HR-pQCT cross-calibration using standard vs. Laplace-Hamming binarization approach.

High-resolution peripheral quantitative computed tomography (HR-pQCT) has emerged as a powerful imaging technique for characterizing bone microarchitecture in the human peripheral skeleton. The second-generation HR-pQCT scanner provides improved spatial resolution and a shorter scan time. However, the transition from the first-generation (XCTI) to second-generation HR-pQCT scanners (XCTII) poses challenges for longitudinal studies, multi-center trials, and comparison to historical data. Cross-calibration, an established approach for determining relationships between measurements obtained from different devices, can bridge this gap and enable the utilization and comparison of legacy data. The goal of this study was to establish cross-calibration equations to estimate XCTII measurements from XCTI data, using both the standard and Laplace-Hamming (LH) binarization approaches. Thirty-six volunteers (26-85 yr) were recruited and their radii and tibiae were scanned on both XCTI and XCTII scanners. XCTI images were analyzed using the manufacturer's standard protocol. XCTII images were analyzed twice: using the manufacturer's standard protocol and the LH segmentation approach previously developed and validated by our team. Linear regression analysis was used to establish cross-calibration equations. Results demonstrated strong correlations between XCTI and XCTII density and geometry outcomes. For most microstructural outcomes, although there were considerable differences in absolute values, correlations between measurements obtained from different scanners were strong, allowing for accurate cross-calibration estimations. For some microstructural outcomes with a higher sensitivity to spatial resolution (eg, trabecular thickness, cortical pore diameter), XCTII standard protocol resulted in poor correlations between the scanners, while our LH approach improved these correlations and decreased the difference in absolute values and the proportional bias for other measurements. For these reasons and due to the improved accuracy of our LH approach compared with the standard approach, as established in our previous study, we propose that investigators should use the LH approach for analyzing XCTII scans, particularly when comparing to XCTI data.

Transferability of bone phenotyping and fracture risk assessment by µFRAC from first-generation high-resolution peripheral quantitative computed tomography to second-generation scan data.

INTRODUCTION: The continued development of high-resolution peripheral quantitative computed tomography (HR-pQCT) has led to a second-generation scanner with higher resolution and longer scan region. However, large multicenter prospective cohorts were collected with first-generation HR-pQCT and have been used to develop bone phenotyping and fracture risk prediction (µFRAC) models. This study establishes whether there is sufficient universality of these first-generation trained models for use with second-generation scan data. METHODS: HR-pQCT data were collected for a cohort of 60 individuals, who had been scanned on both first- and second-generation scanners on the same day to establish the universality of the HR-pQCT models. These data were each used as input to first-generation trained bone microarchitecture models for bone phenotyping and fracture risk prediction, and their outputs were compared for each study participant. Reproducibility of the models were assessed using same-day repeat scans obtained from first-generation (n = 37) and second-generation (n = 74) scanners. RESULTS: Across scanner generations, the bone phenotyping model performed with an accuracy of 93.1%. Similarly, the 5-year fracture risk assessment by µFRAC was well correlated with a Pearson's (r) correlation coefficient of r > 0.83 for the three variations of µFRAC (varying inclusion of clinical risk factors, finite element analysis, and dual X-ray absorptiometry). The first-generation reproducibility cohort performed with an accuracy for categorical assignment of 100% (bone phenotyping) and a correlation coefficient of 0.99 (µFRAC), whereas the second-generation reproducibility cohort performed with an accuracy of 96.4% (bone phenotyping) and a correlation coefficient of 0.99 (µFRAC). CONCLUSION: We demonstrated that bone microarchitecture models trained using first-generation scan data generalize well to second-generation scans, performing with a high level of accuracy and reproducibility. Less than 4% of individuals' estimated fracture risk led to a change in treatment threshold, and in general, these dissimilar outcomes using second-generation data tended to be more conservative.

Establishing the universality of first-generation-trained HR-pQCT prediction models on second-generation scan data is important to move the bone microarchitecture field forward. We found that despite the difference in resolutions between the two HR-pQCT generations, models developed with first-generation data generalized well to second-generation systems. This avoids unnecessarily repeating complex studies.

Cross-Calibration Study of The Stratos And Hologic QDR 4500A Dual-Energy X-Ray Absorptiometers to Assess Bone Mineral Density And Body Composition.

