Quantification in Emission Tomography
Michael Ljungberg in Handbook of Nuclear Medicine and Molecular Imaging for Physicists, 2022
Sometimes lean body weight is used instead of body weight to account for the fact that there is not normally significant tracer uptake in fatty tissue. The result is a unit-less quantity. The activity Ainj is measured in a dose-calibrator, typically an ionization chamber. Therefore, a cross-calibration is needed between the scanner and the dose-calibrator. Despite this use of cross-calibration, SUV is still only a semi-quantitative parameter indicative of regional uptake, reliant on several biological assumptions, and therefore subject to several sources of error. As a result, SUV is useful to illustrate change in an individual’s tracer uptake for multiple scans, but it has more limited value in comparing across individuals where the assumptions may not be valid. A further parameter commonly used in neurological analysis is the ratio of SUV values for a tissue of interest and a reference tissue. This is normally referred to as the SUV ratio (SUVR), but this in effect is simply the ratio of reconstructed tissue values and requires no cross-calibration (injected dose and patient weight cancel in the ratio). It is therefore identical to the semi-quantitative indices mentioned earlier. To call it SUVR is misleading as it implies that it is somehow related to SUV, when it is not.
Etiologies of obesity
G. Michael Steelman, Eric C. Westman in Obesity, 2016
The etiologies of obesity described in this chapter can be considered, on a foundational level, to serve as insight for our continually expanding knowledge and understanding of the complexities of excessive adipose tissue. If lean body mass remains stable and energy output is less than energy intake, body fat does increase. It would be simple if the explanation stopped here, but it does not. This chapter examines the multifaceted keys to susceptibility for obesity that are strongly influenced by genetic, behavioral, environmental, biological, circadian, and other factors. A visual representation of the complex interactions between 108 variables thought by experts to contribute to obesity causation, the Foresight Obesity System map (3), was developed by the UK government in 2007 and gives a good oversight of the multiple interactions among some of the elements discussed later in this chapter.
Medical Management of Uncomplicated Obesity
Susan L. McElroy, David B. Allison, George A. Bray in Obesity and Mental Disorders, 2006
Exercise plays a major role in assisting with weight maintenance, and there is mounting evidence that increased physical activity plays a crucial role in the prevention and management of many chronic diseases even in the absence of weight loss (9). Aerobic exercise is usually recommended for weight management because of the large number of calories burned as well as the health benefits achieved. Strength training may also be of benefit to build lean body mass and improve body composition. Regular adherence to an exercise program is associated with better outcome because it may also improve dietary compliance or be a marker of better dietary compliance. Exercise further improves quality of life by enhancing self-esteem, reducing stress, and relieving depression.
Determinants of Treatment Toxicity in Patients with Soft Tissue Sarcomas
Published in Nutrition and Cancer, 2023
Katja A. Schönenberger, Emilie Reber, Karin Schläppi, Annic Baumgartner, Zeno Stanga, Attila Kollár
A recent review by Barnes et al. presented a comprehensive overview of the current literature on the impact of body mass index (BMI) and body composition on outcomes among patients with STS, highlighting the importance of obesity as a potentially targetable risk factor (2). However, interpreting BMI alone is neither simple nor meaningful as it is a poor measure of obesity. Body mass represents a combination of muscle and fat mass and does not reflect differences in lean body mass (LBM), muscle mass, and fat mass distribution (i.e., intramuscular, visceral, and subcutaneous). Decreased muscle mass is a good indicator of worse clinical outcomes and poor quality of life, especially in cases of sarcopenia, a progressive and generalized loss of muscle mass and function. Sarcopenia is prevalent in cancer and is associated with negative clinical outcomes, such as treatment toxicity, frailty, and increased morbidity and mortality (2). The depletion of muscle mass is characterized by both a reduction in muscle size (quantitative change) and an increased proportion of inter- and intramuscular fat (qualitative change). Therefore, fat infiltration may be a manifestation of the wasting process. Increased intramuscular adipose tissue can be quantified in computed tomography (CT) scans by attenuation of muscle density. Previous research has shown an association between low muscle quality (i.e., low muscle attenuation) and adverse clinical outcomes (5, 6).
Does metabolic status affect serum levels of BDNF and MMP-9 in patients with schizophrenia?
Published in Nordic Journal of Psychiatry, 2019
Jaśmina Arabska, Aleksandra Margulska, Dominik Strzelecki, Adam Wysokiński
Body composition (body fat and lean body mass) was determined using BIA, which provides accurate measurements of body fat, lean body mass and body water [21]. BIA was performed using Maltron BIOSCAN 920-2-S Body Fat Analyzer (Maltron, UK), multi-frequency (5 kHz, 50 kHz, 100 kHz, 200 kHz) analyzer. Briefly, BIA determines the electrical impedance, or opposition to the flow of an electric current through body tissues, which can then be used to calculate an estimate of total body water, which can be used to estimate fat-free body mass and, by difference with body weight, body fat. Standard operating conditions were observed by a trained operator including preparation of the participant, electrode placement and operation. The measurement using BIA was taken immediately prior to anthropometry measurements with participants lying supine, in a rested state. Body fat and lean body mass were expressed as total mass (in kg) and as a percentage of body mass.
Robust inference for skewed data in health sciences
Published in Journal of Applied Statistics, 2022
Amarnath Nandy, Ayanendranath Basu, Abhik Ghosh
We consider the data on health measurements of 706 Australian athletes from 12 different sports which were collected at the Australian Institute of Sports (AIS) in 1990 by Telford and Cunningham [53] to investigate the relationships of the five routine hematological measures, namely, the hemoglobin concentration (HC), hematocrit (H), red cell count (RCC), white cell count (WCC) and plasma ferritin concentration (PFC) in the blood of these athletes with their height (Ht), weight (Wt) and the sports type. These measurements are recorded on 1604 occasions from each athlete based on the blood samples collected from their forearm vein amidst periods of moderate to intense training but at least 6 h after a training session. Some important derived health measurements like body-mass index (BMI) and lean body mass (LBM) are also reported. The data were later used by several researchers in different statistical inference problems; in particular, few of them fitted the SN distribution with the MLE but only to a few measurements and/or a part of the data [43,61].
Related Knowledge Centers
- Body Composition
- Body Fat Percentage
- Body Weight
- Obesity
- Metabolism
- Cell Membrane
- Adipose Tissue
- Opioid
- Propofol
- Contrast CT