The dynamic functional connectivity fingerprint of high-grade gliomas.

Resting state fMRI has been used in many studies to investigate the impact of brain tumours on functional connectivity (FC). However, these studies have so far assumed that FC is stationary, disregarding the fact that the brain fluctuates over dynamic states. Here we utilised resting state fMRI data from 33 patients with high-grade gliomas and 33 healthy controls to examine the dynamic interplay between resting-state networks and to gain insights into the impact of brain tumours on functional dynamics. By employing Hidden Markov Models, we demonstrated that functional dynamics persist even in the presence of a high-grade glioma, and that patients exhibited a global decrease of connections strength, as well as of network segregation. Furthermore, through a multivariate analysis, we demonstrated that patients' cognitive scores are highly predictive of pathological dynamics, thus supporting our hypothesis that functional dynamics could serve as valuable biomarkers for better understanding the traits of high-grade gliomas.

The ImSURE phantoms: a digital dataset for radiomic software benchmarking and investigation.

In radiology and oncology, radiomic models are increasingly employed to predict clinical outcomes, but their clinical deployment has been hampered by lack of standardisation. This hindrance has driven the international Image Biomarker Standardisation Initiative (IBSI) to define guidelines for image pre-processing, standardise the formulation and nomenclature of 169 radiomic features and share two benchmark digital phantoms for software calibration. However, to better assess the concordance of radiomic tools, more heterogeneous phantoms are needed. We created two digital phantoms, called ImSURE phantoms, having isotropic and anisotropic voxel size, respectively, and 90 regions of interest (ROIs) each. To use these phantoms, we designed a systematic feature extraction workflow including 919 different feature values (obtained from the 169 IBSI-standardised features considering all possible combinations of feature aggregation and intensity discretisation methods). The ImSURE phantoms will allow to assess the concordance of radiomic software depending on interpolation, discretisation and aggregation methods, as well as on ROI volume and shape. Eventually, we provide the feature values extracted from these phantoms using five open-source IBSI-compliant software.

Presurgical predictors of early cognitive outcome after brain tumor resection in glioma patients.

Gliomas are commonly characterized by neurocognitive deficits that strongly impact patients' and caregivers' quality of life. Surgical resection is the mainstay of therapy, and it can also cause cognitive impairment. An important clinical problem is whether patients who undergo surgery will show post-surgical cognitive impairment above and beyond that present before surgery. The relevant rognostic factors are largely unknown. This study aims to quantify the cognitive impairment in glioma patients 1-week after surgery and to compare different pre-surgical information (i.e., cognitive performance, tumor volume, grading, and lesion topography) towards predicting early post-surgical cognitive outcome. We retrospectively recruited a sample of N = 47 patients affected by high-grade and low-grade glioma undergoing brain surgery for tumor resection. Cognitive performance was assessed before and immediately after (∼1 week) surgery with an extensive neurocognitive battery. Multivariate linear regression models highlighted the combination of predictors that best explained post-surgical cognitive impairment. The impact of surgery on cognitive functioning was relatively small (i.e., 85% of test scores across the whole sample indicated no decline), and pre-operative cognitive performance was the main predictor of early post-surgical cognitive outcome above and beyond information from tumor topography and volume. In fact, structural lesion information did not significantly improve the accuracy of prediction made from cognitive data before surgery. Our findings suggest that post-surgery neurocognitive deficits are only partially explained by preoperative brain damage. The present results suggest the possibility to make reliable, individualized, and clinically relevant predictions from relatively easy-to-obtain information.

Image-derived Input Function in brain [18F]FDG PET data: which alternatives to the carotid siphons?

Quantification of brain [18F] fluorodeoxyglucose ([18F]FDG) positron emission tomography (PET) data requires an input function. A noninvasive alternative to gold-standard arterial sampling is the image-derived input function (IDIF), typically extracted from the internal carotid arteries (ICAs), which are however difficult to segment and subjected to spillover effects. In this work, we evaluated the feasibility of extracting the IDIF from two different vascular sites, i.e., 1) common carotids (CCA) and 2) superior sagittal sinus (SSS), other than 3) ICA in a large group of glioma patients undergoing a dynamic [18F]FDG PET acquisition on a hybrid PET/MR scanner. Comparisons are drawn between the different IDIFs in terms of peak amplitude and shape, as well as between the estimates of fractional uptake rate (Kr) obtained from the different extraction sites in terms of a) grey/white matter average absolute values, b) ratio of grey-to-white matter, and c) spatial patterns for the hemisphere contralateral to the lesion. Clinical Relevance - This work points towards new feasible IDIF extraction sites (CCA in particular) which could allow for fully noninvasive absolute PET quantification in clinical populations.

