Expert-centered Evaluation of Deep Learning Algorithms for Brain Tumor Segmentation.

Purpose To present results from a literature survey on practices in deep learning segmentation algorithm evaluation and perform a study on expert quality perception of brain tumor segmentation. Materials and Methods A total of 180 articles reporting on brain tumor segmentation algorithms were surveyed for the reported quality evaluation. Additionally, ratings of segmentation quality on a four-point scale were collected from medical professionals for 60 brain tumor segmentation cases. Results Of the surveyed articles, Dice score, sensitivity, and Hausdorff distance were the most popular metrics to report segmentation performance. Notably, only 2.8% of the articles included clinical experts' evaluation of segmentation quality. The experimental results revealed a low interrater agreement (Krippendorff α, 0.34) in experts' segmentation quality perception. Furthermore, the correlations between the ratings and commonly used quantitative quality metrics were low (Kendall tau between Dice score and mean rating, 0.23; Kendall tau between Hausdorff distance and mean rating, 0.51), with large variability among the experts. Conclusion The results demonstrate that quality ratings are prone to variability due to the ambiguity of tumor boundaries and individual perceptual differences, and existing metrics do not capture the clinical perception of segmentation quality. Keywords: Brain Tumor Segmentation, Deep Learning Algorithms, Glioblastoma, Cancer, Machine Learning Clinical trial registration nos. NCT00756106 and NCT00662506 Supplemental material is available for this article. © RSNA, 2023.

Bavituximab Decreases Immunosuppressive Myeloid-Derived Suppressor Cells in Newly Diagnosed Glioblastoma Patients.

PURPOSE: We evaluated the efficacy of bavituximab-a mAb with anti-angiogenic and immunomodulatory properties-in newly diagnosed patients with glioblastoma (GBM) who also received radiotherapy and temozolomide. Perfusion MRI and myeloid-related gene transcription and inflammatory infiltrates in pre-and post-treatment tumor specimens were studied to evaluate on-target effects (NCT03139916). PATIENTS AND METHODS: Thirty-three adults with IDH--wild-type GBM received 6 weeks of concurrent chemoradiotherapy, followed by 6 cycles of temozolomide (C1-C6). Bavituximab was given weekly, starting week 1 of chemoradiotherapy, for at least 18 weeks. The primary endpoint was proportion of patients alive at 12 months (OS-12). The null hypothesis would be rejected if OS-12 was ≥72%. Relative cerebral blood flow (rCBF) and vascular permeability (Ktrans) were calculated from perfusion MRIs. Peripheral blood mononuclear cells and tumor tissue were analyzed pre-treatment and at disease progression using RNA transcriptomics and multispectral immunofluorescence for myeloid-derived suppressor cells (MDSC) and macrophages. RESULTS: The study met its primary endpoint with an OS-12 of 73% (95% confidence interval, 59%-90%). Decreased pre-C1 rCBF (HR, 4.63; P = 0.029) and increased pre-C1 Ktrans were associated with improved overall survival (HR, 0.09; P = 0.005). Pre-treatment overexpression of myeloid-related genes in tumor tissue was associated with longer survival. Post-treatment tumor specimens contained fewer immunosuppressive MDSCs (P = 0.01). CONCLUSIONS: Bavituximab has activity in newly diagnosed GBM and resulted in on-target depletion of intratumoral immunosuppressive MDSCs. Elevated pre-treatment expression of myeloid-related transcripts in GBM may predict response to bavituximab.

Ten-Year Follow-up of Internal Neurofibroma Growth Behavior in Adult Patients With Neurofibromatosis Type 1 Using Whole-Body MRI.

