Opportunistic Computed Tomography Imaging for the Assessment of Fatty Muscle Fraction Predicts Outcome in Patients Undergoing Transcatheter Aortic Valve Replacement

HomeCirculationVol. 141, No. 3Opportunistic Computed Tomography Imaging for the Assessment of Fatty Muscle Fraction Predicts Outcome in Patients Undergoing Transcatheter Aortic Valve Replacement Free AccessLetterPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessLetterPDF/EPUBOpportunistic Computed Tomography Imaging for the Assessment of Fatty Muscle Fraction Predicts Outcome in Patients Undergoing Transcatheter Aortic Valve Replacement Julian A. Luetkens, MD, Anton Faron, MD, Helena L. Geissler, MD, Baravan Al-Kassou, MD, Jasmin Shamekhi, MD, Anja Stundl, MD, Alois M. Sprinkart, PhD, Carsten Meyer, MD, Rolf Fimmers, PhD, Hendrik Treede, MD, Eberhard Grube, MD, Georg Nickenig, MD, Jan-Malte Sinning, MD and Daniel Thomas, MD Julian A. LuetkensJulian A. Luetkens Julian A. Luetkens, MD, University Hospital Bonn, Department of Radiology, Venusberg-Campus 1, 53127 Bonn. Email E-mail Address: [email protected] University Hospital Bonn, Department of Radiology (J.A.L, A.F., H.L.G., A.M.S., C.M., D.T.), Bonn, Germany. , Anton FaronAnton Faron University Hospital Bonn, Department of Radiology (J.A.L, A.F., H.L.G., A.M.S., C.M., D.T.), Bonn, Germany. , Helena L. GeisslerHelena L. Geissler University Hospital Bonn, Department of Radiology (J.A.L, A.F., H.L.G., A.M.S., C.M., D.T.), Bonn, Germany. , Baravan Al-KassouBaravan Al-Kassou Department of Internal Medicine II (B.A.K., J.S., A.S., E.G., G.N., J.M.S.), Bonn, Germany. , Jasmin ShamekhiJasmin Shamekhi Department of Internal Medicine II (B.A.K., J.S., A.S., E.G., G.N., J.M.S.), Bonn, Germany. , Anja StundlAnja Stundl Department of Internal Medicine II (B.A.K., J.S., A.S., E.G., G.N., J.M.S.), Bonn, Germany. , Alois M. SprinkartAlois M. Sprinkart University Hospital Bonn, Department of Radiology (J.A.L, A.F., H.L.G., A.M.S., C.M., D.T.), Bonn, Germany. , Carsten MeyerCarsten Meyer University Hospital Bonn, Department of Radiology (J.A.L, A.F., H.L.G., A.M.S., C.M., D.T.), Bonn, Germany. , Rolf FimmersRolf Fimmers Department of Medical Biometry, Informatics, and Epidemiology (R.F.), Bonn, Germany. , Hendrik TreedeHendrik Treede Department of Cardio-Thoracic Surgery (H.T.), Bonn, Germany. , Eberhard GrubeEberhard Grube Department of Internal Medicine II (B.A.K., J.S., A.S., E.G., G.N., J.M.S.), Bonn, Germany. , Georg NickenigGeorg Nickenig Department of Internal Medicine II (B.A.K., J.S., A.S., E.G., G.N., J.M.S.), Bonn, Germany. , Jan-Malte SinningJan-Malte Sinning Department of Internal Medicine II (B.A.K., J.S., A.S., E.G., G.N., J.M.S.), Bonn, Germany. and Daniel ThomasDaniel Thomas University Hospital Bonn, Department of Radiology (J.A.L, A.F., H.L.G., A.M.S., C.M., D.T.), Bonn, Germany. Originally published20 Jan 2020https://doi.org/10.1161/CIRCULATIONAHA.119.042927Circulation. 2020;141:234–236Frailty is considered a major risk factor for adverse outcomes in patients undergoing transcatheter aortic valve replacement (TAVR). Previous studies proposed frailty scales to estimate procedural risk in these patients. However, assessment of these scales is time-consuming, and reported results are inconsistent.1–3 To some extent, this problem might be related to their semiquantitative nature with an inherent risk of interobserver variability. Because this may discourage the use of standardized frailty assessment in wide preinterventional diagnostic workup, international guidelines demand objective markers for estimation of frailty.2,3 Computed tomography (CT) is a substantial part of routine preinterventional workup and beyond that it allows for opportunistic body composition analysis, including assessment of muscle quality as an indicator of muscle function, which is interrelated with frailty.3,4This study aimed to investigate the prognostic value of fatty muscle fraction (FMF), measured