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

The relationship between prognosis and temporal muscle thickness in 102 patients with glioblastoma

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. Fifty-five cases from 2016 to 2020 contained glioblastoma molecular typing data, of which 45 were IDH wild-type glioblastomas and were analysed separately. TMT was measured on enhanced T1-weighted magnetic resonance images in patients with newly diagnosed glioblastoma.Overall patient survival (OS) was calculated by the Kaplan-Meier method and survival curves were plotted using the log-rank-sum test to determine differences between groups, and multifactorial analyses were performed using a Cox proportional-risk model.The median TMT for 102 patients was 6.775 mm (range: 4.95-10.45 mm). Patients were grouped according to median TMT, and the median overall survival (23.0 months) was significantly longer in the TMT > median group than in the TMT median group (P 0.001; Log-rank test). Analysing 45 patients with IDH wild type alone, the median overall survival (12 months) of patients in the TMT > median group was significantly longer than that of patients in the TMT ≤ median group (8 months) (P < 0.001; Log-rank test).TMT can serve as an independent prognostic factor for glioblastoma.

The prognostic utility of temporalis muscle thickness measured on magnetic resonance scans in patients with intra-axial malignant brain tumours: A systematic review and meta-analysis

Introduction

Sarcopenia is associated with worsened outcomes in solid cancers. Temporalis muscle thickness (TMT) has emerged as a measure of sarcopenia. Hence, this study aims to evaluate the relationship between TMT and outcome measures in patients with malignant intra-axial neoplasms.

Method

We searched Medline, Embase, Scopus and Cochrane databases for relevant studies. Event ratios with 95% confidence intervals (CI) were analysed using the RevMan 5.4 software. Where meta-analysis was impossible, vote counting was used to determine the effect of TMT on outcomes. The GRADE framework was used to determine the certainty of the evidence.

Results

Four outcomes were reported for three conditions across 17 studies involving 4430 patients. Glioblastoma: thicker TMT was protective for overall survival (OS) (HR 0.59; 95% CI 0.46-0.76) (GRADE low), progression free survival (PFS) (HR 0.40; 95% CI 0.26-0.62) (GRADE high), and early discontinuation of treatment (OR 0.408; 95% CI 0.168-0.989) (GRADE high); no association with complications (HR 0.82; 95% CI 0.60-1.10) (GRADE low). Brain Metastases: thicker TMT was protective for OS (HR 0.73; 95% CI 0.67-0.78) (GRADE moderate); no association with PFS (GRADE low). Primary CNS Lymphoma: TMT was protective for overall survival (HR 0.34; 95% CI 0.19-0.60) (GRADE moderate) and progression free survival (HR 0.23; 95% CI 0.09-0.56) (GRADE high).

Conclusion

TMT has significant prognostic potential in intra-axial malignant neoplasms, showing a moderate to high certainty for its association with outcomes following GRADE evaluation. This will enable shared decision making between patients and clinicians.

Automated temporalis muscle quantification and growth charts for children through adulthood

Lean muscle mass (LMM) is an important aspect of human health. Temporalis muscle thickness is a promising LMM marker but has had limited utility due to its unknown normal growth trajectory and reference ranges and lack of standardized measurement. Here, we develop an automated deep learning pipeline to accurately measure temporalis muscle thickness (iTMT) from routine brain magnetic resonance imaging (MRI). We apply iTMT to 23,876 MRIs of healthy subjects, ages 4 through 35, and generate sex-specific iTMT normal growth charts with percentiles. We find that iTMT was associated with specific physiologic traits, including caloric intake, physical activity, sex hormone levels, and presence of malignancy. We validate iTMT across multiple demographic groups and in children with brain tumors and demonstrate feasibility for individualized longitudinal monitoring. The iTMT pipeline provides unprecedented insights into temporalis muscle growth during human development and enables the use of LMM tracking to inform clinical decision-making.

Advances in the relationship between temporal muscle thickness and prognosis of patients with glioblastoma: a narrative review

The most dangerous variety of glioma, glioblastoma, has a high incidence and fatality rate. The prognosis for patients is still bleak despite numerous improvements in treatment approaches. We urgently need to develop clinical parameters that can evaluate patients' conditions and predict their prognosis. Various parameters are available to assess the patient's preoperative performance status and degree of frailty, but most of these parameters are subjective and therefore subject to interobserver variability. Sarcopenia can be used as an objective metric to measure a patient's physical status because studies have shown that it is linked to a bad prognosis in those with cancers. For the purpose of identifying sarcopenia, temporal muscle thickness has demonstrated to be a reliable alternative for a marker of skeletal muscle content. As a result, patients with glioblastoma may use temporal muscle thickness as a potential marker to correlate with the course and fate of their disease. This narrative review highlights and defines the viability of using temporal muscle thickness as an independent predictor of survival in glioblastoma patients, and it evaluates recent research findings on the association between temporal muscle thickness and prognosis of glioblastoma patients.

