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

Objective: To obtain detailed anatomic and physiologic information on the levator veli palatini muscle from MRI in individuals with repaired cleft palate and to compare the results with those from normal subjects reported by Ettema et al. (2002). Design: Prospective study. Setting: University-based hospital. Participants: Four men (ages 22 to 43 years) with repaired cleft lip and palate. Main Outcome Measures: Four quantitative measurements of the levator veli palatini muscle from rest position and dynamic speech magnetic resonance images were obtained: the distance between the origins of the muscle, angle of origin of the muscle, muscle length, and muscle thickness. Results: The length and thickness of the levator veli palatini muscle varied among the subjects and were different from measurements obtained from normal subjects in a previous study. The distance between origin points, length, and thickness of the levator veli palatini muscle were smaller than those of the normal subjects. There were systematic changes of the levator veli palatini muscle, depending upon vowel and consonant types. Levator veli palatini muscle angle of origin and length became progressively smaller from rest, nasal consonants, low vowels, high vowels, and fricative consonants. These changes are consistent with those of the normal subjects. Conclusions: This study contributes to a better understanding of cleft palate anatomy in comparison with normal anatomy of the levator veli palatini muscle. The use of MRI shows promise as an important tool in the diagnosis and eventual aid to treatment decisions for individuals born with cleft palate.

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Macrovascular Networks on Contrast-Enhanced Magnetic Resonance Imaging Improves Survival Prediction in Newly Diagnosed Glioblastoma

Cancers ◽

10.3390/cancers11010084 ◽

2019 ◽

Vol 11 (1) ◽

pp. 84 ◽

Cited By ~ 3

Author(s):

Josep Puig ◽

Carles Biarnés ◽

Pepus Daunis-i-Estadella ◽

Gerard Blasco ◽

Alfredo Gimeno ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

Magnetic Resonance ◽

Prediction Models ◽

Survival Prediction ◽

Dynamic Susceptibility ◽

Imaging Features ◽

Newly Diagnosed ◽

Resonance Imaging ◽

Contrast Enhanced ◽

Newly Diagnosed Glioblastoma

A higher degree of angiogenesis is associated with shortened survival in glioblastoma. Feasible morphometric parameters for analyzing vascular networks in brain tumors in clinical practice are lacking. We investigated whether the macrovascular network classified by the number of vessel-like structures (nVS) visible on three-dimensional T1-weighted contrast–enhanced (3D-T1CE) magnetic resonance imaging (MRI) could improve survival prediction models for newly diagnosed glioblastoma based on clinical and other imaging features. Ninety-seven consecutive patients (62 men; mean age, 58 ± 15 years) with histologically proven glioblastoma underwent 1.5T-MRI, including anatomical, diffusion-weighted, dynamic susceptibility contrast perfusion, and 3D-T1CE sequences after 0.1 mmol/kg gadobutrol. We assessed nVS related to the tumor on 1-mm isovoxel 3D-T1CE images, and relative cerebral blood volume, relative cerebral flow volume (rCBF), delay mean time, and apparent diffusion coefficient in volumes of interest for contrast-enhancing lesion (CEL), non-CEL, and contralateral normal-appearing white matter. We also assessed Visually Accessible Rembrandt Images scoring system features. We used ROC curves to determine the cutoff for nVS and univariate and multivariate cox proportional hazards regression for overall survival. Prognostic factors were evaluated by Kaplan-Meier survival and ROC analyses. Lesions with nVS > 5 were classified as having highly developed macrovascular network; 58 (60.4%) tumors had highly developed macrovascular network. Patients with highly developed macrovascular network were older, had higher volumeCEL, increased rCBFCEL, and poor survival; nVS correlated negatively with survival (r = −0.286; p = 0.008). On multivariate analysis, standard treatment, age at diagnosis, and macrovascular network best predicted survival at 1 year (AUC 0.901, 83.3% sensitivity, 93.3% specificity, 96.2% PPV, 73.7% NPV). Contrast-enhanced MRI macrovascular network improves survival prediction in newly diagnosed glioblastoma.

