BACKGROUND: The psoas muscle has been shown to predict patient outcomes based on the quantification of muscle area using computed tomography (CT) scans. The accuracy of morphomic analysis on other muscles has not been clearly delineated. In this study, we determine the correlation between temporalis muscle mass, psoas muscle area, age, body mass index (BMI), and gender. METHODS: Temporalis and psoas muscle dimensions were determined on all trauma patients who had both abdominal and maxillofacial CT scans at the University of Michigan between 2004 and 2011. Age, BMI, and gender were obtained through chart review. Univariate and multivariate analyses were performed to determine the relative relationship between morphomic data of the temporalis and psoas muscles and the ability of such information to correspond with clinical variables, such as BMI, age, and gender. RESULTS: A total of 646 patients were included in the present study. Among the 249 (38.5%) women and 397 (61.5%) men, the average age was 49.2 y. Average BMI was 27.9 kg/m². Total psoas muscle area directly correlated with mean temporalis muscle thickness (r = 0.57, P < 0.001). There was an indirect correlation between age and psoas muscle area (r = -0.52, P < 0.001) and temporalis muscle thickness (r = -0.36, P < 0.001). Neither psoas nor temporalis measurements correlated strongly with BMI (r = 0.18, P < 0.001; r = 0.14, P = 0.002), although stronger correlations were found in a more "frail," subgroup as defined by a BMI of <20 (r = 0.59, P = 0.002). CONCLUSIONS: We demonstrate that dimensions of the temporalis muscle can be quantified and may serve as a proxy for age. Going forward, we aim to assess the utility of temporalis and psoas morphomics in predicting complication rates among trauma patients admitted to the hospital to predict outcomes in the future.
BACKGROUND: The psoas muscle has been shown to predict patient outcomes based on the quantification of muscle area using computed tomography (CT) scans. The accuracy of morphomic analysis on other muscles has not been clearly delineated. In this study, we determine the correlation between temporalis muscle mass, psoas muscle area, age, body mass index (BMI), and gender. METHODS: Temporalis and psoas muscle dimensions were determined on all traumapatients who had both abdominal and maxillofacial CT scans at the University of Michigan between 2004 and 2011. Age, BMI, and gender were obtained through chart review. Univariate and multivariate analyses were performed to determine the relative relationship between morphomic data of the temporalis and psoas muscles and the ability of such information to correspond with clinical variables, such as BMI, age, and gender. RESULTS: A total of 646 patients were included in the present study. Among the 249 (38.5%) women and 397 (61.5%) men, the average age was 49.2 y. Average BMI was 27.9 kg/m². Total psoas muscle area directly correlated with mean temporalis muscle thickness (r = 0.57, P < 0.001). There was an indirect correlation between age and psoas muscle area (r = -0.52, P < 0.001) and temporalis muscle thickness (r = -0.36, P < 0.001). Neither psoas nor temporalis measurements correlated strongly with BMI (r = 0.18, P < 0.001; r = 0.14, P = 0.002), although stronger correlations were found in a more "frail," subgroup as defined by a BMI of <20 (r = 0.59, P = 0.002). CONCLUSIONS: We demonstrate that dimensions of the temporalis muscle can be quantified and may serve as a proxy for age. Going forward, we aim to assess the utility of temporalis and psoas morphomics in predicting complication rates among traumapatients admitted to the hospital to predict outcomes in the future.
Authors: Julia Furtner; Els Genbrugge; Thierry Gorlia; Martin Bendszus; Martha Nowosielski; Vassilis Golfinopoulos; Michael Weller; Martin J van den Bent; Wolfgang Wick; Matthias Preusser Journal: Neuro Oncol Date: 2019-12-17 Impact factor: 12.300
Authors: Jacob Rinkinen; Shailesh Agarwal; Jeff Beauregard; Oluseyi Aliu; Matthew Benedict; Steven R Buchman; Stewart C Wang; Benjamin Levi Journal: J Surg Res Date: 2014-10-07 Impact factor: 2.192
Authors: Carrie A Kubiak; Kavitha Ranganathan; Niki Matusko; Jon A Jacobson; Stewart C Wang; Pauline K Park; Benjamin L Levi Journal: J Surg Res Date: 2018-10-11 Impact factor: 2.192
Authors: Julia Furtner; Anna S Berghoff; Omar M Albtoush; Ramona Woitek; Ulrika Asenbaum; Daniela Prayer; Georg Widhalm; Brigitte Gatterbauer; Karin Dieckmann; Peter Birner; Bernadette Aretin; Rupert Bartsch; Christoph C Zielinski; Veronika Schöpf; Matthias Preusser Journal: Eur Radiol Date: 2017-01-03 Impact factor: 5.315
Authors: Johannes Leitner; Sebastian Pelster; Veronika Schöpf; Anna S Berghoff; Ramona Woitek; Ulrika Asenbaum; Karl-Heinz Nenning; Georg Widhalm; Barbara Kiesel; Brigitte Gatterbauer; Karin Dieckmann; Peter Birner; Daniela Prayer; Matthias Preusser; Julia Furtner Journal: PLoS One Date: 2018-11-29 Impact factor: 3.240
Authors: Julia Furtner; Anna S Berghoff; Veronika Schöpf; Robert Reumann; Benjamin Pascher; Ramona Woitek; Ulrika Asenbaum; Sebastian Pelster; Johannes Leitner; Georg Widhalm; Brigitte Gatterbauer; Karin Dieckmann; Christoph Höller; Daniela Prayer; Matthias Preusser Journal: J Neurooncol Date: 2018-07-14 Impact factor: 4.130