|
1
|
Ostrom QT, Price M, Neff C, Cioffi G,
Waite KA, Kruchko C and Barnholtz-Sloan JS: CBTRUS statistical
report: Primary brain and other central nervous system tumors
diagnosed in the United States in 2015–2019. Neuro Oncol. 24 (Suppl
5):v1–v95. 2022. View Article : Google Scholar : PubMed/NCBI
|
|
2
|
Fox CP, Phillips EH, Smith J, Linton K,
Gallop-Evans E, Hemmaway C, Auer DP, Fuller C, Davies AJ, McKay P,
et al: Guidelines for the diagnosis and management of primary
central nervous system diffuse large B-cell lymphoma. Br J
Haematol. 184:348–363. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
3
|
Sugita Y, Muta H, Ohshima K, Morioka M,
Tsukamoto Y, Takahashi H and Kakita A: Primary central nervous
system lymphomas and related diseases: Pathological characteristics
and discussion of the differential diagnosis. Neuropathology.
36:313–324. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
4
|
Grommes C, Rubenstein JL, DeAngelis LM,
Ferreri AJM and Batchelor TT: Comprehensive approach to diagnosis
and treatment of newly diagnosed primary CNS lymphoma. Neuro Oncol.
21:296–305. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
5
|
McKinnon C, Nandhabalan M, Murray SA and
Plaha P: Glioblastoma: Clinical presentation, diagnosis, and
management. BMJ. 374:n15602021. View Article : Google Scholar : PubMed/NCBI
|
|
6
|
Alexander BM and Cloughesy TF: Adult
Glioblastoma. J Clin Oncol. 35:2402–2409. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
7
|
Chiavazza C, Pellerino A, Ferrio F,
Cistaro A, Soffietti R and Ruda R: Primary CNS lymphomas:
Challenges in diagnosis and monitoring. Biomed Res Int.
2018:36069702018. View Article : Google Scholar : PubMed/NCBI
|
|
8
|
Grommes C and DeAngelis LM: Primary CNS
Lymphoma. J Clin Oncol. 35:2410–2418. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
9
|
Su L, Ding M, Chen L, Li C and Lao M:
Primary central nervous system lymphoma in a patient with systemic
lupus erythematosus mimicking high-grade glioma: A case report and
review of literature. Medicine (Baltimore). 97:e110722018.
View Article : Google Scholar : PubMed/NCBI
|
|
10
|
Bhatt VR, Shrestha R, Shonka N and Bociek
RG: Near misdiagnosis of glioblastoma as primary central nervous
system lymphoma. J Clin Med Res. 6:299–301. 2014.PubMed/NCBI
|
|
11
|
Louis DN, Perry A, Reifenberger G, von
Deimling A, Figarella-Branger D, Cavenee WK, Ohgaki H, Wiestler OD,
Kleihues P and Ellison DW: The 2016 World Health organization
classification of tumors of the central nervous system: A summary.
Acta Neuropathol. 131:803–820. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
12
|
Giannini C, Dogan A and Salomão DR: CNS
Lymphoma: A practical diagnostic approach. J Neuropathol Exp
Neurol. 73:478–494. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
13
|
Morell AA, Shah AH, Cavallo C, Eichberg
DG, Sarkiss CA, Benveniste R, Ivan ME and Komotar RJ: Diagnosis of
primary central nervous system lymphoma: A systematic review of the
utility of CSF screening and the role of early brain biopsy.
Neurooncol Pract. 6:415–423. 2019.PubMed/NCBI
|
|
14
|
Patrick LB and Mohile NA: Advances in
primary central nervous system lymphoma. Curr Oncol Rep. 17:602015.
View Article : Google Scholar : PubMed/NCBI
|
|
15
|
Velasco R, Mercadal S, Vidal N, Alañá M,
Barceló MI, Ibáñez-Juliá MJ, Bobillo S, Caldú Agud R, García Molina
E, Martínez P, et al: Diagnostic delay and outcome in
immunocompetent patients with primary central nervous system
lymphoma in Spain: A multicentric study. J Neurooncol. 148:545–554.
