Prediction of PD-L1 and Ki-67 status in primary central nervous system diffuse large B-cell lymphoma by diffusion and perfusion MRI: a preliminary study.

OBJECTIVE: To assess whether diffusion and perfusion MRI derived parameters could non-invasively predict PD-L1 and Ki-67 status in primary central nervous system diffuse large B-cell lymphoma (PCNS-DLBCL). METHODS: We retrospectively analyzed DWI, DSC-PWI, and morphological MRI (mMRI) in 88 patients with PCNS-DLBCL. The mMRI features were compared using chi-square tests or Fisher exact test. Minimum ADC (ADCmin), mean ADC(ADCmean), relative minimum ADC (rADCmin), relative mean ADC (rADCmean), and relative maximum CBV (rCBVmax) values were compared in PCNS-DLBCL with different molecular status by using the Mann-Whitney U test. The diagnostic performances were evaluated by receiver operating characteristic curves. RESULTS: PCNS-DLBCL with high PD-L1 expression demonstrated a significantly higher ADCmin value than those with low PD-L1. The ADCmean and rADCmean values were significantly lower in PCNS-DLBCL with high Ki-67 status compared with those in low Ki-67 status. Other ADC, CBV parameters, and mMRI features did not show any association with these molecular statuses The diagnostic efficacy of ADC values in assessing PD-L1 and Ki-67 status was relatively low, with area under the curves (AUCs) values less than 0.7. CONCLUSIONS: DWI-derived ADC values can provide some relevant information about PD-L1 and Ki-67 status in PCNS-DLBCL, but may not be sufficient to predict their expression due to the rather low diagnostic performance.

[«Masks¼ of CNS demyelinating diseases. Primary lymphoma]. / «Maski¼ demieliniziruyushchikh zabolevanii TsNS. Pervichnaya limfoma.

Primary central nervous system lymphoma (PCNSL) is a rare neoplasm that can affect the brain, eyes, and, rarely, the spinal cord. Clinical presentation and MRI findings can mimic a variety of diseases, including high-grade gliomas, infectious and granulomatous diseases, and demyelinating diseases. We describe three cases where the diagnosis of PCNSL was difficult due to an ambiguous clinical, radiological and laboratory results. The role of stereotactic biopsy remains leading in differential diagnosis; however, the invasiveness and frequent limitations of this method determine the search for additional biological markers of the disease. New evidence suggests a potential role for cerebrospinal fluid (CSF) cytokine profiles and proteomic analysis in differential diagnosis, disease progression, and treatment response.

Central nervous system involvement in chronic lymphocytic leukemia: a case report and review of literature.

BACKGROUND: Central nervous system involvement in chronic lymphocytic leukemia rarely occurs, and there is no standard therapy for central nervous system involvement in chronic lymphocytic leukemia. This article aims to analyze the diagnosis and treatment of central nervous system involvement in chronic lymphocytic leukemia. CASE PRESENTATION: It reports two cases of central nervous system involvement in chronic lymphocytic leukemia describing the clinical course, therapy, and prognosis. Case 1 is a 67-year-old Asian male patient, he experienced complications with central nervous system involvement after developing resistance to ibrutinib, bendamustine, and rituximab (BR) chemotherapies. The central nervous system lesion was controlled with high-dose methotrexate combined with pomalidomide, but Richter transformation occurred several months later. Case 2 is a 62-year-old Asian female patient, she had central nervous system involvement at initial diagnosis, and bone marrow and central nervous system lesions were controlled by ibrutinib therapy. CONCLUSION: Central nervous system involvement in chronic lymphocytic leukemia is rare and can be diagnosed on the basis of clinical features, cerebrospinal fluid testing, and radiographic evaluation. Ibrutinib, pomalidomide, and other drugs that can cross the blood-brain barrier may be effective for treating central nervous system involvement in chronic lymphocytic leukemia.

Clinical features, MRI, molecular alternations, and prognosis of astrocytoma based on WHO 2021 classification of central nervous system tumors: A single-center retrospective study.

