PRRT with Lu-177 DOTATATE in Treatment-Refractory Progressive Meningioma: Initial Experience from a Tertiary-Care Neuro-Oncology Center.

PURPOSE: Refractory and/or recurrent meningiomas have poor outcomes, and the treatment options are limited. Peptide receptor radionuclide therapy (PRRT) has been used in this setting with promising results. We have documented our experience of using intravenous (IV) and intra-arterial (IA) approaches of Lu-177 DOTATATE PRRT. METHODS: Eight patients with relapsed/refractory high-grade meningioma received PRRT with Lu-177 DOTATATE by IV and an IA route. At least 2 cycles were administered. Time to progression was calculated from the first PRRT session to progression. The response was assessed on MRI using RANO criteria, and visual analysis of uptake was done on Ga-68 DOTANOC PET/CT. Post-therapy dosimetry calculations for estimating the absorbed dose were performed. RESULTS: Median time to progression was 8.9 months. One patient showed disease progression, whereas seven patients showed stable disease at 4 weeks following 2 cycles of PRRT. Dosimetric analysis showed higher dose and retention time by IA approach. No significant peri-procedural or PRRT associated toxicity was seen. CONCLUSION: PRRT is a safe and effective therapeutic option for relapsed/refractory meningioma. The IA approach yields better dose delivery and should be routinely practised.

Tumor location and neurocognitive function-Unravelling the association and identifying relevant anatomical substrates in intra-axial brain tumors.

Background: Neurocognitive function is a key outcome indicator of therapy in brain tumors. Understanding the underlying anatomical substrates involved in domain function and the pathophysiological basis of dysfunction can help ameliorate the effects of therapy and tailor directed rehabilitative strategies. Methods: Hundred adult diffuse gliomas were co-registered onto a common demographic-specific brain template to create tumor localization maps. Voxel-based lesion symptom (VLSM) technique was used to assign an association between individual voxels and neuropsychological dysfunction in various domains (attention and executive function (A & EF), language, memory, visuospatial/constructive abilities, and visuomotor speed). The probability maps thus generated were further co-registered to cortical and subcortical atlases. A permutation-based statistical testing method was used to evaluate the statistically and clinically significant anatomical parcels associated with domain dysfunction and to create heat maps. Results: Neurocognition was affected in a high proportion of subjects (93%), with A & EF and memory being the most affected domains. Left-sided networks were implicated in patients with A & EF, memory, and language deficits with the perisylvian white matter tracts being the most common across domains. Visuospatial dysfunction was associated with lesions involving the right perisylvian cortical regions, whereas deficits in visuomotor speed were associated with lesions involving primary visual and motor output pathways. Conclusions: Significant baseline neurocognitive deficits are prevalent in gliomas. These are multidomain and the perisylvian network especially on the left side seems to be very important, being implicated in dysfunction of many domains.

CDKN2A/B deletion in IDH-mutant astrocytomas: An evaluation by Fluorescence in-situ hybridization.

INTRODUCTION: CDKN2A/B homozygous deletion is one of the defining features of grade 4 in IDH-mutant astrocytic tumours. AIM: To evaluate CDKN2A/B-deletion in IDH-mutant astrocytic tumours and its clinicopathological impact. MATERIALS AND METHODS: CDKN2A/B-deletion was evaluated by Fluorescence in-situ hybridisation (FISH) and interpreted by two recently accepted methods. RESULTS: Eighty-three out of 94 cases (histologically-grade 2: 3, grade 3: 46, grade 4: 34) were interpretable on FISH. Concordant CDKN2A/B-deletion was observed in 71% (27/38) of lower-grade tumours (n = 49) and 90% (27/30) of histological grade 4 tumours (n = 34). Both the interpretation methods showed good agreement (Kappa = 0.75). CDKN2A/B-deletion showed an inverse correlation for < 10% MIB-1 labeling index (p = 0.01) while that by method-2 showed a significant correlation for grade 4 (p = 0.02). No significant correlation was observed for any other clinicopathological parameters. Twenty-four patients showed progression/recurrence (including deaths), and no significant difference in frequency of CDKN2A/B deletion was observed among cases with disease progression across different histological grades. CONCLUSIONS: CDKN2A/B-deletion was observed across all the histological grades of IDH-mutant astrocytic tumours, expectedly more in the higher grade. FISH, as a method, can be used for the detection of CDKN2A/B homozygous deletion, when there is concordant interpretation.