2020. View Article : Google Scholar : PubMed/NCBI
|
|
16
|
Nabors LB, Portnow J, Baehring J, Bloch O,
Brem S, Butowski N, Cannon DM, Chao S, Chheda MG, Clark SW, et al:
NCCN Clinical Practice Guidelines in Oncology Central Nervous
System Cancers (Version 2.2022 - September 29, 2022). https://www.nccn.org/guidelines/guidelines-detail?category=1&id=1425
|
|
17
|
Chukwueke UN and Nayak L: Central nervous
system lymphoma. Hematol Oncol Clin North Am. 33:597–611. 2019.
View Article : Google Scholar : PubMed/NCBI
|
|
18
|
Ozturk K, Soylu E and Cayci Z:
Differentiation between primary CNS lymphoma and atypical
glioblastoma according to major genomic alterations using diffusion
and susceptibility-weighted MR imaging. Eur J Radiol.
141:1097842021. View Article : Google Scholar : PubMed/NCBI
|
|
19
|
Barajas RF, Politi LS, Anzalone N, Schöder
H, Fox CP, Boxerman JL, Kaufmann TJ, Quarles CC, Ellingson BM, Auer
D, et al: Consensus recommendations for MRI and PET imaging of
primary central nervous system lymphoma: Guideline statement from
the International primary CNS lymphoma collaborative group (IPCG).
Neuro Oncol. 23:1056–1071. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
20
|
Villanueva-Meyer JE, Mabray MC and Cha S:
Current clinical brain tumor imaging. Neurosurgery. 81:397–415.
2017. View Article : Google Scholar : PubMed/NCBI
|
|
21
|
Lin X, Lee M, Buck O, Woo KM, Zhang Z,
Hatzoglou V, Omuro A, Arevalo-Perez J, Thomas AA, Huse J, et al:
Diagnostic accuracy of T1-Weighted dynamic contrast-enhanced-MRI
and DWI-ADC for differentiation of glioblastoma and primary CNS
Lymphoma. AJNR Am J Neuroradiol. 38:485–491. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
22
|
Lu S, Wang S, Gao Q, Zhou M, Li Y, Cao P,
Hong X and Shi H: Quantitative evaluation of diffusion and dynamic
contrast-enhanced magnetic resonance imaging for differentiation
between primary central nervous system lymphoma and glioblastoma. J
Comput Assist Tomogr. 41:898–903. 2017. View Article : Google Scholar : PubMed/NCBI
|
|
23
|
Makino K, Hirai T, Nakamura H, Kuroda JI,
Shinojima N, Uetani H, Kitajima M and Yano S: Differentiating
between primary central nervous system lymphomas and glioblastomas:
Combined use of perfusion-weighted and diffusion-weighted magnetic
resonance imaging. World Neurosurg. 112:e1–e6. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
24
|
Ahn SJ, Shin HJ, Chang JH and Lee SK:
Differentiation between primary cerebral lymphoma and glioblastoma
using the apparent diffusion coefficient: Comparison of three
different ROI methods. PLoS One. 9:e1129482014. View Article : Google Scholar : PubMed/NCBI
|
|
25
|
Nakajima S, Okada T, Yamamoto A, Kanagaki
M, Fushimi Y, Okada T, Arakawa Y, Takagi Y, Miyamoto S and Togashi
K: Primary central nervous system lymphoma and glioblastoma:
Differentiation using dynamic susceptibility-contrast
perfusion-weighted imaging, diffusion-weighted imaging, and
(18)F-fluorodeoxyglucose positron emission tomography. Clin
Imaging. 39:390–395. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
26
|
Suh CH, Kim HS, Jung SC, Choi CG and Kim
SJ: Clinically relevant imaging features for MGMT promoter
methylation in multiple glioblastoma studies: A systematic review
and meta-analysis. AJNR Am J Neuroradiol. 39:1439–1445.
2018.PubMed/NCBI
|
|
27
|
Akbari H, Bakas S, Pisapia JM, Nasrallah
MP, Rozycki M, Martinez-Lage M, Morrissette JJD, Dahmane N,
O'Rourke DM and Davatzikos C: In vivo evaluation of EGFRvIII
mutation in primary glioblastoma patients via complex
multiparametric MRI signature. Neuro Oncol. 20:1068–1079. 2018.