The objective of the study was to assess the agreement between the Stratos (DMS) and QDR 4500A (Hologic) DXAs in determining whole body and regional aBMD, as well as whole body composition. Fifty-five individuals (46 women: 84%) with a mean age of 41 ± 13.0 years (range: 20 to 64) and a mean BMI of 31.9 ± 10 kg/m² (range: 12.2 to 49.5) were consecutively scanned on the same day using the two devices. Predictive equations for areal bone mineral density (aBMD) and whole body composition (WBC) were derived from linear regression of the data. The two DXAs were highly correlated (p<0.001 for all parameters) with a correlation coefficient (r) ranging from 0.89 to 0.99 for aBMD (r=0.89 for whole body, r=0.92 for radius, r=0.95 for femoral neck, r=0.96 for total hip, and r=0.99 for L1-L4). For WBC, the r value was 0.98 for lean tissue mass (LTM) and 1.0 for fat mass (FM). Paired t-tests indicated a statistically significant bias between the two DXAs for the majority of measurements, requiring the determination of specific cross-calibration equations. Compared to QDR 4500A, Stratos underestimated whole body aBMD and LTM and overestimated neck and hip aBMD and whole body FM. Conversely, no significant bias was demonstrated for mean aBMD at L1-L4 and radius. For whole body aBMD and FM, the concordance between the two DXAs was influenced by BMI. Despite a high concordance between the two DXAs, the systematic bias for aBMD and WBC measurements illustrates the need to define cross-calibration equations to compare data across systems.

Calibration of Impairment Severity to Enable Comparison across Somatosensory Domains.

Comparison across somatosensory domains, important for clinical and scientific goals, requires prior calibration of impairment severity. Provided test score distributions are comparable across domains, valid comparisons of impairment can be made by reference to score locations in the corresponding distributions (percentile rank or standardized scores). However, this is often not the case. Test score distributions for tactile texture discrimination (n = 174), wrist joint proprioception (n = 112), and haptic object identification (n = 98) obtained from pooled samples of stroke survivors in rehabilitation settings were investigated. The distributions showed substantially different forms, undermining comparative calibration via percentile rank or standardized scores. An alternative approach is to establish comparable locations in the psychophysical score ranges spanning performance from just noticeably impaired to maximally impaired. Several simulation studies and a theoretical analysis were conducted to establish the score distributions expected from completely insensate responders for each domain. Estimates of extreme impairment values suggested by theory, simulation and observed samples were consistent. Using these estimates and previously discovered values for impairment thresholds in each test domain, comparable ranges of impairment from just noticeable to extreme impairment were found. These ranges enable the normalization of the three test scales for comparison in clinical and research settings.

Comparison of the Discovery A and Stratos DR densitometers for assessing whole-body and regional bone mineral density and body composition.

PURPOSE: The agreement between the Stratos DR and Discovery A densitometers was assessed for measurements of whole-body (WB) and regional fat mass (FM), fat-free soft tissue (FFST) and bone mineral density (BMD). Moreover, the precision of the Stratos DR was also evaluated. METHODS: Fifty participants (35 women, 70%) were measured consecutively, once on the Discovery A and once on the Stratos DR. In a subgroup of participants (n = 29), two successive measurements with the Stratos DR were also performed. RESULTS: FM, FFST and BMD measured with the two devices were highly correlated, with a coefficient of correlation ranging from 0.80 to 0.99. Bland-Altman analyses indicated significant bias between the two devices for all measurements. Thus, compared to the Discovery A, the Stratos DR underestimated WB BMD and WB and regional FM and FFST, with the exception of trunk FM and visceral adipose tissue (VAT), which were overestimated. Precision error for the Stratos DR, when expressed as root mean square-coefficient of variation (RMS-CV%) for FM, was 1.4% for WB, 3.0% for the gynoid and android regions, and 15.9% for VAT. The RMS-CV% for FFST was 1.0% for WB. The root mean square of standard deviation for WB BMD was 0.018 g/cm², corresponding to a 1.4% CV. The least significant change was 0.050 g/cm² (SD), and 4.0% was considered to be a significant biological change. CONCLUSIONS: Differences between the Stratos DR and Discovery A measurements are significant and require the use of translational cross-calibration equations. For most of the BMD and body composition parameters, our results demonstrated good Stratos DR precision.

A cross-calibration study using a novel dual X-ray absorptiometry system for bone mineral density measurements with the European Spine Phantom.

