The use of alternate vertebral levels to L3 in computed tomography scans for skeletal muscle mass evaluation and sarcopenia assessment in patients with cancer: a systematic review

Variations in vertebral muscle mass and muscle quality in adult patients with different types of cancer

OBJECTIVES

Assessment of malnutrition-related muscle depletion with computed tomography (CT) using skeletal muscle index (SMI) and muscle radiation attenuation (MRA) at the third lumbar vertebra is well validated. However, SMI and MRA values at other vertebral locations and interchangeability as parameters in different types of cancer are less known. We aimed to investigate whether adult patients with different types of cancer show differences in SMI and MRA at all vertebral levels.

METHODS

We retrospectively analyzed CT images from 203 patients:120 with head and neck cancer, esophageal cancer, or lung cancer (HNC/EC/LC) and 83 with melanoma (ME). Univariate and multivariate linear regression analyses determined the association between SMI (cm²/m2) and MRA (Hounsfield units) and cancer type at each vertebral level (significance corrected for multiple tests, P ≤ 0.002). The multivariate analyses included age, sex, cancer stage, comorbidity, CT protocol, and body mass index (BMI) (MRA analyses).

RESULTS

SMI was lower in the HNC/EC/LC group versus the ME group at all vertebral levels, except C4 through C6 in the multivariate analyses. Female sex was associated with lower SMI at almost all levels. MRA was similar at most vertebral levels in both cancer groups but was lower at C1 through C4, T7, and L5 in the multivariate analyses. Use of contrast fluid and BMI were associated with higher MRA at all vertebral levels except T8 to T9 and C1 to C2, respectively.

CONCLUSIONS

SMI, but not MRA, was lower in HNC/EC/LC patients than in ME patients at most vertebral levels. This indicates that low muscle mass presents itself across the various vertebral muscle areas. MRA may less consistently mark muscle depletion in malnourished patients.

Association of head and neck CT-derived sarcopenia with mortality and adverse outcomes: A systematic review

BACKGROUND

There is growing interest in the association of CT-assessed sarcopenia with adverse outcomes in non-oncological settings.

PURPOSE

The aim of this systematic review is to summarize existing literature on the prognostic implications of CT-assessed sarcopenia in non-oncological patients.

MATERIALS AND METHODS

Three independent authors searched Medline/PubMed, Embase and Cochrane Library up to 30 December 2023 for observational studies that reported the presence of sarcopenia defined on CT head and neck in association with mortality estimates and other adverse outcomes, in non-oncological patients. The quality of included studies were assessed using the Quality of Prognostic Studies tool.

RESULTS

Overall, 15 studies (3829 participants) were included. Nine studies were at low risk of bias, and six were at moderate risk of bias. Patient populations included those admitted for trauma or treatment of intracranial aneurysms, ischemic stroke, transient ischemic attack, and intracranial stenosis. Sarcopenia was associated with increased 30-day to 2-year mortality in inpatients and patients undergoing carotid endarterectomy or mechanical thrombectomy for acute ischemic stroke. Sarcopenia was also associated with poorer neurological and functional outcomes, increased likelihood of admission to long-term care facilities, and longer duration of hospital stays. The observed associations of sarcopenia with adverse outcomes remained similar across different imaging modalities and methods for quantifying sarcopenia.

CONCLUSION

CT-assessed sarcopenia was associated with increased mortality and poorer outcomes across diverse patient populations. Measurement and early identification of sarcopenia in vulnerable patients allows for enhanced prognostication, and focused allocation of resources to mitigate adverse outcomes.

Prevalence and Association of Sarcopenia with Mortality in Patients with Head and Neck Cancer: A Systematic Review and Meta-Analysis

BACKGROUND

The objective of this meta-analysis was to assess the association of sarcopenia defined on computed tomography (CT) head and neck with survival in head and neck cancer patients.

METHODS

Following a PROSPERO-registered protocol, two blinded reviewers extracted data and evaluated the quality of the included studies using the Quality In Prognostic Studies (QUIPS) tool, in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The quality of evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) framework. A meta-analysis was conducted using maximally adjusted hazard ratios (HRs) with the random-effects model. Heterogeneity was measured using the I2 statistic and was investigated using meta-regression and subgroup analyses where appropriate.

RESULTS

From 37 studies (11,181 participants), sarcopenia was associated with poorer overall survival (HR 2.11, 95% confidence interval [CI] 1.81-2.45; p < 0.01), disease-free survival (HR 1.76, 95% CI 1.38-2.24; p < 0.01), disease-specific survival (HR 2.65, 95% CI 1.80-3.90; p < 0.01), progression-free survival (HR 2.24, 95% CI 1.21-4.13; p < 0.01) and increased chemotherapy or radiotherapy toxicity (risk ratio 2.28, 95% CI 1.31-3.95; p < 0.01). The observed association between sarcopenia and overall survival remained significant across different locations of cancer, treatment modality, tumor stages and geographical region, and did not differ between univariate and multivariate HRs. Statistically significant correlations were observed between the C3 and L3 cross-sectional area, skeletal muscle mass, and skeletal muscle index.

CONCLUSIONS

Among patients with head and neck cancers, CT-defined sarcopenia was consistently associated with poorer survival and greater toxicity.

Thigh muscle by CT images as a predictor of mortality in patients with newly diagnosed colorectal cancer

This study aimed to evaluate the prognostic value of thigh muscle assessed by CT images to predict overall mortality in patients with colorectal cancer (CRC). This was a multicenter cohort study including adults (≥ 18 years old) newly diagnosed with CRC, who performed a diagnostic computed tomography (CT) exam including thigh regions. CT images were analyzed to evaluate skeletal muscle (SM in cm2), skeletal muscle index (SMI in cm2/m2), and skeletal muscle density (SMD in HU). Muscle abnormalities (low SM, SMI, and SMD) were defined as the values below the median by sex. Kaplan-Meyer curves and hazard ratios (HRs) for low SM, SMI and SMD were evaluated for overall mortality, stratified by sex. A total of 257 patients were included in the final analysis. Patients' mean age was 62.6 ± 12.1 years, and 50.2% (n = 129) were females. In males, low thigh SMI was associated with shorter survival (log-rank P = .02). Furthermore, this low thigh SMI (cm2/m2) was independently associated with higher mortality rates (HR adjusted 2.08, 95% CI 1.03-4.18). Our additional findings demonstrated that low SMD was independently associated with overall mortality among early-stage patients (I-III) (HR adjusted 2.78, 95% CI 1.26-6.15).

The prognostic value of pre-treatment sarcopenia in overall survival in head and neck cancer patients: a systematic review

The aim of this study was to determine the prognostic value of pre-treatment sarcopenia, defined radiologically (cervical (C3) or lumbar (L3) region), in adult head and neck cancer (HNC) patients undergoing treatment with curative intent. A systematic search of the PubMed and Scopus databases was performed up to March 2024. Inclusion criteria were adult patients with locally advanced HNC, sarcopenia defined radiologically at the C3 and/or L3 level, and patients receiving primary treatment with curative intent. Risk of bias was assessed using the ROBINS-I tool non-randomised studies. Thirty studies involving a total of 6924 adult patients with HNC were included in this review. Pre-treatment sarcopenia was significantly associated with worse overall survival outcomes in 26 of the 30 studies (87%), across all treatment modalities with curative intent. The most frequent sex-specific SMI cut-off values were <52.4 cm2/m2 for males and <38.5 cm2/m2 for females. The findings of this review suggest that sarcopenia is a strong prognostic factor of overall survival in HNC patients undergoing primary curative treatment. Sarcopenia evaluation appears to be a good prognostic marker in the HNC population. Future nutritional interventional studies might focus on reversing the muscle loss and improving overall outcomes in identified sarcopenic individuals.

