Temporalis muscle width as a measure of sarcopenia correlates with overall survival in patients with newly diagnosed glioblastoma

Hsieh, Kristin; Hwang, M.; Estevez-Inoa, Gabrielle; Save, Akshay; Saraf, Anurag; Spina, Catherine S.; Cheng, Simon K.; Wang, Tony J. C.; Wu, Cheng‐Chia

doi:10.1007/s13566-019-00408-9

Cited by 14 publications

(18 citation statements)

References 28 publications

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“…We found higher temporalis CSA was associated with significantly longer survival and time to progression in GBM with HR of 0.464 and 0.466, and HR of 0.433, consistent with studies of TMW reporting HRs of 0.41-0.79 for OS and 0.46-0.77 for PFS [10][11][12][13]. Sarcopenia is a key feature of cancer-related cachexia.…”

Section: Discussionsupporting

confidence: 88%

“…3D model training and application is also substantially slower with greatly increased computational memory cost, and it is unclear whether 3D temporalis segmentation would be of additional prognostic value. To ameliorate any potential loss of information with 2D segmentation (compared to 3D), we explored the relationship between temporalis muscle area at different orbital levels with survival, similar to previous studies that used the same anatomical landmarks [12]; the existence of a significant relationship at multiple orbital levels indicates generalisability. Our reason for exploring the robustness of the relationship at different orbital levels was also to facilitate our further work to develop a fully automated pipeline for temporalis segmentation with automatic slice selection based on orbital landmarks.…”

Section: Study Limitationsmentioning

confidence: 99%

“…However, GBM patients routinely undergo magnetic resonance imaging (MRI) head during follow-up, rather than body CT, so there is a need for measures of sarcopenia and skeletal muscle mass derivable from MRI head. The most widely studied is temporalis muscle width (TMW), which has been identified as a skeletal muscle mass surrogate [9] and a prognostic factor for OS and PFS in GBM [10][11][12][13] and brain metastases [14,15]. However, no studies have investigated temporalis CSA, which is likely to be a better indicator of muscle mass than width.…”

Section: Introductionmentioning

confidence: 99%

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Deep learning-based quantification of temporalis muscle has prognostic value in patients with glioblastoma

Mauricaite

Pakzad-Shahabi

et al. 2021

Br J Cancer

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Background Glioblastoma is the commonest malignant brain tumour. Sarcopenia is associated with worse cancer survival, but manually quantifying muscle on imaging is time-consuming. We present a deep learning-based system for quantification of temporalis muscle, a surrogate for skeletal muscle mass, and assess its prognostic value in glioblastoma. Methods A neural network for temporalis segmentation was trained with 366 MRI head images from 132 patients from 4 different glioblastoma data sets and used to quantify muscle cross-sectional area (CSA). Association between temporalis CSA and survival was determined in 96 glioblastoma patients from internal and external data sets. Results The model achieved high segmentation accuracy (Dice coefficient 0.893). Median age was 55 and 58 years and 75.6 and 64.7% were males in the in-house and TCGA-GBM data sets, respectively. CSA was an independently significant predictor for survival in both the in-house and TCGA-GBM data sets (HR 0.464, 95% CI 0.218–0.988, p = 0.046; HR 0.466, 95% CI 0.235–0.925, p = 0.029, respectively). Conclusions Temporalis CSA is a prognostic marker in patients with glioblastoma, rapidly and accurately assessable with deep learning. We are the first to show that a head/neck muscle-derived sarcopenia metric generated using deep learning is associated with oncological outcomes and one of the first to show deep learning-based muscle quantification has prognostic value in cancer.

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Section: Discussionsupporting

confidence: 88%

Section: Study Limitationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Deep learning-based quantification of temporalis muscle has prognostic value in patients with glioblastoma

Mauricaite

Pakzad-Shahabi

et al. 2021

Br J Cancer

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“…The unique aspect of this study is that TMT also functions as an independent predictor of glioblasts in the era of molecular staging of glioblastoma. The median overall survival of patients in the TMT > median group (17.5 months) was signi cantly higher than the median overall survival of patients in the median group (9 months) when data from 55 cases with molecular staging of glioblastoma alone were analyzed (P 0.001; Log-rank test).The potential use of TMT as a different oligomyelitis measure to predict survival in GBM patients has drawn more interest in recent years.In 87 patients with newly diagnosed GBM, TMT as determined by postoperative CT was investigated by Hsieh et al They discovered a correlation between TMT and OS in patients with GBM and that patients with thicker TMT had a longer median OS than patients with thinner TMT 12 .TMT was discovered by Huq et al to be related to signi cant GBM prognostic variables and to predict postoperative survival in patients with progressing GBM 13 .In untreated IDH1-2 wild-type, MGMT-methylated GBM patients, the predictive importance of TMT has been investigated in the past. This study indicated that TMT appeared to be useless as a measure for predicting survival in newly diagnosed and untreated IDH1-2 wild-type, MGMT-methylated GBM patients since there was no link between TMT and patient survival 14 .Although we used the same statistical techniques and grouping strategy for temporal muscle thickness as this study, our results were not the same.…”

