Performance of Apparent Diffusion Coefficient Values and Conventional MRI Features in Differentiating Tumefactive Demyelinating Lesions From Primary Brain Neoplasms

MRI-Based Machine Learning Fusion Models to Distinguish Encephalitis and Gliomas

This paper aims to compare the performance of the classical machine learning (CML) model and the deep learning (DL) model, and to assess the effectiveness of utilizing fusion radiomics from both CML and DL in distinguishing encephalitis from glioma in atypical cases. We analysed the axial FLAIR images of preoperative MRI in 116 patients pathologically confirmed as gliomas and clinically diagnosed with encephalitis. The 3 CML models (logistic regression (LR), support vector machine (SVM) and multi-layer perceptron (MLP)), 3 DL models (DenseNet 121, ResNet 50 and ResNet 18) and a deep learning radiomic (DLR) model were established, respectively. The area under the receiver operating curve (AUC) and sensitivity, specificity, accuracy, negative predictive value (NPV) and positive predictive value (PPV) were calculated for the training and validation sets. In addition, a deep learning radiomic nomogram (DLRN) and a web calculator were designed as a tool to aid clinical decision-making. The best DL model (ResNet50) consistently outperformed the best CML model (LR). The DLR model had the best predictive performance, with AUC, sensitivity, specificity, accuracy, NPV and PPV of 0.879, 0.929, 0.800, 0.875, 0.867 and 0.889 in the validation sets, respectively. Calibration curve of DLR model shows good agreement between prediction and observation, and the decision curve analysis (DCA) indicated that the DLR model had higher overall net benefit than the other two models (ResNet50 and LR). Meanwhile, the DLRN and web calculator can provide dynamic assessments. Machine learning (ML) models have the potential to non-invasively differentiate between encephalitis and glioma in atypical cases. Furthermore, combining DL and CML techniques could enhance the performance of the ML models.

Tumefactive demyelinating disorders as stroke mimics: Description of cases and systematic review of the literature

BACKGROUND

tumefactive multiple sclerosis (TmMS) is a rare subtype of a demyelinating disease that develops over time. Cases of hyperacute presentations mimicking cerebrovascular disorders have been reported; however, detailed clinical and demographic data are lacking.

METHODS

this study aimed to systematically review the literature on tumefactive demyelinating disorders presenting as strokes. After screening the PubMed, PubMed Central, and Web of Science databases, 39 articles describing 41 patients were identified, including 2 historical patients from our center.

RESULTS

23 (53.4%) patients were diagnosed with multiple sclerosis variants (vMS), 17 (39.5%) with inflammatory demyelinating variants (vInf), and 3 with tumors; however, only 43.5% of cases were verified histologically. In subgroup analysis, vMS differed from vInf in several aspects. Inflammatory cerebral spinal fluid parameters, including pleocytosis, proteinorachia was more commonly observed in vInf [11 (64.7%) vs. 1 (5.2%), P = 0.001 and 13/17 (76.4%) vs. 6/23 (31.5%), P = 0.02] than that in vMS. Neurological deterioration and fatal outcomes were more commonly observed in vInf [13/17 (76.4%) vs. 7/23 (30.4%), P = 0.003, and 11/17 (64.7%) vs. 0/23 (0%), P = 0.0001] than that in vMS.

CONCLUSIONS

Clinicodemographic data might aid in recognizing different subtypes of TmMS and warrant consideration of unconventional therapies because outcomes may be poor in the vInf of TmMS.

Clinical spectrum and prognosis of pathologically confirmed atypical tumefactive demyelinating lesions

