)
Uncertainty (µg/g)
Tissue Thickness (mm)
Mean
Standard deviation
Mean
Standard deviation
Mean
18.7 28.0 23.1 24.4 22.2
6.3 13.7 10.8 8.7 5.7
5.0 7.1 6.8 5.0 2.6
3.6 5.8 5.0 4.5 3.6
7.7 4.7 16.3 14.1 12.2
Table 2 Pairwise correlations between measurements at different bones weighted by the uncertainty in the bone lead measurement.
Standard deviation
Tibia Patella Skull Ankle Finger
1.5 1.8 1.4 0.9 0.9
275
Tibia
Patella
Skull
Ankle
Finger
1.00
0.50 1.00
0.38 0.46 1.00
0.55 0.33 0.06 1.00
0.46 0.57 0.69 0.32 1.00
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Table 3 Comparison of different bone Pb measurements to tibia measures. Weighteda
Unadjusted
Tibia Patella Ankle Finger Skull a
Table 5 Measurements of bone Pb (ug/g) at 3 sites on the skull. Skull Bone Pb (ug/g)
Estimate (95% CI)
p-value
Estimate (95% CI)
p-value
Measurement Site
Reference − 3.00 (−13.37, 7.37) 8.57 (−0.15, 17.29) 6.44 (−1.81, 14.69) 4.50 (−2.84, 11.84)
– 0.57 0.05 0.13 0.23
Reference 0.86 (−3.92, 5.63) 0.45 (−2.79, 3.69) − 2.20 (−6.41, 2.02) − 0.45 (−2.59, 1.68)
– 0.86 0.89 0.60 0.83
Right Temporal Plate Frontal Plate Left Temporal Plate Mean S.D. Uncertainty (ug/g) Mean S.D.
Model weighted for uncertainty.
Table 4 Measurements of bone Pb (ug/g) at five sites along the tibia. Ratio of Frontal Plate to Medial Plates
Proximal Mid Distal Mean S.D. Mean S.D.
Subject ID 4667 4664 4668 8 2 9 13 − 10 3 19 −4 −5 17 8 7 18 −7 −6 15 −2 2 4.4 7.1 7.0 Uncertainty (ug/g) 1.9 4.0 5.1 0.1 1.1 1.5
4680 23 31 25 28 29 27 3.2 3.9 1.1
4678 17 14 32 19 10 19 8.1 2.3 0.8
4675 14 17 22 11 8 14 5.1 9.1 3.8
ID 4664 − 13 −7 9 −4 11.3
4668 −4 8 −9 −2 9.0
4680 27 22 31 26 4.7
4678 13 29 25 23 8.5
4675 22 26 13 20 7.0
4686 3 −1 14 5 7.6
4687 15 16 −6 8 12.0
4.0 0.8
5.8 1.7
3.7 1.3
2.7 0.4
4.3 0.9
4.2 1.2
3.6 1.0
7.6 0.9
8.0
Tibia Bone Pb (ug/g) Measurement Site
Subject 4667 15 25 17 19 5.1
4686 11 9 17 13 9 12 3.2 2.5 0.6
4687 10 15 14 7 12 12 3.2 3.4 1.3
7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0 -1.0
0
-2.0
3.2. Bone Pb variability along tibia
1
2
3
4
Skull Measurement Location
Fig. 3. Relative difference in skull bone Pb measurement from the right temporal plate to the left temporal plate as a ratio with the frontal plate.
We performed measurements along the tibia at 5 intervals (4 equal intervals down the tibia and a measurement at mid-tibia). The results are shown in Table 4 and Fig. 2. We performed a repeated measures ANOVA using this data and found non-significant differences (pvalue=0.27). However, this was only on a subset of cadavers, so we expect reduced power.
4. Discussion The main results of the study indicate that the portable XRF is primarily measuring cortical bone, regardless of the bone, and there are essentially no differences between measurements of different bones in analyses adjusted for uncertainty. This indicates that results from Lshell measurements at any bone should be comparable to cortical bone measurements. In addition to this, we show the tissue thickness of different possible locations for XRF measurements, which suggests that tibia and skull have the least tissue thickness overlying the bone. This suggests that these bones are preferable for in vivo measurements in order to minimize measurement uncertainties and corresponding device detection limits. Finally, we show no trend in bone measurement variation along the skull or tibia bone, similar to results of previous studies with atomic absorption spectrometry (AAS) measurements (Todd et al., 2001, 2002). The measurements of different bones should be measuring solely cortical bone when using the portable XRF. The low penetration depth only allows for complete sampling of the outer cortical shell of each bone measured (Gray et al., 2005). Using values from the National Institute of Standards and Technology (NIST) we can calculate the average penetration depth of photons in cortical bone using the attenuation properties for 10 keV (bone density of 1.85 g/cm3), which is the energy of the Pb alpha characteristic x-ray (Hubbell and Seltzer, 1982). The Pb characteristic energy would be the most conservative estimate, as the signal arising in the bone would need to be collected by the detector outside the bone. Using the attenuation values from NIST at 10 keV, we calculate a penetration depth of about 0.2 mm, which would reduce the signal intensity to 1/e (Hubbell and Seltzer, 1982). Including soft tissue in this calculation still gives a value of roughly 0.2 mm, as the attenuation of soft tissue is much lower than bone. This would make it impossible to measure trabecular bones with a cortical shell greater than 0.5 mm. Thus, measurements of bone Pb using KXRF and portable XRF would likely be less comparable when not measuring
3.3. Bone Pb variability in skull With our 3 measurements of the skull at the right temporal plate, frontal plate, and left temporal plate, we did an analysis similar to that for tibia bone. Table 5 shows the measurements for each cadaver at each bone site. Fig. 3 shows the variation over location. We performed a repeated measures ANOVA using this data and found non-significant differences (p-value=0.54). Again, this was only for a subset of cadavers, so we expected reduced power in the ANOVA analysis.