Background: For bone health assessment, dual-energy X-ray absorptiometry (DEXA) is recommended to measure bone mineral content and areal bone mineral density (aBMD) in the lumbar spine. However, intermachine differences were not taken into account when developing these recommendations. According to the International Society of Clinical Densitometry (ISCD), phantom-based cross-calibration is adequate after replacing the DEXA system from a different manufacturer. For different DEXA equipment, individual calibration equations were found to be necessary to fit the observed values with the given densities. Methods: The BMD European Spine Phantom (ESP) measurements (L1, L2, and L3) were assessed on 3 machines. We used the Welch test in the one-way analysis of variance (ANOVA) with a post-hoc Tamhane T2 test, linear regressions, and Bland-Altman analysis to assess the consistency of measurements and establish cross-calibration equations. Results: The coefficients of variation (CV)% of the phantom BMD values measured using the 3 systems were less than 3.0%. The 3 DEXA systems were highly correlated with BMD in the lumbar spine, with correlation values ranging from 0.933 to 0.984 (P<0.0001). The cross-calibration regression models of the ESP measurements yielded the highest prediction accuracies with the lowest prediction errors (the standard error of the estimate ranged from 0.004 to 0.008 g/cm2; P<0.0001). After the regression equations were applied, the differences in BMD values among the 3 systems were negligible. In addition, the Bland-Altman plot showed that almost all data points were within the 95% limits of agreement. Conclusions: A strong agreement for BMD measurement was established between the 3 DEXA systems. Cross-calibration equations for the lumbar spine BMD values need to be applied to transform the Hologic Discovery A or GE Lunar iDXA measurements into SONIALVISION SMIT measurements to comply with the ISCD standards for patient continuity of care in assessment during clinical diagnosis.

Cross-Calibration of iDXA and pQCT Scanners at Rural and Urban Research Sites in The Gambia, West Africa.

Between-scanner differences in measures of bone and body composition can obscure or exaggerate physiological differences in multi-site studies or the magnitude of changes in longitudinal studies. We conducted a cross-calibration study at two bone imaging centres in The Gambia, West Africa where DXA (dual-energy X-ray absorptiometry) and pQCT (peripheral Quantitative-Computed Tomography) are routinely used. Repeat scans were obtained from 64 Gambian adults (58% Male) aged Mean(SD) 30.9 (13.5) years with Mean(SD) body mass index (BMI) 21.7 (4.0) kg/m2, using DXA (GE Lunar iDXA, whole body [WB], total hip [TH], lumbar spine [LS]) and pQCT (Stratec XCT2000L/XCT2000, tibia 4%, 50% sites). Between-scanner differences were tested using paired t tests (p < 0.05). Between-scanner correlation was explored with linear regression, and cross-calibration equations derived. Bland-Altman analysis investigated machine trend/bias. When differences were detected (p < 0.05), cross-calibration equations were applied to urban values, with t tests and Bland Altman analysis repeated. Between-scanner differences exceeded the predefined level of statistical significance (p < 0.05) for WB aBMD and BA; all pQCT measures vBMD, BMC, cortical cross-sectional area (CSA) and stress-strain index (SSI). Between-scanner correlation was high (R2:0.92-0.99), except pQCT Mu.Den (R2 = 0.51). Bland Altman plots indicated bias increased with increasing BMD. Cross-calibration equations attenuated all between-scanner differences and systematic bias. Cross-calibration, particularly of pQCT scanners, is an important consideration in multi-site studies particularly where between population comparisons are intended. Our experiences and findings may be generalisable to other resource-limited settings where the logistics of sourcing parts and in-country repair may result in lengthy scanner downtime.

Quantifying misdiagnosis rates from cross-calibration biases and precision errors in dual-energy X-ray absorptiometry of the femoral neck.

