Peritumoral brain edema volume in meningioma correlates with tumor fractional anisotropy but not apparent diffusion coefficient or cerebral blood volume

Predicting peritumoral edema development after gamma knife radiosurgery of meningiomas using machine learning methods: a multicenter study

OBJECTIVES

Edema is a complication of gamma knife radiosurgery (GKS) in meningioma patients that leads to a variety of consequences. The aim of this study is to construct radiomics-based machine learning models to predict post-GKS edema development.

METHODS

In total, 445 meningioma patients who underwent GKS in our institution were enrolled and partitioned into training and internal validation datasets (8:2). A total of 150 cases from multicenter data were included as the external validation dataset. In each case, 1132 radiomics features were extracted from each pre-treatment MRI sequence (contrast-enhanced T1WI, T2WI, and ADC maps). Nine clinical features and eight semantic features were also generated. Nineteen random survival forest (RSF) and nineteen neural network (DeepSurv) models with different combinations of radiomics, clinical, and semantic features were developed with the training dataset, and evaluated with internal and external validation. A nomogram was derived from the model achieving the highest C-index in external validation.

RESULTS

All the models were successfully validated on both validation datasets. The RSF model incorporating clinical, semantic, and ADC radiomics features achieved the best performance with a C-index of 0.861 (95% CI: 0.748-0.975) in internal validation, and 0.780 (95% CI: 0.673-0.887) in external validation. It stratifies high-risk and low-risk cases effectively. The nomogram based on the predicted risks provided personalized prediction with a C-index of 0.962 (95%CI: 0.951-0.973) and satisfactory calibration.

CONCLUSION

This RSF model with a nomogram could represent a non-invasive and cost-effective tool to predict post-GKS edema risk, thus facilitating personalized decision-making in meningioma treatment.

CLINICAL RELEVANCE STATEMENT

The RSF model with a nomogram built in this study represents a handy, non-invasive, and cost-effective tool for meningioma patients to assist in better counselling on the risks, appropriate individual treatment decisions, and customized follow-up plans.

KEY POINTS

• Machine learning models were built to predict post-GKS edema in meningioma. The random survival forest model with clinical, semantic, and ADC radiomics features achieved excellent performance. • The nomogram based on the predicted risks provides personalized prediction with a C-index of 0.962 (95%CI: 0.951-0.973) and satisfactory calibration and shows the potential to assist in better counselling, appropriate treatment decisions, and customized follow-up plans. • Given the excellent performance and convenient acquisition of the conventional sequence, we envision that this non-invasive and cost-effective tool will facilitate personalized medicine in meningioma treatment.

Glymphatic system impairment in sleep disruption: diffusion tensor image analysis along the perivascular space (DTI-ALPS)

PURPOSE

This study aimed to evaluate the relationship between sleep quality as assessed using the Pittsburgh Sleep Quality Index (PSQI) and the index of diffusivity along the perivascular space (ALPS index), a possible indirect indicator of glymphatic system activity.

MATERIALS AND METHODS

This study included the diffusion magnetic resonance imaging (MRI) data of 317 people with sleep disruption and 515 healthy controls (HCs) from the Human Connectome Project (WU-MINN HCP 1200). The ALPS index was calculated automatically based on diffusion tensor image analysis (DTI)-ALPS of diffusion MRI. The ALPS index of the sleep disruption and HC groups was compared using general linear model (GLM) analysis with covariates, such as age, sex, level of education, and intracranial volume. In addition, to confirm the relationship between sleep quality and the ALPS index in the sleep disruption group as well as evaluate the effect of each PSQI component on the ALPS index, correlation analyses between the ALPS indices and PSQI scores of all the components and between the ALPS index and each PSQI component was performed using GLM analysis with the abovementioned covariates, respectively.

RESULTS

The ALPS index was significantly lower in the sleep disruption group than in the HC group (p = 0.001). Moreover, the ALPS indices showed significant negative correlations with the PSQI scores of all the components (false discovery rate [FDR]-corrected p < 0.001). Two significant negative correlations were also found between the ALPS index and PSQI component 2 (sleep latency, FDR-corrected p < 0.001) and 6 (the use of sleep medication, FDR-corrected p < 0.001).

CONCLUSION

Our findings suggest that glymphatic system impairment contributes to sleep disruption in young adults.

Glymphatic system impairment in corticobasal syndrome: diffusion tensor image analysis along the perivascular space (DTI-ALPS)

PURPOSE

This study aimed to evaluate the along the perivascular space (ALPS) index based on the diffusion tensor image ALPS (DTI-ALPS) in corticobasal degeneration with corticobasal syndrome (CBD-CBS) and investigate its correlation with motor and cognitive functions.

