The Corpus Callosum Wallerian Degeneration in the Unilateral Brain Tumors: Evaluation with Diffusion Tensor Imaging (DTI)

Assessment of structural disconnections in gliomas: comparison of indirect and direct approaches

Gliomas are amongst the most common primary brain tumours in adults and are often associated with poor prognosis. Understanding the extent of white matter (WM) which is affected outside the tumoral lesion may be of paramount importance to explain cognitive deficits and the clinical progression of the disease. To this end, we explored both direct (i.e., tractography based) and indirect (i.e., atlas-based) approaches to quantifying WM structural disconnections in a cohort of 44 high- and low-grade glioma patients. While these methodologies have recently gained popularity in the context of stroke and other pathologies, to our knowledge, this is the first time they are applied in patients with brain tumours. More specifically, in this work, we present a quantitative comparison of the disconnection maps provided by the two methodologies by applying well-known metrics of spatial similarity, extension, and correlation. Given the important role the oedematous tissue plays in the physiopathology of tumours, we performed these analyses both by including and excluding it in the definition of the tumoral lesion. This was done to investigate possible differences determined by this choice. We found that direct and indirect approaches offer two distinct pictures of structural disconnections in patients affected by brain gliomas, presenting key differences in several regions of the brain. Following the outcomes of our analysis, we eventually discuss the strengths and pitfalls of these two approaches when applied in this critical field.

Magnetic Resonance Imaging Correlates of Immune Microenvironment in Glioblastoma

Background

Glioblastoma (GBM) is the most commonly occurring primary malignant brain tumor, and it carries a dismal prognosis. Focusing on the tumor microenvironment may provide new insights into pathogenesis, but no clinical tools are available to do this. We hypothesized that the infiltration of different leukocyte populations in the tumoral and peritumoral brain tissues may be measured by magnetic resonance imaging (MRI).

Methods

Pre-operative MRI was combined with immune phenotyping of intraoperative tumor tissue based on flow cytometry of myeloid cell populations that are associated with immune suppression, namely, microglia and bone marrow-derived macrophages (BMDM). These cell populations were measured from the central and marginal areas of the lesion identified intraoperatively with 5-aminolevulinic acid-guided surgery. MRI features (volume, mean and standard deviation of signal intensity, and fractality) were derived from all MR sequences (T1w, Gd+ T1w, T2w, FLAIR) and ADC MR maps and from different tumor areas (contrast- and non-contrast-enhancing tumor, necrosis, and edema). The principal components of MRI features were correlated with different myeloid cell populations by Pearson's correlation.

Results

We analyzed 126 samples from 62 GBM patients. The ratio between BMDM and microglia decreases significantly from the central core to the periphery. Several MRI-derived principal components were significantly correlated (p <0.05, r range: [-0.29, -0.41]) with the BMDM/microglia ratio collected in the central part of the tumor.

Conclusions

We report a significant correlation between structural MRI clinical imaging and the ratio of recruited vs. resident macrophages with different immunomodulatory activities. MRI features may represent a novel tool for investigating the microenvironment of GBM.

Early Detection of Radiation-Induced Injury and Prediction of Cognitive Deficit by MRS Metabolites in Radiotherapy of Low-Grade Glioma

Purpose

To compare the sensitivity of MRS metabolites and MoCA and ACE-R cognitive tests in the detection of radiation-induced injury in low grade glioma (LGG) patients in early and early delayed postradiation stages.

Methods

MRS metabolite ratios of NAA/Cr and Cho/Cr, ACE-R and MoCA cognitive tests, and dosimetric parameters in corpus callosum were analyzed during RT and up to 6-month post-RT for ten LGG patients.

Results

Compared to pre RT baseline, a significant decline in both NAA/Cr and Cho/Cr in the corpus callosum was seen at the 4th week of RT, 1, 3, and 6-month post-RT. These declines were detected at least 3 months before the detection of declines in cognitive functions by ACE-R and MoCA tools. Moreover, NAA/Cr alterations at 4th week of RT and 1-month post-RT were significantly negatively correlated with the mean dose received by the corpus callosum, as well as the corpus callosum 40 Gy dose volume, i.e., the volume of the corpus callosum receiving a dose greater than 40 Gy.

Conclusion

MRS-based biomarkers may be more sensitive than the state-of-the-art cognitive tests in the prediction of postradiation cognitive impairments. They would be utilized in treatment planning and dose sparing protocols, with a specific focus on the corpus callosum in the radiation therapy of LGG patients.

Functional connectivity of the default mode, dorsal attention and fronto-parietal executive control networks in glial tumor patients

PURPOSE

Resting state functional magnetic resonance imaging (rsfMRI) is an emerging tool to explore the functional connectivity of different brain regions. We aimed to assess the disruption of functional connectivity of the Default Mode Network (DMN), Dorsal Attention Network(DAN) and Fronto-Parietal Network (FPN) in patients with glial tumors.