BACKGROUND AND OBJECTIVES: Internal neurofibromas, including plexiform neurofibromas (PNF), can cause significant morbidity in patients with neurofibromatosis type 1 (NF1). PNF growth is most pronounced in children and young adults, with more rapid growth thought to occur in a subset of PNF termed distinct nodular lesions (DNL). Growth behavior of internal neurofibromas and DNL in older adults is not well documented; yet knowledge thereof is important for patient risk stratification and clinical trial design. The primary objective of this study was to evaluate the long-term growth behavior of internal neurofibromas in adults with NF1. Secondary objectives were to correlate tumor growth behavior with patient-specific, tumor-specific, and patient-reported variables. METHODS: In this prospective cohort study, internal neurofibromas were identified on coronal short TI inversion recovery sequences on baseline and follow-up whole-body MRIs (WBMRIs). Tumor growth and shrinkage were defined as a volume change ≥20%. The association between tumor growth and patient-specific (baseline age, sex, and genotype), tumor-specific (morphology, location, DNL presence on baseline WBMRI, and maximum standardized uptake value on baseline PET imaging), and patient-reported variables (endogenous and exogenous hormone exposure, pain intensity, and quality of life) was assessed using the Spearman correlation coefficient and Kruskal-Wallis test. RESULTS: Of 106 patients with a baseline WBMRI obtained as part of a previous research study, 44 had a follow-up WBMRI. Three additional patients with WBMRIs acquired for clinical care were included, generating 47 adults for this study. The median age during baseline WBMRI was 42 years (range 18-70). The median time between WBMRIs was 10.4 years. Among 324 internal neurofibromas, 62.8% (56% of PNF and 62.1% of DNL) shrank spontaneously without treatment and 17.1% (17.9% of PNF and 13.8% of DNL) grew. Growth patterns were heterogeneous within participants. Patient-specific, tumor-specific, and patient-reported variables (including endogenous and exogenous hormone exposure) were not strong predictors of tumor growth. DISCUSSION: Internal neurofibroma growth behavior in older adults differs fundamentally from that in children and young adults, with most tumors, including DNL, demonstrating spontaneous shrinkage. Better growth models are needed to understand factors that influence tumor growth. These results will inform clinical trial design for internal neurofibromas.

Design of a randomized, placebo-controlled, phase 2 study evaluating the safety and efficacy of tanezumab for treatment of schwannomatosis-related pain.

BACKGROUND: Schwannomatosis (SWN) is a rare tumor suppressor syndrome that predisposes affected individuals to develop multiple schwannomas and, less often, meningiomas. The most common symptom is chronic, severe pain. No medications are broadly effective in treating SWN-associated pain. The clinical trial described in this manuscript is a phase 2, randomized, double-blind, placebo-controlled study investigating the safety and efficacy of tanezumab - a humanized monoclonal antibody that inhibits nerve growth factor - for treatment of SWN-related pain. As the first therapeutic trial for SWN-related pain, it also aims to evaluate trial endpoints, understand recruitment patterns, and improve clinical trial design in this rare disease. AIMS: The primary objective of this trial is to assess the analgesic efficacy of subcutaneous tanezumab 10 mg in subjects with SWN who continue pre-existing pain therapy (excluding non-steroidal anti-inflammatory drugs). The secondary objective is to assess safety in this population. Exploratory objectives include assessment of pain features, quality of life, and predictive biomarkers. METHODS: The study is comprised of four periods (pre-treatment, double-blind treatment, single-arm treatment, safety follow-up) across 10 months with a delayed-start trial design to allow all participants to receive tanezumab. Forty-six participants will be enrolled and randomized 1:1 to receive either tanezumab or placebo subcutaneously in the double-blind treatment period; all participants receive tanezumab during the single-arm treatment period. CONCLUSIONS: This study is the first therapeutic trial for SWN patients and targets a biological driver of SWN-related pain. It aims to establish a model for future pain studies in SWN and other rare diseases. CLINICAL TRIAL REGISTRATION: NCT04163419 on ClinicalTrials.gov.

DINs: Deep Interactive Networks for Neurofibroma Segmentation in Neurofibromatosis Type 1 on Whole-Body MRI.

Neurofibromatosis type 1 (NF1) is an autosomal dominant tumor predisposition syndrome that involves the central and peripheral nervous systems. Accurate detection and segmentation of neurofibromas are essential for assessing tumor burden and longitudinal tumor size changes. Automatic convolutional neural networks (CNNs) are sensitive and vulnerable as tumors' variable anatomical location and heterogeneous appearance on MRI. In this study, wepropose deep interactive networks (DINs) to address the above limitations. User interactions guide the model to recognize complicated tumors and quickly adapt to heterogeneous tumors. We introduce a simple but effective Exponential Distance Transform (ExpDT) that converts user interactions into guide maps regarded as the spatial and appearance prior. Comparing with popular Euclidean and geodesic distances, ExpDT is more robust to various image sizes, which reserves the distribution of interactive inputs. Furthermore, to enhance the tumor-related features, we design a deep interactive module to propagate the guides into deeper layers. We train and evaluate DINs on three MRI data sets from NF1 patients. The experiment results yield significant improvements of 44% and 14% in DSC comparing with automated and other interactive methods, respectively. We also experimentally demonstrate the efficiency of DINs in reducing user burden when comparing with conventional interactive methods.

