Estimated skeletal muscle mass and density values measured on computed tomography examinations in over 1000 living kidney donors

Defining Reference Values for Skeletal Muscle Metrics on Abdominal CT Using Data From Healthy Young Adult Populations: A Systematic Review and Meta-Analysis

BACKGROUND. CT muscle metrics hold promise for opportunistic sarcopenia screening and individualized clinical risk stratification, but reference values applicable across broad populations are lacking. OBJECTIVE. To estimate reference cutoff values for CT skeletal muscle metrics using data from populations of healthy young adults. EVIDENCE ACQUISITION. The PubMed, Embase, Cochrane Library, Web of Science, and Scopus databases were searched through January 1, 2025 for studies reporting skeletal muscle index (SMI) and/or skeletal muscle density (SMD) on CT at the L3 vertebral level in healthy young adults (age range, 18-45 years). For SMI and SMD in both men and women, a random effects meta-analysis was used to estimate interstudy SD (as a measure of variance among studies) and mean values for a theoretic global population of healthy young adults. Presence of significant heterogeneity among individual study means was assessed using the Q statistic. Cutoff values for the theoretic global population corresponding with a T-score of -2 (i.e., values ≥ 2 SDs below the population's mean value) were calculated, incorporating the meta-analysis results and pooled intrastudy variance. EVIDENCE SYNTHESIS. The meta-analysis included 14 studies (16,958 individuals; 11,819 men, 5139 women) reporting SMI, of which seven studies (11,175 individuals; 8372 men, 2803 women) also reported SMD. The estimated global mean value for SMI was 54.6 in men and 42.4 in women and for SMD was 47.4 HU in men and 43.6 HU in women. The interstudy SD for SMI was 5.4 in men and 4.3 in women and for SMD was 1.9 in men versus 3.2 in women; significant heterogeneity was present among individual study means for both SMI and SMD in both men and women (all p<.001). The cutoff value corresponding with a T-score of -2 for SMI was 36.3 in men and 27.5 in women and for SMD was 36.4 HU in men and 28.1 HU in women. CONCLUSION. This meta-analysis of studies performed in healthy young adults provides reference mean values and standardized cutoffs analogous to a T-score of -2 for SMI and SMD at the L3 level on abdominal CT. CLINICAL IMPACT. These results can aid opportunistic screening for sarcopenia.

Age- and sex-specific reference values for CT-based low skeletal muscle quantity and quality in healthy living kidney donors

Background

Computed tomography (CT) imaging is a useful tool for assessing skeletal muscle mass and quality. The present study aimed to determine age- and sex-specific reference values for CT-based skeletal muscle markers in a healthy population, and to correlate them with serum creatinine and 24-h urinary creatinine excretion (24h-UCE).

Methods

Skeletal muscle index (SMI) - a marker of muscle mass/quantity - and skeletal muscle radiation attenuation (SMRA) and intermuscular adipose tissue index (IMATI) - markers of muscle quality/myosteatosis - were determined using a deep-learning-based method from axial CT images at the level of the 3rd lumbar vertebra in living kidney donors assessed between 01/2005 and 05/2023. Age- and sex-specific reference values were determined by the 5th percentile, and correlation was tested with the Pearson correlation coefficient.

Results

CT scans of 394 healthy individuals were included. The mean age was 53 years (SD 12), mean BMI was 25.2 kg/m2 (SD 3.9), and 130 patients (33%) were male. The reference values for low skeletal muscle mass (SMI) in males were 43.7 cm2/m2 (20-39 years), 44.9 cm2/m2 (40-59 years), and 39.7 cm2/m2 (≥60 years). In females, the corresponding values were 33.8 cm2/m2 (20-39 years), 34.8 cm2/m2 (40-59 years), and 31.2 cm2/m2 (≥60 years). SMI showed a moderate correlation with serum creatinine (r = 0.452, p < 0.001) but a weak correlation with 24h-UCE (r = 0.188, p = 0.003). Correlations were all weak for SMRA (creatinine: r = 0.220, p < 0.001; 24h-UCE: r = 0.177, p = 0.006) and IMATI (creatinine: r = -0.101, p = 0.054; 24h-UCE, r = -0.108, p = 0.093).

Conclusion

The age- and sex-specific reference values reported here could be used in clinical practice and future studies to identify patients at risk of muscle decline.

