Magnetic resonance texture analysis utility in differentiating intraparenchymal neurosarcoidosis from primary central nervous system lymphoma: a preliminary analysis

Beyond Glioma: The Utility of Radiomic Analysis for Non-Glial Intracranial Tumors

Simple Summary

Tumor qualities, such as growth rate, firmness, and intrusion into healthy tissue, can be very important for operation planning and further treatment. Radiomics is a promising new method that allows the determination of some of these qualities on images performed before surgery. In this article, we provide a review of the use of radiomics in various tumors of the central nervous system, such as metastases, lymphoma, meningioma, medulloblastoma, and pituitary tumors.

Abstract

The field of radiomics is rapidly expanding and gaining a valuable role in neuro-oncology. The possibilities related to the use of radiomic analysis, such as distinguishing types of malignancies, predicting tumor grade, determining the presence of particular molecular markers, consistency, therapy response, and prognosis, can considerably influence decision-making in medicine in the near future. Even though the main focus of radiomic analyses has been on glial CNS tumors, studies on other intracranial tumors have shown encouraging results. Therefore, as the main focus of this review, we performed an analysis of publications on PubMed and Web of Science databases, focusing on radiomics in CNS metastases, lymphoma, meningioma, medulloblastoma, and pituitary tumors.

Retrospective, dual-centre review of imaging findings in neurosarcoidosis at presentation: prevalence and imaging sub-types

AIM

To assess the prevalence of various imaging manifestations in neurosarcoidosis (NS) patients at presentation and to explore if specific imaging findings may cluster in different sub-groups.

MATERIALS AND METHODS

A retrospective, dual-institution, systematic imaging review was undertaken of the magnetic resonance imaging (MRI) findings in 100 consecutive NS patients who presented over a 15-year period. Clustering analysis (k-mode) was performed to evaluate co-occurrence of imaging findings.

RESULTS

Non-enhancing white matter (NEWM) lesions were the most common imaging abnormality (56%), followed by leptomeningeal (47%) and pachymeningeal (32%) involvement. Other common manifestations included cranial nerve involvement (30%), parenchymal granulomas (27%), hypothalamic-pituitary-adrenal axis involvement (26%), and hydrocephalus (14%). Additionally, a higher prevalence of perivascular enhancement (23%), cerebrovascular events (including ischaemic and haemorrhagic events; 17%), and ependymal involvement (20%) were noted than recognised previously. Additional k-mode analysis was performed to explore underlying disease sub-clusters. This was evaluated for clusters varying between two though five (k=2-5). For k=4, the analysis revealed that the imaging findings may possibly be divided into disease sub-sets of four groups, each with varying distribution of imaging manifestations and clinical manifestations.

CONCLUSION

Overall, NEWM lesions and meningeal involvement are the most common imaging manifestations of NS. The prevalence of perivascular enhancement, cerebrovascular events, and ependymal involvement is likely higher than reported previously. Additionally, different imaging findings in NS may cluster together and imaging subtypes in NS possibly exist.

MRI-based texture analysis to differentiate the most common parotid tumours

AIM

To evaluate magnetic resonance imaging (MRI) features and signal characteristics of parotid masses and investigate the added role of texture analysis (TA) in the differentiation of parotid tumours.

MATERIALS AND METHODS

Ninety-five patients (42 women, 53 men; mean age 51.67±14.15) were included in this study. The study group consisted of 40 pleomorphic adenoma, 45 Warthin's tumour, and 10 mucoepidermoid carcinomas. Two reviewers assessed the MRI sequences retrospectively. Fat-suppressed T2-weighted and contrast-enhanced T1-weighted axial images were used for TA. Receiver operating characteristic curve analyses were performed to evaluate the ability to make a diagnosis. Logistic regression analyses were conducted to explore the independent risk factors among the MRI features and to analyse the added value of TA to the qualitative analysis.

RESULTS

Significant differences were found in the tumour border (p<0.001), infiltration of the surrounding tissue (p=0.003), contrast-enhancement grading (p<0.001), perineural spread (p=0.013), and pathological lymph nodes (p<0.001) between the malignant and benign tumours. Kurtosis on contrast-enhanced T1-weighted images, and skewness and kurtosis on T2-weighted images were significantly different between the three groups (p=0.020, <0.001, 0.003; respectively). A kurtosis value on T2-weighted images <2.815 along with an ill-defined border had the highest specificity (98.8%) and positive predictive value (83.3%) in the differentiation of malignant tumours.

CONCLUSION

The addition of TA parameters to the MRI findings may contribute to distinguish benign from malignant parotid tumours.

Current status and quality of radiomics studies in lymphoma: a systematic review

OBJECTIVES

To perform a systematic review regarding the developments in the field of radiomics in lymphoma. To evaluate the quality of included articles by the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2), the phases classification criteria for image mining studies, and the radiomics quality scoring (RQS) tool.

METHODS

We searched for eligible articles in the MEDLINE/PubMed and EMBASE databases using the terms "radiomics", "texture" and "lymphoma". The included studies were divided into two categories: diagnosis-, therapy response- and outcome-related studies. The diagnosis-related studies were evaluated using the QUADAS-2; all studies were evaluated using the phases classification criteria for image mining studies and the RQS tool by two reviewers.

RESULTS

Forty-five studies were included; thirteen papers (28.9%) focused on the differential diagnosis of primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM). Thirty-two (71.1%) studies were classified as discovery science according to the phase classification criteria for image mining studies. The mean RQS score of all studies was 14.2% (ranging from 0.0 to 40.3%), and 23 studies (51.1%) were given a score of < 10%.