Skeletal muscle estimation: A review of techniques and their applications

Quantifying skeletal muscle size is necessary to identify those at risk for conditions that increase frailty, morbidity, and mortality, as well as decrease quality of life. Although muscle strength, muscle quality, and physical performance have been suggested as important assessments in the screening, prevention, and management of sarcopenic and cachexic individuals, skeletal muscle size is still a critical objective marker. Several techniques exist for estimating skeletal muscle size; however, each technique presents with unique characteristics regarding simplicity/complexity, cost, radiation dose, accessibility, and portability that are important factors for assessors to consider before applying these modalities in practice. This narrative review presents a discussion centred on the theory and applications of current non-invasive techniques for estimating skeletal muscle size in diverse populations. Common instruments for skeletal muscle assessment include imaging techniques such as computed tomography, magnetic resonance imaging, peripheral quantitative computed tomography, dual-energy X-ray absorptiometry, and Brightness-mode ultrasound, and non-imaging techniques like bioelectrical impedance analysis and anthropometry. Skeletal muscle size can be acquired from these methods using whole-body and/or regional assessments, as well as prediction equations. Notable concerns when conducting assessments include the absence of standardised image acquisition/processing protocols and the variation in cut-off thresholds used to define low skeletal muscle size by clinicians and researchers, which could affect the accuracy and prevalence of diagnoses. Given the importance of evaluating skeletal muscle size, it is imperative practitioners are informed of each technique and their respective strengths and weaknesses.

AI-based fully automatic image analysis: Optimal abdominal and thoracic segmentation volumes for estimating total muscle volume on computed tomography scans

Objectives

Evaluation of sarcopenia from computed tomography (CT) is often based on measuring skeletal muscle area on a single transverse slice. Automatic segmentation of muscle volume has a lower variance and may be a better proxy for the total muscle volume than single-slice areas. The aim of the study was to determine which abdominal and thoracic anatomical volumes were best at predicting the total muscle volume.

Methods

A cloud-based artificial intelligence tool (recomia.org) was used to segment all skeletal muscle of the torso of 994 patients who had performed whole-torso CT 2008-2020 for various clinical indications. Linear regression models for several anatomical volumes and single-slice areas were compared with regard to predicting the total torso muscle volume.

Results

The muscle volume from the tip of the coccyx and 25 cm cranially was the best of the abdominal volumes and was significantly better than the L3 slice muscle area (R2 0.935 vs 0.830, P < 0.0001). For thoracic volumes, the muscle volume between the top of the sternum to the lower bound of the Th12 vertebra showed the best correlation with the total volume, significantly better than the Th12 slice muscle area (R2 0.892 vs 0.775, P < 0.0001). Adjusting for body height improved the correlation slightly for all measurements but did not significantly change the ordering.

Conclusions

We identified muscle volumes that can be reliably segmented by automated image analysis which is superior to single slice areas in predicting total muscle volume.

New Perspectives for Estimating Body Composition From Computed Tomography: Clothing Associated Artifacts

As the value of clinical imaging is expanded through retrospective analyses, it is imperative that all efforts are made to optimize validity. Such considerations for retrospective designs should prioritize factors like naturalistic conditions for observations and measurement replicability, while avoiding sample biases and reliance on strict clinical timelines. Valid methodological approaches are immanent for successful translation from retrospective observational designs into prospective pragmatic research with actionable potential. In particular, thousands of studies have sought to associate clinical outcomes to measures of body composition across diverse patient groups. Post-hoc use of computed tomography (CT) to quantify adiposity and lean tissue characteristics has most frequently involved just a single slice at the level of the third lumbar vertebrae (L3). Abundant in statistical significance and inconsistencies alike, such methods have yet to be implemented or deemed valuable for making real-world clinical decisions. We present herein a concerning perspective, for both magnitude and prevalence, of a widely overlooked source of data variability for this methodology: the hinderance of pants and other tightly fit clothing.

Sarcopenia Identification Using Alternative Vertebral Landmarks in Individuals with Lung Cancer

Background

(1)Sarcopenia, or low skeletal mass index (SMI), contributes to higher lung cancer mortality. The SMI at third lumbar vertebrae (L3) is the reference standard for body composition analysis. However, there is a need to explore the validity of alternative landmarks in this population. We compared the agreement of sarcopenia identification at the first lumbar (L1) and second lumbar (L2) to L3 in non-Hispanic Black (NHB) and White (NHW) individuals with lung cancer.

Methods

(2)This retrospective, cross-sectional study included 214 NHB and NHW adults with lung cancer. CT scans were analyzed to calculate the SMI at L1, L2, and L3. T-tests, chi-square, Pearson's correlation, Cohen's kappa, sensitivity, and specificity analysis were used.

Results

(3)Subjects presented with a mean age of 68.4 ± 9.9 years and BMI of 26.3 ± 6.0 kg/m2. Sarcopenia prevalence varied from 19.6% at L1 to 39.7% at L3. Cohen's kappa coefficient was 0.46 for L1 and 0.64 for L2, indicating weak and moderate agreement for the identification of sarcopenia compared to L3.

Conclusions

(4)Sarcopenia prevalence varied greatly depending on the vertebral landmark used for assessment. Using L2 or L1 alone resulted in a 16.8% and 23.8% misclassification of sarcopenia in this cohort of individuals with lung cancer.

Visceral obesity and sarcopenia as predictors of efficacy and hematological toxicity in patients with metastatic breast cancer treated with CDK 4/6 inhibitors

PURPOSE

We aimed to investigate whether visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and skeletal muscle area (SMA) index are predictive for efficacy and hematological toxicity in ER + HER2-metastatic breast cancer (BC) patients who received CDK 4/6 inhibitors.

METHODS

This retrospective cohort study analyzed 52 patients who were treated with CDK 4/6 inhibitors between January 2018 and February 2021. The values of VAT, SAT, SMA indices and hematological parameters were noted before the start, at the third and sixth months of this treatment. The skeletal muscle area (SMA) and adipose tissue measurements were calculated at the level of the third lumbar vertebra. A SMA-index value of <40 cm2/m2 was accepted as the threshold value for sarcopenia.

RESULTS

Patients with sarcopenia had a worse progression-free survival (PFS) compared to patients without sarcopenia (19.6 vs. 9.0 months, p = 0.005). Patients with a high-VAT-index had a better PFS (20.4 vs. 9.3 months, p = 0.033). Only the baseline low-SMA- index (HR: 3.89; 95% CI: 1.35-11.25, p = 0.012) and baseline low-VAT-index (HR: 2.15; 95% CI: 1.02-4.53, p = 0.042) had significantly related to poor PFS in univariate analyses. The low-SMA-index was the only independent factor associated with poor PFS (HR: 3.99; 95% CI: 1.38-11.54, p = 0.011). No relationship was observed between body composition parameters and grade 3-4 hematological toxicity.

CONCLUSION

The present study supported the significance of sarcopenia and low visceral adipose tissue as potential early indicators of poor PFS in patients treated with CDK 4/6 inhibitors.