BACKGROUND: The diagnosis of glioma has advanced since the release of the WHO 2021 classification with more molecular alterations involved in the integrated diagnostic pathways. Our study aimed to present our experience with the clinical features and management of astrocytoma, IDH mutant based on the latest WHO classification. METHODS: Patients diagnosed with astrocytoma, IDH-mutant based on the WHO 5th edition classification of CNS tumors at our center from January 2009 to January 2022 were included. Patients were divided into WHO 2-3 grade group and WHO 4 grade group. Integrate diagnoses were retrospectively confirmed according to WHO 2016 and 2021 classification. Clinical and MRI characteristics were reviewed, and survival analysis was performed. RESULTS: A total of 60 patients were enrolled. 21.67% (13/60) of all patients changed tumor grade from WHO 4th edition classification to WHO 5th edition. Of these, 21.43% (6/28) of grade II astrocytoma and 58.33% (7/12) of grade III astrocytoma according to WHO 4th edition classification changed to grade 4 according to WHO 5th edition classification. Sex (p = 0.042), recurrent glioma (p = 0.006), and Ki-67 index (p < 0.001) of pathological examination were statistically different in the WHO grade 2-3 group (n = 27) and WHO grade 4 group (n = 33). CDK6 (p = 0.004), FGFR2 (p = 0.003), and MYC (p = 0.004) alterations showed an enrichment in the WHO grade 4 group. Patients with higher grade showed shorter mOS (mOS = 75.9 m, 53.6 m, 26.4 m for grade 2, 3, and 4, respectively, p = 0.01). CONCLUSIONS: Patients diagnosed as WHO grade 4 according to the 5th edition WHO classification based on molecular alterations are more likely to have poorer prognosis. Therefore, treatment should be tailored to their individual needs. Further research is needed for the management of IDH-mutant astrocytoma is needed in the future.

MRI-based radiomics signatures for preoperative prediction of Ki-67 index in primary central nervous system lymphoma.

PURPOSE: The aim of this study was to develop and validate radiomics signatures based on MRI for preoperative prediction of Ki-67 proliferative index (PI) expression in primary central nervous system lymphoma (PCNSL). METHODS: A total of 341 patients with PCNSL were retrospectively analyzed, including 286 patients in one center as the training set and 55 patients in another two centers as the external validation set. Radiomics features were extracted and selected from preoperative contrast-enhanced T1-weighted images, fluid attenuation inversion recovery to build radiomics signatures according to the Ki-67 PI. The predictive performances of the radiomics model were evaluated using four classifiers including random forest, K-Nearest Neighbors, Neural Network and Decision Tree. A combined model was built by incorporating radiomics signature, clinical variables and MRI radiological characteristics using multivariate logistic regression analysis, and a nomogram was established to predict the expression of Ki-67 individually. The predictive performances of the models were evaluated using area under receiver operating characteristic curve (AUC) and decision curve analysis (DCA). RESULTS: Radiomics signatures were independent predictors of the expression level of Ki-67 (OR: 2.523, P < 0.001). RF radiomics models had the highest accuracy (0.934 in the training set and 0.811 in the external validation set) and F1 Score (0.920 in the training set and 0.836 in the external validation set). The clinic-radiologic-radiomics nomogram showed better predictive performance with AUCs of 0.877(95 % CI: 0.837-0.918) in the training set and 0.866(95 % CI: 0.774-0.957) in the external validation set. The calibration curve and DCA demonstrated goodness-of-fit and improved benefits in clinical practice of the nomogram. CONCLUSIONS: Nomograms integrating MRI-based radiomics and clinical-radiological characteristics could effectively predict Ki-67 PI in primary PCNSL.

Primary central nervous system neuroblastoma mimicking a meningioma: A case report.

