Pectoralis muscle area measured at T4 level is closely associated with adverse COVID-19 outcomes in hospitalized patients.

OBJECTIVES: Skeletal muscle area (SMA) at T4 level on chest computed tomography (CT) is a newly available method that can be used as a surrogate sarcopenia marker. The objective of this study is to evaluate association of SMA with adverse COVID-19 outcomes in hospitalized patients. METHODS: Hospitalized COVID-19 patients were prospectively recorded in a database containing age, gender, date of admission, date of outcome (discharge, mortality, presence of intensive care unit (ICU) stay, additional coding information (comorbidities, superimposed conditions). Admission CT-scans were retrospectively evaluated for segmentation (bilateral pectoralis major/minor, erector spinae, levator scapulae, rhomboideus minor and major and transversospinalis muscles) and SMA calculation using 3-D slicer software. RESULTS: 167 cases were evaluated (68 male, 72 female, 140 survived, 27 dead). Muscle area was lower in patients with ICU stay (p=0.023, p=0.018, p=0.008) and mortality outcome (p=0.004, p=0.007, p=0.002) for pectoralis, back and SMA. In multivariate Cox-regression analysis, hazard ratio (HR) value for the pectoralis muscle area value below 2800 mm2 was found to be 3.138(95% CI: 1.171-8.413) for mortality and 2.361(95% CI: 1.012-5.505) for ICU. CONCLUSIONS: Pectoralis muscle area measured at T4 level with 3-D slicer was closely associated with adverse outcomes (mortality, ICU stay) in hospitalized COVID-19 patients. Since early treatment methods for COVID-19 are being evaluated, this method may be a useful adjunct to clinical decision making in regard to prioritization.

Sarcopenia - Definition, Radiological Diagnosis, Clinical Significance. / Sarkopenie ­ Definition, radiologische Erfassung, klinische Bedeutung.

BACKGROUND: Sarcopenia is an age-related syndrome characterized by a loss of muscle mass and strength. As a result, the independence of the elderly is reduced and the hospitalization rate and mortality increase. The onset of sarcopenia often begins in middle age due to an unbalanced diet or malnutrition in association with a lack of physical activity. This effect is intensified by concomitant diseases such as obesity or metabolic diseases including diabetes mellitus. METHOD: With effective preventative diagnostic procedures and specific therapeutic treatment of sarcopenia, the negative effects on the individual can be reduced and the negative impact on health as well as socioeconomic effects can be prevented. Various diagnostic options are available for this purpose. In addition to basic clinical methods such as measuring muscle strength, sarcopenia can also be detected using imaging techniques like dual X-ray absorptiometry (DXA), computed tomography (CT), magnetic resonance imaging (MRI), and sonography. DXA, as a simple and cost-effective method, offers a low-dose option for assessing body composition. With cross-sectional imaging techniques such as CT and MRI, further diagnostic possibilities are available, including MR spectroscopy (MRS) for noninvasive molecular analysis of muscle tissue. CT can also be used in the context of examinations performed for other indications to acquire additional parameters of the skeletal muscles (opportunistic secondary use of CT data), such as abdominal muscle mass (total abdominal muscle area - TAMA) or the psoas as well as the pectoralis muscle index. The importance of sarcopenia is already well studied for patients with various tumor entities and also infections such as SARS-COV2. RESULTS AND CONCLUSION: Sarcopenia will become increasingly important, not least due to demographic changes in the population. In this review, the possibilities for the diagnosis of sarcopenia, the clinical significance, and therapeutic options are described. In particular, CT examinations, which are repeatedly performed on tumor patients, can be used for diagnostics. This opportunistic use can be supported by the use of artificial intelligence. KEY POINTS: · Sarcopenia is an age-related syndrome with loss of muscle mass and strength.. · Early detection and therapy can prevent negative effects of sarcopenia.. · In addition to DEXA, cross-sectional imaging techniques (CT, MRI) are available for diagnostic purposes.. · The use of artificial intelligence (AI) offers further possibilities in sarcopenia diagnostics.. CITATION FORMAT: · Vogele D, Otto S, Sollmann N et al. Sarcopenia - Definition, Radiological Diagnosis, Clinical Significance. Fortschr Röntgenstr 2023; 195: 393 - 405.

Mapping peripheral and abdominal sarcopenia acquired in the acute phase of COVID-19 during 7 days of mechanical ventilation.