Optimizing Nutritional Care with Machine Learning: Identifying Sarcopenia Risk Through Body Composition Parameters in Cancer Patients-Insights from the NUTritional and Sarcopenia RIsk SCREENing Project (NUTRISCREEN)

Background/Objectives: Cancer and related treatments can impair body composition (BC), increasing the risk of malnutrition and sarcopenia, poor prognosis, and Health-Related Quality of Life (HRQoL). To enhance BC parameter interpretation through Bioelectrical Impedance Analysis (BIA), we developed a predictive model based on unsupervised approaches including Principal Component Analysis (PCA) and k-means clustering for sarcopenia risk in cancer patients at the Istituto Nazionale Tumori IRCCS "Fondazione G. Pascale" (Naples). Methods: Sarcopenia and malnutrition risks were assessed using the NRS-2002 and SARC-F questionnaires, anthropometric measurements, and BIA. HRQoL was evaluated with the EORTC QLQ-C30 questionnaire. PCA and clustering analysis were performed to identify different BC profiles. Results: Data from 879 cancer patients (mean age: 63 ± 12.5 years) were collected: 117 patients (13%) and 128 (15%) were at risk of malnutrition and sarcopenia, respectively. PCA analysis identified three main components, and k-means determined three clusters, namely HMP (High Muscle Profile), MMP (Moderate Muscle Profile), and LMP (Low Muscle Profile). Patients in LMP were older, with a higher prevalence of comorbidities, malnutrition, and sarcopenia. In the multivariable analysis, age, lung cancer site, diabetes, and malnutrition risk were significantly associated with an increased risk of sarcopenia; among the clusters, patients in LMP had an increased risk of sarcopenia (+62%, p = 0.006). Conclusions: The NUTRISCREEN project, part of the ONCOCAMP study (ClinicalTrials.gov ID: NCT06270602), provides a personalized nutritional pathway for early screening of malnutrition and sarcopenia. Using an unsupervised approach, we provide distinct BC profiles and valuable insights into the factors associated with sarcopenia risk. This approach in clinical practice could help define risk categories, ensure the most appropriate nutritional strategies, and improve patient outcomes by providing data-driven care.

[Body composition analysis on computed tomography scans using easy-to-access segmentation software]

Computed tomography (CT) is a direct and reference technique for body composition analysis with interesting possibilities in clinical nutrition. Segmentation is the automatic or semi-automatic software-based process by which different metabolic tissues of interest (muscle tissue, subcutaneous adipose tissue, visceral adipose tissue and intermuscular adipose tissue) that are part of the current diagnoses of malnutrition, sarcopenia and sarcopenic obesity are delimited, separated and quantified. The Alberta protocol is the most common segmentation guide, being applicable in most software. In this paper, we review the main characteristics of the most common open-source segmentation software, their degree of agreement, and some precautions and limitations of this process.

Are Muscle and Fat Loss Predictive of Clinical Events in Pancreatic Cancer? The Importance of Precision Metrics

CONTEXT

Muscle and fat loss from cancer may have prognostic significance. Skeletal muscle and fat areas measured at L3 on a CT scan correlate with body muscle and fat mass. We wished to know if reduced skeletal muscle area or fat on diagnostic CT scans or changes from initial CT scans in patients with pancreatic cancer who died in 2018 and 2019 predicted mortality.

METHOD

Electronic records of 112 patients with locally advanced or metastatic pancreatic cancer were used to extract stage, age, gender, comorbidities, weight, and height at the time of the first CT scan. Survival (in days) was defined from the first CT scan to the death date. Patients had at least one CT scan of the abdomen. I. Two trained medical students read scans independently using TeraRecon software (Durham, NC). Results were averaged, and the differences determined precision. Interclass correlation coefficient (ICC), coefficient of variation, and least significant change determined the precision between readers. Independent prognostic modeling included age and BMI.

RESULTS

An evaluable sample of 104 with an average age of 67, 56 were male. Nearly half had a TNM Stage of IV (45%). The average Charlson Comorbidity index is 7.2. In those undergoing repeat scans, most were in the timeframe of 60-120 days. Changes in visceral fat in men in the unadjusted Cox proportional hazard model and reduced skeletal muscle area in the age-adjusted model of men predicted mortality. In contrast, myosteatosis in women marginally predicted improved survival. ICC's precision between readers was adequate but by least significant change would have missed subtle, clinically important changes.

DISCUSSION

Muscle loss during chemotherapy in men predicted mortality in men but not women. Precision is an important metric when measuring body composition.

CONCLUSION

Muscle loss in men during chemotherapy of pancreatic cancer predicts mortality.

Muscle Biomarkers in Colorectal Cancer Outpatients: Agreement Between Computed Tomography, Bioelectrical Impedance Analysis, and Nutritional Ultrasound

BACKGROUND

Muscle quality and mass in cancer patients have prognostic and diagnostic importance.

OBJECTIVES

The objectives are to analyze agreement between gold-standard and bedside techniques for morphofunctional assessment.