BACKGROUND: Dual-energy X-ray absorptiometry (DXA) is an exam that measures areal bone mineral density (aBMD) and is regularly used to diagnose and monitor osteoporosis. Except for exam quality issues such as operator error, the quantitative results of an exam are not modified by a radiologist or other physician. DXA cross-calibration errors can shift diagnoses, conceivably leading to alternate intervention decisions and patient outcomes. PURPOSE: After identifying and correcting a cross-calibration bias of 3.8% in our two DXA scanners' aBMD measurements, we investigated misdiagnosis rates for given cross-calibration errors in a single patient cohort to determine the impact on patient care and the value of cross-calibration quality control. METHODS: The studied cohort was 8012 patients of all ages and sexes with femoral neck exams that were scanned on a single DXA unit from October 1, 2018 to March 31, 2021. There were six subcohorts delineated by age and sex, three female groups and three male groups. Data reporting focused on the highest risk subcohort of 2840 females aged 65 or older. The DXA unit had no calibration changes during that time. Only one femoral neck-left or right-was randomly chosen for analysis. Patients with multiple qualifying exams within the time interval had one exam randomly chosen. The proof-of-principle simulation shifted the aBMD values within a range of ±10%, ±8%, ±6%, ±4%, ±3.5%, ±3%, ±2.5%, ±2%, ±1.5%, ±1%, ±0.5%, and 0 (no shift); the cross-calibration shifts were informed by published results and institutional experience. Measurement precision was modeled by randomly sampling a Gaussian distribution characterized by the worst acceptable least significant change (LSC) of 6.9%, with 100 000 samplings for each patient. T-scores were recalculated from the shifted aBMD values, followed by reassigned diagnoses from the World Health Organization's T-score-based scheme. RESULTS: The unshifted original subcohort of women aged 65 and older had 599 normal diagnoses (21.1% of the cohort), 1784 osteopenia diagnoses (62.8%), and 455 osteoporosis diagnoses (16.1%). Osteoporosis diagnosis rates were highly sensitive to aBMD shifts. At the extrema, a -10% aBMD shift led to +161% osteoporosis cases, and a +10% aBMD shift led to -64.5% osteoporosis cases. Within the more plausible ±4% aBMD error range, the osteoporosis diagnosis rate changed -10.5% per +1% aBMD shift as indicated by linear regression (R2  = 0.98). Except for the men aged 49 years and younger subcohort, the total cohort and five subcohorts had fit line slopes ranging between -9.7% and -12.1% with R2 ≥ 0.98. Cross-calibration bias had greater influence for diagnosis count rates compared to measurement precision, that is, LSC. CONCLUSIONS: These results quantify the degree of misdiagnosis that can occur in a clinically relevant cohort due to cross-calibration bias. In medical practices where patients may be scanned on more than one DXA unit, ensuring cross-calibration quality is a critical and high-value quality control task with direct impact on patient diagnosis and treatment course. The clinical impact and incidence of poor DXA quality control practices, and cross-calibration in particular, should be studied further.

Trabecular Bone Score (TBS) Cross-Calibration for GE Prodigy and IDXA Scanners.

Dual-energy X-ray absorptiometry (DXA) is used for osteoporosis diagnosis, fracture prediction and to monitor changes in bone mineral density (BMD). Change in DXA instrumentation requires formal cross-calibration and procedures have been described by the International Society for Clinical Densitometry. Whether procedures used for BMD cross-calibration are sufficient to ensure lumbar spine trabecular bone score (TBS) cross-calibration is currently uncertain. The Manitoba Bone Density Program underwent a program-wide upgrade in DXA instrumentation from GE Prodigy to iDXA in 2012, and a representative a sample of 108 clinic patients were scanned on both instruments. Lumbar spine TBS (L1-L4) measurements were retrospectively derived in 2013. TBS calibration phantoms were not available at our site when this was performed. We found excellent agreement for lumbar spine BMD, without deviation from the line of perfect agreement, and low random error (standard error of the estimate [SEE] 2.54% of the mean). In contrast, spine TBS (L1-L4) showed significant deviation from the line of identity: TBS(iDXA) = 0.730 x TBS(Prodigy) + 0.372 (p<0.001 for slope and intercept); SEE 5.12% of the mean with negative bias (r=-0.550). Results were worse for scans acquired in thick versus standard mode, but similar when the population was stratified as BMI < or > 35 kg/m2. In summary, it cannot be assumed that just because BMD cross-calibration is good that this applies to TBS. This supports the need for using TBS phantom calibration to accommodate between-scanner differences as part of the manufacturer's TBS software installation.

Comparison of the Lunar Prodigy and Stratos DR Dual-Energy X-Ray Absorptiometers to Assess Regional Bone Mineral Density.

PURPOSE: The first objective of the study was to assess the agreement between the Stratos DR (DMS) and the GE Prodigy (GE) DXAs in determining femoral neck, total hip and lumbar spine aBMD. The second objective was to assess the potential impact of leg positioning (hip flexed at 90° or not) on lumbar spine aBMD. METHODS: Forty-six individuals (n=42 women, 91.3%), with a mean age of 59.7 ± 13 years and mean BMI of 23.8 ± 4.7 kg/m², were scanned consecutively on the same day using the two devices. In a subgroup (n=30), two consecutive Stratos DR scans (with hip flexed at 90° or not) at the lumbar spine were conducted. Predictive equations for hip and lumbar spine aBMD were derived from linear regression of the data. RESULTS: Correlation coefficients for aBMD measured with the two DXAs were characterised by an R² of 0.76 for the femoral neck, 0.89 for the total hip, and 0.86 for the lumbar spine. However, the derived equations for aBMD determination showed an intercept significantly different from 0 for hip aBMD, and a slope significantly different from 1 for lumbar spine aBMD. These results highlight a bias between the two measurements, thus requiring the determination of specific cross-calibration equations for hip and lumbar spine, femoral neck excepted. When compared with values on the Prodigy, mean aBMD on the Stratos DR was higher at the femoral neck (+4.8%, p<0.001) and total hip (+9.6%, p<0.001) and lower at L2-L4 (-8.8%, p<0.001). The coefficient of variation (CV%) for the two consecutive measures at lumbar spine (with different positioning) with the Stratos DR was 2.9%. CONCLUSIONS: The difference in aBMD measured with the two DXAs illustrates the need to define cross-calibration equations when comparing data across systems in order to avoid erroneous conclusions.

