Advancing body composition assessment in patients with cancer: First comparisons of traditional versus multicompartment models.

BACKGROUND AND AIMS: Measurement of body composition using computed tomography (CT) scans may be a viable clinical tool for low muscle mass assessment in oncology. However, longitudinal assessments are often infeasible with CT. Clinically accessible body composition technologies can be used to track changes in fat-free mass (FFM) or muscle, though their accuracy may be impacted by cancer-related physiological changes. The purpose of this study was to examine the agreement among accessible body composition method with criterion methods for measures of whole-body FFM measurements and, when possible, muscle mass for the classification of low muscle in patients with cancer. METHODS: Patients with colorectal cancer were recruited to complete measures of whole-body DXA, air displacement plethysmography (ADP), and bioelectrical impedance analysis (BIA). These measures were used alone, or in combination to construct the criterion multicompartment (4C) mode for estimating FFM. Patients also underwent abdominal CT scans as part of routine clinical assessment. Agreement of each method with 4C model was analyzed using mean constant error (CE = criterion - alternative), linear regression including root mean square error (RMSE), Bland-Altman limits of agreement (LoA) and mean percentage difference (MPD). Additionally, appendicular lean soft tissue index (ALSTI) measured by DXA and predicted by CT were compared for the absolute agreement, while the ALSTI values and skeletal muscle index by CT were assessed for agreement on the classification of low muscle mass. RESULTS: Forty-five patients received all measures for the 4C model and 25 had measures within proximity of clinical CT measures. Compared to 4C, DXA outperformed ADP and BIA by showing the strongest overall agreement (CE = 1.96 kg, RMSE = 2.45 kg, MPD = 98.15 ± 2.38%), supporting its use for body composition assessment in patients with cancer. However, CT cutoffs for skeletal muscle index or CT-estimated ALSTI were lower than DXA ALSTI (average 1.0 ± 1.2 kg/m2) with 24.0% to 32.0% of patients having a different low muscle classification by CT when compared to DXA. CONCLUSIONS: Despite discrepancies between clinical body composition assessment and the criterion multicompartment model, DXA demonstrates the strongest agreement with 4C. Disagreement between DXA and CT for low muscle mass classification prompts further evaluation of the measures and cutoffs used with each technique. Multicompartment models may enhance our understanding of body composition variations at the individual patient level and improve the applicability of clinically accessible technologies for classification and monitoring change over time.

Future lines of research on phase angle: Strengths and limitations.

Bioelectrical impedance analysis (BIA) is the most widely used technique in body composition analysis. When we focus the use of phase sensitive BIA on its raw parameters Resistance (R), Reactance (Xc) and Phase Angle (PhA), we eliminate the bias of using predictive equations based on reference models. In particular PhA, have demonstrated their prognostic utility in multiple aspects of health and disease. In recent years, as a strong association between prognostic and diagnostic factors has been observed, scientific interest in the utility of PhA has increased. In the different fields of knowledge in biomedical research, there are different ways of assessing the impact of a scientific-technical aspect such as PhA. Single frequency with phase detection bioimpedance analysis (SF-BIA) using a 50 kHz single frequency device and tetrapolar wrist-ankle electrode placement is the most widely used bioimpedance approach for characterization of whole-body composition. However, the incorporation of vector representation of raw bioelectrical parameters and direct mathematical calculations without the need for regression equations for the analysis of body compartments has been one of the most important aspects for the development of research in this area. These results provide new evidence for the validity of phase-sensitive bioelectrical measurements as biomarkers of fluid and nutritional status. To enable the development of clinical research that provides consistent results, it is essential to establish appropriate standardization of PhA measurement techniques. Standardization of test protocols will facilitate the diagnosis and assessment of the risk associated with reduced PhA and the evaluation of changes in response to therapeutic interventions. In this paper, we describe and overview the value of PhA in biomedical research, technical and instrumental aspects of PhA research, analysis of Areas of clinical research (cancer patients, digestive and liver diseases, critical and surgical patients, Respiratory, infectious, and COVID-19, obesity and metabolic diseases, Heart and kidney failure, Malnutrition and sarcopenia), characterisation of the different research outcomes, Morphofunctional assessment in disease-related malnutrition and other metabolic disorders: validation of PhA with reference clinical practice techniques, strengths and limitations. Based on the detailed study of the measurement technique, some of the key issues to be considered in future PhA research. On the other hand, it is important to assess the clinical conditions and the phenotype of the patients, as well as to establish a disease-specific clinical profile. The appropriate selection of the most critical outcomes is another fundamental aspect of research.