View Article : Google Scholar : PubMed/NCBI
|
|
28
|
Quarles CC, Bell LC and Stokes AM: Imaging
vascular and hemodynamic features of the brain using dynamic
susceptibility contrast and dynamic contrast enhanced MRI.
Neuroimage. 187:32–55. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
29
|
Suh CH, Kim HS, Jung SC, Park JE, Choi CG
and Kim SJ: MRI as a diagnostic biomarker for differentiating
primary central nervous system lymphoma from glioblastoma: A
systematic review and meta-analysis. J Magn Reson Imaging.
50:560–572. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
30
|
Neska-Matuszewska M, Bladowska J, Sasiadek
M and Zimny A: Differentiation of glioblastoma multiforme,
metastases and primary central nervous system lymphomas using
multiparametric perfusion and diffusion MR imaging of a tumor core
and a peritumoral zone-Searching for a practical approach. PLoS
One. 13:e01913412018. View Article : Google Scholar : PubMed/NCBI
|
|
31
|
Xu W, Wang Q, Shao A, Xu B and Zhang J:
The performance of MR perfusion-weighted imaging for the
differentiation of high-grade glioma from primary central nervous
system lymphoma: A systematic review and meta-analysis. PLoS One.
12:e01734302017. View Article : Google Scholar : PubMed/NCBI
|
|
32
|
Cindil E, Sendur HN, Cerit MN, Dag N,
Erdogan N, Celebi FE, Oner Y and Tali T: Validation of combined use
of DWI and percentage signal recovery-optimized protocol of DSC-MRI
in differentiation of high-grade glioma, metastasis, and lymphoma.
Neuroradiology. 63:331–342. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
33
|
Chaganti J, Taylor M, Woodford H and Steel
T: Differentiation of primary central nervous system lymphoma and
high-grade glioma with dynamic susceptibility contrast-derived
metrics: Pilot study. World Neurosurg. 151:e979–e987. 2021.
View Article : Google Scholar : PubMed/NCBI
|
|
34
|
Semmineh NB, Xu J, Skinner JT, Xie J, Li
H, Ayers G and Quarles CC: Assessing tumor cytoarchitecture using
multiecho DSC-MRI derived measures of the transverse relaxivity at
tracer equilibrium (TRATE). Magn Reson Med. 74:772–784. 2015.
View Article : Google Scholar : PubMed/NCBI
|
|
35
|
Lee MD, Baird GL, Bell LC, Quarles CC and
Boxerman JL: Utility of percentage signal recovery and baseline
signal in DSC-MRI optimized for relative CBV measurement for
differentiating glioblastoma, lymphoma, metastasis, and meningioma.
AJNR Am J Neuroradiol. 40:1445–1450. 2019.PubMed/NCBI
|
|
36
|
Hsu CC, Watkins TW, Kwan GN and Haacke EM:
Susceptibility-Weighted imaging of glioma: Update on current
imaging status and future directions. J Neuroimaging. 26:383–390.
2016. View Article : Google Scholar : PubMed/NCBI
|
|
37
|
Saini J, Kumar Gupta P, Awasthi A, Pandey
CM, Singh A, Patir R, Ahlawat S, Sadashiva N, Mahadevan A and Kumar
Gupta R: Multiparametric imaging-based differentiation of lymphoma
and glioblastoma: Using T1-perfusion, diffusion, and
susceptibility-weighted MRI. Clin Radiol. 73:986e7–986e15. 2018.
View Article : Google Scholar : PubMed/NCBI
|
|
38
|
Yamasaki F, Takayasu T, Nosaka R, Amatya
VJ, Doskaliyev A, Akiyama Y, Tominaga A, Takeshima Y, Sugiyama K
and Kurisu K: Magnetic resonance spectroscopy detection of high
lipid levels in intraaxial tumors without central necrosis: A
characteristic of malignant lymphoma. J Neurosurg. 122:1370–1379.
