Body composition analysis using CT and MRI: intra-individual intermodal comparison of muscle mass and myosteatosis

Association between myosteatosis and impaired glucose metabolism: A deep learning whole-body magnetic resonance imaging population phenotyping approach

BACKGROUND

There is increasing evidence that myosteatosis, which is currently not assessed in clinical routine, plays an important role in risk estimation in individuals with impaired glucose metabolism, as it is associated with the progression of insulin resistance. With advances in artificial intelligence, automated and accurate algorithms have become feasible to fill this gap.

METHODS

In this retrospective study, we developed and tested a fully automated deep learning model using data from two prospective cohort studies (German National Cohort [NAKO] and Cooperative Health Research in the Region of Augsburg [KORA]) to quantify myosteatosis on whole-body T1-weighted Dixon magnetic resonance imaging as (1) intramuscular adipose tissue (IMAT; the current standard) and (2) quantitative skeletal muscle (SM) fat fraction (SMFF). Subsequently, we investigated the two measures for their discrimination of and association with impaired glucose metabolism beyond baseline demographics (age, sex and body mass index [BMI]) and cardiometabolic risk factors (lipid panel, systolic blood pressure, smoking status and alcohol consumption) in asymptomatic individuals from the KORA study. Impaired glucose metabolism was defined as impaired fasting glucose or impaired glucose tolerance (140-200 mg/dL) or prevalent diabetes mellitus.

RESULTS

Model performance was high, with Dice coefficients of ≥0.81 for IMAT and ≥0.91 for SM in the internal (NAKO) and external (KORA) testing sets. In the target population (380 KORA participants: mean age of 53.6 ± 9.2 years, BMI of 28.2 ± 4.9 kg/m2, 57.4% male), individuals with impaired glucose metabolism (n = 146; 38.4%) were older and more likely men and showed a higher cardiometabolic risk profile, higher IMAT (4.5 ± 2.2% vs. 3.9 ± 1.7%) and higher SMFF (22.0 ± 4.7% vs. 18.9 ± 3.9%) compared to normoglycaemic controls (all P ≤ 0.005). SMFF showed better discrimination for impaired glucose metabolism than IMAT (area under the receiver operating characteristic curve [AUC] 0.693 vs. 0.582, 95% confidence interval [CI] [0.06-0.16]; P < 0.001) but was not significantly different from BMI (AUC 0.733 vs. 0.693, 95% CI [-0.09 to 0.01]; P = 0.15). In univariable logistic regression, IMAT (odds ratio [OR] = 1.18, 95% CI [1.06-1.32]; P = 0.004) and SMFF (OR = 1.19, 95% CI [1.13-1.26]; P < 0.001) were associated with a higher risk of impaired glucose metabolism. This signal remained robust after multivariable adjustment for baseline demographics and cardiometabolic risk factors for SMFF (OR = 1.10, 95% CI [1.01-1.19]; P = 0.028) but not for IMAT (OR = 1.14, 95% CI [0.97-1.33]; P = 0.11).

CONCLUSIONS

Quantitative SMFF, but not IMAT, is an independent predictor of impaired glucose metabolism, and discrimination is not significantly different from BMI, making it a promising alternative for the currently established approach. Automated methods such as the proposed model may provide a feasible option for opportunistic screening of myosteatosis and, thus, a low-cost personalized risk assessment solution.

CT-derived body composition and differential association with age, TNM stage and systemic inflammation in patients with colon cancer

Low skeletal muscle index/density (SMI/SMD) is prevalent in cancer, adversely prognostic and associated with tumour stage and the systemic inflammatory response (SIR). Age and SMI/SMD has not been widely studied. The present study analyses the association between age and SMI/SMD after adjustment for other clinicopathological factors. Patients undergoing resectional surgery for TNM Stage I-III disease within the West of Scotland between 2011 and 2014 were identified. A single CT slice was obtained from each patients staging CT scan. SMI and SMD were stratified normal/abnormal. The SIR was stratified using Systemic Inflammatory Grade (SIG). When stratified by age (< 50/50s/60s/70s/80+), 39%/38%/48%/62%/74% and 27%/48%/64%/82%/92% of patients had a low SMI and SMD respectively (both p < 0.001). Older age (OR 1.47, p < 0.001), female sex (OR 1.32, p = 0.032), lower socioeconomic deprivation (OR 1.15, p = 0.004), higher ASA (OR 1.30, p = 0.019), emergency presentation (OR 1.82, p = 0.003), lower BMI (OR 0.67, p < 0.002) and higher SIG (OR 1.23, p < 0.001) were independently associated with low SMI. Older age (OR 2.28, p < 0.001), female sex (OR 1.38, p = 0.038), higher ASA (OR 1.92, p < 0.001), emergency presentation (OR 1.71, p = 0.023), and higher SIG (OR 1.37, p < 0.001) were independently associated with lower SMD. Tumour factors were not independently associated with either SMI/SMD. Age was a major factor associated with low SMI/SMD in patients with colon cancer. Therefore, in these patients it is likely that this represents largely constitutional body composition as opposed to being a disease mediated effect. Adjustment for age is required when considering the cancer mediated effect on SMI/SMD in patients with colon cancer.

The Biomechanics of Musculoskeletal Tissues during Activities of Daily Living: Dynamic Assessment Using Quantitative Transmission-Mode Ultrasound Techniques

The measurement of musculoskeletal tissue properties and loading patterns during physical activity is important for understanding the adaptation mechanisms of tissues such as bone, tendon, and muscle tissues, particularly with injury and repair. Although the properties and loading of these connective tissues have been quantified using direct measurement techniques, these methods are highly invasive and often prevent or interfere with normal activity patterns. Indirect biomechanical methods, such as estimates based on electromyography, ultrasound, and inverse dynamics, are used more widely but are known to yield different parameter values than direct measurements. Through a series of literature searches of electronic databases, including Pubmed, Embase, Web of Science, and IEEE Explore, this paper reviews current methods used for the in vivo measurement of human musculoskeletal tissue and describes the operating principals, application, and emerging research findings gained from the use of quantitative transmission-mode ultrasound measurement techniques to non-invasively characterize human bone, tendon, and muscle properties at rest and during activities of daily living. In contrast to standard ultrasound imaging approaches, these techniques assess the interaction between ultrasound compression waves and connective tissues to provide quantifiable parameters associated with the structure, instantaneous elastic modulus, and density of tissues. By taking advantage of the physical relationship between the axial velocity of ultrasound compression waves and the instantaneous modulus of the propagation material, these techniques can also be used to estimate the in vivo loading environment of relatively superficial soft connective tissues during sports and activities of daily living. This paper highlights key findings from clinical studies in which quantitative transmission-mode ultrasound has been used to measure the properties and loading of bone, tendon, and muscle tissue during common physical activities in healthy and pathological populations.

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.

Dialysis Duration, Time Interaction, and Visceral Fat Accumulation: A 6-Year Posttransplantation Study

BACKGROUND

Kidney transplantation (KT) leads to body composition change, particularly increasing the fat mass. However, limited researches have focused on the long-term follow-up of these changes and factors influencing body composition after KT.

METHODS

This study evaluated body composition in 31 adult KT recipients, measuring body mass index (BMI), the psoas muscle mass index (PMI) representing muscle mass, visceral and subcutaneous adipose tissue (VAT and SAT) representing fat mass, and skeletal muscle radiodensity (SMR) representing muscle quality before KT and at 2, 4, and 6 years posttransplantation using computed tomography. Linear mixed models (LMM) analyzed temporal changes and contributing factors, while growth curve models assessed influence of these factors on body composition changes posttransplantation.

RESULTS

Following KT, BMI, and PMI remained stable, while SAT increased significantly, revealing a 1.30-fold increase from baseline 2 years after transplantation. Similarly, a substantial increase in VAT was observed, with a 1.47-fold increase from baseline 2 years after transplantation with a further 1.75-fold increase 6 years after transplantation. In contrast, SMR decreased with a 0.86-fold decrease from baseline after 2 years. VAT increase was significantly influenced by the interaction between posttransplantation and dialysis duration. Growth curve models confirmed this interaction effect persistently influenced VAT increase posttransplantation.

CONCLUSIONS

The study revealed that KT promoted significant alterations in body composition characterized by increase in the VAT and SAT and a decline in SMR. Notably, dialysis duration and its interaction with posttransplantation duration emerged as significant factors influencing VAT increase.

Muscle Reference Values From Thoracic and Abdominal CT for Sarcopenia Assessment: The Framingham Heart Study

BACKGROUND

Loss of muscle mass is a known feature of sarcopenia and predicts poor clinical outcomes. Although muscle metrics can be derived from routine computed tomography (CT) images, sex-specific reference values at multiple vertebral levels over a wide age range are lacking.

OBJECTIVE

The aim of this study was to provide reference values for skeletal muscle mass and attenuation on thoracic and abdominal CT scans in the community-based Framingham Heart Study cohort to aid in the identification of sarcopenia.

MATERIALS AND METHODS

This secondary analysis of a prospective trial describes muscle metrics by age and sex for participants from the Framingham Heart Study without prior history of cancer who underwent at least 1 CT scan between 2002 and 2011. Using 2 previously validated machine learning algorithms followed by human quality assurance, skeletal muscle was analyzed on a single axial CT image per level at the 5th, 8th, 10th thoracic, and 3rd lumbar vertebral body (T5, T8, T10, L3). Cross-sectional muscle area (cm 2 ), mean skeletal muscle radioattenuation (SMRA, in Hounsfield units), skeletal muscle index (SMI, in cm 2 /m 2 ), and skeletal muscle gauge (SMRA·SMI) were calculated. Measurements were summarized by age group (<45, 45-54, 55-64, 65-74, ≥75 years), sex, and vertebral level. Models enabling the calculation of age-, sex-, and vertebral-level-specific reference values were created and embedded into an open access online Web application.

RESULTS

The cohort consisted of 3804 participants (1917 [50.4%] males; mean age, 55.6 ± 11.8 years; range, 33-92 years) and 7162 CT scans. Muscle metrics qualitatively decreased with increasing age and female sex.

