The Clinical Utility of a Tiered Approach to Pediatric Glioma Molecular Characterization for Resource-Limited Settings.

PURPOSE: Molecular characterization is key to optimally diagnose and manage cancer. The complexity and cost of routine genomic analysis have unfortunately limited its use and denied many patients access to precision medicine. A possible solution is to rationalize use-creating a tiered approach to testing which uses inexpensive techniques for most patients and limits expensive testing to patients with the highest needs. Here, we tested the utility of this approach to molecularly characterize pediatric glioma in a cost- and time-sensitive manner. METHODS: We used a tiered testing pipeline of immunohistochemistry (IHC), customized fusion panels or fluorescence in situ hybridization (FISH), and targeted RNA sequencing in pediatric gliomas. Two distinct diagnostic algorithms were used for low- and high-grade gliomas (LGGs and HGGs). The percentage of driver alterations identified, associated testing costs, and turnaround time (TAT) are reported. RESULTS: The tiered approach successfully characterized 96% (95 of 99) of gliomas. For 82 LGGs, IHC, targeted fusion panel or FISH, and targeted RNA sequencing solved 35% (29 of 82), 29% (24 of 82), and 30% (25 of 82) of cases, respectively. A total of 64% (53 of 82) of samples were characterized without targeted RNA sequencing. Of 17 HGG samples, 13 were characterized by IHC and four were characterized by targeted RNA sequencing. The average cost per sample was more affordable when using the tiered approach as compared with up-front targeted RNA sequencing in LGG ($405 US dollars [USD] v $745 USD) and HGGs ($282 USD v $745 USD). The average TAT per sample was also shorter using the tiered approach (10 days for LGG, 5 days for HGG v 14 days for targeted RNA sequencing). CONCLUSION: Our tiered approach molecularly characterized 96% of samples in a cost- and time-sensitive manner. Such an approach may be feasible in neuro-oncology centers worldwide, particularly in resource-limited settings.

Comparison of diagnostic performance of radiologist- and AI-based assessments of T2-FLAIR mismatch sign and quantitative assessment using synthetic MRI in the differential diagnosis between astrocytoma, IDH-mutant and oligodendroglioma, IDH-mutant and 1p/19q-codeleted.

PURPOSE: This study aimed to compare assessments by radiologists, artificial intelligence (AI), and quantitative measurement using synthetic MRI (SyMRI) for differential diagnosis between astrocytoma, IDH-mutant and oligodendroglioma, and IDH-mutant and 1p/19q-codeleted and to identify the superior method. METHODS: Thirty-three cases (men, 14; women, 19) comprising 19 astrocytomas and 14 oligodendrogliomas were evaluated. Four radiologists independently evaluated the presence of the T2-FLAIR mismatch sign. A 3D convolutional neural network (CNN) model was trained using 50 patients outside the test group (28 astrocytomas and 22 oligodendrogliomas) and transferred to evaluate the T2-FLAIR mismatch lesions in the test group. If the CNN labeled more than 50% of the T2-prolonged lesion area, the result was considered positive. The T1/T2-relaxation times and proton density (PD) derived from SyMRI were measured in both gliomas. Each quantitative parameter (T1, T2, and PD) was compared between gliomas using the Mann-Whitney U-test. Receiver-operating characteristic analysis was used to evaluate the diagnostic performance. RESULTS: The mean sensitivity, specificity, and area under the curve (AUC) of radiologists vs. AI were 76.3% vs. 94.7%; 100% vs. 92.9%; and 0.880 vs. 0.938, respectively. The two types of diffuse gliomas could be differentiated using a cutoff value of 2290/128 ms for a combined 90th percentile of T1 and 10th percentile of T2 relaxation times with 94.4/100% sensitivity/specificity with an AUC of 0.981. CONCLUSION: Compared to the radiologists' assessment using the T2-FLAIR mismatch sign, the AI and the SyMRI assessments increased both sensitivity and objectivity, resulting in improved diagnostic performance in differentiating gliomas.