2015. View Article : Google Scholar : PubMed/NCBI
|
|
39
|
Nagashima H, Sasayama T, Tanaka K, Kyotani
K, Sato N, Maeyama M, Kohta M, Sakata J, Yamamoto Y, Hosoda K, et
al: Myo-inositol concentration in MR spectroscopy for
differentiating high grade glioma from primary central nervous
system lymphoma. J Neurooncol. 136:317–326. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
40
|
Nomura Y, Asano Y, Shinoda J, Yano H,
Ikegame Y, Kawasaki T, Nakayama N, Maruyama T, Muragaki Y and Iwama
T: Characteristics of time-activity curves obtained from dynamic
11C-methionine PET in common primary brain tumors. J
Neurooncol. 138:649–658. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
41
|
Kong Z, Jiang C, Zhu R, Feng S, Wang Y, Li
J, Chen W, Liu P, Zhao D, Ma W, et al: 18F-FDG-PET-based
radiomics features to distinguish primary central nervous system
lymphoma from glioblastoma. Neuroimage Clin. 23:1019122019.
View Article : Google Scholar : PubMed/NCBI
|
|
42
|
Zhou W, Wen J, Hua F, Xu W, Lu X, Yin B,
Geng D and Guan Y: 18F-FDG PET/CT in immunocompetent
patients with primary central nervous system lymphoma:
Differentiation from glioblastoma and correlation with DWI. Eur J
Radiol. 104:26–32. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
43
|
Kim HO, Kim JS, Kim SO, Chae SY, Oh SJ,
Seo M, Lee SH, Oh JS, Ryu JS, Huh JR and Kim JH:
Clinicopathological characteristics of primary central nervous
system lymphoma with low 18F-fludeoxyglucose uptake on brain
positron emission tomography. Medicine (Baltimore). 99:e201402020.
View Article : Google Scholar : PubMed/NCBI
|
|
44
|
Wang H, Zhou Y, Li L, Hou W, Ma X and Tian
R: Current status and quality of radiomics studies in lymphoma: A
systematic review. Eur Radiol. 30:6228–6240. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
45
|
Lohmann P, Galldiks N, Kocher M, Heinzel
A, Filss CP, Stegmayr C, Mottaghy FM, Fink GR, Jon Shah N and
Langen KJ: Radiomics in neuro-oncology: Basics, workflow, and
applications. Methods. 188:112–121. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
46
|
Priya S, Ward C, Locke T, Soni N,
Maheshwarappa RP, Monga V, Agarwal A and Bathla G: Glioblastoma and
primary central nervous system lymphoma: Differentiation using MRI
derived first-order texture analysis-a machine learning study.
Neuroradiol J. 34:320–328. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
47
|
Han Y, Wang ZJ, Li WH, Yang Y, Zhang J,
Yang XB, Zuo L, Xiao G, Wang SZ, Yan LF and Cui GB: Differentiation
between primary central nervous system lymphoma and atypical
glioblastoma based on MRI morphological feature and signal
intensity ratio: A retrospective multicenter study. Front Oncol.
12:8111972022. View Article : Google Scholar : PubMed/NCBI
|
|
48
|
Suh HB, Choi YS, Bae S, Ahn SS, Chang JH,
Kang SG, Kim EH, Kim SH and Lee SK: Primary central nervous system
lymphoma and atypical glioblastoma: Differentiation using radiomics
approach. Eur Radiol. 28:3832–3839. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
49
|
Chen C, Zheng A, Ou X, Wang J and Ma X:
Comparison of radiomics-based machine-learning classifiers in
diagnosis of glioblastoma from primary central nervous system
lymphoma. Front Oncol. 10:11512020. View Article : Google Scholar : PubMed/NCBI
|
|
50
|
MacIver CL, Busaidi AA, Ganeshan B,
Maynard JA, Wastling S, Hyare H, Brandner S, Markus JE, Lewis MA,
Groves AM, et al: Filtration-Histogram based magnetic resonance
texture analysis (MRTA) for the distinction of primary central
nervous system lymphoma and glioblastoma. J Pers Med. 11:8762021.
