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1Academic Journal
Authors: Keikha M., Karbalaei M.
Source: Russian Journal of Infection and Immunity; Vol 11, No 6 (2021); 1185-1189 ; Инфекция и иммунитет; Vol 11, No 6 (2021); 1185-1189 ; 2313-7398 ; 2220-7619
Subject Terms: ATLL, HAM/TSP, HTLV-1, LIRs, malignancy, immunity, злокачественность, иммунитет
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2Academic Journal
Authors: Ursu, Dănis, Railean, Silvia, Ciupac, Sergiu, Lupan, Roman, Porosencov, Egor
Source: Bulletin of the Academy of Sciences of Moldova. Medical Sciences; Vol. 70 No. 2 (2021): Medical Sciences; 75-79 ; Buletinul Academiei de Științe a Moldovei. Științe medicale; Vol. 70 Nr. 2 (2021): Ştiinţe medicale; 75-79 ; Вестник Академии Наук Молдовы. Медицина; Том 70 № 2 (2021): Медицина; 75-79 ; 1857-0011 ; 10.52692/1857-0011.2021.2-70
Subject Terms: опухоль, полость рта, дети, злокачественность, tumor, oral cavity, children, malignancies, tumoră, cavitate orală, copil, malignitate
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Relation: https://bulmed.md/bulmed/article/view/3317/3317; https://bulmed.md/bulmed/article/view/3317
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3Academic Journal
Authors: Yulia Sergeevna Galchina, Andrey Vyacheslavovich Glotov, Sergey Sergeevich Pyanikin, Юлия Сергеевна Гальчина, Андрей Вячеславович Глотов, Сергей Сергеевич Пьяникин
Source: Medical Visualization; № 3 (2016); 35-49 ; Медицинская визуализация; № 3 (2016); 35-49 ; 2408-9516 ; 1607-0763
Subject Terms: malignancy, мультифазовая компьютерная томография, грайд, злокачественность, clear cell renal carcinoma, Contrast-enhanced MDCT, Grade
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Relation: https://medvis.vidar.ru/jour/article/view/279/280; Каприн А.Д., Старинский В.В., Петров Г.В. Злокачественные новообразования в России в 2014 году. М.: МНИОИ им. П.А. Герцена филиал ФГБУ “НМИРЦ” Минздрава России, 2016. 250 с.; Москвина Л.В., Андреева Ю.Ю., Мальков П.Г. и др. Клинически значимые морфологические параметры почечно-клеточного рака. Онкология. 2013; 4: 34-39.; Дубровский А.Ч., Климова С.М., Суконко О.Г. и др. Морфологическая классификация эпителиальных опухолей паренхимы почки. РНПЦ ОМР им. Н.Н. Александрова, г. Минск. Онкологический журнал. 2014; 4 (2): 68-73.; Алексеев Б.Я., Франк Г.А., Андреева Ю.Ю., Калпинский А.С. Прогностические факторы у больных почечно-клеточным раком и роль онкофага в улучшении выживаемости после хирургического лечения. Онкоурология. 2009: 2: 7-14.; Атдуев В.А., Амоев З.В., Данилов А.А. и др. Над диафрагмальные и интравентрикулярные опухолевые тромбы нижней полой вены при раке почки. Тюменский медицинский журнал. 2015; 17 (1): 22-25.; Зуков Р.А. Эпидемиологические особенности и факторы риска почечно-клеточного рака. Сибирское медицинское обозрение. 2013; 5: 15-21.; Тюляндин С.А., Носов Д.А., Переводчикова Н.И. Минимальные клинические рекомендации Европейского общества медицинской онкологии (ESMO). М.: РОНЦ им. НН Блохина РАМН, 2010: 191-196.; Fuhrman S.A., Lasky L.C., Limas C. Prognostic significance of morphologic parameters in renal cell carcinoma. Am. J. Surg. Pathol. 1982; 6 (7): 655-656.; Eble J.N., Sauter G., Epstein J.I., Sesterhenn I.A. Pathology and Genetics of Tumours of the Urinary System and Male Genital Organs. Lyon: IARCPress, 2004: 23-26.; Андреева Ю.Ю., Франк Г.А. Опухоли почки. Морфологичекская диагностика и генетика: Руководство. М.: РМАПО, 2011. 66 с.; Bretheau D., Lechevallier E., de Fromont M. et al. Prognostic value of nuclear grade of renal cell carcinoma. Cancer. 1995; 76 (12): 2543-2549.; Zisman A., Pantuck A.J., Dorey F. et al. Mathematical model to predict individual survival for patients with renal cell carcinoma. J. Clin. Oncol. 2002; 20 (5): 1368-1374.; Zisman A., Pantuck A.J., Wieder J. et al. Risk group assessment and clinical outcome algorithm to predict the natural history of patients with surgically resected renal cell carcinoma. J. Clin. Oncol. 2002; 20 (23): 4559-4566.; Fuhrman S.A., Lasky L.C., Limas C. Prognostic significance of morphologic parameters in renal cell carcinoma. Am. J. Surg. Pathol. 1982; 6 (7): 655-663.; Birnbaum B.A., Bosniak M.A., Krinsky G.A. et al. Renal cell carcinoma: correlation of CT findings with nuclear morphologic grading in100 tumors. Abdom. Imaging. 