Literature DB >> 24079810

Temporalis muscle morphomics: the psoas of the craniofacial skeleton.

Kavitha Ranganathan1, Michael Terjimanian, Jeffrey Lisiecki, Jacob Rinkinen, Anudeep Mukkamala, Cameron Brownley, Steven R Buchman, Stewart C Wang, Benjamin Levi.   

Abstract

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.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Mandible fracture; Morphomics; Psoas muscle; Sarcopenia; Temporal fat pad; Temporalis muscle

Mesh:

Year:  2013        PMID: 24079810     DOI: 10.1016/j.jss.2013.07.059

Source DB:  PubMed          Journal:  J Surg Res        ISSN: 0022-4804            Impact factor:   2.192


  18 in total

1.  Temporal muscle thickness is an independent prognostic marker in patients with progressive glioblastoma: translational imaging analysis of the EORTC 26101 trial.

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

2.  Morphomic analysis as an aid for preoperative risk stratification in patients undergoing major head and neck cancer surgery.

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

3.  Computed Tomography Evidence of Psoas Muscle Atrophy Without Concomitant Tendon Wasting in Early Sepsis.

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

4.  Sarcopenia in patients with dementia: correlation of temporalis muscle thickness with appendicular muscle mass.

Authors:  Jangho Cho; Mina Park; Won-Jin Moon; Seol-Heui Han; Yeonsil Moon
Journal:  Neurol Sci       Date:  2021-11-30       Impact factor: 3.830

5.  Can Sarcopenia Quantified by Ultrasound of the Rectus Femoris Muscle Predict Adverse Outcome of Surgical Intensive Care Unit Patients as well as Frailty? A Prospective, Observational Cohort Study.

Authors:  Noomi Mueller; Sushila Murthy; Christopher R Tainter; Jarone Lee; Kathleen Riddell; Florian J Fintelmann; Stephanie D Grabitz; Fanny P Timm; Benjamin Levi; Tobias Kurth; Matthias Eikermann
Journal:  Ann Surg       Date:  2016-12       Impact factor: 12.969

6.  Postsurgical functional outcome prediction model using deep learning framework (Prediction One, Sony Network Communications Inc.) for hypertensive intracerebral hemorrhage.

Authors:  Masahito Katsuki; Yukinari Kakizawa; Akihiro Nishikawa; Yasunaga Yamamoto; Toshiya Uchiyama
Journal:  Surg Neurol Int       Date:  2021-05-03

7.  Survival prediction using temporal muscle thickness measurements on cranial magnetic resonance images in patients with newly diagnosed brain metastases.

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

8.  Endoscopic hematoma removal of supratentorial intracerebral hemorrhage under local anesthesia reduces operative time compared to craniotomy.

Authors:  Masahito Katsuki; Yukinari Kakizawa; Akihiro Nishikawa; Yasunaga Yamamoto; Toshiya Uchiyama
Journal:  Sci Rep       Date:  2020-06-25       Impact factor: 4.379

9.  High correlation of temporal muscle thickness with lumbar skeletal muscle cross-sectional area in patients with brain metastases.

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

10.  Temporal muscle thickness is an independent prognostic marker in melanoma patients with newly diagnosed brain metastases.

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

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