Phase angle (PhA) in overweight and obesity: evidence of applicability from diagnosis to weight changes in obesity treatment.

Phase angle (PhA) is a recently proposed marker of nutritional status in many clinical conditions. Its use in patients with obesity presents different critical concerns due to the higher variability of the two measured parameters (resistance, R, and reactance, Xc) that contribute to the determination of PhA. Controversial is the relation between PhA and BMI that might vary with graded levels of obesity due to the variation in fat and free fat mass. Obesity is frequently associated with metabolic, hepatic, cardiovascular and kidney diseases that introduce variations in PhA values, in relation to multimorbidity and severity degree of these diseases. It is reported that the improvement of clinical condition is associated with a positive change in PhA. Also, the treatment of obesity with weight loss might confirm this effect, but with different responses in relation to the type and duration of the intervention applied. In fact, the effect appears not only related to the percentage of weight loss but also the possible loss of free fat mass and the nutritional, metabolic and structural modifications that might follow each therapeutic approach to decrease body weight. We can conclude that the PhA could be used as marker of health status in patients with obesity supporting an appropriate weight loss intervention to monitor efficacy and fat free mass preservation.

Phase angle as an index of physiological status: validating bioelectrical assessments of hydration and cell mass in health and disease.

Bioelectrical impedance (BI) is a practical method to assess body composition in health and disease. This method relies on the passive conduction of an applied, safe, low-level alternating current through water and electrolytes in the body. Using a phase-sensitive device, BI yields measurements of impedance (Z) and its components, resistance (R) and reactance (Xc), that are related geometrically as phase angle (PhA). In vitro studies provide empirical evidence relating BI measurements to physiological variables. Cooking raw food samples results in greater decreases in PhA, predominantly Xc, with smaller reductions R indicating destruction of cell membrane integrity with simultaneous movement of fluid from intracellular to extracellular space. Infusion of saline into a cell-free model shows a proportional decrease in R with increases in volume. Saline infusion in a composite model of cells disproportionately decreases Xc and PhA, compared to R, demonstrating greater relative expansion of extracellular water (ECW) with a lesser relative increase in total fluid volume. Surgical patients treated with fluid infusion and diuresis demonstrate changes in Xc predominantly indicating relative changes in ECW with lesser variations in R indicating fluctuations in total fluid volume. Proteomics studies disclose strong independent associations of PhA with protein markers of fluid overload and protein proliferation. Interpretations of PhA measurements for body cell mass should be examined in the context of hydration status.

Classification of Hydration in Clinical Conditions: Indirect and Direct Approaches Using Bioimpedance.

Although the need to assess hydration is well recognized, laboratory tests and clinical impressions are impractical and lack sensitivity, respectively, to be clinically meaningful. Different approaches use bioelectrical impedance measurements to overcome some of these limitations and aid in the classification of hydration status. One indirect approach utilizes single or multiple frequency bioimpedance in regression equations and theoretical models, respectively, with anthropometric measurements to predict fluid volumes (bioelectrical impedance spectroscopy-BIS) and estimate fluid overload based on the deviation of calculated to reference extracellular fluid volume. Alternatively, bioimpedance vector analysis (BIVA) uses direct phase-sensitive measurements of resistance and reactance, measured at 50 kHz, normalized for standing height, then plotted on a bivariate graph, resulting in a vector with length related to fluid content, and direction with phase angle that indexes hydration status. Comparison with healthy population norms enables BIVA to classify (normal, under-, and over-) and rank (change relative to pre-treatment) hydration independent of body weight. Each approach has wide-ranging uses in evaluation and management of clinical groups with over-hydration with an evolving emphasis on prognosis. This review discusses the advantages and limitations of BIS and BIVA for hydration assessment with comments on future applications.