CONCLUSION

The radiomics features could serve as diagnostic and prognostic indicators in lymphoma. However, the current conclusions should be interpreted with caution due to the suboptimal quality of the studies. In order to introduce radiomics into lymphoma clinical settings, the lesion segmentation and selection, the influence of the pathological pattern and the extraction of multiple modalities and multiple time points features need to be further studied.

KEY POINTS

• The radiomics approach may provide useful information for diagnosis, prediction of the therapy response, and outcome of lymphoma. • The quality of published radiomics studies in lymphoma has been suboptimal to date. • More studies are needed to examine lesion selection and segmentation, the influence of pathological patterns, and the extraction of multiple modalities and multiple time point features.

Diffuse large B-cell lymphoma relapse presenting as extensive neurolymphomatosis

A 56-year-old woman with a history of diffuse large B-cell non-Hodgkin lymphoma (DLBCL-NHL) in remission for two years presented with weight loss and multifocal sensory/motor symptoms. Magnetic resonance imaging (MRI) of the neuraxis and whole-body FDG PET/CT led to a diagnosis of secondary neurolymphomatosis (NL). MRI demonstrated extensive thickening and enhancement of multiple cranial nerves and peripheral nerve plexuses with corresponding elevated metabolism on FDG PET/CT. Treatment with chemotherapy resulted in complete response on FDG PET/CT and subsequently she underwent autologous stem cell transplantation. NL is a rare manifestation of lymphoma affecting the peripheral nervous system. Nonspecific neuropathic symptoms make clinical diagnosis difficult. Though nerve biopsy is considered the gold standard, MRI and FDG PET/CT are accepted alternatives for making the diagnosis. We review imaging findings in NL, describe the differential diagnosis, and discuss the limitations of the imaging modalities.

Analysis of soluble interleukin-2 receptor as CSF biomarker for neurosarcoidosis

OBJECTIVE

To systematically analyze soluble interleukin-2 receptor (sIL-2R) in CSF as a diagnostic and disease activity biomarker in patients with sarcoidosis involving the CNS (neurosarcoidosis).

METHODS

sIL-2R was determined by chemiluminescent immunoassays in CSF/serum samples from patients with neurosarcoidosis (n = 23), MS (n = 19), neurotuberculosis (n = 8), viral (n = 18) and bacterial (n = 9) meningitis, cerebral lymphoma (n = 15), Guillain-Barré syndrome (n = 8), and 115 patients with noninflammatory neurologic diseases (NINDs) as controls. The sIL-2R index was calculated by dividing the CSF/serum sIL-2R quotient (Q_sIL-2R) through the CSF/serum albumin quotient (Q_Alb). sIL-2R quotient diagrams were established by plotting Q_sIL-2R against Q_Alb. sIL-2R levels were correlated with clinical, MRI, and CSF disease activity markers of neurosarcoidosis.

RESULTS

Patients with neurosarcoidosis had higher CSF sIL-2R, Q_sIL-2R, and sIL-2R index values than patients with NINDs (p < 0.0001 for all pairwise group comparisons). sIL-2R quotient diagrams demonstrated an intrathecal sIL-2R synthesis in >50% of neurosarcoidosis samples. Similar findings were observed in viral/bacterial meningitis, CNS lymphoma, and, most pronounced, in neurotuberculosis, but not in patients with MS. CSF sIL-2R parameters were associated with clinical disease activity, leptomeningeal gadolinium enhancement, and the CSF white cell count in patients with neurosarcoidosis.

CONCLUSIONS

CSF sIL-2R parameters are elevated in patients with neurosarcoidosis, but this finding is not specific for neurosarcoidosis. Nevertheless, CSF sIL-2R parameters may help distinguishing neurosarcoidosis from MS and are associated with clinical, radiologic, and CSF disease activity markers of neurosarcoidosis.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that CSF sIL-2R parameters distinguish neurosarcoidosis from NINDs and MS.

Predicting outcome in childhood diffuse midline gliomas using magnetic resonance imaging based texture analysis

BACKGROUND

Diffuse midline gliomas (DMG) are aggressive brain tumours, previously known as diffuse intrinsic pontine gliomas (DIPG), with 10% overall survival (OS) at 18 months. Predicting OS will help refine treatment strategy in this patient group. MRI based texture analysis (MRTA) is novel image analysis technique that provides objective information about spatial arrangement of MRI signal intensity (heterogeneity) and has potential to be imaging biomarker.

OBJECTIVES

To investigate MRTA in predicting OS in childhood DMG.

METHODS

Retrospective study of patients diagnosed with DMG, based on radiological features, treated at our institution 2007-2017. MRIs were acquired at diagnosis and 6 weeks after radiotherapy (54Gy in 30 fractions). MRTA was performed using commercial available TexRAD research software on T2W sequence and Apparent Diffusion Coefficient (ADC) maps encapsulating tumour in the largest single axial plane. MRTA comprised filtration-histogram technique using statistical and histogram metrics for quantification of texture. Kaplan-Meier survival analysis determined association of MRI texture parameters with OS.

RESULTS

In all, 32 children 2-14 years (median 7 years) were included. MRTA was undertaken on T2W (n=32) and ADC (n=22). T2W-MRTA parameters were better at prognosticating than ADC-MRTA. Children with homogenous tumour texture, at medium scale on diagnostic T2W MRI, had worse prognosis (Mean of Positive Pixels (MPP): P=0.005, mean: P=0.009, SD: P=0.011, kurtosis: P=0.037, entropy: P=0.042). Best predictor MPP was able to stratify patients into poor and good prognostic groups with median survival of 7.5 months versus 17.5 months, respectively.

CONCLUSIONS

DMG with more homogeneous texture on diagnostic MRI is associated with worse prognosis. Texture parameter MPP is the most predictive marker of OS in childhood DMG.