To describe the clinical spectrum and prognosis of atypical tumefactive demyelinating lesions (TDLs), which were confirmed by pathology. A total of 11 patients were diagnosed with atypical TDLs confirmed by brain biopsy and surgery between January 2006 and December 2017. The clinical spectrum and prognosis in these patients were analyzed. The patients' ages ranged from 29 to 62 years, with a mean age of 48.9 years; 72.7% were males. The Expanded Disability Status Scale (EDSS) of the patients with first onset was 2.36. Most of the patients started with limb numbness and weakness (45.5%) or alalia (27.2%). The mean time from symptom onset to biopsy or surgery was 12.9 days (3-30 days). Most of the patients had solitary lesions (72.7%), supratentorial lesions (90.9%, particularly predominant in the frontal, temporal, and parietal lobes), moderate edema (63.6%), mild mass effect (54.5%), and patchy lesions (54.5%). Among them, three patients were positive for myelin basic protein (MBP) and one patient was positive for myelin oligodendrocyte glycoprotein (MOG). The patients were followed up for an average of 6.9 years (2-14 years), and recurrent TDLs were observed in 2 patients. Except for the 2 patients who relapsed, only 1 of the 9 patients died; the other 8 patients improved or maintained the status quo (the EDSS scores were lower or unchanged). The patients did not have any serious nervous system injury at onset, and the main presentation included extremity weakness, headache or dizziness, and alalia. The most common form was patchy on MRI enhancement. Cerebrospinal fluid and demyelination test can be an indicator of TDLs, and seizures may be a poor prognostic indicator. Most atypical TDLs have monophasic courses and good outcomes. The effect of neurosurgery alone was good in our group, and the effect of surgery on atypical TDLs can be further studied.

A rare case report of primary uterine and vaginal lymphoma in the elderly

Uterine lymphoma is rare and usually occurs in middle-aged women. The clinical symptoms lack any specific characteristics. Imaging characteristics usually include uterine enlargement with density and uniform signal soft tissue masses. Magnetic resonance T2 weighted imaging, enhanced scanning, diffusion weighted imaging and apparent diffusion coefficient values have certain characteristics. The gold standard for diagnosis remains a pathological examination of a biopsy specimen. The special feature of this current case was that the uterine lymphoma occurred in an 83-year-old female patient that presented with a pelvic mass for more than 1 month. Based on the imaging findings, a primary uterine lymphoma was considered, but her advanced age of onset did not match the disease. After pathological confirmation, the patient was diagnosed with uterine lymphoma and she received eight cycles of R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, prednisolone) plus local radiotherapy for the large masses. The patients achieved good results. Follow-up enhanced computed tomography imaging showed that the uterine volume had significantly reduced compared with before treatment. The diagnosis of elderly patients with uterine lymphoma can provide a more accurate plan for subsequent treatment.

Contribution of advanced neuro-imaging (MR diffusion, perfusion and proton spectroscopy) in differentiation between low grade gliomas GII and MR morphologically similar non neoplastic lesions

Background

Non-neoplastic brain lesions can be misdiagnosed as low-grade gliomas. Conventional magnetic resonance (MR) imaging may be non-specific. Additional imaging modalities such as spectroscopy (MRS), perfusion and diffusion imaging aid in diagnosis of such lesions. However, contradictory and overlapping results are still present. Hence, our purpose was to evaluate the role of advanced neuro-imaging in differentiation between low-grade gliomas (WHO grade II) and MR morphologically similar non-neoplastic lesions and to prove which modality has the most accurate results in differentiation.

Results

All patients were classified into two main groups: patients with low-grade glioma (n = 12; mean age, 38.8 ± 16; 8 males) and patients with non-neoplastic lesions (n = 27; mean age, 36.6 ± 15; 19 males) based on the histopathological and clinical–radiological diagnosis. Using ROC curve analysis, a threshold value of 0.93 for rCBV (AUC = 0.875, PPV = 92%, NPV = 71.4%) and a threshold value of 2.5 for Cho/NAA (AUC = 0.829, PPV = 92%, NPV = 71.4%) had 85.2% sensitivity and 83.3% specificity for predicting neoplastic lesions. The area under the curve (AUC) of ROC analysis was good for relative cerebral blood volume (rCBV) and Cho/NAA ratios (> 0.80) and fair for Cho/Cr and NAA/Cr ratios (0.70–0.80). When the rCBV measurements were combined with MRS ratios, significant improvement was observed in the area under the curve (AUC) (0.969) with improved diagnostic accuracy (89.7%) and sensitivity (88.9%).

Conclusions

Evaluation of rCBV and metabolite ratios at MRS, particularly Cho/NAA ratio, may be helpful in differentiating low-grade gliomas from non-neoplastic lesions. The combination of dynamic susceptibility contrast (DSC) perfusion and MRS can significantly improve the diagnostic accuracy and can help avoiding the need for an invasive biopsy.

Tumefactive multiple sclerosis versus high grade glioma: A diagnostic dilemma

Background:

Tumefactive demyelinating lesions (TDL) share similar clinical features and magnetic resonance imaging (MRI) characteristics with high grade glioma (HGG). This study develops an approach to navigating this diagnostic dilemma, with significant treatment implications as the management of both entities is drastically different.