ABSTRACT: Neuroblastomas are the most common extracranial solid tumor in the pediatric age group (~8%-10% of childhood neoplasms). Most cases of intracranial neuroblastomas occur due to metastasis from some primary extracranial sites and are known as secondary neuroblastomas. However, the occurrence of primary central nervous system neuroblastomas (PCN-NB) is very rare, and only a few cases and case series have been reported in the literature. PCN-NB is mainly an intra-axial pathology, and extra-axial involvement is mainly due to metastasis from some extracranial primary site with involvement of the skull bone. Herein we report a case of a 23-year-old female having a large extra-axial space-occupying lesion in the right frontal region that was mimicking a meningioma, and surprisingly the histopathology was suggestive of a supratentorial neuroblastoma. A right frontal craniotomy was made, and Simpson's grade 1 excision of the tumor was done. The excised tissue was sent for histopathological examination. PCN-NB located extra-axially are extremely rare to occur. Due to inconsistent radiological imaging, it becomes very difficult to diagnose these tumors preoperatively, and these should be kept in mind as one of the differential diagnoses of extra-axial intracranial space-occupying lesions. Histopathological examination is crucial in diagnosing the intracranial neuroblastomas.

Primary diffuse large B-cell lymphoma of the central nervous system identified with CSF biomarkers.

BACKGROUND: Diagnosis of primary diffuse large B-cell lymphoma of the central nervous system (PCNSL) is challenging and often delayed. MRI imaging, CSF cytology and flow cytometry have a low sensitivity and even brain biopsies can be misleading. We report three cases of PCNSL with various clinical presentation and radiological findings where the diagnosis was suggested by novel CSF biomarkers and subsequently confirmed by brain biopsy or autopsy. CASE PRESENTATIONS: The first case is a 79-year-old man with severe neurocognitive dysfunction and static ataxia evolving over 5 months. Brain MRI revealed a nodular ventriculitis. An open brain biopsy was inconclusive. The second case is a 60-year-old woman with progressive sensory symptoms in all four limbs, evolving over 1 year. Brain and spinal MRI revealed asymmetric T2 hyperintensities of the corpus callosum, corona radiata and corticospinal tracts. The third case is a 72-year-old man recently diagnosed with primary vitreoretinal lymphoma of the right eye. A follow-up brain MRI performed 4 months after symptom onset revealed a T2 hyperintense fronto-sagittal lesion, with gadolinium uptake and perilesional edema. In all three cases, CSF flow cytometry and cytology were negative. Mutation analysis on the CSF (either by digital PCR or by next generation sequencing) identified the MYD88 L265P hotspot mutation in all three cases. A B-cell clonality study, performed in case 1 and 2, identified a monoclonal rearrangement of the immunoglobulin light chain lambda (IGL) and kappa (IGK) gene. CSF CXCL-13 and IL-10 levels were high in all three cases, and IL-10/IL-6 ratio was high in two. Diagnosis of PCNSL was later confirmed by autopsy in case 1, and by brain biopsy in case 2 and 3. CONCLUSIONS: Taken together, 5 CSF biomarkers (IL-10, IL-10/IL-6 ratio, CXCL13, MYD88 mutation and monoclonal IG gene rearrangements) were strongly indicative of a PCNSL. Using innovative CSF biomarkers can be sensitive and complementary to traditional CSF analysis and brain biopsy in the diagnosis of PCNSL, potentially allowing for earlier diagnosis and treatment.

Correlation Between CT Density, Incidence, Mortality, and Mortality-to-Incidence Ratio in Central Nervous System Cancers: An Exploratory Analysis of Global Data.

BACKGROUND/AIM: Cancers of the central nervous system (CNS) pose a significant burden, despite their relatively low incidence compared to other types of cancers. The mortality-to-incidence ratio (MIR) is a crucial indicator of long-term survival and healthcare system performance. Computed tomography (CT) plays a crucial role in the screening, diagnosis, and monitoring of brain tumors, enabling early intervention and treatment. This study aimed to explore the relationship between CT density, CNS cancer incidence, mortality, and MIR to investigate regional variations in CT utilization and their impact on CNS cancer mortality rates. PATIENTS AND METHODS: Changes in MIR, referred to as δMIR, were calculated based on data from 2012 and 2018. CT density data for the year 2013 were retrieved from the Global Health Observatory data repository. The association between variables was analyzed using Spearman's rank correlation coefficient. RESULTS: Analysis of data from 107 countries revealed a positive association between CT density and both CNS cancer incidence and mortality. However, a trend was observed between CT density and MIR. These findings suggest that in countries with greater accessibility to CT imaging, CNS cancer cases may be detected earlier and lower mortality rates can be achieved. CONCLUSION: Our research contributes to the understanding of the impact of CT imaging on the management and outcomes of CNS cancers. It informs healthcare strategies and resource allocation to improve patient care.

