The Application of Image Segmentation to Determine the Ratio of Peritumoral Edema Area to Tumor Area on Primary Malignant Brain Tumor and Metastases through Conventional Magnetic Resonance Imaging

BACKGROUND: Primary malignant brain tumor and metastases on the brain have a similar pattern in conventional Magnetic Resonance Imaging (MRI), even though both require entirely different treatment and management. The pathophysiological difference of peritumoral edema can help to distinguish the case of primary malignant brain tumor and brain metastases. AIM: This study aimed to analyze the ratio of the area of peritumoral edema to the tumor using Otsu’s method of image segmentation technique with a user-friendly Graphical User Interface (GUI). METODS: Data was prepared by obtaining the examination results of Anatomical Pathology and MRI imaging. The area of peritumoral edema was identified from MRI image segmentation with T2/FLAIR sequence. While the area of tumor was identified using MRI image segmentation with T1 sequence. RESULTS: The Mann-Whitney test was employed to analyze the ratio of the area of peritumoral edema to tumor on both groups. Data testing produced a significance level of 0.013 (p < 0.05) with a median value (Nmax-Nmin) of 1.14 (3.31-0.08) for the primary malignant brain tumor group and a median value (Nmax-Nmin) of 1.17 (10.30-0.90) for the brain metastases group. CONCLUSIONS: There was a significant difference in the ratio of the area of peritumoral edema to the area of tumor from both groups, in which brain metastases have a greater value than the primary malignant brain tumor.

The Study of Cerebral Blood Flow Variations during Brain Metastasis Radiotherapy

Purpose: To investigate the cerebral blood flow (CBF) variations during brain metastases (BMs) radiotherapy (RT) applying with MR 3D-arterial spin labeling (ASL). Materials and Methods: A total of 26 BMs patients with 54 tumors were retrospectively enrolled. MR examinations were performed before and during RT (30-50 Gy) with a total dose of 36-60 Gy (12-30 fractions) including contrast-enhanced T1-weighted, T2 Flair and 3D-ASL images. The relationship between CBF changes and the largest cross-sectional area changes in BMs was investigated. And CBF changes in BMs, normal brain tissue, and peritumoral edema areas were analyzed under different dose gradients that was divided into 10 Gy intervals. Results: The largest cross-sectional areas and CBF of 54 BMs decreased by 26.46% and 29.64% respectively during RT (P<0.05), but there was no correlation between the two changes (P>0.05). The rates of CBF decrease in BMs were 33.75%, 24.61% and 27.55% at 30-40, 40-50 and >50 Gy, respectively (P<0.05). In normal brain tissue with dose gradients of 0-10, 10-20, 20-30, 30-40, 40-50 and > 50 Gy, the CBF decreased by 7.65%, 11.12%, 18.42%, 20.23%, 19.79% and 17.89%, respectively (P <0.05). The CBF decreases reached a maximum at 30-40 Gy in normal brain tissue as well as BMs. In contrast, the CBF decreases of peritumoral edema areas increased as the dose gradients increased. Moreover, the CBF changes of BMs were more notable than those in normal brain tissue and peritumoral edema areas. Conclusion: CBF changes can be feasibly assessed in different brain regions during RT based on 3D-ASL. The changes should be considered as a critical factor to determine the personal radiation dose for BMs, normal brain tissue and peritumoral edema areas.

A Multiparametric MR-Based RadioFusionOmics Model with Robust Capabilities of Differentiating Glioblastoma Multiforme from Solitary Brain Metastasis

