Body composition from single versus multi-slice abdominal computed tomography: Concordance and associations with colorectal cancer survival

Ethnic differences in CT derived abdominal body composition measures: a comparative retrospect pilot study between European and Inuit study population

Understanding ethnic variations in body composition is crucial for assessing health risks. Universal models may not suit all ethnicities, and there is limited data on the Inuit population. This study aimed to compare body composition between Inuit and European adults using computed tomography (CT) scans and to investigate the influence of demographics on these measurements. A retrospective analysis was conducted on 50 adults (29 Inuit and 21 European) who underwent standard trauma CT scans. Measurements focused on skeletal muscle index (SMI), various fat indices, and densities at the third lumbar vertebra level, analyzed using the Wilcoxon-Mann-Whitney test and multiple linear regression. Inuit women showed larger fat tissue indices and lower muscle and fat densities than European women. Differences in men were less pronouncehd, with only Intramuscular fat density being lower among Inuit men. Regression indicated that SMI was higher among men, and skeletal muscle density decreased with Inuit ethnicity and age, while visceral fat index was positively associated with age. This study suggests ethnic differences in body composition measures particularly among women, and indicates the need for Inuit-specific body composition models. It higlights the importance of further research into Inuit-specific body composition measurements for better health risk assessment.

Volumetric body composition analysis of the Cancer Genome Atlas reveals novel body composition traits and molecular markers Associated with Renal Carcinoma outcomes

Clinically, the body mass index remains the most frequently used metric of overall obesity, although it is flawed by its inability to account for different adipose (i.e., visceral, subcutaneous, and inter/intramuscular) compartments, as well as muscle mass. Numerous prior studies have demonstrated linkages between specific adipose or muscle compartments to outcomes of multiple diseases. Although there are no universally accepted standards for body composition measurement, many studies use a single slice at the L3 vertebral level. In this study, we use computed tomography (CT) studies from patients in The Cancer Genome Atlas (TCGA) to compare current L3-based techniques with volumetric techniques, demonstrating potential limitations with level-based approaches for assessing outcomes. In addition, we identify gene expression signatures in normal kidney that correlate with fat and muscle body composition traits that can be used to predict sex-specific outcomes in renal cell carcinoma.

Evaluation of a fully automated computed tomography image segmentation method for fast and accurate body composition measurements

INTRODUCTION

Body composition evaluation can be used to assess patients' nutritional status to predict clinical outcomes. To facilitate reliable and time-efficient body composition measurements eligible for clinical practice, fully automated computed tomography segmentation methods were developed. The aim of this study was to evaluate automated segmentation by Data Analysis Facilitation Suite in an independent dataset.

MATERIALS AND METHODS

Preoperative computed tomography images were used of 165 patients undergoing cytoreductive surgery with hyperthermic intraperitoneal chemotherapy from 2014 to 2019. Manual and automated measurements of skeletal muscle mass (SMM), visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and intramuscular adipose tissue (IMAT) were performed at the third lumbar vertebra. Segmentation accuracy of automated measurements was assessed using the Jaccard index and intra-class correlation coefficients.

RESULTS

Automatic segmentation provided accurate measurements compared to manual analysis, resulting in Jaccard score coefficients of 94.9 for SMM, 98.4 for VAT, 99.1 for SAT, and 79.4 for IMAT. Intra-class correlation coefficients ranged from 0.98 to 1.00. Automated measurements on average overestimated SMM and SAT areas compared to manual analysis, with mean differences (±2 standard deviations) of 1.10 (-1.91 to 4.11) and 1.61 (-2.26 to 5.48) respectively. For VAT and IMAT, automated measurements on average underestimated the areas with mean differences of -1.24 (-3.35 to 0.87) and -0.93 (-5.20 to 3.35), respectively.

CONCLUSIONS

Commercially available Data Analysis Facilitation Suite provides similar results compared to manual measurements of body composition at the level of third lumbar vertebra. This software provides accurate and time-efficient body composition measurements, which is necessary for implementation in clinical practice.

