THE ROLE OF DIFFUSION-WEIGHTED MRI IN DIFFERENTIAL DIAGNOSIS AND PREDICTION OF SURVIVAL IN PATIENTS WITH BRAIN METASTASES

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  • Authors: Byvaltsev V.A.1,2,3,4,5, Stepanov I.A.1, Kichigin A.I.1,5, Kanigin V.V.5,6, Stupak V.V.7
  • Affiliations:
    1. Irkutsk State Medical University
    2. Railway Clinical Hospital on the station Irkutsk-Passazhirskiy of Russian Railways Ltd.
    3. Irkutsk Scientifi c Center of Surgery and Traumatology
    4. Irkutsk State Academy of Postgraduate Education
    5. Institute of Nuclear Physics n.a. G.I. Budker of the SB RAS
    6. Novosibirsk State Medical University
    7. Novosibirsk Research Institute of Traumatology and Orthopaedics n.a. Ya. L. Tsivyan
  • Issue: Vol 72, No 6 (2017)
  • Pages: 442-449
  • Section: ONCOLOGY: CURRENT ISSUES
  • URL: https://vestnikramn.spr-journal.ru/jour/article/view/890
  • DOI: https://doi.org/10.15690/vramn890
  • Cite item

Abstract


Background: Brain metastases are observed in up to 40% of all intracranial tumors. Some types of metastatic tumors cause difficulties in differential diagnosis, since they have similar signal characteristics with other pathological entities in neuroimaging. Obviously, the additional diagnostic methods to determine the prognosis and tactics of further management of this group of patients should be implemented.

Aim: To study the role of diffusion-weighted magnetic resonance imaging (MRI) in differential diagnostics and predicting the survival rate in patients with brain metastases. Materials and methods: The study included data from MRI and morphological studies of 23 patients with brain metastases. The obtained values of the apparent diffusion coefficient (ADC) of tumors were compared with their histological type, cell density, and the index of proliferative activity Ki-67. In addition, the influence of ADC values on the overall survival rate was assessed.

Results: A reliable inverse correlation of ADC values and the index of proliferative activity for various types of brain metastases (r=-0.74, p=0.014) was established. The dependence of ADC values and overall survival rate of patients with metastases in the brain is presented. The overall survival rate in patients with an ADC value greater than 947.2 mm2/sec was 9.8 months (95% CI: 8.6−11.3), and with ADC value less than 947.2 mm2/sec ― 6.4 months (95% CI: 3.7−9.1).

Conclusion: The technique of diffusion-weighted MRI plays an important role in the differential diagnosis of brain metastases; it can be used as a tool of comprehensive preoperative assessment when planning the surgery and as a prognostic factor of overall survival rate for this group of patients. 


V. A. Byvaltsev

Irkutsk State Medical University; Railway Clinical Hospital on the station Irkutsk-Passazhirskiy of Russian Railways Ltd.; Irkutsk Scientifi c Center of Surgery and Traumatology; Irkutsk State Academy of Postgraduate Education; Institute of Nuclear Physics n.a. G.I. Budker of the SB RAS

Email: byval75vadim@yandex.ru
ORCID iD: 0000-0003-4349-7101

Russian Federation

Доктор медицинских наук, главный нейрохирург Дирекции здравоохранения ОАО «РЖД»; руководитель Центра нейрохирургии ДКБ на ст. Иркутск-Пассажирский ОАО «РЖД-Медицина»; заведующий курсом нейрохирургии ИГМУ; заведующий научно-клиническим отделом нейрохирургии и ортопедии ИНЦХТ; профессор кафедры травматологии, ортопедии и нейрохирургии ИГМАПО; ведущий научный сотрудник ИЯФ им. Г.И. Будкера.

664082, Иркутск, ул. Боткина, д. 10, тел.: +7 (3952) 63-85-28, SPIN-код: 5996-6477

I. A. Stepanov

Irkutsk State Medical University

Author for correspondence.
Email: edmoilers@mail.ru
ORCID iD: 0000-0001-9039-9147

Russian Federation

Аспирант курса нейрохирургии ИГМУ.