1994; 19: 262-266.; Zhu Y.H., Wang X., Zhang J. et al. Low enhancement on multiphase contrast-enhanced CT images: an independent predictor of the presence of high tumor grade of clear cell renal cell carcinoma. Am. J. Roentgenol. 2014; 203 (3): W295-W300.; Huhdanpaa H., Hwang D., Cen S. et al. CT prediction of the Fuhrman grade of clear cell renal cell carcinoma (RCC): towards the development of computer-assisted diagnostic method. Abdom. Imaging. 2015; 40 (8): 3168-3174.; Choi S.Y., Sung D.J., Yang K.S. et al. Small (; Delahunt B., Cheville, J.C., Martignoni G. et al. The International Society of Urological Pathology (ISUP) grading system for renal cell carcinoma and other prognostic parameters. Am. J. Surg. Pathol. 2013; 37 (10): 1490-1504.; Hemmerlein B., Kugler A., Ozisik R. et al. Vascular endothelial growth factor expression angiogenesis, and necrosis in renal cell carcinomas. Virchows Arch. 2001; 439: 645-652.; Delahunt B., McKenney J.K., Lohse C.M. et al. A novel grading system for clear cell renal cell carcinoma incorporating tumor necrosis. Am. J. Surg. Pathol. 2013; 37: 311-322.; Yao M., Tabuchi H., Nagashima Y. et al. Gene expression analysis of renal carcinoma: adipose differentiation-related protein as a potential diagnostic and prognostic biomarker for clear-cell renal carcinoma. J. Pathol. 2005; 205: 377-387.; Yao M., Huang Y., Shioi K. et al. Expression of adipose differentiation-related protein: a predictor of cancerspecific survival in clear cell renal carcinoma. Clin. Cancer Res. 2007; 13: 152-116.; Yu M., Wang H., Zhao J. et al. Expression of CIDE proteinsin clear cell renal cell carcinoma and their prognostic significance Mol. Cell. Biochem. 2013; 378: 145-151.; Pierorazio P.M., Hyams E., Tsai S.S. et al. Multiphasic enhancement patterns of small renal masses (≤4 cm) on preoperative computed tomography: utility for distinguishing subtypes of renal cell carcinoma, angiomyo lipoma, and oncocytoma. Urology. 2013; 81 (6): 1265-1272.; https://medvis.vidar.ru/jour/article/view/279
Availability: https://medvis.vidar.ru/jour/article/view/279
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4Academic Journal
Authors: I. N. Pronin, A. S. Tonoyan, E. I. Shults, L. M. Fadeeva, N. E. Zakharova, S. A. Goryainov, A. E. Bykanov, D. I. Pitskhelauri, A. A. Potapov, И. Н. Пронин, А. С. Тоноян, Е. И. Шульц, Л. М. Фадеева, Н. Е. Захарова, С. А. Горяйнов, А. Е. Быканов, Д. И. Пицхелаури, А. А. Потапов
Contributors: Российский научный фонд
Source: Medical Visualization; № 5 (2016); 6-17 ; Медицинская визуализация; № 5 (2016); 6-17 ; 2408-9516 ; 1607-0763
Subject Terms: злокачественность, diffusion kurtosis, glioma, malignancy grade, диффузионный куртозис, глиома
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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., Keyzer F., Sima D.M. et al. Integrating diffusion kurtosis imaging, dynamic susceptibilityweighted contrast-enhanced MRI, and short echo time chemical shift imaging for grading gliomas. Neuro Oncol. 2014; 16 (7): 1010–1021.; Тоноян А. С., Пронин И. Н., Пицхелаури Д. И. и др. Диффузионно-куртозисная МРТ в диагностике злокачественности глиом головного мозга. Медицинская визуализация. 2015; 1: 7–18 Tonoyan A.S., Pronin I.N., Pitskhelauri D.I. et al. Diffusion kurtosis imaging in diagnostics of brain glioma malignancy. Meditsinskaya vizualizatsiya. 2015; 1: 7–18. (In Russian); Tietze A., Hansen M.B., Ostergaard L. et al. Mean Diffusional Kurtosis in Patients with Glioma: Initial Results with a Fast Imaging Method in a Clinical Setting. Am. J. Neuroradiol. 2015; 36 (8): 1472–1478.; Beppu T., Inoue T., Shibata Y. et al. Measurement of fractional anisotropy using diffusion tensor MRI in supratentorial astrocytic tumors. J. Neurooncol. 2003; 63 (2): 109–116.; 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.; Stadlbauer A., Ganslandt O., Buslei R. et al. Gliomas: histopathologic evaluation of changes in directionality and magnitude of water diffusion at diffusion-tensor MR imaging. Radiology. 