Prediction of malignancy grading using computed tomography perfusion imaging in nonenhancing supratentorial gliomas

Diagnostic Algorithm for Intracranial Lesions in the Emergency Department: Effectiveness of the Relative Brain Volume and Hounsfield Unit Value Measured by Perfusion Tomography

Background Early treatment of intracranial lesions in the emergency department is crucial, but it can be challenging to differentiate between them. This differentiation is essential because the treatment of each type of lesion is different. Cerebral computed tomography perfusion (CTP) imaging can help visualize the vascularity of brain lesions and provide absolute quantification of physiological parameters. Compared to magnetic resonance imaging, CTP has several advantages, such as simplicity, wide availability, and reproducibility. Purpose This study aimed to assess the effectiveness of Hounsfield units (HU) in measuring the density of hypercellular lesions and the ability of CTP to quantify hemodynamics in distinguishing intracranial space-occupying lesions. Methods A retrospective study was conducted from March 2016 to March 2022. All patients underwent CTP and CT scans, and relative cerebral blood volume (rCBV) and HU were obtained for intracranial lesions. Results We included a total of 244 patients in our study. This group consisted of 87 (35.7%) individuals with glioblastomas (GBs), 48 (19.7%) with primary central nervous system lymphoma (PCNSL), 45 (18.4%) with metastases (METs), and 64 (26.2) with abscesses. Our study showed that the HUs for METs were higher than those for GB (S 57.4% and E 88.5%). In addition, rCBV values for PCNSL and abscesses were lower than those for GB and METs. The HU in PCNSL was higher than those in abscesses (S 94.1% and E 96.6%). Conclusion PCT parameters provide valuable information for diagnosing brain lesions. A comprehensive assessment improves accuracy. Combining rCBV and HU enhances diagnostic accuracy, making it a valuable tool for distinguishing between lesions. PCT's widespread availability allows for the use of both anatomical and functional information with high spatial resolution for diagnosing and managing brain tumor patients.

The TIMP protein family: diverse roles in pathophysiology

The tissue inhibitors of matrix metalloproteinases (TIMPs) are a family of four matrisome proteins classically defined by their roles as the primary endogenous inhibitors of metalloproteinases (MPs). Their functions however are not limited to MP inhibition, with each family member harboring numerous MP-independent biological functions that play key roles in processes such as inflammation and apoptosis. Because of these multifaceted functions, TIMPs have been cited in diverse pathophysiological contexts. Herein, we provide a comprehensive overview of the MP-dependent and -independent roles of TIMPs across a range of pathological conditions. The potential therapeutic and biomarker applications of TIMPs in these disease contexts are also considered, highlighting the biomedical promise of this complex and often misunderstood protein family.

Dynamic contrast-enhanced computed tomography perfusion parameters of canine suspected brain tumors at baseline and during radiotherapy might be different depending on tumor location but not associated with survival

Introduction

Treatment of brain tumors in dogs can be associated with significant morbidity and reliable prognostic factors are lacking. Dynamic contrast-enhanced computed tomography (DCECT) can be used to assess tumor perfusion. The objectives of this study were to assess perfusion parameters and change in size of suspected brain tumors before and during radiotherapy (RT) depending on their location and find a potential correlation with survival.

Methods

Seventeen client-owned dogs with suspected brain tumors were prospectively recruited. All dogs had a baseline DCECT to assess mass size, blood volume (BV), blood flow (BF), and transit time (TT). Twelve dogs had a repeat DCECT after 12 Gy of megavoltage RT. Survival times were calculated.

Results

Intra-axial masses had lower BF (p = 0.005) and BV (p < 0.001) than extra-axial masses but not than pituitary masses. Pituitary masses had lower BF (p = 0.001) and BV (p = 0.004) than extra-axial masses. The volume of the mass was positively associated with TT (p = 0.001) but not with BF and BV. Intra-axial masses showed a more marked decrease in size than extra-axial and pituitary masses during RT (p = 0.022 for length, p = 0.05 for height). Extra-axial masses showed a greater decrease in BF (p = 0.011) and BV (p = 0.012) during RT than pituitary masses and intra-axial masses. Heavier dogs had a shorter survival time (p = 0.011). Perfusion parameters were not correlated with survival.

Conclusion

DCECT perfusion parameters and change in size of brain masses during RT might be different based on the location of the mass.

