Primary central nervous system lymphoma MRI

Primary central nervous system lymphoma MRI

Reported signal characteristics include:

T1

Typically hypointense to grey matter

T1 C+ (Gd)

typical high-grade tumours show intense homogeneous enhancement while low-grade tumours have absent to moderate enhancement

Peripheral ring enhancement may be seen in immunocompromised patients (HIV/AIDS)

T2

Variable

Majority are iso to hypointense to grey matter

Isointense: 33%

Hypointense: 20% 9 – when present this is a helpful distinguishing feature

Hyperintense: 15-47%, more common in tumours with necrosis

DWI/ADC

Restricted diffusion with ADC values lower than normal brain, typically between 400 and 600 x 10-6 mm2/s (lower than high-grade gliomas and metastases)

A number of studies have suggested that the lower the ADC values of the tumour the poorer the response to tumour and higher likelihood of recurrence

AADC is particularly useful in assessing response to chemotherapy, with increases in ADC values to above those of normal brain predictive of complete response

MR spectroscopy

Large choline peak

Reversed choline/creatinine ratio

Markedly decreased NAA

Lactate peak may also be seen

MR perfusion

Only modest if any increase in rCBV (much less marked than in high-grade gliomas, where angiogenesis is a prominent feature).

Volume

Precise volumetric assessment of brain tumors is relevant for treatment planning and monitoring. However, manual segmentations are time-consuming and impeded by intra- and inter rater variabilities.

To investigate the performance of a deep learning model (DLM) to automatically detect and segment primary central nervous system lymphoma (PCNSL) on clinical MRI.

Study type: Retrospective.

Population: Sixty-nine scans (at initial and/or follow-up imaging) from 43 patients with PCNSL referred for clinical MRI tumor assessment.

Field strength/sequence: T1 weighted image -/T2 weighted image, T1 -weighted contrast-enhanced (T1 CE), and FLAIR at 1.0, 1.5, and 3.0T from different vendors and study centers.

Fully automated voxelwise segmentation of tumor components was performed using a 3D convolutional neural network (DeepMedic) trained on gliomas (n = 220). DLM segmentations were compared to manual segmentations performed in a 3D voxelwise manner by two readers (radiologist and neurosurgeon; consensus reading) from T1 CE and FLAIR, which served as the reference standard.

Statistical tests: Dice similarity coefficient (DSC) for comparison of spatial overlap with the reference standard, Pearson’s correlation coefficient ® to assess the relationship between volumetric measurements of segmentations, and Wilcoxon rank-sum test for comparison of DSCs obtained in initial and follow-up imaging.

The DLM detected 66 of 69 PCNSL, representing a sensitivity of 95.7%. Compared to the reference standard, DLM achieved good spatial overlap for total tumor volume (TTV, union of tumor volume in T1 CE and FLAIR; average size 77.16 ± 62.4 cm3 , median DSC: 0.76) and tumor core (contrast enhancing tumor in T1 CE; average size: 11.67 ± 13.88 cm3 , median DSC: 0.73). High volumetric correlation between automated and manual segmentations was observed (TTV: r = 0.88, P < 0.0001; core: r = 0.86, P < 0.0001). Performance of automated segmentations was comparable between pretreatment and follow-up scans without significant differences (TTV: P = 0.242, core: P = 0.177).

Data conclusion: In clinical MRI scans, a DLM initially trained on gliomas provides segmentation of PCNSL comparable to manual segmentation, despite its complex and multifaceted appearance. Segmentation performance was high in both initial and follow-up scans, suggesting its potential for application in longitudinal tumor imaging.

Level of evidence: 3 TECHNICAL EFFICACY STAGE: 2 1).

1)

Pennig L, Hoyer UCI, Goertz L, et al. Primary Central Nervous System Lymphoma: Clinical Evaluation of Automated Segmentation on Multiparametric MRI Using Deep Learning [published online ahead of print, 2020 Jul 13]. J Magn Reson Imaging. 2020;e27288. doi:10.1002/jmri.27288

Fungal Infections of the Central Nervous System Pathogens, Diagnosis, and Management

Fungal Infections of the Central Nervous System Pathogens, Diagnosis, and Management

by Mehmet Turgut (Editor), Sundaram Challa (Editor), Ali Akhaddar (Editor)

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This book provides comprehensive information on fungal infections of the central nervous system (CNS). Fungal infections are still a major public health challenge for most of the developing world and even for developed countries due to the rising numbers of immune compromised patients, refugee movements, and international travel. Although fungal infections involving the CNS are not particularly common, when they do occur, the results can be devastating in spite of recent advances and currently available therapies. Further, over the past several years, the incidence of these infections has seen a steep rise among immunodeficient patients. In this context, aggressive surgery remains the mainstay of management, but conservative antifungal drug treatment complemented by aggressive surgical debridement may be necessary. Yet the optimal management approach to fungal infections of the CNS remains controversial, owing to the limited individual experience and the variable clinical course of the conditions. Addressing that problem, this comprehensive book offers the ideal resource for neurosurgeons, neurologists and other specialists working with infectious diseases.

Primary central nervous system lymphoma diagnosis

Diagnosing central nervous system (CNS) lymphoma remains a challenge. Most patients have to undergo brain biopsy to obtain tissue for diagnosis, with associated risks of serious complications. Diagnostic markers in blood or cerebrospinal fluid (CSF) could facilitate early diagnosis with low complication rates.