2006; 240 (3): 803–810.; 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.; Kinoshita M., Hashimoto N., Goto T. et al. Fractional anisotropy 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.; Yin Y., Tong D., Liu X. et al. Correlation of apparent diffusion coefficient with Ki-67 in the diagnosis of gliomas. Zhongguo Yi Xue Ke Xue Yuan Xue Bao. 2012; 34 (5): 503–508.; Fudaba H., Shimomura T., Abe T. et al. Comparison of multiple parameters obtained on 3T pulsed arterial spinlabeling, diffusion tensor imaging, and MRS and the Ki-67 labeling index in evaluating glioma grading. Am. J. Neuroradiol. 2014; 35 (11): 2091–2098.; 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.; Тоноян А.С., Пронин И.Н., Пицхелаури Д.И. и др. Корреляция диффузионно-куртозисной МРТ с пролифе ративной активностью глиом головного мозга. Вопросы нейрохирургии. 2015; 79 (6): 5–14. Tonoyan A.S., Pronin I.N., Pitskhelauri D.I. et al. Correlation of DK-MRI and glioma's prolifaration activity. Voprosi Neurohirurgii. 2015; 79 (6): 5–14. (In Russian); Jiang R., Jiang J., Zhao L. et al. Diffusion kurtosis imaging can efficiently assess the glioma grade and cellular proliferation. Oncotarget. 2015; 6 (39): 42380–42393.; Smith S.M., Jenkinson M., Woolrich M.W. et al. Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage. 2004; 23, Suppl. 1: S208–219.; Woolrich M.W., Jbabdi S., Patenaude B. et al. Bayesian analysis of neuroimaging data in FSL. Neuroimage. 2009; 45 (1, Suppl.): S173–186.; Jenkinson M., Beckmann C.F., Behrens T.E. et al., FSL. Neuroimage, 2012; 62 (2): 782–790.; Leemans A., Jones D.K. The B-matrix must be rotated when correcting for subject motion in DTI data. Magn. Reson. Med. 2009; 61 (6): 1336–1349.; McGibney G., Smith M.R. An unbiased signal-to-noise ratio measure for magnetic resonance images. Med. Phys. 1993; 20 (4): 1077–1078.; Miller A.J., Joseph P.M. The use of power images to perform quantitative analysis on low SNR MR images. Magn. Reson. Imaging. 1993; 11 (7): 1051–1056.; Jensen J.H., Helpern J.A. MRI quantification of nonGaussian water diffusion by kurtosis analysis. NMR Biomed. 2010; 23 (7): 698–710.; Leemans A., Sijbers J., Jones D.K. Explore DTI: A graphical toolbox for processing, analyzing, and visualizing diffusion MR data, in Proceedings of the 17th Scientific Meeting, International Society for Magnetic Resonance in Medicine. Honolulu. 2009; 3537.; Tax C.M., Otte W.M., Max A. et al. REKINDLE: robust extraction of kurtosis INDices with linear estimation. Magn. Reson. Med. 2015; 73 (2): 794–808.; Yushkevich P.A., Piven J., Hazlett H.C. et al. User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage. 2006; 31 (3): 1116–1128.; 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.; 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.; 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.; Тоноян А.С., Пронин И.Н., Пицхелаури Д.И. и др. Диффузионно-куртозисная магнитно-резонансная томография: новый метод характеристики структурной организации мозгового вещества (предварительные результаты у здоровых добровольцев). Радиология-практика. 2015; 1: 57–67. Tonoyan A.S., Pronin I.N., Pitskhelauri D.I. et al. Diffusion Kurtosis Magnetic Resonance Imaging: a New Method of Brain Microstructure Characterization (Preliminary Results in Healthy Volunteers). Radiologiya-practika. 2015; 1: 57–67. (In Russian); Тоноян А.С., Пронин И.Н., Пицхелаури Д.И. и др. Корреляция диффузионно-куртозисной МРТ с пролифер тивной активностью глиом головного мозга. Вопросы нейрохирургии. 2015; 79 (6): 5–14. Tonoyan A.S., Pronin I.N., Pitskhelauri D.I. et al. correlation of DK-MRI and glioma's prolifaration activity. Voprosi Neurohirurgii. 2015; 79 (6): 5–14. (In Russian); Kiss R., Dewitte O., Decaestecker C. et al. The combined determination of proliferative activity and cell density in the prognosis of adult patients with supratentorial high-grade astrocytic tumors. Am. J. Clin. Pathol. 1997; 107 (3): 321–331.; Sugahara T., Korogi Y., Kochi M. et al. Usefulness of diffusion-weighted MRI with echo-planar technique in the evaluation of cellularity in gliomas. J. Magn. Reson. Imaging. 1999; 9 (1): 53–60.; Kono K., Inoue Y., Nakayama K. et al. The role of diffusionweighted imaging in patients with brain tumors. Am. J. Neuroradiol. 