MATERIALS AND METHODS

The data of 21 patients with CBD-CBS and 17 healthy controls (HCs) were obtained from the 4-Repeat Tauopathy Neuroimaging Initiative and the Frontotemporal Lobar Degeneration Neuroimaging Initiative databases. Diffusion magnetic resonance imaging was performed using a 3-Tesla MRI scanner. The ALPS index based on DTI-ALPS was automatically calculated after preprocessing. The ALPS index was compared between the CBD-CBS and HC groups via a general linear model analysis, with covariates such as age, sex, years of education, and intracranial volume (ICV). Furthermore, to confirm the relation between the ALPS index and the motor and cognitive score in CBD-CBS, the partial Spearman's rank correlation coefficient was calculated with covariates such as age, sex, years of education, and ICV. A p value of < 0.05 was considered as statistically significant in all statistical analyses.

RESULTS

The ALPS index of CBD-CBS was significantly lower than that of HC (Cohen's d =  - 1.53, p < 0.005). Moreover, the ALPS index had a significant positive correlation with the mini mental state evaluation score (rs = 0.65, p < 0.005) and a significant negative correlation with the unified Parkinson's Disease Rating Scale III score (rs =  - 0.75, p < 0.001).

CONCLUSION

The ALPS index of patients with CBD-CBS, which is significantly lower than that of HCs, is significantly associated with motor and cognitive functions.

Multisite harmonization of diffusion tensor image analysis along the perivascular space using the COMBined Association Test

PURPOSE

This multisite study aimed to use the COMBined Association Test (COMBAT), a harmonization technique that uses regression of covariates with an empirical Bayesian framework, to harmonize diffusion tensor image analysis along the perivascular space (DTI-ALPS) variations caused by scanner, site, and protocol differences.

MATERIALS AND METHODS

This study included multisite diffusion magnetic resonance imaging (dMRI) data of 45 patients with Alzheimer's disease (AD) and 82 cognitively normal (CN) participants from the AD neuroimaging initiative database. The dMRI data were obtained with two b values (0 and 1000 s/mm2) from 27 institutions and three different 3-Tesla MRI scanners (two vendors). The ALPS index was calculated from multisite dMRI data, and COMBAT was used to harmonize the factors causing site variations. Welch's t test was used, Cohen's d was calculated to compare the difference in the ALPS index between AD and CN before and after harmonization, and Pearson's correlation coefficient was calculated to assess the relationships between the ALPS index and the cognitive score, [18F] fluorodeoxyglucose (FDG)-positron emission tomography (PET), and [18F] florbetapir (AV45)-PET standardized uptake value ratios (SUVRs).

RESULTS

COMBAT harmonized scanner differences and increased Cohen's d of the left and right ALPS indexes between AD and CN from 0.288 to 0.438 and 0.328 to 0.480, respectively. The ALPS indexes were significantly different between AD and CN after harmonization (P < 0.05) but not before it. Moreover, Pearson's correlation coefficients between the ALPS index and cognitive score, FDG-PET, and AV45-PET SUVRs were higher after harmonization than before it.

CONCLUSION

This study demonstrates the application of COMBAT harmonization to eliminate between-scanner, site, and protocol variations in the ALPS index calculated from DTI-ALPS using dMRI and possibly facilitate the use of the ALPS index in multi-center studies.

Reproducibility of automated calculation technique for diffusion tensor image analysis along the perivascular space

PURPOSE

The method of diffusion tensor image analysis along the perivascular space (DTI-ALPS) was gathering attention to evaluate the brain's glymphatic function or interstitial fluid dynamics. However, to the best knowledge, no study was conducted on the reproducibility of these automated methods for ALPS index values. Therefore, the current study evaluated the ALPS index reproducibility based on DTI-ALPS using two major automated calculation techniques in scan and rescan of the same subject on the same day.

MATERIALS AND METHODS

This study included 23 participants, including 2 with Alzheimer's disease, 15 with mild cognitive impairment, and 6 with cognitive normals. Scan and rescan data of diffusion magnetic resonance images were obtained, as well as automatically index for ALPS (ALPS index) and ALPS index maintaining tensor vector orientation information (vALPS index) with region of interest on the template fractional anisotropy map calculated by FSL software.These ALPS indices were compared in terms of scan and rescan reproducibility.

RESULTS

The absolute difference in ALPS-index values between scan and rescan was larger in the ALPS index than in the vALPS index by approximately 0.6% as the relative difference. Cohen's d for the left and right ALPS indices between methods were 0.121 and 0.159, respectively.

CONCLUSION

The vALPS index based on DTI-ALPS maintaining tensor vector orientation information has higher reproducibility than the ALPS index. This result encourages a multisite study on the ALPS index with a large sample size and helps detect a subtle pathological change in the ALPS index.