CONCLUSIONS

This study established age- and sex-specific reference values for CT-based muscle metrics at thoracic and lumbar vertebral levels. These values may be used in future research investigating the role of muscle mass and attenuation in health and disease, and to identify sarcopenia.

Applicability of the CT Radiomics of Skeletal Muscle and Machine Learning for the Detection of Sarcopenia and Prognostic Assessment of Disease Progression in Patients with Gastric and Esophageal Tumors

PURPOSE

Sarcopenia is considered a negative prognostic factor in patients with malignant tumors. Among other diagnostic options, computed tomography (CT), which is repeatedly performed on tumor patients, can be of further benefit. The present study aims to establish a framework for classifying the impact of sarcopenia on the prognosis of patients diagnosed with esophageal or gastric cancer. Additionally, it explores the significance of CT radiomics in both diagnostic and prognostic methodologies.

MATERIALS AND METHODS

CT scans of 83 patients with esophageal or gastric cancer taken at the time of diagnosis and during a follow-up period of one year were evaluated retrospectively. A total of 330 CT scans were analyzed. Seventy three of these patients received operative tumor resection after neoadjuvant chemotherapy, and 74% of the patients were male. The mean age was 64 years (31-83 years). Three time points (t) were defined as a basis for the statistical analysis in order to structure the course of the disease: t1 = initial diagnosis, t2 = following (neoadjuvant) chemotherapy and t3 = end of the first year after surgery in the "surgery" group or end of the first year after chemotherapy. Sarcopenia was determined using the psoas muscle index (PMI). The additional analysis included the analysis of selected radiomic features of the psoas major, quadratus lumborum, and erector spinae muscles at the L3 level. Disease progression was monitored according to the response evaluation criteria in solid tumors (RECIST 1.1). CT scans and radiomics were used to assess the likelihood of tumor progression and their correlation to sarcopenia. For machine learning, the established algorithms decision tree (DT), K-nearest neighbor (KNN), and random forest (RF) were applied. To evaluate the performance of each model, a 10-fold cross-validation as well as a calculation of Accuracy and Area Under the Curve (AUC) was used.

RESULTS

During the observation period of the study, there was a significant decrease in PMI. This was most evident in patients with surgical therapy in the comparison between diagnosis and after both neoadjuvant therapy and surgery (each p < 0.001). Tumor progression (PD) was not observed significantly more often in the patients with sarcopenia compared to those without sarcopenia at any time point (p = 0.277 to p = 0.465). On average, PD occurred after 271.69 ± 104.20 days. The time from initial diagnosis to PD in patients "with sarcopenia" was not significantly shorter than in patients "without sarcopenia" at any of the time points (p = 0.521 to p = 0.817). The CT radiomics of skeletal muscle could predict both sarcopenia and tumor progression, with the best results for the psoas major muscle using the RF algorithm. For the detection of sarcopenia, the Accuracy was 0.90 ± 0.03 and AUC was 0.96 ± 0.02. For the prediction of PD, the Accuracy was 0.88 ± 0.04 and the AUC was 0.93 ± 0.04.

CONCLUSIONS

In the present study, the CT radiomics of skeletal muscle together with machine learning correlated with the presence of sarcopenia, and this can additionally assist in predicting disease progression. These features can be classified as promising alternatives to conventional methods, with great potential for further research and future clinical application. However, when sarcopenia was diagnosed with PMI, no significant correlation between sarcopenia and PD could be observed.

Sex-specific causality of MRI-derived body compositions on glycaemic traits: Mendelian randomization and observational study

AIM

To investigate the sex-specific causality of body compositions in type 2 diabetes and related glycaemic traits using Mendelian randomization (MR).

MATERIALS AND METHODS

We leveraged sex-specific summary-level statistics from genome-wide association studies for three adipose deposits adjusted for body mass index and height, including abdominal subcutaneous adipose tissue, visceral adipose tissue (VATadj) and gluteofemoral adipose tissue (GFATadj), measured by MRI (20 038 women; 19 038 men), and fat mass-adjusted appendicular lean mass (ALMadj) (244 730 women; 205 513 men) in the UK Biobank. Sex-specific statistics of type 2 diabetes were from the Diabetes Genetics Replication and Meta-analysis Consortium and those for fasting glucose and insulin were from the Meta-analyses of Glucose and Insulin-related Traits Consortium. Univariable and multivariable MR (MVMR) were performed. We also performed MR analyses of anthropometric traits and genetic association analyses using individual-level data of body composition as validation.

RESULTS

Univariable MR analysis showed that, in women, higher GFATadj and ALMadj exerted a causally protective effect on type 2 diabetes (GFATadj: odds ratio [OR] 0.59, 95% confidence interval [CI; 0.50, 0.69]; ALMadj: OR 0.84, 95% CI [0.77, 0.91]) and VATadj to be riskier in glycaemic traits. MVMR showed that GFATadj retained a robust effect on type 2 diabetes (OR 0.57, 95% CI [0.42, 0.77]; P = 2.6 × 10-4 ) in women, while it was nominally significant in men (OR 0.58, 95% CI [0.35, 0.96]; P = 3.3 × 10-2 ), after adjustment for ASATadj and VATadj. MR analyses of anthropometric measures and genetic association analyses of glycaemic traits confirmed the results.

CONCLUSIONS

Body composition has a sex-specific effect on type 2 diabetes, and higher GFATadj has an independent protective effect on type 2 diabetes in both sexes.

Impact of sarcopenia on outcomes in surgical patients: a systematic review and meta-analysis

BACKGROUND

Surgeons have historically used age as a preoperative predictor of postoperative outcomes. Sarcopenia, the loss of skeletal muscle mass due to disease or biological age, has been proposed as a more accurate risk predictor. The prognostic value of sarcopenia assessment in surgical patients remains poorly understood. Therefore, the authors aimed to synthesize the available literature and investigate the impact of sarcopenia on perioperative and postoperative outcomes across all surgical specialties.

METHODS

The authors systematically assessed the prognostic value of sarcopenia on postoperative outcomes by conducting a systematic review and meta-analysis according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, searching the PubMed/MEDLINE and EMBASE databases from inception to 1st October 2022. Their primary outcomes were complication occurrence, mortality, length of operation and hospital stay, discharge to home, and postdischarge survival rate at 1, 3, and 5 years. Subgroup analysis was performed by stratifying complications according to the Clavien-Dindo classification system. Sensitivity analysis was performed by focusing on studies with an oncological, cardiovascular, emergency, or transplant surgery population and on those of higher quality or prospective study design.

RESULTS

A total of 294 studies comprising 97 643 patients, of which 33 070 had sarcopenia, were included in our analysis. Sarcopenia was associated with significantly poorer postoperative outcomes, including greater mortality, complication occurrence, length of hospital stay, and lower rates of discharge to home (all P <0.00001). A significantly lower survival rate in patients with sarcopenia was noted at 1, 3, and 5 years (all P <0.00001) after surgery. Subgroup analysis confirmed higher rates of complications and mortality in oncological (both P <0.00001), cardiovascular (both P <0.00001), and emergency ( P =0.03 and P =0.04, respectively) patients with sarcopenia. In the transplant surgery cohort, mortality was significantly higher in patients with sarcopenia ( P <0.00001). Among all patients undergoing surgery for inflammatory bowel disease, the frequency of complications was significantly increased among sarcopenic patients ( P =0.007). Sensitivity analysis based on higher quality studies and prospective studies showed that sarcopenia remained a significant predictor of mortality and complication occurrence (all P <0.00001).

CONCLUSION

Sarcopenia is a significant predictor of poorer outcomes in surgical patients. Preoperative assessment of sarcopenia can help surgeons identify patients at risk, critically balance eligibility, and refine perioperative management. Large-scale studies are required to further validate the importance of sarcopenia as a prognostic indicator of perioperative risk, especially in surgical subspecialties.

Clinical and prognostic role of sarcopenia based on masticatory muscle index on MR images in patients with extranodal natural killer/T cell lymphoma, nasal type

Sarcopenia is known to be associated with an increased risk of adverse outcomes in a variety of malignancies, but its impact in extranodal natural killer/T cell lymphoma, nasal type (ENKTL-NT) is unknown. The aim of this study was to explore the prognostic relevance of sarcopenia defined by MRI-based masticatory muscle index in ENKTL-NT patients. A total of 112 patients with newly diagnosed ENKTL-NT who underwent cranial magnetic resonance imaging (MRI) were enrolled. The masticatory skeletal muscle index (M-SMI) was measured based on T2-weighted MR images and sarcopenia was defined by M-SMI<5.5 cm2/ m2. The median M-SMI was 5.47 (4.91-5.96) cm2/m2; 58 were identified with sarcopenia in this cohort. On multivariate analyses, sarcopenia was the only independently risk factor predicting overall survival (HR, 4.590; 95% CI, 1.657-12.715; p = 0.003), progression-free survival (HR, 3.048; 95% CI, 1.515-6.130; p = 0.002), and treatment response (HR, 0.112; 95% CI, 0.042-0.301; p < 0.001). In addition, we found that integrating sarcopenia into prognostic indices could improve the discriminative power of the corresponding original model. Stratification analysis showed that sarcopenia was able to further identify survival differences in patients that could not be distinguished by prognostic models. In summary, our study suggests that sarcopenia defined by MRI-based M-SMI represents a new and routinely applicable prognostic indicator of clinical outcome or predictor of treatment response in ENKTL-NT patients, and may aid in risk stratification and treatment decisions.

Activin type I receptor polymorphisms and body composition in older individuals with sarcopenia-Analyses from the LACE randomised controlled trial

BACKGROUND

Ageing is associated with changes in body composition including an overall reduction in muscle mass and a proportionate increase in fat mass. Sarcopenia is characterised by losses in both muscle mass and strength. Body composition and muscle strength are at least in part genetically determined, consequently polymorphisms in pathways important in muscle biology (e.g., the activin/myostatin signalling pathway) are hypothesised to contribute to the development of sarcopenia.

METHODS

We compared regional body composition measured by DXA with genotypes for two polymorphisms (rs10783486, minor allele frequency (MAF) = 0.26 and rs2854464, MAF = 0.26) in the activin 1B receptor (ACVR1B) determined by PCR in a cross-sectional analysis of DNA from 110 older individuals with sarcopenia from the LACE trial.