Validating Techniques for Measurement of Cutaneous Neurofibromas: Recommendations for Clinical Trials.

OBJECTIVE: To assess the reliability and variability of digital calipers, 3D photography, and high-frequency ultrasound (HFUS) for measurement of cutaneous neurofibromas (cNF) in patients with neurofibromatosis type 1 (NF1). BACKGROUND: cNF affect virtually all patients with NF1 and are a major source of morbidity. Reliable techniques for measuring cNF are needed to develop therapies for these tumors. METHODS: Adults with NF1 were recruited. For each participant, 6 cNF were assessed independently by 3 different examiners at 5 different time points using digital calipers, 3D photography, and HFUS. The intraclass correlation coefficient (ICC) was used to assess intrarater and interrater reliability of linear and volumetric measurements for each technique, with ICC values >0.90 defined as excellent reliability. The coefficient of variation (CV) was used to estimate the minimal detectable difference (MDD) for each technique. RESULTS: Fifty-seven cNF across 10 participants were evaluated. The ICC for image acquisition and measurement was >0.97 within and across examiners for HFUS and 3D photography. ICC for digital calipers was 0.62-0.88. CV varied by measurement tool, linear vs volumetric measurement, and tumor size. CONCLUSIONS: HFUS and 3D photography demonstrate excellent reliability whereas digital calipers have good to excellent reliability in measuring cNF. The MDD for each technique was used to create tables of proposed thresholds for investigators to use as guides for clinical trials focused on cNF size. These criteria should be updated as the performance of these end points is evaluated.

Imaging Evaluation of Plexiform Neurofibromas in Neurofibromatosis Type 1: A Survey-Based Assessment.

OBJECTIVE: To assess imaging utilization practices across clinical specialists in neurofibromatosis type 1 (NF1) for the evaluation of symptomatic and asymptomatic children and adults with or without plexiform neurofibromas (PN). METHODS: An institutional review board-exempt survey was administered to medical practitioners caring for individuals with NF1 at the Response Evaluation in Neurofibromatosis and Schwannomatosis (REiNS) meeting in September 2019. The survey included questions on respondent demographic data (9 questions), type of imaging obtained for asymptomatic (4 questions) and symptomatic (4 questions) people with and without PN, and utilization of diffusion-weighted imaging (2 questions). RESULTS: Thirty practitioners participated in the survey. Most were academic neuro-oncologists at high-volume (>10 patients/week) NF1 centers. Of 30 respondents, 26 had access to whole-body MRI (WB-MRI). The most common approach to an asymptomatic person without PN was no imaging (adults: 57% [17/30]; children: 50% [15/30]), followed by a screening WB-MRI (adults: 20% [6/30]; children: 26.7% [8/30]). The most common approach to a person with symptoms or known PN was regional MRI (adults: 90% [27/30]; children: 93% [28/30]), followed by WB-MRI (adults: 20% [6/30]; children: 36.7% [11/30]). WB-MRI was most often obtained to evaluate a symptomatic child with PN (37% [11/30]). CONCLUSIONS: More than 90% of practitioners indicated they would obtain a regional MRI in a symptomatic patient without known or visible PN. Otherwise, there was little consensus on imaging practices. Given the high prevalence of PN and risk of malignant conversion in this patient population, there is a need to define imaging-based guidelines for optimal clinical care and the design of future clinical trials.

DeepNeuro: an open-source deep learning toolbox for neuroimaging.

Translating deep learning research from theory into clinical practice has unique challenges, specifically in the field of neuroimaging. In this paper, we present DeepNeuro, a Python-based deep learning framework that puts deep neural networks for neuroimaging into practical usage with a minimum of friction during implementation. We show how this framework can be used to design deep learning pipelines that can load and preprocess data, design and train various neural network architectures, and evaluate and visualize the results of trained networks on evaluation data. We present a way of reproducibly packaging data pre- and postprocessing functions common in the neuroimaging community, which facilitates consistent performance of networks across variable users, institutions, and scanners. We show how deep learning pipelines created with DeepNeuro can be concisely packaged into shareable Docker and Singularity containers with user-friendly command-line interfaces.

Imaging of Central Nervous System Tumors Based on the 2016 World Health Organization Classification.