Our aim was to map acquired peripheral and abdominal sarcopenia in mechanically ventilated adults with COVID-19 through ultrasound measurements. On Days 1, 3, 5 and 7 after admission to critical care, the muscle thickness and cross-sectional area of the quadriceps, rectus femoris, vastus intermedius, tibialis anterior, medial and lateral gastrocnemius, deltoid, biceps brachii, rectus abdominis, internal and external oblique, and transversus abdominis were measured using bedside ultrasound. A total of 5460 ultrasound images were analyzed from 30 patients (age: 59.8 ± 15.6 years; 70% men). Muscle thickness loss was found in the bilateral anterior tibial and medial gastrocnemius muscles (range 11.5-14.6%) between Days 1 and 3; in the bilateral quadriceps, rectus femoris, lateral gastrocnemius, deltoid, and biceps brachii (range 16.3-39.1%) between Days 1 and 5; in the internal oblique abdominal (25.9%) between Days 1 and 5; and in the rectus and transversus abdominis (29%) between Days 1 and 7. The cross-sectional area was reduced in the bilateral tibialis anterior and left biceps brachii (range 24.6-25.6%) between Days 1 and 5 and in the bilateral rectus femoris and right biceps brachii (range 22.9-27.7%) between Days 1 and 7. These findings indicate that the peripheral and abdominal muscle loss is progressive during the first week of mechanical ventilation and is significantly higher in the lower limbs, left quadriceps and right rectus femoris muscles in critically ill patients with COVID-19.

Predictors of Sarcopenia in Outpatients with Post-Critical SARS-CoV2 Disease. Nutritional Ultrasound of Rectus Femoris Muscle, a Potential Tool.

Background and Objectives: The loss of muscle mass in post-critical COVID-19 outpatients is difficult to assess due to the limitations of techniques and the high prevalence of obesity. Ultrasound is an emerging technique for evaluating body composition. The aim is to evaluate sarcopenia and its risk factors, determining ultrasound usefulness as a potential tool for this purpose according to established techniques, such as the bioimpedance vector analysis (BIVA), handgrip strength, and timed up-and-go test. Methods: This is a transversal study of 30 post-critical COVID-19 outpatients. We evaluated nutritional status by ultrasound (Rectus Femoris-cross-sectional-area (RF-CSA), thickness, and subcutaneous-adipose-tissue), BIVA, handgrip strength, timed up-and-go test, and clinical variables during admission. Results: According to The European Society for Clinical Nutrition and Metabolism and the European Association for the Study of Obesity (ESPEN&EASO) Consensus for Sarcopenic and Obesity, in terms of excess fat mass and decreased lean mass, the prevalence of class-1 sarcopenic obesity was 23.4% (n = 7), and class-2 sarcopenic obesity was 33.3% (n = 10) in our study. A total of 46.7% (n = 14) of patients had a handgrip strength below the 10th percentile, and 30% (n = 9) achieved a time greater than 10s in the timed up-and-go test. There were strong correlations between the different techniques that evaluated the morphological (BIVA, Ultrasound) and functional measurements of muscle. Intensive care unit stay, mechanical ventilation, and age all conditioned the presence of sarcopenia in COVID-19 outpatients (R2 = 0.488, p = 0.002). Predictive models for sarcopenic diagnosis based on a skeletal muscle index estimation were established by RF-CSA (R2 0.792, standard error of estimate (SEE) 1.10, p < 0.001), muscle-thickness (R2 0.774, SEE 1.14, p < 0.001), and handgrip strength (R2 0.856, SEE 0.92, p < 0.001). RF-CSA/weight of 5.3 cm2/kg × 100 was the cut-off value for predicting sarcopenia in post-critical COVID-19 outpatients, with 88.2 sensitivity and 69.2% specificity. Conclusion: More than half of the post-critical COVID-19 survivors had sarcopenic obesity and functional impairment of handgrip strength. Intensive care unit stay, age, and mechanical ventilation all predict sarcopenia. An ultrasound, when applied to the assessment of body composition in post-critical COVID-19 patients, provided the possibility of assessing sarcopenia in this population.

Biomarkers extracted by fully automated body composition analysis from chest CT correlate with SARS-CoV-2 outcome severity.

