medvisМедицинская визуализацияMedical Visualization1607-07632408-9516RDS-Media Ltd.medvis-176Research ArticleГОЛОВА И ШЕЯHEAD AND NECKДиффузионно-куртозисная МРТ в диагностике злокачественности глиом головного мозгаDiffusion Kurtosis Imaging in Diagnostics of Brain Glioma MalignancyТоноянАрам СергеевичTonoyanAram Sergeevichatonoyan@nsi.ruПронинИгорь НиколаевичProninIgor Nikolaevichnoemail@neicon.ruПицхелауриДавид ИльичPitskhelauriDavid Ilichnoemail@neicon.ruХачановаНаталья ВалерьевнаKhachanovaNatalya Valerevnanoemail@neicon.ruФадееваЛюдмила МихайловнаFadeevaLjudmila Mihajlovnanoemail@neicon.ruПогосбекянЭдуард ЛеонидовичPogosbekyanEduard Leonidovichnoemail@neicon.ruЗахароваНаталья ЕвгеньевнаZakharovaNatalya Evgenevnanoemail@neicon.ruПотаповАлександр АлександровичPotapovAleksandr Aleksandrovichnoemail@neicon.ruШульцЕвгений ИгоревичShultsEvgeniy Igorevichnoemail@neicon.ruБыкановАндрей ЕгоровичBykanovAndrey Egorovichnoemail@neicon.ruЯковленкоЮрий ГеоргиевичYakovlenkoYuriy Georgievichnoemail@neicon.ruКорниенкоВалерий НиколаевичKornienkoValeriy Nikolaevichnoemail@neicon.ruФГБНУ “Научно-исследовательский институт нейрохирургии им. акад. Н.Н. Бурденко”РоссияN.N. Burdenko Neurosurgery InstituteRussian FederationФГБНУ “Научно-исследовательский институт нейрохирургии им. акад. Н.Н. Бурденко”; ГБОУ ВПО РНИМУ им. Н.И. Пирогова МЗ РФРоссияN.N. Burdenko Neurosurgery InstituteRussian Federation20152802201501718Copyright © Тоноян А.С., Пронин И.Н., Пицхелаури Д.И., Хачанова Н.В., Фадеева Л.М., Погосбекян Э.Л., Захарова Н.Е., Потапов А.А., Шульц Е.И., Быканов А.Е., Яковленко Ю.Г., Корниенко В.Н., 20152015Тоноян А.С., Пронин И.Н., Пицхелаури Д.И., Хачанова Н.В., Фадеева Л.М., Погосбекян Э.Л., Захарова Н.Е., Потапов А.А., Шульц Е.И., Быканов А.Е., Яковленко Ю.Г., Корниенко В.Н.Tonoyan A.S., Pronin I.N., Pitskhelauri D.I., Khachanova N.V., Fadeeva L.M., Pogosbekyan E.L., Zakharova N.E., Potapov A.A., Shults E.I., Bykanov A.E., Yakovlenko Y.G., Kornienko V.N.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://medvis.rdsmedia.ru/jour/article/view/176

Цель исследования: оценить возможности диффузионно-куртозисной МРТ в диагностике злокачественности глиом. Материал и методы. В исследование включен 61 пациент (27 (44%) глиом низкой, 14 (23%) глиом III и 20 (33%) глиом IV степени злокачественности). Абсолютные и нормализованные параметры диффузионного тензора (средняя, аксиальная и радиальная диффузия, фракционная и относительная анизотропия) и диффузионного куртозиса (средний, аксиальный и радиальный куртозис, куртозисная анизотропия) были сравнены между наиболее злокачественными участками глиом различной степени злокачественности (p < 0,05, тест Колмогорова-Смирнова). Результаты. Между глиомами высокой и низкой степени злокачественности все диффузионные параметры, кроме абсолютных фракционной и относительной анизотропии, отличались статистически значимо, а максимальные чувствительность и специфичность были получены для нормализованных среднего куртозиса (85,19 и 85,29%) и радиального куртозиса (85,19 и 85,29%). Между глиомами III и IV степени злокачественности все диффузионные параметры, кроме абсолютных и нормализованных значений фракционной и относительной анизотропии, отличались статистически значимо, а максимальные чувствительность и специфичность были получены для абсолютного среднего куртозиса (92,86 и 90,00%). Между глиомами III и глиомами низкой степени злокачественности статистически значимо отличались нормализованные средний, аксиальный и радиальный куртозис, а максимальные чувствительность и специфичность были получены для нормализованных среднего куртозиса (77,78 и 78,57%) и аксиального куртозиса (77,78 и 78,57%). Заключение. В дифференциации между группами параметры диффузионного куртозиса показали более точные результаты по сравнению с параметрами диффузионного тензора.