Fig. 2. Relative difference in tibia bone Pb measurement along the proximal (-2) to distal (+2) axis of the tibia bone as a ratio with the mid-tibia measurement. 276
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the uncertainties seem high for a quantification of Pb, these values are typical of in vivo measurements. Traditional in vivo KXRF measurements, such as those used for over a decade in the Normative Aging Study, had an average uncertainty for tibia and patella measurements of 5.0 and 6.0 μg/g bone mineral (4.0 and 5.0 μg/g dry bone) respectively, which is similar to the average tibia Pb measurement in our study of 6.3 μg/g (5.0 μg/g with the same cut-off parameters as the NAS) (Weisskopf et al., 2009, 2004; Ji et al., 2015). The portable XRF measurements made in our study may have a similar uncertainty of the traditional KXRF measurements, but the uncertainty itself is more variable, because of the aforementioned dependence on soft tissue thickness (Specht et al., 2014). The portable XRF as a tool should primarily be used as a device in epidemiological studies or in surveillance of highly exposed individuals, as the associated uncertainty makes environmental levels of exposure difficult to discern on an individual basis. Furthermore, with the nature of this study, we utilized statistical corrections for uncertainties in our methods, which should be used in the analysis of portable XRF bone Pb measures in the future to prevent bias from more variable data (McNeill et al., 2017). Procedures in previous health studies utilized a cut-off value at an uncertainty value of 10 or 15 μg/g bone mineral for traditional KXRF bone Pb measurements to ensure the most reliable data (Weisskopf et al., 2009, 2004; Ji et al., 2015), which also decreased the average uncertainty value in those studies. Unlike with traditional KXRF measurements, the portable XRF measurement uncertainties depend on overlying skin, which inturn can be related to BMI or a number of health related outcomes. Thus, for measures of portable XRF in health studies, it is best to use a statistical method of correction rather than omitting these values, which may bias results. Regardless, the results using the portable XRF in general population are likely to have a higher uncertainty than typical KXRF measurements, but the advantages presented by the portable XRF in terms of measurement time and portability more than outweigh a slight increase in uncertainty. Finally, this should not impact the observed results of our main analysis identifying differences between bone sites, as the data set simulated for the power calculation reflected the additional uncertainty observed using portable XRF bone Pb measurements, so the analysis was sufficiently powered, despite the uncertainties observed in our data. Finally, we used measurements to determine the variability of bone Pb along the tibia and over the skull. We found slight non-significant variations in both locations, which is unsurprising considering we had limited power in this analysis and with previous studies indicating only slight differences along bones. The trend identified by Todd et al., which used AAS measurements of surface and core tibia, showed a decrease in bone lead towards the ends of the tibia, but this trend was too small to detect in our study without a much larger sample size (Todd et al., 2001). Previous studies using L-XRF to identify these trends on cadavers were similarly limited by power and uncertainty (Todd et al., 2002). In addition, since our data was on intact cadavers, it is likely that our measurements were further from the true ends of the tibial shaft; thus, this difference was less exaggerated in our results. Our study results, along with the known inherent uncertainty associated with XRF measurements demonstrate a lack of measureable variation over the bone when using portable XRF measurements, which would make results from XRF measurements more comparable even if there were slight deviations in measurement protocols.
predominantly cortical bones (like the tibia) with the KXRF (Todd et al., 2001). This is in line with comparisons of results from other studies comparing L-shell and K-shell XRF measurements of the tibia bone (Specht et al., 2016, 2014). Even though the inability to measure trabecular bone may be seen as a shortcoming for portable XRF, cortical bone is a standard measure of exposure related to many chronic diseases and is a critically important biomarker for epidemiologic studies because of its half-life on the order of decades in contrast to years for lead in trabecular bone (Wilker et al., 2011). Our results indicated correlations between measurements of different bones were much lower than previously observed with K-shell measurement comparisons between tibia and patella in the Normative Aging Study (NAS). Previous measurements in the NAS of cortical and trabecular bone indicated a fairly high correlation (rho~0.7), whereas here we found much lower correlation between bones (Weisskopf et al., 2004). However, this was a direct result of the range of bone Pb values we identified in the 31 cadavers in our study being much more restricted (standard deviation of ~5 μg/g) in comparison to those from the NAS (sd of ~16 μg/g). When the NAS data is restricted to those subjects with bone lead concentrations in the same range observed in our 31 cadavers to achieve a similar standard deviation of bone Pb (sd in the restricted NAS=5.3), the correlation between tibia and patella measurements is (rho~0.2). This rho value is actually less than what we obtained on average with our bone comparisons (rho~0.43). The higher rho value in our cadaver study is expected, since, as stated previously, the portable XRF measurements are of the same bone type (cortical) in contrast to a comparison of KXRF measurements of tibia (mostly cortical bone) and patella (mostly trabecular bone). Thus, one would expect the higher correlation we found if, as we identified in our other results, all the measurements were of primarily cortical bone. There were slight observed differences in quantification between bones. However, most of these differences were negligible when weighting based on the measurement uncertainty. This likely means the observed differences between bones were reflective of the difficulty of measurement of different bones. A flat bone surface is identified easily on skull and tibia. Finger and patella have thicker overlying soft tissue, increasing the uncertainty of measurements, and at times, the ankle surface was hard to identify on cadavers that were more obese. When doing measurements for epidemiologic studies, it is important to be sure that the person making the measurement is trained in identifying the bone for measurement, and that a bone is chosen that is easily accessible on most individuals. We wanted to determine the bone with the lowest overlying tissue thickness. Our results indicated that our choice of tibia was justified for its low tissue thickness, which was about equal to the tissue thickness covering the skull as well. The measurements in skull and tibia produced results and uncertainties typical of previous studies of in vivo bone Pb (Weisskopf et al., 2009, 2004; Ji et al., 2015). A previous study similarly assessed tissue thickness at various locations using ultrasound measurements and got similar results (Pejović-Milić et al., 2002). However, it is possible that the measurements at the finger and patella would have produced lower tissue thickness readings if the finger and leg could have been bent for measurement, but rigor mortis in cadavers made this impossible in the current study. In a previous study on live individuals, the finger tissue thickness was estimated to be even lower than that of tibia, which could indicate that bending the leg or finger would have a significant effect on tissue thickness (Pejović-Milić et al., 2002). If the high uncertainties we found with patella and ankle measurements persisted during typical measurement procedures, we would not recommend their use as a biomarker, as the uncertainty levels were much higher, which would reduce accuracy in any study. In addition, it is important to note that since the cadavers measured in this study had been gifted to Harvard Medical School, they met initial donation criteria, one of which was not being extremely obese. Along with these differences in overlying soft tissue, there were highly variable uncertainty measures between these bones. Although
5. Conclusions Due to the low energy of the portable XRF, it is only able to measure the outer surface of bones, which is cortical bone, even when targeting bones known to be primarily trabecular. Tibia and skull have similarly thin tissue thickness, and more study of live individuals may provide more information on whether finger or patella with bent fingers or legs would have equal or lesser tissue thickness than tibia. Finally, there appears to be little difference in quantification of surface cortical bone 277
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across bones, which would mean that if different bones are measured within the same study, the results should still be comparable.