The 2016 World Health Organization Classification of Tumors of the Central Nervous System (CNS) incorporated well-established molecular markers known to drive tumorigenesis and tumor behavior into the existing classification of CNS tumors based on histopathologic appearance. This integrated classification system has led to a major restructuring of the diffuse gliomas. In addition, it resulted in the categorization of medulloblastomas into four distinct molecular subgroups. Radiogenomic studies have revealed key imaging differences between certain genetic groups and may aid in the diagnosis, longitudinal assessment of treatment response, and evaluation of tumor recurrence in patients with brain tumors.

The Diagnosis and Management of Neurofibromatosis Type 1.

Neurofibromatosis type 1 (NF1), NF2, and schwannomatosis are related, but distinct, tumor suppressor syndromes characterized by a predilection for tumors in the central and peripheral nervous systems. NF1 is one of the most common autosomal dominant conditions of the nervous system. NF1 has a high degree of variability in clinical presentation, which may include multiple neoplasms as well as cutaneous, vascular, bony, and cognitive features. Some of these manifestations overlap with other genetic conditions. Accurate diagnosis of NF1 is important for individualizing clinical care and genetic counseling. This article summarizes the clinical features, diagnostic work-up, and management of NF1.

Automatic assessment of glioma burden: a deep learning algorithm for fully automated volumetric and bidimensional measurement.

BACKGROUND: Longitudinal measurement of glioma burden with MRI is the basis for treatment response assessment. In this study, we developed a deep learning algorithm that automatically segments abnormal fluid attenuated inversion recovery (FLAIR) hyperintensity and contrast-enhancing tumor, quantitating tumor volumes as well as the product of maximum bidimensional diameters according to the Response Assessment in Neuro-Oncology (RANO) criteria (AutoRANO). METHODS: Two cohorts of patients were used for this study. One consisted of 843 preoperative MRIs from 843 patients with low- or high-grade gliomas from 4 institutions and the second consisted of 713 longitudinal postoperative MRI visits from 54 patients with newly diagnosed glioblastomas (each with 2 pretreatment "baseline" MRIs) from 1 institution. RESULTS: The automatically generated FLAIR hyperintensity volume, contrast-enhancing tumor volume, and AutoRANO were highly repeatable for the double-baseline visits, with an intraclass correlation coefficient (ICC) of 0.986, 0.991, and 0.977, respectively, on the cohort of postoperative GBM patients. Furthermore, there was high agreement between manually and automatically measured tumor volumes, with ICC values of 0.915, 0.924, and 0.965 for preoperative FLAIR hyperintensity, postoperative FLAIR hyperintensity, and postoperative contrast-enhancing tumor volumes, respectively. Lastly, the ICCs for comparing manually and automatically derived longitudinal changes in tumor burden were 0.917, 0.966, and 0.850 for FLAIR hyperintensity volume, contrast-enhancing tumor volume, and RANO measures, respectively. CONCLUSIONS: Our automated algorithm demonstrates potential utility for evaluating tumor burden in complex posttreatment settings, although further validation in multicenter clinical trials will be needed prior to widespread implementation.

Publisher Correction: Probing tumor microenvironment in patients with newly diagnosed glioblastoma during chemoradiation and adjuvant temozolomide with functional MRI.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Wide Range of Clinical Outcomes in Patients with Gliomatosis Cerebri Growth Pattern: A Clinical, Radiographic, and Histopathologic Study.