Validation of an automated segmentation method for body composition analysis in colorectal cancer patients using diagnostic abdominal computed tomography images

BACKGROUND & AIMS

Several automated programs have been developed to facilitate body composition analysis of images from abdominal computed tomography (CT) scans. External validation in patients with colorectal cancer is necessary for use in research and clinical practice. Our aim was to validate an automatic method (AutoMATiCA) of segmenting CT images at the third lumbar level (L3) from patients with colorectal cancer, by comparing with manual segmentation.

METHODS

Diagnostic abdominal CT scans of consecutive patients with stage I-III colorectal cancer were analysed to measure cross-sectional areas and tissue densities of skeletal muscle and intra-muscular, visceral, and subcutaneous adipose tissue. Trained analysts performed manual segmentation of L3 CT images using SliceOmatic. Automatic segmentation was performed using AutoMATiCA, an open-source software. The Dice similarity coefficient (DSC) was calculated to assess segmentation accuracy. Agreement of automatic with manual segmentation was evaluated using intra-class correlation coefficients (ICCs) and Bland-Altman plots with limits of agreement.

RESULTS

A total of 292 scans were included, of which 62% were from male patients. The agreement of AutoMATiCA with the manual segmentation was excellent, with median DSC values ranging from 0.900 to 0.991 and ICCs above 0.95 for all segmented areas. No systematic deviations were observed in Bland-Altman plots for all segmented areas, with overall narrow limits of agreement.

CONCLUSIONS

AutoMATiCA provides an accurate segmentation of abdominal CT images from patients with colorectal cancer. Our findings support its use as a highly efficient automated tool for body composition analysis in research and potentially also in clinical practice.

Automated extraction of body composition metrics from abdominal CT or MR imaging: A scoping review

PURPOSE

To review methodological approaches for automated segmentation of subcutaneous adipose tissue, visceral adipose tissue, and skeletal muscle from abdominal cross-sectional imaging for body composition analysis.

METHOD

Four databases were searched for publications describing automated segmentation of subcutaneous adipose tissue, visceral adipose tissue, and/or skeletal muscle from abdominal CT or MR imaging between 2019 and 2023. Included reports were evaluated to assess how imaging modality, cohort size, vertebral level, model dimensionality, and use of a volume or single slice affected segmentation accuracy and/or clinical utility. Exclusion criteria included reports not in English language, manual or semi-automated segmentation methods, reports prior to 2019 or solely of paediatric patients, and those not describing the use of abdominal CT or MR.

RESULTS

After exclusions, 172 reports were included in the review. CT imaging was utilised approximately four times as often as MRI, and segmentation accuracy did not significantly differ between the two modalities. Cohort size had no significant effect on segmentation accuracy. There was little evidence to refute the current practice of extracting body composition metrics from the third lumbar vertebral level. There was no clear benefit of using a 3D model to perform segmentation over a 2D approach.

CONCLUSION

Automated segmentation of intra-abdominal soft tissues for body composition analysis is an intense area of research activity. Segmentation accuracy is not affected by cross-sectional imaging modality. Extracting metrics from a single slice at the third lumbar vertebral level is a common approach, however, extracting metrics from a volumetric slab surrounding this level may increase the resilience of the technique, which is important for clinical translation. A paucity of publicly available datasets led to most reports using different data sources, preventing direct comparison of segmentation techniques. Future efforts should prioritise creating a standardised dataset to facilitate benchmarking of different algorithms and subsequent clinical adoption.