Principal component analysis of texture features for grading of meningioma: not effective from the peritumoral area but effective from the tumor area

PURPOSE

To investigate whether texture features from tumor and peritumoral areas based on sequence combinations can differentiate between low- and non-low-grade meningiomas.

METHODS

Consecutive patients diagnosed with meningioma by surgery (77 low-grade and 28 non-low-grade meningiomas) underwent preoperative magnetic resonance imaging including T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and contrast-enhanced T1WI (CE-T1WI). Manual segmentation of the tumor area was performed to extract texture features. Segmentation of the peritumoral area was performed for peritumoral high-signal intensity (PHSI) on T2WI. Principal component analysis was performed to fuse the texture features to principal components (PCs), and PCs of each sequence of the tumor and peritumoral areas were compared between low- and non-low-grade meningiomas. Only PCs with statistical significance were used for the model construction using a support vector machine algorithm. k-fold cross-validation with receiver operating characteristic curve analysis was used to evaluate diagnostic performance.

RESULTS

Two, one, and three PCs of T1WI, apparent diffusion coefficient (ADC), and CE-T1WI, respectively, for the tumor area, were significantly different between low- and non-low-grade meningiomas, while PCs of T2WI for the tumor area and PCs for the peritumoral area were not. No significant differences were observed in PHSI. Among models of sequence combination, the model with PCs of ADC and CE-T1WI for the tumor area showed the highest area under the curve (0.84).

CONCLUSION

The model with PCs of ADC and CE-T1WI for the tumor area showed the highest diagnostic performance for differentiating between low- and non-low-grade meningiomas. Neither PHSI nor PCs in the peritumoral area showed added value.

[Factors influencing peritumoral edema in meningiomas: CT- and MRI-based quantitative assessment]

Background. Meningiomas may be accompanied by peritumoral edema. Incidence and pathogenesis of edema are nor clearly established. Prevalence and severity of edema vary significantly in patients with meningiomas similar in various parameters.

OBJECTIVE

To assess peritumoral edema in intracranial meningiomas and factors influencing incidence and severity of this process.

MATERIAL AND METHODS

There were 126 patients (69% women) aged 19-76 years (median 53), who were diagnosed with 142 meningiomas. Patients underwent surgery (n=111) and radiotherapy (n=15) in 2016-2018. The MRI protocol included T1, T2, T2-FLAIR, DWI and post-contrast T1-weighted images in three projections, diffusion tensor MRI in 27 cases and MR spectroscopy in 21 patients.

RESULTS

Peritumoral edema was detected in 46% (n=66) of cases including 21 (31%) patients with severe edema. The ALPS index was 1.510±0.1931 in meningiomas without edema and 1.308±0.19 in those with edema (p=0.014). There was positive correlation between edema, dimensions and uneven contours of meningioma, as well as negative correlation with CSF cleft sign. Blood flow velocity was higher in atypical and anaplastic meningiomas with edema (p=0.03). Other signs (localization, histological variant, malignancy grade, characteristics of MR signal, peaks of the main metabolites, diffusion and perfusion parameters of tumor) did not significantly affect peritumoral edema in patients with meningiomas (p>0.05).

CONCLUSION

Diffusion tensor tomography with ALPS index revealed significant effect of glymphatic system dysfunction on peritumoral edema. Large meningioma with uneven contours increased the risk of peritumoral edema, while CSF cleft sign reduced this risk. Other factors did not affect cerebral edema in meningiomas.

Glymphatic Dysfunction in Patients With Ischemic Stroke

Objectives: Rodent experiments have provided some insight into the changes of glymphatic function in ischemic stroke. 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 ischemic stroke. We aimed to investigate the changes of glymphatic function in ischemic stroke and the factors associated with the changes. Materials and Methods: A total of 50 patients (mean age 56.7 years; 30 men) and 44 normal subjects (mean age 53.3 years; 23 men) who had preoperative diffusion-tensor imaging for calculation of the analysis along the perivascular space (ALPS) index were retrospectively included. Information collected from each patient included sex, age, time since stroke onset, infarct location, hemorrhagic change, infarct volume, infarct apparent diffusion coefficient (ADC), infarct fractional anisotropy (FA), and ALPS index of both hemispheres. Interhemispheric differences in ALPS index (infarct side vs. contralateral normal side) were assessed with a paired t-test in all patients. ALPS index was normalized by calculating ALPS ratios (right-to-left and left-to-right) for comparisons between patients and normal subjects. Comparisons of ALPS ratios between patients and normal subjects were performed using analysis of covariance with adjustments for age and sex. Linear regression analyses were performed to identify factors associated with the ALPS index. Results: In patients, the mean ALPS index ipsilateral to infarct was 1.162 ± 0.126, significantly lower (P < 0.001) than that of the contralateral side (1.335 ± 0.160). The right-to-left ALPS index ratio of patients with right cerebral infarct was 0.84 ± 0.08, significantly lower (P < 0.001) than that of normal subjects (0.95 ± 0.07). The left-to-right ALPS ratio of patients with left cerebral infarct was 0.92 ± 0.09, significantly (P < 0.001) lower than that of normal subjects (1.05 ± 0.08). On multiple linear regression analysis, time since stroke onset (β = 0.794, P < 0.001) was the only factor associated with the ALPS index. Conclusion: The ALPS index showed lower values in ischemic stroke suggesting impaired glymphatic function. Following initial impairment, the ALPS index increased with the time since stroke onset, which is suggestive of glymphatic function recovery.

