Association of Chest CT-Based Quantitative Measures of Muscle and Fat with Post-Lung Transplant Survival and Morbidity: A Single Institutional Retrospective Cohort Study in Korean Population

Prognostic impact of low muscle mass on clinical outcomes in patients who undergo lung transplant

BACKGROUND

Low muscle mass (LMM) is recognized as a poor prognostic factor in various chronic lung diseases. However, its prognostic impact on recipients of lung transplants remains inconclusive.

METHODS

We retrospectively analyzed patients who underwent lung transplantation at a tertiary referral center in South Korea. Pretransplant skeletal muscle mass was quantified at the L1 vertebral level by computed tomography scans of the chest using a commercially available body composition analysis software. Patients were classified into LMM and non-LMM group using a threshold for LMM that had been previously validated in the South Korean population. We then evaluated the prognostic impact of preoperative LMM on clinical outcomes after lung transplantation.

RESULTS

A total of 107 patients were included in this analysis, of whom 44 (41.1%) were classified into the LMM group. The median follow-up duration was 958 days posttransplantation. A preoperative LMM was identified as an independent factor associated with a greater risk of overall mortality (adjusted hazard ratio, 2.15; 95% confidence interval, 1.07-4.34). In addition, patients with LMM had a greater risk of developing primary graft dysfunction (adjusted odds ratio, 3.56; 95% confidence interval, 1.25-10.18). At the 1-year follow-up, 37.5% of the patients with baseline LMM had recovered and were reclassified into the non-LMM group, and this improvement was found to mitigate the negative impact of preoperative LMM.

CONCLUSIONS

Pretransplant LMM was significantly associated with poor clinical outcomes in recipients of lung transplants. These findings highlight the importance of maintaining adequate muscle mass during the waiting period for lung transplantation.

Computed Tomography-Based Body Composition is Related to Perioperative Morbidity in Older Lung Transplant Recipients

BACKGROUND

 In older patients, a limited physical reserve is considered a contraindication for lung transplantation (LTx). Herein, we aimed to establish a computed tomography (CT)-based quantification of physical reserve in older patients scheduled for transplantation.

METHODS

 This retrospective study included patients older than 60 years who received LTx. Semiautomatic measurements of the mediastinal fat area and the dorsal muscle group area in pretransplantation CT scans were performed, and normalized data were correlated with clinical parameters.

RESULTS

 Patients (n = 108) were assigned into three groups (Musclehighfatlow [n = 25], Musclelowfathigh [n = 24], and other combinations [n = 59]). The Musclelowfathigh group had a significantly increased risk of wound infections (p = 0.002) and tracheostomy (p = 0.001) compared with Musclehighfatlow patients. The median length of intensive care unit stay (25 vs. 3.5 days; p = 0.002) and the median length of hospital stay (44 vs. 22.5 days; p = 0.013) post-LTx were significantly prolonged in the Musclelowfathigh group. Significantly more patients in this group had a prolonged ventilation time (11 vs. 0; p < 0.001).

CONCLUSION

 Body composition parameters determined in pretransplant chest CT scans in older LTx candidates might aid in identifying high-risk patients with a worse perioperative outcome after LTx.

IA-Body Composition CT at T12 in Idiopathic Pulmonary Fibrosis: Diagnosing Sarcopenia and Correlating with Other Morphofunctional Assessment Techniques

BACKGROUND

Body composition (BC) techniques, including bioelectrical impedance analysis (BIVA), nutritional ultrasound® (NU), and computed tomography (CT), can detect nutritional diagnoses such as sarcopenia (Sc). Sc in idiopathic pulmonary fibrosis (IPF) is associated with greater severity and lower survival. Our aim was to explore the correlation of BIVA, NU and functional parameters with BC at T12 level CT scans in patients with IPF but also its relationship with degree of Sc, malnutrition and mortality.

METHODS

This bicentric cross-sectional study included 60 IPF patients (85.2% male, 70.9 ± 7.8 years). Morphofunctional assessment (MFA) techniques included BIVA, NU, CT at T12 level (T12-CT), handgrip strength, and timed up and go. CT data were obtained using FocusedON®. Statistical analysis was conducted using JAMOVI version 2.3.22 to determine the cutoff points for Sc in T12-CT and to analyze correlations with other MFA techniques.