Am. J. Epidemiol. 144, 749–759. Hubbell J.H., Seltzer S.M., 1982. NIST: X-ray Mass Attenuation Coefficients. Ji, J.S., Power, M.C., Sparrow, D., et al., 2015. Lead exposure and tremor among older men: the VA normative aging study. Environ. Health Perspect. 123, 445–450. Kim, R., Aro, A., Rotnitzky, A., et al., 1995. K x-ray fluorescence measurements of bone lead concentration: the analysis of low-level data. Phys. Med. Biol. 40, 1475–1485. Leggett, R.W., 1993. An age-specific kinetic model of lead metabolism in humans. Environ. Health Perspect. 101, 18. McNeill, F.E., Fisher, M., Chettle, D.R., et al., 2017. The decrease in population bone lead levels in Canada between 1993 and 2010 as assessed by in vivo XRF. Physiol. Meas. 39, 015005. Nie, H., 2005. Studies in bone lead: a new cadmium-109 XRF measurement system. Modeling bone lead metabolism. interpreting low concentration data. McMaster Univ. (Can.) 2005, 191. Nilsson, U., Attewell, R., Christoffersson, J.O., et al., 1991. Kinetics of lead in bone and blood after end of occupational exposure. Pharmacol. Toxicol. 68, 477–484. O'Flaherty, E.J., 1998. A physiologically based kinetic model for lead in children and adults. Environ. Health Perspect. 106 (Suppl 6), 1495–1503. Pejović-Milić, A., Brito, J.A., Gyorffy, J., et al., 2002. Ultrasound measurements of overlying soft tissue thickness at four skeletal sites suitable for in vivo x-ray fluorescence. Med. Phys. 29, 2687–2691. Pemmer, B., Roschger, A., Wastl, A., et al., 2013. Spatial distribution of the trace elements zinc, strontium and lead in human bone tissue. Bone 57, 184–193. Rabinowitz, M.B., 1998. Bone lead as a biological marker in epidemiologic studies of chronic toxicity: conceptual paradigms. Environ. Health Perspect. 106, 8. Rosen, J.F., Markowitz, M.E., Bijur, P.E., et al., 1991. Sequential measurements of bone lead content by L X-ray fluorescence in CaNa2EDTA-treated lead-toxic children. Environ. Health Perspect. 93, 271–277. Specht, A.J., Kirchner, K.E., Weisskopf, M.G., et al., 2019. Lead exposure biomarkers in the Common Loon. Sci. Total Environ. 647, 639–644. Specht, A.J., Lin, Y., Weisskopf, M., et al., 2016. XRF-measured bone lead (Pb) as a biomarker for Pb exposure and toxicity among children diagnosed with Pb poisoning. Biomarkers 21, 347–352. Specht, A.J., Mostafaei, F., Lin, Y., et al., 2017. Measurements of strontium levels in human bone in vivo using portable x-ray fluorescence (XRF). Appl. Spectrosc (0003702817694383). Specht, A.J., Parish, C.N., Wallens, E.K., et al., 2018. Feasibility of a portable x-ray fluorescence device for bone lead measurements of condor bones. Sci. Total Environ. 615, 398–403. Specht, A.J., Weisskopf, M., Nie, L.H., 2014. Portable XRF technology to quantify Pb in bone in vivo. J. Biomark. 2014, 9. Todd, A.C., 2002a. L-shell x-ray fluorescence measurements of lead in bone: system development. Phys. Med. Biol. 47, 15. Todd, A.C., 2002b. L-shell x-ray fluorescence measurements of lead in bone: theoretical considerations. Phys. Med. Biol. 47, 14. Todd, A.C., Carroll, S., Geraghty, C., et al., 2002. L-shell x-ray fluorescence measurements of lead in bone: accuracy and precision. Phys. Med. Biol. 47, 20. Todd, A.C., Parsons, P.J., Tang, S., et al., 2001. Individual variability in human tibia lead concentration. Environ. Health Perspect. 109, 1139–1143. Weisskopf, M.G., Jain, N., Nie, H., et al., 2009. A prospective study of bone lead concentration and death from all causes, cardiovascular diseases, and cancer in the department of veterans affairs normative aging study. Circulation 120, 8. Weisskopf, M.G., Proctor, S.P., Wright, R.O., et al., 2007. Cumulative lead exposure and cognitive performance among elderly men. Epidemiology 18, 59–66. Weisskopf, M.G., Wright, R.O., Schwartz, J., et al., 2004. Cumulative lead exposure and prospective change in cognition among elderly men: the VA Normative Aging Study. Am. J. Epidemiol. 160, 1184–1193. Wilker, E., Korrick, S., Nie, L.H., et al., 2011. Longitudinal changes in bone lead levels: the VA Normative Aging Study. J. Occup. Environ. Med. 53, 850–855. Zhang, Y., Cheng, F., Li, D., et al., 2005. Investigation of elemental content distribution in femoral head slice with osteoporosis by SRXRF microprobe. Biol. Trace Elem. Res. 103, 177–185. Zoeger, N., Wobrauschek, P., Streli, C., et al., 2005. Distribution of Pb and Zn in slices of human bone by synchrotron u-XRF. X-Ray Spectrom. 34, 140–143.
Acknowledgments The authors would like to thank the staff of the Harvard Anatomical Gift Program. Specifically, we would like to thank the Managing Director Mark Cicchetti and the Morgue Manager Cedric Lodge for their support in providing assistance for our work. This work was supported by the National Institute of Environmental Health Science (NIEHS) R21 grant R21ES024700 and R01 grant R01ES024165. Disclosure statement The authors declare they have no actual or potential competing financial interests. Funding sources This work was supported by the National Institute of Environmental Health Science (NIEHS) R21 grant R21ES024700 and R01 grant R01ES024165. Human subject research We used 31 cadavers in this study from the Anatomical Gift Program of Harvard Medical School. The anatomical gift program partnered with Brigham and Women's Hospital and Partners Health Care and received ethical approval from the human subjects research internal review board (IRB) at Brigham and Women's Hospital. Harvard T.H. Chan School of Public Health ceded IRB review to Brigham and Women's Hospital. References Barbosa Jr., F., Tanus-Santos, J.E., Gerlach, R.F., et al., 2005. A critical review of biomarkers used for monitoring human exposure to lead: advantages, limitations, and future needs. Environ. Health Perspect. 113, 1669–1674. Bellis, D.J., Li, D., Chen, Z., et al., 2009. Measurement of the microdistribution of strontium and lead in bone via benchtop monochromatic microbeam x-ray fluorescence with a low power source. J. Anal. Spectrom. 24, 622–626. Chettle, D.R., Scott, M.C., Somervaille, L.J., 1991. Lead in bone: sampling and quantitation using K X-rays excited by 109Cd. Environ. Health Perspect. 91, 49–55. Erkkila, J., Armstrong, R., Riihimaki, V., et al., 1992. In vivo measurements of lead in bone at four anatomical sites: long term occupational and consequent endogenous exposure. Br. J. Ind. Med 49, 631–644. Eswaran, S.K., Gupta, A., Adams, M.F., et al., 2006. Cortical and trabecular load sharing in the human vertebral body. J. Bone Miner. Res. 21, 307–314. Gray, H., Standring, S., Ellis, H., et al., 2005. Gray's Anatomy: the Anatomical Basis of Clinical Practice. Elsevier Churchill Livingstone, Edinburgh; New York. Hu, H., Milder, F.L., Burger, D.E., 1989. X-ray fluorescence: issues surrounding the application of a new tool for measuring burden of lead. Environ. Res. 49, 295–317. Hu, H., Payton, M., Korrick, S., et al., 1996. Determinants of bone and blood lead levels among community-exposed middle-aged to elderly men. The normative aging study.