Peritumoral Brain Edema in Metastases May Be Related to Glymphatic Dysfunction

Objectives

The proliferation of microvessels with increased permeability is thought to be the cause of peritumoral brain edema (PTBE) in metastases. The contribution of the glymphatic system to the formation of PTBE in brain metastases remains unexplored. We aimed to investigate if the PTBE volume of brain metastases is related to glymphatic dysfunction.

Materials and Methods

A total of 56 patients with brain metastases who had preoperative dynamic susceptibility contrast-enhanced perfusion-weighted imaging for calculation of tumor cerebral blood volume (CBV) and diffusion tensor imaging for calculations of tumor apparent diffusion coefficient (ADC), tumor fractional anisotropy (FA), and analysis along perivascular space (ALPS) index were analyzed. The volumes of PTBE, whole tumor, enhancing tumor, and necrotic and hemorrhagic portions were manually measured. Additional information collected for each patient included age, sex, primary cancer, metastasis location and number, and the presence of concurrent infratentorial tumors. Linear regression analyses were performed to identify factors associated with PTBE volume.

Results

Among 56 patients, 45 had solitary metastasis, 24 had right cerebral metastasis, 21 had left cerebral metastasis, 11 had bilateral cerebral metastases, and 11 had concurrent infratentorial metastases. On univariable linear regression analysis, PTBE volume correlated with whole tumor volume (β = -0.348, P = 0.009), hemorrhagic portion volume (β = -0.327, P = 0.014), tumor ADC (β = 0.530, P <.001), and ALPS index (β = -0.750, P <.001). The associations of PTBE volume with age, sex, tumor location, number of tumors, concurrent infratentorial tumor, enhancing tumor volume, necrotic portion volume, tumor FA, and tumor CBV were not significant. On multivariable linear regression analysis, tumor ADC (β = 0.303; P = 0.004) and ALPS index (β = -0.624; P < 0.001) were the two independent factors associated with PTBE volume.

Conclusion

Metastases with higher tumor ADC and lower ALPS index were associated with larger peritumoral brain edema volumes. The higher tumor ADC may be related to increased periarterial water influx into the tumor interstitium, while the lower ALPS index may indicate insufficient fluid clearance. The changes in both tumor ADC and ALPS index may imply glymphatic dysfunction, which is, at least, partially responsible for peritumoral brain edema formation.

Peritumoral Brain Edema in Meningiomas May Be Related to Glymphatic Dysfunction

The pathogenesis of peritumoral brain edema (PTBE) in meningiomas remains unclear. The glymphatic system is recently recognized as a pathway for waste clearance and maintaining fluid balance in the brain parenchymal interstitium. We aimed to investigate if the PTBE volume of meningiomas correlates with their glymphatic function. A total of 80 meningioma patients (mean age, 58.8 years; 37 men) and 44 normal subjects (mean age 53.3 years; 23 men) who had preoperative diffusion-tensor imaging for calculation of the analysis along the perivascular space (ALPS) index were retrospectively included. Information collected from each patient included sex, age, tumor grade, Ki-67 index, tumor location, tumor volume, PTBE volume and ALPS index. Comparisons of ALPS index among meningiomas without PTBE, meningiomas with PTBE, and normal subjects were performed using analysis of covariance with Bonferroni correction and adjustments for age and sex. Pearson correlation coefficient and multivariable linear regression analyses were performed to identify factors associated with PTBE volume. Group comparisons revealed that the ALPS index was significantly higher (P < 0.05) in meningiomas without PTBE vs. meningiomas with PTBE and normal subjects. On the other hand, ALPS index was not different between meningiomas with PTBE and normal subjects. On Pearson correlation and multivariable linear regression analyses, the ALPS index was the only factor significantly (P < 0.05) associated with PTBE volume. In conclusion, PTBE volume inversely correlated with ALPS index in meningiomas. PTBE formation in meningiomas may be related to glymphatic dysfunction.