METHODS

This cross-sectional study included 156 consecutive colorectal cancer outpatients that underwent computed tomography (CT) scanning at lumbar level 3 (L3), whole-body bioelectrical impedance analysis (BIA), point-of-care nutritional ultrasound® (US), anthropometry, and handgrip strength in the same day. Measured muscle biomarkers were stratified by sex, age, BMI-defined obesity, and malnutrition using Global Leadership in Malnutrition (GLIM) criteria. Whole-body estimations for muscle mass (MM) and fat-free mass were calculated using two different equations in CT (i.e., Shen, and Mourtzakis) and four different equations for BIA (i.e., Janssen, Talluri, Kanellakis, and Kotler). Muscle cross-sectional area at L3 was estimated using the USVALID equation in US. Different cut-off points for muscle atrophy and myosteatosis were applied. Sarcopenia was defined as muscle atrophy plus dynapenia. Intra-technique and inter-technique agreement were analyzed with Pearson, Lin (ρ), and Cohen (k) coefficients, Bland-Altman analyses, and hypothesis tests for measures of central tendency.

RESULTS

Intra-technique agreements on muscular atrophy (CT k = 0.134, BIA k = -0.037, US k = 0.127) and myosteatosis (CT k = 0.122) were low, but intra-technique agreement on sarcopenia in CT was fair (k = 0.394). Inter-technique agreement on muscular atrophy and sarcopenia were low. Neither CT and BIA (ρ = 0.468 to 0.772 depending on equation), nor CT and US (ρ = 0.642), were interchangeable. Amongst the BIA equations, MM by Janssen proved the best, with a 1.5 (3.6) kg bias, (-5.6, 8.6) kg LoA, and 9/156 (5.7%) measurements outside the LoA. Muscle biomarkers in all techniques were worse in aged, female, or malnourished participants. Obesity was associated with higher muscle mass or surface biomarkers in all techniques.

CONCLUSIONS

Bedside techniques adequately detected patterns in skeletal muscle biomarkers, but lacked agreement with a reference technique in the study sample using the current methodology.

Skeletal muscle size and quality in healthy kidney donors, normal range and clinical associations

The gold standard to estimate muscle mass and quality is computed tomography (CT) scan. Lower mass and density (intramuscular fat infiltration) of skeletal muscles are markers of sarcopenia, associated with increased mortality risk, impaired physical function, and poorer prognosis across various populations and medical conditions. We aimed to describe standard reference values in healthy population, prospective kidney donors, and correlate clinical parameters to muscle mass and density. Included in the cohort 384 consecutive kidney donors. Mean age was 44.6 ± 11.5 (range 18.4-74.2), 46% were female and mean BMI was 25.6 ± 3.8 kg/m2. Our quantified reference values for psoas cross -sectional area (CSA) index at L3 level (males/females respectively) were 6.3 ± 1.8 and 4.8 ± 1.9 cm2 /m2, and density was 46.1 ± 5 and 41 ± 5 HU at that level. Older age (standardized beta coefficient - 0.12, p = 0.04), sex (- 0.32, p < 0.001) and BMI (0.17, p = 0.002) were significantly associated with CSA index of psoas at L3. Density, however, was associated with triglycerides level (- 0.21, p < 0.001), in addition to age (- 0.22, p < 0.0001), sex (- 0.27, p < 0.001) and BMI (- 0.1, p = 0.05). Our study validates the normative values of psoas muscle mass and density in healthy individuals and suggests correlations with clinical parameters. We demonstrate the significance of measuring not only the mass of the muscle, but also its density, as it has a valid association with metabolic parameters, including BMI and lipid level, even in healthy individuals and in the normal range of the tests.

Relative muscle indices and healthy reference values for sarcopenia assessment using T10 through L5 computed tomography skeletal muscle area

