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Objectives: This study aimed to assess the correlation of temporal muscle thickness (TMT), measured on routine cranial magnetic resonance (MR) images, with lumbar skeletal muscles obtained on computed tomography (CT) images in brain metastasis patients to establish a new parameter estimating skeletal muscle mass on brain MR images., Methods: We retrospectively analyzed the cross-sectional area (CSA) of skeletal muscles at the level of the third lumbar vertebra on computed tomography scans and correlated these values with TMT on MR images of the brain in two independent cohorts of 93 lung cancer and 61 melanoma patients (overall: 154 patients) with brain metastases., Results: Pearson correlation revealed a strong association between mean TMT and CSA in lung cancer and melanoma patients with brain metastases (0.733; p<0.001). The two study cohorts did not differ significantly in patient characteristics, including age (p = 0.661), weight (p = 0.787), and height (p = 0.123). However, TMT and CSA measures differed significantly between male and female patients in both lung cancer and melanoma patients with brain metastases (p<0.001)., Conclusion: Our data indicate that TMT, measured on routine cranial MR images, is a useful surrogate parameter for the estimation of skeletal muscle mass in patients with brain metastases. Thus, TMT may be useful for prognostic assessment, treatment considerations, and stratification or a selection factor for clinical trials in patients with brain metastases. Further studies are needed to assess the association between TMT and clinical frailty parameters, and the usefulness of TMT in patients with primary brain tumors., Competing Interests: The authors have declared that no competing interests exist.

Objectives: The purpose of this study was to evaluate the prognostic relevance of temporal muscle thickness (TMT) in melanoma patients with newly diagnosed brain metastases., Methods: TMT was retrospectively assessed in 146 melanoma patients with newly diagnosed brain metastases on cranial magnetic resonance images. Chart review was used to retrieve clinical parameters, including disease-specific graded prognostic assessment (DS-GPA) and survival times., Results: Patients with a TMT > median showed a statistically significant increase in survival time (13 months) compared to patients with a TMT < median (5 months; p < 0.001; log rank test). A Cox regression model revealed that the risk of death was increased by 27.9% with every millimeter reduction in TMT. In the multivariate analysis, TMT (HR 0.724; 95% 0.642-0.816; < 0.001) and DS-GPA (HR 1.214; 95% CI 1.023-1.439; p = 0.026) showed a statistically significant correlation with overall survival., Conclusion: TMT is an independent predictor of survival in melanoma patients with brain metastases. This parameter may aid in patient selection for clinical trials or to the choice of different treatment options based on the determination of frail patient populations.

Objectives: To evaluate the prognostic relevance of temporal muscle thickness (TMT) in brain metastasis patients., Methods: We retrospectively analysed TMT on magnetic resonance (MR) images at diagnosis of brain metastasis in two independent cohorts of 188 breast cancer (BC) and 247 non-small cell lung cancer (NSCLC) patients (overall: 435 patients)., Results: Survival analysis using a Cox regression model showed a reduced risk of death by 19% with every additional millimetre of baseline TMT in the BC cohort and by 24% in the NSCLC cohort. Multivariate analysis included TMT and diagnosis-specific graded prognostic assessment (DS-GPA) as covariates in the BC cohort (TMT: HR 0.791/CI [0.703-0.889]/p < 0.001; DS-GPA: HR 1.433/CI [1.160-1.771]/p = 0.001), and TMT, gender and DS-GPA in the NSCLC cohort (TMT: HR 0.710/CI [0.646-0.780]/p < 0.001; gender: HR 0.516/CI [0.387-0.687]/p < 0.001; DS-GPA: HR 1.205/CI [1.018-1.426]/p = 0.030)., Conclusion: TMT is easily and reproducibly assessable on routine MR images and is an independent predictor of survival in patients with newly diagnosed brain metastasis from BC and NSCLC. TMT may help to better define frail patient populations and thus facilitate patient selection for therapeutic measures or clinical trials. Further prospective studies are needed to correlate TMT with other clinical frailty parameters of patients., Key Points: • TMT has an independent prognostic relevance in brain metastasis patients. • It is an easily and reproducibly parameter assessable on routine cranial MRI. • This parameter may aid in patient selection and stratification in clinical trials. • TMT may serve as surrogate marker for sarcopenia.

Using conventional MRI methods, the differentiation of primary cerebral lymphomas (PCNSL) and other primary brain tumors, such as glioblastomas, is difficult due to overlapping imaging characteristics. This study was designed to discriminate tumor entities using normalized vascular intratumoral signal intensity values (nVITS) obtained from pulsed arterial spin labeling (PASL), combined with intratumoral susceptibility signals (ITSS) from susceptibility-weighted imaging (SWI). Thirty consecutive patients with glioblastoma (n=22) and PCNSL (n=8), histologically classified according to the WHO brain tumor classification, were included. MRIs were acquired on a 3T scanner, and included PASL and SWI sequences. nVITS was defined by the signal intensity ratio between the tumor and the contralateral normal brain tissue, as obtained by PASL images. ITSS was determined as intratumoral low signal intensity structures detected on SWI sequences and were divided into four different grades. Potential differences in the nVITS and ITSS between glioblastomas and PCNSLs were revealed using statistical testing. To determine sensitivity, specificity, and diagnostic accuracy, as well as an optimum cut-off value for the differentiation of PCNSL and glioblastoma, a receiver operating characteristic analysis was used. We found that nVITS (p=0.011) and ITSS (p=0.001) values were significantly higher in glioblastoma than in PCNSL. The optimal cut-off value for nVITS was 1.41 and 1.5 for ITSS, with a sensitivity, specificity, and accuracy of more than 95%. These findings indicate that nVITS values have a comparable diagnostic accuracy to ITSS values in differentiating glioblastoma and PCNSL, offering a completely non-invasive and fast assessment of tumoral vascularity in a clinical setting., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)

Background and Purpose: Pulsed arterial spin-labeling is a noninvasive MR imaging perfusion method performed with the use of water in the arterial blood as an endogenous contrast agent. The purpose of this study was to determine the inversion time with the largest difference in normalized intratumoral signal intensity between high-grade and low-grade astrocytomas., Materials and Methods: Thirty-three patients with gliomas, histologically classified as low-grade (n = 7) or high-grade astrocytomas (n = 26) according to the World Health Organization brain tumor classification, were included. A 3T MR scanner was used to perform pulsed arterial spin-labeling measurements at 8 different inversion times (370 ms, 614 ms, 864 ms, 1114 ms, 1364 ms, 1614 ms, 1864 ms, and 2114 ms). Normalized intratumoral signal intensity was calculated, which was defined by the signal intensity ratio of the tumor and the contralateral normal brain tissue for all fixed inversion times. A 3-way mixed ANOVA was used to reveal potential differences in the normalized vascular intratumoral signal intensity between high-grade and low-grade astrocytomas., Results: The difference in normalized vascular intratumoral signal intensity between high-grade and low-grade astrocytomas obtained the most statistically significant results at 370 ms (P = .003, other P values ranged from .012-.955)., Conclusions: The inversion time by which to differentiate high-grade and low-grade astrocytomas by use of normalized vascular intratumoral signal intensity was 370 ms in our study. The normalized vascular intratumoral signal intensity values at this inversion time mainly reflect the labeled intra-arterial blood bolus and therefore could be referred to as normalized vascular intratumoral signal intensity. Our data indicate that the use of normalized vascular intratumoral signal intensity values allows differentiation between low-grade and high-grade astrocytomas and thus may serve as a new, noninvasive marker for astrocytoma grading.