View Article : Google Scholar : PubMed/NCBI
|
|
51
|
Mehrnahad M, Rostami S, Kimia F, Kord R,
Taheri MS, Rad HS, Haghighatkhah H, Moradi A and Kord A:
Differentiating glioblastoma multiforme from cerebral lymphoma:
Application of advanced texture analysis of quantitative apparent
diffusion coefficients. Neuroradiol J. 33:428–436. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
52
|
Kang D, Park JE, Kim YH, Kim JH, Oh JY,
Kim J, Kim Y, Kim ST and Kim HS: Diffusion radiomics as a
diagnostic model for atypical manifestation of primary central
nervous system lymphoma: Development and multicenter external
validation. Neuro Oncol. 20:1251–1261. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
53
|
Xia W, Hu B, Li H, Geng C, Wu Q, Yang L,
Yin B, Gao X, Li Y and Geng D: Multiparametric-MRI-Based radiomics
model for differentiating primary central nervous system lymphoma
from glioblastoma: Development and cross-vendor validation. J Magn
Reson Imaging. 53:242–250. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
54
|
Kim Y, Cho HH, Kim ST, Park H, Nam D and
Kong DS: Radiomics features to distinguish glioblastoma from
primary central nervous system lymphoma on multi-parametric MRI.
Neuroradiology. 60:1297–1305. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
55
|
Bathla G, Priya S, Liu Y, Ward C, Le NH,
Soni N, Maheshwarappa RP, Monga V, Zhang H and Sonka M:
Radiomics-based differentiation between glioblastoma and primary
central nervous system lymphoma: A comparison of diagnostic
performance across different MRI sequences and machine learning
techniques. Eur Radiol. 31:8703–8713. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
56
|
Nakagawa M, Nakaura T, Namimoto T,
Kitajima M, Uetani H, Tateishi M, Oda S, Utsunomiya D, Makino K,
Nakamura H, et al: Machine learning based on multi-parametric
magnetic resonance imaging to differentiate glioblastoma multiforme
from primary cerebral nervous system lymphoma. Eur J Radiol.
108:147–154. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
57
|
McAvoy M, Prieto PC, Kaczmarzyk JR,
Fernández IS, McNulty J, Smith T, Yu KH, Gormley WB and Arnaout O:
Classification of glioblastoma versus primary central nervous
system lymphoma using convolutional neural networks. Sci Rep.
11:152192021. View Article : Google Scholar : PubMed/NCBI
|
|
58
|
Zhang Y, Liang K, He J, Ma H, Chen H,
Zheng F, Zhang L, Wang X, Ma X and Chen X: Deep learning with data
enhancement for the differentiation of solitary and multiple
cerebral glioblastoma, lymphoma, and tumefactive demyelinating
lesion. Front Oncol. 11:6658912021. View Article : Google Scholar : PubMed/NCBI
|
|
59
|
Xia W, Hu B, Li H, Shi W, Tang Y, Yu Y,
Geng C, Wu Q, Yang L, Yu Z, et al: Deep learning for automatic
differential diagnosis of primary central nervous system lymphoma
and glioblastoma: Multi-Parametric magnetic resonance imaging based
convolutional neural network model. J Magn Reson Imaging.
54:880–887. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
60
|
Tariciotti L, Caccavella VM, Fiore G,
Schisano L, Carrabba G, Borsa S, Giordano M, Palmisciano P, Remoli
G, Remore LG, et al: A deep learning model for preoperative
differentiation of glioblastoma, brain metastasis and primary
central nervous system lymphoma: A pilot study. Front Oncol.
12:8166382022. View Article : Google Scholar : PubMed/NCBI
|
|
61
|
Yun J, Park JE, Lee H, Ham S, Kim N and
Kim HS: Radiomic features and multilayer perceptron network
classifier: A robust MRI classification strategy for distinguishing
glioblastoma from primary central nervous system lymphoma. Sci Rep.
9:57462019. View Article : Google Scholar : PubMed/NCBI
|
|
62
|
Park JE, Kim HS, Lee J, Cheong EN, Shin I,
Ahn SS and Shim WH: Deep-learned time-signal intensity pattern
analysis using an autoencoder captures magnetic resonance perfusion
heterogeneity for brain tumor differentiation. Sci Rep.
10:214852020. View Article : Google Scholar : PubMed/NCBI
|
|
63
|
Chhieng DC, Elgert P, Cohen JM, Jhala NC
and Cangiarella JF: Cytology of primary central nervous system
neoplasms in cerebrospinal fluid specimens. Diagn Cytopathol.