Purpose. To assess the diagnostic efficacy of diffusion kurtosis inaging in grading of brain gliomas. Material and methods. Absolute and normalized to the contralateral normal appearing white matter values of diffusion tensor parameters (mean, axial and radial diffusivities, fractional and relative anisotropies) and diffusion kurtosis parameters (mean, axial and radial kurtosis, kurtosis anisotropy) of tumors were compared in the most malignant solid parts of 27 (44%) low grade gliomas, 14 (23%) grade-III and 20 (33%) grade-IV gliomas (p < 0.05 significance level, Kolmogorov-Smirnov test). Results. Absolute and normalized values of all diffusion parameters (except of absolute fractional and relative anisotropies) were significantly different between high and low grade gliomas, and maximal sensitivity and specificity were found for normalized values of mean kurtosis (85,19% and 85,29%) and radial kurtosis (85,19% and 85,29%). Absolute and normalized values of all diffusion parameters (except of absolute and normalized values of fractional and relative anisotropies) differed significantly among grade-III and grade-IV gliomas, and maximal sensitivity and specificity were found for absolute mean kurtosis (92.86% and 90.00%). Only normalized values of mean, axial and radial kurtosis were significantly different between low grade and grade-III gliomas, and maximal sensitivity and specificity were found for normalized values of mean kurtosis (77.78% and 78.57%) and axial kurtosis (77.78% and 78.57%). Conclusion. Diffusion kurtosis imaging demonstrated a promising potential to differentiate among glioma grades. Kurtosis parameters better differed between gliomas grades compared with diffusion tensor parameters.

диффузионный тензордиффузионный куртозисглиомазлокачественностьdiffusion tensordiffusion kurtosisgliomamalignancyReferencesLouis D.N.,Ohgaki H., Wiestler O.D. et al. The 2007 WHO classification of tumours of the central nervous system. Acta Neuropathol. 2007; 114 (2): 97-109.Louis D.N.,Ohgaki H., Wiestler O.D. et al. The 2007 WHO classification of tumours of the central nervous system. Acta Neuropathol. 2007; 114 (2): 97-109.Lam W.W., Poon W.S., Metreweli C. Diffusion MR imaging in glioma: does it have any role in the pre-operation determination of grading of glioma? Clin. Radiol. 2002; 57 (3): 219-225.Lam W.W., Poon W.S., Metreweli C. Diffusion MR imaging in glioma: does it have any role in the pre-operation determination of grading of glioma? Clin. Radiol. 2002; 57 (3): 219-225.Tropine A., Vucurevic G., Delani P et al. Contribution of diffusion tensor imaging to delineation of gliomas and glioblastomas. J. Magn. Reson. Imaging. 2004; 20 (6): 905-912.Tropine A., Vucurevic G., Delani P et al. Contribution of diffusion tensor imaging to delineation of gliomas and glioblastomas. J. Magn. Reson. Imaging. 2004; 20 (6): 905-912.Goebell E., Paustenbach S., Vaeterlein O. et al. Low-grade and anaplastic gliomas: differences in architecture evaluated with diffusion-tensor MR imaging. Radiology. 2006; 239 (1): 217-222.Goebell E., Paustenbach S., Vaeterlein O. et al. Low-grade and anaplastic gliomas: differences in architecture evaluated with diffusion-tensor MR imaging. Radiology. 2006; 239 (1): 217-222.Zonari P., Baraldi P., Crisi G. Multimodal MRI in the characterization of glial neoplasms: the combined role of single-voxel MR spectroscopy, diffusion imaging and echo-planar perfusion imaging. Neuroradiology. 2007; 49 (10): 795-803.Zonari P., Baraldi P., Crisi G. Multimodal MRI in the characterization of glial neoplasms: the combined role of single-voxel MR spectroscopy, diffusion imaging and echo-planar perfusion imaging. Neuroradiology. 2007; 49 (10): 795-803.Raab P., Hattingen E., Franz K. et al. Cerebral gliomas: diffusional kurtosis imaging analysis of microstructural differences. Radiology. 