Feasibility of using cross-sectional area of masticatory muscles to predict sarcopenia in healthy aging subjects

Determination of sarcopenia is crucial in identifying patients at high risk of adverse health outcomes. Recent studies reported a significant decline in masticatory muscle (MM) function in patients with sarcopenia. This study aimed to analyze the cross-sectional area (CSA) of MMs on computed tomography (CT) images and to explore their potential to predict sarcopenia. The study included 149 adult subjects retrospectively (59 males, 90 females, mean age 57.4 ± 14.8 years) who underwent head and neck CT examination for diagnostic purposes. Sarcopenia was diagnosed on CT by measuring CSA of neck muscles at the C3 vertebral level and estimating skeletal muscle index. CSA of MMs (temporal, masseter, medial pterygoid, and lateral pterygoid) were measured bilaterally on reference CT slices. Sarcopenia was diagnosed in 67 (45%) patients. Univariate logistic regression analysis demonstrated a significant association between CSA of all MMs and sarcopenia. In the multivariate logistic regression model, only masseter CSA, lateral pterygoid CSA, age, and gender were marked as predictors of sarcopenia. These parameters were combined in a regression equation, which showed excellent sensitivity and specificity in predicting sarcopenia. The masseter and lateral pterygoid CSA can be used to predict sarcopenia in healthy aging subjects with a high accuracy.

Thoracic skeletal muscle index is effective for CT-defined sarcopenia evaluation in patients with head and neck cancer

PURPOSE

Computed tomography (CT)-defined sarcopenia, as a measurement of low skeletal muscle (SM), is a poor prognostic indicator in patients with head and neck cancer (HNC), independent of weight or nutritional status. We used SM measures at the second thoracic vertebra (T2) to determine T2-SM index (SMI) thresholds for sarcopenia, and investigate the impact of low T2-SMI on overall survival (OS), and weight loss during radiotherapy (RT).

METHODS

Adult patients with newly diagnosed HNC with a diagnostic PET-CT or RT planning CT scan were included. SM was analysed at T2 and a model applied to predict SM at L3. T2-SMI thresholds for sarcopenia were established with predicted measures, stratified by BMI and sex. Impact of sarcopenia and low T2-SMI on OS and weight loss during RT was investigated.

RESULTS

A total of 361 scans were analysed (84% males, 54% oropharynx tumours). Sarcopenia was found in 49%, demonstrating worse OS (p = 0.037). T2-SMI cutoff values were: females-74 cm2/m2 [area under the curve (AUC): 0.89 (95%CI 0.80-0.98)], males (BMI < 25)-63 cm2/m2 [AUC 0.93 (95%CI 0.89-0.96)], males (BMI ≥ 25)-88cm2/m2 [AUC 0.86 (95%CI 0.78-0.93)]. No difference in OS with T2-SMI categories. Lowest T2-SMI quartile of < 63 cm2/m2 demonstrated worse OS (p = 0.017). Weight loss during RT was higher in patients; who were not sarcopenic (6.2% vs 4.9%, p = 0.023); with higher T2-SMI (6.3% vs 4.9%, p = 0.014) and; in the highest quartiles (3.6% vs 5.7% vs 7.2%, p < 0.001).

CONCLUSIONS

These T2-SMI thresholds are effective in assessing CT-defined sarcopenia in HNC. Further assessment of clinical application is warranted.

The association of body composition and outcomes following autologous hematopoietic stem cell transplantation in patients with non-Hodgkin lymphoma

Recently there has been a growing interest in evaluating body composition as a marker for prognosis in cancer patients. The association of body composition parameters and outcomes has not been deeply investigated in patients with autologous hematopoietic stem cell transplantation (HSCT) recipients with non-Hodgkin lymphoma (NHL). We conducted a retrospective cohort study of 264 NHL patients who received autologous HSCT. PreHSCT abdominal CT scans at the levels of L3 were assessed for body composition measures. We evaluated sarcopenia, myosteatosis, high visceral adipose tissue (VAT) and high visceral adipose tissue density (VATD). Using multivariable Cox proportional regression, we analyzed the association of clinical and transplant-related characteristics with overall survival (OS), relapse-free survival (RFS), and non-relapse mortality (NRM). In a multivariate regression model, patients with higher VATD had worse OS (HR 1.78; 95% confidence intervals CI 1.08-2.95, p = 0.02) and worse NRM (HR 2.31 95% CI 1.08-4.95, p = 0.02) than with lower VATD. Patients with lower levels of VAT also had worse RFS (HR 1.49 95% CI 1.03-2.15, p = 0.03). Sarcopenia and myosteatosis were not associated with outcomes. High pre-transplant VATD was associated with lower OS and higher NRM, and low pre-transplant VAT was associated with worse RFS in patients with NHL undergoing autologous HSCT.

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.

Association of sarcopenia with oncologic outcomes of primary treatment among patients with oral cavity cancer: A systematic review and meta-analysis

GOAL

We performed a systematic review of the literature and meta-analysis to determine how radiographic sarcopenia assessment methods and the presence of pre-treatment sarcopenia impact oncologic outcomes in patients with oral cavity cancer.

INTRODUCTION

Pre-treatment sarcopenia has been associated with poor outcomes in many different malignancies, including head and neck cancers. However, the impact sarcopenia has on outcomes for oral cavity cancer patients is not well understood.

RESULTS

Twelve studies met our inclusion criteria, totaling 1007 patients. 359 (36%) of these patients were reported as sarcopenic. The most commonly utilized sarcopenia assessment methods were L3 skeletal muscle index (n = 5) and C3 skeletal muscle index to estimate L3 skeletal muscle index (n = 5). The majority of studies established their sarcopenia cutoffs as the lowest quartile skeletal muscle index in their patient cohorts. Five studies were included in our meta-analysis, totaling 251 sarcopenic and 537 non-sarcopenic patients. Compared to non-sarcopenic patients, sarcopenic patients were found to have significantly poorer overall survival (univariate: HR = 2.24, 95% CI: 1.71-2.93, I2 = 0%; multivariate: HR = 1.93, 95% CI: 1.47-2.52, I2 = 0%) and disease-free survival (univariate: HR = 2.10, 95% CI: 1.50-2.92, I2 = 0%; multivariate: HR = 1.79, 95% CI: 1.29-2.47, I2 = 10%).

CONCLUSIONS

Over one-third of oral cavity cancer patients may present with sarcopenia. Pre-treatment sarcopenia is associated with significantly worse overall and disease-free survival.

Automated temporalis muscle quantification and growth charts for children through adulthood

Lean muscle mass (LMM) is an important aspect of human health. Temporalis muscle thickness is a promising LMM marker but has had limited utility due to its unknown normal growth trajectory and reference ranges and lack of standardized measurement. Here, we develop an automated deep learning pipeline to accurately measure temporalis muscle thickness (iTMT) from routine brain magnetic resonance imaging (MRI). We apply iTMT to 23,876 MRIs of healthy subjects, ages 4 through 35, and generate sex-specific iTMT normal growth charts with percentiles. We find that iTMT was associated with specific physiologic traits, including caloric intake, physical activity, sex hormone levels, and presence of malignancy. We validate iTMT across multiple demographic groups and in children with brain tumors and demonstrate feasibility for individualized longitudinal monitoring. The iTMT pipeline provides unprecedented insights into temporalis muscle growth during human development and enables the use of LMM tracking to inform clinical decision-making.

Computed Tomography-Defined Body Composition as Prognostic Parameter in Acute Mesenteric Ischemia

INTRODUCTION

Body composition comprising low-skeletal muscle mass (LSMM) and subcutaneous and visceral adipose tissue (SAT and VAT) can be assessed by using cross-sectional imaging modalities. Previous analyses suggest that these parameters harbor prognostic relevance in various diseases. Aim of this study was to analyze possible associations of body composition parameters on mortality in patients with clinically suspected acute mesenteric ischemia (AMI).