Accuracy, Linearity and Precision of Spine QCT vBMD Phantom Measurements for Different Brands of CT Scanner: A Multicentre Study.

We describe a multicenter study using the European Spine Phantom (ESP) to compare the accuracy, linearity and precision of QCT measurements of spine vBMD between different brands of scanner, different models of the same brand and identical units of the same model. Ten scans of the same ESP with repositioning were performed on forty CT scanners from five manufacturers in different hospitals across China, all calibrated with the Mindways QCT system. The three ESP vertebral bodies simulating low (L1), medium (L2) and high (L3) vBMD and their average (L1-3 vBMD) were compared with phantom values. Linearity was assessed using the standard error of the estimate derived from linear regression. Precision errors were expressed as the standard deviation of the ten measurements on each scanner. Median (IQR) vBMD over all forty CT scanners compared with phantom values were: L1: 52.2 (49.9-56.4) vs 51.0; L2: 104.4 (101.2-108.6) vs 102.2; L3: 201.4 (195.0-204.9) vs 200.4; L1-3: 119.3 (116.6-123.2) vs 117.9 mg/cm3. Statistically significant differences in L1-3 vBMD were found between different brands (p= 0.005) and between different models of the same brand and identical units of the same model (both p< 0.001). Cross-calibration using linear regression gave a good fit for all forty systems with a median standard error of the estimate of 1.7 mg/cm3. The median precision error for L1-3 vBMD was 0.61 mg/cm3. Statistically significant differences in spine vBMD measurements between different scanners reinforce the importance of cross-calibration in multi-center studies. Cross-calibration can be reliably performed using linear regression equations.

Cross-Calibration of Prodigy and Horizon A Densitometers and Precision of the Horizon A Densitometer.

We performed this study to enable a reliable transition for clinical study participants and patients from a GE Lunar Prodigy to a Hologic Horizon A dual-energy X-ray absorptiometry (DXA) scanner and to assess the reproducibility of measurements made on the new DXA scanner. Forty-five older adults had one spine, hip, and total body scan on a Prodigy dual-energy X-ray absorptiometry (DXA) scanner and 2 spine, hip, and total body scans, with repositioning, on a new Hologic Horizon A DXA scanner. Linear regression models were used to derive cross calibration equations for each measure on the 2 scanners. Precision (group root-mean-square average coefficient of variation) of bone mineral density (BMD) of the total hip, femoral neck, and lumbar spine (L1-L4), and total body fat, bone, and lean mass, appendicular lean mass, and trabecular bone score (TBS) was assessed using the International Society of Clinical Densitometry's (ISCD's) Advanced Precision Calculation Tool. Correlation coefficients for the BMD and body composition measures on the 2 scanners ranged from 0.94 to 0.99 (p<0.001). When compared with values on the Prodigy, mean BMD on the Horizon A was lower at each skeletal site (0.136 g/cm2 lower at the femoral neck and 0.169 g/cm2 lower at the lumbar spine (L1-4)), fat mass was 0.47 kg lower, and lean mass was 4.50 kg higher. Precision of the Horizon A scans was 1.60% for total hip, 1.94% for femoral neck, and 1.25% for spine (L1-4) BMD. Precision of TBS was 1.67%. Precision of total body fat mass was 2.16%, total body lean mass was 1.26%, appendicular lean mass was 1.97%, and total body bone mass was 1.12%. The differences in BMD and body composition values on the 2 scanners illustrate the importance of cross-calibration to account for these differences when transitioning clinical study participants and patients from one scanner to another.

Multisite longitudinal calibration of HR-pQCT scanners and precision in osteogenesis imperfecta.