Prognostic value of temporal muscle thickness, a novel radiographic marker of sarcopenia, in patients with brain tumor: A systematic review and meta-analysis

Sarcopenia has been identified as a prognostic factor among certain types of cancer. However, it is unclear whether there is prognostic value of temporalis muscle thickness (TMT), a potential surrogate for sarcopenia, in adults patients with brain tumors. Therefore, we searched the Medline, Embase, and PubMed to systematically review and meta-analyze the relationship between TMT and overall survival, progression-free survival, and complications in patients with brain tumors and the hazard ratio (HR) or odds ratios (OR), and 95% confidence interval (CI) were evaluated. The quality in prognostic studies (QUIPS) instrument was employed to evaluate study quality. Nineteen studies involving 4570 patients with brain tumors were included for qualitative and quantitative analysis. Meta-analysis revealed thinner TMT was associated with poor overall survival (HR, 1.72; 95% CI, 1.45-2.04; P < 0.01) in patients with brain tumors. Sub-analyses showed that the association existed for both primary brain tumors (HR, 2.02; 95% CI, 1.55-2.63) and brain metastases (HR, 1.39; 95% CI, 1.30-1.49). Moreover, thinner TMT also was the independent predictor of progression-free survival in patients with primary brain tumors (HR, 2.88; 95% CI, 1.85-4.46; P < 0.01). Therefore, to improve clinical decision making it is important to integrate TMT assessment into routine clinical settings in patients with brain tumors.

Temporalis muscle thickness predicts early relapse and short survival in primary CNS lymphoma

Background

Most patients with primary CNS lymphoma (PCNSL) achieve durable remission whereas a minority die in the first year. Sarcopenia is a powerful predictor of mortality in the brain and systemic cancers. Temporalis muscle thickness (TMT) is a validated radiographic measure of sarcopenia. We hypothesized that patients with thin TMT at diagnosis would have early progression and short survival.

Methods

Two blinded operators retrospectively measured TMT in 99 consecutive brain MRIs from untreated patients with PCNSL.

Results

We generated a receiver operator characteristic curve and chose a single threshold defining thin TMT in all patients as <5.65 mm, at which specificity and sensitivity for 1-year progression were 98.4% and 29.7% and for 1-year mortality were 97.4% and 43.5% respectively. Those with thin TMT were both more likely to progress (P < .001) and had higher rates of mortality (P < .001). These effects were independent of the effect of age, sex, and Eastern Cooperative Oncology Group performance status in a cox regression. Memorial Sloan Kettering Cancer Center score did not predict progression-free survival or overall survival as well as TMT. Patients with thin TMT received fewer cycles of high-dose methotrexate and were less likely to receive consolidation but neither variable could be included in the Cox regression due to violation of the proportional hazards assumption.

Conclusions

We conclude that PCNSL patients with thin TMT are at high risk for early relapse and short survival. Future trials should stratify patients by TMT to avoid confounding.

The possible relation between temporal muscle mass and glioblastoma multiforme prognosis via sarcopenia perspective

BACKGROUND

The optimal sarcopenia measurement method in patients with a diagnosis of glioblastoma multiforme (GBM) is unknown. It has been found that temporal muscle thickness (TMT) may reflect sarcopenia and be associated with survival, but the relationship between temporal muscle area (TMA) and GBM prognosis has never been evaluated before. The primary outcome of the study was to evaluate the relationship between TMA/TMT and overall survival (OS) time in newly diagnosed GBM patients.

METHODS

The data of patients who presented at the university hospital between January 2009 and January 2019 with a confirmed diagnosis of glioblastoma multiforme at the time of diagnosis were analyzed retrospectively. Temporal muscle thickness and TMA were measured retrospectively from preoperative MRIs of patients diagnosed with GBM. Due to the small number of patients and the failure to determine a cut-off value with acceptable sensitivity and specificity using ROC analysis, the median values were chosen as the cut-off value. The patients were basically divided into two according to their median TMT (6.6 mm) or TMA (452 mm2 ) values, and survival analysis was performed with the Kaplan-Meier analysis.

RESULTS

The median TMT value was 6.6 mm, and the median TMA value was 452 mm2 . The median overall survival (OS) was calculated as 25.8 months in patients with TMT < 6.6 mm, and 15.8 months in patients with TMT ≥ 6.6 mm (p = 0.29). The median overall survival (OS) of patients with TMA < 452mm2 was 26.3 months, and the group with TMA ≥ 452mm2 was 14.6 months (p = 0.06). The median disease-free survival was 18.3 months (%95 CI: 13.2-23.4) in patients with TMT < 6.6mm, while mDFS was 10.9 (%95 CI: 8.0-13.8) months in patients with TMT ≥ 6.6mm (p = 0.21). The median disease-free survival was found to be 21.0 months (%95 CI: 15.8-26.1) in patients with TMA < 452 mm2 and 10.5 months (%95 CI: 7.8-13.2) in patients with TMA ≥ 452 mm2 (p = 0.018).

DISCUSSION

No association could be demonstrated between TMT or TMA and OS of GBM patients. In addition, the median DFS was found to be longer in patients with low TMA. There is an unmet need to determine the optimal method of sarcopenia in GBM patients.

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

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.