Primary central nervous system lymphomas in immunocompromised patients require specific response criteria.

PURPOSE: Immunosuppression is a well-established risk factor for primary central nervous system lymphomas (PCNSLs), which present in this context distinct radiological characteristics. Our aim was to describe the radiological evolution of treated PCNSL in immunocompromised patients and suggest adapted MRI response criteria. METHODS: We conducted a multicenter retrospective study of patients from the French LOC, K-Virogref and CANCERVIH network databases and enrolled adult immunocompromised patients with newly diagnosed PCNSL. RESULTS: We evaluated the baseline, intermediate, end-of-treatment and follow-up MRI data of 31 patients (9 living with HIV, 16 with solid organ transplantation and 6 with an autoimmune disease under chronic immunosuppressive therapy). At baseline, 23/30 (77%) patients had necrotic lesions with ring enhancement and 28% of the lesions were hemorrhagic. At the end of the first-line treatment, 12/28 (43%) patients could not be classified according to the IPCG criteria. Thirteen of 28 (46%) patients still harbored contrast enhancement, and 11/28 (39%) patients had persistent large necrotic lesions with a median diameter of 15 mm. These aspects were not associated with a pejorative outcome and progressively diminished during follow-up. Six patients relapsed; however, we failed to identify any neuroimaging risk factors on the end-of-treatment MRI. CONCLUSION: In immunocompromised patients, PCNSLs often harbor alarming features on end-of-treatment MRI, with persistent contrast-enhanced lesions frequently observed. However, these aspects seemed to be related to the necrotic and hemorrhagic nature of the lesions and were not predictive of a pejorative outcome. Specific response criteria for this population are thereby proposed.

Immunotherapy for Solitary Fibrous Tumor (Hemangiopericytoma): A Unique Treatment Approach for a Rare Central Nervous System Tumor.

INTRODUCTION: Solitary fibrous tumors (SFTs) of the central nervous system represent a unique entity with limited data on best treatment practices. CASE REPORT: Here, we present a case of multiply recurrent central nervous system SFT treated with radiation and immunotherapy. Immunotherapy was chosen based on mutations of genes encoding DNA repair enzymes detected through next-generation sequencing of the tumor, DNA polymerase epsilon catalytic subunit ( POLE ) and mutL homolog 1. The use of radiation and immunotherapy led to slight shrinkage and no recurrence of the tumor for over 2 years. CONCLUSION: The presence of somatic DNA repair enzyme gene mutations in SFT may suggest a benefit from a combination of radiotherapy and immunotherapy. This may serve as a biomarker for guiding management in patients with this rare tumor.

The Utility of Multiparametric Magnetic Resonance Imaging in Reducing Diagnostic Uncertainty for Primary Central Nervous System Lymphoma.

BACKGROUND: A key limitation in treatment initiation in primary central nervous system lymphoma (PCNSL) is the diagnostic delay caused by lack of recognition of a lesion as a possible lymphoma, steroid initiation, and lesion involution, often resulting in an inconclusive biopsy result. We highlight the importance of multiparametric magnetic resonance imaging (MRI), which incorporates diffusion-weighted imaging, dynamic susceptibility contrast-enhanced perfusion-weighted imaging, and proton magnetic resonance spectroscopy in addition to standard MRI sequences in resolving diagnostic uncertainty for PCNSL. METHODS: At our center, a consecutive series of 10 patients with histology-proven PCNSL (specifically, diffuse large B-cell lymphoma of the central nervous system) underwent multiparametric MRI. We retrospectively analyzed qualitative and semiquantitative parameters and assessed their radiological concordance for this diagnosis. RESULTS: We noted overall low apparent diffusion coefficient on diffusion-weighted imaging (mean minimum apparent diffusion coefficient of 0.74), high percentage signal recovery on perfusion-weighted imaging (mean 170%), a high choline-to-creatine ratio, and a high-grade lipid peak on proton magnetic resonance spectroscopy giving an appearance of twin towers. Of 10 patients, 9 had MRI findings concordant for PCNSL, defined as at least 3 of 4 parameters being consistent for PCNSL. CONCLUSIONS: Concordance between these imaging multiparametric modalities could be used as a radiological predictor of PCNSL, reducing diagnostic delays, providing a more accurate biopsy target, and resulting in quicker treatment initiation.