2010; 254 (3): 876-881.Raab P., Hattingen E., Franz K. et al. Cerebral gliomas: diffusional kurtosis imaging analysis of microstructural differences. Radiology. 2010; 254 (3): 876-881.Van Cauter S., Veraart J., Sijbers J. et al., Gliomas: diffusion kurtosis MR imaging in grading. Radiology. 2012; 263 (2): 492-501.Van Cauter S., Veraart J., Sijbers J. et al., Gliomas: diffusion kurtosis MR imaging in grading. Radiology. 2012; 263 (2): 492-501.Poot D.H., den Dekker A.J., Achten E. et al. Optimal experimental design for diffusion kurtosis imaging. IEEE Trans. Med. Imaging. 2010; 29 (3): 819-829.Poot D.H., den Dekker A.J., Achten E. et al. Optimal experimental design for diffusion kurtosis imaging. IEEE Trans. Med. Imaging. 2010; 29 (3): 819-829.Тоноян А.С., Пронин И.Н., Пицхелаури Д.И. и др. Диффузионно-куртозисная магнитно-резонансная томография - новый метод оценки негауссовской диффузии в нейрорадиологии. Медицинская физика. 2014; 4: 57-63.Тоноян А.С., Пронин И.Н., Пицхелаури Д.И. и др. Диффузионно-куртозисная магнитно-резонансная томография - новый метод оценки негауссовской диффузии в нейрорадиологии. Медицинская физика. 2014; 4: 57-63.Van Cauter S., De Keyzer F., Sima D.M. et al. Integrating diffusion kurtosis imaging, dynamic susceptibility- weighted contrast-enhanced MRI, and short echo time chemical shift imaging for grading gliomas. Neuro-Oncol. 2014; 16 (7): 1010-1021.Van Cauter S., De Keyzer F., Sima D.M. et al. Integrating diffusion kurtosis imaging, dynamic susceptibility- weighted contrast-enhanced MRI, and short echo time chemical shift imaging for grading gliomas. Neuro-Oncol. 2014; 16 (7): 1010-1021.Kleihues P., Ohgaki H. Primary and secondary glioblastomas: from concept to clinical diagnosis. Neuro-Oncol. 1999; 1 (1): 44-51.Kleihues P., Ohgaki H. Primary and secondary glioblastomas: from concept to clinical diagnosis. Neuro-Oncol. 1999; 1 (1): 44-51.Falangola M.F., Jensen J.H., Babb J.S. et al. Age-related non-Gaussian diffusion patterns in the prefrontal brain. J. Magn. Reson. Imaging. 2008; 28 (6): 1345-1350.Falangola M.F., Jensen J.H., Babb J.S. et al. Age-related non-Gaussian diffusion patterns in the prefrontal brain. J. Magn. Reson. Imaging. 2008; 28 (6): 1345-1350.Lobel U., Sedlacik J., Gullmar D. et al. Diffusion tensor imaging: the normal evolution of ADC, RA, FA, and eigenvalues studied in multiple anatomical regions of the brain. Neuroradiology. 2009; 51 (4): 253-263.Lobel U., Sedlacik J., Gullmar D. et al. Diffusion tensor imaging: the normal evolution of ADC, RA, FA, and eigenvalues studied in multiple anatomical regions of the brain. Neuroradiology. 2009; 51 (4): 253-263.Kang X., Herron T.J., Woods D.L. Regional variation, hemispheric asymmetries and gender differences in pericortical white matter. Neuroimage. 2011; 56 (4): 2011-2023.Kang X., Herron T.J., Woods D.L. Regional variation, hemispheric asymmetries and gender differences in pericortical white matter. Neuroimage. 2011; 56 (4): 2011-2023.Latt J., Nilsson M., Wirestam R. et al. Regional values of diffusional kurtosis estimates in the healthy brain. J. Magn. Reson. Imaging. 2013; 37 (3): 610-618.Latt J., Nilsson M., Wirestam R. et al. Regional values of diffusional kurtosis estimates in the healthy brain. J. Magn. Reson. Imaging. 2013; 37 (3): 610-618.Wieshmann U.C., Clark C.A., Symms M.R. et al. Reduced anisotropy of water diffusion in structural cerebral abnormalities demonstrated with diffusion tensor imaging. Magn. Reson. Imaging. 1999; 17 (9): 1269-1274.Wieshmann U.C., Clark C.A., Symms M.R. et al. Reduced anisotropy of water diffusion in structural cerebral abnormalities demonstrated with diffusion tensor imaging. Magn. Reson. Imaging. 1999; 17 (9): 1269-1274.Zimmerman R.D. Is there a role for diffusion-weighted imaging in patients with brain tumors or is the “bloom off the rose”? Am. J. Neuroradiol. 