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

Laurent Maïmoun, Krishna Kunal Mahadea, Sandrine Alonso, Thierry

Chevallier, Pierre-olivier Kotzki, Thibault Mura, Vincent Boudousq

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Laurent Maïmoun, Krishna Kunal Mahadea, Sandrine Alonso, Thierry Chevallier, Pierre-olivier Kotzki, et al.. Comparison of the Discovery A and Stratos DR densitometers for assessing whole-body and regional bone mineral density and body composition. Clinical Physiology and Functional Imaging, In press, 10.1111/cpf.12836. hal-04105942

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

Laurent Maïmoun1,2 | Krishna Kunal Mahadea3 | Sandrine Alonso4 | Thierry Chevallier4,5 |
Pierre-Olivier Kotzki6,7 | Thibault Mura4 | Vincent Boudousq6,7

1 Service de Médecine Nucléaire, Hôpital Lapeyronie, CHU de Montpellier, Montpellier, France

2 Physiologie et Médecine Expérimentale du Cœur et des Muscles (PhyMedEx), INSERM, CNRS, Université de Montpellier (UM), Montpellier, France

3 Université de Montpellier, Montpellier, France

4 Department of Biostatistics, Clinical Epidemiology, Public Health, and Innovation in Methodology, Nimes University Hospital, University of Montpellier, Nimes, France

5 Institut Desbrest d'Epidémiologie et de Santé Publique UMR INSERM - Université de Montpellier (UM), Montpellier, France

6 Service de Médecine Nucléaire, Hôpital Carémeau, CHU de Nîmes, Nîmes, France

7 IRCM, Institut de Recherche en Cancérologie de Montpellier, INSERM U1194, Université de Montpellier, Institut Régional du Cancer de Montpellier, Montpellier, France

Correspondence

Laurent Maïmoun, Département de Biophysique, Université Montpellier, Service de Médecine Nucléaire, Hôpital Lapeyronie, 371, Ave du Doyen Gaston Giraud, 34295 Montpellier, France.

Email:

l-maimoun@chu-montpellier.fr

KEYWORDS

body composition, bone mineral density (BMD), cross-calibration, Discovery A, dual X-ray absorptiometry (DXA), Stratos DR, visceral adipose tissue
# Abstract

**Purpose:**

The agreement between the Stratos DR and Discovery A densitometers was assessed for measurements of whole-body (WB) and regional fat mass (FM), fatfree 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.

## 1 | INTRODUCTION

Dual-energy X-ray absorptiometry (DXA) was originally designed to determine bone mineral density (BMD), a parameter associated with fracture risk (Consensus development conference, 1991). DXA is the reference technique for the evaluation of BMD because it is noninvasive and characterized by low radiation and high precision and reproducibility, making it useful to monitor changes in BMD over time and determine treatment efficacy (Powers et al., 2015). Moreover, DXA can also be used to determine whole-body (WB) and regional body composition (fat mass [FM, kg, %] and fat-free soft tissue [FFST, kg]). Although this technology is not considered the gold standard for these analyses in comparison
with other techniques (4-compartiment model, magnetic resonance imaging [MRI] and computed tomography [CT]), it is currently favoured by many clinicians and researchers. This is due notably to its low equipment costs, the speed of the scan and its high precision and reproducibility (Cruz-Jentoft et al., 2019; Donini et al., 2022). In addition, segmental analysis may be important at times, given that trunk FM, for example, is more closely associated with diseases like dyslipidaemia and insulin resistance than are other segmental regions (Van Pelt et al., 2002). The DXA technique has shown its pertinence in clinical and research domains (Albanese et al., 2003) and in pathologies inducing an alteration of body composition, such as anorexia nervosa and obesity (Bazzocchi et al., 2016; El Ghoch et al., 2015; Maïmoun et al., 2020). In the elderly, the loss of FFST with age (Shaw et al., 2007) has been identified as the major factor of invalidity and low quality of life (Roubenoff, 2000), and one part of the sarcopenia definition is based on cut-offs calculated from localized (i.e., upper and lower limbs) FFST measures (Cruz-Jentoft et al., 2019). In addition to the initial analysis of a patient, the follow-up of changes in body composition is arguably of greater interest in clinical cases of the rapid gain or loss of body weight present in anorexia nervosa (El Ghoch et al., 2015) and obesity (Bazzocchi et al., 2015). Thus, it is necessary when measurement is repeated to distinguish between a true biological change in body composition and a random fluctuation related to variability in the measurement procedure (El Maghraoui et al., 2005), which may have many causes (device errors, technician variability, etc.) (Phillipov et al., 2001). Yet, this distinction becomes particularly difficult when measurements are performed on different devices from different manufacturers, given the aBMD and body composition calibration differences. For these reasons, the follow-up of a patient should be performed on the same device. In the situation of an older DXA being replaced by a new DXA or when a multicentre study is performed, the International Society for Clinical Densitometry (ISCD) recommends a cross-calibration study between devices to ensure consistent results (Shuhart et al., 2019). Stratos DR was developed by DMS/APELEM®, but there are no published data to date on crosscalibration with any of the devices that are widely available in clinical centres, such as the Discovery A (Hologic®).