The complex process of manual biomarker extraction from body composition analysis (BCA) has far restricted the analysis of SARS-CoV-2 outcomes to small patient cohorts and a limited number of tissue types. We investigate the association of two BCA-based biomarkers with the development of severe SARS-CoV-2 infections for 918 patients (354 female, 564 male) regarding disease severity and mortality (186 deceased). Multiple tissues, such as muscle, bone, or adipose tissue are used and acquired with a deep-learning-based, fully-automated BCA from computed tomography images of the chest. The BCA features and markers were univariately analyzed with a Shapiro-Wilk and two-sided Mann-Whitney-U test. In a multivariate approach, obtained markers were adjusted by a defined set of laboratory parameters promoted by other studies. Subsequently, the relationship between the markers and two endpoints, namely severity and mortality, was investigated with regard to statistical significance. The univariate approach showed that the muscle volume was significant for female (pseverity ≤ 0.001, pmortality ≤ 0.0001) and male patients (pseverity = 0.018, pmortality ≤ 0.0001) regarding the severity and mortality endpoints. For male patients, the intra- and intermuscular adipose tissue (IMAT) (p ≤ 0.0001), epicardial adipose tissue (EAT) (p ≤ 0.001) and pericardial adipose tissue (PAT) (p ≤ 0.0001) were significant regarding the severity outcome. With the mortality outcome, muscle (p ≤ 0.0001), IMAT (p ≤ 0.001), EAT (p = 0.011) and PAT (p = 0.003) remained significant. For female patients, bone (p ≤ 0.001), IMAT (p = 0.032) and PAT (p = 0.047) were significant in univariate analyses regarding the severity and bone (p = 0.005) regarding the mortality. Furthermore, the defined sarcopenia marker (p ≤ 0.0001, for female and male) was significant for both endpoints. The cardiac marker was significant for severity (pfemale = 0.014, pmale ≤ 0.0001) and for mortality (pfemale ≤ 0.0001, pmale ≤ 0.0001) endpoint for both genders. The multivariate logistic regression showed that the sarcopenia marker was significant (pseverity = 0.006, pmortality = 0.002) for both endpoints (ORseverity = 0.42, 95% CIseverity: 0.23-0.78, ORmortality = 0.34, 95% CImortality: 0.17-0.67). The cardiac marker showed significance (p = 0.018) only for the severity endpoint (OR = 1.42, 95% CI 1.06-1.90). The association between BCA-based sarcopenia and cardiac biomarkers and disease severity and mortality suggests that these biomarkers can contribute to the risk stratification of SARS-CoV-2 patients. Patients with a higher cardiac marker and a lower sarcopenia marker are at risk for a severe course or death. Whether those biomarkers hold similar importance for other pneumonia-related diseases requires further investigation.

Prediction of abdominal CT body composition parameters by thoracic measurements as a new approach to detect sarcopenia in a COVID-19 cohort.

As most COVID-19 patients only receive thoracic CT scans, but body composition, which is relevant to detect sarcopenia, is determined in abdominal scans, this study aimed to investigate the relationship between thoracic and abdominal CT body composition parameters in a cohort of COVID-19 patients. This retrospective study included n = 46 SARS-CoV-2-positive patients who received CT scans of the thorax and abdomen due to severe disease progression. The subcutaneous fat area (SF), the skeletal muscle area (SMA), and the muscle radiodensity attenuation (MRA) were measured at the level of the twelfth thoracic (T12) and the third lumbar (L3) vertebra. Necessity of invasive mechanical ventilation (IMV), length of stay, or time to death (TTD) were noted. For statistics correlation, multivariable linear, logistic, and Cox regression analyses were employed. Correlation was excellent for the SF (r = 0.96) between T12 and L3, and good for the respective SMA (r = 0.80) and MRA (r = 0.82) values. With adjustment (adj.) for sex, age, and body-mass-index the variability of SF (adj. r2 = 0.93; adj. mean difference = 1.24 [95% confidence interval (95% CI) 1.02-1.45]), of the SMA (adj. r2 = 0.76; 2.59 [95% CI 1.92-3.26]), and of the MRA (adj. r2 = 0.67; 0.67 [95% CI 0.45-0.88]) at L3 was well explained by the respective values at T12. There was no relevant influence of the SF, MRA, or SMA on the clinical outcome. If only thoracic CT scans are available, CT body composition values at T12 can be used to predict abdominal fat and muscle parameters, by which sarcopenia and obesity can be assessed.

Sarcopenia and Its Prognostic Role on Hospitalization and In-Hospital Mortality in Coronavirus Disease 2019 Patients with At Least One Cardiovascular Risk Factor.

BACKGROUND: The coronavirus disease 2019 infection is a global pandemic that has affected the whole world population. We aimed to evaluate the prognostic role of cross-sectional area, muscle index, and muscle attenuation values in computed tomography-based skeletal groups [erector spinae muscle, pectoralis muscle, and total skeletal muscle] of patients hospitalized for coronavirus disease 2019 and with at least 1 cardiovascular risk factor. METHODS: A total of 232 patients with coronavirus disease 2019 and at least 1 cardiovascular risk factor were enrolled in the study, retrospectively. The cross-sectional area, muscle index, and attenuation of erector spine muscle, pectoralis muscle, and total skeletal muscle were automatically measured on computed tomography images. The study population was assigned into tertiles on the basis of the total SMcsa index. The relationship between the values obtained and the length of hospital stay, admission to intensive care unit, the need for invasive mechani cal ventilation, and mortality was investigated. RESULTS: Admission to intensive care unit, need for invasive mechanical ventilation, and mor tality were higher at tertile 3 groups than in the other groups (all P values <.001). Statistically, all muscle measurements were significantly lower in tertile 3 (P <.001). Diabetes mellitus, hypertension, and total SMcsa index were predictors of in-hospital mortality in patients with coronavirus disease 2019 on the basis of Cox regression analysis. In the Kaplan-Meier analysis for the proportion of survivors relative to the total SMcsa index, tertile 3 had the highest mortal ity (survival rates 57%, P < .001). CONCLUSIONS: Sarcopenia and attendant cardiovascular comorbidities can effectively assess dis ease severity and predict outcome in patients with coronavirus disease 2019.