Assessment of Brain Tumour Perfusion Using Early-Phase 18F-FET PET: Comparison with Perfusion-Weighted MRI.

PURPOSE: Morphological imaging using MRI is essential for brain tumour diagnostics. Dynamic susceptibility contrast (DSC) perfusion-weighted MRI (PWI), as well as amino acid PET, may provide additional information in ambiguous cases. Since PWI is often unavailable in patients referred for amino acid PET, we explored whether maps of relative cerebral blood volume (rCBV) in brain tumours can be extracted from the early phase of PET using O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET). PROCEDURE: Using a hybrid brain PET/MRI scanner, PWI and dynamic 18F-FET PET were performed in 33 patients with cerebral glioma and four patients with highly vascularized meningioma. The time interval from 0 to 2 min p.i. was selected to best reflect the blood pool phase in 18F-FET PET. For each patient, maps of MR-rCBV, early 18F-FET PET (0-2 min p.i.) and late 18F-FET PET (20-40 min p.i.) were generated and coregistered. Volumes of interest were placed on the tumour (VOI-TU) and normal-appearing brain (VOI-REF). The correlation between tumour-to-brain ratios (TBR) of the different parameters was analysed. In addition, three independent observers evaluated MR-rCBV and early 18F-FET maps (18F-FET-rCBV) for concordance in signal intensity, tumour extent and intratumoural distribution. RESULTS: TBRs calculated from MR-rCBV and 18F-FET-rCBV showed a significant correlation (r = 0.89, p < 0.001), while there was no correlation between late 18F-FET PET and MR-rCBV (r = 0.24, p = 0.16) and 18F-FET-rCBV (r = 0.27, p = 0.11). Visual rating yielded widely agreeing findings or only minor differences between MR-rCBV maps and 18F-FET-rCBV maps in 93 % of the tumours (range of three independent raters 91-94%, kappa among raters 0.78-1.0). CONCLUSION: Early 18F-FET maps (0-2 min p.i.) in gliomas provide similar information to MR-rCBV maps and may be helpful when PWI is not possible or available. Further studies in gliomas are needed to evaluate whether 18F-FET-rCBV provides the same clinical information as MR-rCBV.

Understanding language and cognition after brain surgery - Tumour grade, fine-grained assessment tools and, most of all, individualized approach.

Cognitive performance influences the quality of life and survival of people with glioma. Thus, a detailed neuropsychological and language evaluation is essential. In this work, we tested if an analysis of errors in naming can indicate semantic and/or phonological impairments in 87 awake brain surgery patients. Secondly, we explored how language and cognition change after brain tumour resection. Finally, we checked if low-tumour grade had a protective effect on cognition. Our results indicated that naming errors can be useful to monitor semantic and phonological processing, as their number correlated with scores on tasks developed by our team for testing these domains. Secondly, we showed that - although an analysis at a whole group level indicates a decline in language functions - significantly more individual patients improve or remain stable when compared to the ones who declined. Finally, we observed that having LGG, when compared with HGG, favours patients' outcome after surgery, most probably due to brain plasticity mechanisms. We provide new evidence of the importance of applying a broader neuropsychological assessment and an analysis of naming errors in patients with glioma. Our approach may potentially ensure better detection of cognitive deficits and contribute to better postoperative outcomes. Our study also shows that an individualized approach in post-surgical follow-ups can reveal reassuring results showing that significantly more patients remain stable or improve and can be a promising avenue for similar reports. Finally, the study captures that plasticity mechanisms may act as protective in LGG versus HGG after surgery.

Retrospective longitudinal assessment of optic nerve sheath diameter in patients with malignant glioma.