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Comparison of bone lead measured via portable x-ray fluorescence across and within bones
T
⁎
Aaron J. Specht , Aisha S. Dickerson, Marc G. Weisskopf Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States
A R T I C LE I N FO
A B S T R A C T
Keywords: Heavy metal toxicity Bone Chronic disease Cumulative exposure Biomarkers
Background: Bone lead measured via x-ray fluorescence (XRF) has been used for decades in health studies. A portable XRF device for bone lead measurement is gaining in popularity for its ease of use and shorter measurement times. Previous XRF devices have measured different bone types in order to sample both cortical and trabecular bone, in which lead has different half residence times. Objective: The portable XRF uses lower energy to measure bone lead than previous devices, and, thus, only measures the surface of the bone. Because all bones have a cortical shell, we hypothesized that portable XRF bone lead measurements would be similar regardless of the bone measured. Methods: This study tested differences in portable XRF bone lead measurements across different cortical and trabecular bones in measurements made on 31 cadavers. We also compared tissue thicknesses overlying different bones, which can impact portable XRF measurements. Results: The correlation coefficients found between bones were higher (rho ~0.4) than previous K-shell XRF bone measurements in cortical and trabecular over the same range of values (rho~0.2). The concentrations were shown to vary non-significantly across different bones within individuals.
1. Introduction
are differences between the two approaches. Importantly, the energies that each technique uses are different. Portable XRF uses the L-shell of Pb for measurement at 10.5 and 12.6 keV, much lower energy than the K-shell of Pb at 75, 73, and 84 keV. The lower energy of the portable XRF measurement only allows sampling at a depth of 0.2 mm into the bone (Hubbell and Seltzer, 1982; Todd, 2002b). The low energy also makes L-XRF much more dependent on skin thickness, which, as shown in earlier experimental devices used for in vivo bone Pb measurements, can be difficult to overcome (Todd, 2002b, 2002a; Todd et al., 2002; Rosen et al., 1991). More recent experiments with L-XRF in the form of the portable XRF used in this study, have shown more promise for overcoming some of these critical barriers (Specht et al., 2016, 2018, 2014). In contrast, the higher energy of the KXRF penetrates much deeper into the bone averaging over a large portion of the cross section. Thus, the part of the bone sampled to estimate bone Pb concentration by each approach is different. The different portion of bone sampled by the portable XRF compared with the KXRF may have implications for interpreting the measurement results. Bone Pb analyses have typically measured two different types of bone: more spongy trabecular bone and the harder cortical bone, in which Pb has a half-life on the order of several years vs decades, respectively (Rabinowitz, 1998; Hu et al., 1989; Erkkila et al.,
Bone lead (Pb) has been used for years to assess cumulative Pb exposure levels, which have typically been found to be more strongly associated with many chronic health conditions than more commonly used blood Pb concentrations (Barbosa et al., 2005). The established approach for in vivo bone Pb measurements is K-shell x-ray fluorescence (KXRF) (Chettle et al., 1991; Hu et al., 1989). This technology, however, has disadvantages for use in epidemiological studies mainly related to the need for a radioisotope, resultant facilities approval requirements, lack of portability, and long measurement times. Portable x-ray fluorescence (XRF) is another technology for bone Pb analyses that has become more feasible given advances in detector and other technologies. Advantages of the portable XRF include its portability, a measurement time ten times shorter than KXRF, simpler licensing requirements because it uses an x-ray tube, and the possibility of measuring metals in bone other than Pb. The use of a portable XRF would allow for a much wider undertaking of research on cumulative Pb exposures and so could be tremendously beneficial to clinical and occupational surveillance programs. Work to validate this device in previous studies has proven fairly successful (Specht et al., 2014, 2016). Although both KXRF and portable XRF can measure bone Pb, there ⁎
Correspondence to: 655 Huntington Ave Building 1 Room 1402, Boston, MA 02115, United States. E-mail address: [email protected] (A.J. Specht).
https://doi.org/10.1016/j.envres.2019.02.031 Received 20 November 2018; Received in revised form 19 February 2019; Accepted 20 February 2019 Available online 21 February 2019 0013-9351/ © 2019 Elsevier Inc. All rights reserved.
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1992; Eswaran et al., 2006). Often KXRF measurements are done on both the patella (mostly trabecular) and tibia (mostly cortical) bones (Hu et al., 1989; Erkkila et al., 1992). Trabecular and cortical bones have different mechanisms of uptake for Pb and other metals, which influence their respective use in exposure assessment studies (Hu et al., 1996; Nilsson et al., 1991; O'Flaherty, 1998; Pemmer et al., 2013; Nie, 2005; Leggett, 1993). However, all bones are encased in a cortical shell (Gray et al., 2005). For example, the predominantly trabecular patella bone thickness averages about 2.5 cm, but with a cortical shell that ranges in thickness from 0.2 to 0.6 mm (Gray et al., 2005). Thus, it is likely that the vast majority of bone sampled when measuring any bone with the portable XRF is in fact cortical bone given the penetration depth of the portable XRF energy. Little is known about how using the bone surface as a biomarker may differ epidemiologically from traditional KXRF measurements. The bone surface has been shown to incorporate and turnover bone at a different rate (Leggett, 1993; O'Flaherty, 1998). Characterizations of the structural differences have shown parallel differences in quantification of surface sections in the bone (Pemmer et al., 2013; Bellis et al., 2009; Zhang et al., 2005; Zoeger et al., 2005). However, little is known on the potential of surface bone for impacting health and how the shift from KXRF to portable XRF may influence future epidemiological health studies and exposure comparability to previous studies of bone Pb. In this study, we compared bone Pb concentrations across different bones and within bones in cadavers measured using the portable XRF. We hypothesized that measurement of any bone type with the portable XRF should give readings reflective of cortical bone measurements. We compared correlations of portable XRF measures between different bone sites to correlations of standard KXRF measures in previous studies to identify how the change of biomarker may influence future studies. We also took several measurements along the tibial shaft and skull to determine the variability of measurements along a single bone type.