RESULTS

Neither muscle mass nor strength showed any significant associations with either genotype in this cohort. Initial analysis of rs10783486 showed that males with the AA/AG genotype were taller than GG males (174±7cm vs 170±5cm, p = 0.023) and had higher arm fat mass, (median higher by 15%, p = 0.008), and leg fat mass (median higher by 14%, p = 0.042). After correcting for height, arm fat mass remained significantly higher (median higher by 4% padj = 0.024). No associations (adjusted or unadjusted) were seen in females. Similar analysis of the rs2854464 allele showed a similar pattern with the presence of the minor allele (GG/AG) being associated with greater height (GG/AG = 174±7 cm vs AA = 170 ±5cm, p = 0.017) and greater arm fat mass (median higher by 16%, p = 0.023). Again, the difference in arm fat remained after correction for height. No similar associations were seen in females analysed alone.

CONCLUSION

These data suggest that polymorphic variation in the ACVR1B locus could be associated with body composition in older males. The activin/myostatin pathway might offer a novel potential target to prevent fat accumulation in older individuals.

Myosteatosis independently predicts transplant-free survival in patients with primary sclerosing cholangitis

BACKGROUND

Primary Sclerosing Cholangitis (PSC) is a progressive cholestatic liver disease with liver transplantation (LT) as the only curative therapy. Some regions use body-weight-loss as standard-exception criteria for organ allocation but data on the impact of body composition on survival of patients with PSC is scarce.

METHODS

Abdominal MRI of PSC patients were quantitatively analyzed for intramuscular fat fraction (IMFF) as surrogate of myosteatosis. Clinical and laboratory data were retrieved from patient records. Primary outcome was transplant-free survival (TFS).

RESULTS

116 PSC patients were included. Median age was 38 (18-71) years with 74 (64%) male patients. 15 (13%) patients had significant weigh loss. IMFF was significantly associated with survival. Multivariate regression analysis showed IMFF ≥ 15% as independent predictor for TFS (p = 0.032, HR 3.215 CI 1.104-9.366), but not significant weight loss (p = 0.618).

CONCLUSION

IMFF is independently associated with TFS in patients with PSC and may identify patients with more urgent need for LT. NCT03584204.

Direct deep learning-based survival prediction from pre-interventional CT prior to transcatheter aortic valve replacement

PURPOSE

To investigate survival prediction in patients undergoing transcatheter aortic valve replacement (TAVR) using deep learning (DL) methods applied directly to pre-interventional CT images and to compare performance with survival models based on scalar markers of body composition.

METHOD

This retrospective single-center study included 760 patients undergoing TAVR (mean age 81 ± 6 years; 389 female). As a baseline, a Cox proportional hazards model (CPHM) was trained to predict survival on sex, age, and the CT body composition markers fatty muscle fraction (FMF), skeletal muscle radiodensity (SMRD), and skeletal muscle area (SMA) derived from paraspinal muscle segmentation of a single slice at L3/L4 level. The convolutional neural network (CNN) encoder of the DL model for survival prediction was pre-trained in an autoencoder setting with and without a focus on paraspinal muscles. Finally, a combination of DL and CPHM was evaluated. Performance was assessed by C-index and area under the receiver operating curve (AUC) for 1-year and 2-year survival. All methods were trained with five-fold cross-validation and were evaluated on 152 hold-out test cases.

RESULTS

The CNN for direct image-based survival prediction, pre-trained in a focussed autoencoder scenario, outperformed the baseline CPHM (CPHM: C-index = 0.608, 1Y-AUC = 0.606, 2Y-AUC = 0.594 vs. DL: C-index = 0.645, 1Y-AUC = 0.687, 2Y-AUC = 0.692). Combining DL and CPHM led to further improvement (C-index = 0.668, 1Y-AUC = 0.713, 2Y-AUC = 0.696).

CONCLUSIONS

Direct DL-based survival prediction shows potential to improve image feature extraction compared to segmentation-based scalar markers of body composition for risk assessment in TAVR patients.

Sarcopenia, More Than Just Muscle Atrophy: Imaging Methods for the Assessment of Muscle Quantity and Quality

BACKGROUND

Sarcopenia, a progressive reduction of muscle mass and function, is associated with adverse outcomes in the elderly. Sarcopenia and muscle atrophy are not equal processes. Low muscle strength in association with muscle quantity/quality reduction is currently the optimal method for assessing sarcopenia. There is a practical need for indirect measurement of muscle strength using state-of-the-art imaging techniques.

METHODS

The following provides a narrative, broad review of all current imaging techniques for evaluating muscles and identifying sarcopenia, including DEXA, CT, MRI, and high-resolution ultrasound, their main strengths, weaknesses, and possible solutions to problems regarding each technique.

RESULTS AND CONCLUSION

Well-recognized imaging methods for the assessment of muscle mass are explained, including evaluation with DEXA, CT, and MRI muscle quantity assessment, ultrasound evaluation of muscle thickness and CSA, and their correlations with established muscle mass calculation methods. A special focus is on imaging methods for muscle quality evaluation. Several innovative and promising techniques that are still in the research phase but show potential in the assessment of different properties of muscle quality, including MRI DIXON sequences, MRI spectroscopy, Diffusion Tensor Imaging, ultrasound echo intensity, ultrasound elastography, and speed-of-sound ultrasound imaging are briefly mentioned.

KEY POINTS

· Sarcopenia definition includes low muscle strength and low muscle quantity/quality.. · DEXA is a low-radiation method for whole-body composition measurement in a single image.. · CT has established cut-off values for muscle quality/quantity evaluation and sarcopenia diagnosis.. · MRI is the most sophisticated muscle quality assessment method capable of evaluating myosteatosis, myofibrosis, and microstructure.. · Ultrasound can evaluate muscle quality, including tissue architecture, and elasticity with excellent spatial resolution..

CITATION FORMAT

· Vasilevska Nikodinovska V, Ivanoski S, . Sarcopenia, More Than Just Muscle Atrophy: Imaging Methods for the Assessment of Muscle Quantity and Quality. Fortschr Röntgenstr 2023; 195: 777 - 789.

Impact of sarcopenia on clinical outcomes for patients with resected hepatocellular carcinoma: a retrospective comparison of Eastern and Western cohorts

BACKGROUND

Patient fitness is important for guiding treatment. Muscle mass, as a reflection thereof, can be objectively measured. However, the role of East-West differences remains unclear. Therefore, we compared the impact of muscle mass on clinical outcomes after liver resection for hepatocellular carcinoma (HCC) in a Dutch [the Netherlands (NL)] and Japanese [Japan (JP)] setting and evaluated the predictive performance of different cutoff values for sarcopenia.

METHOD

In this multicenter retrospective cohort study, patients with HCC undergoing liver resection were included. The skeletal muscle mass index (SMI) was determined on computed tomography scans obtained within 3 months before surgery. The primary outcome measure was overall survival (OS). Secondary outcome measures were: 90-day mortality, severe complications, length of stay, and recurrence-free survival. The predictive performance of several sarcopenia cutoff values was studied using the concordance index (C-index) and area under the curve. Interaction terms were used to study the geographic effect modification of muscle mass.

RESULTS

Demographics differed between NL and JP. Gender, age, and body mass index were associated with SMI. Significant effect modification between NL and JP was found for BMI. The predictive performance of sarcopenia for both short-term and long-term outcomes was higher in JP compared to NL (maximum C-index: 0.58 vs. 0.55, respectively). However, differences between cutoff values were small. For the association between sarcopenia and OS, a strong association was found in JP [hazard ratio (HR) 2.00, 95% CI [1.230-3.08], P =0.002], where this was not found in NL (0.76 [0.42-1.36], P =0.351). The interaction term confirmed that this difference was significant (HR 0.37, 95% CI [0.19-0.73], P =0.005).

CONCLUSIONS

The impact of sarcopenia on survival differs between the East and West. Clinical trials and treatment guidelines using sarcopenia for risk stratification should be validated in race-dependent populations prior to clinical adoption.

Ultrasound assessment of rectus femoris pennation angle and echogenicity. Their association with muscle functional measures and fat infiltration measured by CT scan

BACKGROUND & AIMS

Ultrasound can be used to measure the pennation angle between muscle fiver and the presumed axis of force generation and muscle echogenicity as an indicator of muscle fat infiltration. We aimed to assess the association of the rectus femoris pennation angle and echogenicity with muscle functional measures. Also, to assess the concordance of rectus femoris echogenicity with muscle fat infiltration as determined by CT scan.

METHODS

Rectus femoris ultrasound pennation angle and thickness were measured in 78 participants aged 69 (65,73) years (37 women). Also hand grip strength, gait speed in 4 m, the 12 min' walk and body composition by DEXA were measured. In a different group of 114 participants aged 44 (31,52) years (80 females), non-dominant rectus femoris echogenicity and thickness were measured by ultrasound and muscle fat infiltration was assessed by CT scan. Handgrip strength and quadriceps torque were also measured.

RESULTS

There was a weak correlation between the pennation angle and rectus femoris thickness in men (r = 0.31 p = 0.05) but not in women (r = 0.29 NS). Women, but not men with a low pennation angle covered a longer distance during the 12 min' walk. The concordance between the z scores of rectus femoris echogenicity and CT radiological density was 0.43 (p < 0.01) and 0.01 (NS) in men and women, respectively. Men and women with an echogenicity below the 25th percentile had a higher quadriceps torque. Men with an echogenicity 25th percentile below 25th percentile had also a higher handgrip strength.

CONCLUSIONS

Rectus femoris pennation angle had a weak or absent association with muscle performance. Rectus femoris echogenicity had a moderate overall concordance with radiological density by CT scan and was inversely associated with quadriceps torque. Therefore, echogenicity was associated with muscle strength, but pennation angle measurement did not contribute to the assessment of muscle function.

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.