This study aimed to evaluate the diagnostic potential of a novel RFO model in differentiating GBM and SBM with multiparametric MR sequences collected from 244 (131 GBM and 113 SBM) patients. Three basic volume of interests (VOIs) were delineated on the conventional axial MR images (T1WI, T2WI, T2_FLAIR, and CE_T1WI), including volumetric non-enhanced tumor (nET), enhanced tumor (ET), and peritumoral edema (pTE). Using the RFO model, radiomics features extracted from different multiparametric MRI sequence(s) and VOI(s) were fused and the best sequence and VOI, or possible combinations, were determined. A multi-disciplinary team (MDT)-like fusion was performed to integrate predictions from the high-performing models for the final discrimination of GBM vs. SBM. Image features extracted from the volumetric ET (VOIET) had dominant predictive performances over features from other VOI combinations. Fusion of VOIET features from the T1WI and T2_FLAIR sequences via the RFO model achieved a discrimination accuracy of AUC = 0.925, accuracy = 0.855, sensitivity = 0.856, and specificity = 0.853, on the independent testing cohort 1, and AUC = 0.859, accuracy = 0.836, sensitivity = 0.708, and specificity = 0.919 on the independent testing cohort 2, which significantly outperformed three experienced radiologists (p = 0.03, 0.01, 0.02, and 0.01, and p = 0.02, 0.01, 0.45, and 0.02, respectively) and the MDT-decision result of three experienced experts (p = 0.03, 0.02, 0.03, and 0.02, and p = 0.03, 0.02, 0.44, and 0.03, respectively).

How Much Tumor Volume Is Responsible for Development of Clinical Symptoms in Patients With Convexity, Parasagittal, and Falx Meningiomas?

Purpose: Meningiomas are the most common primary intracranial neoplasms and clinical symptom appearance depends on their volume and location. This study aimed to identify factors that influence clinical symptoms and to determine a specific threshold tumor volume for the prediction of symptomatic progression in patients with convexity, parasagittal, and falx meningiomas.Materials and Methods: We retrospectively studied patients with radiologically suspected convexity, parasagittal, or falx meningiomas at our institution.Results: The data of three hundred thirty-three patients were analyzed. We further divided patients into two groups based on clinical symptoms: an asymptomatic group (250 cases) and a symptomatic group (83 cases). Univariate analysis revealed significant differences between the groups in terms of sex (p = 0.002), age at the time of volumetric analysis (p &lt; 0.001), hyperintense lesions on T2-weighted images (p = 0.029), peritumoral edema (p &lt; 0.001), maximum tumor diameter (p &lt; 0.001), and tumor volume (p &lt; 0.001). Further multivariate analysis revealed significant differences between the groups in terms of age at the time of volumetric analysis (p = 0.002), peritumoral edema (p &lt; 0.001), and tumor volume (p &lt; 0.001). The receiver operating characteristic curve revealed a threshold tumor volume of 21.1 ml for predicting whether a patient would develop symptoms (sensitivity 0.843, specificity 0.880, an area under the curve 0.919 [95% confidence interval: 0.887–0.951]).Conclusion: We identified factors predictive of clinical symptoms in patients with convexity, parasagittal, and falx meningiomas and determined the first-ever threshold tumor volume for predicting symptomatic progression in such patients.

P.160 Impact of peritumoral edema during tumor treatment field therapy: a computational modelling study

Background: Tumor treatment fields (TTFields) are an approved adjuvant therapy for glioblastoma. The magnitude of applied electrical field is related to the anti-tumoral response. However, peritumoral edema (ptE) may result in shunting of electrical current around the tumor, thereby reducing the intra-tumoral electric field. In this study, we address this issue with computational simulations. Methods: Finite element models were created with varying amounts of ptE surrounding a virtual tumor. The electric field distribution was simulated using the standard TTFields electrode montage. Electric field magnitude was extracted from the tumor and related to edema thickness. Two patient specific models were created to confirm these results. Results: The inclusion of ptE decreased the magnitude of the electric field within the tumor. In the model considering a frontal tumor and an anterior-posterior electrode configuration, ≥ 6 mm of ptE decreased the electric field by 52%. In the patient specific models, ptE decreased the electric field within the tumor by an average of 26%. The effect of ptE on the electric field distribution was spatially heterogenous. Conclusions: Given the importance of electric field magnitude for the anti-tumoral effects of TTFields, the presence of edema should be considered both in future modelling studies and as a predictor of non-response.