Methods:

A retrospective analysis of 41 TDLs and 91 HGG with respect to demographics, presentation and classical MRI characteristics was performed. A diagnostic pathway was then developed to help diagnose TDLs based on whole neuraxis MRI and cerebrospinal fluid (CSF) examination.

Results:

The diagnosis of TDL is more likely than HGG in younger females who present with subacute or chronic symptoms. MRI characteristics favoring TDL over HGG include smaller size, open rim enhancement, little or no associated edema or mass effect and the presence of a T2 hypointense rim. MRI of the whole neuraxis for detection of other lesions typical of multiple sclerosis (MS), in combination with a lumbar puncture (LP) showing positive CSF-specific oligoclonal bands (OCB), was positive in 90% of the TDL cohort.

Conclusion:

The diagnostic pathway, proposed on the basis of specific clinicoradiological features, should be followed in patients with suspected TDL. If MRI demonstrates other lesions typical of MS and LP demonstrates positive CSF-specific OCBs, then patients should undergo a short course of IV steroids to look for clinical improvement. Patients, who continue to deteriorate, do not demonstrate other lesions on MRI or where the LP is negative for CSF-specific OCB, should be considered for biopsy if safe to do so. This pathway will give the patients the best chance at neurological preservation.

Clinical applications of diffusion-weighted sequence in brain imaging: beyond stroke

Diffusion-weighted imaging (DWI) is a well-established MRI sequence for diagnosing early stroke and provides therapeutic implications. However, DWI yields pertinent information in various other brain pathologies and helps establish a specific diagnosis and management of other central nervous system disorders. Some of these conditions can present with acute changes in neurological status and mimic stroke. This review will focus briefly on diffusion imaging techniques, followed by a more comprehensive description of the utility of DWI in common neurological entities beyond stroke.

Deep Learning With Data Enhancement for the Differentiation of Solitary and Multiple Cerebral Glioblastoma, Lymphoma, and Tumefactive Demyelinating Lesion

Objectives

To explore the MRI-based differential diagnosis of deep learning with data enhancement for cerebral glioblastoma (GBM), primary central nervous system lymphoma (PCNSL), and tumefactive demyelinating lesion (TDL).

Materials and Methods

This retrospective study analyzed the MRI data of 261 patients with pathologically diagnosed solitary and multiple cerebral GBM (n = 97), PCNSL (n = 92), and TDL (n = 72). The 3D segmentation model was trained to capture the lesion. Different enhancement data were generated by changing the pixel ratio of the lesion and non-lesion areas. The 3D classification network was trained by using the enhancement data. The accuracy, sensitivity, specificity, and area under the curve (AUC) were used to assess the value of different enhancement data on the discrimination performance. These results were then compared with the neuroradiologists’ diagnoses.

Results

The diagnostic performance fluctuated with the ratio of lesion to non-lesion area changed. The diagnostic performance was best when the ratio was 1.5. The AUCs of GBM, PCNSL, and TDL were 1.00 (95% confidence interval [CI]: 1.000–1.000), 0.96 (95% CI: 0.923–1.000), and 0.954 (95% CI: 0.904–1.000), respectively.

Conclusions

Deep learning with data enhancement is useful for the accurate identification of GBM, PCNSL, and TDL, and its diagnostic performance is better than that of the neuroradiologists.

Tumefactive demyelination: updated perspectives on diagnosis and management

INTRODUCTION

Tumefactive demyelination (TD) can be a challenging scenario for clinicians due to difficulties distinguishing it from other conditions, such as neoplasm or infection; or with managing the consequences of acute lesions, and then deciding upon the most appropriate longer term treatment strategy.

AREAS COVERED

The authors review the literature regarding TD covering its clinic-radiological features, association with multiple sclerosis (MS), and its differential diagnosis with other neuroinflammatory and non-inflammatory mimicking disorders with an emphasis on atypical forms of demyelination including acute disseminated encephalomyelitis (ADEM), MOG antibody-associated demyelination (MOGAD) and neuromyelitis spectrum disorders (NMOSD). We also review the latest in the acute and long-term treatment of TD.

EXPERT OPINION

It is important that the underlying cause of TD be determined whenever possible to guide the management approach which differs between different demyelinating and other inflammatory conditions. Improved neuroimaging and advances in serum and CSF biomarkers should one day allow early and accurate diagnosis of TD leading to better outcomes for patients.