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.

Widespread cortical functional disconnection in gliomas: an individual network mapping approach.

Assessment of impaired/preserved cortical regions in brain tumours is typically performed via intraoperative direct brain stimulation of eloquent areas or task-based functional MRI. One main limitation is that they overlook distal brain regions or networks that could be functionally impaired by the tumour. This study aims (i) to investigate the impact of brain tumours on the cortical synchronization of brain networks measured with resting-state functional magnetic resonance imaging (resting-state networks) both near the lesion and remotely and (ii) to test whether potential changes in resting-state networks correlate with cognitive status. The sample included 24 glioma patients (mean age: 58.1 ± 16.4 years) with different pathological staging. We developed a new method for single subject localization of resting-state networks abnormalities. First, we derived the spatial pattern of the main resting-state networks by means of the group-guided independent component analysis. This was informed by a high-resolution resting-state networks template derived from an independent sample of healthy controls. Second, we developed a spatial similarity index to measure differences in network topography and strength between healthy controls and individual brain tumour patients. Next, we investigated the spatial relationship between altered networks and tumour location. Finally, multivariate analyses related cognitive scores across multiple cognitive domains (attention, language, memory, decision making) with patterns of multi-network abnormality. We found that brain gliomas cause broad alterations of resting-state networks topography that occurred mainly in structurally normal regions outside the tumour and oedema region. Cortical regions near the tumour often showed normal synchronization. Finally, multi-network abnormalities predicted attention deficits. Overall, we present a novel method for the functional localization of resting-state networks abnormalities in individual glioma patients. These abnormalities partially explain cognitive disabilities and shall be carefully navigated during surgery.

Impaired cognitive control in patients with brain tumors.

Though the assessment of cognitive functions is proven to be a reliable prognostic indicator in patients with brain tumors, some of these functions, such as cognitive control, are still rarely investigated. The objective of this study was to examine proactive and reactive control functions in patients with focal brain tumors and to identify lesioned brain areas more at "risk" for developing impairment of these functions. To this end, a group of twenty-two patients, candidate to surgery, were tested with an AX-CPT task and a Stroop task, along with a clinical neuropsychological assessment, and their performance was compared to that of a well-matched healthy control group. Although overall accuracy and response times were similar for patients and control groups, the patient group failed more on the BX trials of the AX-CPT task and on the incongruent trials of the Stroop task, specifically. Behavioral results were associated with the damaged brain areas, mostly distributed in right frontal regions, by means of a lesion-symptom mapping multivariate approach. This analysis showed that a white matter cluster in the right prefrontal area was associated with lower d'-context values on the AX-CPT, which reflected the fact that these patients rely more on later information (reactive processes) to respond to unexpected and conflicting stimuli, than on earlier contextual cues (proactive processes). Taken together, these results suggest that patients with brain tumors present an imbalance between proactive and reactive control strategies in high interfering conditions, in association with right prefrontal white matter lesions.

Diffusion-based microstructure models in brain tumours: Fitting in presence of a model-microstructure mismatch.