Patterns of Care in Craniopharyngioma: Clinical Outcomes After Surgery and Radiation Therapy in a Real-World Setting.

OBJECTIVE: Craniopharyngioma (CP) is a benign neuroepithelial tumor generally treated with maximal safe resection and radiation therapy (RT) in incompletely resected CP or in recurrent tumors to achieve long-term control. We analyzed the clinical outcomes of patients with CPs treated with a multimodality approach. PATIENTS AND METHODS: A retrospective clinical audit of histologically proven CPs registered between 2008 and 2019 at a specialized neuro-oncology center in India was performed. Time-to-event outcomes (overall survival [OS] and progression-free survival [PFS]) were analyzed. RESULTS: One hundred and twenty-two patients with CP were analyzed. The median age of the population was 14 years (interquartile range [IQR], 8-26) with a significant male preponderance. Gross total resection was achieved in only 25% of patients. At a median follow-up of 57.1 months (IQR, 27.8-87.8), 5-year estimates of PFS and OS were 52% (95% confidence interval, 46%-63.4%) and 85.8% (95% confidence interval, 78.6%-93%), respectively. Recurrence or progression was observed in 48 of 122 patients (39.3%) at a median time of 84.4 months (IQR, 24.7-174.8). On multivariate analysis, the absence of residual disease (P = 0.004), near-total resection (P = 0.035), and use of up-front adjuvant RT (P < 0.001) significantly improved the 5-year PFS, whereas the absence of extracavernous extension (P = 0.058) and any use of postoperative RT (P = 0.026) significantly improved the 5-year OS. CONCLUSIONS: This study represents one of the largest single-institutional series of CPs, showing improved PFS with up-front adjuvant RT in most cases of CP. Deferring adjuvant RT should be considered only in patients with no evidence of residual disease (as shown on dedicated sellar imaging) after primary surgery.

Integrated Meta-Omics Analysis Unveils the Pathways Modulating Tumorigenesis and Proliferation in High-Grade Meningioma.

Meningioma, a primary brain tumor, is commonly encountered and accounts for 39% of overall CNS tumors. Despite significant progress in clinical research, conventional surgical and clinical interventions remain the primary treatment options for meningioma. Several proteomics and transcriptomics studies have identified potential markers and altered biological pathways; however, comprehensive exploration and data integration can help to achieve an in-depth understanding of the altered pathobiology. This study applied integrated meta-analysis strategies to proteomic and transcriptomic datasets comprising 48 tissue samples, identifying around 1832 common genes/proteins to explore the underlying mechanism in high-grade meningioma tumorigenesis. The in silico pathway analysis indicated the roles of extracellular matrix organization (EMO) and integrin binding cascades in regulating the apoptosis, angiogenesis, and proliferation responsible for the pathobiology. Subsequently, the expression of pathway components was validated in an independent cohort of 32 fresh frozen tissue samples using multiple reaction monitoring (MRM), confirming their expression in high-grade meningioma. Furthermore, proteome-level changes in EMO and integrin cell surface interactions were investigated in a high-grade meningioma (IOMM-Lee) cell line by inhibiting integrin-linked kinase (ILK). Inhibition of ILK by administrating Cpd22 demonstrated an anti-proliferative effect, inducing apoptosis and downregulating proteins associated with proliferation and metastasis, which provides mechanistic insight into the disease pathophysiology.

Intraoperative Navigated Three-Dimensional Ultrasound Guidance Improves Resection in Gliomas Compared with Standard Two-Dimensional Ultrasound-Results from a Comparative Cohort Study.

