Validation of quantitative magnetic resonance body composition analysis for infants using piglet model

Development and Validation of a Prediction Model for Infant Fat Mass

OBJECTIVES

To develop and validate a prediction model for fat mass in infants ≤12 kg using easily accessible measurements such as weight and length.

STUDY DESIGN

We used data from a pooled cohort of 359 infants age 1-24 months and weighing 3-12 kg from 3 studies across Southern California and New York City. The training data set (75% of the cohort) included 269 infants and the testing data set (25% of the cohort) included 90 infants age 1-24 months. Quantitative magnetic resonance was used as the standard measure for fat mass. We used multivariable linear regression analysis, with backwards selection of predictor variables and fractional polynomials for nonlinear relationships to predict infant fat mass (from which lean mass can be estimated by subtracting resulting estimates from total mass) in the training data set. We used 5-fold cross-validation to examine overfitting and generalizability of the model's predictive performance. Finally, we tested the adjusted model on the testing data set.

RESULTS

The final model included weight, length, sex, and age, and had high predictive ability for fat mass with good calibration of observed and predicted values in the training data set (optimism-adjusted R²: 92.1%). Performance on the test dataset showed promising generalizability (adjusted R²: 85.4%). The mean difference between observed and predicted values in the testing dataset was 0.015 kg (-0.043 to -0.072 kg; 0.7% of the mean).

CONCLUSIONS

Our model accurately predicted infant fat mass and could be used to improve the accuracy of assessments of infant body composition for effective early identification, surveillance, prevention, and management of obesity and future chronic disease risk.

Anthropometric models to estimate fat mass at 3 days, 15 and 54 weeks

BACKGROUND

Currently available infant body composition measurement methods are impractical for routine clinical use. The study developed anthropometric equations (AEs) to estimate fat mass (FM, kg) during the first year using air displacement plethysmography (PEA POD® Infant Body Composition System) and Infant quantitative magnetic resonance (Infant-QMR) as criterion methods.

METHODS

Multi-ethnic full-term infants (n = 191) were measured at 3 days, 15 and 54 weeks. Sex, race/ethnicity, gestational age, age (days), weight-kg (W), length-cm (L), head circumferences-cm (HC), skinfold thicknesses mm [triceps (TRI), thigh (THI), subscapular (SCP), and iliac (IL)], and FM by PEA POD® and Infant-QMR were collected. Stepwise linear regression determined the model that best predicted FM.

RESULTS

Weight, length, head circumference, and skinfolds of triceps, thigh, and subscapular, but not iliac, significantly predicted FM throughout infancy in both the Infant-QMR and PEA POD models. Sex had an interaction effect at 3 days and 15 weeks for both the models. The coefficient of determination [R² ] and root mean square error were 0.87 (66 g) at 3 days, 0.92 (153 g) at 15 weeks, and 0.82 (278 g) at 54 weeks for the Infant-QMR models; 0.77 (80 g) at 3 days and 0.82 (195 g) at 15 weeks for the PEA POD models respectively.

CONCLUSIONS

Both PEA POD and Infant-QMR derived models predict FM using skinfolds, weight, head circumference, and length with acceptable R² and residual patterns.

Reliability of the EchoMRI Infants System for Water and Fat Measurements in Newborns

OBJECTIVE

The precision and accuracy of a quantitative magnetic resonance (EchoMRI Infants) system in newborns were determined.

METHODS

Canola oil and drinking water phantoms (increments of 10 g to 1.9 kg) were scanned four times. Instrument reproducibility was assessed from three scans (within 10 minutes) in 42 healthy term newborns (12-70 hours post birth). Instrument precision was determined from the coefficient of variation (CV) of repeated scans for total water, lean mass, and fat measures for newborns and the mean difference between weight and measurement for phantoms. In newborns, the system accuracy for total body water (TBW) was tested against deuterium dilution (D₂ O).

RESULTS

In phantoms, the repeatability and accuracy of fat and water measurements increased as the weight of oil and water increased. TBW was overestimated in amounts >200 g. In newborns weighing 3.14 kg, fat, lean mass, and TBW were 0.52 kg (16.48%), 2.28 kg, and 2.40 kg, respectively. EchoMRI's reproducibility (CV) was 3.27%, 1.83%, and 1.34% for total body fat, lean mass, and TBW, respectively. EchoMRI-TBW values did not differ from D₂ O; mean difference, -1.95 ± 6.76%, P = 0.387; mean bias (limits of agreement), 0.046 kg (-0.30 to 0.39 kg).

CONCLUSIONS

The EchoMRI Infants system's precision and accuracy for total body fat and lean mass are better than established techniques and equivalent to D₂ O for TBW in phantoms and newborns.