Fig. 1. Lead beta peak spectrum from an individual with 3 mm of soft tissue thickness.
with the portable XRF reported here are equivalent to µg/g of dry weight bone, which is 1.5 times lower than typical KXRF measurements, which are µg/g of bone mineral. All references to previous KXRF measurements have been labeled as µg/g bone mineral, whereas all other units of µg/g are ug of Pb/g of dry weight bone, unless otherwise noted. Previous works identified the detection limit for the portable XRF used in this study to range between 2 and 11 µg/g dry weight bone for tissue thicknesses ranging from 1 to 5 mm respectively (Specht et al., 2014, 2018). The raw spectra from the bone Pb measurements were fitted for the Pb beta signal as done in our previous works (Specht et al., 2019, 2016, 2014). Briefly, the beta peak from Pb (12.6 keV) was fitted using a Gaussian function combined with an exponential function to fit the background counts using Matlab (Release 2014 A). We used the net counts from Pb and a function of the tissue thickness effect on net counts of Pb derived from our calibration standards to identify the concentration of bone Pb from each individual. A typical lead peak for our spectra is shown in Fig. 1. Measurements were made at the tibia, patella, skull, ankle, and index finger bones. Due to rigor mortis in cadavers, we deviated from typical measurement positioning. Soft tissue was intact on each cadaver, and we believe these measurements should be identical to those expected from typical in vivo measurements. Patella measurements were made with the leg straight, which may have increased the soft tissue thickness overlying the bone and resultant uncertainty compared with patella measurements done on a flexed leg. Finger bone measurements were made at the middle phalanx of the index finger with the finger slightly bent, depending on the cadaver and how they were positioned before rigor mortis. In eight of the cadavers we made multiple measurements of the tibia and skull. Measurements from proximal to distal tibia were made at four equal intervals down the tibia shaft with one extra measurement at mid-tibia level. The skull was measured in 3 locations, one measurement at each temporal plate and one measurement of the frontal plate. The mid-tibia and frontal plate skull measurements were used for the comparisons between bone sites among all 31 cadavers.
2. Materials and methods 2.1. Cadavers We used 31 cadavers in this study from the Anatomical Gift Program of Harvard Medical School. The age of death ranged from 52 to 100 years with a median (interquartile range) of 86 (13) years. There were 15 females and 16 males who all died of natural diseases. The anatomical gift program partnered with Brigham and Women's Hospital and Partners Health Care and received ethical approval from the human subjects research internal review board (IRB) at Brigham and Women's Hospital. Harvard T.H. Chan School of Public Health ceded IRB review to Brigham and Women's Hospital. 2.2. Portable XRF We used a commercially available portable XRF (Niton XL3t GOLDD +, Thermo Fisher Scientific Inc., Billerica, MA) with customizable x-ray tube voltage, current, and filtration to perform this study. We used an xray tube voltage of 50 keV and current of 40 uA with a filter of silver and iron, and 3-min real-time measurements for this study. These are the parameters used previously with a similar device in studies with living humans and lab samples (Specht et al., 2016, 2017, 2014). The device was calibrated for bone Pb in previous work using Pb doped plaster-of-Paris (PP) phantoms at 0, 5, 10, 15, 30, 50, and 100 µg/g PP and soft tissue phantoms made of Lucite (Specht et al., 2014). Although calibration is done on phantoms in unit of µg/g PP, measurements made with the portable XRF have units of µg/g dry bone as shown in our previous work comparing bone measurements using inductively coupled plasma mass spectrometry, KXRF, and portable XRF bone Pb measurements (Specht et al., 2019, 2018). All Pb measurements made
2.3. Statistical analysis The uncertainty values for the portable XRF measurements were determined as in previous studies using counting statistics in the fitted area for Pb (Specht et al., 2017). The uncertainty (σ ) of each measurement was calculated using the following equation,
C× σ=
BKG + Gross t
Net
(1)
where c is the concentration, BKG is the background counts as estimated by our Matlab fitting, Gross is gross counts over the area of the fitted peak, t is measurement time, and Net is the net Pb counts from the 274
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Gaussian function from our Matlab spectral fitting. This gives an uncertainty estimate equivalent to one standard deviation (σ) change from the calculated concentration. This uncertainty value, and the device limit of detection, is different from standard counting error values, which generally underestimate the actual error. Our value is a more conservative estimate to account for the added uncertainty of our tissue thickness calculation, which will have the greatest impact on the associated uncertainty and limit of detection of the device, which was demonstrated in our previous work (Specht et al., 2014). We weighted the analysis on the uncertainty values to utilize the information gained from our Matlab analysis fitting for each measurement, even values lower than the limit of detection, which would normally result in censored data. Hence, negative values are left as such because they represent the point estimate of concentration with uncertainty in the measurement. If an individual measurement is close to zero. To reduce the likelihood of bias from artificial variance reduction, we include the negative point estimate of the measurements in our analysis instead of assigning other values or censoring any data. This has been shown to the most appropriate analysis procedure for in vivo bone Pb analyses in previous studies over other potential methods (Kim et al., 1995). For the measurements of different bone sites, we wanted to determine whether each subject's bone measurements differed based on the location on the bone measured. We performed a repeated-measures multivariate ANOVA to assess the variation in measured Pb concentration across sites on a single bone and across different bones in the body. Each ANOVA analysis was adjusted for subject variation, and the assumption of sphericity was met in each case. The ANOVA had four