664003, Иркутск, ул. Красного Восстания, д. 14, тел.: +7 (3952) 63-88-30, SPIN-код: 5485-5316

A. I. Kichigin

Irkutsk State Medical University; Institute of Nuclear Physics n.a. G.I. Budker of the SB RAS

Email: sam@211.ru
ORCID iD: 0000-0001-8763-2905

Russian Federation

аспирант курса нейрохирургии Иркутского медицинского университета, стажер-исследователь Института ядерной физики им. Г.И. Будкера СО РАН, SPIN-код: 4321-2422

V. V. Kanigin

Institute of Nuclear Physics n.a. G.I. Budker of the SB RAS; Novosibirsk State Medical University

Email: kanigin@mail.ru
ORCID iD: 0000-0003-3533-6076

Russian Federation

Врач-нейрохирург, кандидат медицинских наук, доцент, заведующий лабораторией медико-биологических проблем бор-нейтронзахватной терапии НГУ.

 

630090, Новосибирск, ул. Пирогова, д. 2, тел.: +7 (3833) 63-43-33, SPIN-код: 4211-2417

V. V. Stupak

Novosibirsk Research Institute of Traumatology and Orthopaedics n.a. Ya. L. Tsivyan

Email: vstupak@niito.ru
ORCID iD: 0000-0002-6074-6248

Russian Federation

Доктор медицинских наук, профессор, руководитель клиники нейрохирургии ННИИТО им. Я.Л. Цивьяна.

 

630091, Новосибирск, ул. Фрунзе, д. 17, тел.: +7 (3833) 63-31-31, SPIN-код: 4111-2527