In a retrospective study of patients with Primary central nervous system lymphoma (PCNSL) treated between January 2001 and December 2011 at the Navy General Hospital (Beijing). All included patients were pathologically diagnosed with PCNSL. Specimens were obtained by stereotactic biopsy and diagnosed by pathological examination. Serological panel had to be negative for HIV.

Out of the 118 patients, 73 (61.9%) were male and 45 (38.1%) were female. Median age was 54 (range 11-83) years. All patients had B cell lymphoma. The lesions showed slightly hyperdense shadows on computed tomography (CT) images, and mostly hyperintense T1 and iso- or hyperintense T2 signals on magnetic resonance imaging (MRI). Most lesions showed patchy enhancement after enhanced scanning, and some had the characteristic “butterfly sign” on enhanced MRI. The magnetic resonance spectroscopy of PCNSL manifested as increased Cho peak, moderately decreased NAA peak, and slightly decreased Cr peak. Positron emission tomography indicated high metabolism of 18F-FDG in PCNSL lesions.

MRI is important in the diagnosis of PCNSL. Understanding the imaging features of PCNSL will help improve its diagnosis in clinics 1).


van Westrhenen et al., performed a systematic review literature search for studies on markers in blood or cerebrospinal fluid for the diagnosis CNS lymphoma and assessed the methodological quality of studies with the Quality Assessment of Diagnostic Accuracy Studies tool (QUADAS-2).

They evaluated diagnostic value of the markers at a given threshold, as well as differences between mean or median levels in patients versus control groups. Twenty-five studies were included, reporting diagnostic value for 18 markers in CSF (microRNAs -21, -19b, and -92a, RNU2-1f, CXCL13, interleukins -6, -8, and -10, soluble interleukin-2-receptor, soluble CD19, soluble CD27, tumour necrosis factor-alfa, beta-2-microglobulin, antithrombin III, soluble transmembrane activator and calcium modulator and cyclophilin ligand interactor, soluble B cell maturation antigen, neopterin and osteopontin) and three markers in blood (microRNA-21 soluble CD27, and beta-2-microglobulin). All studies were at considerable risk of bias and there were concerns regarding the applicability of 15 studies. CXCL13, beta 2 microglobulin and neopterin have the highest potential in diagnosing CNS lymphoma, but further study is still needed before they can be used in clinical practice 2).

Radiographic features

The most helpful imaging pattern presents mainly in untreated non-immunocompromised patients is of a CT hyperdense avidly enhancing mass, with MRI T1 hypointense, T2 iso- to hypointense, vivid homogeneous gadolinium-enhancing lesion/s with restricted diffusion, subependymal extension, and crossing of the corpus callosum. Unfortunately, this pattern is not always present.

Typically PCNSL are supratentorial (75-85%) and appear as a mass or multiple masses (11-50%) that are usually in contact with the subarachnoid/ependymal surfaces. Crossing the corpus callosum is not infrequently seen. Enhancement on both CT and MRI is pronounced and usually homogeneous. Even with larger lesions, there is little mass effect for size and limited surrounding vasogenic oedema.

Low-grade tumours differ from the more common high-grade PCNSL in several ways:

Deep locations and spinal involvement is more common

Contrast enhancement is absent, irregular or only mild

Disseminated meningeal/intraventricular disease is uncommon, it is seen in ~5% (range 1-7%) of cases at presentation and usually in high-grade cases.

It should be noted that in patients who are immunocompromised (typically HIV/AIDS or post-transplant) appearances are more heterogeneous, including central non-enhancement/necrosis and haemorrhage, although the latter is still uncommon

CT

Most lesions are hyperattenuating (70%) 3

Shows enhancement

Haemorrhage is distinctly uncommon

There are often multiple lesions in patients with HIV/AIDS

MRI

Scintigraphy

Thallium 201

Shows increased uptake

C11 Methionine PET

Shows increased uptake 3).

Flow cytometry

Flow cytometry has a high specificity and can confirm the diagnosis of a lymphoma significantly faster than immunohistochemistry. This allows for rapid initiation of treatment in this highly aggressive tumor. However, since its sensitivity is less than 100%, van der Meulen et al., recommend to perform histology plus immunohistochemistry in parallel to flow cytometry 4).

References

1)

Cheng G, Zhang J. Imaging features (CT, MRI, MRS, and PET/CT) of primary central nervous system lymphoma in immunocompetent patients. Neurol Sci. 2018 Dec 22. doi: 10.1007/s10072-018-3669-7. [Epub ahead of print] PubMed PMID: 30580380.
2)

van Westrhenen A, Smidt LCA, Seute T, Nierkens S, Stork ACJ, Minnema MC, Snijders TJ. Diagnostic markers for CNS lymphoma in blood and cerebrospinal fluid: a systematic review. Br J Haematol. 2018 May 29. doi: 10.1111/bjh.15410. [Epub ahead of print] PubMed PMID: 29808930.
4)

van der Meulen M, Bromberg JEC, Lam KH, Dammers R, Langerak AW, Doorduijn JK, Kros JM, van den Bent MJ, van der Velden VHJ. Flow cytometry shows added value in diagnosing lymphoma in brain biopsies. Cytometry B Clin Cytom. 2018 May 10. doi: 10.1002/cyto.b.21641. [Epub ahead of print] PubMed PMID: 29747221.
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