The association of BMI and sarcopenia with survival in patients with glioblastoma multiforme

Background: The association between obesity and sarcopenia (via temporal muscle thickness) with overall survival (OS) has been evaluated in several glioblastoma multiforme studies, however, the data are inconclusive. Methods: The authors conducted meta-analyses via the generic inverse-variance method with a random-effects model. Results: In the pooled analysis of five studies, including 973 patients, patients with lower temporal muscle thickness had significantly decreased OS (HR: 1.62, 95% CI: 1.16-2.28, p = 0.005). The pooled analysis of five studies, including 2131 patients, demonstrated decreased OS in patients with lower BMI compared with patients with obesity (HR: 1.45, 95% CI: 1.12-1.88, p = 0.005). Conclusion: Readily available body composition parameters could be used for prognosis prediction and to aid in treatment decisions in patients with glioblastoma multiforme.

A novel radiographic marker of sarcopenia with prognostic value in glioblastoma

OBJECTIVE

Sarcopenia is an important prognostic consideration in surgical oncology that has received relatively little attention in brain tumor patients. Temporal muscle thickness (TMT) has recently been proposed as a novel radiographic marker of sarcopenia that can be efficiently obtained within existing workflows. We investigated the prognostic value of TMT in primary and progressive glioblastoma.

METHODS

TMT measurements were performed on magnetic resonance images of 384 patients undergoing 541 surgeries for glioblastoma. Relationships between TMT and clinical characteristics were examined on bivariate analysis. Optimal TMT cutpoints were established using maximally selected rank statistics. Predictive value of TMT upon postoperative survival (PS) was assessed using Cox proportional hazards regression adjusted for age, sex, Karnofsky performance status (KPS), Stupp protocol completion, extent of resection, and tumor molecular markers.

RESULTS

Average TMT for the primary and progressive glioblastoma cohorts was 9.55 mm and 9.40 mm, respectively. TMT was associated with age (r = -0.14, p = 0.0008), BMI (r = 0.29, p < 0.0001), albumin (r = 0.11, p = 0.0239), and KPS (r = 0.11, p = 0.0101). Optimal TMT cutpoints for the primary and progressive cohorts were ≤ 7.15 mm and ≤ 7.10 mm, respectively. High TMT was associated with increased Stupp protocol completion (p = 0.001). On Cox proportional hazards regression, high TMT predicted increased PS in progressive [HR 0.47 (95% confidence interval (CI)) 0.25-0.90), p = 0.023] but not primary [HR 0.99 (95% CI 0.64-1.51), p = 0.949] glioblastoma.

CONCLUSIONS

TMT correlates with important prognostic variables in glioblastoma and predicts PS in patients with progressive, but not primary, disease. TMT may represent a pragmatic neurosurgical biomarker in glioblastoma that could inform treatment planning and perioperative optimization.

Prognostic relevance of temporal muscle thickness as a marker of sarcopenia in patients with glioblastoma at diagnosis

OBJECTIVES

Temporal muscle thickness (TMT) is a surrogate marker of sarcopenia, correlated with survival expectancy in patients suffering from brain metastases and recurrent or treated glioblastoma. We evaluated the prognostic relevance of TMT measured on brain MRIs acquired at diagnosis in patients affected by glioblastoma.

METHODS

We retrospectively enrolled 51 patients in our Institution affected by methylated MGMT promoter, IDH1-2 wild-type glioblastoma, who underwent complete surgical resection and subsequent radiotherapy with concomitant and maintenance temozolomide, from January 1, 2015, to April 30, 2017. The last clinical/radiological follow-up date was set to September 3, 2019. TMT was measured bilaterally on reformatted post-contrast 3D MPRAGE images, acquired on our 3-T scanner no more than 2 days before surgery. The median, 25th, and 75th percentile TMT values were identified and population was subdivided accordingly; afterwards, statistical analyses were performed to verify the association among overall survival (OS) and TMT, sex, age, and ECOG performance status.

RESULTS

In our cohort, the median OS was 20 months (range 3-51). Patients with a TMT ≥ 8.4 mm (median value) did not show a statistically significant increase in OS (Cox regression model: HR 1.34, 95% CI 0.68-2.63, p = 0.403). Similarly, patients with a TMT ≥ 9.85 mm (fourth quartile) did not differ in OS compared to those with TMT ≤ 7 mm (first quartile). The statistical analyses confirmed a significant association among TMT and sex (p = 0.0186), but none for age (p = 0.642) and performance status (p = 0.3982).

CONCLUSIONS

In our homogeneous cohort of patients with glioblastoma at diagnosis, TMT was not associated with prognosis, age, or ECOG performance status.

KEY POINTS

• Temporal muscle thickness (TMT) is a surrogate marker of sarcopenia and has been correlated with survival expectancy in patients suffering from brain metastases and recurrent or treated glioblastoma. • We appraised the correlation among TMT and survival, sex, age at surgery, and performance status, measured on brain MRIs of patients affected by glioblastoma at diagnosis. • TMT did not show any significant correlation with prognosis, age at surgery, or performance status, and its usefulness might be restricted only to patients with brain metastases and recurrent or treated glioblastoma.