Comparison of Short-Term Surgery Outcomes Between Older and Younger Patients With Middle Third Parasagittal and Falx Meningioma

Background and Purpose Middle third parasagittal and falx meningiomas can cause severe neurological deficits. The incidence of meningioma rises with age and comorbidities. Elderly patients may suffer from operative complications and recover more slowly than younger patients. The aim of this study was to assess the clinical characteristics and surgery outcomes between younger and elderly patients with meningiomas. Methods The patients of middle third parasagittal and falcine meningiomas operated from January 2011 and December 2019 were reviewed in this retrospective study. All lesions arose from the middle third of the falx or superior sagittal sinus (SSS). The complications, such as peritumoral edema, operative blood loss, and neurological deficit, and postoperative hospital stay, were compared between groups. Results Forty-three elderly patients and 63 younger patients were included in the current study. The elderly had larger and more aggressive lesions than younger individuals (P=0.013). Moreover, the aging group had severe peritumoral edema (P=0.019) and longer postoperative hospital stay (P=0.009) than younger patients, while the younger suffered from higher blood loss (P=0.022) and reoperation (3 vs. 1) at perioperative period. Furthermore, no significant difference was detected in the neurological deficit between the two groups (p=0.97). Conclusions Although severe peritumoral edema gave rise to larger lesions, elderly patients with the middle third of parasagittal and falcine meningiomas shared similar surgery outcomes as younger individuals. However, after considering all the factors, elderly patients were more likely to develop minor postoperative complications compared to younger ones.

Exploring Peritumoral Neural Tracts by Using Neurite Orientation Dispersion and Density Imaging

Diffusion Tensor Imaging (DTI) tractography has been widely used in brain tumor surgery to ensure thorough resection and minimize functional damage. However, due to enhanced anisotropic uncertainty in the area with peritumoral edema, diffusion tractography is generally not practicable leading to high false-negative results in neural tracking. In this study, we evaluated the usefulness of the neurite orientation dispersion and density imaging (NODDI) derived tractography for investigating structural heterogeneity of the brain in patients with brain tumor. A total of 24 patients with brain tumors, characterized by peritumoral edema, and 10 healthy counterparts were recruited from 2014 to 2021. All participants underwent magnetic resonance imaging. Moreover, we used the images obtained from the healthy participants for calibrating the orientation dispersion threshold for NODDI-derived corticospinal tract (CST) reconstruction. Compared to DTI, NODDI-derived tractography has a great potential to improve the reconstruction of fiber tracking through regions of vasogenic edema. The regions with edematous CST in NODDI-derived tractography demonstrated a significant decrease in the intracellular volume fraction (VFic, p &lt; 0.000) and an increase in the isotropic volume fraction (VFiso, p &lt; 0.014). Notably, the percentage of the involved volume of the concealed CST and lesion-to-tract distance could reflect the motor function of the patients. After the tumor resection, four patients with 1–5 years follow-up were showed subsidence of the vasogenic edema and normal CST on DTI tractography. NODDI-derived tractography revealed tracts within the edematous area and could assist neurosurgeons to locate the neural tracts that are otherwise not visualized by conventional DTI tractography.

Peritumoral edema status of glioblastoma identifies patients reaching long-term disease control with specific progression patterns after tumor resection and high-dose proton boost

Background Glioblastoma peritumoral edema (PE) extent is associated with survival and progression pattern after tumor resection and radiotherapy (RT). To increase tumor control, proton beam was adopted to give high-dose boost (> 90 Gy). However, the correlation between PE extent and prognosis of glioblastoma after postoperative high-dose proton boost (HDPB) therapy stays unknown. We intend to utilize the PE status to classify the survival and progression patterns. Methods Patients receiving HDPB (96.6 GyE) were retrospectively evaluated. Limited peritumoral edema (LPE) was defined as PE extent < 3 cm with a ratio of PE extent to tumor maximum diameter of < 0.75. Extended progressive disease (EPD) was defined as progression of tumors extending > 1 cm from the tumor bed edge. Results After long-term follow-up (median 88.7, range 63.6–113.8 months) for surviving patients with (n = 13) and without (n = 32) LPE, the median overall survival (OS) and progression-free survival (PFS) were 77.2 vs. 16.7 months (p = 0.004) and 13.6 vs. 8.6 months (p = 0.02), respectively. In multivariate analyses combined with factors of performance, age, tumor maximum diameter, and tumor resection extent, LPE remained a significant factor for favorable OS and PFS. The rates of 5-year complete response, EPD, and distant metastasis with and without LPE were 38.5% vs. 3.2% (p = 0.005), 7.7% vs. 40.6% (p = 0.04), and 0% vs. 34.4% (p = 0.02), respectively. Conclusions The LPE status effectively identified patients with relative long-term control and specific progression patterns after postoperative HDPB for glioblastoma.

