Importance of combined assessment of skeletal muscle mass and density by computed tomography in predicting clinical outcomes after transcatheter aortic valve replacement

Sarcopenia and aortic valve disease

Valvular heart disease, including calcific or degenerative aortic stenosis (AS), is increasingly prevalent among the older adult population. Over the last few decades, treatment of severe AS has been revolutionised following the development of transcatheter aortic valve replacement (TAVR). Despite improvements in outcomes, older adults with competing comorbidities and geriatric syndromes have suboptimal quality of life outcomes, highlighting the cumulative vulnerability that persists despite valve replacement. Sarcopenia, characterised by loss of muscle strength, mass and function, affects 21%-70% of older adults with AS. Sarcopenia is an independent predictor of short-term and long-term outcomes after TAVR and should be incorporated as a prognostic marker in preprocedural planning. Early diagnosis and treatment of sarcopenia may reduce morbidity and mortality and improve quality of life following TAVR. The adverse effects of sarcopenia can be mitigated through resistance training and optimisation of nutritional status. This is most efficacious when administered before sarcopenia has progressed to advanced stages. Management should be individualised based on the patient's wishes/preferences, care goals and physical capability. Exercise during the preoperative waiting period may be safe and effective in most patients with severe AS. However, future studies are needed to establish the benefits of prehabilitation in improving quality of life outcomes after TAVR procedures.

Sarcopenia and adipose tissue evaluation by artificial intelligence predicts the overall survival after TAVI

Sarcopenia is a serious systemic disease that reduces overall survival. TAVI is selectively performed in patients with severe aortic stenosis who are not indicated for open cardiac surgery due to severe polymorbidity. Artificial intelligence-assisted body composition assessment from available CT scans appears to be a simple tool to stratify these patients into low and high risk based on future estimates of all-cause mortality. Within our study, the segmentation of preprocedural CT scans at the level of the lumbar third vertebra in patients undergoing TAVI was performed using a neural network (AutoMATiCA). The obtained parameters (area and density of skeletal muscles and intramuscular, visceral, and subcutaneous adipose tissue) were analyzed using Cox univariate and multivariable models for continuous and categorical variables to assess the relation of selected variables with all-cause mortality. 866 patients were included (median(interquartile range)): age 79.7 (74.9-83.3) years; BMI 28.9 (25.9-32.6) kg/m2. Survival analysis was performed on all automatically obtained parameters of muscle and fat density and area. Skeletal muscle index (SMI in cm2/m2), visceral (VAT in HU) and subcutaneous adipose tissue (SAT in HU) density predicted the all-cause mortality in patients after TAVI expressed as hazard ratio (HR) with 95% confidence interval (CI): SMI HR 0.986, 95% CI (0.975-0.996); VAT 1.015 (1.002-1.028) and SAT 1.014 (1.004-1.023), all p < 0.05. Automatic body composition assessment can estimate higher all-cause mortality risk in patients after TAVI, which may be useful in preoperative clinical reasoning and stratification of patients.

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.

Prognostic value of sarcopenia in older adults with transcatheter aortic valve implantation: A systematic review and meta-analysis

OBJECTIVE

We conducted this systematic review and meta-analysis to summarize the prevalence of sarcopenia and its impact on mortality in patients undergoing TAVI.

METHOD

Medline, EMBASE, and PubMed were searched from inception to October 14, 2022 to retrieve eligible studies that assessed sarcopenia in patients undergoing TAVI. Pooled sarcopenia prevalence was calculated with 95% confidence interval (CI), and heterogeneity was estimated using the I2 test. Associations of sarcopenia with mortality of post-TAVI were expressed as hazard ratio (HR) or odds ratios (OR) and 95% CI.