  1. Caffo M, Barresi V, Caruso G, et al. Innovative therapeutic strategies in the treatment of brain metastases. Int J Mol Sci. 2013;14(1):2135–2174. doi: 10.3390/ijms14012135.
  2. Бывальцев В.А., Сороковиков В.А., Панасенков С.Ю., и др. Редкий случай интравентрикулярного рецидива метастаза меланомы, удаленного с использованием эндоскопической ассистенции // Вопросы нейрохирургии им. Н.Н. Бурденко. ― 2010. ― №2 ― С. 29–33. [Byvaltsev VA, Sorokovikov VA, Panasenkov SYu, et al. A rare case of intraventricular recurrence of melanoma metastasis treated by endoscope-assisted surgery. Zh Vopr Neirokhir Im NN Burdenko. 2010;(2):29−32. (In Russ).].
  3. Kyritsis AP, Markoula S, Levin VA. A systematic approach to the management of patients with brain metastases of known or unknown primary site. Cancer Chemother Pharmacol. 2012;69(1):1–13. doi: 10.1007/s00280-011-1775-9.
  4. El-Habashy SE, Nazief AM, Adkins CE, et al. Novel treatment strategies for brain tumors and metastases. Pharm Pat Anal. 2014;3(3):279–296. doi: 10.4155/ppa.14.19.
  5. Egelhoff JC, Ross JS, Modic MT, et al. MR imaging of metastatic GI adenocarcinoma in brain. AJNR Am J Neuroradiol. 1992;13(4):1221–1224.
  6. Carrier DA, Mawad ME, Kirkpatrick JB, Schmid MF. Metastatic adenocarcinoma to the brain: MR with pathologic correlation. AJNR Am J Neuroradiol. 1994;15(1):155–159.
  7. Duygulu G, Ovali GY, Calli C, et al. Intracerebral metastasis showing restricted diffusion: correlation with histopathologic findings. Eur J Radiol. 2010;74(1):117–120. doi: 10.1016/j.ejrad.2009.03.004.
  8. 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(7):1419–1425.
  9. Tang Y, Dundamadappa SK, Thangasamy S, et al. Correlation of apparent diffusion coefficient with Ki-67 proliferation index in grading meningioma. AJR Am J Roentgenol. 2014;202(6):1303–1308. doi: 10.2214/AJR.13.11637.
  10. Бывальцев В.А., Степанов И.А., Кичигин А.И., Антипина С.Л. Возможности диффузионно-взвешенной МРТ в дифференциальной диагностике степени злокачественности менингиом головного мозга // Сибирский онкологический журнал. ― 2017. ― Т.16. ― №3 ― С. 19–26. [Byvaltsev VA, Stepanov IA, Kichigin AI, Antipina SL. Diffusion-weighted MRI in the differential diagnosis of brain meningiomas. Siberian journal of oncology. 2017;16(3):19–26. (In Russ).] doi: 10.21294/1814-4861-2017-16-3-19-26.
  11. Ginat DT, Mangla R, Yeaney G, Wang HZ. Correlation of diffusion and perfusion MRI with Ki-67 in high-grade meningiomas. AJR Am J Roentgenol. 2010;195(6):1391–1395. doi: 10.2214/AJR.10.4531.
  12. Fatima Z, Motosugi U, Waqar AB, et al. Associations among q-space MRI, diffusion-weighted MRI and histopathological parameters in meningiomas. Eur Radiol. 2013;23(8):2258–2263. doi: 10.1007/s00330-013-2823-0.
  13. Boxerman JL, Rogg JM, Donahue JE, et al. Preoperative MRI evaluation of pituitary macroadenoma: imaging features predictive of successful transsphenoidal surgery. AJR Am J Roentgenol. 2010;195(3):720–728. doi: 10.2214/Ajr.09.4128.
  14. Barajas RF Jr, Rubenstein JL, Chang JS, et al. Diffusion-weighted MR imaging derived apparent diffusion coefficient is predictive of clinical outcome in primary central nervous system lymphoma. AJNR Am J Neuroradiol. 2010;31(1):60–66. doi: 10.3174/ajnr.A1750.
  15. Zakaria R, Das K, Radon M, et al. Diffusion-weighted MRI characteristics of the cerebral metastasis to brain boundary predicts patient outcomes. BMC Med Imaging. 2014;14:26. doi: 10.1186/1471-2342-14-26.
  16. Lee CC, Wintermark M, Xu ZY, et al. Application of diffusion-weighted magnetic resonance imaging to predict the intracranial metastatic tumor response to gamma knife radiosurgery. J Neurooncol. 2014;118(2):351–361. doi: 10.1007/s11060-014-1439-9.
  17. Тоноян А.С., Пронин И.Н., Пицхелаури Д.И., и др. Диффузионно-куртозисная МРТ в диагностике злокачественности глиом головного мозга // Медицинская визуализация. ― 2015. ― №1 ― С. 7–18. [Tonoyan AS, Pronin IN, Pitskhelauri DI, et al. Diffusion kurtosis imaging in diagnostics of brain glioma malignancy. Meditsinskaya vizualizatsiya. 2015;(1):7–18. (In Russ).]