BACKGROUND: For high-resolution peripheral quantitative computed tomography (HR-pQCT) to be used in longitudinal multi-center studies to assess disease and treatment effects, data must be aggregated across multiple timepoints and scanners. This requires an understanding of the factors contributing to scanner precision, and multi-scanner cross-calibration procedures, especially for clinical populations with severe phenotypes, like osteogenesis imperfecta (OI). METHODS: To address this, we first evaluated single- and multi-center short- and long-term precision errors of standard HR-pQCT parameters. Two imaging phantoms were circulated among 13 sites (7 XtremeCT and 6 XtremeCT2) and scanned in triplicate at 3 timepoints/site. Additionally, duplicate in vivo radial and tibial scans were acquired in 29 individuals with OI. Secondly, we investigated subject- and scanner-related factors that contribute to precision errors using regression analysis. Thirdly, we proposed a reference site selection criterion for multisite cross-calibration and demonstrated the external validity of phantom-based calibrations. RESULTS: Our results show excellent short-term single-site precision in both phantoms (CV % < 0.5%) and in density, microarchitecture and finite element parameters of OI participants (CV % = 0.75 to 1.2%). In vivo reproducibility significantly improved with (i) cross sectional area image registration versus no registration and (ii) scans with no motion artifacts. While reproducibility was similar across OI subtypes and anatomical sites, XtremeCT2 scanners achieved ~2.5% better precision than XtremeCT for trabecular parameters. Finally, we demonstrate that multisite longitudinal precision errors resulting from inconsistencies between scanners can be partially corrected through scanner cross-calibration. CONCLUSIONS: This study is the first to assess long-term reproducibility and cross-calibration in a study using first and second generation HR-pQCT scanners. The results presented in this context provide timely guidelines for future use of this powerful clinical imaging modality in multi-center longitudinal clinical trials.

The Importance of Hydration in Body Composition Assessment in Children Aged 6-16 Years.

Body composition is associated with many noncommunicable diseases. The accuracy of many simple techniques used for the assessment of body composition is influenced by the fact that they do not take into account tissue hydration and this can be particularly problematic in paediatric populations. The aims of this study were: (1) to assess the agreement of two dual energy X-ray absorptiometry (DXA) systems for determining total and regional (arms, legs, trunk) fat, lean, and bone mass and (2) to compare lean soft tissue (LST) hydration correction methods in children. One hundred and twenty four healthy children aged between 6 and 16 years old underwent DXA scans using 2 GE healthcare Lunar systems (iDXA and Prodigy). Tissue hydration was either calculated by dividing total body water (TBW), by 4-component model derived fat free mass (HFFMTBW) or by using the age and sex specific coefficients of Lohman, 1986 (HFFMLohman) and used to correct LST. Regression analysis was performed to develop cross-calibration equations between DXA systems and a paired samples t-test was conducted to assess the difference between LST hydration correction methods. iDXA resulted in significantly lower estimates of total and regional fat and lean mass, compared to Prodigy. HFFMTBW showed a much larger age/sex related variability than HFFMLohman. A 2.0 % difference in LST was observed in the boys (34.5 kg vs 33.8 kg respectively, p < 0.05) and a 2.5% difference in the girls (28.2 kg vs 27.5 kg respectively, p < 0.05) when corrected using either HFFMTBW or HFFMLohman. Care needs to be exercised when combining data from iDXA and Prodigy, as total and regional estimates of body composition can differ significantly. Furthermore, tissue hydration should be taken into account when assessing body composition as it can vary considerably within a healthy paediatric population even within specific age and/or sex groups.

DXA body composition corrective factors between Hologic Discovery models to conduct multicenter studies.

BACKGROUND: Dual X-ray absorptiometry body composition measurements are widely used for clinical and research settings. It is well known that measurements vary across instruments, needing caution for longitudinal monitoring or multicentric studies. This study was to quantify intra- and inter-center variability of bone mineral content, bone mineral density, fat and lean body composition measurements between Hologic Discovery models in order to calculate the corrective factors to be applied for multicenter research projects. MATERIALS AND METHODS: A whole body phantom composed of materials representing the thickness and percentage of bone, lean and fat mass in the human physiological range was analyzed ten times in three different centers using dual energy X-ray absorptiometry scanners (Two Hologic Discovery QDR A and one QDR W). In addition, we used a morphometric vertebral phantom to monitor stability and a three steps block phantom to check accuracy. RESULTS: We found a good long-term stability and accuracy for the three devices. Intra-center coefficients of variation were within the range of the manufacturer acceptable values (bone mineral density: 1.40%, bone mineral content: 1%, area: 1.50%, fat mass: 0.89%, lean mass: 0.76%, total mass: 0.12%). Whereas the inter-center coefficient of variation exceeded 8% (bone mineral density: 8.18%, bone mineral content: 3.03%, area: 8.63%: fat mass: 3,92%, lean mass: 7.89%, total mass: 2.85%). CONCLUSION: Our study showed that the discrepancies across centers remain a major concern, particularly with regard to body composition results. Our study highlight the need of cross calibration between densitometers and proposes corrective factors evaluated from a whole body phantom to lead multicentric studies adjustment.