Sarcopenia is the age-related loss of skeletal muscle mass and function. Computed tomography (CT) assessments of sarcopenia utilize measurements of skeletal muscle cross-sectional area (SMA), radiation attenuation (SMRA), and intramuscular adipose tissue (IMAT). Unadjusted SMA is strongly correlated with both height and body mass index (BMI); therefore, SMA must be adjusted for body size to assess sarcopenic low muscle mass fairly in individuals of different heights and BMI. SMA/height (rather than S M A / h e i g h t 2 ) provides optimal height adjustment, and vertebra-specific relative muscle index (RMI) equations optimally adjust for both height and BMI. Since L3 measurement is not available in all CT scans, sarcopenic low muscle mass may be assessed using other levels. Both a mid-vertebral slice and an inferior slice have been used to define 'L3 SMA', but the effect of vertebral slice location on SMA measurements is unexplored. Healthy reference values for skeletal muscle measures at mid- and inferior vertebra slices between T10 and L5, have not yet been reported. We extracted T10 through L5 SMA, SMRA, and IMAT at a mid-vertebral and inferior slice using non-contrast-enhanced CT scans from healthy, adult kidney donor candidates between age 18 and 73. We compared paired differences in SMA between the mid-vertebral slice versus the inferior slice. We calculated the skeletal muscle gauge as S M G HT = S M R A ∗ S M I HT . We used allometric analysis to find the optimal height scaling power for SMA. To enable comparisons with other published reference cohorts, we computed two height-adjusted measures; S M I HT = S M A / h e i g h t (optimal) and S M I H T 2 = S M A / h e i g h t 2 (traditional). Using the young, healthy reference cohort, we utilized multiple linear regression to calculate relative muscle index z-scores ( R M I HT , R M I H T 2 ), which adjust for both height and BMI, at each vertebra level. We assessed Pearson correlations of each muscle area measure versus age, height, weight, and BMI separately by sex and vertebra number. We assessed the differences in means between age 18-40 versus 20-40 as the healthy, young adult reference group. We reported means, standard deviations, and sarcopenia cutpoints (mean-2SD and 5th percentile) by sex and age group for all measures. Sex-specific allometric analysis showed that height to the power of one was the optimal adjustment for SMA in both men and women at all vertebra levels. Differences between mid-vertebra and inferior slice SMA were statistically significant at each vertebra level, except for T10 in men. S M I HT was uncorrelated with height, whereas S M I H T 2 was negatively correlated with height at all vertebra levels. Both S M I HT and S M I H T 2 were positively correlated with BMI at all vertebra levels. R M I HT was uncorrelated with BMI, weight, and height (minimal positive correlation in women at L3 inf , L4 mid , and L5 inf ) whereas R M I H T 2 was uncorrelated with BMI, but negatively correlated with height and weight at all levels. There were no significant differences in SMA between 18-40 versus 20-40 age groups. Healthy reference values and sarcopenic cutpoints are reported stratified by sex, vertebra level, and age group for each measure. Height to the power of one (SMA/height) is the optimal height adjustment factor for SMA at all levels between T10 mid through L5 inf . The use of S M A / h e i g h t 2 should be discontinued as it retains a significant negative correlation with height and is therefore biased towards identifying sarcopenia in taller individuals. Measurement of SMA at a mid-vertebral slice is significantly different from measurement of SMA at an inferior aspect slice. Reference values should be used for the appropriate slice. We report sarcopenic healthy reference values for skeletal muscle measures at the mid-vertebral and inferior aspect slice for T10 through L5 vertebra levels. Relative muscle index (RMI) equations developed here minimize correlation with both height and BMI, producing unbiased assessments of relative muscle mass across the full range of body sizes. We recommend the use of these RMI equations in other cohorts.

Age-related and cancer-related sarcopenia: is there a difference?

PURPOSE OF REVIEW

The aim of this review is the attempt to differentiating the pathophysiologic and clinical features of the aging-related sarcopenia from cancer-related sarcopenia. In fact, there is some controversy among the experts mainly regarding two points: is always sarcopenia, even that aging-related one, the expression of a generalized disease or may exist independently and without major alteration of the muscle function? Are always aging-related and cancer-related sarcopenia completely separated entities?

RECENT FINDINGS

Literature shows that sarcopenia, defined as simple skeletal muscle mass loss, may range from a mainly focal problem which is common in many healthy elderly people, to a component of a complex multiorgan syndrome as cancer cachexia. Disuse, malnutrition and (neuro)degenerative processes can account for most of the aging-related sarcopenias while systemic inflammation and secretion of cancer-and immune-related molecules play an additional major role in cachexia.

SUMMARY

A multimodal approach including physical exercise and optimized nutritional support are the key measures to offset sarcopenia with some contribution by the anti-inflammatory drugs in cancer patients. Results are more promising in elderly patients and are still pending for cancer patients where a more specific approach will only rely on the identification and contrast of the key mediators of the cachectic process.

A Cross-Sectional Validation of Horos and CoreSlicer Software Programs for Body Composition Analysis in Abdominal Computed Tomography Scans in Colorectal Cancer Patients

BACKGROUND

Body composition assessment using computed tomography (CT) scans may be hampered by software costs. To facilitate its implementation in resource-limited settings, two open-source segmentation programs (Horos and CoreSlicer) were transversally validated in colorectal cancer patients.

METHODS

Contrast-enhanced abdominal CT scans were analyzed following the Alberta protocol. The Cross-Sectional Area (CSA) and intensities of skeletal muscle tissue (MT), subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and intramuscular adipose tissue (IMAT) were measured. The Skeletal Muscle Index (SMI) was calculated. Cutoff points were applied to the SMI, MT intensity, and VAT CSA to define muscle atrophy, myosteatosis, and abdominal obesity. The inter-software agreement was evaluated using different statistical tools.

RESULTS

A total of 68 participants were measured. The MT CSA and SMI displayed no differences. The MT CSA agreement was excellent, and both programs provided equal muscle atrophy prevalences. CoreSlicer underestimated the MT intensity, with a non-significant myosteatosis prevalence increase (+5.88% and +8.82%) using two different operative definitions. CoreSlicer overestimated the CSA and intensity in both VAT and SAT, with a non-significant increase (+2.94%) in the abdominal obesity prevalence.