Thus, the first aim of this study was to produce translational regression equations to compare the scans of the Stratos DR and the Discovery A for WB BMD and for WB and regional body composition (FM and FFST). The second aim was to evaluate the short-term in vivo precision of the Stratos DR.

# 2 | MATERIALS AND METHODS

## 2.1 | Participants

The sample consisted of patients admitted to the Department of Nuclear Medicine, Caremeau Hospital (Centre Hospitalier Universitaire de Nîmes, CHRU Nîmes, France), for an evaluation of BMD. Fifty individuals (n = 35 women, 70%), with a mean age of 48.0 ± 13.3 (range: 19–74 years) and a mean BMI of 31.5 ± 7.6 kg/m² (range: 15.3–49.6 kg/m²), were included in this study. According to the BMI classification, one patient was underweight (<18.5 kg/m²), 11 were normal weight (18.5–24.9 g/cm²), 10 were overweight (25–29.9 kg/m²), 11 were obese (30–34.9 kg/m²), and 17 were severely obese (>35.0 kg/m²). All participants were Caucasian and, to be eligible, they had to be over 18 years old, able to lie supine for 10–15 min, and have body weight < 160 kg or height < 192.5 cm (table weight limit restriction of the Discovery A system). Participants were excluded from the study if they
had a history of lumbar spine or proximal femur fracture, hip replacement or osteosynthesis and cementoplasty at the lumbar spine, were pregnant or breastfeeding, or had undergone an X-ray examination with the use of a contrast medium such as barium within the 7 days before this visit. In accordance with the ISCD recommendations (Shuhart et al., 2019), these groups are representative of those routinely scanned in our department.

## 2.2 | Study procedures

The study was approved by the Ethics Review Committee of Nîmes, France (Commission de Protection des Personnes, Sud Méditerranée III), and permission for the clinical trial was granted by the French Medicine and Healthcare Products Regulatory Agency (ID RCB: 2015-A00987-42). All participants were volunteers and all gave informed signed consent before the scans. All activities performed in this study were in accordance with the Declaration of Helsinki. Standing height was measured with a stadiometer to the nearest 0.1 cm and recorded as the mean of two consecutive measurements. Body weight was measured with a calibrated scale having a precision of 0.1 kg. Body mass index (BMI) was calculated as weight (kg) divided by the square of height (m).

## 2.3 | Dual-energy X-ray absorptiometry measurements

As the two systems were situated at the same site, each participant was scanned consecutively on the same day with the Discovery A (Hologic; software version 12.6.1) and the Stratos DR (DMS, Mauguio, France, software version 4.0.2.3) within a 1-h period by the same operator. Participants wore the same light clothing with all metal and plastic artefacts removed. The Discovery A was used as the reference device for this comparison study. A WB scan was used to determine WB BMD, as well as body composition (i.e., FM and FFST) at the whole body and several subregions (i.e., arms, trunk, legs, gynoid, android and visceral adipose tissue [VAT]). These measurements were performed following the procedures described in each densitometer's operating manual. Calibration block quality assurance and encapsulated spine phantom quality control scans were performed on each device at the start of each scanning day.

## 2.4 | Scan procedure

This procedure was previously described in detail (Maïmoun et al., 2017). Briefly, participants assumed a stationary supine position and were centred on the scanner table with the head, neck and torso positioned parallel to the long axis of the scan bed and the shoulder and pelvis positioned perpendicular to it. Their arms were out to the sides, with the legs internally rotated to 45° and fixed together with strapping tape to minimize incidental movement, with the feet pointed downward. We scrupulously followed the manufacturer's standard scan and positioning protocols. The full-body images were separated into axial (trunk), appendicular (arms and legs) and gynoid, android and VAT regions using the predefined and mandatory WB model, as required by the software.

To evaluate the repeatability of the Stratos DR, WB composition was evaluated twice successively in a subgroup of participants (n = 29). The participants got off the DXA table between the two scans so that they could be repositioned for the second scan. The two evaluations were performed at whole body to determine WB BMD, as well as body composition (i.e., FM and FFST) at the whole body and subregions (i.e., arms, trunk, legs, gynoid, android and VAT). All scans were performed by the same technician, who analysed each scan individually.
For the cross-calibration equations and the repeatability assessment, voluntary patients meeting the inclusion criteria were included consecutively for a period of 6 months.

**2.5 | Statistical analysis**

Quantitative data are expressed as mean ± standard deviation (SD) or median with 25th and 75th percentiles ([25th percentile–75th percentile]) according to the variable distribution. Qualitative variables are expressed as frequency with percentage.

The reproducibility of measurements was assessed by calculating the systematic difference between the Discovery A measurements and the Stratos DR measurements (systematic bias) and tested against the 0 value using a paired Student's t test. We then estimated an intraclass correlation coefficient (ICC) with its 95% confidence interval (95% CI) (Lachin, 2004) for each measurement. ICC is considered to be excellent over 0.9, acceptable over 0.8, weak over 0.6 and inexistent below. Cross-calibration equations were estimated using Deming regression to generate reversible conversion for translating Discovery A results to Stratos DR results or vice versa, incorporating estimates of measurement error for both measurement methods. Measurement errors were assumed to be independent and normally distributed. Slope and intercept 95% CI were estimated using the Jackknife method (Linnet, 1993). A published SAS macro was used (Canchola and Oza, 2022). The λ parameter for Deming regression was estimated by the Sxx/Syy ratio. Reproducibility between DXA measurements converted using the cross-calibration equations and measurements obtained with Stratos DR was assessed using the ICC and its 95% confidence interval.