Examination of cross-calibration and concentration linearity with quantitative gallium-67 single-photon emission computed tomography: phantom experiment.

We evaluated whether scattered radiation should be considered for cross-calibration and concentration linearity with quantitative gallium-67 (67Ga) single-photon emission computed tomography (SPECT). The scanned data from cylinder and spherical phantoms were used. They were reconstructed using ordered subset expectation maximization with resolution recovery, scatter, and computed tomography (CT)-based attenuation correction. The standardized uptake values (SUVs) of the cylinder phantom SPECT/CT images were calculated using system planar sensitivity with and without scatter correction, and the results were compared with the theoretical value. To determine concentration linearity, the relationship between the measured SUVs in three different spherical phantoms was evaluated. SUVs calculated by system planar sensitivity without scatter correction were closer to the theoretical values. Furthermore, the 37-mm sphere showed proper radioactive linearity. Our study suggests the utility of the SUV for 67Ga SEPCT/CT. Nevertheless, additional studies are required.

Comparison of bioimpedance body composition in young adults in the Russian Children's Study.

BACKGROUND & AIMS: Body mass index is a simple anthropometric measure (kg/m2) used as an indirect estimate of body fat in individuals, and in assessments of population health and comparisons between populations. Bioelectrical impedance analysis (BIA) is often used to provide additional information on body fat and fat-free mass, and has been used to generate body composition reference data in national health surveys. However, BIA measurements are known to be device-specific and there are few published studies comparing results from different BIA instruments. Therefore, we compared the performance of two BIA instruments in the Russian Children's Study (RCS) of male growth, pubertal development and maturation. METHODS: Paired BIA measurements were obtained using the Tanita BC-418MA (Tanita Corp., Tokyo, Japan) and ABC-01 'Medas' (Medas Ltd, Moscow, Russia) BIA instruments. Cross-sectional data on 236 RCS subjects aged 18-22 years were used for the BIA comparison and the development of a conversion formula between measured resistances; follow-up data (n = 96) were used for validation of the conversion formula. RESULTS: Whole-body resistances were highly correlated (Spearman rho = 0.95), but fat mass (FM) estimates were significantly higher with the Medas than the Tanita device (median difference 3.3 kg, 95% CI: 2.9, 3.6 kg) with large limits of agreement (LoA) for the FM difference (-2.0, 8.6 kg). A conversion formula between the resistances (Res) was obtained: Medas Res = 0.882 × Tanita Res+26.2 (r2 = 0.91, SEE = 17.6 Ohm). After applying the conversion formula to Tanita data and application of the Medas assessment algorithm, the 'converted' Tanita FM estimates closely matched the Medas original estimates (median difference -0.1 kg, 95% CI: -0.3, 0.2 kg), with relatively small LoA for the FM difference (-2.3 to 2.1 kg), suggesting potential interchangeability of the ABC-01 'Medas' and Tanita BC-418MA data at the group level. CONCLUSIONS: Our results support the importance of cross-calibration of BIA instruments for population comparisons and proper data interpretation in clinical and epidemiological studies.

A Cross-Calibration Study of GE Lunar iDXA and GE Lunar DPX Pro for Body Composition Measurements in Children and Adults.

OBJECTIVE: To cross-calibrate dual energy X-ray absorptiometry machines when replacing GE Lunar DPX-Pro with GE Lunar iDXA. METHODS: A cross-sectional study was conducted in 126 children (3-19 years) and 135 adults (20-66 years). Phantom cross calibration was carried out using aluminum phantom provided with each of the machines on both machines. Total body less head (TBLH), lumbar spine (L2-L4) and left femoral neck bone mineral density (BMD), bone mineral content (BMC), and bone area were assessed for each patient on both machines. TBLH lean and fat mass were also measured. Bland-Altman analysis, linear regressions, and independent sample t test were performed to evaluate consistency of measurements and to establish cross-calibration equations. RESULTS: iDXA measured 0.33% lower BMD and 0.64% lower BMC with iDXA phantom as compared to DPX-Pro phantom (p < 0.001). In children, TBLH-BMC, femoral BMC and area were measured 10%-14% lesser, TBLH area was higher by 1%-2% and L2-L4 area by 10%-14% by iDXA as compared to DPX-Pro. iDXA measured higher TBLH fat [15% (girls), 31% (boys)] than DPX-Pro. In adults, TBLH-BMD (1.7%-3.4%), BMC (6.0%-10.9%) and area (4.2%-7.6%) were measured lesser by iDXA than DPX-Pro. L2-L4 BMD was higher [2.7% (men), 1.8% (women)] by iDXA than DPX-Pro. Femoral BMC was 2.11% higher in men and 4.1% lower in women by iDXA as compared to DPX-Pro. In children, R2 of cross-calibration equations, ranged from 0.91 to 0.96; in adults, it ranged from 0.93 to 0.99 (p < 0.01). After the regression equations were applied, differences in BMD values between both machines were negligible. CONCLUSION: A strong agreement for bone mass and body composition was established between both machines. Cross-calibration equations need to be applied to transform DPX-Pro measurements into iDXA measurements to avoid errors in assessment. This study documents a need for use of cross-calibration equations to transform DPX-Pro body composition data into iDXA values for clinical diagnosis.