26:209–212. 2002. View Article : Google Scholar : PubMed/NCBI
|
|
64
|
Bromberg JE, Breems DA, Kraan J, Bikker G,
van der Holt B, Smitt PS, van den Bent MJ, van't Veer M and Gratama
JW: CSF flow cytometry greatly improves diagnostic accuracy in CNS
hematologic malignancies. Neurology. 68:1674–1679. 2007. View Article : Google Scholar : PubMed/NCBI
|
|
65
|
Schroers R, Baraniskin A, Heute C, Vorgerd
M, Brunn A, Kuhnhenn J, Kowoll A, Alekseyev A, Schmiegel W,
Schlegel U, et al: Diagnosis of leptomeningeal disease in diffuse
large B-cell lymphomas of the central nervous system by flow
cytometry and cytopathology. Eur J Haematol. 85:520–528. 2020.
View Article : Google Scholar : PubMed/NCBI
|
|
66
|
Baraniskin A, Deckert M,
Schulte-Altedorneburg G, Schlegel U and Schroers R: Current
strategies in the diagnosis of diffuse large B-cell lymphoma of the
central nervous system. Br J Haematol. 156:421–432. 2012.
View Article : Google Scholar : PubMed/NCBI
|
|
67
|
van Westrhenen A, Smidt LCA, Seute T,
Nierkens S, Stork ACJ, Minnema MC and Snijders TJ: Diagnostic
markers for CNS lymphoma in blood and cerebrospinal fluid: A
systematic review. Br J Haematol. 182:384–403. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
68
|
Yang ZZ, Grote DM, Ziesmer SC, Manske MK,
Witzig TE, Novak AJ and Ansell SM: Soluble IL-2Rα facilitates
IL-2-mediated immune responses and predicts reduced survival in
follicular B-cell non-Hodgkin lymphoma. Blood. 118:2809–2820. 2011.
View Article : Google Scholar : PubMed/NCBI
|
|
69
|
Wolska A, Reimund M and Remaley AT:
Apolipoprotein C-II: The re-emergence of a forgotten factor. Curr
Opin Lipidol. 31:147–153. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
70
|
Saade M, Araujo de Souza G, Scavone C and
Kinoshita PF: The Role of GPNMB in inflammation. Front Immunol.
12:6747392021. View Article : Google Scholar : PubMed/NCBI
|
|
71
|
Waldera-Lupa DM, Poschmann G,
Kirchgaessler N, Etemad-Parishanzadeh O, Baberg F, Brocksieper M,
Seidel S, Kowalski T, Brunn A, Haghikia A, et al: A multiplex assay
for the stratification of patients with primary central nervous
system lymphoma using targeted mass spectrometry. Cancers (Basel).
12:17322020. View Article : Google Scholar : PubMed/NCBI
|
|
72
|
Maeyama M, Sasayama T, Tanaka K, Nakamizo
S, Tanaka H, Nishihara M, Fujita Y, Sekiguchi K, Kohta M, Mizukawa
K, et al: Multi-marker algorithms based on CXCL13, IL-10, sIL-2
receptor, and β2-microglobulin in cerebrospinal fluid to diagnose
CNS lymphoma. Cancer Med. 9:4114–4125. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
73
|
Rubenstein JL, Wong VS, Kadoch C, Gao HX,
Barajas R, Chen L, Josephson SA, Scott B, Douglas V, Maiti M, et
al: CXCL13 plus interleukin 10 is highly specific for the diagnosis
of CNS lymphoma. Blood. 121:4740–4748. 2013. View Article : Google Scholar : PubMed/NCBI
|
|
74
|
Shao J, Chen K, Li Q, Ma J, Ma Y, Lin Z,
Kang H and Chen B: High level of IL-10 in cerebrospinal fluid is
specific for diagnosis of primary central nervous system lymphoma.
Cancer Manag Res. 12:6261–6268. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
75
|
Masouris I, Manz K, Pfirrmann M, Dreyling
M, Angele B, Straube A, Langer S, Huber M, Koedel U and Von
Baumgarten L: CXCL13 and CXCL9 CSF levels in central nervous system
lymphoma-diagnostic, therapeutic, and prognostic relevance. Front
Neurol. 12:6545432021. View Article : Google Scholar : PubMed/NCBI
|
|
76
|
McEwen AE, Leary SES and Lockwood CM:
Beyond the blood: CSF-Derived cfDNA for diagnosis and
characterization of CNS tumors. Front Cell Dev Biol. 8:452020.