Lack of agreement of in vivo raw bioimpedance measurements obtained from two single and multi-frequency bioelectrical impedance devices.

BACKGROUND: It is important for highly active individuals to accurately assess their hydration level. Bioelectrical impedance (BIA) can potentially meet these needs but its validity in active individuals is not well established. METHODS: We compared whole-body bioimpedance measurements obtained from multi-frequency bioelectrical impedance spectroscopy (BIS, Xitron 4200) at a 50 kHz frequency with those determined by a phase-sensitive single-frequency device (SF-BIA, BIA-101, RJL/Akern Systems) in two populations: active adults and elite athletes. RESULTS: One hundred twenty-six participants, including active males involved in recreational sports (N = 25, 20-39 yr) and elite athletes (females: N = 26, 18-35 yr; males: N = 75, 18-38 yr) participated in this study. Reactance (Xc), Resistance (R), Impedance (Z), and phase angle (PhA) were obtained by BIS and SF-BIA. Small but significant differences (R: -9.91 ± 15.09 Ω; Xc: -0.97 ± 2.56 Ω; Z: -9.96 ± 15.18 Ω; PhA: 0.12 ± 0.2°) were observed between the bioimpedance equipment in all measured variables (p < 0.05) though differences were within the devices' technical error of measurements. Device-specific values were highly (p < 0.0001) correlated [R2 ranged from 0.881 (Xc) to 0.833 (R)], but slopes and intercepts were different (p < 0.0001) from 1 and 0, respectively. Relatively large limits of agreement were observed for R (-40 to 21 Ω), Xc (-6 to 4 Ω), PhA (-0.4 to 0.5°), and impedance (-40 to 20 Ω). CONCLUSION: Bioimpedance measurements from the current single- and multi-frequency devices should not be used interchangeably. The of lack of agreement between devices was observed in determining individual values of R, Xc, Z and PhA of highly active populations possibly due to methodological and biological factors.

Chromium.

Two oxidation states of chromium are considered to be biologically and environmentally relevant based on their stability in the presence of water and oxygen. Compounds containing chromium(6 + ) are mutagenic and carcinogenic when inhaled and potentially when ingested orally in large quantity as well. Chromium as the trivalent will be the focus of this work as it was proposed to be an essential element for mammals ∼60 y ago; however, in the last 2 decades its status has been questioned. Chromium has been postulated to be involved in regulating carbohydrate and lipid (and potentially also protein) metabolism by enhancing insulin's efficacy (1). However, in 2014, the European Food Safety Authority found no convincing evidence that chromium is an essential element (2). Dietary chromium apparently is absorbed via passive diffusion and the extent of absorption is low (∼1%). Chromium is maintained in the bloodstream bound to the protein transferrin. It is generally believed to be delivered to tissues by transferrin via endocytosis (1). No unambiguous animal model of chromium deficiency has been established (2). One limitation in characterizing chromium deficiency in humans is the lack of an accepted biomarker of chromium nutritional status. Attempts to identify a glucose tolerance factor have not provided a chemically defined functional compound that conforms with the proposed physiologic role of chromium as a facilitator of insulin action in vivo.

Assessment of adult malnutrition and prognosis with bioelectrical impedance analysis: phase angle and impedance ratio.

PURPOSE OF REVIEW: Malnutrition affects prognosis in many groups of patients. Although screening tools are available to identify adults at risk for poor nutritional status, a need exists to improve the assessment of malnutrition by identifying the loss of functional tissues that can lead to frailty, compromised physical function, and increased risk of morbidity and mortality, particularly among hospitalized and ill patients and older adults. Bioimpedance analysis (BIA) offers a practical approach to identify malnutrition and prognosis by assessing whole-body cell membrane quality and depicting fluid distribution for an individual. RECENT FINDINGS: Two novel applications of BIA afford opportunities to safely, rapidly, and noninvasively assess nutritional status and prognosis. One method utilizes single-frequency phase-sensitive measurements to determine phase angle, evaluate nutritional status, and relate it to prognosis, mortality, and functional outcomes. Another approach uses the ratio of multifrequency impedance values to indicate altered fluid distribution and predict prognosis. SUMMARY: Use of basic BIA measurements, independent of use of regression prediction models and assumptions of constant chemical composition of the fat-free body, enables new options for practical assessment and clinical evaluation of impaired nutritional status and prognosis among hospitalized patients and elders that potentially can contribute to improved patient care and clinical outcomes. However, these novel applications have some technical and physiological limitations that should be considered.

