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

Responsive Neurostimulation System

Responsive Neurostimulation System

Patients with medically refractory temporal lobe epilepsy (TLE) are candidates for neuromodulation procedures. While vagus nerve stimulation (VNS) was historically the procedure of choice for this condition, the responsive neurostimulation system (RNS) has come into favor for its more targeted approach.


This treatment was approved by the U.S. Food and Drug Administration (FDA) in 2013.


Neuromodulation such as vagus nerve stimulation (VNS) and responsive neurostimulation (RNS) are safe and effective strategies for medically intractable epilepsy secondary to complex partial seizures, but researchers have yet to compare their efficacies.


Wang et al. retrospectively reviewed the records of all patients with TLE who underwent VNS or RNS placement at our institution from 2003 to 2018. The primary outcome was change in seizure frequency. Other outcomes included Engel score, change in anti-epileptic medications, and complications.

Twenty-three patients met inclusion criteria; 11 underwent VNS and 12 underwent RNS. At baseline, the 2 groups were statistically similar regarding age at surgery, epilepsy duration, and preoperative seizure frequency. At last follow-up, both groups displayed reduced seizure frequency (mean reduction of 46.3% for the VNS group and 58.1% for the RNS group, p = 0.49). Responder rate, Engel score, and change in medications were statistically similar between groups. Compared to 0.0% of the VNS group, 13.3% of the RNS group experienced infection requiring re-operation.

Despite their different mechanisms, VNS and RNS resulted in similar response rates for patients with TLE. We suggest that VNS should not be excluded as a treatment for patients with medically refractory TLE who are not candidates for resective or ablative procedures 1).


The goal of a study of Ellens et al. was to compare VNS and RNS efficacy at reducing seizure frequency and complication rates in subjects with medically intractable epilepsy secondary to complex partial seizures.

This is a retrospective chart review of 30 patients with medically intractable complex partial epilepsy, who underwent either VNS or RNS placement at a single institution between June 2012 and January 2016. There was a mean follow-up of 19 months. Seizure frequency reduction and complications were identified.

The median seizure frequency reduction was similar for VNS (66%) and RNS (58%). There was no major morbidity or mortality, and the frequency of minor complications was similar between VNS (15%) and RNS (18%).

They found that VNS and RNS reduced the median seizure frequency similarly with no difference in morbidity or mortality. Further prospective studies are warranted as VNS and RNS therapy improves over time 2).

Systematic reviews

Boon et al., conducted a systematic review on the currently available neurostimulation modalities primarily with regard to effectiveness and safety.

For vagus nerve stimulation (VNS), there is moderate-quality evidence for its effectiveness in adults with drug-resistant partial epilepsies. Moderate-to-low-quality evidence supports the efficacy and safety of deep brain stimulation (DBS) and responsive neurostimulation (RNS) in patients with DRE. There is moderate-to-very low-quality evidence that transcranial direct current stimulation (tDCS) is effective or well tolerated. For transcutaneous vagus nerve stimulation (tVNS), transcranial magnetic stimulation (TMS) and trigeminal nerve stimulation (TNS), there are insufficient data to support the efficacy of any of these modalities for DRE. These treatment modalities, nevertheless, appear well tolerated, with no severe adverse events reported.

Head-to-head comparison of treatment modalities such as VNS, DBS and RNS across different epileptic syndromes are required to decide which treatment modality is the most effective for a given patient scenario. Such studies are challenging and it is unlikely that data will be available in the near future. Additional data collection on potentially promising noninvasive neurostimulation modalities like tVNS, TMS, TNS and tDCS is warranted to get a more precise estimate of their therapeutic benefit and long-term safety 3).


Jobst BC, Kapur R, Barkley GL, Bazil CW, Berg MJ, Bergey GK, Boggs JG, Cash SS, Cole AJ, Duchowny MS, Duckrow RB, Edwards JC, Eisenschenk S, Fessler AJ, Fountain NB, Geller EB, Goldman AM, Goodman RR, Gross RE, Gwinn RP, Heck C, Herekar AA, Hirsch LJ, King-Stephens D, Labar DR, Marsh WR, Meador KJ, Miller I, Mizrahi EM, Murro AM, Nair DR, Noe KH, Olejniczak PW, Park YD, Rutecki P, Salanova V, Sheth RD, Skidmore C, Smith MC, Spencer DC, Srinivasan S, Tatum W, Van Ness P, Vossler DG, Wharen RE Jr, Worrell GA, Yoshor D, Zimmerman RS, Skarpaas TL, Morrell MJ. Brain-responsive neurostimulation in patients with medically intractable seizures arising from eloquent and other neocortical areas. Epilepsia. 2017 Jun;58(6):1005-1014. doi: 10.1111/epi.13739. Epub 2017 Apr 7. PubMed PMID: 28387951.

References

1)

Wang AJ, Bick SK, Williams ZM. Vagus Nerve Stimulation versus Responsive Neurostimulator System in Patients with Temporal Lobe Epilepsy. Stereotact Funct Neurosurg. 2020 Feb 19:1-9. doi: 10.1159/000504859. [Epub ahead of print] PubMed PMID: 32074618.
2)

Ellens NR, Elisevich K, Burdette DE, Patra SE. A Comparison of Vagal Nerve Stimulation and Responsive Neurostimulation for the Treatment of Medically Refractory Complex Partial Epilepsy. Stereotact Funct Neurosurg. 2018 Aug 27:1-5. doi: 10.1159/000492232. [Epub ahead of print] PubMed PMID: 30149389.
3)

Boon P, De Cock E, Mertens A, Trinka E. Neurostimulation for drug-resistant epilepsy: a systematic review of clinical evidence for efficacy, safety, contraindications and predictors for response. Curr Opin Neurol. 2018 Apr;31(2):198-210. doi: 10.1097/WCO.0000000000000534. PubMed PMID: 29493559.

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)

List Price:$199.99

Buy

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.

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