RESULTS

13 studies involving 5248 patients (mean age from 78.1 to 84.9 years) undergoing TAVI were included. There were eleven studies defined sarcopenia based on loss of skeletal muscle mass index (SMI), while only two studies used low muscle mass plus low muscle strength and/or low physical performance. Overall, the pooled prevalence of sarcopenia in patients undergoing TAVI was 49% (95% CI 41%-58%). Sarcopenia was associated with an increased risk of long-term (≥1 year) mortality in patients after TAVI (HR 1.57, 95% CI 1.33-1.85, P < 0.001), with similar findings in the subgroups stratified by follow-up time, definition of sarcopenia, study location, and study design. Furthermore, the 1-, 2-, and 3-year cumulative probabilities of survival in patients with sarcopenia were significantly lower than non-sarcopenia (74.0% vs 91.0%, 68.3% vs 78.0%, and 72.6% vs 79.8%, all P < 0.05).

CONCLUSIONS

Although there are substantial differences in diagnostic criteria, sarcopenia is highly prevalent in patients undergoing TAVI and its linked to increased long-term mortality after TAVI.

Sarcopenia and Cardiovascular Diseases

Sarcopenia is the loss of muscle strength, mass, and function, which is often exacerbated by chronic comorbidities including cardiovascular diseases, chronic kidney disease, and cancer. Sarcopenia is associated with faster progression of cardiovascular diseases and higher risk of mortality, falls, and reduced quality of life, particularly among older adults. Although the pathophysiologic mechanisms are complex, the broad underlying cause of sarcopenia includes an imbalance between anabolic and catabolic muscle homeostasis with or without neuronal degeneration. The intrinsic molecular mechanisms of aging, chronic illness, malnutrition, and immobility are associated with the development of sarcopenia. Screening and testing for sarcopenia may be particularly important among those with chronic disease states. Early recognition of sarcopenia is important because it can provide an opportunity for interventions to reverse or delay the progression of muscle disorder, which may ultimately impact cardiovascular outcomes. Relying on body mass index is not useful for screening because many patients will have sarcopenic obesity, a particularly important phenotype among older cardiac patients. In this review, we aimed to: (1) provide a definition of sarcopenia within the context of muscle wasting disorders; (2) summarize the associations between sarcopenia and different cardiovascular diseases; (3) highlight an approach for a diagnostic evaluation; (4) discuss management strategies for sarcopenia; and (5) outline key gaps in knowledge with implications for the future of the field.

Quality of Life after Transcatheter Aortic Valve Replacement in Sarcopenic Patients Using the Toronto Aortic Stenosis Quality of Life Questionnaire

BACKGROUND

Sarcopenia is the core component of frailty; however, its role in patients undergoing transcatheter aortic valve replacement (TAVR) is a matter of debate. The Toronto Aortic Stenosis Quality of Life Questionnaire (TASQ) is a validated instrument for assessing quality of life (QoL) in patients with severe aortic stenosis (AS).

AIMS

We aim to evaluate the QoL of sarcopenic and non-sarcopenic patients with severe AS undergoing TAVR.

METHODS

TASQ was prospectively administered to patients undergoing TAVR. All patients completed the TASQ before TAVR and at a 3-month follow-up. The study population was divided in two groups according to sarcopenic status. The primary endpoint was the TASQ score in the sarcopenic and non-sarcopenic cohorts.

RESULTS

In total, 99 patients were eligible for the analysis. In both sarcopenic (n = 56) and non-sarcopenic (n = 43) cohorts, significant changes were observed in the overall TASQ score and in all but one (i.e., health expectations) of the individual domains (p < 0.01). Sarcopenic and non-sarcopenic patients showed substantial improvements across TASQ subscores. The mean change in overall TASQ score at three months revealed a significant improvement in both cohorts (p < 0.01). Health expectations worsened in sarcopenic patients at the 3-month follow-up (p = 0.06).

CONCLUSIONS

The TASQ questionnaire revealed changes in QoL after TAVR, regardless of patients' sarcopenic status. Health status improved substantially in both sarcopenic and non-sarcopenic patients following TAVR. Lack of improvement in health expectations seems to depend on patients' expectations regarding the procedure and specific aspects in the evaluation of the outcome.