A Review of Clinical and Imaging Findings in Tumefactive Demyelination

OBJECTIVE. Tumefactive demyelination mimics primary brain neoplasms on imaging, often necessitating brain biopsy. This article reviews the literature for the clinical and radiologic findings of tumefactive demyelination in various disease processes to facilitate identification of tumefactive demyelination on imaging. CONCLUSION. Both clinical and radiologic findings must be integrated to distinguish tumefactive demyelinating lesions from similarly appearing lesions on imaging. Further research on the immunopathogenesis of tumefactive demyelination and associated conditions will elucidate their interrelationship.

Tumefactive multiple sclerosis versus high-grade glioma: A diagnostic dilemma

Background:

Tumefactive demyelinating lesions (TDLs) share similar clinical features and MRI characteristics with high-grade glioma (HGG). This study develops an approach to navigating this diagnostic dilemma, with significant treatment implications as the management of both entities is drastically different.

Methods:

A retrospective analysis of 41 TDLs and 91 HGG with respect to demographics, presentation, and classical MRI characteristics was performed. A diagnostic pathway was then developed to help diagnose TDLs based on whole neuraxis MRI and cerebrospinal fluid (CSF) examination.

Results:

The diagnosis of TDL is more likely than HGG in younger females who present with subacute or chronic symptoms. MRI characteristics favoring TDL over HGG include smaller size, open rim enhancement, little or no associated edema or mass effect, and the presence of a T2 hypointense rim. MRI of the whole neuraxis for detection of other lesions typical of multiple sclerosis (MS), in combination with a lumbar puncture (LP) showing positive CSF-specific oligoclonal bands (OCB), was positive in 90% of the TDL cohort.

Conclusion:

The diagnostic pathway, proposed on the basis of specific clinicoradiological features, should be followed in patients with suspected TDL. If MRI demonstrates other lesions typical of MS and LP demonstrates positive CSF-specific OCBs, then patients should undergo a short course of IV steroids to look for clinical improvement. Patients who continue to deteriorate, do not demonstrate other lesions on MRI or where the LP is negative for CSF-specific OCB, should be considered for biopsy if safe to do so. This pathway will give the patients the best chance at neurological preservation.

Intracranial Abnormalities with Diffusion Restriction

Multiple pathologic conditions can cause changes in the random movement of water, which can be detected with diffusion-weighted imaging (DWI). DWI plays a powerful clinical role in detecting restricted diffusion associated with acute brain infarction. Other disorders can also result in restricted diffusion. This article focuses on showing examples of common and uncommon disorders that have restricted diffusion secondary to cytotoxic and/or intramyelinic edema. These disorders include ischemia, infection, noninfectious demyelinating diseases, genetic mutations affecting metabolism, acquired metabolic disorders, toxic or drug exposures, neoplasms and tumorlike lesions, radiation treatment, trauma, and denervation.

Differential imaging of atypical demyelinating lesions of the central nervous system

The detection of atypical and sometimes aggressive or tumefactive demyelinating lesions of the central nervous system often poses difficulties in the differential diagnosis. The clinical presentation is generally aspecific, related to the location and similar to a number of different lesions, including neoplasms and other intracranial lesions with mass effect. CSF analysis may also be inconclusive, especially for lesions presenting as a single mass at onset. As a consequence, a brain biopsy is frequently performed for characterization. Advanced MRI imaging plays an important role in directing the diagnosis, reducing the rate of unnecessary biopsies and allowing a prompt start of therapy that is often crucial, especially in the case of infratentorial lesions. In this review, the main pattern of presentation of atypical inflammatory demyelinating diseases is discussed, with particular attention on the differential diagnosis and how to adequately define the correct etiology.

Distinguishing brain inflammation from grade II glioma in population without contrast enhancement: a radiomics analysis based on conventional MRI

PURPOSE

In populations without contrast enhancement, the imaging features of atypical brain parenchyma inflammations can mimic those of grade II gliomas. The aim of this study was to assess the value of the conventional MR-based radiomics signature in differentiating brain inflammation from grade II glioma.