CT-derived Chest Muscle Metrics for Outcome Prediction in Patients with COVID-19.

Background Lower muscle mass is a known predictor of unfavorable outcomes, but its prognostic impact on patients with COVID-19 is unknown. Purpose To investigate the contribution of CT-derived muscle status in predicting clinical outcomes in patients with COVID-19. Materials and Methods Clinical or laboratory data and outcomes (intensive care unit [ICU] admission and death) were retrospectively retrieved for patients with reverse transcriptase polymerase chain reaction-confirmed SARS-CoV-2 infection, who underwent chest CT on admission in four hospitals in Northern Italy from February 21 to April 30, 2020. The extent and type of pulmonary involvement, mediastinal lymphadenopathy, and pleural effusion were assessed. Cross-sectional areas and attenuation by paravertebral muscles were measured on axial CT images at the T5 and T12 vertebral level. Multivariable linear and binary logistic regression, including calculation of odds ratios (ORs) with 95% CIs, were used to build four models to predict ICU admission and death, which were tested and compared by using receiver operating characteristic curve analysis. Results A total of 552 patients (364 men and 188 women; median age, 65 years [interquartile range, 54-75 years]) were included. In a CT-based model, lower-than-median T5 paravertebral muscle areas showed the highest ORs for ICU admission (OR, 4.8; 95% CI: 2.7, 8.5; P < .001) and death (OR, 2.3; 95% CI: 1.0, 2.9; P = .03). When clinical variables were included in the model, lower-than-median T5 paravertebral muscle areas still showed the highest ORs for both ICU admission (OR, 4.3; 95%: CI: 2.5, 7.7; P < .001) and death (OR, 2.3; 95% CI: 1.3, 3.7; P = .001). At receiver operating characteristic analysis, the CT-based model and the model including clinical variables showed the same area under the receiver operating characteristic curve (AUC) for ICU admission prediction (AUC, 0.83; P = .38) and were not different in terms of predicting death (AUC, 0.86 vs AUC, 0.87, respectively; P = .28). Conclusion In hospitalized patients with COVID-19, lower muscle mass on CT images was independently associated with intensive care unit admission and in-hospital mortality. © RSNA, 2021 Online supplemental material is available for this article.

Association of Paraspinal Muscle Measurements on Chest Computed Tomography With Clinical Outcomes in Patients With Severe Coronavirus Disease 2019.

BACKGROUND: Skeletal muscle depletion is common in old adults and individuals with chronic comorbidities, who have an increased risk of developing severe coronavirus disease 2019 (COVID-19), which is defined by hypoxia requiring supplemental oxygen. This study aimed to determine the association between skeletal muscle depletion and clinical outcomes in patients with severe COVID-19. METHODS: One hundred and sixteen patients with severe COVID-19 who underwent chest computed tomography scan on admission were included in this multicenter, retrospective study. Paraspinal muscle index (PMI) and radiodensity (PMD) were measured using computed tomography images. The primary composite outcome was the occurrence of critical illness (respiratory failure requiring mechanical ventilation, shock, or intensive care unit admission) or death, and the secondary outcomes were the duration of viral shedding and pulmonary fibrosis in the early rehabilitation phase. Logistic regression and Cox proportional hazards models were employed to evaluate the associations. RESULTS: The primary composite outcome occurred in 48 (41.4%) patients, who were older and had lower PMD (both p < .05). Higher PMD was associated with reduced risk of critical illness or death in a fully adjusted model overall (odds ratio [OR] per standard deviation [SD] increment: 0.87, 95% confidence interval [CI]: 0.80-0.95; p = .002) and in female patients (OR per SD increment: 0.71, 95% CI: 0.56-0.91; p = .006), although the effect was not statistically significant in male patients (p = .202). Higher PMD (hazard ratio [HR] per SD increment: 1.08, 95% CI: 1.02-1.14; p = .008) was associated with shorter duration of viral shedding among female survivors. However, no significant association was found between PMD and pulmonary fibrosis in the early rehabilitation phase, or between PMI and any outcome in both men and women. CONCLUSIONS: Higher PMD, a proxy measure of lower muscle fat deposition, was associated with a reduced risk of disease deterioration and decreased likelihood of prolonged viral shedding among female patients with severe COVID-19.