Comparative analysis of body composition using torso CT from PET/CT with bioelectrical impedance and muscle strength in healthy adults

The role of torso computed tomography (CT) in evaluating body composition has been unexplored. This study assessed the potential of low-dose torso CT from positron emission tomography (PET)/CT for analyzing body composition and its relation to muscle strength. We retrospectively recruited 384 healthy Korean adults (231 men, 153 women) who underwent torso 18F-FDG PET/CT, bioelectrical impedance analysis (BIA), and muscle strength tests (handgrip strength [HGS] and knee extension strength [KES]). CT images were segmented into three compartments: torso volumetric, abdominal volumetric, and abdominal areal. Muscle amounts from each compartment were indexed to height (m2). BIA and HGS served as reference standards, with correlation coefficients (r) calculated. Torso muscle volumetric index (TorsoMVI) had the strongest correlations with BIA-derived values (r = 0.80 for men; r = 0.73 for women), surpassing those from the abdominal compartments. TorsoMVI was also correlated significantly with HGS (r = 0.39, p < 0.01) and differentiated between normal and possible sarcopenia in men (n = 225, 5960 ± 785 cm3/m2 vs. n = 6, 5210 ± 487 cm3/m2, p = 0.02). In women, KES correlated more strongly with muscle parameters than HGS. Despite gender-specific variations, torso CT-derived parameters show promise for evaluating body composition and sarcopenia.

Effectiveness of magnetic resonance imaging and spiral computed tomography in the staging and treatment prognosis of colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is a prevalent cancer type in clinical settings; its early signs can be difficult to detect, which often results in late-stage diagnoses in many patients. The early detection and diagnosis of CRC are crucial for improving treatment success and patient survival rates. Recently, imaging techniques have been hypothesized to be essential in managing CRC, with magnetic resonance imaging (MRI) and spiral computed tomography (SCT) playing a significant role in enhancing diagnostic and treatment approaches.

AIM

To explore the effectiveness of MRI and SCT in the preoperative staging of CRC and the prognosis of laparoscopic treatment.

METHODS

Ninety-five individuals admitted to Zhongshan Hospital Xiamen University underwent MRI and SCT and were diagnosed with CRC. The precision of MRI and SCT for the presurgical classification of CRC was assessed, and pathological staging was used as a reference. Receiver operating characteristic curves were used to evaluate the diagnostic efficacy of blood volume, blood flow, time to peak, permeability surface, blood reflux constant, volume transfer constant, and extracellular extravascular space volume fraction on the prognosis of patients with CRC.

RESULTS

Pathological biopsies confirmed the following CRC stages: 23, 23, 32, and 17 at T1, T2, T3, and T4, respectively. There were 39 cases at the N0 stage, 22 at N1, 34 at N2, 44 at M0 stage, and 51 at M1. Using pathological findings as the benchmark, the combined use of MRI and SCT for preoperative TNM staging in patients with CRC demonstrated superior sensitivity, specificity, and accuracy compared with either modality alone, with a statistically significant difference in accuracy (P < 0.05). Receiver operating characteristic curve analysis revealed the predictive values for laparoscopic treatment prognosis, as indicated by the areas under the curve for blood volume, blood flow, time to peak, and permeability surface, blood reflux constant, volume transfer constant, and extracellular extravascular space volume fraction were 0.750, 0.683, 0.772, 0.761, 0.709, 0.719, and 0.910, respectively. The corresponding sensitivity and specificity values were also obtained (P < 0.05).

CONCLUSION

MRI with SCT is effective in the clinical diagnosis of patients with CRC and is worthy of clinical promotion.

Skeletal muscle density performance for screening frailty in older adults with cancer and the impact of diabetes: The CARE Registry

INTRODUCTION

Skeletal muscle density (SMD) measurements from imaging scans identify myosteatosis and could screen patients for geriatric assessment. We assessed SMD performance as a screening tool to identify older adults with cancer likely to be frail and who could benefit from in-depth assessment; we compared performance by sex and diabetes status.

MATERIALS AND METHODS

We analyzed patients in the Cancer & Aging Resilience Evaluation (CARE) Registry. Frailty and diabetes were captured using a patient-reported geriatric assessment (CARE tool). Frailty was defined using CARE frailty index (CARE-FI) based on principles of deficit accumulation. SMD was calculated from computed tomography scans (L3 vertebrae). Analyses were conducted by sex and diabetes status. Scatterplots and linear regression described crude associations between SMD and frailty score. Classification performance (frail vs. non-frail) was analyzed with (1) area under the receiver operating characteristic curves (AUC) and confidence intervals (CIs); and (2) sensitivity/specificity for sex-specific SMD quartile cut-offs (Q1, median, Q3). Performance was compared between patients with and without diabetes using differences and estimated CIs (2000 bootstrap replicates). We additionally calculated positive and negative likelihood ratios (LR+, LR-).