from routine preinterventional CT, as an objective surrogate for frailty in patients undergoing TAVR for treatment of severe, symptomatic aortic stenosis.The institutional review board approved this retrospective study with waiver of informed consent. Consecutive patients undergoing TAVR at the University Hospital Bonn between 2010 and 2018 were evaluated with CT scans, and skeletal muscle area at the L3/L4 level was determined as previously reported.4 On the basis of densitometric thresholds, skeletal muscle area was separated in areas of fatty and lean muscle and FMF was calculated (Figure, A).Download figureDownload PowerPointFigure. Summary of study results. A, Synopsis of body composition analysis. Ai, Single-slice cross-sectional computed tomography (CT) images at the level of the intervertebral disc space L3/L4 were used for analysis. Aii, Abdominal skeletal muscles (purple) were separated from adipose tissue compartments (green, subcutaneous adipose tissue; pink, visceral adipose tissue) as well remaining ambient tissues based on densitometric thresholds. Aiii, Mean muscle attenuation of the entire skeletal muscle area was obtained to visualize overall myosteatosis. Aiv, To quantify muscular fat infiltration as a measure of muscle quality, the skeletal muscle area was separated into areas of fatty and lean muscle using attenuation thresholds of -30 to 29 Hounsfield units (HU) and 30 to 100 HU, respectively. Areas of fatty and lean muscle are highlighted by areas of light and dark blue within the skeletal muscle compartment, respectively. B, Fatty muscle fraction (FMF) was calculated as the fraction of fatty muscle referred to the total skeletal muscle area. Patients were divided into tertiles and defined to have low (<37.3%), medium (51.8-37.3%), and high (>51.8%) FMF, respectively. Panels highlight exemplary female and male patients with low, medium, and high FMF and corresponding 1-year mortality rates. C, Kaplan-Meier curves illustrating 1-year survival of the entire study population (N=937) stratified by FMF. On log-rank test, 1-year survival significantly decreased in the order of low, medium, and high FMF (P<0.001). Numbers at risk are given 0, 120, 240, and 365 days after transcatheter aortic valve replacement (TAVR). Vertical lines refer to censored events. D, Penalized cubic regression spline graph of relative mortality risk according to fatty muscle infiltration normalized for 50% FMF. Spline curve is plotted with 95% confidence intervals. FMF percentage is given on the x-axis. Interaction analysis did not reveal any evidence of a significant interaction between gender and mortality risk.SPSS Statistics 24 (IBM, Armonk, NY, USA) and Prism 8 (GraphPad Software, La Jolla, CA, USA) were used for statistical analysis. The cohort was subdivided into tertiles with cutoff values of >51.8%, 51.8 to 37.3%, and <37.3% to define high, medium, and low FMF, respectively. One-way ANOVA followed by Tukey's multiple comparison tests were used to compare baseline variables and FMF on outcomes. Spearman correlation coefficients were used to test correlation between continuous markers of frailty and FMF. Kaplan-Meier log-rank tests were applied to compare survival curves across the 3 groups, and an adjusted Cox regression including a set of clinically relevant covariates, was fit to test the impact of clinical variables on 1-year mortality. Linearity between covariates and outcome was tested using penalized cubic spline regression analysis.Among 1491 patients undergoing TAVR, 937 had interpretable CT scans and were included in the analytic cohort. Patients with high FMF were less likely to be male (34.0% versus 46.3% versus 66.3%; P<0.001), were older (82.7±5.8 years versus 81.7±5.5 years versus 78.9±6.7 years; P<0.001), and had higher body mass index (26.8±4.7 kg/m2 ± 26.8±4.9 kg/m2 versus 25.4±4.2 kg/m2; P<0.001) compared to patients with medium and low FMF. According to EuroSCORE