METHODS

All patients with clinically suspected AMI were retrospectively assessed between 2016 and 2020. Overall, 137 patients (52 female patients, 37.9%) with a median age of 71 years were included in the present analysis. For all patients, the preoperative abdominal computed tomography (CT) was used to calculate LSMM, VAT, and SAT.

RESULTS

Overall, 94 patients (68.6%) of the patient cohort died within 30 days within a median of 2 days, range 1-39 days. Of these, 27 patients (19.7%) died within 24 h. According to the CT, 101 patients (73.7%) were classified as being visceral obese, 102 patients (74.5%) as being sarcopenic, and 69 patients (50.4%) as being sarcopenic obese. Skeletal muscle index (SMI) was lower in non-survivors compared to survivors (37.5 ± 12.4 cm2/m2 vs. 44.1 ± 13.9 cm2/m2, p = 0.01). There were no associations between body composition parameters with mortality in days (SMI r = 0.07, p = 0.48, SAT r = -0.03, p = 0.77, and VAT r = 0.04, p = 0.68, respectively). In Cox regression analysis, a nonsignificant trend for visceral obesity was observed (HR: 0.62, 95% CI: 0.36-1.05, p = 0.07).

CONCLUSION

SMI might be a valuable CT-based parameter, which could help discriminate between survivors and non-survivors. Further studies are needed to elucidate the associations between body composition and survival in patients with AMI.

Deep Learning for Medical Image-Based Cancer Diagnosis

(1) Background: The application of deep learning technology to realize cancer diagnosis based on medical images is one of the research hotspots in the field of artificial intelligence and computer vision. Due to the rapid development of deep learning methods, cancer diagnosis requires very high accuracy and timeliness as well as the inherent particularity and complexity of medical imaging. A comprehensive review of relevant studies is necessary to help readers better understand the current research status and ideas. (2) Methods: Five radiological images, including X-ray, ultrasound (US), computed tomography (CT), magnetic resonance imaging (MRI), positron emission computed tomography (PET), and histopathological images, are reviewed in this paper. The basic architecture of deep learning and classical pretrained models are comprehensively reviewed. In particular, advanced neural networks emerging in recent years, including transfer learning, ensemble learning (EL), graph neural network, and vision transformer (ViT), are introduced. Five overfitting prevention methods are summarized: batch normalization, dropout, weight initialization, and data augmentation. The application of deep learning technology in medical image-based cancer analysis is sorted out. (3) Results: Deep learning has achieved great success in medical image-based cancer diagnosis, showing good results in image classification, image reconstruction, image detection, image segmentation, image registration, and image synthesis. However, the lack of high-quality labeled datasets limits the role of deep learning and faces challenges in rare cancer diagnosis, multi-modal image fusion, model explainability, and generalization. (4) Conclusions: There is a need for more public standard databases for cancer. The pre-training model based on deep neural networks has the potential to be improved, and special attention should be paid to the research of multimodal data fusion and supervised paradigm. Technologies such as ViT, ensemble learning, and few-shot learning will bring surprises to cancer diagnosis based on medical images.

Is the ECOG-PS similar to the sarcopenia status for predicting mortality in older adults with cancer? A prospective cohort study

PURPOSE

Sarcopenia is a muscle dysfunction that increases negative outcomes in patients with cancer. However, its diagnosis remains uncommon in clinical practice. The Eastern Cooperative Oncology Group Performance Status (ECOG-PS) is a questionnaire to assess the functional status, but it is unknown if is comparable with sarcopenia. We aimed at comparing ECOG-PS with sarcopenia to predict 12-month mortality in patients with cancer.

METHODS

Cohort study including older adult patients with cancer in treatment (any stage of the disease or treatment) at a reference hospital for oncological care. Socio-demographic, clinical, and anthropometric data, muscle mass, and physical function variables (handgrip strength [HGS] and gait speed [GS]) were collected. Skeletal muscle quantity and quality were assessed by computed tomography at the L3. Sarcopenia was diagnosed according to the EWGSP2. ECOG-PS and all-cause mortality were evaluated. The Cox proportional hazards model was calculated.

RESULTS

We evaluated 159 patients (69 years old, 55% males). Low performance (ECOG-PS ≥ 2) was found in 23.3%, 35.8% presented sarcopenia, and 22.0% severe sarcopenia. ECOG-PS ≥ 2 was not an independent predictor of mortality. Sarcopenia, severe sarcopenia, and probable sarcopenia has increased by 3.25 (confidence interval, CI 95% 1.55-6.80), 2.64 (CI 95% 1.23-5.67), and 2.81 (CI 95% 1.30-6.07) times the risk of mortality, respectively.

CONCLUSION

Sarcopenia, but not ECOG-PS, was a predictor of mortality. Therefore, ECOG-PS was not similar to sarcopenia to predict mortality in patients with cancer.

The use of the second thoracic vertebral landmark for skeletal muscle assessment and computed tomography-defined sarcopenia evaluation in patients with head and neck cancer

BACKGROUND

The cross-sectional area (CSA) of skeletal muscle (SM) at the third lumbar vertebra (L3) is used to determine computed tomography (CT)-defined sarcopenia. We investigated the feasibility of SM assessment at the second thoracic vertebra (T2) in patients with head and neck cancer (HNC).

METHODS

Diagnostic PET-CT scans were used to develop a prediction model for L3-CSA using T2-CSA. Effectiveness of the model and cancer-specific survival (CSS) were investigated.

RESULTS

Scans of 111 patients (85% male) were evaluated. The predictive formula: L3-CSA (cm² ) = 174.15 + [0.212 × T2-CSA (cm² )] - [40.032 × sex] - [0.928 × age (years)] + [0.285 × weight (kg)] had good correlation r = 0.796, ICC = 0.882 (p < 0.001). SM index (SMI) mean difference (bias) was -3.6% (SD 10.2, 95% CI -8.7% to 1.3%). Sensitivity (82.8%), specificity (78.2%), with moderate agreement (ƙ = 0.540, p < 0.001). Worse 5-year CSS with lower quartile T2-SMI (51%, p = 0.003).

CONCLUSIONS

SM at T2 can be effectively used for CT-defined sarcopenia evaluation in HNC.

Human skeletal muscle-specific atrophy with aging: a comprehensive review

Age-related skeletal muscle atrophy appears to be a muscle group-specific process, yet only a few specific muscles have been investigated and our understanding in this area is limited. This review provides a comprehensive summary of the available information on age-related skeletal muscle atrophy in a muscle-specific manner, nearly half of which comes from the quadriceps. Decline in muscle-specific size over ∼50 yr of aging was determined from 47 cross-sectional studies of 982 young (∼25 yr) and 1,003 old (∼75 yr) individuals and nine muscle groups: elbow extensors (-20%, -0.39%/yr), elbow flexors (-19%, -0.38%/yr), paraspinals (-24%, -0.47%/yr), psoas (-29%, -0.58%/yr), hip adductors (-13%, -0.27%/yr), hamstrings (-19%, -0.39%/yr), quadriceps (-27%, -0.53%/yr), dorsiflexors (-9%, -0.19%/yr), and triceps surae (-14%, -0.28%/yr). Muscle-specific atrophy rate was also determined for each of the subcomponent muscles in the hamstrings, quadriceps, and triceps surae. Of all the muscles included in this review, there was more than a fivefold difference between the least (-6%, -0.13%/yr, soleus) to the most (-33%, -0.66%/yr, rectus femoris) atrophying muscles. Muscle activity level, muscle fiber type, sex, and timeline of the aging process all appeared to have some influence on muscle-specific atrophy. Given the large range of muscle-specific atrophy and the large number of muscles that have not been investigated, more muscle-specific information could expand our understanding of functional deficits that develop with aging and help guide muscle-specific interventions to improve the quality of life of aging women and men.