RESULTS

the cutoff for muscle area in T12-CT was ≤77.44 cm2 (area under the curve (AUC) = 0.734, sensitivity = 41.7%, specificity = 100%). The skeletal muscle index (SMI_T12CT) cutoff was ≤24.5 cm2/m2 (AUC = 0.689, sensitivity = 66.7%, specificity = 66.7%). Low SMI_T12CT exhibited significantly reduced median survival and higher risk of mortality compared to those with normal muscle mass (SMI cut off ≥ 28.8 cm/m2). SMI_T12CT was highly correlated with body cell mass from BIVA (r = 0.681) and rectus femoris cross-sectional area (RF-CSA) from NU (r = 0.599). Cronbach's α for muscle parameters across different MFA techniques and CT was 0.735, confirming their validity for evaluating muscle composition.

CONCLUSIONS

T12-CT scan is a reliable technique for measuring low muscle mass in patients with IPF, specifically when the L3 vertebrae are not captured. An SMI value of <28.8 is a good predictor of low lean mass and 12-month mortality in IPF patients.

Association of ratios of visceral fat area/subcutaneous fat area and muscle area/standard body weight at T12 CT level with the prognosis of acute respiratory distress syndrome

Background

It is well-known that body composition metrics can influence the prognosis of various diseases. This study investigated how body composition metrics predict acute respiratory distress syndrome (ARDS) prognosis, focusing on the ratio of visceral fat area (VFA) to subcutaneous fat area (SFA), SFA to standard body weight (SBW), VFA to SBW, and muscle area (MA) to SBW. These metrics were assessed at the level of the twelfth thoracic vertebra (T12 computed tomography [CT] level) to determine their correlation with the outcomes of ARDS. The goal was to utilize these findings to refine and personalize treatment strategies for ARDS.

Methods

Patients with ARDS admitted to the intensive care units (ICUs) of three hospitals from January 2016 to July 2023 were enrolled in this study. Within 24 hours of ARDS onset, we obtained chest CT scans to measure subcutaneous fat, visceral fat, and muscle area at the T12 level. We then compared these ratios between survivors and non-survivors. Logistic regression was employed to identify prognostic risk factors. Receiver operating characteristic (ROC) curve analysis was utilized to determine the optimal cutoff for predictors of in-hospital mortality. Based on this cutoff, patients with ARDS were stratified. To reduce confounding factors, 1:1 propensity score matching (PSM) was applied. We conducted analyses of clinical feature and prognostic differences pre- and post-PSM between the stratified groups. Additionally, Kaplan-Meier survival curves were generated to compare the survival outcomes of these groups.

Results

Of 258 patients with ARDS, 150 survived and 108 did not. Non-survivors had a higher VFA/SFA ratio (P <0.001) and lower SFA/SBW and MA/SBW ratios (both P <0.001). Key risk factors were high VFA/SFA ratio (OR=2.081; P=0.008), age, acute physiology and chronic health evaluation (APACHE) II score, and lactate levels, while MA/SBW and albumin were protective. Patients with a VFA/SFA ratio ≥0.73 were associated with increased mortality, while those with an MA/SBW ratio >1.55 cm²/kg had lower mortality, both pre- and post-PSM (P=0.001 and P <0.001, respectively). Among 170 patients with pulmonary-origin ARDS, 87 survived and 83 did not. The non-survivor group showed a higher VFA/SFA ratio (P <0.001) and lower SFA/SBW and MA/SBW (P=0.003, P <0.001, respectively). Similar risk and protective factors were observed in this cohort. For VFA/SFA, a value above the cutoff of 1.01 predicted higher mortality, while an MA/SBW value below the cutoff of 1.48 cm²/kg was associated with increased mortality (both P <0.001 pre-/post-PSM).

Conclusions

Among all patients with ARDS, the VFA to SFA ratio, MA to SBW ratio at the T12 level, age, APACHE II score, and lactate levels emerged as independent risk factors for mortality.