Correlations were assessed using Pearson correlation coefficients (with 95% CI). Agreement between the two measurements was assessed using Bland-Altman plots (Bland & Altman, 1986).

The repeatability of the Stratos DR was assessed using an ICC. The precision parameters between two successive measurements, such as the precision error expressed as the root mean square of standard deviation (RMS-SD) coefficient of variation CV (%) and the resulting least significant change (LSC) at 95% CI, were calculated as recommended by the ISCD (Shuhart et al., 2019). The percentage of change between two measurements for the same subject was expected to be less than the LSC for 95% of the pairs of observations. Thus, when the percentage of change was greater than LSC, there was 95% confidence that a true change had occurred.

Our sample size was established according to ISCD recommendations (Shuhart et al., 2019).

All analyses were performed using SAS software version 9.4 (SAS Institute Inc.).
<table><caption>TABLE 1 Characteristics of the study population.</caption><thead><tr><th rowspan="2">Participants</th><th colspan="2">Reproducibility (n = 50)</th><th colspan="2">Repeatability (n = 29)</th></tr><tr><th>Mean ± SD</th><th>Range</th><th>Mean ± SD</th><th>Range</th></tr></thead><tbody><tr><td>Age (years)</td><td>48.0 ± 13.3</td><td>19-74</td><td>46.2 ± 12.6</td><td>19-69</td></tr><tr><td>Weight (kg)</td><td>86.1 ± 23.0</td><td>33.5-146.0</td><td>91.6 ± 22.4</td><td>45-146</td></tr><tr><td>Height (cm)</td><td>164.8 ± 8.3</td><td>148-180</td><td>164.3 ± 8.4</td><td>150-80</td></tr><tr><td>BMI (kg/m²)</td><td>31.5 ± 7.6</td><td>15.3-49.6</td><td>33.7 ± 7.3</td><td>20-49.6</td></tr><tr><td>Sex [Male/<br>Female]<br>(number/%)</td><td>15 (30)/35 (70)</td><td>-</td><td>7 (24.1)/<br>22 (75.9)</td><td>-</td></tr></tbody></table>

Note: Data are given by mean ± SD.

Abbreviation: BMI, body mass index.

3 | RESULTS

Characteristics of the study population are given in Table 1. A total of 50 participants (15 men and 35 women), with a mean age of 48.0 ± 13.3 years and a mean BMI of 31.5 ± 7.6 kg/m², participated in the reproducibility study. Twenty-nine participants (7 men and 22 women), with a mean age of 46.2 ± 12.6 years and a BMI of 33.7 ± 7.3 kg/m², participated in the repeatability study. The repartition of participants according to BMI class is presented in Table 2.

Results of the comparisons of mean FM, FFST, BMD and bone mineral content (BMC) measured by the Stratos DR and Discovery A are given in Table 3. FM and FFST measured with the two devices were highly correlated, with a coefficient of correlation ranging from 0.80 to 0.99 (for all measures p < 0.0001). However, there was a statistically significant measurement bias (p values ranging from 0.0135 to p < 0.0001) between the Stratos DR and Discovery A for all measurements, except for android FM and WB BMD, which showed a bias with a nonsignificant tendency (p = 0.058 and p = 0.051, respectively). Compared to Discovery A, Stratos DR underestimated FM, FFST and BMD for the whole body and regional areas, with the exception of trunk FM, VAT (mass, area and volume) and BMC, which were overestimated. The systematic differences are depicted in Figures 1 and 2 with Bland-Altman analyses (Stratos DR vs. Discovery A). For patients with the highest BMI, the arms could extend slightly beyond the measurement range of the DXA. However, the
difference between the two arms was found to be very small and all the patients were conserved for the final statistical analysis.

<table><caption>TABLE 2 Repartition of participants according to body mass index class.</caption><thead><tr><th>BMI class</th><th>&lt;18.5</th><th>[18.5-25]</th><th>[25-30]</th><th>[30-35]</th><th>&gt;35</th></tr></thead><tbody><tr><td>Number of participants for reproducibility (n = 50)</td><td>1</td><td>11</td><td>10</td><td>11</td><td>17</td></tr><tr><td>Number of participants for repeatability (n = 29)</td><td>0</td><td>4</td><td>7</td><td>4</td><td>14</td></tr></tbody></table>

Abbreviation: n, number.

As the subjects participating in this study presented a large dispersion of BMI, ranging from 15.3 to 49.6 kg/m², the concordance of measurements between Startos DR and Discovery A was analysed according to two specific classes of BMI (<30 kg/m²; n = 22 and ≥30 kg/m²; n = 28) (Supporting Information: Materials 1). For most body compartments, the bias between the two measurements was higher in the group with the BMI ≥ 30 kg/m² compared to <30 kg/m², suggesting that the value of BMI may have modified the concordance of the measurement between the two DXA devices.

Due to the observed differences between the two densitometers, Deming regression cross-calibration equations were performed and are presented in Table 4.