Internal calibration for opportunistic computed tomography muscle density analysis

INTRODUCTION

Muscle weakness can lead to reduced physical function and quality of life. Computed tomography (CT) can be used to assess muscle health through measures of muscle cross-sectional area and density loss associated with fat infiltration. However, there are limited opportunities to measure muscle density in clinically acquired CT scans because a density calibration phantom, allowing for the conversion of CT Hounsfield units into density, is typically not included within the field-of-view. For bone density analysis, internal density calibration methods use regions of interest within the scan field-of-view to derive the relationship between Hounsfield units and bone density, but these methods have yet to be adapted for muscle density analysis. The objective of this study was to design and validate a CT internal calibration method for muscle density analysis.

METHODOLOGY

We CT scanned 10 bovine muscle samples using two scan protocols and five scan positions within the scanner bore. The scans were calibrated using internal calibration and a reference phantom. We tested combinations of internal calibration regions of interest (e.g., air, blood, bone, muscle, adipose).

RESULTS

We found that the internal calibration method using two regions of interest, air and adipose or blood, yielded accurate muscle density values (< 1% error) when compared with the reference phantom. The muscle density values derived from the internal and reference phantom calibration methods were highly correlated (R2 > 0.99). The coefficient of variation for muscle density across two scan protocols and five scan positions was significantly lower for internal calibration (mean = 0.33%) than for Hounsfield units (mean = 6.52%). There was no difference between coefficient of variation for the internal calibration and reference phantom methods.

CONCLUSIONS

We have developed an internal calibration method to produce accurate and reliable muscle density measures from opportunistic computed tomography images without the need for calibration phantoms.

Evaluation of a Fully Automatic Deep Learning-Based Method for the Measurement of Psoas Muscle Area

Background

Manual muscle mass assessment based on Computed Tomography (CT) scans is recognized as a good marker for malnutrition, sarcopenia, and adverse outcomes. However, manual muscle mass analysis is cumbersome and time consuming. An accurate fully automated method is needed. In this study, we evaluate if manual psoas annotation can be substituted by a fully automatic deep learning-based method.

Methods

This study included a cohort of 583 patients with severe aortic valve stenosis planned to undergo Transcatheter Aortic Valve Replacement (TAVR). Psoas muscle area was annotated manually on the CT scan at the height of lumbar vertebra 3 (L3). The deep learning-based method mimics this approach by first determining the L3 level and subsequently segmenting the psoas at that level. The fully automatic approach was evaluated as well as segmentation and slice selection, using average bias 95% limits of agreement, Intraclass Correlation Coefficient (ICC) and within-subject Coefficient of Variation (CV). To evaluate performance of the slice selection visual inspection was performed. To evaluate segmentation Dice index was computed between the manual and automatic segmentations (0 = no overlap, 1 = perfect overlap).

Results

Included patients had a mean age of 81 ± 6 and 45% was female. The fully automatic method showed a bias and limits of agreement of -0.69 [-6.60 to 5.23] cm2, an ICC of 0.78 [95% CI: 0.74-0.82] and a within-subject CV of 11.2% [95% CI: 10.2-12.2]. For slice selection, 84% of the selections were on the same vertebra between methods, bias and limits of agreement was 3.4 [-24.5 to 31.4] mm. The Dice index for segmentation was 0.93 ± 0.04, bias and limits of agreement was -0.55 [1.71-2.80] cm2.

Conclusion

Fully automatic assessment of psoas muscle area demonstrates accurate performance at the L3 level in CT images. It is a reliable tool that offers great opportunities for analysis in large scale studies and in clinical applications.

Computed tomography measured psoas muscle attenuation predicts mortality after transcatheter aortic valve implantation

AIMS

The aim of this study was to determine if computed tomography (CT) psoas muscular attenuation measurements may predict all-cause mortality in patients undergoing TAVI.