Adipose Tissue Segmentation after Lung Slice Localization in Chest CT Images Based on ConvBiGRU and Multi-Module UNet

The distribution of adipose tissue in the lungs is intricately linked to a variety of lung diseases, including asthma, chronic obstructive pulmonary disease (COPD), and lung cancer. Accurate detection and quantitative analysis of subcutaneous and visceral adipose tissue surrounding the lungs are essential for effectively diagnosing and managing these diseases. However, there remains a noticeable scarcity of studies focusing on adipose tissue within the lungs on a global scale. Thus, this paper introduces a ConvBiGRU model for localizing lung slices and a multi-module UNet-based model for segmenting subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT), contributing to the analysis of lung adipose tissue and the auxiliary diagnosis of lung diseases. In this study, we propose a bidirectional gated recurrent unit (BiGRU) structure for precise lung slice localization and a modified multi-module UNet model for accurate SAT and VAT segmentations, incorporating an additive weight penalty term for model refinement. For segmentation, we integrate attention, competition, and multi-resolution mechanisms within the UNet architecture to optimize performance and conduct a comparative analysis of its impact on SAT and VAT. The proposed model achieves satisfactory results across multiple performance metrics, including the Dice Score (92.0% for SAT and 82.7% for VAT), F1 Score (82.2% for SAT and 78.8% for VAT), Precision (96.7% for SAT and 78.9% for VAT), and Recall (75.8% for SAT and 79.1% for VAT). Overall, the proposed localization and segmentation framework exhibits high accuracy and reliability, validating its potential application in computer-aided diagnosis (CAD) for medical tasks in this domain.

Estimating Body Weight From Measurements From Different Single-Slice Computed Tomography Levels: An Evaluation of Total Cross-Sectional Body Area Measurements and Deep Learning

OBJECTIVE

This study aimed to evaluate the correlation between the estimated body weight obtained from 2 easy-to-perform methods and the actual body weight at different computed tomography (CT) levels and determine the best reference site for estimating body weight.

METHODS

A total of 862 patients from a public database of whole-body positron emission tomography/CT studies were retrospectively analyzed. Two methods for estimating body weight at 10 single-slice CT levels were evaluated: a linear regression model using total cross-sectional body area and a deep learning-based model. The accuracy of body weight estimation was evaluated using the mean absolute error (MAE), root mean square error (RMSE), and Spearman rank correlation coefficient ( ρ ).

RESULTS

In the linear regression models, the estimated body weight at the T5 level correlated best with the actual body weight (MAE, 5.39 kg; RMSE, 7.01 kg; ρ = 0.912). The deep learning-based models showed the best accuracy at the L5 level (MAE, 6.72 kg; RMSE, 8.82 kg; ρ = 0.865).

CONCLUSIONS

Although both methods were feasible for estimating body weight at different single-slice CT levels, the linear regression model using total cross-sectional body area at the T5 level as an input variable was the most favorable method for single-slice CT analysis for estimating body weight.

Effect of pretransplant sarcopenia on patient and graft outcomes in solid organ transplant recipients: A systematic review and meta-analysis

The relationship between sarcopenia and prognosis in solid organ transplantation recipients (SOTr) remains unverified. We aimed to quantify the prevalence of pretransplant sarcopenia and its effect on patient and graft survival in SOTr. We used PubMed, EMBASE, Cochrane Library and Web of Science to search relevant studies published in English (from inception to December 31, 2021). Prospective and retrospective cohort studies that reported the prevalence of sarcopenia before transplant or the association between sarcopenia and clinical outcomes in SOTr were included. Primary outcomes were the prevalence of sarcopenia and its impact on patient and graft survival. Secondary outcomes included perioperative complications, acute rejection, length of hospital stay, length of intensive care unit stay (ICU LOS) and early readmission. Thirty-nine studies involving 5792 patients were included. Pooled prevalence of sarcopenia amongst SOTr candidates was 40 % (95 % confidence interval [CI]: 34%-47 % and I2 = 97 %). Sarcopenia was associated with increased risk of death (hazard ratio [HR] = 1.87, 95 % CI: 1.46-2.41 and I2 = 60 %), poor graft survival (HR = 1.71, 95 % CI: 1.16-2.54 and I2 = 57 %) and increased liver graft loss (HR = 1.43, 95 % CI: 1.03-1.99 and I2 = 38 %). Patients with sarcopenia demonstrated increased incidence of perioperative complications (risk ratio [RR] = 1.34, 95 % CI: 1.17-1.53 and I2 = 40 %), long ICU LOS (mean difference = 2.31 days, 95 % CI: 0.58-4.04 and I2 = 97 %) and decreased risk of acute rejection (RR = 0.61, 95 % CI: 0.42-0.89 and I2 = 0 %). In Conclusion, sarcopenia is prevalent in SOTr candidates and associated with death and graft loss. Identifying sarcopenia before transplantation and intervening may improve long-term outcomes.