Machine Learning-Based Analysis of Magnetic Resonance Radiomics for the Classification of Gliosarcoma and Glioblastoma

ObjectiveTo identify optimal machine-learning methods for the radiomics-based differentiation of gliosarcoma (GSM) from glioblastoma (GBM).Materials and MethodsThis retrospective study analyzed cerebral magnetic resonance imaging (MRI) data of 83 patients with pathologically diagnosed GSM (58 men, 25 women; mean age, 50.5 ± 12.9 years; range, 16-77 years) and 100 patients with GBM (58 men, 42 women; mean age, 53.4 ± 14.1 years; range, 12-77 years) and divided them into a training and validation set randomly. Radiomics features were extracted from the tumor mass and peritumoral edema. Three feature selection and classification methods were evaluated in terms of their performance in distinguishing GSM and GBM: the least absolute shrinkage and selection operator (LASSO), Relief, and Random Forest (RF); and adaboost classifier (Ada), support vector machine (SVM), and RF; respectively. The area under the receiver operating characteristic curve (AUC) and accuracy (ACC) of each method were analyzed.ResultsBased on tumor mass features, the selection method LASSO + classifier SVM was found to feature the highest AUC (0.85) and ACC (0.77) in the validation set, followed by Relief + RF (AUC = 0.84, ACC = 0.72) and LASSO + RF (AUC = 0.82, ACC = 0.75). Based on peritumoral edema features, Relief + SVM was found to have the highest AUC (0.78) and ACC (0.73) in the validation set. Regardless of the method, tumor mass features significantly outperformed peritumoral edema features in the differentiation of GSM from GBM (P &lt; 0.05). Furthermore, the sensitivity, specificity, and accuracy of the best radiomics model were superior to those obtained by the neuroradiologists.ConclusionOur radiomics study identified the selection method LASSO combined with the classifier SVM as the optimal method for differentiating GSM from GBM based on tumor mass features.

Diffuse midline gliomas, H3 K27M-mutant are associated with less peritumoral edema and contrast enhancement in comparison to glioblastomas, H3 K27M-wildtype of midline structures

Purpose The entity ‘diffuse midline glioma, H3 K27M-mutant (DMG)’ was introduced in the revised 4th edition of the 2016 WHO classification of brain tumors. However, there are only a few reports on magnetic resonance imaging (MRI) of these tumors. Thus, we conducted a retrospective survey focused on MRI features of DMG compared to midline glioblastomas H3 K27M-wildtype (mGBM-H3wt). Methods We identified 24 DMG cases and 19 mGBM-H3wt patients as controls. After being retrospectively evaluated for microscopic evidence of microvascular proliferations (MVP) and tumor necrosis by two experienced neuropathologists to identify the defining histological criteria of mGBM-H3wt, the samples were further analyzed by two experienced readers regarding imaging features such as shape, peritumoral edema and contrast enhancement. Results The DMG were found in the thalamus in 37.5% of cases (controls 63%), in the brainstem in 50% (vs. 32%) and spinal cord in 12.5% (vs. 5%). In MRI and considering MVP, DMG were found to be by far less likely to develop peritumoral edema (OR: 0.13; 95%-CL: 0.02–0.62) (p = 0.010). They, similarly, were associated with a significantly lower probability of developing strong contrast enhancement compared to mGBM-H3wt (OR: 0.10; 95%-CL: 0.02–0.47) (P = 0.003). Conclusion Despite having highly variable imaging features, DMG exhibited markedly less edema and lower contrast enhancement in MRI compared to mGBM-H3wt. Of these features, the enhancement level was associated with evidence of MVP.