CONCLUSIONS

Both software programs were feasible tools in the study group. The MT CSA showed great inter-software agreement and no muscle atrophy misdiagnosis. Segmentation differences in the MT intensity and VAT CSA caused limited diagnostic misclassification in the study sample.

The role of the nutrition in malnourished cancer patients: Revisiting an old dilemma

BACKGROUND & AIMS

GLIM definition of malnutrition is recognised all over the world and, when is referring to cancer, it specifies that weight or muscle loss are associated with an inflammatory status. However, the real-world practice shows that GLIM definition cannot encompass all the wide and heterogenous clinical presentations of cancer patients with malnutrition, which involves many other drivers beyond inflammation. Moreover, placing an excessive emphasis on the inflammation can overshadow, in the clinical practice, the role of the nutritional support in malnourished cancer patients. The aim of this paper is not to criticize the rationale of the GLIM definition of cancer cachexia, but to show the complexity and heterogeneity of malnutrition of cancer patients and reasons why nutritional support should deserve such a better consideration among the oncologists.

METHODS

Literature pertinent to pathophysiology of malnutrition of cancer patients is scrutinised and reasons for the frequent underuse of nutritional support are critically analysed.

RESULTS

The appraisal of the literature shows that there are various pathophysiological patterns of malnutrition among cancer patients and inflammatory markers are not universally present in weight-losing cancer patients. Inflammation alone does not account for weight loss in all cancer patients and factors other than inflammation can drive hypophagia and weight loss, and hypophagia appears to be a primary catalyst for weight loss. Furthermore, malnutrition may be the consequence of the presence of several Nutrition Impact Symptoms or of the oncologic therapy. The nutritional support may fail to show benefits in malnourished cancer patients because the golden standard to validate a therapy relies on RCT, but it is ethically impossible to have an unfed control group of malnourished patients. Furthermore, nutritional interventions often fell short of the optimal standards, adherence to treatment plans was often poor, nutritional support was mainly reserved for very advanced patients and the primary endpoints of the studies on nutritional support were sometimes unrealistic.

CONCLUSION

There is a gap between the suggestion of the guidelines which advocate the use of nutritional support to improve the compliance of patients facing intensive oncologic treatments or to prevent an early demise when patients enter a chronic phase of slow nutritional deterioration, and the poor use of nutrition in the real-world practice. This requires a higher level of awareness of the oncologists concerning the reasons for the lacking evidence of efficacy of the nutritional support and an understanding of its potential contribute to improve the outcome of the patients. Finally, this paper calls for a change of the oncologist's approach to the cancer patient, from only focusing on the cure of the tumour to taking care of the patient as a whole.

Quantifying the severity of sarcopenia in patients with cancer of the head and neck

BACKGROUND & AIMS

Existing skeletal muscle index (SMI) thresholds for sarcopenia are inconsistent, and do not reflect severity of depletion. In this study we aimed to define criterion values for moderate and severe skeletal muscle depletion based on the risk of mortality in a population of patients with head and neck cancer (HNC). Additionally, we aimed to identify clinical and demographic predictors of skeletal muscle depletion, evaluate the survival impact of skeletal muscle depletion in patients with minimal nutritional risk or good performance status, and finally, benchmarking SMI values of patients with HNC against healthy young adults.

METHODS

Population cohort of 1231 consecutive patients and external validation cohorts with HNC had lumbar SMI measured by cross-sectional imaging. Optimal stratification determined sex-specific thresholds for 2-levels of SMI depletion (Class I and II) based on overall survival (OS). Adjusted multivariable regression analyses (tumor site, stage, performance status, age, sex, dietary intake, weight loss) determined relationships between 2-levels of SMI depletion and OS.

RESULTS

Mean SMI (cm2/m2) was 51.7 ± 9.9 (males) and 39.8 ± 7.1 (females). The overall and sex-specific population demonstrated an increased risk of mortality associated with decreasing SMI. Sex-specific SMI (cm2/m2) depletion thresholds for 2-levels of muscle depletion determined by optimal stratification for males and females, respectively (male: 45.2-37.5, and <37.5; female: 40.9-34.2, and <34.2). In the overall population, Normal SMI, Class I and II SMI depletion occurred in 65.0%, 24.0%, and 11.0%, respectively. Median OS was: Normal SMI (114 months, 95% CI, 97.1-130.8); Class I SMI Depletion (42 months, 95% CI, 28.5-55.4), and Class II SMI Depletion (15 months, 95% CI, 9.8-20.1). Adjusted multivariable analysis compared with Normal SMI (reference), Class I SMI Depletion (HR, 1.49; 95% CI, 1.18-1.88; P < .001), Class II SMI Depletion (HR, 1.91; 95% CI, 1.42-2.58; P < .001).