View Article : Google Scholar : PubMed/NCBI
|
|
77
|
Wang Z, Jiang W, Wang Y, Guo Y, Cong Z, Du
F and Song B: MGMT promoter methylation in serum and cerebrospinal
fluid as a tumor-specific biomarker of glioma. Biomed Rep.
3:543–548. 2015. View Article : Google Scholar : PubMed/NCBI
|
|
78
|
Juratli TA, Stasik S, Zolal A, Schuster C,
Richter S, Daubner D, Juratli MA, Thowe R, Hennig S, Makina M, et
al: TERT promoter mutation detection in cell-free tumor-derived DNA
in patients with IDH wild-type glioblastomas: A pilot prospective
study. Clin Cancer Res. 24:5282–5291. 2018. View Article : Google Scholar : PubMed/NCBI
|
|
79
|
Nakamura T, Tateishi K, Niwa T, Matsushita
Y, Tamura K, Kinoshita M, Tanaka K, Fukushima S, Takami H, Arita H,
et al: Recurrent mutations of CD79B and MYD88 are the hallmark of
primary central nervous system lymphomas. Neuropathol Appl
Neurobiol. 42:279–290. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
80
|
Hiemcke-Jiwa LS, Leguit RJ, Snijders TJ,
Bromberg JEC, Nierkens S, Jiwa NM, Minnema MC and Huibers MMH:
MYD88 p.(L265P) detection on cell-free DNA in liquid biopsies of
patients with primary central nervous system lymphoma. Br J
Haematol. 185:974–977. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
81
|
Ferreri AJM, Calimeri T, Lopedote P,
Francaviglia I, Daverio R, Iacona C, Belloni C, Steffanoni S,
Gulino A, Anghileri E, et al: MYD88 L265P mutation and
interleukin-10 detection in cerebrospinal fluid are highly specific
discriminating markers in patients with primary central nervous
system lymphoma: Results from a prospective study. Br J Haematol.
193:497–505. 2021. View Article : Google Scholar : PubMed/NCBI
|
|
82
|
Downs BM, Ding W, Cope LM, Umbricht CB, Li
W, He H, Ke X, Holdhoff M, Bettegowda C, Tao W and Sukumar S:
Methylated markers accurately distinguish primary central nervous
system lymphomas (PCNSL) from other CNS tumors. Clin Epigenetics.
13:1042021. View Article : Google Scholar : PubMed/NCBI
|
|
83
|
Jelski W and Mroczko B: Molecular and
circulating biomarkers of brain tumors. Int J Mol Sci. 22:70392021.
View Article : Google Scholar : PubMed/NCBI
|
|
84
|
Kim S, Jeon OH and Jeon YJ: Extracellular
RNA: Emerging roles in cancer cell communication and biomarkers.
Cancer Lett. 495:33–40. 2020. View Article : Google Scholar : PubMed/NCBI
|
|
85
|
Birkó Z, Nagy B, Klekner Á and Virga J:
Novel molecular markers in glioblastoma-benefits of liquid biopsy.
Int J Mol Sci. 21:75222020. View Article : Google Scholar : PubMed/NCBI
|
|
86
|
Colombo M, Raposo G and Théry C:
Biogenesis, secretion, and intercellular interactions of exosomes
and other extracellular vesicles. Annu Rev Cell Dev Biol.
30:255–289. 2014. View Article : Google Scholar : PubMed/NCBI
|
|
87
|
Yang K, Wang S, Cheng Y, Tian Y and Hou J:
Role of miRNA-21 in the diagnosis and prediction of treatment
efficacy of primary central nervous system lymphoma. Oncol Lett.
17:3475–3481. 2019.PubMed/NCBI
|
|
88
|
Xia H, Qi Y, Ng SS, Chen X, Chen S, Fang
M, Li D, Zhao Y, Ge R, Li G, et al: MicroRNA-15b regulates cell
cycle progression by targeting cyclins in glioma cells. Biochem
Biophys Res Commun. 380:205–210. 2009. View Article : Google Scholar : PubMed/NCBI
|
|
89
|
Baraniskin A, Kuhnhenn J, Schlegel U,
Maghnouj A, Zollner H, Schmiegel W, Hahn S and Schroers R:
Identification of microRNAs in the cerebrospinal fluid as biomarker
for the diagnosis of glioma. Neuro Oncol. 14:29–33. 2012.