OBJECTIVE: Intraoperative ultrasound is a promising tool for intraoperative tumor resection control. Navigated three-dimensional US (n3DUS) has many benefits over standard two-dimensional US (2DUS). METHODS: Two cohorts (2DUS and n3DUS) of patients with histologically confirmed adult diffuse gliomas undergoing US-guided resection control were compared. The primary outcomes assessed were extent of resection and morbidity. Multivariate analysis was performed to account for tumor characteristics (delineation and eloquence) and surgeon experience, which could confound the results. RESULTS: n3DUS was used more often (n = 252) than 2DUS (n = 86). Tumor delineation was similar in 2DUS and n3DUS cohorts, although the n3DUS cohort included more nonenhancing, histologically lower grade (2-3) gliomas and had more gliomas located in eloquent regions; also, n3DUS was more often used by senior surgeons. Gross total resection (GTR) rates were 47%, and major morbidity was 9.5%. On multivariate analysis, after controlling for all other variables between the 2 groups, patients with well-delineated tumors, patients with prior treatment, and patients who underwent n3DUS were more likely to have GTR (adjusted odds ratios 3.0, 1.8, and 2.2, respectively), whereas patients with tumors in eloquent locations were half as likely (adjusted odds ratio 0.5) to have GTR. Eloquent located tumors were likely to be associated with higher neurological morbidity, although major morbidity was not significantly different. CONCLUSIONS: Good delineation, noneloquent location, and use of n3DUS was associated with a higher probability of GTR in glioma surgery. Surgeons' experience did not influence the extent of resection. Morbidity was predominantly associated with eloquent location, independent of all other factors.

A large-scale targeted proteomics of serum and tissue shows the utility of classifying high grade and low grade meningioma tumors.

BACKGROUND: Meningiomas are the most prevalent primary brain tumors. Due to their increasing burden on healthcare, meningiomas have become a pivot of translational research globally. Despite many studies in the field of discovery proteomics, the identification of grade-specific markers for meningioma is still a paradox and requires thorough investigation. The potential of the reported markers in different studies needs further verification in large and independent sample cohorts to identify the best set of markers with a better clinical perspective. METHODS: A total of 53 fresh frozen tumor tissue and 51 serum samples were acquired from meningioma patients respectively along with healthy controls, to validate the prospect of reported differentially expressed proteins and claimed markers of Meningioma mined from numerous manuscripts and knowledgebases. A small subset of Glioma/Glioblastoma samples were also included to investigate inter-tumor segregation. Furthermore, a simple Machine Learning (ML) based analysis was performed to evaluate the classification accuracy of the list of proteins. RESULTS: A list of 15 proteins from tissue and 12 proteins from serum were found to be the best segregator using a feature selection-based machine learning strategy with an accuracy of around 80% in predicting low grade (WHO grade I) and high grade (WHO grade II and WHO grade III) meningiomas. In addition, the discriminant analysis could also unveil the complexity of meningioma grading from a segregation pattern, which leads to the understanding of transition phases between the grades. CONCLUSIONS: The identified list of validated markers could play an instrumental role in the classification of meningioma as well as provide novel clinical perspectives in regard to prognosis and therapeutic targets.

Deep learning based clinico-radiological model for paediatric brain tumor detection and subtype prediction.

Aim: Early diagnosis of paediatric brain tumors significantly improves the outcome. The aim is to study magnetic resonance imaging (MRI) features of paediatric brain tumors and to develop an automated segmentation (AS) tool which could segment and classify tumors using deep learning methods and compare with radiologist assessment. Methods: This study included 94 cases, of which 75 were diagnosed cases of ependymoma, medulloblastoma, brainstem glioma, and pilocytic astrocytoma and 19 were normal MRI brain cases. The data was randomized into training data, 64 cases; test data, 21 cases and validation data, 9 cases to devise a deep learning algorithm to segment the paediatric brain tumor. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of the deep learning model were compared with radiologist's findings. Performance evaluation of AS was done based on Dice score and Hausdorff95 distance. Results: Analysis of MRI semantic features was done with necrosis and haemorrhage as predicting features for ependymoma, diffusion restriction and cystic changes were predictors for medulloblastoma. The accuracy of detecting abnormalities was 90%, with a specificity of 100%. Further segmentation of the tumor into enhancing and non-enhancing components was done. The segmentation results for whole tumor (WT), enhancing tumor (ET), and non-enhancing tumor (NET) have been analyzed by Dice score and Hausdorff95 distance. The accuracy of prediction of all MRI features was compared with experienced radiologist's findings. Substantial agreement observed between the classification by model and the radiologist's given classification [K-0.695 (K is Cohen's kappa score for interrater reliability)]. Conclusions: The deep learning model had very high accuracy and specificity for predicting the magnetic resonance (MR) characteristics and close to 80% accuracy in predicting tumor type. This model can serve as a potential tool to make a timely and accurate diagnosis for radiologists not trained in neuroradiology.