Investigation of the Trajectory of Muscle and Body Mass as a Prognostic Factor in Patients With Colorectal Cancer: Longitudinal Cohort Study

BACKGROUND

Skeletal muscle and BMI are essential prognostic factors for survival in colorectal cancer (CRC). However, there is a lack of understanding due to scarce studies on the continuous aspects of these variables.

OBJECTIVE

This study aimed to evaluate the prognostic impact of the initial status and trajectories of muscle and BMI on overall survival (OS) and assess whether these 4 profiles within 1 year can represent the profiles 6 years later.

METHODS

We analyzed 4056 newly diagnosed patients with CRC between 2010 to 2020. The volume of the muscle with 5-mm thickness at the third lumbar spine level was measured using a pretrained deep learning algorithm. The skeletal muscle volume index (SMVI) was defined as the muscle volume divided by the square of the height. The correlation between BMI status at the first, third, and sixth years of diagnosis was analyzed and assessed similarly for muscle profiles. Prognostic significances of baseline BMI and SMVI and their 1-year trajectories for OS were evaluated by restricted cubic spline analysis and survival analysis. Patients were categorized based on these 4 dimensions, and prognostic risks were predicted and demonstrated using heat maps.

RESULTS

Trajectories of SMVI were categorized as decreased (812/4056, 20%), steady (2014/4056, 49.7%), or increased (1230/4056, 30.3%). Similarly, BMI trajectories were categorized as decreased (792/4056, 19.5%), steady (2253/4056, 55.5%), or increased (1011/4056, 24.9%). BMI and SMVI values in the first year after diagnosis showed a statistically significant correlation with those in the third and sixth years (P<.001). Restricted cubic spline analysis showed a nonlinear relationship between baseline BMI and SMVI change ratio and OS; BMI, in particular, showed a U-shaped correlation. According to survival analysis, increased BMI (hazard ratio [HR] 0.83; P=.02), high baseline SMVI (HR 0.82; P=.04), and obesity stage 1 (HR 0.80; P=.02) showed a favorable impact, whereas decreased SMVI trajectory (HR 1.31; P=.001), decreased BMI (HR 1.23; P=.02), and initial underweight (HR 1.38; P=.02) or obesity stages 2-3 (HR 1.79; P=.01) were negative prognostic factors for OS. Considered simultaneously, BMI >30 kg/m² with a low SMVI at the time of diagnosis resulted in the highest mortality risk. We observed improved survival in patients with increased muscle mass without BMI loss compared to those with steady muscle mass and BMI.

CONCLUSIONS

Profiles within 1 year of both BMI and muscle were surrogate indicators for predicting the later profiles. Continuous trajectories of body and muscle mass are independent prognostic factors of patients with CRC. An automatic algorithm provides a unique opportunity to conduct longitudinal evaluations of body compositions. Further studies to understand the complicated natural courses of muscularity and adiposity are necessary for clinical application.

Cervical body composition on radiotherapy planning computed tomography scans predicts overall survival in glioblastoma patients

Background and purpose

Glioblastoma (GBM) patients face a strongly unfavorable prognosis despite multimodal therapy regimens. However, individualized mortality prediction remains imprecise. Harnessing routine radiation planning cranial computed tomography (CT) scans, we assessed cervical body composition measures as novel biomarkers for overall survival (OS) in GBM patients.

Materials and methods

We performed threshold-based semi-automated quantification of muscle and subcutaneous fat cross-sectional area (CSA) at the levels of the first and second cervical vertebral body. First, we tested this method's validity by correlating cervical measures to established abdominal body composition in an open-source whole-body CT cohort. We then identified consecutive patients undergoing radiation planning for recent GBM diagnosis at our institution from 2010 to 2020 and quantified cervical body composition on radiation planning CT scans. Finally, we performed univariable and multivariable time-to-event analyses, adjusting for age, sex, body mass index, comorbidities, performance status, extent of surgical resection, extent of tumor at diagnosis, and MGMT methylation.

Results

Cervical body composition measurements were well-correlated with established abdominal markers (Spearman's rho greater than 0.68 in all cases). Subsequently, we included 324 GBM patients in our study cohort (median age 63 years, 60.8% male). 293 (90.4%) patients died during follow-up. Median survival time was 13 months. Patients with below-average muscle CSA or above-average fat CSA demonstrated shorter survival. In multivariable analyses, continuous cervical muscle measurements remained independently associated with OS.

Conclusion

This exploratory study establishes novel cervical body composition measures routinely available on cranial radiation planning CT scans and confirms their association with OS in patients diagnosed with GBM.

Comparison of Skeletal Muscle Changes at Three Vertebral Levels Following Radiotherapy in Patients With Oropharyngeal Carcinoma

Evaluation of skeletal muscle (SM) depletion, or sarcopenia, utilizes the cross-sectional area (CSA) of computed tomography (CT) scans at the lumbar level L3. However, alternate vertebral landmarks are used in patients with head and neck cancer due to scan unavailability. Muscle changes following radiotherapy at cervical (C3) and thoracic (T2) levels were compared to L3 in patients with oropharyngeal carcinoma. Muscle density data were derived retrospectively from diagnostic PET-CT scans at C3, T2 and L3 pretreatment, and up to six months post. CSA changes were compared to L3 in scans of 33 patients (88% male, mean age 61 (SD 8.5) years). On matched pair analysis; mean L3-CSA change -12.1 cm² (SD 9.7, 95%CI -15.5 to -8.6, and p < 0.001), T2-CSA -30.5 cm² (SD 34.8, 95%CI -42.8 to -18.1, and p < 0.001) and C3-CSA +2.1 cm² (SD 4.1, 95%CI 0.63 to 3.5, and p < 0.00). No difference was found in the percentage change of T2-CSA with L3-CSA (mean -2.2%, SD 10.6, 95%CI -6.0 to 1.6, and p = 0.240), however, was significantly different to C3-CSA (mean 13.2%, SD 11.6, 95%CI 9.1 to 17.3, and p < 0.001). Results suggest SM at C3 does not change proportionately and may not be a reliable representation of whole-body SM change over time.

Diagnostic Value of Sarcopenia Computed Tomography Metrics for Older Patients with or without Cancers with Gastrointestinal Disorders

OBJECTIVES

The diagnostic utility of poor body composition measures in sarcopenia remains unclear. We hypothesize that the skeletal muscle gauge [combination of skeletal muscle index (SMI) and skeletal muscle density (SMD); SMG = SMI × SMD] would have significant diagnostic and predictive value in certain muscle regions and populations.

DESIGN

Prospective cross-sectional study.

SETTING AND PARTICIPANTS

We examined inpatients age ≥60 years with or without cancer and with gastrointestinal disorders.

METHODS

We used computed tomography (CT) image metrics in the 12th thoracic (T12), third lumbar (L3), erector spinae muscle (ESM), and psoas muscle (PM) regions to establish correlations with the 2019 Asian Working Group for Sarcopenia Consensus and used receiver operating characteristic area under the curve (AUC) to compare differences between metrics. Associations between CT metrics and mortality were reported as relative risk after adjustments.