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OS05.3.A Temporal muscle thickness as surrogate parameter of sarcopenia in newly diagnosed glioblastoma patients:translational imaging analysis of the CENTRIC EORTC 26071-22072 and CORE trials

Neuro-Oncology ◽

10.1093/neuonc/noab180.020 ◽

2021 ◽

Vol 23 (Supplement_2) ◽

pp. ii7-ii7

Author(s):

J Furtner ◽

M Weller ◽

M Weber ◽

T Gorlia ◽

B Nabors ◽

...

Keyword(s):

At Risk ◽

Muscle Mass ◽

Muscle Thickness ◽

Rank Test ◽

Newly Diagnosed ◽

Normal Muscle ◽

Cox Models ◽

Temporal Muscle ◽

Patients At Risk ◽

Newly Diagnosed Glioblastoma

Abstract BACKGROUND Temporal muscle thickness (TMT) was described as surrogate parameter of skeletal muscle mass. This study aimed to investigate the prognostic relevance of TMT in patients with newly diagnosed glioblastoma. MATERIAL AND METHODS TMT was assessed in cranial magnetic resonance images (MRI) of 755 pts enrolled in the CENTRIC EORTC 26071-22072 study (n=508) and CORE study (n=247). Predefined sex-specific TMT cutoff values were used to categorize “patients at risk of sarcopenia” and “patients with normal muscle status” at baseline. Furthermore, patients were categorized according to the extent of TMT loss over time. Cox models adjusted for other explanatory variables were used to evaluate the associations with progression-free survival (PFS) and overall survival (OS). RESULTS Overall, 510/755 (67.6%) patients were categorized as “at risk of sarcopenia” and 245/755 (32.4%) patients had normal muscle status at baseline. In both study cohorts patient at risk of sarcopenia at baseline had significantly higher risk of progression and death than patients with normal muscle status (CENTRIC: PFS = HR 0.16, 95% CI: 0.12, 0.21, p<0.001; OS = HR 0.341, 95% CI: 0.27, 0.44, p < 0.001; CORE: PFS = HR 0.29, 95% CI: 0.21, 0.39, p<0.001; OS = HR 0.365, 95% CI: 0.27, 0.49, p<0.001). In multivariate Cox models adjusted for other important prognostic parameters similar results were obtained. In patients at risk for sarcopenia the extent of TMT loss over time showed a significant inverse correlation with median OS times (CENTRIC: p < 0.001, CORE: p = 0.005, log-rank test), but not in patients with normal baseline muscle mass in both study cohorts (CENTRIC: p = 0.538, CORE: p = 0.28, log-rank test). CONCLUSION TMT identifies patients with newly diagnosed glioblastoma at risk for progressive sarcopenia and adverse outcomes. Early intervention for muscle mass preservation including exercise and resistance training as well as nutritional support may prevent skeletal muscle loss and improve patient outcome in this group of patients.

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3D Deep Attention Network for Survival Prediction from Magnetic Resonance Images in Glioblastoma

2019 IEEE International Conference on Image Processing (ICIP) ◽

10.1109/icip.2019.8803077 ◽

2019 ◽

Cited By ~ 2

Author(s):

Zijia Liu ◽

Qiuchang Sun ◽

Hongmin Bai ◽

Chaofeng Liang ◽

Yinsheng Chen ◽

...

Keyword(s):

Magnetic Resonance ◽

Magnetic Resonance Images ◽

Survival Prediction ◽

Attention Network

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Validation of Cartilage Thickness Calculations Using Indentation Analysis

Journal of Biomechanical Engineering ◽

10.1115/1.4000989 ◽

2010 ◽

Vol 132 (4) ◽

Cited By ~ 7

Author(s):

Matthew F. Koff ◽

Le Roy Chong ◽

Patrick Virtue ◽

Dan Chen ◽

Xioanan Wang ◽

...