2001; 22 (6): 1081–1088.; 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.; 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.; Beppu T., Inoue T., Shibata Y. et al. Fractional anisotropy value by diffusion tensor magnetic resonance imaging as a predictor of cell density and proliferation activity of glioblastomas. Surg. Neurol. 2005; 63 (1): 56–61.; 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.; Wang S., Kim S., Chawla S. et al. Differentiation between glioblastomas and solitary brain metastases using diffusion tensor imaging. Neuroimage. 2009; 44 (3): 653–660.; 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.; White M.L., Zhang Y., Yu.F. et al. Diffusion tensor MR imaging of cerebral gliomas: evaluating fractional anisotropy 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.; 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.; 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): e156–165.; 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. Tonoyan A.S., Pronin I.N., Pitskhealuri D.I. et al. Diffusion kurtosis magnetic resonance imaging – a new method of non-Gaussian diffusion assessment in neuroradiology. Meditsinskaya Fizika. 2014; 4: 57–63. (In Russian); 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.; Schiffer D., Dutto A., Cavalla P. et al. Prognostic factors in oligodendroglioma. Can. J. Neurol. Sci. 1997; 24 (4): 313–319.; Schiffer D., Dutto A., Cavalla P. et al. The prognostic role of vessel productive changes and vessel density in oligodendroglioma. J. 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Availability: https://medvis.vidar.ru/jour/article/view/326
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5Academic Journal
Authors: Aram Sergeevich Tonoyan, Igor Nikolaevich Pronin, David Ilich Pitskhelauri, Natalya Valerevna Khachanova, Ljudmila Mihajlovna Fadeeva, Eduard Leonidovich Pogosbekyan, Natalya Evgenevna Zakharova, Aleksandr Aleksandrovich Potapov, Evgeniy Igorevich Shults, Andrey Egorovich Bykanov, Yuriy Georgievich Yakovlenko, Valeriy Nikolaevich Kornienko, Арам Сергеевич Тоноян, Игорь Николаевич Пронин, Давид Ильич Пицхелаури, Наталья Валерьевна Хачанова, Людмила Михайловна Фадеева, Эдуард Леонидович Погосбекян, Наталья Евгеньевна Захарова, Александр Александрович Потапов, Евгений Игоревич Шульц, Андрей Егорович Быканов, Юрий Георгиевич Яковленко, Валерий Николаевич Корниенко
Source: Medical Visualization; № 1 (2015); 7-18 ; Медицинская визуализация; № 1 (2015); 7-18 ; 2408-9516 ; 1607-0763
Subject Terms: malignancy, диффузионный куртозис, глиома, злокачественность, diffusion tensor, diffusion kurtosis, glioma
File Description: application/pdf
Relation: https://medvis.vidar.ru/jour/article/view/176/177; 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.; 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.; 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. 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6Academic Journal
Subject Terms: ХЕМОДЕКТОМА, ЭЛЕКТРОННО-МИКРОСКОПИЧЕСКАЯ РАДИОАВТОГРАФИЯ, ИММУНОГИСТОХИМИЯ, ЗЛОКАЧЕСТВЕННОСТЬ
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7Academic Journal
Authors: Чхиквадзе, Т.
Subject Terms: отечный рак молочной железы, злокачественность, лимфогенное и гематогенное метастазирование, прогноз, диагностика, лечение
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8Academic Journal
Source: Вестник Российского государственного медицинского университета.
Subject Terms: ХЕМОДЕКТОМА, ЭЛЕКТРОННО-МИКРОСКОПИЧЕСКАЯ РАДИОАВТОГРАФИЯ, ИММУНОГИСТОХИМИЯ, ЗЛОКАЧЕСТВЕННОСТЬ, 3. Good health
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9Academic Journal
Source: Вестник Российского научного центра рентгенорадиологии Минздрава России.
Subject Terms: отечный рак молочной железы, злокачественность, лимфогенное и гематогенное метастазирование, прогноз, диагностика, лечение, 3. Good health
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10Academic Journal
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11Academic Journal
Authors: Сенютович, Роман Васильович, Унгурян, Володимир Петрович, Олійник, Едуард Валентинович, Гушул, Іван Ярославович
Subject Terms: гліома, низька злоякісність, тактика лікування, глиома, низкая злокачественность, тактика лечения, glioma, low-grade, tactic of treatment
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