## 3.1 | Stratos DR in vivo repeatability

The repeatability of the measurements for regional and total body FM, FFST, BMD and BMC are presented in Table 5. The Bland-Altman plot (Figures 3 and 4) illustrates the random variability observed between each of the two measurements. Precision error, when represented by RMS-CV% for FM, ranged from 1.4% for WB to 3.0% for the gynoid and android regions. For FFST, it ranged from 1.0% for WB to 2.2% for trunk. However, the agreement between the two measurements was altered for FM and FFST at the arms (ICC ≥ 0.90, 95% CI: 0.80–0.95), characterized by an RMS-CV% of 8% and 8.8%, respectively.

When the same site was considered, a systematically better precision for FFST compared to FM was observed (arm: 8% vs. 8.8%, trunk: 2.2% vs. 2.8%, leg: 2% vs. 2.5%, and whole body: 1.0% vs. 1.4%).

The RMS-SD for VAT mass was 203.6 g (average: 1580.7 ± 1194.6 g), corresponding to 15.9% CV (Table 5).

The RMS-SD for WB BMD and WB BMC was 0.018 g/cm² (average: 1.182 ± 0.161 g/cm²) and 38.2 g (average 2646.2 ± 476.4 g), respectively, corresponding to 1.4% CV for the two parameters. The LSC were 0.050 g/cm² (SD) and 105.7 g (SD) for WB BMD and WB BMC, respectively, and 4.0% (%) for the two parameters was considered a significant biological change.
<table><caption>TABLE 3 Comparison of fat mass, fat free soft tissue and bone mineral density measured by Strata DR and Discovery A at whole body and specific regions.</caption><thead><tr><th>Site</th><th>Strata DR</th><th>Discovery A</th><th>Bias</th><th>p Value for Bias</th><th>Mean relative change (%) with 95% CI</th><th>r (p Value)</th><th>ICC (95% CI)</th></tr></thead><tbody><tr><td colspan="8">Fat mass (%)</td></tr><tr><td>Arm</td><td>1457.7 ± 563.8</td><td>1826.8 ± 733.0</td><td>349.1 ± 351.4</td><td>0.0001</td><td>2435 (17.78-30.93)</td><td>0.89; p < 0.0001</td><td>0.73 (0.57-0.84)</td></tr><tr><td>Trunk</td><td>18234.6 ± 9284.0</td><td>17421.1 ± 9314.0</td><td>-713.5 ± 3266.7</td><td>0.0002</td><td>-549 (-8.01 to 30.93)</td><td>0.99; p < 0.0001</td><td>0.99 (0.98-0.97)</td></tr><tr><td>Leg</td><td>5942.7 ± 2233.0</td><td>5578.1 ± 2442.2</td><td>335.4 ± 695.3</td><td>0.0013</td><td>761 (-0.18 to 15.40)</td><td>0.96; p < 0.0001</td><td>0.95 (0.91-0.97)</td></tr><tr><td>Arterial</td><td>3139.2 ± 6 ± 1802.1</td><td>391.1 ± 2434.6</td><td>181.8 ± 1389.1</td><td>0.0577</td><td>889 (-1.49 to 19.27)</td><td>0.82; p < 0.0001</td><td>0.78 (0.65-0.87)</td></tr><tr><td>Cardiac</td><td>5218.2 ± 2121.9</td><td>5550.8 ± 2314.5</td><td>232.6 ± 491.1</td><td>0.0016</td><td>364 (0.93-6.35)</td><td>0.98; p < 0.0001</td><td>0.97 (0.95-0.98)</td></tr><tr><td>Whole body</td><td>37340.8 ± 13887.8</td><td>33655.9 ± 14805.1</td><td>1315.2 ± 2108.1</td><td>0.0001</td><td>340 (1.15-5.68)</td><td>0.99; p < 0.0001</td><td>0.99 (0.98-0.99)</td></tr><tr><td colspan="8">Viseral adipose tissue</td></tr><tr><td>VAT mass (g)</td><td>1417.0 ± 1277.4</td><td>703.7 ± 445.3</td><td>-713.2 ± 884.0</td><td>0.0001</td><td>-1614 (-37.06 to 4.77)</td><td>0.92; p < 0.0001</td><td>0.39 (0.13-0.60)</td></tr><tr><td>VAT area (cm²)</td><td>329.3 ± 156.3</td><td>346.0 ± 92.4</td><td>-63.3 ± 81.0</td><td>0.0001</td><td>-2224 (-29.29 to -15.09)</td><td>0.91; p < 0.0001</td><td>0.70 (0.53-0.82)</td></tr><tr><td>VAT volume (cm³)</td><td>1491.6 ± 1344.6</td><td>760.7 ± 481.4</td><td>-730.8 ± 920.1</td><td>0.0001</td><td>-1389 (-26.36 to 7.58)</td><td>0.92; p < 0.0001</td><td>0.41 (0.15-0.62)</td></tr><tr><td colspan="8">FFST (g)</td></tr><tr><td>Arm</td><td>2478.8 ± 666.7</td><td>2661.0 ± 920.9</td><td>182.2 ± 460.4</td><td>0.0001</td><td>668 (3.61-13.76)</td><td>0.89; p < 0.0001</td><td>0.82 (0.71-0.89)</td></tr><tr><td>Trunk</td><td>24440.0 ± 6452.9</td><td>27387.0 ± 6968.4</td><td>3176.9 ± 3535.3</td><td>0.0001</td><td>1354 (11.76-15.31)</td><td>0.98; p < 0.0001</td><td>0.87 (0.78-0.92)</td></tr><tr><td>Leg</td><td>8361.4 ± 2304.5</td><td>8346.9 ± 2131.4</td><td>185.5 ± 303.6</td><td>0.0001</td><td>803 (-534 to 21.40)</td><td>0.89; p < 0.0001</td><td>0.89 (0.82-0.94)</td></tr><tr><td>Whole body</td><td>49254.7 ± 12115.1</td><td>53843.3 ± 13188.2</td><td>4588.5 ± 2798.5</td><td>0.0001</td><td>970 (7.70-11.69)</td><td>0.98; p < 0.0001</td><td>0.91 (0.85-0.95)</td></tr><tr><td>Whole body BMD (g/cm³)</td><td>1173 ± 0.184</td><td>1204 ± 0.148</td><td>0.031 ± 0.09</td><td>0.0512</td><td>356 (0.76-6.35)</td><td>0.82; p < 0.0001</td><td>0.77 (0.63-0.84)</td></tr><tr><td>Whole body BWC (g)</td><td>2994.2 ± 556.4</td><td>2515.3 ± 575.8</td><td>-58.9 ± 562.6</td><td>0.0015</td><td>-219 (-4.55 to 0.16)</td><td>0.96; p < 0.0001</td><td>0.95 (0.91-0.97)</td></tr></tbody></table>