Evaluation of the relationship of the T and M stage with the erector spinae muscle area in male lung cancer patients

OBJECTIVES

Sarcopenia is very common due to cachexia and presents with a decrease in skeletal muscle mass. In this study, we aimed to investigate the relationship between the T, M category and the erector spinae muscle area (ESMa).

MATERIAL AND METHODS

The initial first thorax and high-resolution computed tomography (CT) of patients with lung cancer between 2015 and 2019 were retrospectively screened. After exclusion criterias remaining 226 male patients constituted the study group. ESMa was measured manually in the section taken from the T12 vertebra spinous process level as previously described in the literature and its relationship with the T and M stage were evaluated.

RESULTS

The mean ages of patients were 70 ± 9.57 years. The T stage was T1 in 34 (15%) patients, T2 in 46 (20.4%), T3 in 59 (26.1%), and T4 in 87 (38.5%). Metastasis was detected in 83 (36.7%) patients. The mean ESMa of the patients was 34.15 ± 7.21 mm² and did not differ according to the T stage (p = .39). ESMa was lower in the metastatic group (mean 30.42 ± 6.38 mm²) than the non-metastatic group (mean 36.32 ± 6.78 mm²) (p = .0001).

CONCLUSIONS

ESMa, one of the indicators of sarcopenia, is lower in patients with metastatic lung cancer than in nonmetastatic.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Predictive Value of CT Biomarkers in Lung Transplantation Survival: Preliminary Investigation in a Diverse, Underserved, Urban Population

INTRODUCTION

Survival following lung transplant is low. With limited donor lung availability, predicting post-transplant survival is key. We investigated the predictive value of pre-transplant CT biomarkers on survival.

METHODS

In this single-center retrospective cohort study of adults in a diverse, underserved, urban lung transplant program (11/8/2017-5/20/2022), chest CTs were analyzed using TeraRecon to assess musculature, fat, and bone. Erector spinae and pectoralis muscle area and attenuation were analyzed. Sarcopenia thresholds were 34.3 (women) and 38.5 (men) Hounsfield Units (HU). Visceral and subcutaneous fat area and HU, and vertebral body HU were measured. Demographics and pre-transplant metrics were recorded. Survival analyses included Kaplan-Meier and Cox proportional hazard.

RESULTS

The study cohort comprised 131 patients, 50 women, mean age 60.82 (SD 10.15) years, and mean follow-up 1.78 (SD 1.23) years. Twenty-nine percent were White. Mortality was 32.1%. Kaplan-Meier curves did not follow the proportional hazard assumption for sex, so analysis was stratified. Pre-transplant EMR metrics did not predict survival. Women without sarcopenia at erector spinae or pectoralis had 100% survival (p = 0.007). Sarcopenia did not predict survival in men and muscle area did not predict survival in either sex. Men with higher visceral fat area and HU had decreased survival (p = 0.02). Higher vertebral body density predicted improved survival in men (p = 0.026) and women (p = 0.045).

CONCLUSION

Pre-transplantation CT biomarkers had predictive value in lung transplant survival and varied by sex. The absence of sarcopenia in women, lower visceral fat attenuation and area in men, and higher vertebral body density in both sexes predicted survival in our diverse, urban population.

Myosteatosis as a prognostic factor of Mycobacterium avium complex pulmonary disease

Quantitative body composition affects the prognosis of patients with Mycobacterium avium complex pulmonary disease (MAC-PD). However, whether the qualitative body composition obtained indirectly through computed tomography (CT) affects their prognosis is debatable. We retrospectively analyzed patients with MAC-PD who underwent non-contrast CT at MAC-PD diagnosis. The cross-sectional area of the erector spinae muscle (ESM area), the Hounsfield unit of the erector spinae muscle (ESM HU), and the cross-sectional area of subcutaneous fat (SQF area) were measured at the level of the first lumbar vertebra. Myosteatosis were defined below the median value of ESM HU for each sex. Of 377 patients, 45 (11.9%) died during the follow-up. Patients who died were older and had a lower ratio of females (33.3%). In body compositions, SQF area and ESM HU were lower in the patients who died. In multivariable analysis, a low ESM HU was associated with increased mortality (ESM HU adjusted hazard ratio [aHR] 0.95, 95% confidence interval [CI] 0.93-0.97) through body composition. SQF area revealed protective effects in MAC-PD patients with body mass index ≥ 18.5 kg/m2 (aHR 0.98, 95% CI 0.95-1.00). In conclusion, the decrease in ESM HU, which indirectly reflects myosteatosis, is associated with mortality in patients with MAC-PD.