METHODS

Fifty-seven patients (39 patients with grade II glioma and 18 patients with inflammation) were divided into primary (n = 44) and validation cohorts (n = 13). Radiomics features were extracted from T₁-weighted images (T₁WI) and T₂-weighted images (T₂WI). Two-sample t-test and least absolute shrinkage and selection operator (LASSO) regression were adopted to select features and build radiomics signature models for discriminating inflammation from glioma. The predictive performance of the models was evaluated via area under the receiver operating characteristic curve (AUC) and compared with the radiologists' assessments.

RESULTS

Based on the primary cohort, we developed T₁WI, T₂WI and combination (T₁WI + T₂WI) models for differentiating inflammation from glioma with 4, 8, and 5 radiomics features, respectively. Among these models, T₂WI and combination models achieved better diagnostic efficacy, with AUC of 0.980, 0.988 in primary cohort and that of 0.950, 0.925 in validation cohort, respectively. The AUCs of radiologist 1's and 2's assessments were 0.661 and 0.722, respectively.

CONCLUSION

The signature based on radiomics features helps to differentiate inflammation from grade II glioma and improved performance compared with experienced radiologists, which could potentially be useful in clinical practice.

Review of Radiologic Considerations in an Immunocompetent Patient With Primary Central Nervous System Lymphoma

Primary central nervous system lymphoma is increasingly seen in immunocompetent patients and should be considered in any patient with multiple nervous system lesions.

Necrotic Primary Central Nervous System Lymphoma in an Immunocompetent Patient: A Case Report and Literature Review

Primary lymphoma that arises de novo from the central nervous system (CNS) is most commonly a non-Hodgkin's B-cell lymphoma and by definition lacks the presence of disease outside the CNS. It demonstrates a characteristic imaging appearance on computed tomography (CT) and magnetic resonance imaging (MRI) exams related to its inherent hypercellularity. On CT, primary CNS lymphoma (PCNSL) demonstrates a hyperdense appearance; on MRI, it commonly demonstrates restricted water diffusion on diffusion-weighted sequences and homogeneous enhancement on post-contrast sequences. We present a case of primary CNS lymphoma in an immunocompetent patient with progressive necrosis and loss of restricted diffusion on diffusion-weighted imaging (DWI) with an atypical enhancement pattern. We further provide a review of the literature regarding the CT and MRI appearance of primary CNS lymphoma and discuss the role of immune status in determining the imaging characteristics of this disease process.

MRI Findings in Tumefactive Demyelinating Lesions: A Systematic Review and Meta-Analysis

BACKGROUND

Accurate diagnosis of tumefactive demyelinating lesions is clinically important to avoid unnecessary invasive biopsy or inappropriate treatment.

PURPOSE

We aimed to evaluate conventional and advanced MR imaging findings of tumefactive demyelinating lesions and determine the diagnostic performance of MR imaging for differentiating tumefactive demyelinating lesions from primary brain tumor.

DATA SOURCES

A systematic search of Ovid MEDLINE and EMBASE up to December 6, 2017, was conducted.

STUDY SELECTION

Original articles describing MR imaging findings in patients with tumefactive demyelinating lesions were selected.

DATA ANALYSIS

The pooled incidences of conventional MR imaging findings of tumefactive demyelinating lesions were obtained with the DerSimonian and Liard random-effects model. The pooled sensitivity and specificity of MR imaging for differentiating tumefactive demyelinating lesions from primary brain tumor were obtained using the bivariate random-effects model.

DATA SYNTHESIS

Nineteen eligible studies with 476 patients with tumefactive demyelinating lesions were included. The pooled incidence of open ring or incomplete rim enhancement was 35% (95% CI, 24%-47%), which was significantly higher than the incidence of closed ring or complete rim enhancement (18% [95% CI, 11%-29%]; P = .0281). The pooled incidences of T2 hypointense rim, absent or mild mass effect, and absent or mild perilesional edema were 48%, 67%, and 57%, respectively. On advanced MR imaging, tumefactive demyelinating lesions showed a high apparent diffusion coefficient, peripheral restricted diffusion, and low cerebral blood volume. The pooled sensitivity and specificity of MR imaging for differentiating tumefactive demyelinating lesions from primary brain tumor were 89% (95% CI, 82%-93%) and 94% (95% CI, 89%-97%), respectively.

LIMITATIONS

Seventeen of 19 studies were retrospective studies.

CONCLUSIONS

Conventional MR imaging findings may help differentiate tumefactive demyelinating lesions from primary brain tumor, though further study is needed to determine the added value of advanced MR imaging.