RESULTS

We evaluated 385 patients (median age, 69.0 years; 60.8% men) and found consistent trends in cancer (49.6%) and noncancer (50.4%) cohorts. SMG had a stronger correlation with muscle mass than SMD [mean rho: 0.68 (range, 0.59‒0.73) vs 0.39 (range, 0.28‒0.48); all P < .01] in T12, L3, and PM regions and a stronger correlation with muscle function than SMI [mean rho: 0.60 (range, 0.50‒0.77) vs 0.36 (range, 0.22‒0.58); all P < .05] in T12, ESM, and L3 regions. SMG outperformed SMI in diagnostic accuracy in all regions, particularly for L3 (AUC: 0.87‒0.88 vs 0.80‒0.82; both P < .05). PMG (PM gauge) and L3SMG did not differ, whereas EMG (ESM gauge) or T12SMG and L3SMG did (AUC: 0.80‒0.82 vs 0.87‒0.88; all P < .05). L3SMI, L3SMD, T12SMG, EMG, and PMG showed no association with 1-year cancer-related mortality after adjusting for confounders; however, L3SMG [relative risk = 0.92 (0.85‒0.99); P = .023) was.

CONCLUSIONS AND IMPLICATIONS

L3SMG covers all features of sarcopenia with more diagnostic value than other metrics, allowing a complete sarcopenia assessment with CT alone and not just in populations with cancer.

A prediction model for skeletal muscle evaluation and computed tomography-defined sarcopenia diagnosis in a predominantly overweight cohort of patients with head and neck cancer

PURPOSE

This study investigates the feasibility of computed tomography (CT)-defined sarcopenia assessment using a prediction model for estimating the cross-sectional area (CSA) of skeletal muscle (SM) in CT scans at the third lumbar vertebra (L3), using measures at the third cervical level (C3) in a predominantly overweight population with head and neck cancer (HNC).

METHODS

Analysis was conducted on adult patients with newly diagnosed HNC who had a diagnostic positron emission tomography-CT scan. CSA of SM in CT images was measured at L3 and C3 in each patient, and a predictive formula developed using fivefold cross-validation and linear regression modelling. Correlation and agreement between measured CSA at L3 and predicted values were evaluated using intraclass correlation coefficients (ICC) and Bland-Altman plot. The model's ability to identify sarcopenia was investigated using Cohen's Kappa (k).

RESULTS

A total of 109 patient scans were analysed, with 64% of the cohort being overweight or obese. The prediction model demonstrated high level of correlation between measured and predicted CSA measures (ICC 0.954, r = 0.916, p < 0.001), and skeletal muscle index (SMI) (ICC 0.939, r = 0.883, p < 0.001). Bland-Altman plot showed good agreement in SMI, with mean difference (bias) = 0.22% (SD 8.65, 95% CI - 3.35 to 3.79%), limits of agreement (- 16.74 to 17.17%). The model had a sensitivity of 80.0% and specificity of 85.0%, with moderate agreement on sarcopenia diagnosis (k = 0.565, p = 0.004).

CONCLUSION

This model is effective in predicting lumbar SM CSA using measures at C3, and in identifying low SM in a predominately overweight group of patients with HNC.

Prevalence and Impact of Computed Tomography-Defined Sarcopenia on Survival in Patients with Human Papillomavirus-Positive Oropharyngeal Cancer: A Systematic Review

Sarcopenia is a known independent prognostic factor for decreased survival in patients with head and neck cancer; yet, its importance for the growing number of younger patients diagnosed with human papillomavirus (HPV)-positive oropharyngeal carcinoma (OPC+) has not been established. This systematic literature review aimed to determine the prevalence and impact of computed tomography (CT)-defined sarcopenia on survival outcomes for adult OPC+ patients (>18 y) undergoing any treatment modality. Prospective studies were searched using PubMed, Embase, CENTRAL, CINAHL, and Web of Science up until and including February 2022. Bias was assessed using the Quality In Prognosis Studies (QUIPS) tool, and certainty of evidence using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system. In total, 9 studies (total pooled OPC+ patients, n  = 744) were identified and included in this review; 2 at low, 6 at moderate, and 1 at high risk of bias. All studies varied in sarcopenia assessment methods and skeletal muscle index threshold cutoff values. These studies demonstrated the cumulative prevalence of sarcopenia for OPC+ patients to be 42.9% (95% CI: 37.8%, 47.9%). While overall survival (3 studies, n = 253) and progression-free survival (1 study, n = 117) was lower in sarcopenic OPC+ patients, this was not statistically significant. GRADE certainty of evidence for impact of pretreatment sarcopenia on overall survival was low and progression-free survival was very low. Although these studies showed there to be a high prevalence of pretreatment sarcopenia in patients with OPC+, which may decrease survival, the impact on progression-free survival is very uncertain. Further, high-quality research utilizing consistent sarcopenia definitions and assessment methods that are conducted specifically in OPC+ is required to strengthen evidence certainty and determine if sarcopenia is an independent prognostic factor for this population.

Influence of reduced muscle mass and quality on ventilator weaning and complications during intensive care unit stay in COVID-19 patients

BACKGROUND & AIMS

Sarcopenia, a loss of muscle mass, quality and function, which is particularly evident in respiratory muscles, has been associated with many clinical adverse outcomes. In this study, we aimed at evaluating the role of reduced muscle mass and quality in predicting ventilation weaning, complications, length of intensive care unit (ICU) and of hospital stay and mortality in patients admitted to ICU for SARS-CoV-2-related pneumonia.

METHODS

This was an observational study based on a review of medical records of all adult patients admitted to the ICU of a tertiary hospital in Milan and intubated for SARS-CoV-2-related pneumonia during the first wave of the COVID-19 pandemic. Muscle mass and quality measurement were retrieved from routine thoracic CT scans, when sections passing through the first, second or third lumbar vertebra were available.

RESULTS

A total of 81 patients were enrolled. Muscle mass was associated with successful extubation (OR 1.02, 95% C.I. 1.00-1.03, p = 0.017), shorter ICU stay (OR 0.97, 95% C.I. 0.95-0.99, p = 0.03) and decreased hospital mortality (HR 0.98, 95% C.I. 0.96-0.99, p = 0.02). Muscle density was associated with successful extubation (OR 1.07, 95% C.I. 1.01-1.14; p = 0.02) and had an inverse association with the number of complications in ICU (Β -0.07, 95% C.I. -0.13 - -0.002, p = 0.03), length of hospitalization (Β -1.36, 95% C.I. -2.21 - -0.51, p = 0.002) and in-hospital mortality (HR 0.88, 95% C.I. 0.78-0.99, p = 0.046).

CONCLUSIONS

Leveraging routine CT imaging to measure muscle mass and quality might constitute a simple, inexpensive and powerful tool to predict survival and disease course in patients with COVID-19. Preserving muscle mass during hospitalisation might have an adjuvant role in facilitating remission from COVID-19.