RESULTS

The analytic cohort included 872 patients (39% female, median age 68 years, 27% with diabetes) with predominately stage III/IV gastrointestinal cancer; >60% planning to initiate first-line chemotherapy. SMD was negatively associated with frailty score; models were best fit in male patients with diabetes. AUC estimates for female (range: 0.58-0.62) and male (0.58-0.68) patients were low. Q3 cut-offs had high sensitivity (range: 0.76-0.89), but poor specificity (0.25-0.34). Diabetes did not impact estimates for female patients. Male patients with diabetes had greater sensitivity estimates compared to those without (sensitivity differences: 0.23 [0.07, 0.38], 0.08 [-0.07, 0.24], and 0.11 [0.00, 0.22] for Q1, median, Q3, respectively). LR estimates were most notable for male patients with diabetes (LR+ = 2.92, Q1 cut-off; LR- = 0.46, Q3 cut-off).

DISCUSSION

Using SMD alone to screen older patients for geriatric assessment requires improvement. High-sensitivity cut-off points could miss 11-24% of patients with frailty, and many non-frail patients may be flagged. Screening with SMD is practical but work is needed to understand clinical andresource impacts of different cut-off points. Future research should evaluate performance with additional clinical data and in subgroups.

Body weight and composition endpoints in cancer cachexia clinical trials: Systematic Review 4 of the cachexia endpoints series

Significant variation exists in the outcomes used in cancer cachexia trials, including measures of body composition, which are often selected as primary or secondary endpoints. To date, there has been no review of the most commonly selected measures or their potential sensitivity to detect changes resulting from the interventions being examined. The aim of this systematic review is to assess the frequency and diversity of body composition measures that have been used in cancer cachexia trials. MEDLINE, Embase and Cochrane Library databases were systematically searched between January 1990 and June 2021. Eligible trials examined adults (≥18 years) who had received an intervention aiming to treat or attenuate the effects of cancer cachexia for >14 days. Trials were also of a prospective controlled design and included body weight or at least one anthropometric, bioelectrical or radiological endpoint pertaining to body composition, irrespective of the modality of intervention (e.g., pharmacological, nutritional, physical exercise and behavioural) or comparator. Trials with a sample size of <40 patients were excluded. Data extraction used Covidence software, and reporting followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidance. This review was prospectively registered (PROSPERO: CRD42022276710). A total of 84 clinical trials, comprising 13 016 patients, were eligible for inclusion. Non-small-cell lung cancer and pancreatic cancer were studied most frequently. The majority of trial interventions were pharmacological (52%) or nutritional (34%) in nature. The most frequently reported endpoints were assessments of body weight (68 trials, n = 11 561) followed by bioimpedance analysis (BIA)-based estimates (23 trials, n = 3140). Sixteen trials (n = 3052) included dual-energy X-ray absorptiometry (DEXA)-based endpoints, and computed tomography (CT) body composition was included in eight trials (n = 841). Discrepancies were evident when comparing the efficacy of interventions using BIA-based estimates of lean tissue mass against radiological assessment modalities. Body weight, BIA and DEXA-based endpoints have been most frequently used in cancer cachexia trials. Although the optimal endpoints cannot be determined from this review, body weight, alongside measurements from radiological body composition analysis, would seem appropriate. The choice of radiological modality is likely to be dependent on the trial setting, population and intervention in question. CT and magnetic resonance imaging, which have the ability to accurately discriminate tissue types, are likely to be more sensitive and provide greater detail. Endpoints are of particular importance when aligned with the intervention's mechanism of action and/or intended patient benefit.