2001; 22 (6): 1013-1014.Zimmerman R.D. Is there a role for diffusion-weighted imaging in patients with brain tumors or is the “bloom off the rose”? Am. J. Neuroradiol. 2001; 22 (6): 1013-1014.Kono K.,Inoue Y., Nakayama K. et al. The role of diffusion-weighted imaging in patients with brain tumors. Am. J. Neuroradiol. 2001; 22 (6): 1081-1088.Kono K.,Inoue Y., Nakayama K. et al. The role of diffusion-weighted imaging in patients with brain tumors. Am. J. Neuroradiol. 2001; 22 (6): 1081-1088.Guo A.C., Cummings T.J., Dash R.C. et al. Lymphomas and high-grade astrocytomas: comparison of water diffusibility and histologic characteristics. Radiology. 29. 2002; 224 (1): 177-183.Guo A.C., Cummings T.J., Dash R.C. et al. Lymphomas and high-grade astrocytomas: comparison of water diffusibility and histologic characteristics. Radiology. 29. 2002; 224 (1): 177-183.Beppu T., Inoue T., Shibata Y. et al. Measurement of fractional anisotmpy using diffusion tensor MRI in supratentorial astrocytic tumors. J. Neurooncol. 2003; 63 (2): 30. 109-116.Beppu T., Inoue T., Shibata Y. et al. Measurement of fractional anisotmpy using diffusion tensor MRI in supratentorial astrocytic tumors. J. Neurooncol. 2003; 63 (2): 30. 109-116.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 (1): 221-228.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 (1): 221-228.Inoue T., Ogasawara K., Beppu T. et al. Diffusion tensor imaging for preoperative evaluation of tumor grade in gliomas. Clin. Neurol. Neurosurg. 2005; 107 (3): 174-180.Inoue T., Ogasawara K., Beppu T. et al. Diffusion tensor imaging for preoperative evaluation of tumor grade in gliomas. Clin. Neurol. Neurosurg. 2005; 107 (3): 174-180.Higano S., Yun X., Kumabe T. et al. Malignant astrocytic tumors: clinical importance of apparent diffusion coefficient in prediction of grade and prognosis. Radiology. 2006; 241 (3): 839-846.Higano S., Yun X., Kumabe T. et al. Malignant astrocytic tumors: clinical importance of apparent diffusion coefficient in prediction of grade and prognosis. Radiology. 2006; 241 (3): 839-846.Lee E.J., Lee S.K., Agid R. et al. Preoperative grading of presumptive low-grade astrocytomas on MR imaging: diagnostic value of minimum apparent diffusion coefficient. Am. J. Neuroradiol. 2008; 29 (10): 1872-1877.Lee E.J., Lee S.K., Agid R. et al. Preoperative grading of presumptive low-grade astrocytomas on MR imaging: diagnostic value of minimum apparent diffusion coefficient. Am. J. Neuroradiol. 2008; 29 (10): 1872-1877.Yuan W., Holland S.K., Jones B.V. et al. Characterization of abnormal diffusion properties of supratentorial brain tumors: a preliminary diffusion tensor imaging study. J. Neurosurg. Pediatr. 2008; 1 (4): 263-269.Yuan W., Holland S.K., Jones B.V. et al. Characterization of abnormal diffusion properties of supratentorial brain tumors: a preliminary diffusion tensor imaging study. J. Neurosurg. Pediatr. 2008; 1 (4): 263-269.Kinoshita M., Hashimoto N., Goto T. et al. Fractional anisotmpy and tumor cell density of the tumor core show positive correlation in diffusion tensor magnetic resonance imaging of malignant brain tumors. Neuroimage. 2008; 43 (1): 29-35.Kinoshita M., Hashimoto N., Goto T. et al. Fractional anisotmpy and tumor cell density of the tumor core show positive correlation in diffusion tensor magnetic resonance imaging of malignant brain tumors. Neuroimage. 2008; 43 (1): 29-35.Kang Y., Choi S.H., Kim Y.J. et al. Gliomas: Histogram analysis of apparent diffusion coefficient maps with standard- or high-b-value diffusion-weighted MR imagingcorrelation with tumor grade. Radiology. 2011; 261 (3): 882-890.Kang Y., Choi S.H., Kim Y.J. et al. Gliomas: Histogram analysis of apparent diffusion coefficient maps with standard- or high-b-value diffusion-weighted MR imagingcorrelation with tumor grade. Radiology. 