Everything You Always Wanted to Know about Sarcopenia but Were Afraid to Ask: A Quick Guide for Radiation Oncologists (Impact of Sarcopenia in Radiotherapy: The AFRAID Project)

Sarcopenia (SP) is a syndrome characterized by age-associated loss of skeletal muscle mass and function. SP worsens both acute and late radiation-induced toxicity, prognosis, and quality of life. Myosteatosis is a pathological infiltration of muscle tissue by adipose tissue which often precedes SP and has a proven correlation with prognosis in cancer patients. Sarcopenic obesity is considered a "hidden form" of SP (due to large fat mass) and is independently related to higher mortality and worse complications after surgery and systemic treatments with worse prognostic impact compared to SP alone. The evaluation of SP is commonly based on CT images at the level of the middle of the third lumbar vertebra. On this scan, all muscle structures are contoured and then the outlined surface area is calculated. Several studies reported a negative impact of SP on overall survival in patients undergoing RT for tumors of the head and neck, esophagus, rectum, pancreas, cervix, and lung. Furthermore, several appetite-reducing side effects of RT, along with more complex radiation-induced mechanisms, can lead to SP through, but not limited to, reduced nutrition. In particular, in pediatric patients, total body irradiation was associated with the onset of SP and other changes in body composition leading to an increased risk of cardiometabolic morbidity in surviving adults. Finally, some preliminary studies showed the possibility of effectively treating SP and preventing the worsening of SP during RT. Future studies should be able to provide information on how to prevent and manage SP before, during, or after RT, in both adult and pediatric patients.

Effect of musculature on mortality, a retrospective cohort study

BACKGROUND

While often life-saving, treatment for head and neck cancer (HNC) can be debilitating resulting in unplanned hospitalization. Hospitalizations in cancer patients may disrupt treatment and result in poor outcomes. Pre-treatment muscle quality and quantity ascertained through diagnostic imaging may help identify patients at high risk of poor outcomes early. The primary objective of this study was to determine if pre-treatment musculature was associated with all-cause mortality.

METHODS

Patient demographic and clinical characteristics were abstracted from the cancer center electronic database (n = 403). Musculature was ascertained from pre-treatment CT scans. Propensity score matching was utilized to adjust for confounding bias when comparing patients with and without myosteatosis and with and without low muscle mass (LMM). Overall survival (OS) was evaluated using the Kaplan-Meier method and Cox multivariable analysis.

RESULTS

A majority of patients were male (81.6%), white (89.6%), with stage IV (41.2%) oropharyngeal cancer (51.1%) treated with definitive radiation and chemotherapy (93.3%). Patients with myosteatosis and those with LMM were more likely to die compared to those with normal musculature (5-yr OS HR 1.55; 95% CI 1.03-2.34; HR 1.58; 95% CI 1.04-2.38).

CONCLUSIONS

Musculature at the time of diagnosis was associated with overall mortality. Diagnostic imaging could be utilized to aid in assessing candidates for interventions targeted at maintaining and increasing muscle reserves.

Role of visceral fat areas defined by thoracic CT in acute pulmonary embolism

OBJECTIVE

Visceral adipose tissue (VAT) has been established as an important parameter of body composition. It can be assessed by imaging modalities like computed tomography (CT). The purpose of the present study was to analyse the prognostic role of VAT derived from thoracic CT in patients with acute pulmonary embolism (PE).

METHODS

The clinical database of our center was retrospectively screened for patients with acute PE between 2014 and 2017. Overall, 184 patients were included into the analysis. VAT was assessed on axial slices of the thoracic CT at the level of the first lumbar vertebra. Clinical scores, serological parameters, need for intubation, ICU admission and 30 days mortality were assessed.

RESULTS

Using the previously reported threshold of 100 cm² for visceral obesity definition 136 (73.9%), patients were considered as visceral obese. There was a moderate correlation between VAT and BMI (r = 0.56, p < 0.0001). There was also a moderate correlation between VAT and body height (r = 0.41, p =< 0.0001). Of all investigated clinical scores relating to acute PE, only the GENEVA score correlated weakly with VAT (r = 0.15, p = 0.04). There were significant correlations between VAT and creatinine (r = 0.38, p < 0.0001) and Glomerular filtration rate (r = -0.21, p = 0.005). No associations were identified for VAT and mortality or visceral obesity and mortality.

CONCLUSION

VAT was not associated with mortality in patients with acute pulmonary embolism.

ADVANCES IN KNOWLEDGE

Visceral obesity is frequent in patients with acute pulmonary embolism but it is not associated with mortality.

Measurement of Sarcopenia in Head and Neck Cancer Patients and Its Association With Frailty

In head and neck cancer (HNC) there is a need for more personalized treatment based on risk assessment for treatment related adverse events (i.e. toxicities and complications), expected survival and quality of life. Sarcopenia, defined as a condition characterized by loss of skeletal muscle mass and function, can predict adverse outcomes in HNC patients. A review of the literature on the measurement of sarcopenia in head and neck cancer patients and its association with frailty was performed. Skeletal muscle mass (SMM) measurement only is often used to determine if sarcopenia is present or not. SMM is most often assessed by measuring skeletal muscle cross-sectional area on CT or MRI at the level of the third lumbar vertebra. As abdominal scans are not always available in HNC patients, measurement of SMM at the third cervical vertebra has been developed and is frequently used. Frailty is often defined as an age-related cumulative decline across multiple physiologic systems, with impaired homeostatic reserve and a reduced capacity of the organism to withstand stress, leading to increased risk of adverse health outcomes. There is no international standard measure of frailty and there are multiple measures of frailty. Both sarcopenia and frailty can predict adverse outcomes and can be used to identify vulnerable patients, select treatment options, adjust treatments, improve patient counselling, improve preoperative nutritional status and anticipate early on complications, length of hospital stay and discharge. Depending on the definitions used for sarcopenia and frailty, there is more or less overlap between both conditions. However, it has yet to be determined if sarcopenia and frailty can be used interchangeably or that they have additional value and should be used in combination to optimize individualized treatment in HNC patients.

Preoperative Pectoralis Muscle Index Predicts Distant Metastasis-Free Survival in Breast Cancer Patients

Background

Breast cancer is one of the most commonly diagnosed cancers, and the fourth leading cause of cancer deaths in females worldwide. Sarcopenia is related to adverse clinical outcomes in patients with malignancies. Muscle index is a key parameter in evaluating sarcopenia. However, there is no data investigating the association between muscle index and distant metastasis in breast cancer. The aim of this study was to explore whether muscle index can effectively predict distant metastasis and death outcomes in breast cancer patients.

Study Design

The clinical data of 493 breast cancer patients at the Harbin Medical University Cancer Hospital between January 2014 and December 2015 were retrospectively analyzed. Quantitative measurements of pectoralis muscle area and skeletal muscle area were performed at the level of the fourth thoracic vertebra (T4) and the eleventh thoracic vertebra (T11) of the chest computed tomography image, respectively. The pectoralis muscle index (PMI) and skeletal muscle index (SMI) were assessed by the normalized muscle area (area/the square of height). Survival analysis was performed using the log-rank test and Cox proportional hazards regression analysis.

Result

The patients with metastases had lower PMI at T4 level (PMI/T4) and SMI at T11 level (SMI/T11) compared with the patients without metastases. Moreover, there were significant correlations between PMI/T4 and lymphovascular invasion, Ki67 expression, multifocal disease, and molecular subtype. In addition, multivariate analysis revealed that PMI/T4, not SMI/T11, was an independent prognostic factor for distant metastasis-free survival (DMFS) and overall survival (OS) in breast cancer patients.

Conclusions

Low PMI/T4 is associated with worse DMFS and OS in breast cancer patients. Future prospective studies are needed.