CONCLUSIONS

Moderate and severe SMI depletion demonstrate discrimination in OS in patients with HNC. Moderate and severe SMI depletion is prevalent in patients with minimal nutrition risk and good performance status. Benchmarking SMI values against healthy young adults exemplifies the magnitude of SMI depletion in patients with HNC and may be a useful method in standardizing SMI assessment.

Lumbar muscle involvement in the occurrence of osteoporotic vertebral fracture

Objective

To determine if a lumbar musculature deficiency (paravertebral - PVM - and psoas - PM - muscles) is associated with a higher prevalence of vertebral fractures in osteoporotic patients.

Methods

To constitute the fracture group, data were collected retrospectively from patients with one or more recent osteoporotic vertebral fractures between T10 and L5 such as non-injected computerized tomography (CT), dual-energy X-ray absorptiometry (DXA). A control group was made by matching the patients on age, bone mineral density measured by DXA and gender. We analyzed PM and PVM atrophy based on cross-sectional area (CSA) adjusted to the body area as well as fatty infiltration on a 3-level scale and the average muscle density in Hounsfield units (HU).

Results

One hundred seventeen patients were included in each group. The fracture group had a lower PVM CSA than the control group (2197.92 ± 460.19 versus 2335.20 ± 394.42 mm2.m-2, respectively p = 0.015), but there was no significant difference in the PM (746.92 ± 197.89 versus 731.74 ± 215.53 mm2.m-2, respectively p = 0.575). The fracture group had a higher grade of fatty infiltration than the control group (PM: 1.3 ± 0.46 versus 1.07 ± 0.25, p < 0.001; PVM: 1.93 ± 0.5 versus 1.74 ± 0.5, p = 0.003) and a lower average muscle density (PM: 26.99 ± 12.83 versus 33.91 ± 8.12 HU, p < 0.001; PVM: 3.42 ± 21.06 versus 12.94 ± 18.88 HU, p < 0.001).

Conclusion

This study shows an association between a lack of axial musculature and the occurrence of osteoporotic vertebral fractures. Preventive strengthening exercises could be proposed to osteoporotic patients.

Circulating Adipocytokines and Insulin Like-Growth Factors and Their Modulation in Obesity-Associated Endometrial Cancer

The rising global incidence of uterine cancer is linked to the escalating prevalence of obesity. Obesity results in alterations in adipocytokines and IGFs, driving cancer progression via inflammation, increased cell proliferation, and apoptosis inhibition, although the precise mechanisms are still unclear. This study examined a set of six markers, namely, adiponectin, leptin, IL6, TNFα, IGF1, and IGF2 and compared them between fifty age-matched endometrial cancer patients (study group) and non-cancer patients with benign gynaecological conditions (control group). We also assessed the relationship of these markers with obesity and explored the correlation between these markers and various tumour characteristics. In the cancer population, these markers were also assessed 24 h and 6 months post-surgery. Remarkably, low adiponectin levels were associated with a 35.8% increase in endometrial cancer risk. Interestingly, compared to control subjects where IGF levels decreased after menopause, post-menopausal women in the study group showed elevated IGF1 and IGF2 levels, suggesting a potential influence of endometrial cancer on the IGF system, particularly after menopause. Lastly, it is noteworthy that a discernible inverse relationship trend was observed in the levels of adipocytokines and IGFs 6 months post-surgery. This indicates that treatment for endometrial cancer may have a differential impact on adipocytokines and IGFs, potentially holding clinical significance that merits further investigation.

Current Therapeutic Targets in Cancer Cachexia: A Pathophysiologic Approach

Significant progress in our understanding of cancer cachexia has occurred in recent years. Despite these advances, no pharmacologic agent has achieved US Food and Drug Administration approval for this common and highly morbid syndrome. Fortunately, improved understanding of the molecular basis of cancer cachexia has led to novel targeted approaches that are in varying stages of drug development. This article reviews two major thematic areas that are driving these pharmacologic strategies, including those targeting signal mediators at the level of the CNS and skeletal muscle. Additionally, pharmacologic strategies are being tested in combination with targeted nutrients, nutrition therapy, and exercise to treat cancer cachexia. To this end, we highlight recently published and ongoing trials evaluating cancer cachexia therapies in these specific areas.

Adverse effects of systemic cancer therapy on skeletal muscle: myotoxicity comes out of the closet

PURPOSE OF REVIEW

Systemic cancer therapy-associated skeletal muscle wasting is emerging as a powerful impetus to the overall loss of skeletal muscle experienced by patients with cancer. This review explores the clinical magnitude and biological mechanisms of muscle wasting during systemic cancer therapy to illuminate this adverse effect. Emerging strategies for mitigation are also discussed.