Primary central nervous system lymphoma: Comprehension of cell-of-origin subtypes.

Primary central nervous system diffuse large B-cell lymphoma (PCNS-DLBCL) is an uncommon extranodal lymphoma that accounts for more than 95% of all the CNS lymphomas. Unlike its systemic/nodal counterpart, which is currently subtyped into cell-of origin (COO) subtypes, its feasibility and utility are largely debatable in PCNS-DLBCL. Objectives: To classify PCNS-DLBCL into COO-subtypes based on immunohistochemical algorithms by Hans and Choi and evaluate concordance between the two. A further aim is to investigate the clinicoradiological and histomorphological parameters of the subtypes thus obtained. Materials and Methods: As many as 143 cases of primary CNS lymphoma were evaluated by immunohistochemistry for CD10, BCL6, MUM1, GCET, and FOXP1 and based on which the said 143 cases were further classified into COO subtypes using Hans and Choi algorithms. Results: Mean age was 53.8 years with marginal male preponderance and predominantly centroblastic morphology (75.5%). CD 10 was positive in 8.9% of the cases, BCL6 in 58.6%, MUM1 in 89.9%, GCET in 32.9%, and FOXP1 in 79.5%. As much as 84.9% cases were of non-germinal center B-cell (GCB) subtype and 15.1% cases were of GCB subtype as determined based on Hans algorithm. Furthermore, 90.7% cases were of activated B-cell (ABC) subtype and 9.3% cases were of GCB subtype according to Choi algorithm. A 91.8% concordance was observed between Hans and Choi algorithms. Among the 6 discordant cases, 5 cases were subtyped as GCB by Hans and ABC by Choi and 1 case as ABC by Hans and GCB by Choi. Conclusion: Most of PCNS-DLBCLs are of non-GCB/ABC COO subtype, but inconsistences abound in the utility of IHC algorithms in PCNS-DLBCL COO subtypes.

Implications of use of different intraoperative ultrasound modalities during glioma surgery - A comparative study of factors affecting outcomes.

BACKGROUND: The main goal of glioma surgery is to remove the maximum amount of tumor without worsening the patient's neurological condition. Intraoperative ultrasound (US) imaging technologies (2D and 3D) are available to assist surgeons, providing real-time updates. Considering additional time, personnel, and cost, we investigate if comparable outcomes can be achieved using basic (2D) and advanced (3D) technology. OBJECTIVE: We propose predictive models for (i) glioma tumor resectability (ii) surgical outcome, and (iii) a model to predict the outcome of surgery aided with a particular ultrasound and compare outcomes between 2D and 3D US. METHODOLOGY: We used real-world surgery data from a tertiary cancer centre. Three groups of cases were analyzed (2D US used, 3D US used, and no US used during resection). The data analysis uses hypothesis testing, bootstrap sampling, and logistic regression. RESULTS: The preoperatively anticipated extent of tumor removal correlated with the postoperative MRI measurement of tumor removal for US-supported surgery (p=0.01) but not for no US-supported surgeries (p = 0.13). A combination of delineation, eloquence, and the multifocal/multicentric nature of the tumor effectively predicted resectability. The eventual outcome of surgery (actual extent of resection achieved) can be predicted by prior treatment status, delineation, eloquence, and satellite nodules. Based on our prediction model (training set of 350 cases and test of 40 cases of US-guided surgeries), we identify some cases where 3D US seems to offer superior EORs. CONCLUSION: The resectability of glioma tumors is crucial in determining surgical objectives, and the type of ultrasound used as support impacts tumor removal. The findings in this study aid informed decision-making and optimize imaging technology usage, providing a decision flow for selecting ultrasound based on tumor characteristics.

Primary Intracranial Germ Cell Tumors: A Study with an Integrated Clinicopathological Approach.

