1H-MRS is useful to reinforce the suspicion of primary central nervous system lymphoma prior to surgery

Imaging of Lymphomas Involving the CNS: An Update-Review of the Full Spectrum of Disease with an Emphasis on the World Health Organization Classifications of CNS Tumors 2021 and Hematolymphoid Tumors 2022

Lymphomas of the CNS are the second most frequent primary brain malignancy in adults after gliomas. Presurgical suspicion of lymphoma greatly impacts patient management. The radiologic features of this tumor have been widely covered in the literature for decades, but under current classifications, mainly corresponding to the most common presentations of the most frequent type: primary diffuse large B-cell lymphoma of the CNS. Nevertheless, rarer presentations of this specific lymphoma and of other World Health Organization lymphoma subtypes with different imaging features are rarely treated. Moreover, important advances in imaging techniques, changing epidemiologic factors with relevant impact on these tumors (eg, immunodeficiency/dysregulation), and recent updates of the World Health Organization Classification of CNS Tumors 2021 and Hematolymphoid Tumors 2022 may have rendered some accepted concepts outdated. In this article, the authors aim to fulfill a critical need by providing a complete update-review, emphasizing the latest clinical-radiologic features of the full spectrum of lymphomas involving the CNS.

Radiomic-Based MRI for Classification of Solitary Brain Metastases Subtypes From Primary Lymphoma of the Central Nervous System

BACKGROUND

Differential diagnosis of brain metastases subtype and primary central nervous system lymphoma (PCNSL) is necessary for treatment decisions. The application of machine learning facilitates the classification of brain tumors, but prior investigations into primary lymphoma and brain metastases subtype classification have been limited.

PURPOSE

To develop a machine-learning model to classify PCNSL, brain metastases with primary lung and non-lung origin.

STUDY TYPE

Retrospective.

POPULATION

A total of 211 subjects with pathologically confirmed PCNSL or brain metastases (training cohort 168 and testing cohort 43).

FIELD STRENGTH/SEQUENCE

A 3.0 T axial contrast-enhanced T1-weighted spin-echo inversion recovery sequence (T1WI-CE), axial T2-weighted fluid-attenuation inversion recovery sequence (T2FLAIR) ASSESSMENT: Several machine-learning models (support vector machine, random forest, and K-nearest neighbors) were built with least absolute shrinkage and selection operator (LASSO) using features from T1WI-CE, T2FLAIR, and clinical. The model with the highest performance in the training cohort was selected to differentiate lesions in the testing cohort. Then, three radiologists conducted a two-round classification (with and without model reference) using images and clinical information from testing cohorts.

STATISTICAL TESTS

Five-fold cross-validation was used for model evaluation and calibration. Model performance was assessed based on sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC).

RESULTS

Twenty-five image features were selected by LASSO analysis. Random forest classifier was selected for its highest performance on the training set with an AUC of 0.73. After calibration, this model achieved an accuracy of 0.70 on the testing set. Accuracies of all three radiologists improved under model reference (0.49 vs. 0.70, 0.60 vs. 0.77, 0.58 vs. 0.72, respectively).

DATA CONCLUSION

The random forest model based on conventional MRI and clinical data can diagnose PCNSL and brain metastases subtypes (lung and non-lung origin). Model classification can help foster the diagnostic accuracy of specialists and streamline prognostication workflow.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 2.

Lymphomatosis cerebri: Multimodality imaging features and misdiagnosis analysis

Lymphomatosis cerebri (LC) is a significant challenge in terms of its clinical diagnosis due to it being a rare disease. The purpose of the present study was to investigate the multimodality imaging characteristics, clinical features and reasons for misdiagnosis of LC with the goal of potentially facilitating early and accurate diagnosis of this frequently misdiagnosed disease. In the present study, clinical data and cerebral multimodality imaging findings from 11 patients with LC proven based on pathology were retrospectively analyzed and reviewed with consultation of the literature. The results indicated that the common symptoms included cognitive decline (8/11), gait disturbance (9/11) and behavioral abnormalities (5/11). Cerebrospinal fluid analysis indicated that the number of cells and level of protein increased (8/10). All patients had both deep and lobar lesion distribution of bilateral cerebral white matter with equal or slightly low-density shadows on CT plain scan and slightly longer signals on T1- and T2-weighted MRI. Most of the lesions (9/11) exhibited isointensity or slight hyperintensity on diffusion-weighted imaging and hyperintensity on apparent diffusion coefficient maps. In addition, five patients presented with a marked decrease in N-acetylaspartate/creatine (Cr) and increase in choline/Cr on ¹H-magnetic resonance spectroscopy, including an increase in lipid/Cr in 3 cases. Of these, one case exhibited no increase in lesion metabolism and 2 cases had slightly increased uptake on positron emission tomography/CT. The present study indicated that the multimodality imaging findings of LC have certain distinct characteristics and prompt recognition of these features may significantly improve early diagnosis and patient prognosis. Misdiagnosis may be mainly due to insufficient understanding knowledge of the condition and improper brain biopsy.