INTRODUCTION: Glioblastoma (GBM) is a tumor with rapid growth and a possible relationship to elevated intracranial pressure (ICP). High ICP may not always be associated with clinical signs. A non-invasive technique for assessment of ICP is measuring the optic nerve sheath diameter (ONSD). Identifying patients who need immediate intervention is of importance in neuro-oncological care. The goal of this study is to assess the available magnetic resonance imaging (MRI) of patients with GBM with respect to pre- and postoperative ONSD. METHODS AND MATERIALS: Retrospective data analysis was performed on all patients operated for GBM at a tertiary care center between 2010 and 2020. Two pre and one postoperative MRI had to be available. Clinical data and ONSD at multiple time points were analyzed and correlated, as well as preoperative volumetrics. RESULTS: Sixty-seven patients met the inclusion criteria. Clinical signs of elevated ICP were seen in 25.4% (n = 17), while significant perifocal edema was present in 67.2% (n = 45) of patients. Clinical signs of preoperatively elevated ICP were associated with significantly elevated ONSD at diagnosis (p < 0.001) as well as preoperative tumor volume (p < 0.001). Significant perifocal edema at the time of diagnosis was associated with elevated ONSD (p = 0.029) and higher tumor volume (p = 0.003). In patients with significant edema, ONSD increased significantly between preoperative MRIs (p = 0.003/005). In patients with clinical signs of raised ICP, ONSD also increased, whereas it was stable in asymptomatic patients (yes: 5.01+/-4.17 to 5.83+/-0.55 mm, p = 0.010, no: 5.17+/-0.46 mm to 5.38+/-0.41 mm, p = 0.81). A significant increase of ONSD from diagnosis to preoperative MRI and a significant decrease until 3 months postoperatively were observed (p < 0.001). CONCLUSIONS: ONSD might help identify high ICP in patients with GBM. In this first-of-its kind study, we observed a significant increase of ONSD preoperatively, likely associated with edema. Postoperatively, ONSD decreased significantly until 3 months after surgery and increased again at 12 months. Further prospective data collection is warranted.

Review of imaging recommendations from Response Assessment in Pediatric Neuro-Oncology (RAPNO).

The Response Assessment in Pediatric Neuro-Oncology (RAPNO) working group includes neuroradiologists, neuro-oncologists, neurosurgeons, radiation oncologists, and clinicians in various additional specialties. This review paper will summarize the imaging recommendations from RAPNO for the six RAPNO publications to date covering pediatric low-grade glioma, pediatric high-grade glioma, medulloblastoma and other leptomeningeal seeding tumors, diffuse intrinsic pontine glioma, ependymoma, and craniopharyngioma.

RANO 2.0: Update to the Response Assessment in Neuro-Oncology Criteria for High- and Low-Grade Gliomas in Adults.

PURPOSE: The Response Assessment in Neuro-Oncology (RANO) criteria for high-grade gliomas (RANO-HGG) and low-grade gliomas (RANO-LGG) were developed to improve reliability of response assessment in glioma trials. Over time, some limitations of these criteria were identified, and challenges emerged regarding integrating features of the modified RANO (mRANO) or the immunotherapy RANO (iRANO) criteria. METHODS: Informed by data from studies evaluating the different criteria, updates to the RANO criteria are proposed (RANO 2.0). RESULTS: We recommend a standard set of criteria for both high- and low-grade gliomas, to be used for all trials regardless of the treatment modalities being evaluated. In the newly diagnosed setting, the postradiotherapy magnetic resonance imaging (MRI), rather than the postsurgical MRI, will be used as the baseline for comparison with subsequent scans. Since the incidence of pseudoprogression is high in the 12 weeks after radiotherapy, continuation of treatment and confirmation of progression during this period with a repeat MRI, or histopathologic evidence of unequivocal recurrent tumor, are required to define tumor progression. However, confirmation scans are not mandatory after this period nor for the evaluation of treatment for recurrent tumors. For treatments with a high likelihood of pseudoprogression, mandatory confirmation of progression with a repeat MRI is highly recommended. The primary measurement remains the maximum cross-sectional area of tumor (two-dimensional) but volumetric measurements are an option. For IDH wild-type glioblastoma, the nonenhancing disease will no longer be evaluated except when assessing response to antiangiogenic agents. In IDH-mutated tumors with a significant nonenhancing component, clinical trials may require evaluating both the enhancing and nonenhancing tumor components for response assessment. CONCLUSION: The revised RANO 2.0 criteria refine response assessment in gliomas.