Note: Data are given by mean ± SD. Mean relative change is calculated as (Discovery A - Strata DR)/Discovery A. Bias is defined as the Pearson coefficient of correlation between the two measurements performed by Strata DR and Discovery A. p Values are for paired two-way comparisons using a paired Student's t test.

Abbreviations: CI, confidence interval; ICC, Intraclass correlation coefficient; FFST, fat-free soft tissue; Bias is defined as the mean difference between Discovery A and Strata DR measurements.
<figure><img src="image_1.png" /><figcaption>**FIGURE 1** Correlations between fat mass values measured by Stratos DR and Discovery A (Solid line is deming regression line, Dashed line is line of identity) and Bland-Altman plot of Discovery A and Stratos DR for fat mass. VAT, visceral adipose tissue.</figcaption></figure>

<figure><img src="image_2.png" /><figcaption>**FIGURE 2** Correlations between fat-free soft tissue (FFST) values or whole body BMD and BMC values measured by Stratos DR and Discovery A and Bland-Altman plot of Discovery A and Stratos DR. BMC, bone mineral content; BMD, bone mineral density.</figcaption></figure>

4 | DISCUSSION

This study aimed to assess the agreement of the two DXA systems (Stratos DR and Discovery A) and our results clearly demonstrated the need to cross-calibrate these systems from two manufacturers. The short-term in vivo precision of the Stratos DR was also analysed for standard parameters (WB BMD, BMC, FM and FFST) and less investigated parameters (gynoid FM, android FM and VAT).
Using the methodology recommended by the ISCD for crosscalibrating two DXA (scanning at least 30 participants twice on the new system and once on the old on a representative sample of the facility's patient population at the anatomical sites most commonly measured) (Shuhart et al., 2019), we identified significant differences between the Stratos DR and Discovery A for all the measurements. Thus, compared to Discovery A, the Stratos DR tended to underestimate WB BMD and WB and regional FM and FFST and tended to overestimate trunk FM and VAT. Inter-device differences ranged from 3.6% for WB BMD to 24.4% for FM at the arm. The results concerning BMD were in line with previous results showing a similar range of differences between DXA devices produced by different manufacturers such as Discovery A and Stratos produced by the same manufacturer, DMS® (Nalda et al., 2011). Nevertheless, compared to other DXA devices that have benefited from numerous cross-calibration evaluations, such as iDXA versus Prodigy (Choi et al., 2009; Hind et al., 2015), this is the first study to compare the Stratos DR with the Discovery A, and we therefore have no basis for comparisons. In line with the ISCD recommendations concerning the measurement differences between two DXA that exceed 1% in all regions of interest (Shuhart et al., 2019), we generated reversible equations for translating Discovery A results to Stratos DR results and vice versa to ensure the comparability of the acquired data. These equations may be used when a scanner is replaced during a longitudinal study or when data from multicentres are merged (Shuhart et al., 2019). After applying the correction coefficients, the differences between these two DXA measures were negligible. We noted that patient BMI influenced the bias between the two devices, as indicated by the systematically greater difference in the measurements from participants with $BMI \ge 30 \text{ kg/m}^2$ compared to those with $BMI < 30 \text{ kg/m}^2$. Moreover, for larger subjects who did not fit within the constraints of the scanning field, the hands were placed laterally against the hip, whereas current DXA protocol guidelines recommend positioning the hands with palms flat against the densitometer table (Hangartner et al., 2013). Yet, this adapted position may induce a post-scan technician error associated with the difficulty of performing a precise demarcation of landmarks between trunk and arm (Knapp et al., 2012; Rothney et al., 2012). The higher bias found at the arms in patients with the highest BMI confirmed these hypotheses. Other technological issues have been identified that may also contribute to the differences between two densitometers, including the procedure of image acquisition and software analysis (Covey et al., 2010).