Primary CNS Lymphomas: Challenges in Diagnosis and Monitoring

Primary Central Nervous System Lymphoma (PCNSL) is a rare neoplasm that can involve brain, eye, leptomeninges, and rarely spinal cord. PCNSL lesions most typically enhance homogeneously on T1-weighted magnetic resonance imaging (MRI) and appear T2-hypointense, but high variability in MRI features is commonly encountered. Neurological symptoms and MRI findings may mimic high grade gliomas (HGGs), tumefactive demyelinating lesions (TDLs), or infectious and granulomatous diseases. Advanced MRI techniques (MR diffusion, spectroscopy, and perfusion) and metabolic imaging, such as Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) or amino acid PET (usually employing methionine), may be useful in distinguishing these different entities and monitoring the disease course. Moreover, emerging data suggest a role for cerebrospinal fluid (CSF) markers in predicting prognosis and response to treatments. In this review, we will address the challenges in PCNSL diagnosis, assessment of response to treatments, and evaluation of potential neurotoxicity related to chemotherapy and radiotherapy.

Application value of CT and MRI in diagnosis of primary brain lymphoma

This study explored the correlation between computed tomography (CT) and magnetic resonance imaging (MRI) manifestations and pathological features of primary brain lymphoma to improve the diagnostic accuracy. A total of 230 patients with primary brain lymphoma admitted to People's Hospital of Rizhao from July, 2005 to December, 2016 were selected into the study and their clinical data were analyzed retrospectively. Among them, 87 patients were examined by CT, 74 patients by MRI, 69 patients by both MRI and CT. Features of MRI and CT scanning figures were observed with a focus on the density, number and margins of the lesions, and the diagnostic accuracy was analyzed. A total of 353 lesions were identified from 230 primary brain lymphoma patients, of which 224 were single lesions, and 129 were multiple lesions. Most lesions were on the upper curtain (81.3%, 187 cases) and 43 cases (18.7%) were on the lower curtain. Lesion signal of CT and MRI plain scan showed uniform state, and enhanced scan showed significantly enhanced signal. Diagnostic accuracy of CT was 82.8%, and sensitivity and specificity was 75.5 and 67.4%, respectively. Diagnostic accuracy of MRI was 83.8%, and sensitivity and specificity was 79.3 and 64.9%, respectively. Diagnostic accuracy of MRI combined with CT was 89.9%, and sensitivity and specificity was 86.3 and 75.8%, respectively. CT combined with MRI can provide better diagnosis for primary brain lymphoma compared with CT or MRI alone, but pathological test is still needed.

Pattern Recognition of the Multiple Sclerosis Syndrome

During recent decades, the autoimmune disease neuromyelitis optica spectrum disorder (NMOSD), once broadly classified under the umbrella of multiple sclerosis (MS), has been extended to include autoimmune inflammatory conditions of the central nervous system (CNS), which are now diagnosable with serum serological tests. These antibody-mediated inflammatory diseases of the CNS share a clinical presentation to MS. A number of practical learning points emerge in this review, which is geared toward the pattern recognition of optic neuritis, transverse myelitis, brainstem/cerebellar and hemispheric tumefactive demyelinating lesion (TDL)-associated MS, aquaporin-4-antibody and myelin oligodendrocyte glycoprotein (MOG)-antibody NMOSD, overlap syndrome, and some yet-to-be-defined/classified demyelinating disease, all unspecifically labeled under MS syndrome. The goal of this review is to increase clinicians’ awareness of the clinical nuances of the autoimmune conditions for MS and NMSOD, and to highlight highly suggestive patterns of clinical, paraclinical or imaging presentations in order to improve differentiation. With overlay in clinical manifestations between MS and NMOSD, magnetic resonance imaging (MRI) of the brain, orbits and spinal cord, serology, and most importantly, high index of suspicion based on pattern recognition, will help lead to the final diagnosis.

Clinical and imaging correlation in patients with pathologically confirmed tumefactive demyelinating lesions

OBJECTIVES

To characterize clinical and imaging features in patients with pathologically confirmed demyelinating lesions.

METHODS

In this retrospective chart review, we analyzed clinical-radiological-pathological correlations in patients >15years old who underwent brain biopsy at our institution between 2000 and 2015 and had inflammatory demyelination on neuropathology.