Automated Brain Tumor Detection and Segmentation for Treatment Response Assessment Using Amino Acid PET.

Evaluation of metabolic tumor volume (MTV) changes using amino acid PET has become an important tool for response assessment in brain tumor patients. MTV is usually determined by manual or semiautomatic delineation, which is laborious and may be prone to intra- and interobserver variability. The goal of our study was to develop a method for automated MTV segmentation and to evaluate its performance for response assessment in patients with gliomas. Methods: In total, 699 amino acid PET scans using the tracer O-(2-[18F]fluoroethyl)-l-tyrosine (18F-FET) from 555 brain tumor patients at initial diagnosis or during follow-up were retrospectively evaluated (mainly glioma patients, 76%). 18F-FET PET MTVs were segmented semiautomatically by experienced readers. An artificial neural network (no new U-Net) was configured on 476 scans from 399 patients, and the network performance was evaluated on a test dataset including 223 scans from 156 patients. Surface and volumetric Dice similarity coefficients (DSCs) were used to evaluate segmentation quality. Finally, the network was applied to a recently published 18F-FET PET study on response assessment in glioblastoma patients treated with adjuvant temozolomide chemotherapy for a fully automated response assessment in comparison to an experienced physician. Results: In the test dataset, 92% of lesions with increased uptake (n = 189) and 85% of lesions with iso- or hypometabolic uptake (n = 33) were correctly identified (F1 score, 92%). Single lesions with a contiguous uptake had the highest DSC, followed by lesions with heterogeneous, noncontiguous uptake and multifocal lesions (surface DSC: 0.96, 0.93, and 0.81 respectively; volume DSC: 0.83, 0.77, and 0.67, respectively). Change in MTV, as detected by the automated segmentation, was a significant determinant of disease-free and overall survival, in agreement with the physician's assessment. Conclusion: Our deep learning-based 18F-FET PET segmentation allows reliable, robust, and fully automated evaluation of MTV in brain tumor patients and demonstrates clinical value for automated response assessment.

Low-coverage and cost-effective whole-genome sequencing assay for glioma risk stratification.

PURPOSE: To investigate chromosomal instability (CIN) as a biomarker for glioma risk stratifications, with cost-effective, low-coverage whole-genome sequencing assay (WGS). METHODS: Thirty-five formalin-fixed paraffin-embedded glioma samples were collected from Huashan Hospital. DNA was sent for WGS by Illumina X10 at low (median) genome coverage of 1.86x (range: 1.03-3.17×), followed by copy number analyses, using a customized bioinformatics workflow-Ultrasensitive Copy number Aberration Detector. RESULTS: Among the 35 glioma patients, 12 were grade IV, 10 grade III, 11 grade II, and 2 Grade I cases, with high chromosomal instability (CIN +) in 24 (68.6%) of the glioma patients. The other 11 (31.4%) had lower chromosomal instability (CIN-). CIN significantly correlates with overall survival (P = 0.00029). Patients with CIN + /7p11.2 + (12 grade IV and 3 grade III) had the worst survival ratio (hazard ratio:16.2, 95% CI:6.3-41.6) with a median overall survival of 24 months. Ten (66.7%) patients died during the first two follow-up years. In the CIN + patients without 7p11.2 + (6 grade III, 3 grade II), 3 (33.3%) patients died during follow-up, and the estimated overall survival was around 65 months. No deaths were reported in the 11 CIN- patients (2 grade I, 8 grade II, 1 grade III) during the 80-month follow-up period. In this study, chromosomal instability served as a prognosis factor for gliomas independent of tumor grades. CONCLUSION: It is feasible to use cost-effective, low-coverage WGS for risk stratification of glioma. Elevated chromosomal instability is associated with poor prognosis.