  18. Byvaltsev VA, Stepanov IA, Kalinin AA, Shashkov KV. Diffusion-weighted magnetic resonance tomography in the diagnosis of intervertebral disk degeneration. Biomed Eng (NY). 2016;50(4):253–256. doi: 10.1007/s10527-016-9632-0.
  19. Пронин И.Н., Тоноян А.С., Шульц Е.И., и др. Диффузионно-куртозисная МРТ в оценке Ki-67/MIB-1 LI глиальных опухолей // Медицинская визуализация. ― 2016. ― №5 ― С. 6–17. [Pronin IN, Tonoyan AS, Shults EI, et al. Diffusion kurtosis MRI in assesment of Ki-67/MIB-1 LI in gliomas. Meditsinskaya vizualizatsiya. 2016;(5):6–17. (In Russ).]
  20. Nakajo M, Kajiya Y, Kaneko T, et al. FDG PET/CT and diffusion-weighted imaging for breast cancer: prognostic value of maximum standardized uptake values and apparent diffusion coefficient values of the primary lesion. Eur J Nucl Med Mol Imaging. 2010;37(11):2011–2020. doi: 10.1007/s00259-010-1529-7.
  21. Ohno Y, Koyama H, Yoshikawa T, et al. Diffusion-weighted MRI versus 18F-FDG PET/CT: performance as predictors of tumor treatment response and patient survival in patients with non-small cell lung cancer receiving chemoradiotherapy. AJR Am J Roentgenol. 2012;198(1):75–82. doi: 10.2214/AJR.11.6525.
  22. Curvo-Semedo L, Lambregts DMJ, Maas M, et al. Diffusion-weighted MRI in rectal cancer: apparent diffusion coefficient as a potential noninvasive marker of tumor aggressiveness. J Magn Reson Imaging. 2012;35(6):1365–1371. doi: 10.1002/jmri.23589.
  23. Teixidor P, Arráez MÁ, Villalba G, et al. Safety and efficacy of 5-aminolevulinic acid for high grade glioma in usual clinical practice: a prospective cohort study. PLoS One. 2016;11(2):e0149244. doi: 10.1371/journal.pone.0149244.
  24. Abercrombie M. Estimation of nuclear population from microtome sections. Anat Rec. 1946;94:239–247. doi: 10.1002/ar.1090940210.
  25. Cox DR, Snell EJ. Analysis of binary data. 2nd ed. London, UK: Chapman & Hall; 1989.
  26. Kaplan EL, Meier P. Nonparametric estimation from incomplete observations. J Am Stat Assoc. 1958;53(282):457–481. doi: 10.2307/2281868.
  27. Ramli N, Khairy AM, Seow P, et al. Novel application of chemical shift gradient echo in- and opposed-phase sequences in 3 T MRI for the detection of H-MRS visible lipids and grading of glioma. European Radiology. 2016;26:2019–2029. doi: 10.1007/s00330-015-4045-0.
  28. 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. doi: 10.1002/(SICI)1522-2586(199901)9:1<53::AID-JMRI7>3.0.CO;2-2.
  29. Fan GG, Deng QL, Wu ZH, Guo QY. Usefulness of diffusion/perfusion-weighted MRI in patients with non-enhancing supratentorial brain gliomas: a valuable tool to predict tumour grading? Br J Radiol. 2006;79(944):652–658. doi: 10.1259/bjr/25349497.
  30. Langley RR, Fidler IJ. The seed and soil hypothesis revisited ― the role of tumor-stroma interactions in metastasis to different organs. Int J Cancer. 2011;128(11):2527–2535. doi: 10.1002/ijc.26031.
  31. Moorman AM, Vink R, Heijmans HJ, et al. The prognostic value of tumour-stroma ratio in triple-negative breast cancer. Eur J Surg Oncol. 2012;38(4):307–313. doi: 10.1016/j.ejso.2012.01.002.
  32. Inwald EC, Klinkhammer-Schalke M, Hofstadter F, et al. Ki-67 is a prognostic parameter in breast cancer patients: results of a large population-based cohort of a cancer registry. Breast Cancer Res Treat. 2013;139(2):539–552. doi: 10.1007/s10549-013-2560-8.
  33. Rosell R, Tian Y, Ma Z, et al. Clinicopathological and prognostic value of Ki-67 expression in bladder cancer: a systematic review and meta-analysis. PLoS One. 2016;11(7):e0158891. doi: 10.1371/journal.pone.0158891.
  34. Zheng G, Cheng X, Wang L, et al. [Correlation of MRI apparent diffusion coefficient with molecular marker Ki-67 in gastric cancer. (In Chinese).] Zhonghua Wei Chang Wai Ke Za Zhi. 2017;20(7):803–808.
  35. Huang ZQ, Xu XQ, Meng XJ, et al. Correlations between ADC values and molecular markers of Ki-67 and HIF-1 alpha in hepatocellular carcinoma. Eur J Radiol. 2015;84(12):2464–2469. doi: 10.1016/j.ejrad.2015.09.013.

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