Keyword(s):

Magnetic Resonance ◽

Measurement Techniques ◽

Magnetic Resonance Images ◽

Cartilage Thickness ◽

Mr Images ◽

Data Set ◽

Data Points ◽

Indentation Analysis ◽

Thickness Measurements

Different methods have been used to cross-validate cartilage thickness measurements from magnetic resonance images (MRIs); however, a majority of these methods rely on interpolated data points, regional mean and/or maximal thickness, or surface mean thickness for data analysis. Furthermore, the accuracy of MRI cartilage thickness measurements from commercially available software packages has not necessarily been validated and may lead to an under- or overestimation of cartilage thickness. The goal of this study was to perform a matching point-to-point validation of indirect cartilage thickness calculations using a magnetic resonance (MR) image data set with direct cartilage thickness measurements using biomechanical indentation testing at the same anatomical locations. Seven bovine distal femoral condyles were prepared and a novel phantom filled with dilute gadolinium solution was rigidly attached to each specimen. High resolution MR images were acquired, and thickness indentation analysis of the cartilage was performed immediately after scanning. Segmentation of the MR data and cartilage thickness calculation was performed using semi-automated software. Registration of MR and indentation data was performed using the fluid filled phantom. The inter- and intra-examiner differences of the measurements were also determined. A total of 105 paired MRI-indentation thickness data points were analyzed, and a significant correlation between them was found (r=0.88, p<0.0001). The mean difference (±std. dev.) between measurement techniques was 0.00±0.23 mm, with Bland–Altman limits of agreement of 0.45 mm and −0.46 mm. The intra- and inter-examiner measurement differences were 0.03±0.22 mm and 0.05±0.24 mm, respectively. This study validated cartilage thickness measurements from MR images with thickness measurements from indentation by using a novel phantom to register the image-based and laboratory-based data sets. The accuracy of the measurements was comparable to previous cartilage thickness validation studies in literature. The results of this study will aid in validating a tool for clinical evaluation of in-vivo cartilage thickness.

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Standard values for temporal muscle thickness in the Japanese population who undergo brain check-up by magnetic resonance imaging

Surgical Neurology International ◽

10.25259/sni_3_2021 ◽

2021 ◽

Vol 12 ◽

pp. 67

Author(s):

Masahito Katsuki ◽

Norio Narita ◽

Keisuke Sasaki ◽

Yoshimichi Sato ◽

Yasuhiro Suzuki ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

Skeletal Muscle ◽

Magnetic Resonance ◽

Muscle Mass ◽

Reference Values ◽

Muscle Thickness ◽

Muscle Volume ◽

Resonance Imaging ◽

Temporal Muscle ◽

Brain Check

Background: Skeletal muscle mass is an important factor for various diseases’ outcomes. The psoas muscle cross-sectional area on the abdominal computed tomography (CT), gait speed, and handgrip strength is used to measure it. However, it is difficult to measure the neurological patients’ muscle mass or function because (1) we do not perform abdominal CT. (2) Such patients have impaired consciousness, gait disturbance, paresis, and need of rest. Temporal muscle thickness (TMT) on magnetic resonance imaging (MRI) is now attractive for skeletal muscle volume indicator, but the reference values are not established. We herein investigated the standard value of the Japanese TMT using the brain check-up database by MRI. Methods: We retrospectively investigated 360 Japanese individuals from two institutions between 2017 and 2019. We measured TMT on the T1-weighted images in the previously reported way. The associations between TMT and other variables were analyzed. Results: TMT of 214 women and 146 men, ranging from 35 to 84 years old, was investigated. TMT ranged from 3.69 to 16.90 mm. Mean TMT values were significantly higher in men compared to women except for the over 70-year-old cohort. TMT was correlated to weight and body mass index in both sexes. Conclusion: This is the first retrospective study on the standard TMT values from the Japanese brain check-up database. Our results were just reference values, but these would be useful for further investigation in other neurosurgical and neurological diseases regarding muscle volume or sarcopenia.

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