Subpial technique in supratentorial glioma resection: state of the art and analysis of costs and effectiveness in a single institute experience.

BACKGROUND: Many neurosurgeons advocate subpial technique as the best technique to remove supratentorial gliomas. However, few authors clearly defined advantages and features of this technique. The aim of our study is to describe microsurgical subpial technique related to glioma surgery, with regard to its safety and cost effectiveness. METHODS: We analyzed retrospectively all consecutive patients surgically treated for supratentorial glioma from January 2017 to April 2018 at Neurosurgery Department of Neuromed Institute. All patients underwent to surgical glioma resection performing microsurgical subpial technique. Extent of resection and neurological complications were evaluated as primary outcomes; Karnofsky Performance Status and postoperative edema extent were secondary outcomes. Statistical analysis was obtained. RESULTS: The study included 70 patients. Gross Total Removal was obtained in 91.3% of patients with low grade glioma (LGG) and in 81% of patients with high grade glioma. Neurological complications amounted to 34% at early assessment in LGG patients, which were permanent at 3 months in 17% of patients. In high grade glioma patients, neurological complications amounted to 51% at early assessment, which were permanent at 3 months in 25% of them. CONCLUSIONS: We obtained good postoperative results with regard to the extent of tumor resection using this technique. Subpial resection is an effective surgical technique to get a safer and more complete tumor resection. It should be combined with other modern neurosurgical tools such as neuronavigation, ultrasound and cortical mapping to obtain the best tumor resection and functional neurological preservation.

DeepEOR: automated perioperative volumetric assessment of variable grade gliomas using deep learning.

PURPOSE: Volumetric assessments, such as extent of resection (EOR) or residual tumor volume, are essential criterions in glioma resection surgery. Our goal is to develop and validate segmentation machine learning models for pre- and postoperative magnetic resonance imaging scans, allowing us to assess the percentagewise tumor reduction after intracranial surgery for gliomas. METHODS: For the development of the preoperative segmentation model (U-Net), MRI scans of 1053 patients from the Multimodal Brain Tumor Segmentation Challenge (BraTS) 2021 as well as from patients who underwent surgery at the University Hospital in Zurich were used. Subsequently, the model was evaluated on a holdout set containing 285 images from the same sources. The postoperative model was developed using 72 scans and validated on 45 scans obtained from the BraTS 2015 and Zurich dataset. Performance is evaluated using Dice Similarity score, Jaccard coefficient and Hausdorff 95%. RESULTS: We were able to achieve an overall mean Dice Similarity Score of 0.59 and 0.29 on the pre- and postoperative holdout sets, respectively. Our algorithm managed to determine correct EOR in 44.1%. CONCLUSION: Although our models are not suitable for clinical use at this point, the possible applications are vast, going from automated lesion detection to disease progression evaluation. Precise determination of EOR is a challenging task, but we managed to show that deep learning can provide fast and objective estimates.

A new study protocol for in-vivo assessment of tumor diagnosis and microscopic tumor infiltration at the resection cavity in central nervous system tumors by a new miniature confocal endomicroscope (CONVIVO system).