RECENT FINDINGS

Clinical findings include precise, specific measures of muscle loss over the course of chemotherapy, targeted therapy and immunotherapy. All these therapeutic classes associate with quantitatively important muscle loss, independent of tumor response. Parallel experimental studies provide understanding of the specific molecular basis of wasting, which can include inhibition of protein synthesis, proliferation and differentiation, and activation of inflammation, reactive oxygen species, autophagy, mitophagy, apoptosis, protein catabolism, fibrosis and steatosis in muscle. Strategies to mitigate these muscle-specific adverse effects of cancer therapy remain in the earliest stages of development.

SUMMARY

The adverse side effect of cancer therapy on skeletal muscle has been largely ignored in the development of cancer therapeutics. Given the extent to which loss of muscle mass and function can bear on patients' function and quality of life, protection/mitigation of these side effects is a research priority.

Reference values for low muscle mass and myosteatosis using tomographic muscle measurements in living kidney donors

Low muscle mass and myosteatosis are associated with poor clinical outcomes. Computed tomography (CT) imaging is an objective method for muscle mass and quality assessment; however consensus on cut-off values is lacking. This study assessed age-, sex-, and body mass index (BMI)-specific reference values of skeletal muscle parameters and correlated muscle mass with 24-h urinary creatinine excretion (24-h UCE). In total, 960 healthy subjects were included in this study. Muscle mass and quality were determined using axial CT slices at the vertebral level L3. The muscle area was indexed for height (skeletal muscle index [SMI]). The mean age was 53 ± 11 years, and 50% were male. The SMI reference values for low muscle mass in males were 38.8 cm²/m² (20-29 years), 39.2 (30-39 years), 39.9 (40-49 years), 39.0 (50-59 years), 37.0 (60-69 years), and 36.8 (70-79 years). For females, these reference values were 37.5 cm²/m² (20-29 years), 35.5 (30-39 years), 32.8 (40-49 years), 33.2 (50-59 years), 31.2 (60-69 years), and 31.5 (70-79 years). 24-h UCE and SMI were significantly correlated (r = 0.54, p < 0.001) without bias between the two methods of assessing muscle mass. This study provides age-, sex-, and BMI-specific reference values for skeletal muscle parameters that will support clinical decision making.

Validation of skeletal muscle mass assessment at the level of the third cervical vertebra in patients with head and neck cancer

BACKGROUND

Low skeletal muscle mass (SMM) is associated with adverse outcomes. SMM is often assessed at the third lumbar vertebra (L3) on abdominal imaging. Abdominal imaging is not routinely performed in patients with head and neck cancer (HNC). We aim to validate SMM measurement at the level of the third cervical vertebra (C3) on head and neck imaging.

MATERIAL AND METHODS

Patients with pre-treatment whole-body computed tomography (CT) between 2010 and 2018 were included. Cross-sectional muscle area (CSMA) was manually delineated at the level of C3 and L3. Correlation coefficients and intraclass correlation coefficients (ICCs) were calculated. Cohen's kappa was used to assess the reliability of identifying a patient with low SMM.

RESULTS

Two hundred patients were included. Correlation between CSMA at the level of C3 and L3 was good (r = 0.75, p < 0.01). Using a multivariate formula to estimate CSMA at L3, including gender, age, and weight, correlation improved (r = 0.82, p < 0.01). The agreement between estimated and actual CSMA at L3 was good (ICC 0.78, p < 0.01). There was moderate agreement in the identification of patients with low SMM based on the estimated lumbar skeletal muscle mass index (LSMI) and actual LSMI (Cohen's κ: 0.57, 95%CI 0.45-0.69).

CONCLUSIONS

CSMA at C3 correlates well with CSMA at L3. There is moderate agreement in the identification of patients with low SMM based on the estimated lumbar SMI (based on measurement at C3) and actual LSMI.

Impact of Body Composition in Overweight and Obese Patients With Localised Renal Cell Carcinoma

BACKGROUND/AIM

To investigate the impact of body composition on morbidity and mortality at the initial diagnosis of localised renal cell carcinoma (RCC) in patients with overweight or obesity.

PATIENTS AND METHODS

Sarcopenia was defined using sex-specific cut-off points and other body composition parameters by median values with computed tomography imaging.

RESULTS

Among the 96 patients, 40 had sarcopenia (43.0%) at diagnosis. Body composition had no effect on morbidity and 5-year disease-free survival contrary to the classic factors (p<0.05). In the subgroup of obese patients, those with sarcopenia had a poor prognosis (p=0.04) but not in the population with overweight (p=0.9).

CONCLUSION

Sarcopenia was frequently associated with localised RCC at the initial diagnosis. Body composition did not affect morbidity or outcomes. BMI was involved in morbidity and there was paradoxically longer survival in the obesity group.