Associations of myosteatosis with disc degeneration: A 3T magnetic resonance imaging study in individuals with impaired glycaemia

BACKGROUND

Intervertebral disc degeneration (IVDD) may be linked to dysregulations of skeletal muscle glucose metabolism and fatty alterations of muscle composition (Myosteatosis). Our aim was to evaluate the different associations of magnetic resonance imaging (MRI)-based paravertebral myosteatosis with lumbar disc degeneration in individuals with impaired glucose metabolism and normoglycaemic controls.

METHODS

In total, 304 individuals (mean age: 56.3 ± 9.1 years, 53.6% male sex, mean body mass index [BMI]: 27.6 ± 4.7 kg/m² ) from a population-based cohort study who underwent 3-Tesla whole-body chemical-shift-encoded (six echo times) and T2-weighted single-shot-fast-spin-echo MRI were included. Lumbar disc degeneration was assessed at motion segments L1 to L5, categorized according to the Pfirrmann score and defined as Pfirrmann grade > 2 and/or disc bulging/herniation on at least one segment. Fat content of the autochthonous back muscles and the quadratus lumborum muscle was quantified as proton density fat fraction (PDFF_muscle ). Logistic regression models adjusted for age, sex, BMI and regular physical activity were calculated to evaluate the association between PDFF_muscle and outcome IVDD.

RESULTS

The overall prevalence of IVDD was 79.6%. There was no significant difference in the prevalence or severity distribution of IVDD between participants with or without impaired glucose metabolism (77.7% vs. 80.7%, P = 0.63 and P = 0.71, respectively). PDFF_muscle was significantly and positively associated with an increased risk for the presence of IVDD in participants with impaired glycaemia when adjusted for age, sex and BMI (PDFF_{autochthonous back muscles} : odds ratio [OR] 2.16, 95% confidence interval [CI] [1.09, 4.3], P = 0.03; PDFF_{quadratus lumborum} : OR 2.01, 95% CI [1.04, 3.85], P = 0.04). After further adjustment for regular physical activity, the results attenuated, albeit approaching statistical significance (PDFF_{autochthonous back muscles} : OR 1.97, 95% CI [0.97, 3.99], P = 0.06; PDFF_{quadratus lumborum} : OR 1.86, 95% CI [0.92, 3.76], P = 0.09). No significant associations were shown in healthy controls (PDFF_{autochthonous back muscles} : OR 0.62, 95% CI [0.34, 1.14], P = 0.13; PDFF_{quadratus lumborum} : OR 1.06, 95% CI [0.6, 1.89], P = 0.83).

CONCLUSIONS

Paravertebral myosteatosis is positively associated with intervertebral disc disease in individuals with impaired glucose metabolism, independent of age, sex and BMI. Regular physical activity may confound these associations. Longitudinal studies will help to better understand the pathophysiological role of skeletal muscle in those with concomitant disturbed glucose haemostasis and intervertebral disc disease, as well as possible underlying causal relationships.

Association of body composition with postoperative complications after laparoscopic sleeve gastrectomy and Roux-en-Y gastric bypass

OBJECTIVE

To evaluate predictive values of body composition parameters measured from preoperative CT/MRIs for postoperative complications after laparoscopic sleeve gastrectomy (LSG) and Roux-en-Y gastric bypass (LRYGB) in patients with obesity.

METHODS

In this retrospective case-control study, patients performing abdominal CT/MRIs within one month before and developing 30-day complications after bariatric procedures were matched for age, sex, and type of surgery with patients without complications (1/3 ratio, respectively). Complications were determined by documentation in the medical record. Two readers blindly segmented the total abdominal muscle area (TAMA) and visceral fat area (VFA) using predetermined thresholds for the Hounsfield unit (HU) on unenhanced CT and the signal intensity (SI) on T1-weighted MRI at the L3 vertebral level. Visceral obesity (VO) was defined as VFA > 136 cm² in males and > 95 cm² in females. These measures, along with perioperative variables, were compared. Multivariate logistic regression analyses were performed.

RESULTS

Of 145 included patients, 36 had postoperative complications. No significant differences between LSG and LRYGB were present regarding complications and VO. Hypertension (p = 0.022), impaired lung function (p = 0.018), American Society of Anesthesiologists (ASA) grade (p = 0.046), VO (p = 0.021), and VFA/TAMA ratio (p < 0.0001) were associated with postoperative complications in the univariate logistic analysis; the VFA/TAMA ratio was the only independent predictor in multivariate analyses (OR 2.01, 95% CI 1.37-2.93, p < 0.001).

CONCLUSION

The VFA/TAMA ratio provides important perioperative information in predicting patients who are likely to develop postoperative complications undergoing bariatric surgery.

Role of Machine Learning-Based CT Body Composition in Risk Prediction and Prognostication: Current State and Future Directions

CT body composition analysis has been shown to play an important role in predicting health and has the potential to improve patient outcomes if implemented clinically. Recent advances in artificial intelligence and machine learning have led to high speed and accuracy for extracting body composition metrics from CT scans. These may inform preoperative interventions and guide treatment planning. This review aims to discuss the clinical applications of CT body composition in clinical practice, as it moves towards widespread clinical implementation.

Sarcopenia - Definition, Radiological Diagnosis, Clinical Significance

BACKGROUND

 Sarcopenia is an age-related syndrome characterized by a loss of muscle mass and strength. As a result, the independence of the elderly is reduced and the hospitalization rate and mortality increase. The onset of sarcopenia often begins in middle age due to an unbalanced diet or malnutrition in association with a lack of physical activity. This effect is intensified by concomitant diseases such as obesity or metabolic diseases including diabetes mellitus.

METHOD

 With effective preventative diagnostic procedures and specific therapeutic treatment of sarcopenia, the negative effects on the individual can be reduced and the negative impact on health as well as socioeconomic effects can be prevented. Various diagnostic options are available for this purpose. In addition to basic clinical methods such as measuring muscle strength, sarcopenia can also be detected using imaging techniques like dual X-ray absorptiometry (DXA), computed tomography (CT), magnetic resonance imaging (MRI), and sonography. DXA, as a simple and cost-effective method, offers a low-dose option for assessing body composition. With cross-sectional imaging techniques such as CT and MRI, further diagnostic possibilities are available, including MR spectroscopy (MRS) for noninvasive molecular analysis of muscle tissue. CT can also be used in the context of examinations performed for other indications to acquire additional parameters of the skeletal muscles (opportunistic secondary use of CT data), such as abdominal muscle mass (total abdominal muscle area - TAMA) or the psoas as well as the pectoralis muscle index. The importance of sarcopenia is already well studied for patients with various tumor entities and also infections such as SARS-COV2.

RESULTS AND CONCLUSION

 Sarcopenia will become increasingly important, not least due to demographic changes in the population. In this review, the possibilities for the diagnosis of sarcopenia, the clinical significance, and therapeutic options are described. In particular, CT examinations, which are repeatedly performed on tumor patients, can be used for diagnostics. This opportunistic use can be supported by the use of artificial intelligence.

KEY POINTS

· Sarcopenia is an age-related syndrome with loss of muscle mass and strength.. · Early detection and therapy can prevent negative effects of sarcopenia.. · In addition to DEXA, cross-sectional imaging techniques (CT, MRI) are available for diagnostic purposes.. · The use of artificial intelligence (AI) offers further possibilities in sarcopenia diagnostics..

CITATION FORMAT

· Vogele D, Otto S, Sollmann N et al. Sarcopenia - Definition, Radiological Diagnosis, Clinical Significance. Fortschr Röntgenstr 2023; DOI: 10.1055/a-1990-0201.

Effect of alternate day fasting combined with aerobic exercise on non-alcoholic fatty liver disease: A randomized controlled trial

Innovative non-pharmacological lifestyle strategies to treat non-alcoholic fatty liver disease (NAFLD) are critically needed. This study compared the effects of alternate day fasting (ADF) combined with exercise to fasting alone, or exercise alone, on intrahepatic triglyceride (IHTG) content. Adults with obesity and NAFLD (n = 80, 81% female, age: 23-65 years) were randomized to 1 of 4 groups for 3 months: combination of ADF (600 kcal/2,500 kJ "fast day" alternated with an ad libitum intake "feast day") and moderate-intensity aerobic exercise (5 session per week, 60 min/session); ADF alone; exercise alone; or a no-intervention control group. By month 3, IHTG content was significantly reduced in the combination group (-5.48%; 95% CI, -7.77% to -3.18%), compared with the exercise group (-1.30%; 95% CI, -3.80% to 1.20%; p = 0.02) and the control group (-0.17%; 95% CI, -2.17% to 1.83%; p < 0.01) but was not significantly different versus the ADF group (-2.25%; 95% CI, -4.46% to -0.04%; p = 0.05). Body weight, fat mass, waist circumference, and alanine transaminase (ALT) levels significantly decreased, while insulin sensitivity significantly increased in the combination group compared with the control group. Lean mass, aspartate transaminase (AST), HbA1c, blood pressure, plasma lipids, liver fibrosis score, and hepatokines (fetuin-A, FGF-21, and selenoprotein P) did not differ between groups. Combining intermittent fasting with exercise is effective for reducing hepatic steatosis in patients with NAFLD but may offer no additional benefit versus fasting alone.

Impact of muscle mass on survival of patients with hepatocellular carcinoma after liver transplantation beyond the Milan criteria

BACKGROUND

Access to the liver transplant waitlist for patients with hepatocellular carcinoma (HCC) depends on tumour presentation, biology, and response to treatments. The Milan Criteria (MC) represent the benchmark for expanded criteria that incorporate additional prognostic factors. The purpose of this study was to determine the added value of skeletal muscle index (SMI) in HCC patients beyond the MC.

METHOD

Patients with HCC that were transplanted beyond the MC were included in this retrospective multicentre study. SMI was quantified using the Computed Tomography (CT) within 3 months prior to transplantation. Cox regression models were used to identify predictors of overall survival (OS). The discriminative performance of SMI extended Metroticket 2.0 and AFP models was also assessed.