Prognostic value of low muscle mass at the 12th thoracic vertebral level in multiple myeloma treated with transplantation: CAREMM-2101 study

PURPOSE

Autologous hematopoietic stem cell transplantation (ASCT) has been introduced as a standard treatment for newly diagnosed multiple myeloma (NDMM) following novel agent-based induction chemotherapy. This study investigated whether pre-ASCT low muscle mass evaluated using the paraspinal muscle index (PMI) at the 12th thoracic vertebra (T12) level is a reliable prognostic marker in NDMM after chemotherapy.

METHODS

A multi-center registry database was retrospectively analyzed. Between 2009 and 2020, 190 patients with chest computed tomography images underwent frontline ASCT following induction therapy. The PMI was defined as the value of the paraspinal muscle area at the T12 level divided by the square of the patient's height. The cut-off value indicating a low muscle mass was sex-specific, using the lowest quintiles.

RESULTS

Of the 190 patients, 38 (20%) were in the low muscle mass group. The low muscle mass group had a lower 4-year overall survival (OS) rate than the non-low muscle mass group (68.5% vs. 81.2%; P = 0.074). The median progression-free survival (PFS) in the low muscle mass group was significantly shorter compared with the non-low muscle mass group (23.3 months vs. 29.2 months; P = 0.029). The cumulative incidence of transplant-related mortality (TRM) was significantly higher in the low muscle mass group than in the non-low muscle mass group (4-year probability of TRM incidence, 10.6% vs. 0.7%; P < 0.001). In contrast, no significant difference in the cumulative incidence of disease progression was found between the two groups. Multivariate analysis revealed that low muscle mass was associated with significant negative outcomes for OS [(hazard ratio (HR): 2.14; P = 0.047], PFS (HR: 1.78; P = 0.012), and TRM (HR: 12.05; P = 0.025).

CONCLUSION

Paraspinal muscle mass may have a prognostic role in NDMM patients who undergo ASCT. Patients with low paraspinal muscle mass have lower survival outcomes compared to non-low muscle mass group.

CT analysis of thoracolumbar body composition for estimating whole-body composition

BACKGROUND

To evaluate the correlation between single- and multi-slice cross-sectional thoracolumbar and whole-body compositions.

METHODS

We retrospectively included patients who underwent whole-body PET-CT scans from January 2016 to December 2019 at multiple institutions. A priori-developed, deep learning-based commercially available 3D U-Net segmentation provided whole-body 3D reference volumes and 2D areas of muscle, visceral fat, and subcutaneous fat at the upper, middle, and lower endplate of the individual T1-L5 vertebrae. In the derivation set, we analyzed the Pearson correlation coefficients of single-slice and multi-slice averaged 2D areas (waist and T12-L1) with the reference values. We then built prediction models using the top three correlated levels and tested the models in the validation set.

RESULTS

The derivation and validation datasets included 203 (mean age 58.2 years; 101 men) and 239 patients (mean age 57.8 years; 80 men). The coefficients were distributed bimodally, with the first peak at T4 (coefficient, 0.78) and the second peak at L2-3 (coefficient 0.90). The top three correlations in the abdominal scan range were found for multi-slice waist averaging (0.92) and single-slice L3 and L2 (0.90, each), while those in the chest scan range were multi-slice T12-L1 averaging (0.89), single-slice L1 (0.89), and T12 (0.86). The model performance at the top three levels for estimating whole-body composition was similar in the derivation and validation datasets.

CONCLUSIONS

Single-slice L2-3 (abdominal CT range) and L1 (chest CT range) analysis best correlated with whole-body composition around 0.90 (coefficient). Multi-slice waist averaging provided a slightly higher correlation of 0.92.

