Share:
Share this content in WeChat
X
Clinical Article
Predictive value of temporal muscle thickness measurements on cranial magnetic resonance images in the prognosis of patients with primary glioblastoma
LIU Fang  XING Dong  ZHA Yunfei  LI Liang  GONG Wei  HU Lei 

Cite this article as: Liu F, Xing D, Zha YF, et al. Predictive value of temporal muscle thickness measurements on cranial magnetic resonance images in the prognosis of patients with primary glioblastoma. Chin J Magn Reson Imaging, 2020, 11(1): 20-24. DOI:10.12015/issn.1674-8034.2020.01.005.


[Abstract] Objective: To investigate the predictive value of prognosis in patients with glioblastoma (GBM) by temporal muscle thickness (TMT) on three-dimensional MR images of the brain.Materials and Methods: One hundred and six primary GBM patients from the TCGA-GBM database were analyzed retrospectively. TMT was measured on three-dimensional MR images of the brain, and 30 patients were randomly selected for repetitive measurement by a second radiologist to calculate the inter-class correlation (ICC). The Kaplan-Meier curve was used to calculate the overall survival time of the patients. The median survival time was compared by Log-rank test. The Cox regression model was used for multivariate analysis.Results: TMT was reproducibly assessable on three-dimensional MR images, and the ICC calculated by two radiologists of the left and right side TMT were 0.878 and 0.895 (P<0.001). Decreased TMT is a risk factor related to the prognosis in the patients with GBM, with a hazard ratio (HR) of 0.787 (95%CI 0.678-0.913; P=0.002; Cox regression model). That was the risk of death would increase by 21.3% with every millimeter decrease in TMT. Grouped by median TMT, patients with a TMT> median showed a significant increase in survival time (17.4 months) compared to patients with a TMT<median (9.4 months)(P<0.001; Log-rank test). In the multivariate survival analysis using a Cox regression model, TMT (HR 0.850; 95%CI 0.734-0.984; P=0.03), tumor diagnosis age (HR 1.037; 95%CI 1.018—1.056; P<0.001) and concurrent chemoradiotherapy (HR 0.567; 95%CI 0.371—0.868; P=0.009) were dramatically associated with survival time.Conclusions: TMT can be used as an independent predictor of survival prognosis in patients with primary glioblastoma and contributes to assess the survival time of them.
[Keywords] glioblastoma;temporal muscle thickness;magnetic resonance imaging;overall survival time;sarcopenia

LIU Fang Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, China

XING Dong Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, China

ZHA Yunfei* Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, China

LI Liang Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, China

GONG Wei Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, China

HU Lei Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, China

*Correspondence to: Zha YF, E-mail: zhayunfei999@126.com

Conflicts of interest   None.

ACKNOWLEDGMENTS  This thesis is sponsored by the National Natural Science Foundation of China No. 81801670, 81871332
Received  2019-09-26
Accepted  2019-11-21
DOI: 10.12015/issn.1674-8034.2020.01.005
Cite this article as: Liu F, Xing D, Zha YF, et al. Predictive value of temporal muscle thickness measurements on cranial magnetic resonance images in the prognosis of patients with primary glioblastoma. Chin J Magn Reson Imaging, 2020, 11(1): 20-24. DOI:10.12015/issn.1674-8034.2020.01.005.