The Value of Artificial Intelligence-Assisted Imaging in Identifying Diagnostic Markers of Sarcopenia in Patients with Cancer

Sarcopenia is defined as the loss of skeletal muscle mass and muscle function. It is common in patients with malignancies and often associated with adverse clinical outcomes. The presence of sarcopenia in patients with cancer is determined by body composition, and recently, radiologic technology for the accurate estimation of body composition is under development. Artificial intelligence- (AI-) assisted image measurement facilitates the detection of sarcopenia in clinical practice. Sarcopenia is a prognostic factor for patients with cancer, and confirming its presence helps to recognize those patients at the greatest risk, which provides a guide for designing individualized cancer treatments. In this review, we examine the recent literature (2017-2021) on AI-assisted image assessment of body composition and sarcopenia, seeking to synthesize current information on the mechanism and the importance of sarcopenia, its diagnostic image markers, and the interventions for sarcopenia in the medical care of patients with cancer. We concluded that AI-assisted image analysis is a reliable automatic technique for segmentation of abdominal adipose tissue. It has the potential to improve diagnosis of sarcopenia and facilitates identification of oncology patients at the greatest risk, supporting individualized prevention planning and treatment evaluation. The capability of AI approaches in analyzing series of big data and extracting features beyond manual skills would no doubt progressively provide impactful information and greatly refine the standard for assessing sarcopenia risk in patients with cancer.

Interconnection between Cardiac Cachexia and Heart Failure—Protective Role of Cardiac Obesity

Cachexia may be caused by congestive heart failure, and it is then called cardiac cachexia, which leads to increased morbidity and mortality. Cardiac cachexia also worsens skeletal muscle degradation. Cardiac cachexia is the loss of edema-free muscle mass with or without affecting fat tissue. It is mainly caused by a loss of balance between protein synthesis and degradation, or it may result from intestinal malabsorption. The loss of balance in protein synthesis and degradation may be the consequence of altered endocrine mediators such as insulin, insulin-like growth factor 1, leptin, ghrelin, melanocortin, growth hormone and neuropeptide Y. In contrast to many other health problems, fat accumulation in the heart is protective in this condition. Fat in the heart can be divided into epicardial, myocardial and cardiac steatosis. In this review, we describe and discuss these topics, pointing out the interconnection between heart failure and cardiac cachexia and the protective role of cardiac obesity. We also set the basis for possible screening methods that may allow for a timely diagnosis of cardiac cachexia, since there is still no cure for this condition. Several therapeutic procedures are discussed including exercise, nutritional proposals, myostatin antibodies, ghrelin, anabolic steroids, anti-inflammatory substances, beta-adrenergic agonists, medroxyprogesterone acetate, megestrol acetate, cannabinoids, statins, thalidomide, proteasome inhibitors and pentoxifylline. However, to this date, there is no cure for cachexia.

Older cancer patients receiving radiotherapy: a systematic review for the role of sarcopenia in treatment outcomes

BACKGROUND

Previous studies have evaluated the prognostic effects of sarcopenia in cancer patients receiving various treatments, including chemotherapy and surgery, but few studies have focused on radiotherapy (RT).

AIMS

We aimed to investigate the prevalence of sarcopenia and the relationship between sarcopenia and outcomes in older cancer patients who underwent RT without chemotherapy.

METHODS

A systematic review of the literature was conducted in Pubmed/Medline and Cochrane databases in September 2021. We used the search terms and medical subject heading terms "sarcopenia," "low muscle mass (LMM)," "low muscle strength," "LMM and low muscle strength," "LMM and low muscle strength and low physical performance," and "RT." Outcomes were overall survival (OS), progression-free survival, non-cancer death, cancer death, disease-specific survival, local failure-free survival, distant failure-free survival, and RT-related toxicities.

RESULTS

Among 460 studies, 8 studies were eligible for inclusion. The prevalence of sarcopenia was between 42.8% and 72%. Sarcopenia was not associated with OS or OS at 3 years in seven studies in which it was defined as the presence of LMM, while it was related in one study, in which it was defined as the concomitant presence of LMM and muscle strength/function.

DISCUSSION

There was heterogeneity between the studies because there was diversity in their inclusion criteria, definition and assessment methods used for detection of sarcopenia, considered cutoffs for low muscle mass and strength, cross-sectional locations on imaging to assess muscle mass and included covariates. The discrepancy in the results of the studies may also result from the variations in diagnoses, sample sizes, and treatment modalities. The low number of included studies and a small number of patients in each study limited generalizability.

CONCLUSIONS

Sarcopenia may be a prognostic factor, especially in OS when low muscle strength/function is integrated into its definition. We suggest that clinicians focus on muscle strength/function while considering sarcopenia and its association with cancer and RT-related outcomes.

The effectiveness of skeletal muscle evaluation at the third cervical vertebral level for computed tomography-defined sarcopenia assessment in patients with head and neck cancer

Background

Computed tomography (CT)‐defined sarcopenia is a prognostic indicator in head and neck cancer (HNC), with the gold standard for muscle evaluation using cross‐sectional area (CSA) at the third lumbar vertebra (L3). We compared methods using CSA at the third cervical vertebra (C3).

Methods

Muscle CSA was measured at L3, and CSA at C3 was used to estimate L3 CSA using a prediction model. Agreement and sarcopenia diagnosis were evaluated.

Results

Good correlation was found between measured and estimated CSA (101 scans; r = 0.86, p < 0.001). CSA mean difference (bias) 9.99 cm², (SD = 20.3 cm²). Skeletal muscle index bias 5.85% (SD = 13.4%), 95% limits of agreement (LoA) (−20.4 to 32.1%, r = 0.29), exceeded clinically accepted limits of 5%. Sarcopenia was diagnosed in 26%‐(L3), 45%‐(C3), with weak agreement (ƙ = 0.368, 95% confidence interval, 0.192–0.544, p < 0.001) (sensitivity 79.2%, specificity 66.7%).

Conclusion

Agreement between measures was weak. Widespread LoA, proportional bias, and sarcopenia misclassification indicates that estimates using C3 cannot replace actual measures at L3.

Evaluation of a novel pre-treatment model of nutrition care for patients with head and neck cancer receiving chemoradiotherapy

AIMS

Weight loss and malnutrition occur frequently in patients with head and neck cancer and are associated with reduced survival. This pragmatic study aimed to determine the effect of a novel pre-treatment model of nutrition care on nutrition outcomes for patients with head and neck cancer receiving chemoradiotherapy.

METHODS

This health service evaluation consisted of an evaluation of the new model of care implementation (Phase 1) and an evaluation of patient outcomes (Phase 2) in pre- and post-implementation cohorts (n = 64 and n = 47, respectively). All Phase 2 patients received a prophylactic gastrostomy. The new model of care consisted of dietary counselling and commencement of proactive supplementary enteral nutrition via a prophylactic gastrostomy, in addition to normal oral intake, prior to treatment commencement. Nutrition outcomes were collected at baseline (pre-treatment) and 3 months post-radiotherapy completion.

RESULTS

The new model of care was successfully incorporated into practice with high referral (96.5%) and attendance (91.5%) rates to the counselling session, and high adherence rates to proactive tube feeding (80.9%). Patients in the post-implementation cohort had less weight-loss (1.2%; p = 0.338) and saw less of a decline in nutritional status compared to patients in the pre-implementation cohort (23% vs. 30%, respectively; p = 0.572), deemed clinically important. However, patients still experienced critical weight loss overall (mean 9.9%).

CONCLUSION

Pre-treatment nutrition care was feasible in standard clinical practice and demonstrated clinically relevant outcome improvements for patients. Future high-quality research is warranted to investigate further multidisciplinary strategies to attenuate weight-loss further, inclusive of patient-reported barriers and enablers to nutrition interventions.