BACKGROUND: The 2016 World Health Organization Classification of Central Nervous System Tumors categorizes gliomatosis cerebri growth pattern (GC) as a subgroup of diffuse infiltrating gliomas, defined by extent of brain involvement on magnetic resonance imaging (MRI). Clinical and radiographic features in GC patients are highly heterogeneous; however, prognosis has historically been considered poor. SUBJECTS, MATERIALS, AND METHODS: We performed a retrospective search for patients at our institution meeting radiographic criteria of primary, type I GC (defined as diffuse tumor infiltration without associated tumor mass and contrast enhancement on MRI) and analyzed their clinical, imaging, and histopathologic features. RESULTS: A total of 34 patients met radiographic criteria of primary, type I GC, and 33 had a confirmed histologic diagnosis of an infiltrating glial neoplasm. Age >47 years at diagnosis was associated with worse overall survival (OS) compared with age ≤47 years (hazard ratio [HR] 1.04, 95% confidence interval [CI] 1.01-1.07, p = .003). Patients with grade 2 tumors demonstrated a trend for improved OS compared with those with grade 3 tumors (HR 2.65, 95% CI 0.99-7.08, p = .051). Except for brainstem involvement, extent or location of radiographic involvement did not detectably affect clinical outcome. IDH mutation status identified a subgroup of GC patients with particularly long survival up to 25 years and was associated with longer time to progression (HR 4.81, 95% CI 0.99-23.47, p = .052). CONCLUSION: Patients with primary, type I GC do not uniformly carry a poor prognosis, even in the presence of widespread radiographic involvement. Consistent with other reports, IDH mutation status may identify patients with improved clinical outcome. Molecular characterization, rather than MRI features, may be most valuable for prognostication and management of GC patients. IMPLICATIONS FOR PRACTICE: Patients with gliomatosis cerebri growth pattern (GC) constitute a challenge to clinicians, given their wide range of clinical, histologic, and radiographic presentation, heterogeneous outcome patterns, and the lack of consensus on a standardized treatment approach. This study highlights that radiographic extent of disease-albeit category-defining-does not detectably influence survival and that IDH mutations may impact clinical outcome. Practicing oncologists should be aware that select GC patients may demonstrate exceptionally favorable survival times and prognosticate patients based on molecular markers, rather than imaging features alone.

Probing tumor microenvironment in patients with newly diagnosed glioblastoma during chemoradiation and adjuvant temozolomide with functional MRI.

Functional MRI may identify critical windows of opportunity for drug delivery and distinguish between early treatment responders and non-responders. Using diffusion-weighted, dynamic contrast-enhanced, and dynamic susceptibility contrast MRI, as well as pro-angiogenic and pro-inflammatory blood markers, we prospectively studied the physiologic tumor-related changes in fourteen newly diagnosed glioblastoma patients during standard therapy. 153 MRI scans and blood collection were performed before chemoradiation (baseline), weekly during chemoradiation (week 1-6), monthly before each cycle of adjuvant temozolomide (pre-C1-C6), and after cycle 6. The apparent diffusion coefficient, volume transfer coefficient (Ktrans), and relative cerebral blood volume (rCBV) and flow (rCBF) were calculated within the tumor and edema regions and compared to baseline. Cox regression analysis was used to assess the effect of clinical variables, imaging, and blood markers on progression-free (PFS) and overall survival (OS). After controlling for additional covariates, high baseline rCBV and rCBF within the edema region were associated with worse PFS (microvessel rCBF: HR = 7.849, p = 0.044; panvessel rCBV: HR = 3.763, p = 0.032; panvessel rCBF: HR = 3.984; p = 0.049). The same applied to high week 5 and pre-C1 Ktrans within the tumor region (week 5 Ktrans: HR = 1.038, p = 0.003; pre-C1 Ktrans: HR = 1.029, p = 0.004). Elevated week 6 VEGF levels were associated with worse OS (HR = 1.034; p = 0.004). Our findings suggest a role for rCBV and rCBF at baseline and Ktrans and VEGF levels during treatment as markers of response. Functional imaging changes can differ substantially between tumor and edema regions, highlighting the variable biologic and vascular state of tumor microenvironment during therapy.

The Role of Advanced Brain Tumor Imaging in the Care of Patients with Central Nervous System Malignancies.

OPINION STATEMENT: T1-weighted post-contrast and T2-weighted fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) constitute the gold standard for diagnosis and response assessment in neuro-oncologic patients but are limited in their ability to accurately reflect tumor biology and metabolism, particularly over the course of a patient's treatment. Advanced MR imaging methods are sensitized to different biophysical processes in tissue, including blood perfusion, tumor metabolism, and chemical composition of tissue, and provide more specific information on tissue physiology than standard MRI. This review provides an overview of the most common and emerging advanced imaging modalities in the field of brain tumor imaging and their applications in the care of neuro-oncologic patients.

Pharmacodynamics of mutant-IDH1 inhibitors in glioma patients probed by in vivo 3D MRS imaging of 2-hydroxyglutarate.