The Value of H2BC12 for Predicting Poor Survival Outcomes in Patients With WHO Grade II and III Gliomas

Purpose: Glioma is a common primary malignant brain tumor. Grade II (GII) gliomas are prone to develop into anaplastic grade III (GIII) gliomas, which indicate a higher malignancy and poorer survival outcome. This study aimed to satisfy the increasing demand for novel sensitive biomarkers and potential therapeutic targets in the treatment of GII and GIII gliomas.

Methods: A TCGA dataset was used to investigate the expression of H2BC12 mRNA in GII and GIII gliomas and its relation to clinical pathologic characteristics. Glioma tissues were collected to verify results from the TCGA dataset, and H2BC12 mRNA was detected by RT-qPCR. ROC analysis was employed to evaluate the classification power for GII and GIII. The significance of H2BC12 mRNA GII and GIII gliomas was also investigated. In addition, H2BC12 expression-related pathways were enriched by gene set enrichment analysis (GSEA). DNA methylation level and mutation of H2BC12 were analyzed by the UALCAN and CBioPortal databases, respectively.

Results: Based on the sample data from multiple databases and RT-qPCR, higher expression of H2BC12 mRNA was found in GII and GIII glioma tissue compared to normal tissue, which was consistent with a trend with our clinical specimen. H2BC12 mRNA had a better power in distinguishing between GII and GIII and yielded an AUC of 0.706 with a sensitivity of 76.9% and specificity of 81.8%. Meanwhile, high H2BC12 levels were associated with IDH status, 1p/19q codeletion, primary therapy outcome, and the histological type of gliomas. Moreover, the overall survival (OS), disease-specific survival (DSS), and progress-free interval (PFI) of GII glioma patients with higher levels of H2BC12 were shorter than those of patients with lower levels as well as GIII patients. In the multivariate analysis, a high H2BC12 level was an independent predictor for poor survival outcomes of gliomas. The Wnt or PI3K-AKT signaling pathways, DNA repair, cellular senescence, and DNA double-strand break repair were differentially activated in phenotypes that were positively associated with H2BC12. H2BC12 DNA methylation was high in TP53 nonmutant patients, and no H2BC12 mutation was observed in gliomas patients.

Conclusion: H2BC12 is a promising biomarker for the diagnosis and prognosis of patients with WHO grade II and III gliomas.

Dual-layer detector spectral CT-a new supplementary method for preoperative evaluation of glioma

PURPOSE

To investigate the value of the iodine concentration (IC) measured by dual-layer detector spectral CT (DLDSCT) in evaluating the factors related to the treatment scheme and survival prognosis of patients with glioma.

METHODS

From 2018 to 2019, we prospectively collected the data of 99 patients with glioma. The degree of CT enhancement and the IC of low grade gliomas (LGGs, II), high grade gliomas (HGGs, III and IV), grade II and III gliomas, were compared. The predictive performance of the degree of CT enhancement and IC was examined via receiver operating characteristic (ROC) analysis. The correlations between IC and Ki-67 labeling index, isocitrate dehydrogenase (IDH) mutation, chromosome 1p/19q deletion status of the tumor were examined.

RESULTS

Both IC and the degree of CT enhancement of patients with HGG were significantly higher than those of patients with LGG (p < 0.001; χ² =41.707, p <  0.001); IC had large area under the ROC curve for diagnostic HGG (0.931; 95 % CI: 0.882-0.979; p <  0.001). The IC in the grade III gliomas was significantly higher than that in grade II gliomas (p < 0.001); IC had a large area under the ROC curve for diagnostic grade III gliomas (0.865; 95 % CI: 0.779-0.952; p <  0.001). There was a significant positive correlation between IC and Ki-67 LI (r = 0.679; p < 0.001).

CONCLUSIONS

The DLDSCT technology can be used as a supplementary method to provide more information for preoperative grading of the gliomas and the prognosis assessment of the patients.