BACKGROUND: Confocal laser technology has been recently suggested as a promising method to obtain near real-time intraoperative histological data. We recently demonstrated the accuracy of a newly designed confocal endomiscroscope (CONVIVO) in offering an intraoperative diagnosis during high-grade gliomas (HGGs) removal in an ex vivo study. With this work we aim to perform a standardized, prospective and blinded-to-histological section study for evaluating the potentiality of CONVIVO in offering in-vivo data regarding histological diagnosis and presence of tumor at margins during resection of central nervous system (CNS) tumors. METHODS: This prospective, observational, standardized, blinded-to-histological section, clinical trial was approved by the institutional review board in Carlo Besta Neurologic Institute IRCCS Foundation in Milan and is expected to last 24 months. 75 patients will be included, with at least 53 of them being HGGs based on the statistical sample size calculation. Main objectives will be the assessing of the concordance of tumor diagnoses between CONVIVO images and frozen section at the center of all tumor subtypes and the evaluation of the accuracy of CONVIVO in the identification of tumor tissue at the margins, compared to standard histology. For this purpose, "virtual biopsies" and physical biopsies will be performed directly on patient tumor tissue and surrounding brain parenchima during tumor resection, comparing the results of CONVIVO analysis and frozen and histological sections. RESULTS: Despite promising preliminary data on ex vivo usefulness of CLE machines are emerging in literature, still few studies are available when looking at in vivo potentiality of CONVIVO. At this regard, this study will be the first work where a standardized, prospective, and blinded-to-histological section CONVIVO analysis will be performed in an in-vivo setting in neuro-oncological surgery. CONCLUSIONS: We hypothesize that this new technique may have a role in offering data regarding presence of tumor tissue, eventually giving an intraoperative diagnosis in neuro-oncological surgery, rendering more fluid the decision-making process in the operating room. Furthermore, the result of this study will provide a solid base for further expanding the clinical applications of confocal machines in neurosurgery.

Artificial intelligence (AI)-based decision support improves reproducibility of tumor response assessment in neuro-oncology: An international multi-reader study.

BACKGROUND: To assess whether artificial intelligence (AI)-based decision support allows more reproducible and standardized assessment of treatment response on MRI in neuro-oncology as compared to manual 2-dimensional measurements of tumor burden using the Response Assessment in Neuro-Oncology (RANO) criteria. METHODS: A series of 30 patients (15 lower-grade gliomas, 15 glioblastoma) with availability of consecutive MRI scans was selected. The time to progression (TTP) on MRI was separately evaluated for each patient by 15 investigators over two rounds. In the first round the TTP was evaluated based on the RANO criteria, whereas in the second round the TTP was evaluated by incorporating additional information from AI-enhanced MRI sequences depicting the longitudinal changes in tumor volumes. The agreement of the TTP measurements between investigators was evaluated using concordance correlation coefficients (CCC) with confidence intervals (CI) and P-values obtained using bootstrap resampling. RESULTS: The CCC of TTP-measurements between investigators was 0.77 (95% CI = 0.69,0.88) with RANO alone and increased to 0.91 (95% CI = 0.82,0.95) with AI-based decision support (P = .005). This effect was significantly greater (P = .008) for patients with lower-grade gliomas (CCC = 0.70 [95% CI = 0.56,0.85] without vs. 0.90 [95% CI = 0.76,0.95] with AI-based decision support) as compared to glioblastoma (CCC = 0.83 [95% CI = 0.75,0.92] without vs. 0.86 [95% CI = 0.78,0.93] with AI-based decision support). Investigators with less years of experience judged the AI-based decision as more helpful (P = .02). CONCLUSIONS: AI-based decision support has the potential to yield more reproducible and standardized assessment of treatment response in neuro-oncology as compared to manual 2-dimensional measurements of tumor burden, particularly in patients with lower-grade gliomas. A fully-functional version of this AI-based processing pipeline is provided as open-source (https://github.com/NeuroAI-HD/HD-GLIO-XNAT).

Assessment of radiographic and prognostic characteristics of programmed death-ligand 1 expression in high-grade gliomas.