RESULTS

Of 31 patients, the mean age was 42years (range 16 to 69years) and 55% were female. All but one of the biopsied lesions were considered tumefactive demyelinating lesions (TDLs) by imaging criteria, measuring >2cm on contrast-enhanced brain MRI. On clinical follow-up, the final diagnosis was a CNS malignancy in 2 patients (6.5%). In patients without malignant tumor, the TDL was solitary in 12 (41%) and multifocal in 17 (59%), with contrast enhancement in all but one case, primarily in an incomplete rim enhancement pattern (75.9%). Of 16 patients with at least 12months of clinical follow-up, 7 (43.8%) had a clinical relapse. Of patients without a prior neurologic history, relapse occurred in 2/7 (29%) in solitary TDL and 2/6 (33%) in multifocal lesions at initial presentation. Recurrent TDLs occurred in 3 patients, all with initially solitary TDLs. Stratifying by CSF analysis, 4 of 6 patients (67%) with either an elevated IgG Index or >2 oligoclonal bands suffered a clinical relapse compared to 2/8 (25%) with non-inflammatory CSF.

CONCLUSIONS

Pathologically confirmed TDLs call for careful clinical correlation, clinical follow-up and imaging surveillance. Although sometimes clinically monophasic, tumefactive demyelinating lesions carried nearly a 45% risk of near-term clinical relapse in our study, even when presenting initially as a solitary mass lesion.

CSF and clinical data are useful in differentiating CNS inflammatory demyelinating disease from CNS lymphoma

Background:

It is often difficult to diagnose central nervous system (CNS) inflammatory demyelinating diseases (IDDs) because they are similar to CNS lymphoma and glioma.

Objective:

To evaluate whether cerebrospinal fluid (CSF) analysis can differentiate CNS IDDs from CNS lymphoma and glioma.

Methods:

We measured CSF cell counts; concentrations of proteins, glucose, interleukin (IL)-6, IL-10, soluble IL-2 receptor (sIL-2R), and myelin basic protein; and IgG index in patients with multiple sclerosis (MS, n = 64), neuromyelitis optica spectrum disorder (NMOSD, n = 35), tumefactive demyelinating lesion (TDL, n = 17), CNS lymphoma ( n = 12), or glioma ( n = 10). We detected diagnostic markers using logistic regression and receiver operating characteristic (ROC) analyses.

Results:

Median CSF IL-10 and sIL-2R levels were higher in CNS lymphoma patients than in MS, NMOSD, or TDL patients. Logistic regression revealed that CSF sIL-2R levels predicted CNS lymphoma. In the ROC analysis of CSF sIL-2R levels, the area under the curve was 0.867, and the sensitivity and specificity were 83.3% and 90.0%, respectively.

Conclusion:

CSF sIL-2R levels can be used to differentiate CNS lymphoma from CNS IDDs. Further studies may identify other applications of CSF as a diagnostic biomarker.

The Challenge of Primary Central Nervous System Lymphoma

Primary central nervous system (CNS) lymphoma is a challenging subtypes of aggressive non-Hodgkin lymphoma. Emerging clinical data suggest that optimized outcomes are achieved with dose-intensive CNS-penetrant chemotherapy and avoiding whole brain radiotherapy. Anti-CD20 antibody-based immunotherapy as a component of high-dose methotrexate-based induction programs may contribute to improved outcomes. An accumulation of insights into the molecular and cellular basis of disease pathogenesis is providing a foundation for the generation of molecular tools to facilitate diagnosis as well as a roadmap for integration of targeted therapy within the developing therapeutic armamentarium for this challenging brain tumor.

Synthetic MRI for Clinical Neuroimaging: Results of the Magnetic Resonance Image Compilation (MAGiC) Prospective, Multicenter, Multireader Trial

BACKGROUND AND PURPOSE

Synthetic MR imaging enables reconstruction of various image contrasts from 1 scan, reducing scan times and potentially providing novel information. This study is the first large, prospective comparison of synthetic-versus-conventional MR imaging for routine neuroimaging.

MATERIALS AND METHODS

A prospective multireader, multicase noninferiority trial of 1526 images read by 7 blinded neuroradiologists was performed with prospectively acquired synthetic and conventional brain MR imaging case-control pairs from 109 subjects (mean, 53.0 ± 18.5 years of age; range, 19-89 years of age) with neuroimaging indications. Each case included conventional T1- and T2-weighted, T1 and T2 FLAIR, and STIR and/or proton density and synthetic reconstructions from multiple-dynamic multiple-echo imaging. Images were randomized and independently assessed for diagnostic quality, morphologic legibility, radiologic findings indicative of diagnosis, and artifacts.