In Vivo Determination of Body Composition in Zebrafish (Danio rerio) by Quantitative Magnetic Resonance

Zebrafish (Danio rerio) as a model research organism continues to expand its relevance and role in multiple research disciplines, with recent work directed toward models of metabolism, nutrition, and energetics. Multiple technologies exist to assess body composition in animal research models at various levels of detail (tissues/organs, body regions, and whole organism). The development and/or validation of body composition assessment tools can open new areas of research questions for a given organism. Using fish from a comparative nutrition study, quantitative magnetic resonance (QMR) assessment of whole body fat and fat-free mass (FFM) in live fish was performed. QMR measures from two cohorts (n = 26 and n = 27) were compared with chemical carcass analysis (CCA) of FM and FFM. QMR was significantly correlated with chemical carcass values (fat, p < 0.001; lean, p = 0.002), although QMR significantly overestimated fat mass (FM) (0.011 g; p < 0.0001) and underestimated FFM (-0.024 g; p < 0.0001) relative to CCA. In a separate cross-validation group of fish, prediction equations corrected carcass values for FM (p = 0.121) and FFM (p = 0.753). These results support the utilization of QMR-a nonlethal nondestructive method-for cross-sectional or longitudinal body composition assessment outcomes in zebrafish.

Body composition during fetal development and infancy through the age of 5 years

Fetal body composition is an important determinant of body composition at birth, and it is likely to be an important determinant at later stages in life. The purpose of this work is to provide a comprehensive overview by presenting data from previously published studies that report on body composition during fetal development in newborns and the infant/child through 5 years of age. Understanding the changes in body composition that occur both in utero and during infancy and childhood, and how they may be related, may help inform evidence-based practice during pregnancy and childhood. We describe body composition measurement techniques from the in utero period to 5 years of age, and identify gaps in knowledge to direct future research efforts. Available literature on chemical and cadaver analyses of fetal studies during gestation is presented to show the timing and accretion rates of adipose and lean tissues. Quantitative and qualitative aspects of fetal lean and fat mass accretion could be especially useful in the clinical setting for diagnostic purposes. The practicality of different pediatric body composition measurement methods in the clinical setting is discussed by presenting the assumptions and limitations associated with each method that may assist the clinician in characterizing the health and nutritional status of the fetus, infant and child. It is our hope that this review will help guide future research efforts directed at increasing the understanding of how body composition in early development may be associated with chronic diseases in later life.

Correlation of X-ray computed tomography with quantitative nuclear magnetic resonance methods for pre-clinical measurement of adipose and lean tissues in living mice

Numerous obesity studies have coupled murine models with non-invasive methods to quantify body composition in longitudinal experiments, including X-ray computed tomography (CT) or quantitative nuclear magnetic resonance (QMR). Both microCT and QMR have been separately validated with invasive techniques of adipose tissue quantification, like post-mortem fat extraction and measurement. Here we report a head-to-head study of both protocols using oil phantoms and mouse populations to determine the parameters that best align CT data with that from QMR. First, an in vitro analysis of oil/water mixtures was used to calibrate and assess the overall accuracy of microCT vs. QMR data. Next, experiments were conducted with two cohorts of living mice (either homogenous or heterogeneous by sex, age and genetic backgrounds) to assess the microCT imaging technique for adipose tissue segmentation and quantification relative to QMR. Adipose mass values were obtained from microCT data with three different resolutions, after which the data were analyzed with different filter and segmentation settings. Strong linearity was noted between the adipose mass values obtained with microCT and QMR, with optimal parameters and scan conditions reported herein. Lean tissue (muscle, internal organs) was also segmented and quantified using the microCT method relative to the analogous QMR values. Overall, the rigorous calibration and validation of the microCT method for murine body composition, relative to QMR, ensures its validity for segmentation, quantification and visualization of both adipose and lean tissues.

Lean tissue imaging: a new era for nutritional assessment and intervention

Body composition refers to the amount of fat and lean tissues in our body; it is a science that looks beyond a unit of body weight, accounting for the proportion of different tissues and its relationship to health. Although body weight and body mass index are well-known indexes of health status, most researchers agree that they are rather inaccurate measures, especially for elderly individuals and those patients with specific clinical conditions. The emerging use of imaging techniques such as dual energy x-ray absorptiometry, computerized tomography, magnetic resonance imaging, and ultrasound imaging in the clinical setting have highlighted the importance of lean soft tissue (LST) as an independent predictor of morbidity and mortality. It is clear from emerging studies that body composition health will be vital in treatment decisions, prognostic outcomes, and quality of life in several nonclinical and clinical states. This review explores the methodologies and the emerging value of imaging techniques in the assessment of body composition, focusing on the value of LST to predict nutrition status.