The recent developments in DXA technology and software enabled us to determine not only FM and FFST for the whole body, but also at specific regions that have greater clinical relevance. For example, the android/gynoid fat ratio is strongly and positively correlated with glycated haemoglobin (Konieczna et al., 2019). Moreover, VAT determination with DXA is not inferior to that obtained with gold standard techniques (CT or MRI) (Goldberg & Fung, 2020; Micklesfield et al., 2012; Neeland et al., 2016), and VAT is more associated with higher cardiometabolic risk and insulin resistance than subcutaneous adipose tissue (Kuk et al., 2006). Consequently, these parameters must also be subject to crosscalibration between DXA devices. Compared with android FM (r = 0.83), the gynoid FM and VAT as measured with the Stratos DR and Discovery A appeared strongly correlated (r = 0.98 and r = 0.92, respectively). A previous preliminary study also reported a good correlation (r² = 0.88) between VAT estimated with Stratos DR and Lunar iDXA in 58 subjects with BMI ranging from 15.4 to 39.7 kg/m² (Geitner et al., 2017). Nevertheless, the presence of bias between the two DXA devices also justified the development of specific crosscalibration equations for each of these parameters.
<table><caption>TABLE 4 Cross-calibration equations relating Stratos DR and Discovery A.</caption><thead><tr><th>Sites</th><th>Slope [95% CI]</th><th>Intercept [95% CI]</th><th>ICC [95% CI] after conversion</th></tr></thead><tbody><tr><td colspan="4">Fat mass (g)</td></tr><tr><td>Arm</td><td>0.723 [0.602-0.845]</td><td>150.91 [-32.03 to 333.86]</td><td>0.89 [0.82-0.94]</td></tr><tr><td>Trunk</td><td>0.997 [0.944-1.049]</td><td>770.66 [-67.90 to 1609.22]</td><td>0.99 [0.98-0.99]</td></tr><tr><td>Leg</td><td>0.908 [0.825-0.990]</td><td>180.15 [-338.73 to 699.02]</td><td>0.96 [0.93-0.98]</td></tr><tr><td>Total</td><td>0.937 [0.909-0.965]</td><td>805.51 [-316.35 to 1927.36]</td><td>0.99 [0.98-0.99]</td></tr><tr><td>Android</td><td>1.016 [0.949-1.084]</td><td>22.82 [-136.38 to 182.01]</td><td>0.99 [0.98-0.99]</td></tr><tr><td>Gynoid</td><td>0.913 [0.844-0.983]</td><td>247.91 [-85.61 to 584.43]</td><td>0.98 [0.97-0.99]</td></tr><tr><td colspan="4">Visceral adipose tissue</td></tr><tr><td>VAT mass (g)</td><td>3.106 [2.705-3.506]</td><td>-768.36 [-1038.14 to -498.59]</td><td>0.92 [0.86-0.95]</td></tr><tr><td>VAT area (cm²)</td><td>1.818 [1.546-2.089]</td><td>-56.02 [-90.55 to -21.49]</td><td>0.91 [0.85-0.95]</td></tr><tr><td>VAT volume (cm³)</td><td>3.023 [2.633-3.413]</td><td>-808.11 [-1091.86; -524.35]</td><td>0.92 [0.86-0.95]</td></tr><tr><td colspan="4">FFST (g)</td></tr><tr><td>Arm</td><td>0.671 [0.546-0.796]</td><td>693.21 [358.55-1027.87]</td><td>0.88 [0.80-0.93]</td></tr><tr><td>Trunk</td><td>0.923 [0.854-0.991]</td><td>-1043.68 [-2774.29 to 686.93]</td><td>0.98 [0.97-0.99]</td></tr><tr><td>Leg</td><td>1.101 [0.820-1.383]</td><td>-1051.31 [-3580.06 to 1477.44]</td><td>0.90 [0.83-0.94]</td></tr><tr><td>Total</td><td>0.915 [0.852; 0.979]</td><td>-30.23 [-3590.31 to 3529.85]</td><td>0.98 [0.97-0.99]</td></tr><tr><td>Whole body BMD (g/cm³)</td><td>1.378 [1.047-1.709]</td><td>-0.486 [-0.880 to -0.092]</td><td>0.80 [0.68-0.88]</td></tr><tr><td>Whole body BMC (g)</td><td>0.963 [0.860-1.067]</td><td>151.51 [-130.943 to 433.95]</td><td>0.96 [0.93-0.98]</td></tr></tbody></table>

Note: The cross-calibration equations were defined as follow: [Stratos values = Intercept + Discovery A values * Slope] and [Discovery A values = Intercept + Stratos values * Slope].

Abbreviations: BMC, bone mineral content; BMD, bone mineral density; CI, confidence intervals; ICC, intraclass correlation coefficient; VAT, visceral adipose tissue.