METHODS

rsfMRI data acquired on 3T-MR of treatment-naive glioma patients prospectively recruited (2015-2019) and matched controls from the 1000 functional-connectomes-project were analyzed using the CONN functional toolbox. Seed-Based Connectivity Analysis (SBCA) and Independent Component Analysis (ICA, with 10 to 100 components) were performed to study reliably the three networks of interest.

RESULTS

35 patients with gliomas (17 WHO grade I-II, 18 grade III-IV) and 70 controls were included. Global increased DMN connectivity was consistently found with SBCA and ICA in patients compared to controls (Cluster1: Precuneus, height: p < 10^-6; Cluster2: subcallosum; height: p < 10^-5). However, an area of decreased connectivity was found in the posterior corpus callosum, particularly in high-grade gliomas (height: p < 10^-5). The DAN demonstrated small areas of increased connectivity in frontal and occipital regions (height: p < 10^-6). For the FPN, increased connectivity was noted in the precuneus, posterior cingulate gyrus, and frontal cortex. No difference in the connectivity of the networks of interest was demonstrated between low- and high-grade gliomas, as well as when stratified by their IDH1-R132H (isocitrate dehydrogenase) mutation status.

CONCLUSION

Altered functional connectivity is reliably found with SBCA and ICA in the DMN, DAN, and FPN in glioma patients, possibly explained by decreased connectivity between the cerebral hemispheres across the corpus callosum due to disruption of the connections.

Quantitative assessment of changes in diffusion tensor imaging (DTI) metrics along the courses of the cortico-ponto-cerebellar tracts secondary to supratentorial human brain glial tumors

BACKGROUND

The cortico-ponto-cerebellar tract (CPCT) is the largest projection pathway, which synapses at the pons. Remote effects of supratentorial brain tumors have not been evaluated along the infratentorial course of the CPCT.

AIM

The purpose of this study is to evaluate the possible lateralization of the diffusion tensor metrics of the affected CPCT in patients with supratentorial brain tumor.

METHODS AND RESULTS

We included 39 patients with 29 left-sided tumors (LST) and 10 right-sided tumors, retrospectively. We measured the magnitude of changes of the fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values of the CPCT prior to the brain surgery at the level of crus cerebri and middle cerebellar peduncle. Regions of interest (ROIs) were placed on the lateral side of crus cerebri, and ROI-1 (anterior 1/3), ROI-2 (middle 1/3), ROI-3 (posterior 1/3), and ROI-4 were placed at the level of middle cerebellar peduncle. We hypothesized that there would be decreased FA and increased ADC values of the ipsilesional CPCT compared with contralesional CPCT. Ipsilesional FA values were decreased with simultaneous increased ADC value along the CPCT compared with contralesional CPCT in following ROIs, ROI-1 (LST FA: P = .005, ADC: P = .037) and ROI-3 (LST FA: P = .049, ADC: P = .049), respectively. Affected ROI-4 in LST cases also showed lower FA values, although not statistically significant.

CONCLUSION

We observed a statistically significant FA value decrease and ADC increase along the left ROI-1 and ROI-3 as well as the nonstatistically significant FA decrease of the left ROI-4 at the second neuron level when there was a related supratentorial tumor. These findings are suggestive of presynaptic and postsynaptic microstructural changes of these tracts following the presynaptic involvement by a primary supratentorial brain tumor.

Diffusion Tensor Imaging Shows Corpus Callosum Differences between High-Grade Gliomas and Metastases

BACKGROUND AND PURPOSE

The corpus callosum (CC) has an important role in regulating interhemispheric transfer and is thought to be instrumental in contralateral brain reorganization in patients with brain tumors, as suggested by a previous study reporting callosal differences between language dominance groups through diffusion tensor imaging (DTI) characteristics. The purpose of this study was to explore the structural differences in the CC between high-grade gliomas (HGGs) and metastatic tumors (METs) using the DTI characteristics of fractional anisotropy (FA), mean diffusivity (MD), and axial diffusivity (AD).

METHODS

HGG (n = 30) and MET (n = 20) subjects with Magnetic Resonance Imaging (MRI) scans including DTI were retrospectively studied. The tumor and CC were segmented using the 3-dimensional T1-weighted scans to determine their volumes. The region of interest (ROI; mean volume of the ROI = 3,090 ± 464 mm³ ) of the body of the CC was overlaid onto the DTI parametric maps to obtain the averaged FA, MD, and AD values.

RESULTS

There were significant differences in the distributions of FA and MD values between the two patient groups (mean FA for HGG/MET = .691/.646, P < .05; mean MD for HGG/MET = .894×10-3 mm 2/ second /.992×10-3 mm² /second, P < .01), while there was no correlation between the DTI parameters and the anatomical volumes.

CONCLUSION

These results suggest that there is more contralateral brain reorganization in HGG patients than MET patients and that neither the tumor nor callosal volume impact the degree of contralateral brain reorganization.

