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DOI: 10.1055/s-0042-115572
Discrimination of Different Brain Metastases and Primary CNS Lymphomas Using Morphologic Criteria and Diffusion Tensor Imaging
Unterscheidung verschiedener Hirnmetastasen und primärer ZNS-Lymphome anhand morphologischer Kriterien und Diffusions-Tensor-BildgebungPublication History
17 June 2016
13 August 2016
Publication Date:
19 September 2016 (online)
![](https://www.thieme-connect.de/media/roefo/201612/lookinside/thumbnails/roefo-2710_10-1055-s-0042-115572-1.jpg)
Abstract
Purpose: Brain metastases are a common complication of cancer and occur in about 15 – 40 % of patients with malignancies. The aim of this retrospective study was to differentiate between metastases from different primary tumors/CNS lymphyomas using morphologic criteria, fractional anisotropy (FA) and apparent diffusion coefficient (ADC).
Materials and Methods: Morphologic criteria such as hemorrhage, cysts, pattern of contrast enhancement and location were reported in 200 consecutive patients with brain metastases/primary CNS lymphomas. FA and ADC values were measured in regions of interest (ROIs) placed in the contrast-enhancing tumor part, the necrosis and the non-enhancing peritumoral region (NEPTR). Differences between histopathological subtypes of metastases were analyzed using non-parametric tests, decision trees and hierarchical clustering analysis.
Results: Significant differences were found in morphologic criteria such as hemorrhage or pattern of contrast enhancement. In diffusion measurements, significant differences between the different tumor entities were only found in ADC analyzed in the contrast-enhancing tumor part. Among single tumor entities, primary CNS lymphomas showed significantly lower median ADC values in the contrast-enhancing tumor part (ADClymphoma 0.92 [0.83 – 1.07] vs. ADCno_lymphoma 1.35 [1.10 – 1.64] P = 0.001). Further differentiation between types of metastases was not possible using FA and ADC.
Conclusion: There were morphologic differences among the main subtypes of brain metastases/CNS lymphomas. However, due to a high variability of common types of metastases and low specificity, prospective differentiation remained challenging. DTI including FA and ADC was not a reliable tool for differentiation between different histopathological subtypes of brain metastases except for CNS lymphomas showing lower ADC values. Biopsy, surgery and staging remain essential for diagnosis.
Key Points:
• Histopathological subtypes of brain metastases/CNS lymphomas show different morphologic features on MRI
• Primary CNS lymphomas show significantly reduced ADC values
• DTI is not a reliable tool for differentiation between brain metastases
Citation Format:
• Bette S, Wiestler B, Delbridge C et al. Discrimination of Different Brain Metastases and Primary CNS Lymphomas Using Morphologic Criteria and Diffusion Tensor Imaging. Fortschr Röntgenstr 2016; 188: 1134 – 1143
Zusammenfassung
Ziel: Hirnmetastasen treten in ca. 15 – 40 % der Patienten mit malignen Grunderkrankungen auf. Ziel dieser Studie war es, zwischen Hirnmetastasen unterschiedlicher Primärtumore/ZNS-Lymphomen bildgebend anhand morphologischer Kriterien sowie der Fraktionalen Anisotropie (FA) und dem „apparent diffusion coefficient“ (ADC) der Diffusions-Tensor-Bildgebung (DTI) zu differenzieren.
Material und Methoden: 200 Patienten mit zerebralen Hirnmetastasen/primären ZNS-Lymphomen wurden retrospektiv eingeschlossen. Morphologische Kriterien wie Blutung, Zysten, Art der Kontrastmittelanreicherung sowie Lokalisation wurden untersucht. Die FA- und ADC-Werte wurden mithilfe von regions of interest (ROIs) im Kontrastmittelanreichernden Tumoranteil, der Nekrose sowie der peritumoralen Region untersucht. Unterschiede wurde anhand von nicht-parametrischen Tests, Entscheidungsbäumen sowie Clusteranalysen statistisch analysiert.
Ergebnisse: Signifikante Unterschiede zwischen den Hirnmetastasen verschiedener Primärtumoren zeigten sich bei den morphologischen Kriterien wie Blutung und Art der Kontrastmittelanreicherung. Zudem zeigten sich signifikante Unterschiede für die ADC-Werte im Kontrastmittelanreichernden Tumoranteil. Primäre ZNS-Lymphome zeigten signifikant niedrigere mediane ADC-Werte im Kontrastmittelanreichernden Tumoranteil (ADClymphom 0,92 [0,83 – 1,07] vs ADCkein_lymphom 1,35 [1,10 – 1,64] P = 0,001). Eine weitere Differenzierung anhand von FA- und ADC-Werten war nicht möglich.
