Peranan Sekuen Susceptibility Weight Imaging (SWI) Pada Pemeriksaan MRI Brain Pada Kasus Tumor
Abstract
The aim of the research is to find out the role of the transverse suspectibility weighted imaging (SWI) sequence in brain MRI examination techniques in tumor cases. The research method used in this research is a qualitative descriptive study that uses a literature study approach to explore, analyze and identify information about how the Susceptibility Weighted Imaging (SWI) sequence plays a role in the Brain MRI examination process in patients who have tumors. The results and discussion of the literature review show: 1) Susceptibility-Weighted Imaging (SWI) on MRI brain has an important role in detecting blood degradation products, calcification and iron accumulation in glioblastoma. SWI allows visualization of small blood vessels, detection of iron, as well as identification of areas of calcification within the tumor, providing a more detailed picture of the nature and malignancy of glioblastoma. The Intratumoral Susceptibility Signal (ITSS) on SWI images is a visual marker associated with microhemorrhage, neoangiogenesis, and calcification, enabling tumor grading based on the frequency and distribution of these signals. In addition, Intralesional Susceptibility Signal (ILSS) also has an important role in differentiating glioblastoma from abscesses and metastases, with high levels of ILSS tending to be associated with tumor severity. Thus, the integration of SWI and ITSS and ILSS analysis can make a significant contribution to the characterization and assessment of the level of malignancy. 2) Susceptibility-Weighted Imaging (SWI) in the diagnosis of glioblastoma has the advantage of providing internal visualization of the tumor with high resolution. SWI is highly sensitive to differences in tissue susceptibility, allows the detection of neovascularization, hemorrhage, and calcification within glioblastoma, and provides detailed information about cerebral vascular anatomy. The advantages of SWI include its ability to image the Intratumoral Susceptibility Signal (ITSS) and Intralesional Susceptibility Signal (ILSS) and increase the visibility of low signal intensity structures. However, its shortcomings, namely sensitivity to artifacts, dependence on susceptibility phenomena, and subjective interpretation are aspects that need to be considered.
References
Paulsen F, Waschke J. Sobotta Atlas of Anatomy. 2018. p. 1376.
Sun H, Liu X, Feng X, Liu C, Zhu N, Gjerswold-Selleck SJ, et al. Substituting Gadolinium in Brain MRI Using DeepContrast. Proc - Int Symp Biomed Imaging. 2020;2020-April(January):908–12.
Narang A, Aggarwal V, Kavita D, Maheshwari C, Bansal P. Cerebral pilocytic astrocytoma with spontaneous intratumoral haemorrhage in the elderly - a rare entity. Rom Neurosurg. 2019 Jun 15;156–9.
Louis DN, Perry A, Wesseling P, Brat DJ, Cree IA, Figarella-Branger D, et al. The 2021 WHO classification of tumors of the central nervous system: A summary. Neuro Oncol. 2021;23(8):1231–51.
Ostrom QT, Francis SS, Barnholtz-Sloan JS. Epidemiology of Brain and Other CNS Tumors. Curr Neurol Neurosci Rep [Internet]. 2021;21(12). Available from: https://doi.org/10.1007/s11910-021-01152-9
Aninditha T, Pratama PY, Sofyan HR, Imran D, Estiasari R, Octaviana F, et al. Adults brain tumor in Cipto Mangunkusumo General Hospital: A descriptive epidemiology. Rom J Neurol Rev Rom Neurol. 2021;20(4):480–4.
Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209–49.
Kang H, Jang S. The diagnostic value of postcontrast susceptibility-weighted imaging in the assessment of intracranial brain neoplasm at 3T. Acta radiol. 2021;62(6):791–8.
Catherine Westbrook JT. MRI In Practice. 1st ed. Vol. 4. 2019. 88–100 p.
Piao S, Luo X, Bao Y, Hu B, Liu X, Zhu Y, et al. An MRI-based joint model of radiomics and spatial distribution differentiates autoimmune encephalitis from low-grade diffuse astrocytoma. Front Neurol. 2022;13.
Elmaoğlu M, Azim Celik. MRI Handbook MR Physics, Patient Positioning and Protocols. 1st editio. Springer New York Dordrecht Heidelberg London. Antalya Turkey: Springer; 2012. 12–26 p.
Torsten B. Moeller ER. MRI Parameters and Positioning,2nd Edition.Thieme. Nuevos sistemas de comunicación e información. 2010. 2013–2015 p.