PURPOSE: Gliomas are characterized by immunosuppressive features. Programmed death-ligand 1 (PD-L1) is overexpressed and plays an important role in the immunosuppressive tumor microenvironments of gliomas. However, the radiographical and prognostic significance of PD-L1 expression remains unclear. METHODS: Using tissue microarrays, we evaluated PD-L1 expression and the presence of tumor-infiltrating CD4+ and CD8+T cells and CD204+macrophages using immunohistochemical analysis. Contrast enhancement area and fluid-attenuated inversion recovery (FLAIR) hyperintensity area were evaluated by two-dimensional analysis. Kaplan-Meier analysis was performed to evaluate the overall survival time in 44 patients with isocitrate dehydrogenase (IDH)-wildtype glioblastoma. RESULTS: We evaluated 71 patients with newly diagnosed high-grade gliomas who were treated between October 1998 and April 2012. PD-L1 expression was observed in 15 patients (21.1%). A significant association of PD-L1 expression with the CD4+ and CD8+ T cell densities, but not with CD204+ macrophage densities, was observed (p = 0.025, p = 0.0098, and p = 0.19, respectively). The FLAIR-to-enhancement ratio was significantly higher in PD-L1+ tumors than in PD-L1- tumors (p = 0.0037). PD-L1 expression did not show a significant association with the median survival time (PD-L1 + vs. PD-L1-: 19.2 vs 14.9 months; p = 0.39). CONCLUSION: PD-L1 expression was associated with CD4+ and CD8+ T cell infiltration, indicating a significant interplay between PD-L1 and immune cells. The positive correlation of PD-L1 expression with an increased FLAIR-to-enhancement ratio suggested that radiographical characteristics could reflect the immunological status. Our results did not support the prognostic impact of PD-L1 in patients with IDH-wildtype glioblastomas.

Launching Awake Craniotomy Technique in a Resource-Limited Center: New Insights into the Patient Experience, Costs, and Long-Term Outcomes and a Narrative Review of the Literature.

BACKGROUND: Awake craniotomy (AC) with brain mapping is a standard surgical technique for the excision of lesions located in eloquent areas. We aimed to assess the clinical challenges, patient experience, costs, and long-term outcomes of AC in a resource-limited setting. METHODS: In this cross-sectional study, electronic documents of 12 patients who underwent AC with functional brain mapping were prospectively collected from August 2017 to October 2020. Patient characteristics, surgical specifications, hospitalization period, intraoperative and postoperative events, functional outcome, patients' satisfaction, costs, and survivals were collected and analyzed. RESULTS: Twelve patients with a median age of 42.5 (interquartile range, 13.5) were enrolled, of whom 8 were male (66.7%), and 9 (75%) were harboring grade 2 glioma. Of the patients, 8.34%, 33.34%, and 58.33% had partial, subtotal, and gross total excision of the tumors, respectively. The intraoperative seizure was the only complication and occurred in 2 cases (16.67%). At 1 year follow-up, none of the patients experienced any neurologic deficit. Eleven patients (91.6%) had a satisfactory opinion about reappearing in the AC. At 38 months follow-up, mortality was 8% for AC group and 25% among the historically matched controls who had surgery under general anesthesia (P = 0.27). Most costs belonged to the neurosurgery team (43%), and the overall expenses were reduced by 13% compared with a putatively well-equipped setting in our country. CONCLUSIONS: In carefully selected individuals, AC with brain mapping for excision of gliomas could be a safe, effective, and affordable strategy in a resource-limited setting and can be successfully performed with satisfactory outcomes.

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.

Assessment of brain tumors by magnetic resonance dynamic susceptibility contrast perfusion-weighted imaging and computed tomography perfusion: a comparison study.