[1]
Ostrom QT, Bauchet L, Davis FG, et al. The epidemiology of glioma in adults: a "state of the science" review. Neuro Oncol, 2014, 16(7): 896-913.
[2]
刘琦,熊丽,田少斌,等.原发性胶质母细胞瘤预后危险因素分析.中国临床神经外科杂志, 2016, 21(6): 341-343.
[3]
Miller CR, Dunham CP, Scheithauer BW, et al. Significance of necrosis in grading of oligodendroglial neoplasms: a clinicopathologic and genetic study of newly diagnosed high-grade gliomas. J Clin Oncol, 2006, 24(34): 5419-5426.
[4]
魏若伦,陈若琨,薛亚轲,等.胶质母细胞瘤的预后影响因素分析.中国微侵袭神经外科杂志, 2018, 23(9): 393-396.
[5]
梁进华,刘湘衡,白红民,等.多形性胶质母细胞瘤的预后影响因素分析.中华神经外科杂志, 2016, 32(8): 831-835.
[6]
马洁玲,艾林. MRI在胶质母细胞瘤患者预后的应用进展.磁共振成像, 2015, 6(5): 394-400.
[7]
Furtner J, Berghoff AS, Albtoush OM, et al. Survival prediction using temporal muscle thickness measurements on cranial magnetic resonance images in patients with newly diagnosed brain metastases. Eur Radiol, 2017, 27(8): 3167-3173.
[8]
Furtner J, Berghoff AS, Schöpf V, et al. Temporal muscle thickness is an independent prognostic marker in melanoma patients with newly diagnosed brain metastases. J Neuro Oncol, 2018, 140(1): 173-178.
[9]
Furtner J, Genbrugge E, Gorlia T, et al. Temporal muscle thickness is an independent prognostic marker in patients with progressive glioblastoma: translational imaging analysis of the EORTC 26101 trial. Neuro Oncol, 2019. DOI:
[10]
Prior F, Smith K, Sharma A, et al. The public cancer radiology imaging collections of the cancer imaging archive. Sci Data, 2017, 4: 170124.
[11]
Sinelnikov A, Qu C, Fetzer DT, et al. Measurement of skeletal muscle area: comparison of CT and MR imaging. Eur J Radiol, 2016, 85(10): 1716-1721.
[12]
Di Sebastiano KM, Mourtzakis M. A critical evaluation of body composition modalities used to assess adipose and skeletal muscle tissue in cancer. Appl Physiol Nutr Metab, 2012, 37(5): 811-821.
[13]
Heymsfield SB, Adamek M, Gonzalez MC, et al. Assessing skeletal muscle mass: historical overview and state of the art. J Cachexia Sarcopenia Muscle, 2014, 5(1): 9-18.
[14]
Portal D, Hofstetter L, Eshed I, et al. L3 skeletal muscle index (L3SMI) is a surrogate marker of sarcopenia and frailty in non-small cell lung cancer patients. Cancer Manag Res, 2019, 11: 2579-2588.
[15]
Heymsfield SB, Gonzalez MC, Lu J, et al. Skeletal muscle mass and quality: evolution of modern measurement concepts in the context of sarcopenia. Proc Nutr Soc, 2015, 74(4): 355-366.
[16]
Ranganathan K, Terjimanian M, Lisiecki J, et al. Temporalis muscle morphomics: the psoas of the craniofacial skeleton. J Surg Res, 2014, 186(1): 246-252.
[17]
Leitner J, Pelster S, Schöpf V, et al. High correlation of temporal muscle thickness with lumbar skeletal muscle cross-sectional area in patients with brain metastases. PloS One, 2018, 13(11): e207849.
[18]
White JV, Guenter P, Jensen G, et al. Consensus statement: academy of nutrition and dietetics and American Society for Parenteral and Enteral Nutrition: characteristics recommended for the identification and documentation of adult malnutrition (undernutrition). JPEN J Parenter Enteral Nutr, 2012, 36(3): 275-83
[19]
Hasegawa Y, Yoshida M, Sato A, et al. Temporal muscle thickness as a new indicator of nutritional status in older individuals. Geriatr Gerontol Int, 2019, 19(2): 135-140.
[20]
van Vugt JLA, Levolger S, Gharbharan A, et al. A comparative study of software programmes for cross-sectional skeletal muscle and adipose tissue measurements on abdominal computed tomography scans of rectal cancer patients. J Cachexia, Sarcopenia Muscle, 2017, 8(2): 285-297.
[21]
Gomez-Perez SL, Haus JM, Sheean P, et al. Measuring abdominal circumference and skeletal muscle from a single cross-sectional computed tomography image. J Parenter Enteral Nutr, 2015, 40(3): 308-318.
[22]
Grunheid T, Langenbach GEJ, Korfage JAM, et al. The adaptive response of jaw muscles to varying functional demands. Eur J Orthod, 2009, 31(6): 596-612.

PREV MRI typing study of microcystic meningiomas
NEXT The research value of quantitative study of parotid gland fat infiltration in early Sjogren,s syndrome patients by using 3.0 T MR IDEAL-IQ sequence
  



Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn