CT-derived body composition analysis could possibly replace DXA and BIA to monitor NET-patients.
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ABSTRACT:
SUBMITTER: Kroll L
PROVIDER: S-EPMC9352897 | biostudies-literature | 2022 Aug
REPOSITORIES: biostudies-literature
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CT-derived body composition analysis could possibly replace DXA and BIA to monitor NET-patients.
Kroll Lennard L Mathew Annie A Baldini Giulia G Hosch René R Koitka Sven S Kleesiek Jens J Rischpler Christoph C Haubold Johannes J Fuhrer Dagmar D Nensa Felix F Lahner Harald H
Scientific reports 20220804 1
Patients with neuroendocrine tumors of gastro-entero-pancreatic origin (GEP-NET) experience changes in fat and muscle composition. Dual-energy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA) are currently used to analyze body composition. Changes thereof could indicate cancer progression or response to treatment. This study examines the correlation between CT-based (computed tomography) body composition analysis (BCA) and DXA or BIA measurement. 74 GEP-NET-patients received ...[more]
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Project description:BackgroundBody composition analysis is a valuable tool for assessing and monitoring the nutritional status of children with spinal muscular atrophy (SMA). This study was designed to compare the consistency of bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA), as the gold standard method for assessing body composition in clinical practice when treating children with type II and III SMA.MethodsFrom 2019 to 2021, we performed a retrospective analysis of body composition by DXA and BIA measurement methods in patients with type II and III SMA treated at a Chinese tertiary children's hospital. Fat mass (FM), muscle mass (MM), bone mineral content (BMC), and visceral fat area (VFA) were compared using paired sample t-tests. We calculated Lin's concordance correlation coefficient (CCC) and Spearman correlation coefficient to verify the correlation between DXA and BIA measurements. Bland-Altman analysis was used to assess the consistency of the two methods.ResultsFifty-seven children with type II and III SMA were recruited. Compared with body composition measured by DXA, the average FM measured by BIA is significantly lower (P <0.001), whereas the average MM, BMC, and VFA measured by BIA are significantly higher (P < 0.001) in children with SMA. Overall, the difference between MM (Delta [BIA-DAX] = 1.6 kg) and FM (Delta [BIA-DAX] = -1.6 kg) measured by DXA and BIA was minor, whereas the difference of VFA (Delta [BIA-DAX] = -43.5 cm) was significantly large. Correlation analysis indicated a substantial correlation of MM (CCC = 0.96 [95% confidence interval (CI) = 0.93-0.98], r = 0.967 [P < 0.0001]) and FM (CCC = 0.95 [95% CI = 0.92-0.97], r = 0.953 [P < 0.0001]), and poor correlation of BMC (CCC = 0.61 [95% CI = 0.42-0.75], r = 0.612 [P < 0.0001]) and VFA (CCC = 0.54 [95% CI = 0.33-0.70], r = 0.689 [P < 0.0001]) measurements between the two methods. The Bland-Altman analysis suggests that the majority of participants were within LOA. In addition, differences in MM and VFA measurements between BIA and DAX increased according to patients' increasing height, whereas differences in FM and BMC did not differ with height.ConclusionBIA overestimates MM and underestimates the FM, BMC, and VFA in children with SMA compared with DXA measurements. Overall, the non-invasive, easy-to-use, and repeatable BIA measurements were found to be in good agreement with DXA measurements, especially for FM and MM, which are essential parameters for the nutritional evaluation of children with SMA.
| S-EPMC9715747 | biostudies-literature
Project description:Muscle mass and strength are crucial for physiological function and performance in athletes, playing a significant role in maintaining health and optimal athletic performance. Skeletal muscle, which constitutes the majority of lean soft tissue (LST) and appendicular lean soft tissue (ALST) when measured by dual-energy X-ray absorptiometry (DXA), represents a commonly used surrogate for strength. Research has investigated alternative measures of body composition, such as the assessment of ALST through bioelectrical impedance analysis (BIA) and the determination of whole-body muscle mass from creatine pool size using the deuterated creatine (D3Cr) dilution method, for their associations to strength. While the relationship between body composition measures and strength has been studied in older adults, this relationship remains unexplored in athletic populations. This study examined muscle body composition measures using DXA, D3Cr, and BIA and their association with strength in a sample of collegiate athletes. The study enrolled 80 collegiate athletes (40 females) of differing sports disciplines who consumed a 60 mg dose of D3Cr and completed DXA and BIA measures in addition to trunk and leg strength tests. Analysis was sex-stratified using Pearson's correlations, linear regression, and quartile p trend significance. With an average participant age of 21.8 years, whole-body DXA correlations to muscle strength surpassed height- or mass-normalized values. This trend was especially pronounced in trunk strength's relationship with body composition over leg strength, across measurement methods. While DXA LST values were higher than BIA and D3Cr in predicting strength, the values did not differ significantly. Adjustments for age, BMI, and BIA variables didn't enhance this association. A significant trend between DXA LST and all strength measures underscored the equal relevance of DXA and D3Cr muscle mass to strength, favoring whole-body over regional assessments. This calls for future research on muscle mass's effects on LST and functional outcomes in broader groups, highlighting the importance of comprehensive body composition analysis in athletic performance studies.