degrees of freedom for the main analysis as we had 5 measures of bone lead per cadaver. A pairwise correlation matrix was used to show the relationship between bone types of each individual. The correlations were weighted based on the uncertainty of the bone with the greatest average uncertainty value. For example, the correlation between tibia and patella was weighted based on the squared inverse of the uncertainty in the patella lead measurements, since the uncertainty in patella (13.7 μg/g) was greater than tibia (6.3 μg/g) (Table 1). Since the goal of the analysis was to identify differences between bones measured with portable XRF, we ran a simulation to assess our power to detect differences given the uncertainties in these measures. We simulated 1000 data sets for 31 cadavers assuming they had portable XRF Pb measurements from five bones each. Two of the five bones were simulated as trabecular (slightly higher bone Pb) and the other three bones were simulated as cortical (slightly lower bone Pb) on an individual basis. This simulated dataset was created based on the distributions found in our measured cadavers using the portable XRF. This should reflect the variance observed from portable XRF measurements from bone lead, which takes into account both the variance of the bone lead between individuals and the uncertainty in the measurements from the portable XRF itself. We found that we would have 86.7% power to detect an average individual difference of 5 μg/g (or a 0.8 standard deviation difference) between bones using our repeated-measures ANOVA adjusted for within and between subject variance. This is
equivalent to less than half of the within person difference seen between tibia, mostly cortical, and patella, mostly trabecular, bone measures in the Normative Aging Study, which was 11.6 μg/g (Weisskopf et al., 2007). All Pb measurements from the cadavers were normally distributed in our samples and checked at each analysis step. The aforementioned statistical analysis was done using R statistical software, version 3.0.3 (Foundation for Statistical Computing, Vienna, Austria). Additionally, since many previous environmental epidemiologic studies use tibia Pb measurements when assessing associations between Pb exposures and health outcomes, tibia measurements were further compared to measurements of other bones using generalized estimating equations (GEE) with repeated measures to verify our results using ANOVA. The GEE used tibia as the reference group, as tibia was shown to be > 90% cortical bone. Using this comparison, we would compare other bones with high percentage of trabecular bone to tibia with a high percentage of cortical bone. The GEE was conducted using an identity link function and an unstructured covariance matrix for within and between subject measurements. Then the GEE model was weighted based on the uncertainty of the bone lead measurements. This portion of the statistical analysis was done using SAS Version 9.4 statistical software (SAS Institute Inc., Cary, NC, USA).
3. Results 3.1. Bone Pb results from different bones In Table 1, we show a summary of the results for the measurements, uncertainties, and tissue thicknesses of mid-tibia, patella, frontal plate, ankle, and finger bones for each cadaver. Results from repeated measures ANOVA found non-significant differences between each bone measurement (mid-tibia, patella, frontal plate of the skull, ankle, and finger) with a p-value of 0.12 and F-ratio of 1.85. There was no significant relationship between age and bone Pb in our population. This analysis was adjusted for within and between subject variances. The average detection limit across all measurements was 12.6 μg/g, which is equivalent to previous studies using in vivo KXRF measurements. We also did a sensitivity analysis excluding measurements with tissue thicknesses greater than 5 mm, which has been shown to substantially increase the detection limit and uncertainty. Results for this analysis still showed non-significant differences between bones (p-value=0.40) with F-ratio of 1.03. We show the correlation matrix comparing the pairwise correlations between bones of individuals in Table 2. Results from the GEEs are presented in Table 3. In the unadjusted models, patella Pb estimates were lower than tibia measures (β = -3.00; 95% CI: -13.37, 7.37). The expected difference of patella measures compared to tibia measures became almost zero after adjustment and weighting for uncertainty (β = 0.86; 95% CI: -3.92, 5.63). Mean ankle measures were 8.57 µg/g higher with marginal significance (p = 0.05), though the mean decreased to 0.45 µg/g and significance diminished (p = 0.89) after weighting for uncertainty. Additionally, finger, and skull measures were slightly higher than tibia measures in crude analyses, but essentially no different in weighted models. All differences in measurements between bones were far from statistically significant.
Table 1 Summary of bone Pb (ug/g) measurements of the different bones and the uncertainties (sigma) associated with measurement for each bone.
Tibia Patella Ankle Finger Skull
Bone Pb (µg/g)
Uncertainty (µg/g)
Tissue Thickness (mm)
Mean
Standard deviation
Mean
Standard deviation
Mean
18.7 28.0 23.1 24.4 22.2
6.3 13.7 10.8 8.7 5.7
5.0 7.1 6.8 5.0 2.6
3.6 5.8 5.0 4.5 3.6
7.7 4.7 16.3 14.1 12.2
Table 2 Pairwise correlations between measurements at different bones weighted by the uncertainty in the bone lead measurement.
Standard deviation
Tibia Patella Skull Ankle Finger
1.5 1.8 1.4 0.9 0.9
275
Tibia
Patella
Skull
Ankle
Finger
1.00
0.50 1.00
0.38 0.46 1.00
0.55 0.33 0.06 1.00
0.46 0.57 0.69 0.32 1.00
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Table 3 Comparison of different bone Pb measurements to tibia measures. Weighteda
Unadjusted
Tibia Patella Ankle Finger Skull a
Table 5 Measurements of bone Pb (ug/g) at 3 sites on the skull. Skull Bone Pb (ug/g)
Estimate (95% CI)
p-value
Estimate (95% CI)
p-value
Measurement Site
Reference − 3.00 (−13.37, 7.37) 8.57 (−0.15, 17.29) 6.44 (−1.81, 14.69) 4.50 (−2.84, 11.84)
– 0.57 0.05 0.13 0.23
Reference 0.86 (−3.92, 5.63) 0.45 (−2.79, 3.69) − 2.20 (−6.41, 2.02) − 0.45 (−2.59, 1.68)
– 0.86 0.89 0.60 0.83
Right Temporal Plate Frontal Plate Left Temporal Plate Mean S.D. Uncertainty (ug/g) Mean S.D.
Model weighted for uncertainty.
Table 4 Measurements of bone Pb (ug/g) at five sites along the tibia. Ratio of Frontal Plate to Medial Plates
Proximal Mid Distal Mean S.D. Mean S.D.