2011; 261 (3): 882-890.Liu X., Tian W., Kolar B. et al. MR diffusion tensor and perfusion-weighted imaging in preoperative grading of supratentorial nonenhancing gliomas. Neuro-Oncol. 2011; 13 (4): 447-455.Liu X., Tian W., Kolar B. et al. MR diffusion tensor and perfusion-weighted imaging in preoperative grading of supratentorial nonenhancing gliomas. Neuro-Oncol. 2011; 13 (4): 447-455.White M.L., Zhang Y., Yu F. et al. Diffusion tensor MR imaging of cerebral gliomas: evaluating fractional anisotmpy characteristics. Am. J. Neuroradiol. 2011; 32 (2): 374-381.White M.L., Zhang Y., Yu F. et al. Diffusion tensor MR imaging of cerebral gliomas: evaluating fractional anisotmpy characteristics. Am. J. Neuroradiol. 2011; 32 (2): 374-381.Hilario A., Ramos A., Perez-Nunez A. et al. The added value of apparent diffusion coefficient to cerebral blood volume in the preoperative grading of diffuse gliomas. Am. J. Neuroradiol. 2012; 33 (4): 701-707.Hilario A., Ramos A., Perez-Nunez A. et al. The added value of apparent diffusion coefficient to cerebral blood volume in the preoperative grading of diffuse gliomas. Am. J. Neuroradiol. 2012; 33 (4): 701-707.Ma L., Song Z.J. Differentiation between low-grade and high-grade glioma using combined diffusion tensor imaging metrics. Clin. Neurol. Neurosurg. 2013; 115 (12): 2489-2495.Ma L., Song Z.J. Differentiation between low-grade and high-grade glioma using combined diffusion tensor imaging metrics. Clin. Neurol. Neurosurg. 2013; 115 (12): 2489-2495.Alexiou G.A., Zikou A., Tsiouris S. et al. Correlation of diffusion tensor, dynamic susceptibility contrast MRI and (99m)Tc-Tetrofosmin brain SPECT with tumour grade and Ki-67 immunohistochemistry in glioma. Clin. Neurol. Neurosurg. 2014; 116: 41-45.Alexiou G.A., Zikou A., Tsiouris S. et al. Correlation of diffusion tensor, dynamic susceptibility contrast MRI and (99m)Tc-Tetrofosmin brain SPECT with tumour grade and Ki-67 immunohistochemistry in glioma. Clin. Neurol. Neurosurg. 2014; 116: 41-45.Server A., Graff B.A., Josefsen R. et al. Analysis of diffusion tensor imaging metrics for gliomas grading at 3T. Eur. J. Radiol. 2014; 83 (3): e156-e165.Server A., Graff B.A., Josefsen R. et al. Analysis of diffusion tensor imaging metrics for gliomas grading at 3T. Eur. J. Radiol. 2014; 83 (3): e156-e165.Budde M.D., Xie M., Cross A.H. et al. Axial diffusivity is the primary correlate of axonal injury in the experimental autoimmune encephalomyelitis spinal cord: a quantitative pixelwise analysis. J. Neurosci. 2009; 29 (9): 2805-2813.Budde M.D., Xie M., Cross A.H. et al. Axial diffusivity is the primary correlate of axonal injury in the experimental autoimmune encephalomyelitis spinal cord: a quantitative pixelwise analysis. J. Neurosci. 2009; 29 (9): 2805-2813.Hui E.S., Cheung M.M., Qi L. et al. Towards better MR characterization of neural tissues using directional diffusion kurtosis analysis. Neuroimage. 2008; 42 (1): 122-134.Hui E.S., Cheung M.M., Qi L. et al. Towards better MR characterization of neural tissues using directional diffusion kurtosis analysis. Neuroimage. 2008; 42 (1): 122-134.Veraart J., Poot D.H., Van Hecke W. et al. More accurate estimation of diffusion tensor parameters using diffusion Kurtosis imaging. Magn. Reson. Med. 2011; 65 (1): 138-145.Veraart J., Poot D.H., Van Hecke W. et al. More accurate estimation of diffusion tensor parameters using diffusion Kurtosis imaging. Magn. Reson. Med. 2011; 65 (1): 138-145.Veraart J., Van Hecke W., Sijbers J. Constrained maximum likelihood estimation of the diffusion kurtosis tensor using a Rician noise model. Magn. Reson. Med. 2011; 66 (3): 678-686.Veraart J., Van Hecke W., Sijbers J. Constrained maximum likelihood estimation of the diffusion kurtosis tensor using a Rician noise model. Magn. Reson. Med. 2011; 66 (3): 678-686.

The authors declare that there are no conflicts of interest present.