Prediction of malignant glioma grades using contrast-enhanced T1-weighted and T2-weighted magnetic resonance images based on a radiomic analysis

We conducted a feasibility study to predict malignant glioma grades via radiomic analysis using contrast-enhanced T1-weighted magnetic resonance images (CE-T1WIs) and T2-weighted magnetic resonance images (T2WIs). We proposed a framework and applied it to CE-T1WIs and T2WIs (with tumor region data) acquired preoperatively from 157 patients with malignant glioma (grade III: 55, grade IV: 102) as the primary dataset and 67 patients with malignant glioma (grade III: 22, grade IV: 45) as the validation dataset. Radiomic features such as size/shape, intensity, histogram, and texture features were extracted from the tumor regions on the CE-T1WIs and T2WIs. The Wilcoxon-Mann-Whitney (WMW) test and least absolute shrinkage and selection operator logistic regression (LASSO-LR) were employed to select the radiomic features. Various machine learning (ML) algorithms were used to construct prediction models for the malignant glioma grades using the selected radiomic features. Leave-one-out cross-validation (LOOCV) was implemented to evaluate the performance of the prediction models in the primary dataset. The selected radiomic features for all folds in the LOOCV of the primary dataset were used to perform an independent validation. As evaluation indices, accuracies, sensitivities, specificities, and values for the area under receiver operating characteristic curve (or simply the area under the curve (AUC)) for all prediction models were calculated. The mean AUC value for all prediction models constructed by the ML algorithms in the LOOCV of the primary dataset was 0.902 ± 0.024 (95% CI (confidence interval), 0.873-0.932). In the independent validation, the mean AUC value for all prediction models was 0.747 ± 0.034 (95% CI, 0.705-0.790). The results of this study suggest that the malignant glioma grades could be sufficiently and easily predicted by preparing the CE-T1WIs, T2WIs, and tumor delineations for each patient. Our proposed framework may be an effective tool for preoperatively grading malignant gliomas.

Diagnostic Performance of Arterial Spin Labeling for Grading Nonenhancing Astrocytic Tumors

Purpose:

We evaluated the utility of arterial spin labeling (ASL) imaging of tumor blood flow (TBF) for grading non-enhancing astrocytic tumors.

Materials and Methods:

Thirteen non-enhancing astrocytomas were divided into high-grade (n = 7) and low-grade (n = 6) groups. Both ASL and conventional sequences were acquired using the same magnetic resonance machine. Intratumoral absolute maximum TBF (TBF_max), absolute mean TBF (TBF_mean), and corresponding values normalized to cerebral blood flow (TBF_max and TBF_mean ratios) were measured. The Mann-Whitney U test and receiver operating characteristic (ROC) curve analysis were used to assess the accuracy of TBF variables for tumor grading.

Results:

Compared with low-grade astrocytoma, high-grade astrocytoma exhibited significantly greater absolute TBF_max (90.93 ± 24.96 vs 46.94 ± 20.97 ml/100 g/min, P < 0.001), TBF_mean (58.75 ± 19.89 vs 31.16 ± 17.63 ml/100 g/min, P < 0.001), TBF_max ratio (3.34 ± 1.22 vs 1.35 ± 0.5, P < 0.001), and TBF_mean ratio (2.15 ± 0.94 vs 0.88 ± 0.41, P < 0.001). The TBF_max ratio yielded the highest diagnostic accuracy (sensitivity 100%, specificity 86.3%), while absolute TBF_mean yielded the lowest accuracy (sensitivity 85.7%, specificity 70.1%) by ROC analysis.

Conclusion:

Parameters from ASL perfusion imaging, particularly TBF_max ratio, may be useful for distinguishing high-grade from low-grade astrocytoma in cases with equivocal conventional MRI findings.

Application of computed tomography for differential diagnosis of glioma stoke and simple cerebral hemorrhage

OBJECTIVE

To explore the value of computed tomography (CT) in the differential diagnosis of glioma stroke and simple cerebral hemorrhage.

MATERIALS AND METHODS

A total of 45 patients with glioma stroke and stroke as the initial symptom in our hospital from Jun., 2009 to Oct., 2013 were selected along with 50 individuals with simple cerebral hemorrhage in the same period randomly collected as a control group. The CT results in both groups were analyzed and compared.

RESULTS

In the observation group, there were 25 patients with astrocytoma (55.6%), 11 with oligodendroglioma (24.4%), 8 with ependymoma (17.2%) and 1 with glioblastoma multiforma (GBM, 2.22%). Additionally, the major CT manifestation was coexistence of hemorrhage and tumor signs. By comparison, it could be found that the proportions of patients respectively with peripheral edema and space- occupying effect in the observation group were significantly higher than in the control group (P<0.01).

CONCLUSIONS

Application of CT examination combined with medical history in patients has very important clinical value in the differential diagnosis of glioma stroke and simple cerebral hemorrhage.