Background and Objective: Primary intracranial germ cell tumors (ICGCTs) are rare and are histologically classified as germinomas and non-germinomatous with distinctive prognostic and therapeutic implications. ICGCTs, essentially due to the inherent difficulty of surgical access, pose different challenges and management connotations than their extracranial counterparts. This is a retrospective analysis of histologically verified ICGCTs, which was undertaken to evaluate various clinicopathological features and their implications on patient management. Materials and Methods: Eighty-eight histologically diagnosed cases (over 14 years) of ICGCT at our institute formed the study cohort and were classified into germinoma and non-germinomatous germ cell tumors (NGGCTs). Additionally, germinomas were further subdivided on the basis of 1) tumor marker (TM) levels, as germinoma with normal TM, mildly elevated TM, and markedly elevated TM and 2) radiology features, as germinomas with typical radiology and atypical radiological features. Results: ICGCT with age ≤6 years (P = 0.049), elevated TM (P = 0.047), and NGGCT histology (P < 0.001) showed significantly worse outcomes. Furthermore, germinomas with markedly elevated TM and certain atypical radiological features showed prognosis akin to NGGCT. Conclusions: Analysis of our largest single cancer center Indian patient cohort of ICGCT shows that inclusion of age ≤6 years, raised TM, and certain radiological features may assist clinicians in overcoming the limitations of surgical sampling, with better prognostication of histologically diagnosed germinomas.

Baseline neurocognitive dysfunction is ubiquitous in intrinsic brain tumors- results from a large Indian cohort of patients and analysis of factors associated with domain-specific dysfunction.

Background: Neurocognitive function (NCF) before surgery is an important marker of baseline performance in patients with brain tumors. Increasingly, neurocognitive deficits (NCD) have been demonstrated in a high proportion of patients. Selection bias (patient, tumor, and surgical procedure related) may influence the prevalence and type of domains involved in patients with gliomas. Methods: We evaluated baseline NCF in a consecutive cohort of intra-axial tumors in Indian patients (n = 142). A comprehensive battery evaluating five domains - attention & executive function (EF), memory, language, visuospatial function and visuomotor abilities was used. Deficits were categorized as severe and mild-moderate. Factors associated with severe NCD were evaluated. Results: Severe NCD was present in 90% of the patients, 70% of them having affection of at least 2 domains. Attention-EF, memory and visuomotor speed were most affected. 132 underwent surgery (69 awake, 63 under general anesthesia - GA). The awake cohort had younger patients with lower grade gliomas and more left sided tumors. Multi-domain dysfunction was seen almost equally in awake/GA groups as well as left/right sided tumors. On multivariate analysis, older age, lower educational status and larger tumor volume adversely affected NCF in many of the domains. Only language dysfunction was location specific (temporal lobe tumors) though not laterality (left/right) specific. Conclusions: NCD were seen in a large majority of cases before surgery, including those undergoing awake surgery. Language may be affected even in tumors in the non-dominant hemisphere. Attention-EF and memory are most affected and need to be factored in while assessing patient performance intraoperatively during awake surgery as well as tailoring rehabilitative measures subsequently.

Imaging-Based Patterns of Failure following Re-Irradiation for Recurrent/Progressive High-Grade Glioma.

BACKGROUND: Re-irradiation (ReRT) is an effective treatment modality in appropriately selected patients with recurrent/progressive high-grade glioma (HGG). The literature is limited regarding recurrence patterns following ReRT, which was investigated in the current study. METHODS: Patients with available radiation (RT) contours, dosimetry, and imaging-based evidence of recurrence were included in the retrospective study. All patients were treated with fractionated focal conformal RT. Recurrence was detected on imaging with magnetic resonance imaging (MRI) and/ or amino-acid positron emission tomography (PET), which was co-registered with the RT planning dataset. Failure patterns were classified as central, marginal, and distant if >80%, 20-80%, or <20% of the recurrence volumes were within 95% isodose lines, respectively. RESULTS: Thirty-seven patients were included in the current analysis. A total of 92% of patients had undergone surgery before ReRT, and 84% received chemotherapy. The median time to recurrence was 9 months. Central, marginal, and distant failures were seen in 27 (73%), 4 (11%), and 6 (16%) patients, respectively. None of the patient-, disease-, or treatment-related factors were significantly different across different recurrence patterns. CONCLUSION: Failures are seen predominantly within the high-dose region following ReRT in recurrent/ progressive HGG.

Demographics, Pattern of Care & Outcomes of Primary CNS Lymphoma- Experience from a Tertiary Care Cancer Center in India.