Establishment of a novel weight reduction model after laparoscopic sleeve gastrectomy based on abdominal fat area

In light of ongoing research elucidating the intricacies of obesity and metabolic syndrome, the role of abdominal fat (especially visceral fat) has been particularly prominent. Studies have revealed that visceral adipose tissue can accelerate the development of metabolic syndrome by releasing various bioactive compounds and hormones, such as lipocalin, leptin and interleukin. A retrospective analysis was performed on the clinical data of 167 patients with obesity. Among them, 105 patients who satisfied predefined inclusion and exclusion criteria were included. The parameters evaluated included total abdominal fat area (TAFA), laboratory indicators and anthropometric measurements. Weight reduction was quantified through percent total weight loss (%TWL) and percent excess weight loss (%EWL) postoperatively. Binary logistic regression analysis and receiver operating characteristic (ROC) curve analysis were employed to identify predictors of weight loss. Binary logistic regression analysis emphasized that total abdominal fat area was an independent predictor of %EWL ≥75% (p < 0.001). Total abdominal fat area (p = 0.033) and BMI (p = 0.003) were independent predictors of %TWL ≥30%. In our cohort, %TWL ≥30% at 1 year after surgery was closely related to the abdominal fat area and BMI. Based on these results, we formulated a novel model based on these factors, exhibiting superior predictive value for excellent weight loss.

Clinical, functional, and opportunistic CT metrics of sarcopenia at the point of imaging care: analysis of all-cause mortality

PURPOSE

This study examines clinical, functional, and CT metrics of sarcopenia and all-cause mortality in older adults undergoing outpatient imaging.

METHODS

The study included outpatients ≥ 65 years of age undergoing CT or PET/CT at a tertiary care institution. Assessments included screening questionnaires for sarcopenia (SARC-F) and frailty (FRAIL scale), and measurements of grip strength and usual gait speed (6 m course). Skeletal muscle area (SMA), index (SMI, area/height2) and density (SMD) were measured on CT at T12 and L3. A modified SMI was also examined (SMI-m, area/height). Mortality risk was studied with Cox proportional hazard analysis.

RESULTS

The study included 416 patients; mean age 73.8 years [sd 6.2]; mean follow-up 2.9 years (sd 1.34). Abnormal grip, SARC-F, and FRAIL scale assessments were associated with higher mortality risk (HR [95%CI] = 2.0 [1.4-2.9], 1.6 [1.1-2.3], 2.0 [1.4-2.8]). Adjusting for age, higher L3-SMA, T12-SMA, T12-SMI and T12-SMI-m were associated with lower mortality risk (HR [95%CI] = 0.80 [0.65-0.90], 0.76 [0.64-0.90], 0.84 [0.70-1.00], and 0.80 [0.67-0.90], respectively). T12-SMD and L3-SMD were not predictive of mortality. After adjusting for abnormal grip strength and FRAIL scale assessments, T12-SMA and T12-SMI-m remained predictive of mortality risk (HR [95%CI] = 0.83 [0.70-1.00] and 0.80 [0.67-0.97], respectively).

CONCLUSION

CT areal metrics were weaker predictors of all-cause mortality than clinical and functional metrics of sarcopenia in our older patient cohort; a CT density metric (SMD) was not predictive. Of areal CT metrics, SMI (area/height2) appeared to be less effective than non-normalized SMA or SMA normalized by height1.

Biomarkers of Body Composition

The importance and impact of imaging biomarkers has been increasing over the past few decades. We review the relevant clinical and imaging terminology needed to understand the clinical and research applications of body composition. Imaging biomarkers of bone, muscle, and fat tissues obtained with dual-energy X-ray absorptiometry, computed tomography, magnetic resonance imaging, and ultrasonography are described.