The value of diffusion tensor imaging in differentiating high-grade gliomas from brain metastases: a systematic review and meta-analysis

Purpose

Differentiation of high-grade gliomas and solitary brain metastases is an important clinical issue because the treatment strategies differ greatly. Our study aimed to investigate the potential value of diffusion tensor imaging (DTI) in differentiating high-grade gliomas from brain metastases using a meta-analytic approach.

Materials and Methods

We searched Pubmed, Embase and the Cochrane Library for relevant articles published in English. Studies that both investigated high-grade gliomas and brain metastases using DTI were included. Random effect model was used to compare fractional anisotropy (FA) and mean diffusivity (MD) values in the two tumor entities.

Results

Nine studies were included into the meta-analysis. In the peritumoral region, compared with brain metastases, high-grade gliomas had a significant increase of FA (SMD  = 0.47; 95% CI, 0.22–0.71; P<0.01) and a significant decrease of MD (SMD  = −1.49; 95% CI, −1.91 to −1.06; P<0.01). However, in the intratumoral area, no significant change in FA (SMD  = 0.16; 95% CI, −0.49 to 0.82; P = 0.73) or MD (SMD  = 0.34; 95% CI, −0.91 to 1.60; P = 0.59) was detected between gliomas and metastases.

Conclusions

High-grade gliomas may be distinguished from brain metastases by comparing the peritumoral FA and MD values. DTI appears to be a promising tool in diagnosing solitary intracranial lesions.

Global diffusion tensor imaging derived metrics differentiate glioblastoma multiforme vs. normal brains by using discriminant analysis: introduction of a novel whole-brain approach

Background

Histological behavior of glioblastoma multiforme suggests it would benefit more from a global rather than regional evaluation. A global (whole-brain) calculation of diffusion tensor imaging (DTI) derived tensor metrics offers a valid method to detect the integrity of white matter structures without missing infiltrated brain areas not seen in conventional sequences. In this study we calculated a predictive model of brain infiltration in patients with glioblastoma using global tensor metrics.

Methods

Retrospective, case and control study; 11 global DTI-derived tensor metrics were calculated in 27 patients with glioblastoma multiforme and 34 controls: mean diffusivity, fractional anisotropy, pure isotropic diffusion, pure anisotropic diffusion, the total magnitude of the diffusion tensor, linear tensor, planar tensor, spherical tensor, relative anisotropy, axial diffusivity and radial diffusivity. The multivariate discriminant analysis of these variables (including age) with a diagnostic test evaluation was performed.

Results

The simultaneous analysis of 732 measures from 12 continuous variables in 61 subjects revealed one discriminant model that significantly differentiated normal brains and brains with glioblastoma: Wilks’ λ = 0.324, χ² (3) = 38.907, p < .001. The overall predictive accuracy was 92.7%.

Conclusions

We present a phase II study introducing a novel global approach using DTI-derived biomarkers of brain impairment. The final predictive model selected only three metrics: axial diffusivity, spherical tensor and linear tensor. These metrics might be clinically applied for diagnosis, follow-up, and the study of other neurological diseases.

Predicting future brain tissue loss from white matter connectivity disruption in ischemic stroke

BACKGROUND AND PURPOSE

The Network Modification (NeMo) Tool uses a library of brain connectivity maps from normal subjects to quantify the amount of structural connectivity loss caused by focal brain lesions. We hypothesized that the Network Modification Tool could predict remote brain tissue loss caused by poststroke loss of connectivity.

METHODS

Baseline and follow-up MRIs (10.7±7.5 months apart) from 26 patients with acute ischemic stroke (age, 74.6±14.1 years, initial National Institutes of Health Stroke Scale, 3.1±3.1) were collected. Lesion masks derived from diffusion-weighted images were superimposed on the Network Modification Tool's connectivity maps, and regional structural connectivity losses were estimated via the Change in Connectivity (ChaCo) score (ie, the percentage of tracks connecting to a given region that pass through the lesion mask). ChaCo scores were correlated with subsequent atrophy.

RESULTS

Stroke lesions' size and location varied, but they were more frequent in the left hemisphere. ChaCo scores, generally higher in regions near stroke lesions, reflected this lateralization and heterogeneity. ChaCo scores were highest in the postcentral and precentral gyri, insula, middle cingulate, thalami, putamen, caudate nuclei, and pallidum. Moderate, significant partial correlations were found between baseline ChaCo scores and measures of subsequent tissue loss (r=0.43, P=4.6×10(-9); r=0.61, P=1.4×10(-18)), correcting for the time between scans.

CONCLUSIONS

ChaCo scores varied, but the most affected regions included those with sensorimotor, perception, learning, and memory functions. Correlations between baseline ChaCo and subsequent tissue loss suggest that the Network Modification Tool could be used to identify regions most susceptible to remote degeneration from acute infarcts.