RESULTS

Clinical MR imaging studies revealed 46 healthy and 63 pathologic cases. Overall diagnostic quality of synthetic MR images was noninferior to conventional imaging on a 5-level Likert scale (P < .001; mean synthetic-conventional, -0.335 ± 0.352; Δ = 0.5; lower limit of the 95% CI, -0.402). Legibility of synthetic and conventional morphology agreed in >95%, except in the posterior limb of the internal capsule for T1, T1 FLAIR, and proton-density views (all, >80%). Synthetic T2 FLAIR had more pronounced artifacts, including +24.1% of cases with flow artifacts and +17.6% cases with white noise artifacts.

CONCLUSIONS

Overall synthetic MR imaging quality was similar to that of conventional proton-density, STIR, and T1- and T2-weighted contrast views across neurologic conditions. While artifacts were more common in synthetic T2 FLAIR, these were readily recognizable and did not mimic pathology but could necessitate additional conventional T2 FLAIR to confirm the diagnosis.

Combining Diffusion Tensor Metrics and DSC Perfusion Imaging: Can It Improve the Diagnostic Accuracy in Differentiating Tumefactive Demyelination from High-Grade Glioma?

BACKGROUND AND PURPOSE

Tumefactive demyelinating lesions with atypical features can mimic high-grade gliomas on conventional imaging sequences. The aim of this study was to assess the role of conventional imaging, DTI metrics (p:q tensor decomposition), and DSC perfusion in differentiating tumefactive demyelinating lesions and high-grade gliomas.

MATERIALS AND METHODS

Fourteen patients with tumefactive demyelinating lesions and 21 patients with high-grade gliomas underwent brain MR imaging with conventional, DTI, and DSC perfusion imaging. Imaging sequences were assessed for differentiation of the lesions. DTI metrics in the enhancing areas and perilesional hyperintensity were obtained by ROI analysis, and the relative CBV values in enhancing areas were calculated on DSC perfusion imaging.

RESULTS

Conventional imaging sequences had a sensitivity of 80.9% and specificity of 57.1% in differentiating high-grade gliomas (P = .049) from tumefactive demyelinating lesions. DTI metrics (p:q tensor decomposition) and DSC perfusion demonstrated a statistically significant difference in the mean values of ADC, the isotropic component of the diffusion tensor, the anisotropic component of the diffusion tensor, the total magnitude of the diffusion tensor, and rCBV among enhancing portions in tumefactive demyelinating lesions and high-grade gliomas (P ≤ .02), with the highest specificity for ADC, the anisotropic component of the diffusion tensor, and relative CBV (92.9%). Mean fractional anisotropy values showed no significant statistical difference between tumefactive demyelinating lesions and high-grade gliomas. The combination of DTI and DSC parameters improved the diagnostic accuracy (area under the curve = 0.901). Addition of a heterogeneous enhancement pattern to DTI and DSC parameters improved it further (area under the curve = 0.966). The sensitivity increased from 71.4% to 85.7% after the addition of the enhancement pattern.

CONCLUSIONS

DTI and DSC perfusion add profoundly to conventional imaging in differentiating tumefactive demyelinating lesions and high-grade gliomas. The combination of DTI metrics and DSC perfusion markedly improved diagnostic accuracy.

Marginal zone dural lymphoma: the Memorial Sloan Kettering Cancer Center and University of Miami experiences

Dural lymphoma (DL) is a rare type of primary CNS lymphoma arising from the dura mater. The optimal treatment is uncertain. A retrospective review was performed on 26 DL patients. Seventeen patients underwent resection and nine had a biopsy. Twenty three patients could be assessed for a response to treatment after surgery. Thirteen received focal radiotherapy (RT), six whole brain RT (WBRT), three chemotherapy alone and one chemotherapy followed by WBRT. Twenty two achieved complete response (CR) and one a partial response (PR). Four patients relapsed (two local and two systemic). Median follow up was 64 months, with median progression free survival (PFS) and OS not reached. Three year PFS was 89% (95% CI 0.64-0.97). All patients are alive at last follow-up, demonstrating that DL is an indolent tumor with long survival. CR is achievable with focal therapy in the majority of cases, but there is a risk for relapses and long-term follow-up is recommended.