RESULTS

Out of 889 patients transplanted outside the MC, 528 had a CT scan within 3 months prior to liver transplantation (LT), of whom 176 (33%) were classified as sarcopenic. The median time between assessment of the SMI and LT was 1.8 months (IQR: 0.77-2.67). The median follow-up period was 5.1 95% CI [4.7-5.5] years, with a total of 177 recorded deaths from any cause. In a linear regression model with SMI as the dependent variable, only male gender (8.55 95% CI [6.51-10.59], P < 0.001) and body mass index (0.74 95% CI [0.59-0.89], P < 0.001) were significant. Univariable survival analysis of patients with sarcopenia versus patients without sarcopenia showed a significant difference in OS (HR 1.44 95% CI [1.07 - 1.94], P = 0.018). Also the SMI was significant (HR 0.98 95% CI [0.96-0.99], P = 0.014). The survival difference between the lowest SMI quartile versus the highest SMI quartile was significant (log-rank: P = 0.005) with 5 year OS of 57% and 71%, respectively. Data from 423 patients, describing 139 deaths, was used for multivariate analysis. Both sarcopenia (HR 1.45 95% CI [1.02 - 2.05], P = 0.036) and SMI were (HR 0.98 95% CI [0.95-0.99], P = 0.035) significant. On the survival scale this translates to a 5 year OS difference of 11% between sarcopenia and no sarcopenia. Whereas for SMI, this translates to a survival difference of 8% between first and third quartiles for both genders.

CONCLUSIONS

Overall, we can conclude that higher muscle mass contributes to a better long-term survival. However, for individual patients, low muscle mass should not be considered an absolute contra-indication for LT as its discriminatory performance was limited.

Impact of sarcopenia in bladder preservation therapy for muscle-invasive bladder cancer patients: a narrative review

BACKGROUND AND OBJECTIVE

Muscle-invasive bladder cancer (MIBC) is a biologically aggressive disease and its prognosis is poor. Radical cystectomy (RC) with urinary diversion and lymph node dissection is the gold standard treatment for MIBC patients. Accumulating evidence indicates that sarcopenia, the degenerative and systemic loss of skeletal muscle mass, is a significant predictor of higher rates of mortality and perioperative complications following RC. Recently, bladder preservation therapy has been offered as an alternative in appropriately selected MIBC patients who desire to preserve their bladders and those unfit or unwilling for RC. Here, we performed a narrative review on the impact of sarcopenia on oncological outcomes and complication rates in MIBC patients treated with bladder preservation therapy.

METHODS

A literature review was performed using the PubMed and Scopus databases.

KEY CONTENT AND FINDINGS

We identified two studies reported the impact of sarcopenia on responses to trimodal therapy and survival outcomes in MIBC patients. Consolidative partial cystectomy was performed in patients who achieved clinical complete response (CR) to trimodal therapy in one of the two studies. In both studies, CR rates to trimodal therapy are comparable between sarcopenic and non-sarcopenic patients. Sarcopenia was not significantly associated with shorter survival after completing bladder preservation therapy in either study. For complication rates of bladder preservation therapy, one study showed equivalent complication rates of consolidative partial cystectomy between sarcopenic and non-sarcopenic patients. In addition, in another small series of trimodal therapy, sarcopenic patients showed a higher rate of complications of trimodal therapy compared with non-sarcopenic patients.

CONCLUSIONS

According to the result of our literature review, sarcopenia would not affect responses to trimodal therapy and prognosis in MIBC patients treated with bladder preservation therapy. Although the effect of sarcopenia on complication rates of bladder preservation therapy is inconclusive due to limited evidence, bladder preservation therapy could be a viable alternative option in carefully selected MIBC patients regardless of the presence of sarcopenia.

Fat Distribution Patterns and Future Type 2 Diabetes

Fat accumulation in the liver, pancreas, skeletal muscle, and visceral bed relates to type 2 diabetes (T2D). However, the distribution of fat among these compartments is heterogenous and whether specific distribution patterns indicate high T2D risk is unclear. We therefore investigated fat distribution patterns and their link to future T2D. From 2,168 individuals without diabetes who underwent computed tomography in Japan, this case-cohort study included 658 randomly selected individuals and 146 incident cases of T2D over 6 years of follow-up. Using data-driven analysis (k-means) based on fat content in the liver, pancreas, muscle, and visceral bed, we identified four fat distribution clusters: hepatic steatosis, pancreatic steatosis, trunk myosteatosis, and steatopenia. In comparisons with the steatopenia cluster, the adjusted hazard ratios for incident T2D were 4.02 (95% CI 2.27-7.12) for the hepatic steatosis cluster, 3.38 (1.65-6.91) for the pancreatic steatosis cluster, and 1.95 (1.07-3.54) for the trunk myosteatosis cluster. The clusters were replicated in 319 German individuals without diabetes who underwent MRI and metabolic phenotyping. The distribution of the glucose area under the curve across the four clusters found in Germany was similar to the distribution of T2D risk across the four clusters in Japan. Insulin sensitivity and insulin secretion differed across the four clusters. Thus, we identified patterns of fat distribution with different T2D risks presumably due to differences in insulin sensitivity and insulin secretion.

Myosteatosis as a Shared Biomarker for Sarcopenia and Cachexia Using MRI and Ultrasound

Purpose

Establish bedside biomarkers of myosteatosis for sarcopenia and cachexia. We compared ultrasound biomarkers against MRI-based percent fat, histology, and CT-based muscle density among healthy adults and adults undergoing treatment for lung cancer.

Methods

We compared ultrasound and MRI myosteatosis measures among young healthy, older healthy, and older adults with non-small cell lung cancer undergoing systemic treatment, all without significant medical concerns, in a cross-sectional pilot study. We assessed each participant's rectus femoris ultrasound-based echo intensity (EI), shear wave elastography-based shear wave speed, and MRI-based proton density fat-fraction (PDFF). We also assessed BMI, rectus femoris thickness and cross-sectional area. Rectus femoris biopsies were taken for all older adults (n = 20) and we analyzed chest CT scans for older adults undergoing treatment (n = 10). We determined associations between muscle assessments and BMI, and compared these assessments between groups.

Results

A total of 10 young healthy adults, 10 older healthy adults, and 10 older adults undergoing treatment were recruited. PDFF was lower in young adults than in older healthy adults and older adults undergoing treatment (0.3 vs. 2.8 vs. 2.9%, respectively, p = 0.01). Young adults had significantly lower EI than older healthy adults, but not older adults undergoing treatment (48.6 vs. 81.8 vs. 75.4, p = 0.02). When comparing associations between measures, PDFF was strongly associated with EI (ρ = 0.75, p < 0.01) and moderately negatively associated with shear wave speed (ρ = −0.49, p < 0.01) but not BMI, whole leg cross-sectional area, or rectus femoris cross-sectional area. Among participants with CT scans, paraspinal muscle density was significantly associated with PDFF (ρ = −0.70, p = 0.023). Histological markers of inflammation or degradation did not differ between older adult groups.

Conclusion

PDFF was sensitive to myosteatosis between young adults and both older adult groups. EI was less sensitive to myosteatosis between groups, yet EI was strongly associated with PDFF unlike BMI, which is typically used in cachexia diagnosis. Our results suggest that ultrasound measures may serve to determine myosteatosis at the bedside and are more useful diagnostically than traditional weight assessments like BMI. These results show promise of using EI, shear wave speed, and PDFF proxies of myosteatosis as diagnostic and therapeutic biomarkers of sarcopenia and cachexia.

Assessment of anterior thigh muscle size and fat infiltration using single-slice CT imaging versus automated MRI analysis in adults

OBJECTIVES

We examined the longitudinal and cross-sectional relationship between automated MRI-analysis and single-slice axial CT imaging for determining muscle size and muscle fat infiltration (MFI) of the anterior thigh.

METHODS

Twenty-two patients completing sex-hormone treatment expected to result in muscle hypertrophy (n = 12) and atrophy (n = 10) underwent MRI scans using 2-point Dixon fat/water-separated sequences and CT scans using a system operating at 120 kV and a fixed flux of 100 mA. At baseline and 12 months after, automated volumetric MRI analysis of the anterior thigh was performed bilaterally, and fat-free muscle volume and MFI were computed. In addition, cross-sectional area (CSA) and radiological attenuation (RA) (as a marker of fat infiltration) were calculated from single slice axial CT-images using threshold-assisted planimetry. Linear regression models were used to convert units.

RESULTS

There was a strong correlation between MRI-derived fat-free muscle volume and CT-derived CSA (R = 0.91), and between MRI-derived MFI and CT-derived RA (R = -0.81). The 95% limits of agreement were ±0.32 L for muscle volume and ±1.3% units for %MFI. The longitudinal change in muscle size and MFI was comparable across imaging modalities.

CONCLUSIONS

Both automated MRI and single-slice CT-imaging can be used to reliably quantify anterior thigh muscle size and MFI.

ADVANCES IN KNOWLEDGE

This is the first study examining the intermodal agreement between automated MRI analysis and CT-image assessment of muscle size and MFI in the anterior thigh muscles. Our results support that both CT- and MRI-derived measures of muscle size and MFI can be used in clinical settings.

Influence of Baseline CT Body Composition Parameters on Survival in Patients with Pancreatic Adenocarcinoma

Pancreatic cancer is the seventh leading cause of cancer death in both sexes. The aim of this study is to analyze baseline CT body composition using artificial intelligence to identify possible imaging predictors of survival. We retrospectively included 103 patients. First, the presence of surgical treatment and cut-off values for sarcopenia and obesity served as independent variates. Second, the presence of surgery, subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and skeletal muscle index (SMI) served as independent variates. Cox regression analysis was performed for 1-year, 2-year, and 3-year survival. Possible differences between patients undergoing surgical versus nonsurgical treatment were analyzed. Presence of surgery significantly predicted 1-year, 2-year, and 3-year survival (p = 0.01, <0.001, and <0.001, respectively). Across the follow-up periods of 1-year, 2-year, and 3-year survival, the presence of sarcopenia became an equally important predictor of survival (p = 0.25, 0.07, and <0.001, respectively). Additionally, increased VAT predicted 2-year and 3-year survival (p = 0.02 and 0.04, respectively). The impact of sarcopenia on 3-year survival was higher in the surgical treatment group (p = 0.02 and odds ratio = 2.57) compared with the nonsurgical treatment group (p = 0.04 and odds ratio = 1.92). Fittingly, a lower SMI significantly affected 3-year survival only in patients who underwent surgery (p = 0.02). Especially if surgery is performed, AI-derived sarcopenia and reduced muscle mass are unfavorable imaging predictors.