## 4.1 | Stratos DR in vivo precision

The ISCD recommends that the minimum acceptable precision error within a population of interest should not exceed 3% for WB FM and 2% for WB FFST (Shuhart et al., 2019), which was the case in our study (<1.4%). These results indicated the good precision of the Stratos DR. We note that FFST showed a lower precision error compared to FM, which has previously been reported (Barlow et al., 2015; Bazzocchi et al., 2016; Henriksen et al., 2021; Rothney et al., 2012). In the absence of other works evaluating the precision of the Stratos DR, we could only compare our results to those previously obtained for other manufacturers. Nevertheless, our findings seem to be in accordance with the precision reported for the Lunar iDXA (ranging from 0.4% to 1%) (Henriksen et al., 2021; Hind et al., 2011; Rothney et al., 2012; Watson et al., 2017) and better than that of older generation DXA models such as Prodigy (ranging from 0.8% to 2.5%) (Oldroyd et al., 2003). It has also been suggested that the population studied and, particularly, an increase in body size can alter the precision of the
measurement (Barlow et al., 2015; Hind et al., 2011; Knapp et al., 2012). The limited number of participants available per BMI class in our study did not permit us to test this hypothesis.

<table><caption>TABLE 5 Repeatability of the measurements for fat mass, fat-free soft tissue and BMD for Stratos DR</caption><thead><tr><th>Sites</th><th>First measure</th><th>Second measure</th><th>RMS-SD</th><th>RMS-CV (%)</th><th>LSC-RMS SD</th><th>LSC %CV (%)</th><th>ICC [95% CI]</th></tr></thead><tbody><tr><td colspan="8">Fat mass (g)</td></tr><tr><td>Arm</td><td>1607.7 ± 506.2</td><td>1597.6 ± 509.6</td><td>157.2</td><td>8.8</td><td>435.4</td><td>24.5</td><td>0.90 [0.80-0.95]</td></tr><tr><td>Trunk</td><td>20527.3 ± 8705.8</td><td>20653.4 ± 8784.3</td><td>544.3</td><td>2.8</td><td>1507.8</td><td>7.8</td><td>1.00 [1.00-1.00]</td></tr><tr><td>Leg</td><td>5878.9 ± 2303.6</td><td>5842.0 ± 2314.72</td><td>120.7</td><td>2.5</td><td>334.3</td><td>7.0</td><td>1.00 [1.00-1.00]</td></tr><tr><td>Total</td><td>36342.4 ± 13069.0</td><td>36318.7 ± 13124.1</td><td>513.8</td><td>1.4</td><td>1423.2</td><td>3.9</td><td>1.00 [1.00-1.00]</td></tr><tr><td>Android</td><td>3549.9 ± 1610.6</td><td>3598.1 ± 1670.8</td><td>115.6</td><td>3.0</td><td>320.2</td><td>8.4</td><td>1.00 [1.00-1.00]</td></tr><tr><td>Gynoid</td><td>5932.1 ± 2107.3</td><td>5949.9 ± 2071.8</td><td>193.1</td><td>3.0</td><td>534.9</td><td>8.2</td><td>0.99 [0.98-1.00]</td></tr><tr><td colspan="8">Visceral adipose tissue</td></tr><tr><td>VAT mass (g)</td><td>1580.7 ± 1194.6</td><td>1604.2 ± 1218.7</td><td>203.6</td><td>15.9</td><td>564.1</td><td>44.0</td><td>0.97 [0.94-0.99]</td></tr><tr><td>VAT area (cm²)</td><td>231.5 ± 149.5</td><td>231.6 ± 151.4</td><td>24.5</td><td>9.8</td><td>68.0</td><td>27.2</td><td>0.97 [0.94-0.99]</td></tr><tr><td>VAT volume (cm³)</td><td>1663.9 ± 1257.4</td><td>1688.7 ± 1282.9</td><td>214.3</td><td>15.9</td><td>593.8</td><td>44.0</td><td>0.97 [0.94-0.99]</td></tr><tr><td colspan="8">FFST (g)</td></tr><tr><td>Arm</td><td>2522.8 ± 618.4</td><td>2572.6 ± 637.1</td><td>183.9</td><td>8.0</td><td>509.4</td><td>22.3</td><td>0.91 [0.82-0.96]</td></tr><tr><td>Trunk</td><td>24980.5 ± 6531.0</td><td>25197.0 ± 6749.8</td><td>555.8</td><td>2.2</td><td>1539.4</td><td>6.2</td><td>0.99 [0.98-1.00]</td></tr><tr><td>Leg</td><td>8984.1 ± 1997.3</td><td>8915.6 ± 1890.9</td><td>198.0</td><td>2.0</td><td>548.5</td><td>5.5</td><td>0.99 [0.98-1.00]</td></tr><tr><td>Total</td><td>51156.2 ± 11536.1</td><td>51301.6 ± 11722.0</td><td>509.3</td><td>1.0</td><td>1410.7</td><td>2.7</td><td>1.00 [1.00-1.00]</td></tr><tr><td>Whole body BMD (g/cm²)</td><td>1.182 ± 0.161</td><td>1.189 ± 0.162</td><td>0.018</td><td>1.4</td><td>0.050</td><td>4.0</td><td>0.99 [0.98-1]</td></tr><tr><td>Whole body BMC (g)</td><td>2646.2 ± 476.4</td><td>2672.9 ± 485.7</td><td>38.2</td><td>1.4</td><td>105.7</td><td>4.0</td><td>0.99 [0.98-1]</td></tr></tbody></table>

Note: Data are presented as mean ± SD (standard deviation).

Abbreviations: %CV, percent coefficient of variance; ICC, intraclass correlation coefficient; IC95%, confidence interval of 95%; LSC, ideal least significant change; RMS-SD, root mean square standard deviation.