Primary CNS lymphoma (PCNSL) is a rare subtype of non-Hodgkin lymphoma with the worst outcomes amongst all extranodal lymphomas. There is a scarcity of data on real-world outcomes of primary CNS lymphoma (PCNSL) owing to the rarity of the disease. This study analyzed the demographic patterns, risk stratification, treatment regimens used, & outcomes of patients treated at Tata Memorial Center Mumbai, India. This is a retrospective analysis of newly diagnosed primary CNS lymphoma patients treated at our centre over seven years from January 2013 to December 2019. A total of 142 patients with PCNSL were diagnosed during this period. Thirty (21.1%) patients were deemed ineligible for any systemic or local therapies,ten patients were referred to other hospitals, two patients had relapsed disease, and one was excluded because age less than 18 years. Finally 99 patients were included in the final analysis. Among these 99 patients,72 patients (72.7%) were < 60 years,70 (70.7%) patients had Eastern cooperative oncology group (ECOG) performance status (PS) less than equal to 2. DLBCL was the most common histology (86.4%) while rests were high grade B cell NHL NOS (11.4%),Burkitt's Lymphoma(1%),Peripheral T-cell Lymphoma NOS (1.2%). Only one of 99 patients was positive for HIV serology. Multiple intracranial lesions were found in 59.5%. Surgical resection was performed in 28.4% of patients. Out of 63 patients in whom the International extranodal lymphoma study group (IELSG) score is available, 34(54%) were IELSG high-risk groups. As per Memorial Sloan Kettering Cancer Center (MSKCC) risk grouping, patients were almost equally distributed in all the risk groups, with 32(32.3%) patients in risk group 1 (age < 50 years), 36(36.4%) patients in risk group 2 (age > 50 years, KPS > = 70), and 31(31.3%) patients in risk group 3 age > 50 years, KPS < 70). First-line treatment with high dose methotrexate (HD-MTX) based regimens was administered to 92 (92.9%) patients, and 72.8% of these patients received rituximab. Of these 92 patients, 59 (64.1%) patients could complete induction, and 52 patients received consolidation. Thirty-one patients received high dose cytarabine based chemo consolidation, one patient underwent high dose chemotherapy followed by autologous stem cell transplantation (ACST), and 19 patients received whole-brain radiotherapy (WBRT) and 1 patient received temozolomide as consolidation regimen. Thus only 52 patients completed the entire course of induction with consolidation therapy. The response to treatment was assessed using International PCNSL Collaborative Group Criteria. Post completion of consolidation, 49(94.2%) patients had a complete response. With a median follow-up duration of 39.2 months, the median progression-free survival (PFS) and the median overall survival (OS) of the patients taken into the analysis (N = 99) were 21 and 37 months respectively. On multivariate analysis, age < 60 yrs, > = 5 HD-MTX cycles received & the use of rituximab predicted better OS.Outcomes of patients with PCNSL treated with HD-MTX based therapy are comparable to reported literature however a large proportion of patients do not undergo required treatment despite the curable nature of disease. Supplementary Information: The online version supplementary material available at 10.1007/s12288-022-01557-7.

An Analysis of Eosinophil- and Basophil-Based Indices in Patients with Glioblastoma and their Correlation with Survival.

BACKGROUND: Glioblastoma (GBM) is the most frequently diagnosed malignant brain tumor in adults. GBM is usually lethal within 24 months of diagnosis, despite aggressive multimodality treatment. Although it has been established that cancer-related inflammation is associated with worse outcomes, the role of eosinophils, basophils, atopy, and allergy in glioma biology is only gradually being delineated. In this study, we aimed to examine if eosinophil-based and basophil-based indices were altered in patients with GBM compared with healthy controls. We also aimed to study if there was any correlation between these indices and patient-related and tumor-related factors and survival. METHODS: This study was a retrospective analysis of prospectively maintained databases. Data pertaining to patient-related and tumor-related factors, hemograms, and survival data were obtained from the electronic medical records of selected patients. Correlations between eosinophil-based and basophil-based indices and these factors were studied, as was the association with overall survival. RESULTS: All the indices were altered in patients with GBM compared with normal healthy controls. The absolute eosinophil count was higher and the neutrophils/eosinophils ratio was lower in the better prognosis groups: those with better performance status; those without features of increased intracranial pressure or altered sensorium at presentation; those with ATRX-retained tumors that did not overexpress p53; and in the long-term survivors. The total lymphocyte count/basophils ratio and the absolute eosinophil count both independently predicted survival in a multivariate analysis. CONCLUSIONS: The absolute eosinophil count was consistently higher in the better prognosis groups and is likely to be incorporated into prognostic models for GBM.

