MRS as an Aid to Diagnose Malignant Transformation in Low-Grade Gliomas with Increasing Contrast Enhancement

Clinical, pathological, and radiological features of 80 pediatric diffuse intrinsic pontine gliomas: A single-institute study

Objective

Diffuse intrinsic pontine gliomas (DIPGs) are rare but devastating diseases. This retrospective cross-sectional study aimed to investigate the clinical, radiological, and pathological features of DIPGs.

Materials and methods

The clinical data of 80 pediatric DIPGs under clinical treatment in Beijing Tiantan Hospital from July 2013 to July 2019 were retrospectively collected and studied. A follow-up evaluation was performed.

Results

This study included 48 men and 32 women. The most common symptoms were cranial nerve palsy (50.0%, 40/80 patients) and limb weakness (41.2%, 33/80 patients). Among the 80 patients, 24 cases were clinically diagnosed, 56 cases were pathologically verified, and 45 cases were tested for H3K27 alteration status, with 34 H3K27 alteration cases confirmed. Radiological results indicated that enhancement was common (65.0%, 52/80 patients). Cho/Cr was of predictive value for H3K27 alteration status (P = 0.012, cutoff value = 2.38, AUC = 0.801). Open cranial surgery followed by further chemotherapy and radiotherapy was beneficial for patients' overall survival. Cox regression analysis indicated H3K27 alteration to be the independent prognostic influencing factor for DIPGs in this series (P = 0.002).

Conclusion

DIPGs displayed a wide spectrum of clinical and imaging features. Surgery-suitable patients could benefit from postoperative comprehensive therapy for a better overall survival. H3K27 alteration was the independent prognostic influencing factor for DIPGs.

Relative T2-FLAIR signal intensity surrounding residual cavity is associated with survival prognosis in patients with lower-grade gliomas

Aims

To investigate whether the relative signal intensity surrounding the residual cavity on T2-fluid-attenuated inversion recovery (rFLAIR) can improve the survival prediction of lower-grade glioma (LGG) patients.

Methods

Clinical and pathological data and the follow-up MR imaging of 144 patients with LGG were analyzed. We calculated rFLAIR with Image J software. Logistic analysis was used to explore the significant impact factors on progression-free survival (PFS) and overall survival (OS). Several models were set up to predict the survival prognosis of LGG.

Results

A higher rFLAIR [1.81 (0.83)] [median (IQR)] of non-enhancing regions surrounding the residual cavity was detected in the progressed group (n=77) than that [1.55 (0.33)] [median (IQR)] of the not-progressed group (n = 67) (P<0.001). Multivariate analysis showed that lower KPS (≤75), and higher rFLAIR (>1.622) were independent predictors for poor PFS (P<0.05), whereas lower KPS (≤75) and thick-linear and nodular enhancement were the independent predictors for poor OS (P<0.05). The cutoff rFLAIR value of 1.622 could be used to predict poor PFS (HR = 0.31, 95%CI 0.20–0.48) (P<0.001) and OS (HR = 0.27, 95%CI 0.14–0.51) (P=0.002). Both the areas under the ROC curve (AUCs) for predicting poor PFS (AUC, 0.771) and OS (AUC, 0.831) with a combined model that contained rFLAIR were higher than those of any other models.

Conclusion

Higher rFALIR (>1.622) in non-enhancing regions surrounding the residual cavity can be used as a biomarker of the poor survival of LGG. rFLAIR is helpful to improve the survival prediction of posttreatment LGG patients.

Prediction of Malignant Transformation of WHO II Astrocytoma Using Mathematical Models Incorporating Apparent Diffusion Coefficient and Contrast Enhancement

Using only increasing contrast enhancement as a marker of malignant transformation (MT) in gliomas has low specificity and may affect interpretation of clinical outcomes. Therefore we developed a mathematical model to predict MT of low-grade gliomas (LGGs) by considering areas of reduced apparent diffusion coefficient (ADC) with increased contrast enhancement. Patients with contrast-enhancing LGGs who had contemporaneous ADC and histopathology were retrospectively analyzed. Multiple clinical factors and imaging factors (contrast-enhancement size, whole-tumor size, and ADC) were assessed for association with MT. Patients were split into training and validation groups for the development of a predictive model using logistic regression which was assessed with receiver operating characteristic analysis. Among 132 patients, (median age 46.5 years), 106 patients (64 MT) were assigned to the training group and 26 (20 MT) to the validation group. The predictive model comprised age (P = 0.110), radiotherapy (P = 0.168), contrast-enhancement size (P = 0.015), and ADC (P < 0.001). The predictive model (area-under-the-curve [AUC] 0.87) outperformed ADC (AUC 0.85) and contrast-enhancement size (AUC 0.67). The model had an accuracy of 84% for the training group and 85% respectively for the validation group. Our model incorporating ADC and contrast-enhancement size predicted MT in contrast-enhancing LGGs.

Factors Associated With Dysfunction of Glymphatic System in Patients With Glioma

Objectives

Rodent experiments have provided some insights into the changes of glymphatic function associated with glioma growth. The diffusion tensor image analysis along the perivascular space (DTI-ALPS) method offers an opportunity for the noninvasive investigation of the glymphatic system in patients with glioma. We aimed to investigate the factors associated with glymphatic function changes in patients with glioma.

Materials and Methods

A total of 201 glioma patients (mean age = 47.4 years, 116 men; 86 grade II, 52 grade III, and 63 grade IV) who had preoperative diffusion tensor imaging for calculation of the ALPS index were retrospectively included. Information collected from each patient included sex, age, tumor grade, isocitrate dehydrogenase 1 (IDH1) mutation status, peritumoral brain edema volume, tumor volume, and ALPS index. Group differences in the ALPS index according to sex, tumor grade, and IDH1 mutation status were assessed using analysis of covariance with age adjustment. Linear regression analyses were performed to identify the factors associated with the ALPS index.

Results

Group comparisons revealed that the ALPS index of grade II/III gliomas was significantly higher than that of grade IV gliomas (p < 0.001). The ALPS index of IDH1 mutant gliomas was significantly higher than that of IDH1 wild-type gliomas (p < 0.001). On multivariable linear regression analysis, IDH1 mutation (β = 0.308, p < 0.001) and peritumoral brain edema volume (β = −0.353, p < 0.001) were the two independent factors associated with the ALPS index.

Conclusion

IDH1 wild-type gliomas and gliomas with larger peritumoral brain edema volumes were associated with a lower ALPS index, which may reflect impaired glymphatic function.