Correction: Farina, G.L., et al. A Smartphone Application for Personal Assessments of Body Composition and Phenotyping. Sensors 2016, 16, 2163.

The authors wish to make the following corrections to Table 1 of their paper [...].

Estimation of total body water and extracellular water with bioimpedance in athletes: A need for athlete-specific prediction models.

PURPOSE: Bioelectrical impedance analysis (BIA) equations can predict total body water (TBW) and extracellular water (ECW) in non-athletic healthy populations. This study aimed: a) to develop BIA-based models for TBW and ECW prediction based on dilution methods in a sample of national level athletes; and b) to validate the new models with a cross-validation approach in a separate cohort using dilution methods as criterion. METHODS: Two hundred and eight highly trained athletes (21.3 ± 5.0 years) were evaluated during their respective competitive seasons. Athletes were randomly split into development (n = 139) and validation groups (n = 69). The criterion method for TBW was deuterium dilution and for ECW was bromide dilution, where ICW was the respective difference between both. Resistance (R) and reactance (Xc) were obtained with a phase-sensitive 50 kHz BIA device and used for the estimation of TBW and ECW. RESULTS: Athletic BIA-based models were developed for TBW and ECW [TBW = 0.286 + 0.195*S(2)/R + 0.385*Wt + 5.086*Sex; ECW = 1.579 + 0.055*S(2)/R + 0.127*Wt + 0.006*S(2)/Xc + 0.932*Sex, where sex is 0 if female or 1 if male, Wt is weight (kg), S is stature (cm), and R and Xc are in ohm (Ω)]. Cross validation revealed R(2) of 0.91 for TBW and R(2) 0.70 for ECW and no mean bias. CONCLUSIONS: The new equations can be considered valid, with no observed bias, thus affording practical means to quantify TBW and ECW in national level athletes.

The effect of heat acclimation on sweat microminerals: artifact of surface contamination.

UNLABELLED: Heat acclimation (HA) reportedly conveys conservation in sweat micromineral concentrations when sampled from arm sweat, but time course is unknown. The observation that comprehensive cleaning of the skin surface negates sweat micromineral reductions during prolonged sweating raises the question of whether the reported HA effect is real or artifact of surface contamination. PURPOSE: To measure sweat mineral concentrations serially during HA and determine if surface contamination plays a role in the reported mineral reductions. METHODS: Calcium (Ca), copper (Cu), magnesium (Mg), and zinc (Zn) were measured in sweat obtained from 17 male volunteers using an arm bag on Day 1, 5, and 10 of a HA protocol. To study the role of contamination, sweat was simultaneously (n = 10 subjects) sampled twice daily from a cleaned site (WASH) and unclean site (NO WASH) on the scapular surface. RESULTS: Sweat Ca, Cu, and Mg from Arm Bag trended progressively downward from Day 1 to Day 10 of HA (p = .10-0.25). Micromineral concentrations from the WASH site did not change between Day 1, 5, or 10 (Ca = 0.30 ± 0.12 mmol/L, Cu 0.41 ± 0.53 µmol/L; Zn 1.11 ± 0.80 µmol/L). Surface contamination can confound sweat mineral estimates, as sweat Ca and Cu from NO WASH site were initially higher than WASH (p < .05) but became similar to WASH when sampled serially. CONCLUSION: Heat acclimation does not confer reductions in sweat Ca, Cu, Mg, or Zn. When the skin surface is not cleaned, mineral residue inflates initial sweat mineral concentrations. Earlier reports of micromineral reductions during HA may have been confounded by interday cleaning variability.