Sarcopenia Predicts Outcomes After Lung Transplantation in Older Lung Transplant Candidates

Background

As lung transplantation (LT) expands to older recipients, objective approaches to evaluate the aging are needed to optimize posttransplantation outcomes. Frailty assessment and sarcopenia have shown promise as tools for predicting clinical outcomes.

Methods

Patients older than 55 years undergoing evaluation for LT were enrolled in an institutional review board-approved study. Sarcopenia was measured on pretransplantation chest computed tomography images, measuring cross-sectional area and average attenuation of the pectoralis major muscle at 1 slice above the aortic arch. Frailty was measured using the Fried frailty phenotype (FFP) and Short Performance Physical Battery (SPPB).

Results

The study evaluated 84 patients with results of computed tomography of the chest available for review; 63% were classified as frail or prefrail by SPPB and 53% were frail by FFP. Sex-corrected sarcopenia was associated with frailty by FFP (P = .004) or SPPB (P = .044). Sarcopenia, measured by area or average attenuation, was significantly associated with length of stay after transplantation (P = .017 and P = .022, respectively), with a median 12 days for those with higher muscle mass compared with 21 days for those with lower muscle mass. Total time in the hospital in the first year after transplantation was also associated with sarcopenia by area (P = .090) or average attenuation (P = .046).

Conclusions

A multifaceted approach to the evaluation of older patients can improve risk stratification, optimizing organ allocation to improve LT outcomes.

The effect of computed tomography parameters on sarcopenia and myosteatosis assessment: a scoping review

Computed tomography (CT) is a valuable assessment method for muscle pathologies such as sarcopenia, cachexia, and myosteatosis. However, several key underappreciated scan imaging parameters need consideration for both research and clinical use, specifically CT kilovoltage and the use of contrast material. We conducted a scoping review to assess these effects on CT muscle measures. We reviewed articles from PubMed, Scopus, and Web of Science from 1970 to 2020 on the effect of intravenous contrast material and variation in CT kilovoltage on muscle mass and density. We identified 971 articles on contrast and 277 articles on kilovoltage. The number of articles that met inclusion criteria for contrast and kilovoltage was 11 and 7, respectively. Ten studies evaluated the effect of contrast on muscle density of which nine found that contrast significantly increases CT muscle density (arterial phase 6-23% increase, venous phase 19-57% increase, and delayed phase 23-43% increase). Seven out of 10 studies evaluating the effect of contrast on muscle area found significant increases in area due to contrast (≤2.58%). Six studies evaluating kilovoltage on muscle density found that lower kilovoltage resulted in a higher muscle density (14-40% increase). One study reported a significant decrease in muscle area when reducing kilovoltage (2.9%). The use of contrast and kilovoltage variations can have dramatic effects on skeletal muscle analysis and should be considered and reported in CT muscle analysis research. These significant factors in CT skeletal muscle analysis can alter clinical and research outcomes and are therefore a barrier to clinical application unless better appreciated.

Validation for measurements of skeletal muscle areas using low-dose chest computed tomography

Various methods were suggested to measure skeletal muscle areas (SMAs) using chest low-dose computed tomography (chest LDCT) as a substitute for SMA at 3rd lumbar vertebra level (L3-SMA). In this study, four SMAs (L1-SMA, T12-erector spinae muscle areas, chest wall muscle area at carina level, pectoralis muscle area at aortic arch level) were segmented semi-automatically in 780 individuals taking concurrent chest and abdomen LDCT for healthcare screening. Four SMAs were compared to L3-SMA and annual changes were calculated from individuals with multiple examinations (n = 101). Skeletal muscle index (SMI; SMA/height²) cut-off for sarcopenia was determined by lower 5th percentile of young individuals (age ≤ 40 years). L1-SMA showed the greatest correlation to L3-SMA (men, R² = 0.7920; women, R² = 0.7396), and the smallest annual changes (0.3300 ± 4.7365%) among four SMAs. L1-SMI cut-offs for determining sarcopenia were 39.2cm²/m² in men, and 27.5cm²/m² in women. Forty-six men (9.5%) and ten women (3.4%) were found to have sarcopenia using L1-SMI cut-offs. In conclusion, L1-SMA could be a reasonable substitute for L3-SMA in chest LDCT. Suggested L1-SMI cut-offs for sarcopenia were 39.2cm²/m² for men and 27.5cm²/m² for women in Asian.