Parry AH, Wani AH, Shaheen FA, Wani AA, Feroz Im, IlyaS MD. Evaluation of intracranial tuberculomas using diffusion-weighted imaging (DWI), magnetic resonance spectroscopy (MRS) and susceptibility weighted imaging (SWI). Br J Radiol. 2018;91(1091).
Hsu CCT, Watkins TW, Kwan GNC, Haacke EM. Susceptibility-Weighted Imaging of Glioma: Update on Current Imaging Status and Future Directions. J Neuroimaging. 2016;26(4):383–90.
Mohammed W, Xunning H, Haibin S, Jingzhi M. Clinical applications of susceptibility-weighted imaging in detecting and grading intracranial gliomas: A review. Cancer Imaging. 2013;13(2):186–95.
Kim JY, Jung TY, Lee KH, Kim SK. Subependymal Giant Cell Astrocytoma Presenting with Tumoral Bleeding: A Case Report. Brain Tumor Res Treat. 2017;5(1):37.
Phuttharak W, Wannasarnmetha M, Lueangingkasut P, Waraasawapati S, Mukherji SK. Differentiation between germinoma and other pineal region tumors using diffusion-and susceptibility-weighted MRI. Eur J Radiol [Internet]. 2023;159(November 2022):110663. Available from: https://doi.org/10.1016/j.ejrad.2022.110663
Di Ieva A, Le Reste PJ, Carsin-Nicol B, Ferre JC, Cusimano MD. Diagnostic Value of Fractal Analysis for the Differentiation of Brain Tumors Using 3-Tesla Magnetic Resonance Susceptibility-Weighted Imaging. Neurosurgery. 2016;79(6):839–45.
Aker L, Abandeh L, Abdelhady M, Aboughalia H, Vattoth S. Susceptibility-weighted Imaging in Neuroradiology: Practical Imaging Principles, Pearls and Pitfalls. Curr Probl Diagn Radiol [Internet]. 2022;51(4):568–78. Available from: https://doi.org/10.1067/j.cpradiol.2021.05.001
Saini J, Kumar Gupta P, Awasthi A, Pandey CM, Singh A, Patir R, et al. Multiparametric imaging-based differentiation of lymphoma and glioblastoma: using T1-perfusion, diffusion, and susceptibility-weighted MRI. Clin Radiol [Internet]. 2018;73(11):986.e7-986.e15. Available from: https://doi.org/10.1016/j.crad.2018.07.107
Hakim A, Oertel M, Wiest R. Pyogenic brain abscess with atypical features resembling glioblastoma in advanced MRI imaging. Radiol Case Reports [Internet]. 2017;12(2):365–70. Available from: http://dx.doi.org/10.1016/j.radcr.2016.12.007
Falk Delgado A, Van Westen D, Nilsson M, Knutsson L, Sundgren PC, Larsson EM, et al. Diagnostic value of alternative techniques to gadolinium-based contrast agents in MR neuroimaging—a comprehensive overview. Insights Imaging. 2019;10(1):1–15.
McFaline-Figueroa JR, Lee EQ. Brain Tumors. Am J Med [Internet]. 2018;131(8):874–82. Available from: https://doi.org/10.1016/j.amjmed.2017.12.039
Osborn AG, Louis DN, Poussaint TY, Linscott LL, Salzman KL. The 2021 World Health Organization Classification of Tumors of the Central Nervous System: What Neuroradiologists Need to Know. Am J Neuroradiol. 2022;43(7):928–37.
Martucci M, Russo R, Schimperna F, D’Apolito G, Panfili M, Grimaldi A, et al. Magnetic Resonance Imaging of Primary Adult Brain Tumors: State of the Art and Future Perspectives. Biomedicines. 2023;11(2).
Catherine Westbrook. Handbook of MRI Technique. Fourth Edi. Garsington Road, Oxford, OX4 2DQ U, editor. Vol. 4, John Wiley & Sons, Ltd. The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK; 2014. 88–100 p.
Fu JH, Chuang TC, Chung HW, Chang HC, Lin HS, Hsu SS, et al. Discriminating pyogenic brain abscesses, necrotic glioblastomas, and necrotic metastatic brain tumors by means of susceptibility-weighted imaging. Eur Radiol. 2015;25(5):1413–20.
Lai PH, Chung HW, Chang HC, Fu JH, Wang PC, Hsu SH, et al. Susceptibility-weighted imaging provides complementary value to diffusion-weighted imaging in the differentiation between pyogenic brain abscesses, necrotic glioblastomas, and necrotic metastatic brain tumors. Vol. 117, European Journal of Radiology. 2019. p. 56–61.