Section: Discussionmentioning

confidence: 99%

The relationship between prognosis and temporal muscle thickness in 102 patients with primary glioblastoma:real-world evidence

Tang,

Dong,

Yang

et al. 2023

Preprint

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Temporal muscle thickness measured on 3D MRI has recently been linked to prognosis in glioblastoma patients and may serve as an independent prognostic indicator. This single-center study looked at temporal muscle thickness and prognosis in patients with primary glioblastoma. Overall survival was the major study outcome. For a retrospective analysis from 2010 to 2020, clinical data from 102 patients with glioblastoma at the Department of Oncology Radiotherapy of the First Affiliated Hospital of Dalian Medical University were gathered. Of these, 55 cases from 2016 to 2020 included glioblastoma molecular typing data, which were analyzed separately.TMT was measured using improved T1-weighted magnetic resonance imaging at the time of GBM diagnosis. The overall survival (OS) of the patients was calculated using the Kaplan-Meier technique, the differences between the groups were assessed using the log-rank test, and the clinical outcomes of the two groups were compared using the Cox proportional risk model and multifactorial analysis. In 102 patients, the median TMT was 6.775 mm (range 4.95–10.45). Patients were grouped according to median TMT, and those in the TMT > median group had a considerably longer median overall survival (23.0 months) than those in the TMT median group (P 0.001; Log-rank test). Data from 55 cases containing molecular staging of glioblastoma alone were analyzed, and the median overall survival of patients in the TMT > median group (17.5 months) was significantly increased compared with the median overall survival of patients in the ≤ median group (9 months) (P < 0.001; Log-rank test). We can concluded that TMT can serve as an independent predictor of survival prognosis in patients with primary GBM, as well as in the era of molecular typing.

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“…As such, it is unsurprising that sarcopenia has been linked with poor prognosis [11] as well as reduced ability to tolerate chemotherapy [12]. For example, in systemic diffuse large B cell lymphomas, sarcopenic patients have been shown to have two year survival of 46%, compared with 84% in nonsarcopenic patients [13].Temporalis muscle thickness (TMT) has become accepted as a radiographic measure of sarcopenia which is strongly correlated to survival in multiple neurologic diseases, including glioblastoma [14,15]. TMT is also been validated as highly predictive of grip strength, another frequently used measure of sarcopenia [16].…”

Section: Introductionmentioning

confidence: 99%

Sarcopenia Measured by Temporalis Muscle Thickness Independently Predicts Early Relapse and Short Survival in Primary CNS Lymphoma

Bonm¹,

Menghini²,

Graber³

2021

Preprint

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Introduction: Primary CNS lymphoma (PCNSL) outcomes diverge between a majority of patients who achieve long term remission and a smaller minority who have aggressive disease course and die in the first year. Sarcopenia is increasingly recognized as a powerful predictor of mortality in brain and systemic cancers. Temporalis muscle thickness (TMT) is a validated radiographic measure of sarcopenia. We hypothesized that patients with TMT less than one standard deviation below the mean (“very thin TMT”) would go on to have shorter survival. Methods: Two blinded operators retrospectively measured TMT in 99 consecutive pretreatment brain MRIs from patients that were subsequently diagnosed with PCNSL. Results: On univariate analysis TMT predicted early progression (HR 4.25, 95% CI 1.95 – 9.29, p<0.001) and early mortality (HR 4.38, 95% CI 2.25 – 8.53, p<0.001), and these effects were maintained in subgroups of patients both <65 and ³65 years of age. Very thin TMT predicted mortality more robustly than IELSG or MSKCC scores. Patients with very thin TMT received fewer cycles of high-dose methotrexate (HD-MTX) and were less likely to receive consolidation. On multivariate analysis which included the covariates age, sex, TMT, ECOG, BMI, lifetime doses of HD-MTX, and consolidation, very thin TMT was independently associated with both early progression (HR = 7.87, 95% CI = 3.55 – 17.45, p<0.001) and short survival (HR 4.49, 95% CI = 1.94 – 10.40, p<0.001). Conclusions: We conclude that PCNSL patients with very thin TMT are at high risk for relapse and early mortality. Future trials should stratify patients by TMT to avoid potential confounding.

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Temporalis muscle width as a measure of sarcopenia correlates with overall survival in patients with newly diagnosed glioblastoma

Cited by 14 publications

References 28 publications

Deep learning-based quantification of temporalis muscle has prognostic value in patients with glioblastoma

Deep learning-based quantification of temporalis muscle has prognostic value in patients with glioblastoma

The relationship between prognosis and temporal muscle thickness in 102 patients with primary glioblastoma:real-world evidence

Sarcopenia Measured by Temporalis Muscle Thickness Independently Predicts Early Relapse and Short Survival in Primary CNS Lymphoma

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