METHODS

Ninety-four consecutive patients undergoing TAVI were analysed. The CT axial slice at the level of the fourth lumbar vertebra was selected. The psoas muscle areas were manually contoured. The circumferential surface area (CSA) of both psoas muscles was determined by selecting the voxels with attenuation values, ranging from 0 to 100 Hounsfield Units (HU). The mean CT attenuation coefficient of the psoas muscle (Psoas mean HU) was measured. The muscle was subdivided into a low-density muscle (LDM) (0-29 HU) and high-density muscle (HDM) (30-100 HU) portion. The HDM/LDM ratio was calculated. We searched for a correlation between HDM/LDM, CSA LDM (%), Psoas mean HU and all-cause mortality.

RESULTS

The mean age was 81.2 ± 7.5 years. Thirty patients had adverse outcome (all-cause mortality). Compared with patients with the lowest CSA LDM (%), patients in the third and second tertiles had an increased hazard ratio for mortality (2.871; 95% confidence interval 0.880-9.371 and 5.044; 95% confidence interval 1.641-15.795, respectively) in a multivariable model with EuroSCORE II, Barthel frailty index and CSA LDM (%) (P = 0.231, 0.097 and 0.019, respectively). HDM/LDM and Psoas mean HU (as continuous variable) were also independent predictors of all-cause mortality (P = 0.019, P = 0.013, respectively).

CONCLUSION

CSA LDM (%), Psoas mean HU and HDM/LDM are independent and incremental predictors of all-cause mortality in patients undergoing TAVI.

Psoas Muscle Volume and Attenuation are Better Predictors than Muscle Area for Hospital Readmission in Older Patients after Transcatheter Aortic Valve Implantation

OBJECTIVE

This study aimed to determine whether the psoas muscle volume (PMV) and its muscle attenuation (MA) are associated with hospital readmission after transcatheter aortic valve implantation (TAVI).

METHOD

We included 113 older patients with aortic stenosis who underwent TAVI at Sakakibara Heart Institute (mean age 85 ± 5 years, 69% women). We measured PMV and psoas muscle area (PMA) as well as total muscle area (TMA) at the third lumbar vertebra using preoperative computed tomography (CT) images. The crude values of the PMV, PMA, and TMA were normalized by dividing by height squared.

RESULTS

The median follow-up period was 724 days (interquartile range: 528-730 days), and there were 25 all-cause readmissions during the follow-up period (22% of all patients). In the multivariate Cox regression analysis adjusted for age, sex, and EuroSCORE II, the PMV and its MA and crude PMA were significantly associated with all-cause readmission [HR: 0.957 (0.930-0.985), p = 0.003, HR: 0.927 (0.862-0.997), p = 0.040], whereas the PMA and TMA and each MA were not (all p > 0.05). The groups with low PMV and MA had significantly higher incidences of all-cause readmission than that with high PMV and MA (log-rank test: p = 0.011).

CONCLUSION

PMV and its MA measured from preoperative CT images were independent predictors of all-cause readmission in TAVI patients.

Impact of Severe Sarcopenia on Rehospitalization and Survival One Year After a TAVR Procedure in Patients Aged 75 and Older

BACKGROUND

Transcatheter aortic-valve replacement (TAVR) reduces mortality and improves quality of life in patients with severe aortic valve stenosis. One third of patients have no benefit one year after TAVR. Sarcopenia, an age-related loss of skeletal muscle mass, is associated with increased physical disability and mortality. The main purpose was to evaluate the impact of severe sarcopenia on rehospitalization one year after TAVR in older patients.

METHODS

All patients aged ≥75 referred for a TAVR in 2018 were included. Severe sarcopenia was defined by a loss of skeletal muscle mass defined on CT-scan measurement associated with a gait speed ≤0.8m/s. The main outcome was rehospitalization one year after TAVR.

RESULTS

Median age of the 182 included patients was 84, and 35% had an unplanned hospitalization at one year. Severe sarcopenia was diagnosed in 9 patients (4.9%). Univariable analysis showed that gait speed was a factor associated with readmission [HR=0.32, 95% CI (0.10-0.97), p=0.04] but not severe sarcopenia. In multivariable analysis, only diabetes was significantly associated with rehospitalization [HR=2.06, 95% CI (1.11-3.84), p=0.02]. Prevalence of severe sarcopenia varied according to different thresholds of skeletal muscle mass on CT-scan.

CONCLUSION

Even though severe sarcopenia was not correlated with rehospitalization and mortality at one year after TAVR, our results emphasize the changes in the prevalence according to cutoff used. It highlights the need to define standardized methods and international threshold for sarcopenia diagnosis by CT-scan measurements, in general population and for patients with valvular heart disease.

Sarcopenia in Patients Undergoing Transcatheter Aortic Valve Implantation (TAVI): A Systematic Review of the Literature

BACKGROUND

In older patients, sarcopenia is a prevalent disease associated with negative outcomes. Sarcopenia has been investigated in patients undergoing transcatheter aortic valve implantation (TAVI), but the criteria for diagnosis of the disease are heterogeneous. This systematic review of the current literature aims to evaluate the prevalence of sarcopenia in patients undergoing TAVI and to analyse the impact of sarcopenia on clinical outcomes.

METHODS

A comprehensive search of the literature has been performed in electronic databases from the date of initiation until March 2020. Using a pre-defined search strategy, we identified studies assessing skeletal muscle mass, muscle quality and muscle function as measures for sarcopenia in patients undergoing TAVI. We evaluated how sarcopenia affects the outcomes mortality at ≥1 year, prolonged length of hospital stay, and functional decline.

RESULTS

We identified 18 observational studies, enrolling a total number of 9'513 patients. For assessment of skeletal muscle mass, all included studies used data from computed tomography. Cut-off points for definition of low muscle mass were heterogeneous, and prevalence of sarcopenia varied between 21.0% and 70.2%. In uni- or multivariate regression analysis of different studies, low muscle mass was found to be a significant predictor of mortality, prolonged length of hospital stay, and functional decline. No interventional study was identified measuring the effect of nutritional or physiotherapy interventions on sarcopenia in TAVI patients.

CONCLUSIONS

Sarcopenia is highly prevalent among patients undergoing TAVI, and negatively affects important outcomes. Early diagnosis of this condition might allow a timely start of nutritional and physiotherapy interventions to prevent negative outcomes in TAVI patients.

Skeletal Muscle Characteristics May Inform Preprocedural Risk Stratification in Transcatheter Aortic Valve Replacement Patients

OBJECTIVES

Low psoas muscle mass previously has been associated with mortality after transcatheter aortic valve replacement (TAVR). Evidence from other clinical disciplines suggests that psoas density (PD) may be a better predictor than psoas muscle cross-sectional area indexed to body surface area (PI). The authors hypothesized that PD would be more strongly correlated with patient discharge disposition and survival after TAVR than PI.

DESIGN

The authors performed a single-center, retrospective study of TAVR patients from 2013 to 2016. PI and PD were assessed at the third lumbar spine level using computed tomography imaging. Propensity-score matching was used to investigate the association of PI and PD with discharge disposition and mortality.

SETTING

Tertiary university hospital PARTICIPANTS: Cohort of 245 TAVR patients.

INTERVENTIONS

None MEASUREMENTS AND MAIN RESULTS: A total of 245 patients met inclusion criteria. Following propensity score matching, patients with PI <4 cm²/m² and PD <25 Hounsfield units (HU) were less likely to survive and to be discharged home compared with patients with PI ≥4 cm²/m² or PD >25 HU. After repeating the propensity score matching with PI as a covariable, PD remained associated with mortality (90 days: odds ratio [OR] 4.59; 95% confidence interval [CI] 2.96-10.31, p < 0.001, 1 year: OR 6.14; 95% CI 3.45-28.57, p = 0.01, 3 years: OR 4.55; 95% CI 2.41-40.00, p = 0.03).

CONCLUSIONS

PD may be more relevant than PI in risk stratification for TAVR patients.