Clinical Characteristics and Delayed Diagnosis of Pediatric Patients Presenting to the Emergency Department With a Newly Diagnosed Central Nervous System Tumor: A Single Institutional Experience.

BACKGROUND: Due to the varied symptomatology and inconsistent features on neurologic exam, central nervous system (CNS) tumors are difficult to diagnosis in a timely manner. OBJECTIVE: To determine the clinical, neurological, and neuroimaging features of newly diagnosed CNS tumors presenting to the emergency department (ED). METHODS: We evaluated a retrospective cohort of 121 consecutive patients presenting to a tertiary care pediatric ED over 7 consecutive years with newly diagnosed CNS tumors. Clinical symptomatology, neurologic findings reported by emergency room and neurology physicians, neuroimaging features, and time to diagnosis were analyzed. RESULTS: A total of 116 (48 female, median age 8.0 years (interquartile range, 4.4-12.6), 52% Hispanic) presented to the ED (64% self-referred) diagnosed with a brain tumor (54% posterior fossa, 24% embryonal, 24% low-grade glioma, 16% high-grade glioma) resulting in hospital admission in 92% of cases. Five were diagnosed with extradural spinal, clivus, or orbital apex tumors. Symptomatology or duration did not differ when stratified by demographics, location, or histologic subtype. Moderate degree of concordance was observed among neurologic examinations performed by ED physicians and neurologists. Delayed diagnosis (median delay = 3.5 [1-7] months) was seen in 14% of patients, 13 with primary brain tumors (11 hemispheric, 2 brain stem). Six children with delayed diagnosis of low-grade glial tumors had a nonfocal neurologic examination in comparison to 5 patients with abnormal examinations observed with primary spinal or extradural CNS tumors. Four patients with posterior fossa tumors (3 medulloblastoma, 1 ependymoma) had normal/near normal neurologic examination at presentation despite posterior fossa symptomatology related to increased intracranial pressure. CONCLUSIONS: Our series highlights the complexity of symptomology and neurologic findings in children presenting to the ED with newly diagnosed CNS tumors who may have a normal neurologic examination. Standardization of symptom assessment and focused neurologic examinations may lead to earlier neuroimaging and prevent delayed diagnosis.

An improved attention module based on nnU-Net for segmenting primary central nervous system lymphoma (PCNSL) in MRI images1.

BACKGROUND: Accurate volumetric segmentation of primary central nervous system lymphoma (PCNSL) is essential for assessing and monitoring the tumor before radiotherapy and the treatment planning. The tedious manual segmentation leads to interindividual and intraindividual differences, while existing automatic segmentation methods cause under-segmentation of PCNSL due to the complex and multifaceted nature of the tumor. OBJECTIVE: To address the challenges of small size, diffused distribution, poor inter-layer continuity on the same axis, and tendency for over-segmentation in brain MRI PCNSL segmentation, we propose an improved attention module based on nnUNet for automated segmentation. METHODS: We collected 114 T1 MRI images of patients in the Huashan Hospital, Shanghai. Then randomly split the total of 114 cases into 5 distinct training and test sets for a 5-fold cross-validation. To efficiently and accurately delineate the PCNSL, we proposed an improved attention module based on nnU-Net with 3D convolutions, batch normalization, and residual attention (res-attention) to learn the tumor region information. Additionally, multi-scale dilated convolution kernels with different dilation rates were integrated to broaden the receptive field. We further used attentional feature fusion with 3D convolutions (AFF3D) to fuse the feature maps generated by multi-scale dilated convolution kernels to reduce under-segmentation. RESULTS: Compared to existing methods, our attention module improves the ability to distinguish diffuse and edge enhanced types of tumors; and the broadened receptive field captures tumor features of various scales and shapes more effectively, achieving a 0.9349 Dice Similarity Coefficient (DSC). CONCLUSIONS: Quantitative results demonstrate the effectiveness of the proposed method in segmenting the PCNSL. To our knowledge, this is the first study to introduce attention modules into deep learning for segmenting PCNSL based on brain magnetic resonance imaging (MRI), promoting the localization of PCNSL before radiotherapy.