Low Thoracic Skeletal Muscle Area Is Not Associated With Negative Outcomes in Patients With COVID-19

OBJECTIVE

Sarcopenia has been related to negative outcomes in different clinical scenarios from critical illness to chronic conditions. The aim of this study was to verify whether there was an association between low skeletal muscle index and in-hospital mortality, intensive care unit admission, and invasive mechanical ventilation need in hospitalized patients with COVID-19.

DESIGN

This was a retrospective cohort study of a referral center for COVID-19. We included all consecutive patients admitted to the hospital between February 26 and May 15, 2020, with a confirmed diagnosis of COVID-19. Skeletal muscle index was assessed from a transverse computed tomography image at the level of twelfth thoracic vertebra with National Institutes of Health ImageJ software, and statistical analysis was performed to find an association between skeletal muscle index and in-hospital mortality, need of invasive mechanical ventilation, and intensive care unit admission.

RESULTS

We included 519 patients, the median age was 51 (42-61) yrs, and 115 patients (22%) had low skeletal muscle index. On multivariable analysis, skeletal muscle index was not associated with mortality, intensive care unit admission, or invasive mechanical ventilation need nor in a subanalysis of patients 65 yrs or older.

CONCLUSIONS

Skeletal muscle index determined by computed tomography at the level of twelfth thoracic vertebra was not associated with negative outcomes in hospitalized patients with COVID-19.

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

Body composition measurement using diagnostic computed tomography (CT) scans has emerged as a method to assess sarcopenia (low muscle mass) in oncology patients. Assessment of skeletal muscle mass (SMM) using the cross-sectional area of a single vertebral slice (at lumbar L3) in a CT scan is correlated with whole-body skeletal muscle volume. This method is used to assess CT-defined sarcopenia in patients with cancer, with low SMM effecting outcomes. However, as diagnostic scans are based on tumour location, not all include L3. We evaluated the evidence for the use of alternate vertebral CT slices for SMM evaluation when L3 is not available. Five electronic databases were searched from January 1996 to April 2020 for studies using CT scan vertebral slices above L3 for SM measurement in adults with cancer (solid tumours). Validation with whole-body SMM, rationale for the chosen slice and sarcopenia cut-off values were investigated. Thirty-two studies were included, all retrospective and cross-sectional in design. Cervical, thoracic and lumbar slices were used (from C3 to L1), with no validation of whole-body SMM using CT scans. Alternate slices were used in lung, and head and neck cancer patients. Sarcopenia cut-off values were reported in 75 % of studies, with differing methods, with or without sex-specific values, and a lack of consensus. Current evidence is inadequate to provide definitive recommendations for alternate vertebral slice use for SMM evaluation in cancer patients. Variation in sarcopenia cut-offs warrants more robust investigation, in order for risk stratification to be applied to all patients with cancer.

CLINICAL IMPLICATIONS OF BODY COMPOSITION AND EXERCISE CAPACITY FOLLOWING PULMONARY ENDARTERECTOMY

BACKGROUND

Pulmonary endarterectomy (PEA) is a curative procedure for patients with chronic thromboembolic pulmonary hypertension. Body composition and exercise capacity have been associated with adverse outcomes in patients undergoing cardiothoracic surgeries, but their significance with PEA is unclear. We evaluated the association of body composition and 6-minute walk distance (6MWD) with disease severity, hospital length of stay, discharge disposition and post-operative functional recovery.

METHODS

Retrospective, single-center cohort study of patients who underwent PEA (Jan/2014-Dec/2017). Body composition (skeletal muscle mass and adiposity cross sectional area, body mass index) was quantified using thoracic computed tomography with Slice-O-Matic software. Association of body composition measures and 6MWD with clinical outcomes was evaluated using multivariable regression models.

RESULTS

127 patients (58±14 years; 42% males, Body Mass Index: 31±7 kg/m², 6MWD: 361±165 m) were included. Muscle and 6MWD were associated with disease severity measures. Of those surviving hospitalization (n=125), a greater 6MWD was associated with a shorter hospital stay (1.9 median days per 100m, p<0.001) and higher likelihood of being discharged directly home from hospital (OR: 2.1 per 100m, p= 0.004), independent of age, sex and body mass index. Those with a lower pre-operative 6MWD (per 100m) had a greater increase in their post-operative 6MWD (52m, p< 0.0001), independent of age, sex, and body mass index. Body composition measures were not associated with hospital outcomes or exercise capacity in the first-year post-operatively.