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Project description:BackgroundBody composition can be accurately quantified based on computed tomography (CT) and typically reflects an individual's overall health status. However, there is a dearth of research examining the relationship between body composition and survival following esophagectomy.MethodsWe created a cohort consisting of 183 patients who underwent esophagectomy for esophageal cancer without neoadjuvant therapy. The cohort included preoperative PET-CT scans, along with pathologic and clinical data, which were collected prospectively. Radiomic, tumor, PET, and body composition features were automatically extracted from the images. Cox regression models were utilized to identify variables associated with survival. Logistic regression and machine learning models were developed to predict one-, three-, and five-year survival rates. Model performance was evaluated based on the area under the receiver operating characteristics curve (ROC/AUC). To test for the statistical significance of the impact of body composition on survival, body composition features were excluded for the best-performing models, and the DeLong test was used.ResultsThe one-year survival model contained 10 variables, including three body composition variables (bone mass, bone density, and visceral adipose tissue (VAT) density), and demonstrated an AUC of 0.817 (95% CI: 0.738-0.897). The three-year survival model incorporated 14 variables, including three body composition variables (intermuscular adipose tissue (IMAT) volume, IMAT mass, and bone mass), with an AUC of 0.693 (95% CI: 0.594-0.792). For the five-year survival model, 10 variables were included, of which two were body composition variables (intramuscular adipose tissue (IMAT) volume and visceral adipose tissue (VAT) mass), with an AUC of 0.861 (95% CI: 0.783-0.938). The one- and five-year survival models exhibited significantly inferior performance when body composition features were not incorporated.ConclusionsBody composition features derived from preoperative CT scans should be considered when predicting survival following esophagectomy.
| S-EPMC10058526 | biostudies-literature
Project description:BackgroundThe relevance of body composition (BC) to performance in sport has long been appreciated with special concern on the total and regional proportion of fat and muscle. Dual-energy X-ray absorptiometry (DXA) is able to accurately measure BC, but it may not be easily available in practice; anthropometry has long been used as a simple and inexpensive field method to objectively assess BC. The aim of this study was twofold: first, to develop and validate a sport-specific anthropometric predictive equation for total body fat mass (FM) and lean mass components in female handball players to be used in the sport setting; second, to cross-validate in female team handball players several independently developed, predictive equations for BC in female athletes.MethodsA total of 85 female team handball players (30 wings, 31 backs, 14 pivots, 10 goalkeepers) of different competitive levels underwent anthropometry and a whole-body DXA scan. Multiple linear regression analysis was used to develop predictive equations in a derivation sample (n = 60) of randomly selected players using demographic and anthropometric variables. The developed equations were used to predict DXA outcomes in an independent validation sample (n = 25).ResultsStatistically significant (P < 0.001) models were developed for total body FM (adjusted R 2 = 0.943, standard error of the estimate, SEE = 1,379 g), percentage FM (adjusted R 2 = 0.877, SEE = 2.00%), fat-free soft tissue mass (FFSTM) (adjusted R 2 = 0.834, SEE = 2,412 g), fat-free mass (FFSTM + bone mineral content; adjusted R 2 = 0.829, SEE = 2,579 g). All models were robust to collinearity. Each developed equation was successfully validated in the remaining 25 players using correlation analysis, mean signed difference, t-test, and Bland-Altman plot. The whole dataset of team handball players (n = 85) was used to cross-validate several predictive equations independently developed by others in female athletes. Equations significantly (P < 0.001 for all; t-test) over- or underestimated the corresponding DXA measurements.DiscussionIt is concluded that in team female handball players the anthropometric equations presented herein are able to estimate body fat and FFSTM with accuracy. Several BC predictive anthropometric equations developed in different female athletic populations revealed inaccurate when tested in team handball players. These results should be of use for coaches, physical trainers, and nutritionists when evaluating the physical status of female team handball players.