Magnetic Resonance Imaging and Proton Magnetic Resonance Spectroscopy for Differentiating Between Enhanced Gliomas and Malignant Lymphomas

BACKGROUND

Although the treatment strategies for malignant lymphomas and gliomas differ, it is usually difficult to preoperatively distinguish between them. Magnetic resonance spectroscopy (MRS) was recently reported to be useful for preoperative diagnoses; however, MRS data analysis using LCModel, which is a quantitative and objective method, was performed in only a few of the existing reports.

METHODS

The clinical characteristics, conventional magnetic resonance imaging findings, and MRS parameters using LCModel were evaluated to identify the factors that can help distinguish between malignant lymphomas and enhanced gliomas.

RESULTS

In total, 59 cases were evaluated, including 13 cases of malignant lymphoma, 1 case of pilocytic astrocytoma, 5 cases of grade Ⅱ glioma, 5 cases of grade Ⅲ glioma, and 35 cases of glioblastoma. There was no correlation between clinical characteristics (sex and age) and diagnosis. Neither T1- nor T2-weighted image was useful for differentiation between the 2 forms of tumors, but the apparent diffusion coefficient minimum value was useful for distinguishing malignant lymphomas from gliomas, with an area under the curve (AUC) value of 0.852. MRS analysis using LCModel revealed differences in glutamate (Glu), N-acetylaspartate (NAA) + N-acetylaspartylglutamate (NAAG), Glu + glutamine, and Lipid (Lip) 13a + Lip13b between malignant lymphomas and gliomas. The largest AUC was 0.904, which was obtained for the Glu level, followed by 0.883 and 0.866 for NAA + NAAG and Lip13a + Lip13b, respectively.

CONCLUSIONS

Quantitative analysis of proton-MRS using LCModel is considered to be a valuable method for distinguishing between gliomas and malignant lymphomas.

The value of magnetic resonance spectroscopy as a supplement to MRI of the brain in a clinical setting

BACKGROUND

There are different opinions of the clinical value of MRS of the brain. In selected materials MRS has demonstrated good results for characterisation of both neoplastic and non-neoplastic lesions. The aim of this study was to evaluate the supplemental value of MR spectroscopy (MRS) in a clinical setting.

MATERIAL AND METHODS

MRI and MRS were re-evaluated in 208 cases with a clinically indicated MRS (cases with uncertain or insufficient information on MRI) and a confirmed diagnosis. Both single voxel spectroscopy (SVS) and chemical shift imaging (CSI) were performed in 105 cases, only SVS or CSI in 54 and 49 cases, respectively. Diagnoses were grouped into categories: non-neoplastic disease, low-grade tumour, and high-grade tumour. The clinical value of MRS was considered very beneficial if it provided the correct category or location when MRI did not, beneficial if it ruled out suspected diseases or was more specific than MRI, inconsequential if it provided the same level of information, or misleading if it provided less or incorrect information.

RESULTS

There were 70 non-neoplastic lesions, 43 low-grade tumours, and 95 high-grade tumours. For MRI, the category was correct in 130 cases (62%), indeterminate in 39 cases (19%), and incorrect in 39 cases (19%). Supplemented with MRS, 134 cases (64%) were correct, 23 cases (11%) indeterminate, and 51 (25%) incorrect. Additional information from MRS was beneficial or very beneficial in 31 cases (15%) and misleading in 36 cases (17%).

CONCLUSION

In most cases MRS did not add to the diagnostic value of MRI. In selected cases, MRS may be a valuable supplement to MRI.