II, preinterventional risk did not differ significantly between these groups (7.2±6.0% versus 6.6±6.7% versus 6.4±6.3%, P=0.330). Higher FMF was strongly associated with increased 1-year (20.8% versus 14.7% versus 9.3 %; P<0.001), 2-year (27.2% versus 20.4% versus 15.7 %; P=0.002), and 3-year mortality (30.8% versus 24.0% versus 19.2 %; P=0.009) (Figure, B and C]). Spline analysis did not reveal any evidence of nonlinearity of the interrelationship between FMF and mortality (Figure, D). On multivariable risk factor analysis, FMF was identified as a predictor of 1-year mortality (hazard ratio [HR] per SD increment 1.641 [95% CI, 1.295–2.079]; P<0.001), independent from EuroSCORE II, year of intervention, creatinine at baseline, age, sex, and body mass index. In a subgroup of patients (n=425), albumin and hemoglobin as laboratory markers of frailty were available for analysis. FMF was correlated with these markers (albumin, r=−0.186; hemoglobin, r=−0.151; both P<0.001). For this subgroup, an additional regression model was calculated including all aforementioned variables and also albumin and hemoglobin. In this model, FMF remained as a predictor of 1-year mortality (HR per SD increment, 1.555 [95% CI, 1.067–2.268]; P=0.022) while albumin and hemoglobin were not associated with outcome (P>0.5, respectively).Skeletal muscle fat infiltration is known to be related to age and obesity.5 Accordingly, patients with higher FMF were older and had higher body mass index in our study. Compared to the assessment of other frailty markers, FMF can be quickly calculated from routine diagnostic images, does not require additional equipment, and is an objective and normalized measure of muscle quality.1,2 In clinical routine, the radiologist could report FMF alongside with other important TAVR planning parameters.3 Although in our study body composition was assessed using an in-house software,4 also several commercially available applications exist for this purpose. In the future, these applications could be automated with the help of machine learning. Post-processing algorithms could help to reduce metal artifacts, which may affect the accuracy of measurements for example in patients with lumbar spine implants. In conclusion, our results indicate CT-derived FMF as a potentially new frailty marker, which provides additional information for risk stratification in TAVR patients. Future studies should explore the clinical value of FMF compared with other frailty markers and the prognostic role of FMF for other cardiovascular and oncologic diseases.DisclosuresNone.Footnotes*Drs Luetkens, Faron, Sinning, and Thomas contributed equally.https://www.ahajournals.org/journal/circData are available on request from the authors.Julian A. Luetkens, MD, University Hospital Bonn, Department of Radiology, Venusberg-Campus 1, 53127 Bonn. Email julian.[email protected]deReferences1. Afilalo J, Lauck S, Kim DH, Lefèvre T, Piazza N, Lachapelle K, Martucci G, Lamy A, Labinaz M, Peterson MD, et al. Frailty in older adults undergoing aortic valve replacement: the FRAILTY-AVR study.J Am Coll Cardiol. 2017; 70:689–700. doi: 10.1016/j.jacc.2017.06.024CrossrefMedlineGoogle Scholar2. Shimura T, Yamamoto M, Kano S, Kagase A, Kodama A, Koyama Y, Tsuchikane E, Suzuki T, Otsuka T, Kohsaka S, et al; OCEAN-TAVI Investigators. Impact of the clinical frailty scale on outcomes after transcatheter aortic valve replacement.Circulation. 2017; 135:2013–2024. doi: 10.1161/CIRCULATIONAHA.116.025630LinkGoogle Scholar3. Baumgartner H, Falk V, Bax JJ, De Bonis M, Hamm C, Holm PJ, Iung B, Lancellotti P, Lansac E, Rodriguez Muñoz D, et al; ESC Scientific Document Group. 2017 ESC/EACTS guidelines for the management of valvular heart disease.Eur Heart J. 2017; 38:2739–2791. doi: 10.1093/eurheartj/ehx391CrossrefMedlineGoogle Scholar4. Faron A, Luetkens JA, Schmeel FC, Kuetting DLR, Thomas D, Sprinkart AM. 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