Subject ID 4667 4664 4668 8 2 9 13 − 10 3 19 −4 −5 17 8 7 18 −7 −6 15 −2 2 4.4 7.1 7.0 Uncertainty (ug/g) 1.9 4.0 5.1 0.1 1.1 1.5
4680 23 31 25 28 29 27 3.2 3.9 1.1
4678 17 14 32 19 10 19 8.1 2.3 0.8
4675 14 17 22 11 8 14 5.1 9.1 3.8
ID 4664 − 13 −7 9 −4 11.3
4668 −4 8 −9 −2 9.0
4680 27 22 31 26 4.7
4678 13 29 25 23 8.5
4675 22 26 13 20 7.0
4686 3 −1 14 5 7.6
4687 15 16 −6 8 12.0
4.0 0.8
5.8 1.7
3.7 1.3
2.7 0.4
4.3 0.9
4.2 1.2
3.6 1.0
7.6 0.9
8.0
Tibia Bone Pb (ug/g) Measurement Site
Subject 4667 15 25 17 19 5.1
4686 11 9 17 13 9 12 3.2 2.5 0.6
4687 10 15 14 7 12 12 3.2 3.4 1.3
7.0 6.0 5.0 4.0 3.0 2.0 1.0 0.0 -1.0
0
-2.0
3.2. Bone Pb variability along tibia
1
2
3
4
Skull Measurement Location
Fig. 3. Relative difference in skull bone Pb measurement from the right temporal plate to the left temporal plate as a ratio with the frontal plate.
We performed measurements along the tibia at 5 intervals (4 equal intervals down the tibia and a measurement at mid-tibia). The results are shown in Table 4 and Fig. 2. We performed a repeated measures ANOVA using this data and found non-significant differences (pvalue=0.27). However, this was only on a subset of cadavers, so we expect reduced power.
4. Discussion The main results of the study indicate that the portable XRF is primarily measuring cortical bone, regardless of the bone, and there are essentially no differences between measurements of different bones in analyses adjusted for uncertainty. This indicates that results from Lshell measurements at any bone should be comparable to cortical bone measurements. In addition to this, we show the tissue thickness of different possible locations for XRF measurements, which suggests that tibia and skull have the least tissue thickness overlying the bone. This suggests that these bones are preferable for in vivo measurements in order to minimize measurement uncertainties and corresponding device detection limits. Finally, we show no trend in bone measurement variation along the skull or tibia bone, similar to results of previous studies with atomic absorption spectrometry (AAS) measurements (Todd et al., 2001, 2002). The measurements of different bones should be measuring solely cortical bone when using the portable XRF. The low penetration depth only allows for complete sampling of the outer cortical shell of each bone measured (Gray et al., 2005). Using values from the National Institute of Standards and Technology (NIST) we can calculate the average penetration depth of photons in cortical bone using the attenuation properties for 10 keV (bone density of 1.85 g/cm3), which is the energy of the Pb alpha characteristic x-ray (Hubbell and Seltzer, 1982). The Pb characteristic energy would be the most conservative estimate, as the signal arising in the bone would need to be collected by the detector outside the bone. Using the attenuation values from NIST at 10 keV, we calculate a penetration depth of about 0.2 mm, which would reduce the signal intensity to 1/e (Hubbell and Seltzer, 1982). Including soft tissue in this calculation still gives a value of roughly 0.2 mm, as the attenuation of soft tissue is much lower than bone. This would make it impossible to measure trabecular bones with a cortical shell greater than 0.5 mm. Thus, measurements of bone Pb using KXRF and portable XRF would likely be less comparable when not measuring
3.3. Bone Pb variability in skull With our 3 measurements of the skull at the right temporal plate, frontal plate, and left temporal plate, we did an analysis similar to that for tibia bone. Table 5 shows the measurements for each cadaver at each bone site. Fig. 3 shows the variation over location. We performed a repeated measures ANOVA using this data and found non-significant differences (p-value=0.54). Again, this was only for a subset of cadavers, so we expected reduced power in the ANOVA analysis.
Fig. 2. Relative difference in tibia bone Pb measurement along the proximal (-2) to distal (+2) axis of the tibia bone as a ratio with the mid-tibia measurement. 276
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the uncertainties seem high for a quantification of Pb, these values are typical of in vivo measurements. Traditional in vivo KXRF measurements, such as those used for over a decade in the Normative Aging Study, had an average uncertainty for tibia and patella measurements of 5.0 and 6.0 μg/g bone mineral (4.0 and 5.0 μg/g dry bone) respectively, which is similar to the average tibia Pb measurement in our study of 6.3 μg/g (5.0 μg/g with the same cut-off parameters as the NAS) (Weisskopf et al., 2009, 2004; Ji et al., 2015). The portable XRF measurements made in our study may have a similar uncertainty of the traditional KXRF measurements, but the uncertainty itself is more variable, because of the aforementioned dependence on soft tissue thickness (Specht et al., 2014). The portable XRF as a tool should primarily be used as a device in epidemiological studies or in surveillance of highly exposed individuals, as the associated uncertainty makes environmental levels of exposure difficult to discern on an individual basis. Furthermore, with the nature of this study, we utilized statistical corrections for uncertainties in our methods, which should be used in the analysis of portable XRF bone Pb measures in the future to prevent bias from more variable data (McNeill et al., 2017). Procedures in previous health studies utilized a cut-off value at an uncertainty value of 10 or 15 μg/g bone mineral for traditional KXRF bone Pb measurements to ensure the most reliable data (Weisskopf et al., 2009, 2004; Ji et al., 2015), which also decreased the average uncertainty value in those studies. Unlike with traditional KXRF measurements, the portable XRF measurement uncertainties depend on overlying skin, which inturn can be related to BMI or a number of health related outcomes. Thus, for measures of portable XRF in health studies, it is best to use a statistical method of correction rather than omitting these values, which may bias results. Regardless, the results using the portable XRF in general population are likely to have a higher uncertainty than typical KXRF measurements, but the advantages presented by the portable XRF in terms of measurement time and portability more than outweigh a slight increase in uncertainty. Finally, this should not impact the observed results of our main analysis identifying differences between bone sites, as the data set simulated for the power calculation reflected the additional uncertainty observed using portable XRF bone Pb measurements, so the analysis was sufficiently powered, despite the uncertainties observed in our data. Finally, we used measurements to determine the variability of bone Pb along the tibia and over the skull. We found slight non-significant variations in both locations, which is unsurprising considering we had limited power in this analysis and with previous studies indicating only slight differences along bones. The trend identified by Todd et al., which used AAS measurements of surface and core tibia, showed a decrease in bone lead towards the ends of the tibia, but this trend was too small to detect in our study without a much larger sample size (Todd et al., 2001). Previous studies using L-XRF to identify these trends on cadavers were similarly limited by power and uncertainty (Todd et al., 2002). In addition, since our data was on intact cadavers, it is likely that our measurements were further from the true ends of the tibial shaft; thus, this difference was less exaggerated in our results. Our study results, along with the known inherent uncertainty associated with XRF measurements demonstrate a lack of measureable variation over the bone when using portable XRF measurements, which would make results from XRF measurements more comparable even if there were slight deviations in measurement protocols.