PURPOSE: To investigate the association and agreement between magnetic resonance dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) and computed tomography perfusion (CTP) in determining vascularity and permeability of primary and secondary brain tumors. MATERIAL AND METHODS: DSC-PWI and CTP studies from 97 patients with high-grade glioma, low-grade glioma and solitary brain metastasis were retrospectively reviewed. Normalized cerebral blood flow (nCBF), cerebral blood volume (nCBV), capillary transfer constant (nK2) and permeability surface area product (nPS) values were obtained. Variables among groups were compared, and correlation and agreement between DSC-PWI and CTP were tested. RESULTS: All DSC-PWI and CTP parameters were higher in high-grade than in low-grade gliomas (p < 0.01 and p < 0.001). Metastases had greater DSC-PWI nCBV (p < 0.05), nCTP-CBF (p < 0.05), nCTP-CBV (p < 0.01) and nCTP-PS (p < 0.0001) than low-grade gliomas and more elevated nCTP-PS (p < 0.01) than high-grade gliomas. The correlation was strong between DSC-PWI nCBF and CTP nCBF (r = 0.79; p < 0.00001) and between DSC-PWI nCBV and CTP nCBV (r = 0.83; p < 0.00001), weaker between DSC-PWI nK2 and CTP nPS (r = 0.29; p < 0.01). Bland-Altman plots indicated that the agreement was strong between DSC-PWI nCBF and CTP nCBF, good between DSC-PWI nCBV and CTP nCBV and poorer between DSC-PWI nK2 and CTP nPS. CONCLUSION: DSC-PWI and CTP CBF and CBV maps were comparable and interchangeable in the assessment of tumor vascularity, unlike DSC-PWI K2 and CTP PS maps that were more discordant in the analysis of tumor permeability. CTP could be an alternative method to quantify tumor neoangiogenesis when MRI is not available or when the patient does not tolerate it.

Radiographic Response Assessment Strategies for Early-Phase Brain Trials in Complex Tumor Types and Drug Combinations: from Digital "Flipbooks" to Control Systems Theory.

There is an urgent need for drug development in brain tumors. While current radiographic response assessment provides instructions for identifying large treatment effects in simple high- and low-grade gliomas, there remains a void of strategies to evaluate complex or difficult to measure tumors or tumors of mixed grade with enhancing and non-enhancing components. Furthermore, most patients exhibit some period of alteration in tumor growth after starting a new therapy, but simple response categorization (e.g., stable disease, progressive disease) fails to provide any meaningful insight into the depth or degree of potential "subclinical" therapeutic response. We propose a creative solution to these issues based on a tiered strategy meant to increase confidence in identifying therapeutic effects even in the most challenging tumor types, while also providing a framework for complex evaluation of combination and sequential treatment schemes. Specifically, we demonstrate the utility of digital "flipbooks" to quickly identify subtle changes in complex tumors. We show how a modified Levin criteria can be used to quantify the degree of visual changes, while establishing estimates of the association between tumor volume and visual inspection. Lastly, we introduce the concept of quantifying therapeutic response using control systems theory. We propose measuring changes in volume (proportional), the area under the volume vs. time curve (integral) and changes in growth rates (derivative) to utilize a "PID" controller model of single or combination therapeutic activity.

First-in-human assessment of the novel LAT1 targeting PET probe 18F-FIMP.

In the first-in-human PET study, we evaluated the biodistribution and tumor accumulation of the novel PET probe, (S)-2-amino-3-[3-(2-18F-fluoroethoxy)-4-iodophenyl]-2-methylpropanoic acid (18F-FIMP), which targets the tumor-related L-type amino acid transporter 1 (LAT1), and compared it with L-[methyl-11C]methionine (11C-MET) and 2-Deoxy-2-18F-fluoro-D-glucose (18F-FDG). 18F-FIMP biodistribution was revealed by whole-body and brain scans in 13 healthy controls. Tumor accumulation of 18F-FIMP was evaluated in 7 patients with a brain tumor, and compared with those of 11C-MET and 18F-FDG. None of the subjects had significant problems due to probe administration, such as adverse effects or abnormal vital signs. 18F-FIMP was rapidly excreted from the kidneys to the urinary bladder. There was no characteristic physiological accumulation in healthy controls. 18F-FIMP PET resulted in extremely clear images in patients with suspected glioblastoma compared with 11C-MET and 18F-FDG. 18F-FIMP could be a useful novel PET probe for LAT1-positive tumor imaging including glioblastoma.