Sarcopenia in Children with Solid Organ Tumors: An Instrumental Era

Sarcopenia has recently been studied in both adults and children and was found to be a prognostic marker for adverse outcome in a variety of patient groups. Our research showed that sarcopenia is a relevant marker in predicting outcome in children with solid organ tumors, such as hepatoblastoma and neuroblastoma. This was especially true in very ill, high-risk groups. Children with cancer have a higher likelihood of ongoing loss of skeletal muscle mass due to a mismatch in energy intake and expenditure. Additionally, the effects of cancer therapy, hormonal alterations, chronic inflammation, multi-organ dysfunction, and a hypermetabolic state all contribute to a loss of skeletal muscle mass. Sarcopenia seems to be able to pinpoint this waste to a high degree in a new and objective way, making it an additional tool in predicting and improving outcome in children. This article focuses on the current state of sarcopenia in children with solid organ tumors. It details the pathophysiological mechanisms behind sarcopenia, highlighting the technical features of the available methods for measuring muscle mass, strength, and function, including artificial intelligence (AI)-based techniques. It also reviews the latest research on sarcopenia in children, focusing on children with solid organ tumors.

Myosteatosis Significantly Predicts Persistent Dyspnea and Mobility Problems in COVID-19 Survivors

Background

Persistent symptoms including dyspnea and functional impairment are common in COVID-19 survivors. Poor muscle quality (myosteatosis) associates with poor short-term outcomes in COVID-19 patients. The aim of this observational study was to assess the relationship between myosteatosis diagnosed during acute COVID-19 and patient-reported outcomes at 6 months after discharge.

Methods

Myosteatosis was diagnosed based on CT-derived skeletal muscle radiation attenuation (SM-RA) measured during hospitalization in 97 COVID-19 survivors who had available anthropometric and clinical data upon admission and at the 6-month follow-up after discharge. Dyspnea in daily activities was assessed using the modified Medical Research Council (mMRC) scale for dyspnea. Health-related quality of life was measured using the European quality of life questionnaire three-level version (EQ-5D-3L).

Results

Characteristics of patients with (lowest sex- and age-specific tertile of SM-RA) or without myosteatosis during acute COVID-19 were similar. At 6 months, patients with myosteatosis had greater rates of obesity (48.4 vs. 27.7%, p = 0.046), abdominal obesity (80.0 vs. 47.6%, p = 0.003), dyspnea (32.3 vs. 12.5%, p = 0.021) and mobility problems (32.3 vs. 12.5%, p = 0.004). Myosteatosis diagnosed during acute COVID-19 was the only significant predictor of persistent dyspnea (OR 3.19 [95% C.I. 1.04; 9.87], p = 0.043) and mobility problems (OR 3.70 [95% C.I. 1.25; 10.95], p = 0.018) at 6 months at logistic regression adjusted for sex, age, and BMI.

Conclusion

Myosteatosis diagnosed during acute COVID-19 significantly predicts persistent dyspnea and mobility problems at 6 months after hospital discharge independent of age, sex, and body mass.

Clinical Trial Registration

[www.ClinicalTrials.gov], identifier [NCT04318366].

Associations of Computed Tomography Image-Assessed Adiposity and Skeletal Muscles with Triple-Negative Breast Cancer

Obesity measured by anthropometrics is associated with increased risk of triple-negative breast cancer (TNBC). It is unclear to what extent specific adipose tissue components, aside from muscle, are associated with TNBC. This retrospective study included 350 breast cancer patients who received treatment between October 2011 and April 2020 with archived abdominal or pelvic computed tomography (CT) images. We measured the areas of adipose tissue and five-density levels of skeletal muscle on patients' third lumbar vertebra (L3) image. Logistic regression was performed to examine the associations of specific adiposity and skeletal muscles components and a four-category body composition phenotype with the TNBC subtype. Results showed that higher vs. lower areas (3rd vs. 1st tertiles) of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) were associated with increased odds of TNBC vs. non-TNBC after adjusting for age, race, stage, tumor grade, tumor size, and skeletal muscle areas (adjusted odds ratio [AOR], 11.25 [95% CI = 3.46-36.52]) and (AOR, 10.34 [95% CI = 2.90-36.90]) respectively. Higher areas of low density muscle was also associated with increased odds of TNBC (AOR, 3.15 [95% CI = 1.05-10.98]). Compared to normal body composition (low adipose tissue/high muscle), high adiposity/high muscle was associated with higher odds of TNBC (AOR, 5.54 [95% CI = 2.12-14.7]). These associations were mainly in premenopausal women and among patients with the CT performed after breast cancer surgery. Specific adipose tissue and low-density muscle can be associated with the TNBC subtype in breast cancer patients. The direction of association warrants confirmation by prospective studies.

Utility of handgrip strength (HGS) and bioelectrical impedance analysis (BIA) in the diagnosis of sarcopenia in cirrhotic patients

BACKGROUND

Sarcopenia is associated with disability, mortality, and poorer survival in cirrhotic patients. For the evaluation of muscle volume, computed tomography (CT) is the most accurate tool. Unfortunately, it would be hard to apply a muscle mass measuring CT to daily practice. This research aims to study the utility of handgrip strength (HGS) and bioelectrical impedance analysis (BIA) to detect sarcopenia in cirrhotic patients compared with CT as the reference.

METHODS

In cirrhotic patients who met inclusions criteria (age 20-70 years, ascites < grade 2 of International Ascites Club grading system, no active malignancy, and no cardiac implanted device), HGS were measured using a Jamar dynamometer. Subsequently, patients with low muscle strength (defined as JSH criteria, < 26 kg in male, < 18 kg in female) were then underwent CT and BIA (Tanita MC780 MA) on the same day to measure muscle volume, the definition of sarcopenia by CT was according to the Japan Society of Hepatology (JSH). We also collected data from patients with normal HGS whose CT results were available in the study period.

RESULTS

From 146 cirrhotic patients who underwent HGS, 30 patients (20.5%) had diagnosed low HSG. Data from 50 patients whose available CT results included 30 low HGS and 20 patients with normal HSG. The HGS was strongly correlated with skeleton muscle index (SMI) by CT (r = 0.81, p < 0.001) and had an excellent diagnostic performance for detecting sarcopenia by using JSH criteria the sensitivity, specificity, NPV and PPV were 88.2%, 100%, 100%, and 98.7% respectively. In contrast, only 6 of 30 patients (20%) met sarcopenic criteria by BIA. Among sarcopenic patients, the result showed a fair correlation between SMI and BIA (r = 0.54; p < 0.002).

CONCLUSION

Our study demonstrated an excellent correlation between HGS and SMI by CT in the mixed cirrhotic population from the sarcopenia and non-sarcopenia groups. The HGS using the JSH criteria showed an excellent performance in detecting sarcopenia compared to CT. Nonetheless, for the BIA by using the current cut-offs demonstrated unacceptable rate to detect sarcopenia.

Diagnosis and Management of Sarcopenia after Hip Fracture Surgery: Current Concept Review

To date, family medicine and internal medicine fields have been responsible for defining, researching, and development of treatments for sarcopenia, focusing mainly on diabetes and metabolic diseases. Therefore, application of current guidelines for diagnosis of sarcopenia which differ according to continent to patients with hip fractures in the orthopedic field is difficult. The purpose of this review was to understand the recent consensus on the definition and diagnosis of sarcopenia and to highlight the importance of research and future research opportunities on the management of sarcopenia in patients with hip fractures by orthopedic surgeons. The global prevalence of sarcopenia in patients with hip fractures is statistically significant. Despite establishment of various therapeutic and diagnostic criteria for osteoporosis in the clinical field, there are no clear, useful diagnostic criteria for sarcopenia in the clinical field. In particular, few studies on the evaluation and treatment of sarcopenia in patients with hip fractures have been reported. In addition, the quality of life of postoperative patients with hip fractures could be significantly improved by development of precise assessment for muscle regeneration and rehabilitation in the operating room.

Effects of Artificial Intelligence-Derived Body Composition on Kidney Graft and Patient Survival in the Eurotransplant Senior Program

The Eurotransplant Senior Program allocates kidneys to elderly transplant patients. The aim of this retrospective study is to investigate the use of computed tomography (CT) body composition using artificial intelligence (AI)-based tissue segmentation to predict patient and kidney transplant survival. Body composition at the third lumbar vertebra level was analyzed in 42 kidney transplant recipients. Cox regression analysis of 1-year, 3-year and 5-year patient survival, 1-year, 3-year and 5-year censored kidney transplant survival, and 1-year, 3-year and 5-year uncensored kidney transplant survival was performed. First, the body mass index (BMI), psoas muscle index (PMI), skeletal muscle index (SMI), visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) served as independent variates. Second, the cut-off values for sarcopenia and obesity served as independent variates. The 1-year uncensored and censored kidney transplant survival was influenced by reduced PMI (p = 0.02 and p = 0.03, respectively) and reduced SMI (p = 0.01 and p = 0.03, respectively); 3-year uncensored kidney transplant survival was influenced by increased VAT (p = 0.04); and 3-year censored kidney transplant survival was influenced by reduced SMI (p = 0.05). Additionally, sarcopenia influenced 1-year uncensored kidney transplant survival (p = 0.05), whereas obesity influenced 3-year and 5-year uncensored kidney transplant survival. In summary, AI-based body composition analysis may aid in predicting short- and long-term kidney transplant survival.

Percentile-based averaging and skeletal muscle gauge improve body composition analysis: validation at multiple vertebral levels

BACKGROUND

Skeletal muscle metrics on computed tomography (CT) correlate with clinical and patient-reported outcomes. We hypothesize that aggregating skeletal muscle measurements from multiple vertebral levels and skeletal muscle gauge (SMG) better predict outcomes than skeletal muscle radioattenuation (SMRA) or -index (SMI) at a single vertebral level.