Diffusion-based biophysical models have been used in several recent works to study the microenvironment of brain tumours. While the pathophysiological interpretation of the parameters of these models remains unclear, their use as signal representations may yield useful biomarkers for monitoring the treatment and the progression of this complex and heterogeneous disease. Up to now, however, no study was devoted to assessing the mathematical stability of these approaches in cancerous brain regions. To this end, we analyzed in 11 brain tumour patients the fitting results of two microstructure models (Neurite Orientation Dispersion and Density Imaging and the Spherical Mean Technique) and of a signal representation (Diffusion Kurtosis Imaging) to compare the reliability of their parameter estimates in the healthy brain and in the tumoral lesion. The framework of our between-tissue analysis included the computation of 1) the residual sum of squares as a goodness-of-fit measure 2) the standard deviation of the models' derived metrics and 3) models' sensitivity functions to analyze the suitability of the employed protocol for parameter estimation in the different microenvironments. Our results revealed no issues concerning the fitting of the models in the tumoral lesion, with similar goodness of fit and parameter precisions occurring in normal appearing and pathological tissues. Lastly, with the aim of highlight possible biomarkers, in our analysis we briefly discuss the correlation between the metrics of the three techniques, identifying groups of indices which are significantly collinear in all tissues and thus provide no additional information when jointly used in data-driven analyses.

The contribution of beta-amyloid to dementia in Lewy body diseases: a 1-year follow-up study.

Dementia in Lewy Body Diseases (Parkinson's disease and dementia with Lewy Bodies) affects progression of disabilities, quality of life and well-being. Understanding its pathogenetic mechanisms is critical to properly implement disease-modifying strategies. It has been hypothesized that synuclein- and amyloid-pathology act synergistically aggravating cognitive decline in elderly patients but their precise contribution to dementia is debated. In this study, we aimed at exploring if presence of amyloid deposits influences clinical, cognitive and neuroanatomical correlates of mental decline in a cohort of 40 Parkinson's disease patients with normal cognition (n = 5), mild cognitive impairment (n = 22), and dementia (n = 13) as well as in Dementia with Lewy Bodies (n = 10). Patients underwent simultaneous 3 T PET/MRI with [18F]-flutemetamol and were assessed with an extensive baseline motor and neuropsychological examination, which allowed level II diagnosis of mild cognitive impairment and dementia. The role of amyloid positivity on each cognitive domain, and on the rate of conversion to dementia at 1-year follow-up was explored. A Kaplan Meier and the Log Rank (Mantel-Cox) test were used to assess the pairwise differences in time-to-develop dementia in Parkinson's disease patients with and without significant amyloidosis. Furthermore, the presence of an Alzheimer's dementia-like morphological pattern was evaluated using visual and automated assessment of T1-weighted and T2-weighted MRI images. We observed similar percentage of amyloid deposits in Parkinson's disease dementia and dementia with Lewy Bodies cohorts (50% in each group) with an overall prevalence of 34% of significant amyloid depositions in Lewy Body Diseases. PET amyloid positivity was associated with worse global cognition (Montreal Cognitive Assessment and Mini Mental State Examination), executive and language difficulties. At 12-month follow-up, amyloid positive Parkinson's disease patients were more likely to have become demented than those without amyloidosis. Moreover, there was no difference in the presence of an Alzheimer's disease-like atrophy pattern and in vascular load (at Fazekas scale) between Lewy Body Diseases with and without significant amyloid deposits. Our findings suggest that in Lewy Body Diseases, amyloid deposition enhances cognitive deficits, particularly attention-executive and language dysfunctions. However, the large number of patients without significant amyloid deposits among our cognitively impaired patients indicates that synuclein pathology itself plays a critical role in the development of dementia in Lewy Body Diseases.

Preoperative Prediction of Facial Nerve in Patients with Vestibular Schwannomas: The Role of Diffusion Tensor Imaging-A Systematic Review.

In vestibular schwannoma surgery, the preservation of facial and cochlear nerves is of paramount concern regarding to their effect on patients' quality of life. The rate of nerve function preservation has increased with advancements in surgical technique and neuroimaging and the introduction of intraoperative neuromonitoring. The preoperative depiction of anatomical issues between the nerves and tumor could help in surgical planning. Many studies investigating advanced imaging for cranial nerves detection, in particular diffusion tensor imaging, have been reported in the past decade. A systematic review of the reported data evaluating preoperative facial nerve fiber tracking, followed by intraoperative verification, was conducted. Seventeen studies with 223 patients (mean age, 47.5 years; range 17-77; male/female ratio 1:1.4) met our inclusion criteria. Preoperative facial nerve fiber tracking was obtained for 214 patients (96%), and subsequent intraoperative verification revealed a correct prediction for 187 cases (85.5%). The results from the present review have confirmed that preoperative fiber tracking for facial nerve identification during large vestibular schwannoma surgery is valuable and reliable. However, the included studies were not comparable in terms of images, acquisitions, or postprocessing elaboration. Larger series and homogenous magnetic resonance imaging parameters are required to strengthen these findings.