Abdominal adipose tissue and type 2 diabetic kidney disease: adipose radiology assessment, impact, and mechanisms

Diabetic kidney disease (DKD) is a significant healthcare burden worldwide that substantially increases the risk of kidney failure and cardiovascular events. To reduce the prevalence of DKD, extensive research is being conducted to determine the risk factors and consequently implement early interventions. Patients with type 2 diabetes mellitus (T2DM) are more likely to be obese. Abdominal adiposity is associated with a greater risk of kidney damage than general obesity. Abdominal adipose tissue can be divided into different fat depots according to the location and function, including visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), perirenal adipose tissue (PAT), and renal sinus adipose tissue (RSAT), which can be accurately measured by radiology techniques, such as computed tomography (CT) and magnetic resonance imaging (MRI). Abdominal fat depots may affect the development of DKD through different mechanisms, and radiologic abdominal adipose characteristics may serve as imaging indicators of DKD risk. This review will first describe the CT/MRI-based assessment of abdominal adipose depots and subsequently describe the current studies on abdominal adipose tissue and DKD development, as well as the underlying mechanisms in patients of T2DM with DKD.

SARC-F as a screening tool to detect computed tomography-based sarcopenia and myosteatosis among older adults with cancer

BACKGROUND

The European Working Group on Sarcopenia in Older People (EWGSOP) recommends SARC-F as a tool for identifying sarcopenia among older adults. However, the role of SARC-F among older adults with cancer remains unexplored. We aimed to evaluate the diagnostic utility of SARC-F to identify those with sarcopenia, or low muscle mass (using skeletal muscle index [SMI]), and myosteatosis (using skeletal muscle density [SMD]) from computed tomography (CT) imaging and the association of SARC-F with all-cause mortality.

METHODS

Older adults (≥60 years) presenting for initial consultation at UAB medical oncology clinic who underwent geriatric assessment were enrolled in a prospective cohort study. We identified study participants who completed SARC-F screening and had available CT imaging within 60 days of study enrollment. Using single-slice CT images at the L3 vertebral level, we computed SMI and SMD using published methods. Sarcopenia and myosteatosis were defined using published cutpoints. We calculated the sensitivity and specificity of SARC-F for detecting low muscle mass and low muscle density using published thresholds. Finally, we computed the impact of SARC-F and CT measures on overall survival using Kaplan-Meier curves and Cox regression models, after adjusting for age, sex, cancer type, and cancer stage.

RESULTS

We identified 212 older adults with a median age of 68.8 years; with 60.8% males, 76.6% whites, and pancreatic cancer (21.2%) being the most common malignancy. In the overall cohort, 30.7% had abnormal SARC-F using published cutpoints. SARC-F ≥ 4 had a sensitivity of 35% and a specificity of 76% to identify low muscle mass. SARC-F ≥ 4 had a sensitivity of 38% and a specificity of 74% to identify low muscle density. Those with SARC-F ≥ 4 and low SMI/SMD had worse survival compared to those with low SMI/SMD alone. Incorporating SARC-F improved survival prognostication beyond SMI and SMD (HR = 3.1; p < 0.001; Harrel's C from 0.73 to 0.76).

CONCLUSIONS

SARC-F as a screening tool has limited diagnostic utility for identifying older adults with low muscle mass and/or density. However, SARC-F retains prognostic value independent of CT-based muscle measures in predicting mortality among older adults with cancer.

Application of the D3 -creatine muscle mass assessment tool to a geriatric weight loss trial: A pilot study

BACKGROUND

Traditionally, weight loss (WL) trials utilize dual energy X-ray absorptiometry (DXA) to measure lean mass. This method assumes lean mass, as the sum of all non-bone and non-fat tissue, is a reasonable proxy for muscle mass. In contrast, the D3 -creatine (D3 Cr) dilution method directly measures whole body skeletal muscle mass, although this method has yet to be applied in the context of a geriatric WL trial. The purpose of this project was to (1) describe estimates of change and variability in D3 Cr muscle mass in older adults participating in an intentional WL intervention and (2) relate its change to other measures of body composition as well as muscle function and strength.