CONCLUSIONS

Exercise capacity was a more prognositc marker of PEA outcomes compared to body composition. Future research is needed to explore pre-PEA rehabilitation strategies.

Clinical outcomes associated with computed tomography-based body composition measures in lung transplantation: a systematic review

Computed tomography (CT) is gaining increased recognition in the assessment of body composition in lung transplant (LTx) candidates as a prognostic marker of post-transplant outcomes. This systematic review was conducted to describe the methodology of CT measures of body composition used in LTx patients and its association with post-transplant outcomes. Six databases were searched (inception-April 2020) for studies of adult LTx patients with thoracic or abdominal CT measures [muscle cross-sectional area (CSA) and/or adiposity]. Thirteen articles were included with 1911 LTx candidates, 58% males, mean age range (48-61 years) and body mass index of 21.0-26.1 kg/m2 . Several methods were utilized using thoracic or abdominal CT scans to assess skeletal muscle (n = 11) and adiposity (n = 4) at various anatomic locations (carina, thoracic, and lumbar vertebrae), differing muscle groups, and adipose tissue compartments. Low muscle mass was associated with adverse outcomes in 6/11 studies, including longer mechanical ventilation days (n = 2), intensive care (n = 2) and hospital stay (n = 2), and mortality (n = 4). Greater subcutaneous and mediastinal fat were associated with increased risk of primary graft dysfunction (n = 2), but implications of adiposity on survival were variable across four studies. Further standardization of CT body composition assessments is needed to assess the prognostic utility of these measures on LTx outcomes.

Quantitative Imaging of Body Composition

Body composition refers to the amount and distribution of lean tissue, adipose tissue, and bone in the human body. Lean tissue primarily consists of skeletal muscle; adipose tissue comprises mostly abdominal visceral adipose tissue and abdominal and nonabdominal subcutaneous adipose tissue. Hepatocellular and myocellular lipids are also fat pools with important metabolic implications. Importantly, body composition reflects generalized processes such as increased adiposity in obesity and age-related loss of muscle mass known as sarcopenia.In recent years, body composition has been extensively studied quantitatively to predict overall health. Multiple imaging methods have allowed precise estimates of tissue types and provided insights showing the relationship of body composition to varied pathologic conditions. In this review article, we discuss different imaging methods used to quantify body composition and describe important anatomical locations where target tissues can be measured.

The association of silicosis severity with pectoralis major muscle and subcutaneous fat volumes and the pulmonary artery/aorta ratio evaluated by CT

PURPOSE

Silicosis is an incurable occupational disease that sometimes rapidly progresses with fatal outcomes. We aimed to evaluate the association between disease severity and the change in the pectoralis major muscle volume (PMV), subcutaneous fat volume (SFV), and the pulmonary artery/aorta (P/Ao) ratio in patients with silicosis using computed tomography (CT).

METHODS

The study included 41 male silicosis patients and 41 control group subjects with available chest CT images. Using dedicated software, we measured PMV and SFV from the axial CT images. We calculated the P/Ao ratio and obtained body mass index (BMI) and forced expiratory volume/forced vital capacity (FEV1/FVC) results from hospital records. We used the chest X-ray profusion score according to the International Labor Organization (ILO) classification to evaluate the severity of the silicosis.

RESULTS

The mean age was 33.5±4.4 and 34.7±4.7 years in the silicotic and control groups, respectively. The mean BMI, PMV, SFV, and P/Ao values significantly differed between the study and control groups (P = 0.0009, P < 0.0001, P < 0.0001, and P = 0.0029, respectively). According to the ILO classification, there were 12 silicosis patients in category 1, 13 in category 2, and 16 in category 3. A significant difference was found between disease categories in terms of PMV, SFV, P/Ao, BMI, and FEV1/FVC values (P = 0.0425, P = 0.0341, P = 0.0002, P = 0.0492, and P = 0.0004, respectively).

CONCLUSION

Disease severity had a stronger association with decreased PMV and SFV and increased P/Ao ratios than BMI in patients with silicosis caused by denim sandblasting. Thus, CT evaluation might be a useful indicator of disease severity.