Development of Magnetic Resonance-Compatible Head Immobilization Device and Initial Experience of Magnetic Resonance-Guided Radiation Therapy for Central Nervous System Tumors.

PURPOSE: We aimed to develop and investigate positional reproducibility using a fixation device (Unity Brain tumor Immobilization Device [UBID]) in patients with brain tumor undergoing magnetic resonance (MR)-guided radiation therapy (RT) with a 1.5 Tesla (T) MR-linear accelerator (MR-LINAC) to evaluate its feasibility in clinical practice and report representative cases of patients with central nervous system (CNS) tumor. MATERIALS AND METHODS: Quantitative analysis was performed by comparing images obtained by placing only the MR phantom on the couch with those obtained by placing UBID next to the MR phantom. Twenty patients who underwent RT for CNS tumors using 1.5T MR-LINAC between June and October 2022 were retrospectively analyzed. Among them, 5 did not use UBID, whereas 15 used UBID. The positional reproducibility of UBID was evaluated using the median interfractional and intrafractional errors in the first 10 fractions. RESULTS: Each MR quality factor of the MR phantom with UBID satisfied the criteria presented by Elekta. Median values of median shifts in the mediolateral, anteroposterior, and craniocaudal axes for interfractional errors were 2.98, 2.35, and 1.40 mm, respectively. For intrafractional errors, the median values were 0.05, 0.03, and 0.06 mm, respectively. The median values of the median rotations in pitch, roll, and yaw for both interfractional and intrafractional rotations were 0.00°. One patient diagnosed with an optic nerve sheath meningioma received RT with motion monitoring during irradiation. In 2 patients, changes in the tumor cavity and residual lesions were observed in the MRI obtained using 1.5T MR-LINAC on the day of the first treatment and immediately before the 21st fraction, respectively; therefore, offline/online adaptation was performed. CONCLUSIONS: The reproducible and immobile UBID is clinically feasible in patients with CNS tumors receiving RT with 1.5T MR-LINAC. Based on our initial experience, we developed a workflow for 1.5T MR-LINAC treatment of CNS tumors.

18F-FDG PET/MR for diagnosis of primary central nervous system lymphoma: protocol for a systematic review and meta-analysis.

BACKGROUND: Primary central nervous system lymphoma (PCNSL) is a rare form of extranodal non-Hodgkin's lymphoma with poor prognosis. 18F-flourodeoxyglucose positron emission tomography (PET)/magnetic resonance (MR) combines the advantages of PET and MR. The aim of this study is to evaluate the validity of PET/MR for the diagnosis of PCNSL by means of a meta-analysis. METHODS AND ANALYSIS: Wanfang Database, SinoMed, China National Knowledge Infrastructure, the Cochrane Library, PubMed and Embase will be searched for candidate studies about PET/MRI in PCNSL diagnosis from database inception to October 2024. The following keywords will be applied: "Primary central nervous system lymphoma", "Primary intracerebral lymphoma", "Positron Emission Tomography Magnetic Resonance" and "PET-MR". Studies meeting the inclusion criteria will be included. Studies without full true positive, false positive, false negative and true negative values; studies reported in languages other than English and Chinese; conference abstracts not available in full text and case reports will be excluded. Quality Assessment of Diagnostic Accuracy Studies will be used to evaluate the study quality. The STATA software (V.15.0) and Meta-Disc software (V.1.4) will be used to carry out meta-analysis. When heterogeneity is evident, subgroup analysis will be used to investigate the origin of heterogeneity. The robustness of the analysis will be checked with sensitivity analysis. ETHICS AND DISSEMINATION: This research is based on public databases and does not require ethical approval. The results will seek publication in a peer-reviewed journal after the completion of this systematic review and meta-analysis. PROSPERO REGISTRATION NUMBER: CRD42023472570.