METHODS

The INVEST in Bone Health trial (NCT04076618), used as a scaffold for this ancillary pilot project, is a three-armed, 12-month randomized, controlled trial designed to determine the effects of resistance training or weighted vest use during intentional WL on a battery of musculoskeletal health outcomes among 150 older adults living with obesity. A convenience sample of 24 participants (n = 8/arm) are included in this analysis. At baseline and 6 months, participants were weighed, ingested a 30 mg D3 Cr tracer dose, provided a fasted urine sample 3-6 days post-dosage, underwent DXA (total body fat and lean masses, appendicular lean mass) and computed tomography (mid-thigh and trunk muscle/intermuscular fat areas) scans, and performed 400-m walk, stair climb, knee extensor strength, and grip strength tests.

RESULTS

Participants were older (68.0 ± 4.4 years), mostly White (75.0%), predominantly female (66.7%), and living with obesity (body mass index: 33.8 ± 2.7 kg/m2 ). Six month total body WL was -10.3 (95% confidence interval, CI: -12.7, -7.9) kg. All DXA and computed tomography-derived body composition measures were significantly decreased from baseline, yet D3 Cr muscle mass did not change [+0.5 (95% CI: -2.0, 3.0) kg]. Of muscle function and strength measures, only grip strength significantly changed [+2.5 (95% CI: 1.0, 4.0) kg] from baseline.

CONCLUSIONS

Among 24 older adults, significant WL with or without weighted vest use or resistance training over a 6-month period was associated with significant declines in all bioimaging metrics, while D3 Cr muscle mass and muscle function and strength were preserved. Treatment assignment for the trial remains blinded; therefore, full interpretation of these findings is limited. Future work in this area will assess change in D3 Cr muscle mass by parent trial treatment group assignment in all study participants.

Imaging modalities for measuring body composition in patients with cancer: opportunities and challenges

Body composition assessment (ie, the measurement of muscle and adiposity) impacts several cancer-related outcomes including treatment-related toxicities, treatment responses, complications, and prognosis. Traditional modalities for body composition measurement include body mass index, body circumference, skinfold thickness, and bioelectrical impedance analysis; advanced imaging modalities include dual energy x-ray absorptiometry, computerized tomography, magnetic resonance imaging, and positron emission tomography. Each modality has its advantages and disadvantages, thus requiring an individualized approach in identifying the most appropriate measure for specific clinical or research situations. Advancements in imaging approaches have led to an abundance of available data, however, the lack of standardized thresholds for classification of abnormal muscle mass or adiposity has been a barrier to adopting these measurements widely in research and clinical care. In this review, we discuss the different modalities in detail and provide guidance on their unique opportunities and challenges.

Body composition and lung cancer-associated cachexia in TRACERx

Cancer-associated cachexia (CAC) is a major contributor to morbidity and mortality in individuals with non-small cell lung cancer. Key features of CAC include alterations in body composition and body weight. Here, we explore the association between body composition and body weight with survival and delineate potential biological processes and mediators that contribute to the development of CAC. Computed tomography-based body composition analysis of 651 individuals in the TRACERx (TRAcking non-small cell lung Cancer Evolution through therapy (Rx)) study suggested that individuals in the bottom 20th percentile of the distribution of skeletal muscle or adipose tissue area at the time of lung cancer diagnosis, had significantly shorter lung cancer-specific survival and overall survival. This finding was validated in 420 individuals in the independent Boston Lung Cancer Study. Individuals classified as having developed CAC according to one or more features at relapse encompassing loss of adipose or muscle tissue, or body mass index-adjusted weight loss were found to have distinct tumor genomic and transcriptomic profiles compared with individuals who did not develop such features. Primary non-small cell lung cancers from individuals who developed CAC were characterized by enrichment of inflammatory signaling and epithelial-mesenchymal transitional pathways, and differentially expressed genes upregulated in these tumors included cancer-testis antigen MAGEA6 and matrix metalloproteinases, such as ADAMTS3. In an exploratory proteomic analysis of circulating putative mediators of cachexia performed in a subset of 110 individuals from TRACERx, a significant association between circulating GDF15 and loss of body weight, skeletal muscle and adipose tissue was identified at relapse, supporting the potential therapeutic relevance of targeting GDF15 in the management of CAC.