The kinetics of 18F-FDG in lung cancer: compartmental models and voxel analysis.

BACKGROUND: The validation of the most appropriate compartmental model that describes the kinetics of a specific tracer within a specific tissue is mandatory before estimating quantitative parameters, since the behaviour of a tracer can be different among organs and diseases, as well as between primary tumours and metastases. The aims of our study were to assess which compartmental model better describes the kinetics of 18F-Fluorodeoxygluxose(18F-FDG) in primary lung cancers and in metastatic lymph nodes; to evaluate whether quantitative parameters, estimated using different innovative technologies, are different between lung cancers and lymph nodes; and to evaluate the intra-tumour inhomogeneity. RESULTS: Twenty-one patients (7 females; 71 ± 9.4 years) with histologically proved lung cancer, prospectively evaluated, underwent 18F-FDG PET-CT for staging. Spectral analysis iterative filter (SAIF) method was used to design the most appropriate compartmental model. Among the compartmental models arranged using the number of compartments suggested by SAIF results, the best one was selected according to Akaike information criterion (AIC). Quantitative analysis was performed at the voxel level. K1, Vb and Ki were estimated with three advanced methods: SAIF approach, Patlak analysis and the selected compartmental model. Pearson's correlation and non-parametric tests were used for statistics. SAIF showed three possible irreversible compartmental models: Tr-1R, Tr-2R and Tr-3R. According to well-known 18F-FDG physiology, the structure of the compartmental models was supposed to be catenary. AIC indicated the Sokoloff's compartmental model (3K) as the best one. Excellent correlation was found between Ki estimated by Patlak and by SAIF (R2 = 0.97, R2 = 0.94, at the global and the voxel level respectively), and between Ki estimated by 3K and by SAIF (R2 = 0.98, R2 = 0.95, at the global and the voxel level respectively). Using the 3K model, the lymph nodes showed higher mean and standard deviation of Vb than lung cancers (p < 0.0014, p < 0.0001 respectively) and higher standard deviation of K1 (p < 0.005). CONCLUSIONS: One-tissue reversible plus one-tissue irreversible compartmental model better describes the kinetics of 18F-FDG in lung cancers, metastatic lymph nodes and normal lung tissues. Quantitative parameters, estimated at the voxel level applying different advanced approaches, show the inhomogeneity of neoplastic tissues. Differences in metabolic activity and in vascularization, highlighted among all cancers and within each individual cancer, confirm the wide variability in lung cancers and metastatic lymph nodes. These findings support the need of a personalization of therapeutic approaches.

Frequency and time-frequency analysis of intraoperative ECoG during awake brain stimulation.

Electrocortical stimulation remains the standard for functional brain mapping of eloquent areas to prevent postoperative functional deficits. The aim of this study was to investigate whether the short-train technique (monopolar stimulation) and Penfield's technique (bipolar stimulation) would induce different effects on brain oscillatory activity in awake patients, as quantified by electrocorticography (ECoG). The study population was seven patients undergoing brain tumor surgery. Intraoperative bipolar and monopolar electrical stimulation for cortical mapping was performed during awake surgery. ECoG was recorded using 1 × 8 electrode strip. Spectral estimation was calculated using a parametric approach based on an autoregressive model. Wavelet-based time-frequency analysis was then applied to evaluate the temporal evolution of brain oscillatory activity. Both monopolar and bipolar stimulation produced an increment in delta and a decrease in beta powers for the motor and the sensory channels. These phenomena lasted about 4 s. Comparison between monopolar and bipolar stimulation showed no significant difference in brain activity. Given the importance of quantitative signal analysis for evaluating response accuracy, ECoG recording during electrical stimulation is necessary to characterize the dynamic processes underlying changes in cortical responses in vivo. This study is a preliminary approach to the quantitative analysis of post-stimulation ECoG signals.

Assessment of clinical data of nonlinear stochastic deconvolution versus block-circulant singular value decomposition for quantitative dynamic susceptibility contrast magnetic resonance imaging.

Dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) allows the noninvasive assessment of brain hemodynamics alterations by quantifying, via deconvolution, the cerebral blood flow (CBF) and mean transit time (MTT). Singular value decomposition (SVD) and block-circulant SVD (cSVD) are the most widely adopted deconvolution method, although they bear some limitations, including unphysiological oscillations in the residue function and bias in the presence of delay and dispersion between the tissue and the arterial input function. A nonlinear stochastic regularization (NSR) has been proposed, which performs better than SVD and cSVD on simulated data both in the presence and absence of dispersion. Moreover, NSR allows to quantify the dispersion level. Here, cSVD and NSR are compared for the first time on a group of nine patients with severe atherosclerotic unilateral stenosis of internal carotid artery before and after carotid stenting to investigate the effect of arterial dispersion. According to region of interest-based analysis, NSR characterizes the pathologic tissue more accurately than cSVD, thus improving the quality of the information provided to physicians for diagnosis. In fact, in 7 (78%) of the 9 subjects, CBF and MTT maps provided by NSR allow to correctly identify the pathologic hemisphere to the physician. Moreover, by emphasizing the difference between pathologic and healthy tissues, NSR may be successfully used to monitor the subject's recovery after the treatment and/or surgery. NSR also generates dispersion level and non-dispersed CBF and MTT maps. The dispersion level provides information on CBF and MTT estimates reliability and may also be used as a clinical indicator of pathological tissue state complementary to CBF and MTT, thus increasing the clinical information provided by DSC-MRI analysis.

Novel reference region model reveals increased microglial and reduced vascular binding of 11C-(R)-PK11195 in patients with Alzheimer's disease.

UNLABELLED: 11C-(R)-PK11195 is a PET radiotracer for the quantification of peripheral benzodiazepine binding sites (PBBSs). The PBBS is a consistent marker of activated microglia, and 11C-(R)-PK11195 has been used to image microglial activity in the diseased brain and in neoplasia. However, the PBBS is also expressed in the brain vasculature (endothelium and smooth muscles), and no evidence, to our knowledge, exists of a change in the vascular PBBS in pathologic brains or of such a change having an effect on the quantification of 11C-(R)-PK11195 binding. To investigate this issue, we have used a modified reference-tissue model (SRTMV) that accounts for tracer vascular activity both in reference and target tissues and applied it for the estimation of binding potential (BP) in a cohort of patients with Alzheimer's disease (AD). METHODS: A total of 10 patients with AD and 10 age-matched healthy subjects who underwent a 11C-(R)-PK11195 scan were considered in the analysis. The time-activity curves of 11 regions of interest were extracted using the Hammersmith maximum probability atlas. BPs were first estimated using the standard simplified reference-tissue model (SRTM) with the reference tissue computed with a supervised selection algorithm. Subsequently, we applied an SRTMV that models PBBS vascular activity using an additional linear term for both target (VbT) and reference (VbR) regions accounting for vascular tracer activity (C(B)), whereas C(B) was extracted directly from the images. VbR was fixed to 5%, and R1, k2, BP, and VbT were estimated. PBBS density in the vasculature was also assessed by immunocytochemistry on a separate cohort of young and elderly controls and 3 AD postmortem brains. RESULTS: The inclusion of a vascular component in the SRTM increased BPs in all subjects, but the amount of the increase was different (about 11.9% in controls and 16.8% in patients with AD). In addition, average VbT values derived using the SRTMV were 4.22% for controls but only 2.87% in patients with AD. Immunochemistry showed reduced PBBS expression in AD due to vascular fibrosis. CONCLUSION: The reduction of VbT in AD can be interpreted as a consequence of 2 independent but concurring phenomena. The vascular fibrosis in the AD brain causes the well-documented decrease of the size of lumens and the reduction of blood volume. At the same time, the fibrotic process determines the loss of vascular PBBS, particularly in smooth muscles, as here documented by immunochemistry. The inclusion of the additional vascular component in the SRTM effectively models these 2 concurrent processes and amplifies the BP in AD more than in controls because of the decrease in tracer binding to the vasculature in the disease cohort.