Regional FM and FFST, particularly at the arm, showed higher precision errors than whole body (8.8%-8% vs. 1.4%-1%, respectively), as has also been reported for different manufacturers and in different populations including healthy subjects, patients with obesity or cancer, and athletes (ranging from 2.8% to 11.4%) (Barlow et al., 2015; Henriksen et al., 2021; Knapp et al., 2012; Rothney et al., 2012). These observations appear relevant because one of the criteria to define sarcopenia – the appendicular lean tissue mass index, which is defined as the sum of the FFST of the arms and legs/ height² (Cruz-Jentoft et al., 2019)–needs to be determined with high precision and high reproducibility to monitor the effectiveness of interventions. As discussed above, it is probable that the inclusion of a large proportion of patients with obesity partially explains this finding, as the precision error increases with increasing BMI (Knapp et al., 2012). Moreover, Rothney et al. (2012) suggested that as arms are a small region of the body, modest changes in FM and FFST can lead to larger percentage changes than are observed at the trunk. The precision as measured by the CV (%) of the android and gynoid FM was 3% in our study. Although slightly higher, our results are in
accordance with those of other reports (CV [%] around 0.96-2.8%) (Carver et al., 2013; Hind et al., 2011; Rothney et al., 2012). Concerning VAT mass, we measured a CV (%) of 15.9% (203.6 g on a 1.58 kg VAT), and this value was lower than the mean CV of 29% reported by Meredith-Jones et al. (Meredith-Jones et al., 2018) in participants with different classes of BMI with the Lunar Prodigy. Other studies using the Lunar iDXA nevertheless reported a lower precision error for VAT (ranging from 3.6% to 5.3%) in various populations composed of healthy subjects, and patients with obesity or colorectal cancer, as well as in phantom experiments (Henriksen et al., 2021; Rothney et al., 2012). Last, Mellis et al. (2014) reported CV (%) values ranging from 17% in a normal BMI group to 5.4% in a combined overweight and obesity BMI group. It is interesting to note that, compared with other peripheral sites, CV (%) decreased with BMI increases (Henriksen et al., 2021; Mellis et al., 2014; Meredith-Jones et al., 2018). In previous and current studies, VAT precision has been poor compared with measures of total and regional soft tissue, which have been higher. This may be due to the small size of the region and the mathematical modelling approach to separate the subcutaneous fat from VAT (Ergun et al., 2013). Moreover, FM in the abdominal cavity is not in a fixed position and may therefore move between two successive scans, resulting in inherent errors in measurement made in this anatomical area (Knapp et al., 2012).

Conversely to lumbar spine and hip BMD, WB BMD has not been used to diagnose osteoporosis and consequently the reproducibility has been poorly evaluated. In our study, the CV (%) for WB BMD was 1.4, and this appears slightly elevated compared to other reports (<0.8%) (Knapp et al., 2012). Nevertheless, as mentioned above, the relatively high proportion of participants with obesity may explain our findings, as observed by Knapp et al. (Knapp et al., 2012), who reported an increase in CV (%) from 0.77% in normal-weight participants to 0.91% in participants presenting obesity.

Our study presents some limitations and these are particularly due to our population, which included a wide range of ages and BMIs. Thus, the mean BMI of 31.5 kg/m² classified our population as obese and differed from other studies that evaluated precision in normal overweight participants (Hind et al., 2011; Rothney et al., 2012). Nevertheless, as recommended by the ISCD, precision should be evaluated in a sample that is representative of the facility's patient population and at the anatomical sites most often measured (Shuhart et al., 2019). One part of the activity of our department is devoted to the follow-up of body composition changes in patients with obesity after surgical and nonsurgical medical care (Maïmoun et al., 2017; Maimoun, Lefebvre, et al., 2019; Maimoun, Mariano-Goulart, 2019; Maimoun et al., 2023). Also, our population was mostly composed of women, and we were thus unable to evaluate the effect of sex on reproducibility, and principally at gynoid, android and VAT regions, which present sex specificity.

In conclusion, these data show that when the Discovery A scanner is replaced with the Stratos DR, or when a multicentre study is necessary, the cross-calibration equation defined in this study should be used to ensure the comparability of scan data. The Stratos DR presents good precision for repeat measurements of body composition over a wide range of BMI, although it was better for measurements of FFST than FM and better for whole body than for regional areas.
<figure><img src="image_3.png" /><figcaption>**FIGURE 3** Correlations between fat mass values measured successively two times by Stratos DR and Bland-Altman plot. VAT, visceral adipose tissue.</figcaption></figure>

<figure><img src="image_4.png" /><figcaption>**FIGURE 4** Relationship between fat-free soft tissue (FFST) or bone mineral density (BMD) measured successively two fold by Stratos DR and Bland-Altman plot. BMC, bone mineral content; BMD, bone mineral density.</figcaption></figure>

## ACKNOWLEDGEMENTS

The authors would like to thank all the participants.

## CONFLICT OF INTEREST STATEMENT

The authors declare no conflict of interest.
DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available on request from the
corresponding author Laurent Maïmoun (l-maimoun@chumontpellier.fr).

ORCID

Laurent Maïmoun http://orcid.org/0000-0002-1727-1048

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