METHODS

We performed a secondary analysis of prospectively collected clinical (overall survival, hospital readmission, time to unplanned hospital readmission or death, and readmission or death within 90 days) and patient-reported outcomes (physical and psychological symptom burden captured as Edmonton Symptom Assessment Scale and Patient Health Questionnaire) of patients with advanced cancer who experienced an unplanned admission to Massachusetts General Hospital from 2014 to 2016. First, we assessed the correlation of skeletal muscle cross-sectional area, SMRA, SMI, and SMG at one or more of the following thoracic (T) or lumbar (L) vertebral levels: T5, T8, T10, and L3 on CT scans obtained ≤50 days before index assessment. Second, we aggregated measurements across all available vertebral levels using percentile-based averaging (PBA) to create the average percentile. Third, we constructed one regression model adjusted for age, sex, sociodemographic factors, cancer type, body mass index, and intravenous contrast for each combination of (i) vertebral level and average percentile, (ii) muscle metrics (SMRA, SMI, & SMG), and (iii) clinical and patient-reported outcomes. Fourth, we compared the performance of vertebral levels and muscle metrics by ranking otherwise identical models by concordance statistic, number of included patients, coefficient of determination, and significance of muscle metric.

RESULTS

We included 846 patients (mean age: 63.5 ± 12.9 years, 50.5% males) with advanced cancer [predominantly gastrointestinal (32.9%) or lung (18.9%)]. The correlation of muscle measurements between vertebral levels ranged from 0.71 to 0.84 for SMRA and 0.67 to 0.81 for SMI. The correlation of individual levels with the average percentile was 0.90-0.93 for SMRA and 0.86-0.92 for SMI. The intrapatient correlation of SMRA with SMI was 0.21-0.40. PBA allowed for inclusion of 8-47% more patients than any single-level analysis. PBA outperformed single-level analyses across all comparisons with average ranks 2.6, 2.9, and 1.6 for concordance statistic, coefficient of determination, and significance (range 1-5, μ = 3), respectively. On average, SMG outperformed SMRA and SMI across outcomes and vertebral levels: the average rank of SMG was 1.4, 1.4, and 1.4 for concordance statistic, coefficient of determination, and significance (range 1-3, μ = 2), respectively.

CONCLUSIONS

Multivertebral level skeletal muscle analyses using PBA and SMG independently and additively outperform analyses using individual levels and SMRA or SMI.

Progressive Skeletal Muscle Loss After Surgery and Adjuvant Radiotherapy Impact Survival Outcomes in Patients With Early Stage Cervical Cancer

The effect of skeletal muscle loss associated with surgery and adjuvant radiotherapy on survival outcomes in patients with early-stage cervical cancer remains unclear. We analyzed the data of 133 patients with early-stage cervical cancer who underwent surgery and adjuvant radiotherapy between 2013 and 2018 at two tertiary centers. Skeletal muscle changes were measured using computed tomography scans at baseline, at simulation for radiotherapy, and at 3 months post-treatment. A decrease of ≥5% in the skeletal muscle was defined as “muscle loss.” The Patient-Reported Outcome version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) was used to assess gastrointestinal toxicity. The Patient-Generated Subjective Global Assessment (PG-SGA) was used for nutritional assessment. Predictors of overall survival were identified using the Cox regression models. The median follow-up period was 3.7 years. After treatment, 32 patients (24.1%) experienced muscle loss. The rate of muscle loss was higher in patients with PRO-CTCAE score ≥3 or PG-SGA score ≥4 at the end of radiotherapy than in patients with PRO-CTCAE score ≤2 or PG-SGA score 0–3 (75.0 vs. 10.5%, p < 0.001; 71.4 vs. 2.2%, p < 0.001). The 3-year overall survival was significantly lower in patients with muscle loss than in those with muscle preserved (65.6 vs. 93.9%, p < 0.001). Multivariate analysis showed that muscle loss was independently associated with poor overall survival (hazard ratio, 4.55; 95% confidence interval: 1.63–12.72; p < 0.001). Muscle loss after surgery and adjuvant radiotherapy was associated with poor overall survival in patients with early-stage cervical cancer. Muscle loss is associated with patient-reported gastrointestinal toxicity and deterioration in nutritional status.

Methodology, clinical applications, and future directions of body composition analysis using computed tomography (CT) images: A review

PURPOSE OF THE REVIEW

We aim to review the methods, current research evidence, and future directions in body composition analysis (BCA) with CT imaging.

RECENT FINDINGS

CT images can be used to evaluate muscle tissue, visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) compartments. Manual and semiautomatic segmentation methods are still the gold standards. The segmentation of skeletal muscle tissue and VAT and SAT compartments is most often performed at the level of the 3rd lumbar vertebra. A decreased amount of CT-determined skeletal muscle mass is a marker of impaired survival in many patient populations, including patients with most types of cancer, some surgical patients, and those admitted to the intensive care unit (ICU). Patients with increased VAT are more susceptible to impaired survival / worse outcomes; however, those patients who are critically ill or admitted to the ICU or who will undergo surgery appear to be exceptions. The independent significance of SAT is less well established. Recently, the roles of the CT-determined decrease of muscle mass and increased VAT area and epicardial adipose tissue (EAT) volume have been shown to predict a more debilitating course of illness in patients suffering from severe acute respiratory syndrome coronavirus 2 (COVID-19) infection.

SUMMARY

The field of CT-based body composition analysis is rapidly evolving and shows great potential for clinical implementation.

Muscle Loss During Androgen Deprivation Therapy Is Associated With Higher Risk of Non-Cancer Mortality in High-Risk Prostate Cancer

The changes in body composition are early adverse effects of androgen deprivation therapy (ADT); however, their prognostic impact remains unclear in prostate cancer. This study aimed to evaluate the association between body composition changes and survival in patients with high-risk prostate cancer. We measured the skeletal muscle index (SMI) and total adipose tissue index (TATI) at the L3 vertebral level using computed tomography at baseline and within one year after initiating ADT in 125 patients with high-risk prostate cancer treated with radiotherapy and ADT between 2008 and 2018. Non-cancer mortality predictors were identified using Cox regression models. The median follow-up was 49 months. Patients experienced an average SMI loss of 5.5% over 180 days (95% confidence interval: -7.0 to -4.0; p<0.001) and TATI gain of 12.6% over 180 days (95% confidence interval: 9.0 to 16.2; p<0.001). Body mass index changes were highly and weakly correlated with changes in TATI and SMI, respectively (Spearman ρ for TATI, 0.78, p<0.001; ρ for SMI, 0.27, p=0.003). As a continuous variable, each 1% decrease in SMI was independently associated with a 9% increase in the risk of non-cancer mortality (hazard ratio: 1.09; p=0.007). Moreover, the risk of non-cancer mortality increased 5.6-fold in patients with SMI loss ≥5% compared to those with unchanged SMI (hazard ratio: 5.60; p=0.03). Body mass index and TATI were not associated with non-cancer mortality. Muscle loss during ADT is occult, independent of weight change, and independently associated with increased non-cancer mortality in patients with high-risk prostate cancer.

End-to-end automated body composition analyses with integrated quality control for opportunistic assessment of sarcopenia in CT

OBJECTIVES

To develop a pipeline for automated body composition analysis and skeletal muscle assessment with integrated quality control for large-scale application in opportunistic imaging.

METHODS

First, a convolutional neural network for extraction of a single slice at the L3/L4 lumbar level was developed on CT scans of 240 patients applying the nnU-Net framework. Second, a 2D competitive dense fully convolutional U-Net for segmentation of visceral and subcutaneous adipose tissue (VAT, SAT), skeletal muscle (SM), and subsequent determination of fatty muscle fraction (FMF) was developed on single CT slices of 1143 patients. For both steps, automated quality control was integrated by a logistic regression model classifying the presence of L3/L4 and a linear regression model predicting the segmentation quality in terms of Dice score. To evaluate the performance of the entire pipeline end-to-end, body composition metrics, and FMF were compared to manual analyses including 364 patients from two centers.

RESULTS

Excellent results were observed for slice extraction (z-deviation = 2.46 ± 6.20 mm) and segmentation (Dice score for SM = 0.95 ± 0.04, VAT = 0.98 ± 0.02, SAT = 0.97 ± 0.04) on the dual-center test set excluding cases with artifacts due to metallic implants. No data were excluded for end-to-end performance analyses. With a restrictive setting of the integrated segmentation quality control, 39 of 364 patients were excluded containing 8 cases with metallic implants. This setting ensured a high agreement between manual and fully automated analyses with mean relative area deviations of ΔSM = 3.3 ± 4.1%, ΔVAT = 3.0 ± 4.7%, ΔSAT = 2.7 ± 4.3%, and ΔFMF = 4.3 ± 4.4%.

CONCLUSIONS

This study presents an end-to-end automated deep learning pipeline for large-scale opportunistic assessment of body composition metrics and sarcopenia biomarkers in clinical routine.

KEY POINTS

• Body composition metrics and skeletal muscle quality can be opportunistically determined from routine abdominal CT scans. • A pipeline consisting of two convolutional neural networks allows an end-to-end automated analysis. • Machine-learning-based quality control ensures high agreement between manual and automatic analysis.

Imaging modalities for diagnosis and monitoring of cancer cachexia

Cachexia, a multifactorial wasting syndrome, is highly prevalent among advanced-stage cancer patients. Unlike weight loss in healthy humans, the progressive loss of body weight in cancer cachexia primarily implicates lean body mass, caused by an aberrant metabolism and systemic inflammation. This may lead to disease aggravation, poorer quality of life, and increased mortality. Timely detection is, therefore, crucial, as is the careful monitoring of cancer progression, in an effort to improve management, facilitate individual treatment and minimize disease complications. A detailed analysis of body composition and tissue changes using imaging modalities—that is, computed tomography, magnetic resonance imaging, (¹⁸F) fluoro-2-deoxy-d-glucose (¹⁸FDG) PET and dual-energy X-ray absorptiometry—shows great premise for charting the course of cachexia. Quantitative and qualitative changes to adipose tissue, organs, and muscle compartments, particularly of the trunk and extremities, could present important biomarkers for phenotyping cachexia and determining its onset in patients. In this review, we present and compare the imaging techniques that have been used in the setting of cancer cachexia. Their individual limitations, drawbacks in the face of clinical routine care, and relevance in oncology are also discussed.