Measurement of the small field output factors for 10 MV photon beam using IAEA TRS-483 dosimetry protocol and implementation in Eclipse TPS commissioning.

Dosimetry of small fields (SF) is vital for the success of highly conformal techniques. IAEA along with AAPM recently published a code of practice TRS-483 for SF dosimetry. The scope of this paper is to investigate the performance of three different detectors with 10 MV with-flatting-filter (WFF) beam using TRS-483 for SF dosimetry and subsequent commissioning of the Eclipse treatment planning system (TPS version-13.6) for SF data. SF dosimetry data (beam-quality TPR20,10(10), cross-calibration, beam-profile, and field-output-factor(F.O.F)) measurements were performed for PTW31006-pinpoint, IBA-CC01 and IBA-EFD-3G diode detectors in nominal field size (F.S) range 0.5 × 0.5cm2to 10 × 10 cm2with water and solid water medium using Varian Truebeam linac. However, Eclipse-TPS commissioning data was acquired using IBA-EFD-3G diode, and absolute dose calibration was performed with FC-65G detector. The dosimetric performance of the Eclipse-TPS was validated using TLD-LiF chips, IBA-PFD, and IBA-EFD-3G diodes. Dosimetric performance of the PTW31006-pinpoint, IBA-CC01, and IBA-EFD-3G detectors was successfully tested for SF dosimetry. The F.O.Fs were generated and found in close agreement for all F.S except 0.5 × 0.5cm2. It is also found that TPR20,10(10) value can be derived within 0.5% accuracy from a non-reference field using Palmans equation. Cross-calibration can be performed in F.S 6 × 6 cm2with a maximum variation of 0.5% with respect to 10 × 10cm2. During profile measurement, the full-width half-maxima (FWHM) of F.S 0.5 × 0.5cm2was found maximum deviated from the geometric F.S. In addition, Eclipse-TPS was commissioned along with some limitations: F.O.F below F.S 1 × 1cm2was ignored by TPS, PDD and profiles were dropped from configuration below F.S 2 × 2 cm2, and F.O.F which does not satisfy the condition 0.7 < A/B < 1.4 (A and B are FWHM in cross-line and in-line direction) have higher uncertainty than specified in TRS-483. Validation tests for Eclipse-TPS generated plans were also performed. The measured dose was in close agreement (3%) with TPS calculated dose up to F.S 1.5 × 1.5cm2.

Cross-calibration, Least Significant Change and Quality Assurance in Multiple Dual-Energy X-ray Absorptiometry Scanner Environments: 2019 ISCD Official Position.

In preparation for the International Society for Clinical Densitometry Position Development Conference (PDC) 2019 in Kuala Lumpur, Malaysia, a cross-calibration and precision task force was assembled and tasked to review the literature, summarize the findings, and generate positions to answer 4 related questions provided by the PDC Steering Committee, which expand upon the current ISCD official positions on these subjects. (1) How should a provider with multiple dual-energy X-ray absorptiometry (DXA) scanners of the same make and model calculate least significant change (LSC)? (2) How should a provider with multiple DXA systems with the same manufacturer but different models calculate LSC? (3) How should a provider with multiple DXA systems from different manufacturers and models calculate LSC? (4) Are there specific phantom procedures that one can use to provide trustworthy in vitro cross calibration for same models, different models, and different makes? Based on task force deliberations and the resulting systematic literature reviews, 3 new positions were developed to address these more complex scenarios not addressed by current official positions on single scanner cross calibration and LSC. These new positions provide appropriate guidance to large multiple DXA scanner providers wishing to offer patients flexibility and convenience, and clearly define good clinical practice requirements to that end.