Choice of intraoperative ultrasound adjuncts for brain tumor surgery.

BACKGROUND: Gliomas are among the most typical brain tumors tackled by neurosurgeons. During navigation for surgery of glioma brain tumors, preoperatively acquired static images may not be accurate due to shifts. Surgeons use intraoperative imaging technologies (2-Dimensional and navigated 3-Dimensional ultrasound) to assess and guide resections. This paper aims to precisely capture the importance of preoperative parameters to decide which type of ultrasound to be used for a particular surgery. METHODS: This paper proposes two bagging algorithms considering base classifier logistic regression and random forest. These algorithms are trained on different subsets of the original data set. The goodness of fit of Logistic regression-based bagging algorithms is established using hypothesis testing. Furthermore, the performance measures for random-forest-based bagging algorithms used are AUC under ROC and AUC under the precision-recall curve. We also present a composite model without compromising the explainability of the models. RESULTS: These models were trained on the data of 350 patients who have undergone brain surgery from 2015 to 2020. The hypothesis test shows that a single parameter is sufficient instead of all three dimensions related to the tumor ([Formula: see text]). We observed that the choice of intraoperative ultrasound depends on the surgeon making a choice, and years of experience of the surgeon could be a surrogate for this dependence. CONCLUSION: This study suggests that neurosurgeons may not need to focus on a large set of preoperative parameters in order to decide on ultrasound. Moreover, it personalizes the use of a particular ultrasound option in surgery. This approach could potentially lead to better resource management and help healthcare institutions improve their decisions to make the surgery more effective.

Predicting IDH subtype of grade 4 astrocytoma and glioblastoma from tumor radiomic patterns extracted from multiparametric magnetic resonance images using a machine learning approach.

Background and purpose: Semantic imaging features have been used for molecular subclassification of high-grade gliomas. Radiomics-based prediction of molecular subgroups has the potential to strategize and individualize therapy. Using MRI texture features, we propose to distinguish between IDH wild type and IDH mutant type high grade gliomas. Methods: Between 2013 and 2020, 100 patients were retrospectively analyzed for the radiomics study. Immunohistochemistry of the pathological specimen was used to initially identify patients for the IDH mutant/wild phenotype and was then confirmed by Sanger's sequencing. Image texture analysis was performed on contrast-enhanced T1 (T1C) and T2 weighted (T2W) MR images. Manual segmentation was performed on MR image slices followed by single-slice multiple sampling image augmentation. Both whole tumor multislice segmentation and single-slice multiple sampling approaches were used to arrive at the best model. Radiomic features were extracted, which included first-order features, second-order (GLCM-Grey level co-occurrence matrix), and shape features. Feature enrichment was done using LASSO (Least Absolute Shrinkage and Selection Operator) regression, followed by radiomic classification using Support Vector Machine (SVM) and a 10-fold cross-validation strategy for model development. The area under the Receiver Operator Characteristic (ROC) curve and predictive accuracy were used as diagnostic metrics to evaluate the model to classify IDH mutant and wild-type subgroups. Results: Multislice analysis resulted in a better model compared to the single-slice multiple-sampling approach. A total of 164 MR-based texture features were extracted, out of which LASSO regression identified 14 distinctive GLCM features for the endpoint, which were used for further model development. The best model was achieved by using combined T1C and T2W MR images using a Quadratic Support Vector Machine Classifier and a 10-fold internal cross-validation approach, which demonstrated a predictive accuracy of 89% with an AUC of 0.89 for each IDH mutant and IDH wild subgroup. Conclusion: A machine learning classifier of radiomic features extracted from multiparametric MRI images (T1C and T2w) provides important diagnostic information for the non-invasive prediction of the IDH mutant or wild-type phenotype of high-grade gliomas and may have potential use in either escalating or de-escalating adjuvant therapy for gliomas or for using targeted agents in the future.