Total Psoas Muscle Area as a Marker for Sarcopenia Is Related to Outcome in Children With Neuroblastoma

Background: Sarcopenia describes a generalized loss of skeletal muscle mass, strength, or function. Determined by measuring the total psoas muscle area (tPMA) on cross-sectional imaging, sarcopenia is an independent marker for poor post-surgical outcomes in adults and children. Children with cancer are at high risk for sarcopenia due to immobility, chemotherapy, and cachexia. We hypothesize that sarcopenic children with neuroblastoma are at higher risk for poor post-operative outcomes. Patients and Methods: Retrospective analysis of children with neuroblastoma ages 1-15 years who were treated at our hospital from 2008 to 2016 with follow-up through March 2021. Psoas muscle area (PMA) was measured from cross-sectional images, using computed tomography (CT) and magnetic resonance imaging (MRI) scans at lumbar disc levels L3-4 and L4-5. tPMA is the sum of the left and right PMA. Z-scores were calculated using age- and gender-specific reference values. Sarcopenia was defined as a tPMA z-score below -2. A correlation of tPMA z-scores and sarcopenia with clinical variables and outcome was performed. Results: One hundred and sixty-four children with workup for neuroblastoma were identified, and 101 children fulfilled inclusion criteria for further analysis, with a mean age of 3.92 years (SD 2.71 years). Mean tPMA z-score at L4-5 was -2.37 (SD 1.02). Correlation of tPMA z-score at L4-5 with weight-for-age z-score was moderate (r = 0.54; 95% CI, 0.38, 0.66). No association between sarcopenia and short-term outcome was observed. Sarcopenia had a sensitivity of 0.82 (95% CI, 0.62-0.93) and a specificity of 0.48 (95% CI 0.36-0.61) in predicting 5-year survival. In a multiple regression analysis, pre-operative sarcopenia, pre-operative chemotherapy in the NB2004 high-risk group, unfavorable tumor histology, and age at diagnosis were associated with 5-year survival after surgery, with hazard ratios of 4.18 (95% CI 1.01-17.26), 2.46 (95% CI 1.02-5.92), 2.39 (95% CI 1.03-5.54), and 1.01 (95% CI 1.00-1.03), respectively. Conclusion: In this study, the majority of children had low tPMA z-scores and sarcopenia was a risk factor for decreased 5-year survival in children with neuroblastoma. Therefore, we suggest measuring the tPMA from pre-surgical cross-sectional imaging as a biomarker for additional risk stratification in children with neuroblastoma.

Artificial intelligence-based analysis of body composition in Marfan: skeletal muscle density and psoas muscle index predict aortic enlargement

BACKGROUND

Patients with Marfan syndrome are at risk for aortic enlargement and are routinely monitored by computed tomography (CT) imaging. The purpose of this study is to analyse body composition using artificial intelligence (AI)-based tissue segmentation in patients with Marfan syndrome in order to identify possible predictors of progressive aortic enlargement.

METHODS

In this study, the body composition of 25 patients aged ≤50 years with Marfan syndrome and no prior aortic repair was analysed at the third lumbar vertebra (L3) level from a retrospective dataset using an AI-based software tool (Visage Imaging). All patients underwent electrocardiography-triggered CT of the aorta twice within 2 years for suspected progression of aortic disease, suspected dissection, and/or pre-operative evaluation. Progression of aortic enlargement was defined as an increase in diameter at the aortic sinus or the ascending aorta of at least 2 mm. Patients meeting this definition were assigned to the 'progressive aortic enlargement' group (proAE group) and patients with stable diameters to the 'stable aortic enlargement' group (staAE group). Statistical analysis was performed using the Mann-Whitney U test. Two possible body composition predictors of aortic enlargement-skeletal muscle density (SMD) and psoas muscle index (PMI)-were analysed further using multivariant logistic regression analysis. Aortic enlargement was defined as the dependent variant, whereas PMI, SMD, age, sex, body mass index (BMI), beta blocker medication, and time interval between CT scans were defined as independent variants.

RESULTS

There were 13 patients in the proAE group and 12 patients in the staAE group. AI-based automated analysis of body composition at L3 revealed a significantly increased SMD measured in Hounsfield units (HUs) in patients with aortic enlargement (proAE group: 50.0 ± 8.6 HU vs. staAE group: 39.0 ± 15.0 HU; P = 0.03). PMI also trended towards higher values in the proAE group (proAE group: 6.8 ± 2.3 vs. staAE group: 5.6 ± 1.3; P = 0.19). Multivariate logistic regression revealed significant prediction of aortic enlargement for SMD (P = 0.05) and PMI (P = 0.04).

CONCLUSIONS

Artificial intelligence-based analysis of body composition at L3 in Marfan patients is feasible and easily available from CT angiography. Analysis of body composition at L3 revealed significantly higher SMD in patients with progressive aortic enlargement. PMI and SMD significantly predicted aortic enlargement in these patients. Using body composition as a predictor of progressive aortic enlargement may contribute information for risk stratification regarding follow-up intervals and the need for aortic repair.

Artificial intelligence to assess body composition on routine abdominal CT scans and predict mortality in pancreatic cancer- A recipe for your local application

BACKGROUND

Body composition is associated with mortality; however its routine assessment is too time-consuming.

PURPOSE

To demonstrate the value of artificial intelligence (AI) to extract body composition measures from routine studies, we aimed to develop a fully automated AI approach to measure fat and muscles masses, to validate its clinical discriminatory value, and to provide the code, training data and workflow solutions to facilitate its integration into local practice.

METHODS

We developed a neural network that quantified the tissue components at the L3 vertebral body level using data from the Liver Tumor Challenge (LiTS) and a pancreatic cancer cohort. We classified sarcopenia using accepted skeletal muscle index cut-offs and visceral fat based its median value. We used Kaplan Meier curves and Cox regression analysis to assess the association between these measures and mortality.

RESULTS

Applying the algorithm trained on LiTS data to the local cohort yielded good agreement [>0.8 intraclass correlation (ICC)]; when trained on both datasets, it had excellent agreement (>0.9 ICC). The pancreatic cancer cohort had 136 patients (mean age: 67 ± 11 years; 54% women); 15% had sarcopenia; mean visceral fat was 142 cm². Concurrent with prior research, we found a significant association between sarcopenia and mortality [mean survival of 15 ± 12 vs. 22 ± 12 (p < 0.05), adjusted HR of 1.58 (95% CI: 1.03-3.33)] but no association between visceral fat and mortality. The detector analysis took 1 ± 0.5 s.

CONCLUSIONS

AI body composition analysis can provide meaningful imaging biomarkers from routine exams demonstrating AI's ability to further enhance the clinical value of radiology reports.

Skeletal Muscle and Childhood Cancer: Where are we now and where we go from here

Skeletal muscle (muscle) is essential for physical health and for metabolic integrity, with sarcopenia (progressive muscle mass loss and weakness), a pre-curser of aging and chronic disease. Loss of lean mass and muscle quality (force generation per unit of muscle) in the general population are associated with fatigue, weakness, and slowed walking speed, eventually interfering with the ability to maintain physical independence, and impacting participation in social roles and quality of life. Muscle mass and strength impairments are also documented during childhood cancer treatment, which often persist into adult survivorship, and contribute to an aging phenotype in this vulnerable population. Although several treatment exposures appear to confer increased risk for loss of mass and strength that persists after therapy, the pathophysiology responsible for poor muscle quantity and quality is not well understood in the childhood cancer survivor population. This is partly due to limited access to both pediatric and adult survivor muscle tissue samples, and to difficulties surrounding non-invasive investigative approaches for muscle assessment. Because muscle accounts for just under half of the body's mass, and is essential for movement, metabolism and metabolic health, understanding mechanisms of injury responsible for both initial and persistent dysfunction is important, and will provide a foundation for intervention. The purpose of this review is to provide an overview of the available evidence describing associations between childhood cancer, its treatment, and muscle outcomes, identifying gaps in current knowledge.

Radiologic Definition of Sarcopenia in Chronic Liver Disease

Sarcopenia is prevalent in patients with chronic liver disease, and affected patients tend to have worse clinical outcomes and higher mortality. However, relevant analyses are limited by heterogeneity in the definition of sarcopenia and in the methodological approaches in assessing it. We reviewed several radiologic methods for sarcopenia in patients with chronic liver disease. Dual energy X-ray absorptiometry (DXA) can measure muscle mass, but it is difficult to evaluate muscle quality using this technique. Computed tomography, known as the gold standard for diagnosing sarcopenia, enables the objective measurement of muscle quantity and quality. The third lumbar skeletal muscle index (L3 SMI) more accurately predicted the mortality of subjects than the psoas muscle index (PMI). Few studies have evaluated the sarcopenia of chronic liver disease using ultrasonography and magnetic resonance imaging, and more studies are needed. Unification of the measurement method and cut-off value would facilitate a more systematic and universal prognosis evaluation in patients with chronic liver disease.

Radiologic Definition of Sarcopenia in Chronic Liver Disease

Sarcopenia is prevalent in patients with chronic liver disease, and affected patients tend to have worse clinical outcomes and higher mortality. However, relevant analyses are limited by heterogeneity in the definition of sarcopenia and in the methodological approaches in assessing it. We reviewed several radiologic methods for sarcopenia in patients with chronic liver disease. Dual energy X-ray absorptiometry (DXA) can measure muscle mass, but it is difficult to evaluate muscle quality using this technique. Computed tomography, known as the gold standard for diagnosing sarcopenia, enables the objective measurement of muscle quantity and quality. The third lumbar skeletal muscle index (L3 SMI) more accurately predicted the mortality of subjects than the psoas muscle index (PMI). Few studies have evaluated the sarcopenia of chronic liver disease using ultrasonography and magnetic resonance imaging, and more studies are needed. Unification of the measurement method and cut-off value would facilitate a more systematic and universal prognosis evaluation in patients with chronic liver disease.