View Article : Google Scholar : PubMed/NCBI
|
|
90
|
Meng F, Henson R, Wehbe-Janek H, Ghoshal
K, Jacob ST and Patel T: MicroRNA-21 regulates expression of the
PTEN tumor suppressor gene in human hepatocellular cancer.
Gastroenterology. 133:647–658. 2007. View Article : Google Scholar : PubMed/NCBI
|
|
91
|
Cabarcas S, Watabe K and Schramm L:
Inhibition of U6 snRNA transcription by PTEN. Online J Biol Sci.
10:114–125. 2010. View Article : Google Scholar : PubMed/NCBI
|
|
92
|
Puigdelloses M, Gonzalez-Huarriz M,
Garcia-Moure M, Martinez-Velez N, Esparragosa Vazquez I, Bruna J,
Zandio B, Agirre A, Marigil M, Petrirena G, et al: RNU6-1 in
circulating exosomes differentiates GBM from non-neoplastic brain
lesions and PCNSL but not from brain metastases. Neurooncol Adv.
2:vdaa0102020.PubMed/NCBI
|
|
93
|
Eisenhut F, Schmidt MA, Putz F, Lettmaier
S, Fröhlich K, Arinrad S, Coras R, Luecking H, Lang S, Fietkau R
and Doerfler A: Classification of primary cerebral lymphoma and
glioblastoma featuring dynamic susceptibility contrast and apparent
diffusion coefficient. Brain Sci. 10:8862020. View Article : Google Scholar : PubMed/NCBI
|
|
94
|
Mabray MC, Barajas RF, Villanueva-Meyer
JE, Zhang CA, Valles FE, Rubenstein JL and Cha S: The combined
performance of ADC, CSF CXC Chemokine Ligand 13, and CSF
Interleukin 10 in the diagnosis of central nervous system lymphoma.
AJNR Am J Neuroradiol. 37:74–79. 2016. View Article : Google Scholar : PubMed/NCBI
|
|
95
|
Hatakeyama J, Ono T, Takahashi M, Oda M
and Shimizu H: Differentiating between primary central nervous
system lymphoma and glioblastoma: The diagnostic value of combining
18F-fluorodeoxyglucose positron emission tomography with
arterial spin labeling. Neurol Med Chir (Tokyo). 61:367–375. 2021.
View Article : Google Scholar : PubMed/NCBI
|
|
96
|
Weller M, Martus P, Roth P, Thiel E and
Korfel A; German PCNSL Study Group, : Surgery for primary CNS
lymphoma? Challenging a paradigm. Neuro Oncol. 14:1481–1484. 2012.
View Article : Google Scholar : PubMed/NCBI
|
|
97
|
Deng X, Xu X, Lin D, Zhang X, Yu L, Sheng
H, Yin B, Zhang N and Lin J: Real-World impact of surgical excision
on overall survival in primary central nervous system lymphoma.
Front Oncol. 10:1312020. View Article : Google Scholar : PubMed/NCBI
|
|
98
|
Labak CM, Holdhoff M, Bettegowda C, Gallia
GL, Lim M, Weingart JD and Mukherjee D: Surgical resection for
primary central nervous system lymphoma: A systematic review. World
Neurosurg. 126:e1436–e1448. 2019. View Article : Google Scholar : PubMed/NCBI
|
|
99
|
Schellekes N, Barbotti A, Abramov Y, Sitt
R, Di Meco F, Ram Z and Grossman R: Resection of primary central
nervous system lymphoma: Impact of patient selection on overall
survival. J Neurosurg. Feb 26–2021.(Epub ahead of print).
View Article : Google Scholar : PubMed/NCBI
|
|
100
|
Bierman PJ: Surgery for primary central
nervous system lymphoma: Is it time for reevaluation? Oncology
(Williston Park). 28:632–637. 2014.PubMed/NCBI
|