Inhibitors of the mutant isocitrate dehydrogenase 1 (IDH1) entered recently in clinical trials for glioma treatment. Mutant IDH1 produces high levels of 2-hydroxyglurate (2HG), thought to initiate oncogenesis through epigenetic modifications of gene expression. In this study, we show the initial evidence of the pharmacodynamics of a new mutant IDH1 inhibitor in glioma patients, using non-invasive 3D MR spectroscopic imaging of 2HG. Our results from a Phase 1 clinical trial indicate a rapid decrease of 2HG levels by 70% (CI 13%, P = 0.019) after 1 week of treatment. Importantly, inhibition of mutant IDH1 may lead to the reprogramming of tumor metabolism, suggested by simultaneous changes in glutathione, glutamine, glutamate, and lactate. An inverse correlation between metabolic changes and diffusion MRI indicates an effect on the tumor-cell density. We demonstrate a feasible radiopharmacodynamics approach to support the rapid clinical translation of rationally designed drugs targeting IDH1/2 mutations for personalized and precision medicine of glioma patients.

Clinical Relevance of Steroid Use in Neuro-Oncology.

BACKGROUND: Corticosteroids are commonly used in the management of primary central nervous system (CNS) tumors and CNS metastases to treat cancer- and treatment-related cerebral edema and improve neurologic function. However, they are also associated with significant morbidity and mortality, given their wide range of adverse effects. PURPOSE OF REVIEW: To review the mechanism of action, pharmacology, and toxicity profile of corticosteroids and to critically appraise the evidence that supports their use in neuro-oncologic practice based on the latest scientific and clinical data. RECENT FINDINGS: Recent data suggest that corticosteroids may negatively impact survival in glioma patients. In addition, corticosteroids should be incorporated as a standard criterion to assess a patient's clinical and radiographic response to treatment. Corticosteroids should be used judiciously in neuro-oncologic patients, given the potential deleterious effects on clinical outcome and patient survival. Anti-angiogenic agents, which lack these adverse effects, may be a reasonable alternative to corticosteroids.

Primary central nervous system lymphoma treated with high-dose methotrexate and rituximab: A single-institution experience.

Rituximab (RTX) improves the outcome in patients with systemic diffuse large B-cell lymphoma (DLBCL), but its benefit in primary central nervous system lymphoma (PCNSL) is unclear. In the present study, a single-institution retrospective analysis was performed for 12 patients with newly diagnosed PCNSL treated with combined high-dose methotrexate (HD-MTX) and RTX. MTX was administered biweekly at 8 g/m2/dose until a complete response (CR) was achieved or for a maximum of eight doses. RTX was provided for a total of eight weekly doses at 375 mg/m2/dose. Following a median of 11 cycles of MTX, the radiographic overall response rate was 91% and the CR rate was 58%. A CR was achieved after a median 6 cycles of MTX. The median progression-free survival time was 22 months and the median overall survival time has not yet been attained. These results compare favorably to single-agent HD-MTX and suggest a role for immunochemotherapy in the treatment of PCNSL.

Improvement in Visual Fields After Treatment of Intracranial Meningioma With Bevacizumab.

High-grade (World Health Organization [WHO] Grade II and III) meningiomas constitute a minority of all meningioma cases but are associated with significant morbidity and mortality, due to more aggressive tumor behavior and a tendency to recur despite standard therapy with resection and radiotherapy. They display a higher degree of vascularity than WHO Grade I meningiomas and produce angiogenic and growth factors, including vascular endothelial growth factor (VEGF). Bevacizumab, a humanized monoclonal antibody against VEGF-A, has been used in the treatment of recurrent or progressive meningiomas resistant to standard therapy. We report a patient with a recurrent left frontotemporal meningioma and associated-vision loss who experienced substantial visual field recovery after 3 cycles of bevacizumab. In addition, we provide a review of the literature regarding the efficacy of bevacizumab in the treatment of recurrent meningiomas.

Novel diagnostic approaches in Bing-Neel syndrome.

The central nervous system (CNS) manifestations of Waldenström's macroglobulinemia (WM) are known as the Bing-Neel syndrome (BNS). Patients with BNS can be classified into Group A and Group B based on the presence of lymphoplasmacytoid (LMP) cells within the brain parenchyma, leptomeninges, dura, and/or cerebrospinal fluid (CSF). To identify characteristic imaging findings for both Group A and Group B patients, we reviewed all 36 cases (26 referenced, 10 unreported) of proven WM with CNS symptoms, CSF analysis and/or biopsy, and magnetic resonance imaging (MRI) of the brain and/or spinal cord. Enhancement on MRI suggests invasion of the central neuraxis by LMP cells, and can help distinguish between Group A and Group B patients. In addition to differentiating true WM lesions in the CNS from ischemia, hyperviscosity events, and demyelinating lesions, evaluation of brain and spinal cord with gadolinium-enhanced MRI has the potential to guide management.