predominantly cortical bones (like the tibia) with the KXRF (Todd et al., 2001). This is in line with comparisons of results from other studies comparing L-shell and K-shell XRF measurements of the tibia bone (Specht et al., 2016, 2014). Even though the inability to measure trabecular bone may be seen as a shortcoming for portable XRF, cortical bone is a standard measure of exposure related to many chronic diseases and is a critically important biomarker for epidemiologic studies because of its half-life on the order of decades in contrast to years for lead in trabecular bone (Wilker et al., 2011). Our results indicated correlations between measurements of different bones were much lower than previously observed with K-shell measurement comparisons between tibia and patella in the Normative Aging Study (NAS). Previous measurements in the NAS of cortical and trabecular bone indicated a fairly high correlation (rho~0.7), whereas here we found much lower correlation between bones (Weisskopf et al., 2004). However, this was a direct result of the range of bone Pb values we identified in the 31 cadavers in our study being much more restricted (standard deviation of ~5 μg/g) in comparison to those from the NAS (sd of ~16 μg/g). When the NAS data is restricted to those subjects with bone lead concentrations in the same range observed in our 31 cadavers to achieve a similar standard deviation of bone Pb (sd in the restricted NAS=5.3), the correlation between tibia and patella measurements is (rho~0.2). This rho value is actually less than what we obtained on average with our bone comparisons (rho~0.43). The higher rho value in our cadaver study is expected, since, as stated previously, the portable XRF measurements are of the same bone type (cortical) in contrast to a comparison of KXRF measurements of tibia (mostly cortical bone) and patella (mostly trabecular bone). Thus, one would expect the higher correlation we found if, as we identified in our other results, all the measurements were of primarily cortical bone. There were slight observed differences in quantification between bones. However, most of these differences were negligible when weighting based on the measurement uncertainty. This likely means the observed differences between bones were reflective of the difficulty of measurement of different bones. A flat bone surface is identified easily on skull and tibia. Finger and patella have thicker overlying soft tissue, increasing the uncertainty of measurements, and at times, the ankle surface was hard to identify on cadavers that were more obese. When doing measurements for epidemiologic studies, it is important to be sure that the person making the measurement is trained in identifying the bone for measurement, and that a bone is chosen that is easily accessible on most individuals. We wanted to determine the bone with the lowest overlying tissue thickness. Our results indicated that our choice of tibia was justified for its low tissue thickness, which was about equal to the tissue thickness covering the skull as well. The measurements in skull and tibia produced results and uncertainties typical of previous studies of in vivo bone Pb (Weisskopf et al., 2009, 2004; Ji et al., 2015). A previous study similarly assessed tissue thickness at various locations using ultrasound measurements and got similar results (Pejović-Milić et al., 2002). However, it is possible that the measurements at the finger and patella would have produced lower tissue thickness readings if the finger and leg could have been bent for measurement, but rigor mortis in cadavers made this impossible in the current study. In a previous study on live individuals, the finger tissue thickness was estimated to be even lower than that of tibia, which could indicate that bending the leg or finger would have a significant effect on tissue thickness (Pejović-Milić et al., 2002). If the high uncertainties we found with patella and ankle measurements persisted during typical measurement procedures, we would not recommend their use as a biomarker, as the uncertainty levels were much higher, which would reduce accuracy in any study. In addition, it is important to note that since the cadavers measured in this study had been gifted to Harvard Medical School, they met initial donation criteria, one of which was not being extremely obese. Along with these differences in overlying soft tissue, there were highly variable uncertainty measures between these bones. Although
5. Conclusions Due to the low energy of the portable XRF, it is only able to measure the outer surface of bones, which is cortical bone, even when targeting bones known to be primarily trabecular. Tibia and skull have similarly thin tissue thickness, and more study of live individuals may provide more information on whether finger or patella with bent fingers or legs would have equal or lesser tissue thickness than tibia. Finally, there appears to be little difference in quantification of surface cortical bone 277
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across bones, which would mean that if different bones are measured within the same study, the results should still be comparable.
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Acknowledgments The authors would like to thank the staff of the Harvard Anatomical Gift Program. Specifically, we would like to thank the Managing Director Mark Cicchetti and the Morgue Manager Cedric Lodge for their support in providing assistance for our work. This work was supported by the National Institute of Environmental Health Science (NIEHS) R21 grant R21ES024700 and R01 grant R01ES024165. Disclosure statement The authors declare they have no actual or potential competing financial interests. Funding sources This work was supported by the National Institute of Environmental Health Science (NIEHS) R21 grant R21ES024700 and R01 grant R01ES024165. Human subject research We used 31 cadavers in this study from the Anatomical Gift Program of Harvard Medical School. The anatomical gift program partnered with Brigham and Women's Hospital and Partners Health Care and received ethical approval from the human subjects research internal review board (IRB) at Brigham and Women's Hospital. Harvard T.H. Chan School of Public Health ceded IRB review to Brigham and Women's Hospital. References Barbosa Jr., F., Tanus-Santos, J.E., Gerlach, R.F., et al., 2005. A critical review of biomarkers used for monitoring human exposure to lead: advantages, limitations, and future needs. Environ. Health Perspect. 113, 1669–1674. Bellis, D.J., Li, D., Chen, Z., et al., 2009. Measurement of the microdistribution of strontium and lead in bone via benchtop monochromatic microbeam x-ray fluorescence with a low power source. J. Anal. Spectrom. 24, 622–626. Chettle, D.R., Scott, M.C., Somervaille, L.J., 1991. Lead in bone: sampling and quantitation using K X-rays excited by 109Cd. Environ. Health Perspect. 91, 49–55. Erkkila, J., Armstrong, R., Riihimaki, V., et al., 1992. In vivo measurements of lead in bone at four anatomical sites: long term occupational and consequent endogenous exposure. Br. J. Ind. Med 49, 631–644. Eswaran, S.K., Gupta, A., Adams, M.F., et al., 2006. Cortical and trabecular load sharing in the human vertebral body. J. Bone Miner. Res. 21, 307–314. Gray, H., Standring, S., Ellis, H., et al., 2005. Gray's Anatomy: the Anatomical Basis of Clinical Practice. Elsevier Churchill Livingstone, Edinburgh; New York. Hu, H., Milder, F.L., Burger, D.E., 1989. X-ray fluorescence: issues surrounding the application of a new tool for measuring burden of lead. Environ. Res. 49, 295–317. Hu, H., Payton, M., Korrick, S., et al., 1996. Determinants of bone and blood lead levels among community-exposed middle-aged to elderly men. The normative aging study.
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