Noninvasive measurements of body composition and body water via quantitative magnetic resonance, deuterium water, and dual-energy x-ray absorptiometry in cats

OBJECTIVE

To compare quantitative magnetic resonance (QMR), dual-energy x-ray absorptiometry (DXA), and deuterium oxide (D2O) dilution methods for measurement of total body water (TBW), lean body mass (LBM), and fat mass (FM) in healthy cats and to assess QMR precision and accuracy.

ANIMALS

Domestic shorthair cats (58 and 32 cats for trials 1 and 2, respectively).

PROCEDURES

QMR scans of awake cats performed with 2 units were followed by administration of D2O tracer (100 mg/kg, PO). Cats then were anesthetized, which was followed by QMR and DXA scans. Jugular blood samples were collected before and 120 minutes after D2O administration.

RESULTS

QMR precision was similar between units (coefficient of variation < 2.9% for all measures). Fat mass, LBM, and TBW were similar for awake or sedated cats and differed by 4.0%, 3.4%, and 3.9%, respectively, depending on the unit. The QMR minimally underestimated TBW (1.4%) and LBM (4.4%) but significantly underestimated FM (29%), whereas DXA significantly underestimated LBM (9.2%) and quantitatively underestimated FM (9.3%). A significant relationship with D2O measurement was detected for all QMR (r(2) > 0.84) and DXA (r(2) > 0.84) measurements.

CONCLUSIONS AND CLINICAL RELEVANCE

QMR was useful for determining body composition in cats; precision was improved over DXA. Quantitative magnetic resonance can be used to safely and rapidly acquire data without the need for anesthesia, facilitating frequent monitoring of weight changes in geriatric, extremely young, or ill pets. Compared with the D2O dilution method, QMR correction equations provided accurate data over a range of body compositions.

Noninvasive measurements of body composition and body water via quantitative magnetic resonance, deuterium water, and dual-energy x-ray absorptiometry in awake and sedated dogs

OBJECTIVE

To compare quantitative magnetic resonance (QMR), dual-energy x-ray absorptiometry (DXA), and deuterium oxide (D2O) methods for measurement of total body water (TBW), lean body mass (LBM), and fat mass (FM) in healthy dogs and to assess QMR accuracy.

ANIMALS

58 Beagles (9 months to 11.5 years old).

PROCEDURES

QMR scans were performed on awake dogs. A D2O tracer was administered (100 mg/kg, PO) immediately before dogs were sedated, which was followed by a second QMR or DXA scan. Jugular blood samples were collected before and 120 minutes after D2O administration.

RESULTS

TBW, LBM, and FM determined via QMR were not significantly different between awake or sedated dogs, and means differed by only 2.0%, 2.2%, and 4.3%, respectively. Compared with results for D2O dilution, QMR significantly underestimated TBW (10.2%), LBM (13.4%), and FM (15.4%). Similarly, DXA underestimated LBM (7.3%) and FM (8.4%). A significant relationship was detected between FM measured via D2O dilution and QMR (r(2) > 0.89) or DXA (r(2) > 0.88). Even though means of TBW and LBM differed significantly between D2O dilution and QMR or DXA, values were highly related (r(2) > 0.92).

CONCLUSIONS AND CLINICAL RELEVANCE

QMR was useful for determining body composition in dogs and can be used to safely and rapidly acquire accurate data without the need for sedation or anesthesia. These benefits can facilitate frequent scans, particularly in geriatric, extremely young, or ill pets. Compared with the D2O dilution method, QMR correction equations provided accurate assessment over a range of body compositions.

Air-displacement plethysmography for determining body composition in neonates: validation using live piglets

INTRODUCTION

Air-displacement plethysmography (ADP) was developed as a noninvasive tool to assess body composition, i.e., the proportion of fat mass (%FM) and lean body mass. The results of previous studies comparing ADP with labeled water dilution in infants and with chemical analysis in phantoms have validated the ADP approach indirectly. We assessed the precision and accuracy of measurements of % FM proportions in live animals, using ADP in comparison with biochemical analyses.

METHODS

Three groups of 12 piglets each underwent four consecutive body composition assessments at 2, 7, and 21 d and were euthanized to determine whole-body lipid content by direct chemical analysis.

RESULTS

The average body weights were 1,490, 2,210, and 5,610 g at d2, d7, and d21, respectively. The mean %FM values determined by biochemical analysis and ADP were 8.63 ± 4.08% and 8.01 ± 4.03%, respectively. Linear regression and Bland-Altman analyses indicated good agreement for %FM. The root mean square coefficient of variation (RMS-CV) for ADP was 17.9%, with a better precision in the higher fat mass range.

DISCUSSION

Despite its relatively poor precision in the low range of %FM, ADP measures fat mass with reasonable precision and accuracy in the range of body weight encountered in low-birth-weight infants.