BCOR::CREBBP fusion in malignant neuroepithelial tumor of CNS expands the spectrum of methylation class CNS tumor with BCOR/BCOR(L1)-fusion.

Methylation class "CNS tumor with BCOR/BCOR(L1)-fusion" was recently defined based on methylation profiling and tSNE analysis of a series of 21 neuroepithelial tumors with predominant presence of a BCOR fusion and/or characteristic CNV breakpoints at chromosome 22q12.31 and chromosome Xp11.4. Clear diagnostic criteria are still missing for this tumor type, specially that BCOR/BCOR(L1)-fusion is not a consistent finding in these tumors despite being frequent and that none of the Heidelberger classifier versions is able to clearly identify these cases, in particular tumors with alternative fusions other than those involving BCOR, BCORL1, EP300 and CREBBP. In this study, we introduce a BCOR::CREBBP fusion in an adult patient with a right temporomediobasal tumor, for the first time in association with methylation class "CNS tumor with BCOR/BCOR(L1)-fusion" in addition to 35 cases of CNS neuroepithelial tumors with molecular and histopathological characteristics compatible with "CNS tumor with BCOR/BCOR(L1)-fusion" based on a comprehensive literature review and data mining in the repository of 23 published studies on neuroepithelial brain Tumors including 7207 samples of 6761 patients. Based on our index case and the 35 cases found in the literature, we suggest the archetypical histological and molecular features of "CNS tumor with BCOR/BCOR(L1)-fusion". We also present four adult diffuse glioma cases including GBM, IDH-Wildtype and Astrocytoma, IDH-Mutant with CREBBP fusions and describe the necessity of complementary molecular analysis in "CNS tumor with BCOR/BCOR(L1)-alterations for securing a final diagnosis.

How does deep learning/machine learning perform in comparison to radiologists in distinguishing glioblastomas (or grade IV astrocytomas) from primary CNS lymphomas?: a meta-analysis and systematic review.

BACKGROUND: Several studies have been published comparing deep learning (DL)/machine learning (ML) to radiologists in differentiating PCNSLs from GBMs with equivocal results. We aimed to perform this meta-analysis to evaluate the diagnostic accuracy of ML/DL versus radiologists in classifying PCNSL versus GBM using MRI. METHODOLOGY: The study was performed in accordance with PRISMA guidelines. Data was extracted and interpreted by two researchers with 12 and 23 years' experience, respectively, and QUADAS-2 tool was used for quality and risk-bias assessment. We constructed contingency tables to derive sensitivity, specificity accuracy, summary receiver operating characteristic (SROC) curve, and the area under the curve (AUC). RESULTS: Our search identified 11 studies, of which 8 satisfied our inclusion criteria and restricted the analysis in each study to reporting the model showing highest accuracy, with a total sample size of 1159 patients. The random effects model showed a pooled sensitivity of 0.89 [95% CI:0.84-0.92] for ML and 0.82 [95% CI:0.76-0.87] for radiologists. Pooled specificity was 0.88 [95% CI: 0.84-0.91] for ML and 0.90 [95% CI: 0.81-0.95] for radiologists. Pooled accuracy was 0.88 [95% CI: 0.86-0.90] for ML and 0.86 [95% CI: 0.78-0.91] for radiologists. Pooled AUC of ML was 0.94 [95% CI:0.92-0.96]and for radiologists, it was 0.90 [95% CI: 0.84-0.93]. CONCLUSIONS: MRI-based ML/DL techniques can complement radiologists to improve the accuracy of classifying GBMs from PCNSL, possibly reduce the need for a biopsy, and avoid any unwanted neurosurgical resection of a PCNSL.