Management of primary central nervous system lymphoma

A rare tumor, primary central nervous system lymphoma can affect immunocompetent and immunocompromised patients. While sensitive to radiotherapy or chemotherapy crossing the blood-brain barrier, it often recurs. Modern treatment consists of high-dose methotrexate-based induction chemotherapy, often followed by consolidation with either radiotherapy or further chemotherapy. Neurotoxicity is however a concern with radiotherapy, especially for patients older than 60 years. The benefit of the addition of rituximab to chemotherapy is unclear. Targeted therapies and immunotherapy have been effective in some patients and are tested on a larger scale. Survival has improved in the last decade, but remains poor in older patients.

Glioma imaging in Europe: A survey of 220 centres and recommendations for best clinical practice

Objectives

At a European Society of Neuroradiology (ESNR) Annual Meeting 2015 workshop, commonalities in practice, current controversies and technical hurdles in glioma MRI were discussed. We aimed to formulate guidance on MRI of glioma and determine its feasibility, by seeking information on glioma imaging practices from the European Neuroradiology community.

Methods

Invitations to a structured survey were emailed to ESNR members (n=1,662) and associates (n=6,400), European national radiologists’ societies and distributed via social media.

Results

Responses were received from 220 institutions (59% academic). Conventional imaging protocols generally include T2w, T2-FLAIR, DWI, and pre- and post-contrast T1w. Perfusion MRI is used widely (85.5%), while spectroscopy seems reserved for specific indications. Reasons for omitting advanced imaging modalities include lack of facility/software, time constraints and no requests. Early postoperative MRI is routinely carried out by 74% within 24–72 h, but only 17% report a percent measure of resection. For follow-up, most sites (60%) issue qualitative reports, while 27% report an assessment according to the RANO criteria. A minority of sites use a reporting template (23%).

Conclusion

Clinical best practice recommendations for glioma imaging assessment are proposed and the current role of advanced MRI modalities in routine use is addressed.

Key Points

• We recommend the EORTC-NBTS protocol as the clinical standard glioma protocol.

• Perfusion MRI is recommended for diagnosis and follow-up of glioma.

• Use of advanced imaging could be promoted with increased education activities.

• Most response assessment is currently performed qualitatively.

• Reporting templates are not widely used, and could facilitate standardisation.

Electronic supplementary material

The online version of this article (10.1007/s00330-018-5314-5) contains supplementary material, which is available to authorized users.

Lymphomatosis cerebri: a rare variant of primary central nervous system lymphoma and MR imaging features

BACKGROUND

Lymphomatosis cerebri (LC) is a rare variant of primary central nervous system lymphoma (PCNSL), characterized by diffuse infiltration without the formation of a discrete mass. The diagnosis of LC is a challenge because the imaging findings are atypical for lymphoma. The purpose of present study is to investigate MRI characteristics and clinical features of LC and potentially facilitate an early and accurate diagnosis of this often-missed disease.

METHODS

Seven patients (average 44 years, 19-58 years) with LC proved basing on MRI and histology were retrospectively reviewed the clinical data and cerebral MR imaging findings.

RESULTS

The common presenting symptoms were cognitive decline, behavioral disturbance, gait disturbance. All patients had both deep and lobar lesion distribution, and two of them had infratentorial involvement. Lack of contrast enhancement and subtle patchy enhanced pattern were observed in two and three patients, respectively. The remaining two patients presented multiple patchy enhancement. Most of the lesions were slightly hyperintense to normal brain on DWI as well as hyperintense on ADC maps. Three patients presented a pattern of marked decrease of NAA/Cr, increase of Cho/Cr, and two of the three cases showed increased Lip/Cr and Lac/Cr on MRS.

CONCLUSIONS

We conclude that diffuse bilateral lesions especially in deep and lobar region including white and gray matter, without enhancement or with patchy enhancement, marked decrease of NAA/Cr and increase of Cho/Cr, and increased Lip/Cr and Lac/Cr are suggestive of LC. Prompt recognition of these imaging patterns may lead to early diagnosis of LC and brain biopsy with improved prognosis.

Multiparametric Imaging Analysis: Magnetic Resonance Spectroscopy

Magnetic resonance spectroscopy (MRS) is a magnetic resonance-based imaging modality that allows noninvasive sampling of metabolic changes in normal and abnormal brain parenchyma. MRS is particularly useful in the differentiation of developmental or non-neoplastic disorders from neoplastic processes. MRS is also useful during routine imaging follow-up after radiation treatment or during antiangiogenic treatment and for predicting outcomes and treatment response. The objective of this article is to provide a concise but thorough review of the basic physical principles, important applications of MRS in brain tumor imaging, and future directions.