Assessing skeletal muscle radiodensity by computed tomography: An integrative review of the applied methodologies

Low-radiodensity skeletal muscle has been related to the degree of muscle fat infiltration and seems to be associated with worse outcomes. The aim of this study was to summarize the methodologies used to appraise skeletal muscle radiodensity by computed tomography, to describe the terms used in the literature to define muscle radiodensity and to give recommendations for its measurement standardization. An integrative bibliographic review in four databases included studies published until August 2019 in Portuguese, English or Spanish and performed in humans, adults and/or the elderly, of both sex, which investigated skeletal muscle radiodensity through computed tomography (CT) of the region between the third and fifth lumbar vertebrae and evaluated at least two muscular groups. One hundred and seventeen studies were selected. We observed a trend towards selecting all abdominal region muscle. A significant methodological variation in terms of contrast use, selection of skeletal muscle areas, radiodensity ranges delimitation and their cut-off points, as well as the terminologies used, was also found. The methodological differences detected are probably due to the lack of more precise information about the correlation between skeletal muscle radiodensity by CT and its molecular composition, among others. Therefore, until the gaps are addressed in future studies, authors should avoid arbitrary approaches when reporting skeletal muscle radiodensity, especially when it comes to prognosis inference. Studies using both CT and direct methods of muscle composition evaluation are encouraged, to enable the definition and validation of the best approach to classify fat-infiltrated muscle tissue, which will favour the nomenclature uniformization.

Prognostic impact of low muscle mass and low muscle density in patients with diffuse large B-cell lymphoma

Low muscle mass (LMM) and low muscle density (LMD) are increasingly recognized as prognostic factors for survival in different malignancies. This study determined the association of LMM and LMD with survival in DLBCL (diffuse large B-cell lymphoma) patients. CT-based measurement of muscle was performed in 164 DLBCL patients prior to chemo-immunotherapy. Z-scores adjusted for gender, age, and body mass index were derived from a healthy reference population. LMM or LMD were defined as a Z-score below -1 and were related to OS and PFS. The co-existence of both LMM and LMD was observed in 13% of the DLBCL patients and was significantly associated with shorter OS and PFS. Also, these patients more often did not complete the planned treatment. The combination of LMM and LMD is an independent prognostic factor for survival in DLBCL patients. This may guide clinical decision-making in patients with suspected insufficient performance to benefit from chemo-immunotherapy in standard doses.Key pointsPatients with DLBCL have low muscle mass (LMM) and low muscle density (LMD) compared to healthy counterparts.The combination of LMM and LMD is a negative prognostic factor for survival, independent of comorbidities and unfavorable lymphoma characteristics.

Deep learning-based muscle segmentation and quantification at abdominal CT: application to a longitudinal adult screening cohort for sarcopenia assessment

OBJECTIVE

To investigate a fully automated abdominal CT-based muscle tool in a large adult screening population.

METHODS

A fully automated validated muscle segmentation algorithm was applied to 9310 non-contrast CT scans, including a primary screening cohort of 8037 consecutive asymptomatic adults (mean age, 57.1±7.8 years; 3555M/4482F). Sequential follow-up scans were available in a subset of 1171 individuals (mean interval, 5.1 years). Muscle tissue cross-sectional area and attenuation (Hounsfield unit, HU) at the L3 level were assessed, including change over time.

RESULTS

Mean values were significantly higher in males for both muscle area (190.6±33.6 vs 133.3±24.1 cm², p<0.001) and density (34.3±11.1 HU vs 27.3±11.7 HU, p<0.001). Age-related losses were observed, with mean muscle area reduction of -1.5 cm²/year and attenuation reduction of -1.5 HU/year. Overall age-related muscle density (attenuation) loss was steeper than for muscle area for both sexes up to the age of 70 years. Between ages 50 and 70, relative muscle attenuation decreased significantly more in females (-30.6% vs -18.0%, p<0.001), whereas relative rates of muscle area loss were similar (-8%). Between ages 70 and 90, males lost more density (-22.4% vs -7.5%) and area (-13.4% vs -6.9%, p<0.001). Of the 1171 patients with longitudinal follow-up, 1013 (86.5%) showed a decrease in muscle attenuation, 739 (63.1%) showed a decrease in area, and 1119 (95.6%) showed a decrease in at least one of these measures.

CONCLUSION

This fully automated CT muscle tool allows for both individualized and population-based assessment. Such data could be automatically derived at abdominal CT regardless of study indication, allowing for opportunistic sarcopenia detection.

ADVANCES IN KNOWLEDGE

This fully automated tool can be applied to routine abdominal CT scans for prospective or retrospective opportunistic sarcopenia assessment, regardless of the original clinical indication. Mean values were significantly higher in males for both muscle area and muscle density. Overall age-related muscle density (attenuation) loss was steeper than for muscle area for both sexes, and therefore may be a more valuable predictor of adverse outcomes.