| S-EPMC6266933 | biostudies-literature
Project description:BackgroundTo evaluate the correlation between single- and multi-slice cross-sectional thoracolumbar and whole-body compositions.MethodsWe retrospectively included patients who underwent whole-body PET-CT scans from January 2016 to December 2019 at multiple institutions. A priori-developed, deep learning-based commercially available 3D U-Net segmentation provided whole-body 3D reference volumes and 2D areas of muscle, visceral fat, and subcutaneous fat at the upper, middle, and lower endplate of the individual T1-L5 vertebrae. In the derivation set, we analyzed the Pearson correlation coefficients of single-slice and multi-slice averaged 2D areas (waist and T12-L1) with the reference values. We then built prediction models using the top three correlated levels and tested the models in the validation set.ResultsThe derivation and validation datasets included 203 (mean age 58.2 years; 101 men) and 239 patients (mean age 57.8 years; 80 men). The coefficients were distributed bimodally, with the first peak at T4 (coefficient, 0.78) and the second peak at L2-3 (coefficient 0.90). The top three correlations in the abdominal scan range were found for multi-slice waist averaging (0.92) and single-slice L3 and L2 (0.90, each), while those in the chest scan range were multi-slice T12-L1 averaging (0.89), single-slice L1 (0.89), and T12 (0.86). The model performance at the top three levels for estimating whole-body composition was similar in the derivation and validation datasets.ConclusionsSingle-slice L2-3 (abdominal CT range) and L1 (chest CT range) analysis best correlated with whole-body composition around 0.90 (coefficient). Multi-slice waist averaging provided a slightly higher correlation of 0.92.
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Project description:BackgroundIn terms of assessing obesity-associated risk, quantification of visceral adipose tissue (VAT) has become increasingly important in risk assessment for cardiovascular and metabolic diseases. However, differences exist in the accuracy of various modalities, with a lack of up-to-date comparison with three-dimensional whole volume assessment.AimsUsing CT or MRI three-dimensional whole volume VAT as a reference, we evaluated the correlation of various commonly used modalities and techniques namely body impedance analysis (BIA), dual-energy x-ray absorptiometry (DXA) as well as single slice CT to establish how these methods compare.MethodsWe designed the study in two parts. First, we performed an intra-individual comparison of the 4558 participants from the UK Biobank cohorts with matching data of MRI abdominal body composition, DXA with VAT estimation, and BIA. Second, we evaluated 174 CT scans from the publicly available dataset to assess the correlation of the commonly used single-slice technique compared to three-dimensional VAT volume.ResultsAcross the UK Biobank cohort, the DXA-derived VAT measurement correlated better (R2 0.94, p<0.0001) than BIA (R2 0.49, p<0.0001) with reference three-dimensional volume on MRI. However, DXA-derived VAT correlation was worse for participants with a BMI of < 20 (R2 = 0.62, p=0.0013). A commonly used single slice method on CT demonstrated a modest correlation (R2 between 0.51 - 0.64), with best values at L3- and L4 (R2 L3 = 0.63, p<0.0001; L4 = 0.64, p<0.0001) compared to reference three-dimensional volume. Combining multiple slices yielded a better correlation, with a strong correlation when L2-L3 levels were combined (R2 = 0.92, p<0.0001).ConclusionWhen deployed at scale, DXA-derived VAT volume measurement shows excellent correlation with three-dimensional volume on MRI based on the UK Biobank cohort. Whereas a single slice CT technique demonstrated moderate correlation with three-dimensional volume on CT, with a stronger correlation achieved when multiple levels were combined.
| S-EPMC10368369 | biostudies-literature
Project description:BackgroundAccurate and precise methods to measure of body composition in infancy and childhood are needed.ObjectivesThis study evaluated differences and precision of three methods when compared with the four-compartment (4C) model for estimating fat mass (FM).MethodsFM of children (age 14 days to 6 years of age, N = 346) was obtained using quantitative nuclear magnetic resonance (QMR, EchoMRI-AH), air-displacement plethysmography (ADP, PeaPod, less than or equal to 8 kg, BodPod age 6 years or older), and dual-energy X-ray absorptiometry (DXA, Hologic QDR). The 4C model was computed. Correlation, concordance, and Bland-Altman analyses were performed.ResultsIn infants, PeaPod had high individual FM accuracy, whereas DXA had high group FM accuracy compared with 4C. In children, DXA had high group and individual FM accuracies compared with 4C. QMR underestimated group FM in infants and children (300 and 510 g, respectively). The instrument FM precision was best for QMR (10 g) followed by BodPod (34 g), PeaPod (38 g), and DXA (45 g).ConclusionsIn infants, PeaPod was the best method to estimate individual FM whereas DXA was best to estimate group FM. In children, DXA was best to estimate individual and group FM. QMR had the highest instrument precision.