Schlussfolgerung: Hirnmetastasen unterschiedlicher Primärtumoren/primärer ZNS-Lymphome unterscheiden sich hinsichtlich morphologischer Kriterien. Jedoch zeigt sich aufgrund der hohen Variabilität eine niedrige Spezifität. Anhand von FA und ADC ist keine verlässliche Differenzierung unterschiedlicher Hirnmetastasen möglich mit Ausnahme von ZNS-Lymphomen, die niedrigere ADC-Werte zeigen. Somit bleiben die Operation, Biopsie oder das Staging weiterhin notwendig für die Diagnosestellung.
Kernaussagen:
• Histopathologische Subtypen von Hirnmetastasen/ZNS-Lymphomen unterscheiden sich hinsichtlich der Morphologie im MRT
• Primäre ZNS-Lymphome zeigen signifikant niedrigere ADC-Werte
• DTI kann nicht zwischen Subtypen von Hirnmetastasen differenzieren
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References
- 1 Fink KR, Fink JR. Imaging of brain metastases. Surgical neurology international 2013; 4: S209-S219
- 2 Soffietti R, Cornu P, Delattre JY et al. EFNS Guidelines on diagnosis and treatment of brain metastases: report of an EFNS Task Force. European journal of neurology: the official journal of the European Federation of Neurological Societies 2006; 13: 674-681
- 3 Haryu S, Saito A, Inoue M et al. Brain metastasis from invasive thymoma mimicking intracerebral hemorrhage: case report. Neurologia medico-chirurgica 2014; 54: 673-676
- 4 Terada T, Maruo H. Unusual extrahepatic metastatic sites from hepatocellular carcinoma. International journal of clinical and experimental pathology 2013; 6: 816-820
- 5 Kurra V, Krajewski KM, Jagannathan J et al. Typical and atypical metastatic sites of recurrent endometrial carcinoma. Cancer imaging: the official publication of the International Cancer Imaging Society 2013; 13: 113-122
- 6 Chiang IC, Kuo YT, Lu CY et al. Distinction between high-grade gliomas and solitary metastases using peritumoral 3-T magnetic resonance spectroscopy, diffusion, and perfusion imagings. Neuroradiology 2004; 46: 619-627
- 7 Lee EJ, terBrugge K, Mikulis D et al. Diagnostic value of peritumoral minimum apparent diffusion coefficient for differentiation of glioblastoma multiforme from solitary metastatic lesions. Am J Roentgenol 2011; 196: 71-76
- 8 Kickingereder P, Wiestler B, Sahm F et al. Primary central nervous system lymphoma and atypical glioblastoma: multiparametric differentiation by using diffusion-, perfusion-, and susceptibility-weighted MR imaging. Radiology 2014; 272: 843-850
- 9 Duygulu G, Ovali GY, Calli C et al. Intracerebral metastasis showing restricted diffusion: correlation with histopathologic findings. European journal of radiology 2010; 74: 117-120
- 10 Potgieser AR, Wagemakers M, van Hulzen AL et al. The role of diffusion tensor imaging in brain tumor surgery: a review of the literature. Clinical neurology and neurosurgery 2014; 124: 51-58
- 11 Wang S, Kim SJ, Poptani H et al. Diagnostic utility of diffusion tensor imaging in differentiating glioblastomas from brain metastases. AJNR Am J Neuroradiol 2014; 35: 928-934
- 12 General Assembly of the World Medical A. World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. The Journal of the American College of Dentists 2014; 81: 14-18
- 13 Tan WL, Huang WY, Yin B et al. Can diffusion tensor imaging noninvasively detect IDH1 gene mutations in astrogliomas? A retrospective study of 112 cases. AJNR Am J Neuroradiol 2014; 35: 920-927
- 14 Gaujoux R, Seoighe C. A flexible R package for nonnegative matrix factorization. BMC bioinformatics 2010; 11: 367
- 15 Kakeda S, Korogi Y, Hiai Y et al. Detection of brain metastasis at 3T: comparison among SE, IR-FSE and 3D-GRE sequences. Eur Radiol 2007; 17: 2345-2351