| S-EPMC7323309 | biostudies-literature
Project description:BackgroundLow skeletal muscle mass and density, as assessed by CT-body composition (CT-BC), are recognised to have prognostic value in non-cancer and cancer patients. The aim of the present study was to compare CT-BC parameters between non-cancer (abdominal aortic aneurysm, AAA) and cancer (colorectal cancer, CRC) patients.MethodsTwo retrospective multicentre cohorts were compared. Thresholds of visceral fat area (VFA, Doyle), skeletal fat index (SFI, Ebadi), skeletal muscle index (SMI, Martin), and skeletal muscle density (SMD, Martin) were applied to these cohorts and compared. The systemic inflammatory response (SIR) was measured by the systemic inflammatory grade (SIG).Results1695 patients were included; 759 patients with AAA and 936 patients with CRC. Low SMD (33% vs. 66%, p <0.001) was more prevalent in the CRC cohort. Low SMI prevalence was similar in both cohorts (51% vs. 51%, p = 0.80). Compared with the AAA cohort, the CRC cohort had a higher prevalence of raised SIG (p <0.001). Increasing age (OR 1.54, 95% CI 1.38-1.72, p < 0.001) and elevated SIG (OR 1.23, 95% CI 1.09-1.40, p = 0.001) were independently associated with increased odds of low SMI. Increasing age (OR 1.90, 95% CI 1.66-2.17, p < 0.001) CRC diagnosis (OR 5.89, 95% CI 4.55-7.62, p < 0.001), ASA > 2 (OR 1.37, 95% CI 1.08-1.73, p = 0.01), and elevated SIG (OR 1.19, 95% CI 1.03-1.37, p = 0.02) were independently associated with increased odds of low SMD.ConclusionsIncreasing age and systemic inflammation appear to be important determinants of loss of skeletal muscle mass and quality irrespective of disease.
| S-EPMC10956827 | biostudies-literature
Project description:BACKGROUND:Due to a clinical and public health interest of neck circumference (NC), a better understanding of this simple anthropometric measurement, as a valid marker of body composition is necessary. METHODS:A total of 119 young healthy adults participated in this study. NC was measured over the thyroid cartilage and perpendicular to the longitudinal axis of the neck. Body weight, height, waist circumference (WC), and hip circumference were measured. A Dual X-ray absorptiometry (DXA) scan was used to determine fat mass, lean mass, and visceral adipose tissue (VAT). Additionally, body mass index (BMI) and triponderal mass index (TMI), the waist to hip and waist to height ratios, and the fat mass and lean mass indexes (FMI and LMI, respectively) were calculated. RESULTS:NC was positively associated in women (W) and men (M), with BMI (rW = 0.70 and rM = 0.84, respectively), TMI (rW = 0.63 and rM = 0.80, respectively), WC (rW = 0.75 and rM = 0.86, respectively), VAT (rW = 0.74 and rM = 0.82, respectively), Waist/hip (rW = 0.51 and rM = 0.67, respectively), Waist/height (rW = 0.68 and rM = 0.83, respectively) and FMI (rW = 0.61 and rM = 0.81, respectively). The association between NC and indicators of body composition was however weaker than that observed by BMI, TMI, WC and Waist/height in both women and men. It is of note that in women, NC was associated with FMI, VAT and LMI independently of BMI. In men, adding NC to anthropometric variables did not improve the prediction of body composition, while slight improvements were observed in women. CONCLUSIONS:Taken together, the present study provides no indication for NC as a useful proxy of body composition parameters in young adults, yet future studies should explore its usefulness as a measure to use in combination with BMI, especially in women.
| S-EPMC7071265 | biostudies-literature
Project description:ObjectivesThe aim of this study was to evaluate whether simple 2D measurements in axial slices of head and neck CT examinations correlate with generally established measurements of body composition in abdominal CT at the height of the third lumbar vertebra and thus allow for an estimation of muscle and fat masses.MethodsOne hundred twenty-two patients who underwent concurrent CT of the head and neck and the abdomen between July 2016 and July 2020 were retrospectively included. For a subset of 30 patients, additional bioelectrical impedance analysis (BIA) was available. Areas of paraspinal muscles at the height of the third (C3) and fifth cervical vertebrae (C5) as well as the total cross-sectional area at the height of C3 and at the submandibular level were correlated with the results of abdominal measurements and BIA. Furthermore, intra- and interreader variabilities of all measurements were assessed.ResultsRegarding adipose tissue, good correlations were found between the total cross-sectional area of the patient's body at the submandibular level and at the height of C3 between both abdominal measurements and BIA results (r = 0.8-0.92; all p < 0.001). Regarding muscle, the total paraspinal muscle area at the height of C3 and C5 showed strong correlations with abdominal measurements and moderate to strong correlations with BIA results (r = 0.44-0.80; all p < 0.001), with the muscle area on C5 yielding slightly higher correlations.ConclusionsBody composition information can be obtained with comparable reliability from head and neck CT using simple biplanar measurements as from abdominal CT.Key points• The total paraspinal muscle area at the height of C3 and C5 correlates strongly with abdominal muscle mass. • The total cross-sectional area at the submandibular level and at the height of C3 shows good correlations with abdominal fat mass. • The described measurements facilitate a rapid, opportunistic assessment of relevant body composition parameters.
| S-EPMC9381610 | biostudies-literature