- 16 Komada T, Naganawa S, Ogawa H et al. Contrast-enhanced MR imaging of metastatic brain tumor at 3 tesla: utility of T(1)-weighted SPACE compared with 2D spin echo and 3D gradient echo sequence. Magnetic resonance in medical sciences: MRMS: an official journal of Japan Society of Magnetic Resonance in Medicine 2008; 7: 13-21
- 17 Radbruch A, Graf M, Kramp L et al. Differentiation of brain metastases by percentagewise quantification of intratumoral-susceptibility-signals at 3Tesla. European journal of radiology 2012; 81: 4064-4068
- 18 Bauer AH, Erly W, Moser FG et al. Differentiation of solitary brain metastasis from glioblastoma multiforme: a predictive multiparametric approach using combined MR diffusion and perfusion. Neuroradiology 2015; 57: 697-703
- 19 Crisi G, Orsingher L, Filice S. Lipid and macromolecules quantitation in differentiating glioblastoma from solitary metastasis: a short-echo time single-voxel magnetic resonance spectroscopy study at 3 T. Journal of computer assisted tomography 2013; 37: 265-271
- 20 Halshtok Neiman O, Sadetzki S, Chetrit A et al. Perfusion-weighted imaging of peritumoral edema can aid in the differential diagnosis of glioblastoma mulltiforme versus brain metastasis. The Israel Medical Association journal: IMAJ 2013; 15: 103-105
- 21 Gempt J, Bette S, Buchmann N et al. Volumetric Analysis of F-18-FET-PET Imaging for Brain Metastases. World neurosurgery 2015; DOI: 10.1016/j.wneu.2015.07.067.
- 22 Guo AC, Cummings TJ, Dash RC et al. Lymphomas and high-grade astrocytomas: comparison of water diffusibility and histologic characteristics. Radiology 2002; 224: 177-183
- 23 Shim WH, Kim HS, Choi CG et al. Comparison of Apparent Diffusion Coefficient and Intravoxel Incoherent Motion for Differentiating among Glioblastoma, Metastasis, and Lymphoma Focusing on Diffusion-Related Parameter. PloS one 2015; 10: e0134761
- 24 Basser PJ, Pierpaoli C. Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J Magn Reson B 1996; 111: 209-219
- 25 Okamoto K, Ito J, Ishikawa K et al. Diffusion-weighted echo-planar MR imaging in differential diagnosis of brain tumors and tumor-like conditions. Eur Radiol 2000; 10: 1342-1350
- 26 Byrnes TJ, Barrick TR, Bell BA et al. Diffusion tensor imaging discriminates between glioblastoma and cerebral metastases in vivo. NMR Biomed 2011; 24: 54-60
- 27 Lu S, Ahn D, Johnson G et al. Peritumoral diffusion tensor imaging of high-grade gliomas and metastatic brain tumors. AJNR Am J Neuroradiol 2003; 24: 937-941
- 28 Tsougos I, Svolos P, Kousi E et al. Differentiation of glioblastoma multiforme from metastatic brain tumor using proton magnetic resonance spectroscopy, diffusion and perfusion metrics at 3 T. Cancer imaging: the official publication of the International Cancer Imaging Society 2012; 12: 423-436
- 29 Lu S, Ahn D, Johnson G et al. Diffusion-tensor MR imaging of intracranial neoplasia and associated peritumoral edema: introduction of the tumor infiltration index. Radiology 2004; 232: 221-228
- 30 Hayashida Y, Hirai T, Morishita S et al. Diffusion-weighted imaging of metastatic brain tumors: comparison with histologic type and tumor cellularity. AJNR Am J Neuroradiol 2006; 27: 1419-1425
- 31 Mabray MC, Barajas RF, Villanueva-Meyer JE et al. 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 2016; 37: 74-79
- 32 Zacharia TT, Law M, Naidich TP et al. Central nervous system lymphoma characterization by diffusion-weighted imaging and MR spectroscopy. Journal of neuroimaging: official journal of the American Society of Neuroimaging 2008; 18: 411-417
- 33 Kang X, Herron TJ, Woods DL. Regional variation, hemispheric asymmetries and gender differences in pericortical white matter. Neuroimage 2011; 56: 2011-2023
- 34 Wakana S, Caprihan A, Panzenboeck MM et al. Reproducibility of quantitative tractography methods applied to cerebral white matter. Neuroimage 2007; 36: 630-644