Share:
Share this content in WeChat
X
Lecture
The analysis method of intracranial hypointense disease on T2WI
ZHAO Xuemei  QIAN Yinfeng 

Cite this article as: Zhao XM, Qian YF. The analysis method of intracranial hypointense disease on T2WI[J]. Chin J Magn Reson Imaging, 2021, 12(9): 81-87. DOI:10.12015/issn.1674-8034.2021.09.021.


[Abstract] Most of intracranial lesions have hyperintense on T2WI, but part of the intracranial lesions can be characterized hypointense on T2WI, T2WI hypointense is an important imaging features of this kind of disease. On this basis, we give a induction and summary of these diseases, we hope for clinical work to narrow the differential diagnosis, and even can diagnose some diseases. The types of intracranial T2WI hypointense lesions are complex and the pathological basis is different.In this paper, according to the pathology base can be divided into nine categories, including hemoglobin degradation products (deoxyhemoglobin,intracellular methemoglobin hemoglobin and hemosiderin), containing melanin lesions, rich in mucus/protein/cholesterol clefts, rich in cell lesion, mineral deposits, flowing void effect, intracranial pneumatosis, fiber lesions and coagulation necrosis. The clinical lesion manifestations, pathological features and MRI features of the specific diseases under each category were summarized. The clinical features (such as age, sex, clinical manifestations and laboratory examination) and MRI manifestations (including lesion location, morphology, adjacent structure, and peripheral edema, etc.) that have diagnostic and differential diagnostic significance were emphasized. However, it is sometimes difficult to make a definitive diagnosis based on the low signal of T2WI alone. Therefore, the typical features of these diseases in other sequences and enhanced T1WI are also described. Combined with clinical and other MRI sequences, it is helpful for the diagnosis and differential diagnosis of T2WI hypointense lesions. A variety of intracranial lesions may present as T2WI hypointensity, but each of them has its own characteristics. We summarize their imaging findings for diagnosis.
[Keywords] brain;magnetic resonance imaging;T2 weighted imaging;hypointense;diagnose;differential diagnosis;lecture

ZHAO Xuemei   QIAN Yinfeng*  

Department of Radiology, the First Affiliated Hospital of Anhui Medical University, Hefei 230022, China

QianYF, E-mail: 894206876@qq.com

Conflicts of interest   None.

Received  2021-04-15
Accepted  2021-06-11
DOI: 10.12015/issn.1674-8034.2021.09.021
Cite this article as: Zhao XM, Qian YF. The analysis method of intracranial hypointense disease on T2WI[J]. Chin J Magn Reson Imaging, 2021, 12(9): 81-87. DOI:10.12015/issn.1674-8034.2021.09.021.

[1]
Miao YW, Liu T, Wu JL, et al. Susceptibility weighted imaging evaluation of brain iron content of gray nucleus in healthy people[J]. Chin J Med Imaging Technol, 2009, 25(3): 377-379. DOI: 10.3321/j.issn:1003-3289.2009.03.014.
[2]
Smith EE, Rosand J, Greenberg SM. Hemorrhagic stroke[J]. Neuroimaging Clin N Am, 2005, 15(2): 259-272. DOI: 10.1016/j.nic.2005.05.003.
[3]
Altmeyer W, Steven A, Gutierrez J. Use of magnetic resonance in the evaluation of cranial trauma[J]. Magn Reson Imaging Clin N Am, 2016, 24(2): 305-323. DOI: 10.1016/j.mric.2015.11.011.
[4]
Chen YB, Sha DJ, Zhang J. Treatment of hemorrhagic transformation in patients with ischemic stroke[J]. Int J Cerebrovasc Dis, 2017, 25(3): 268-274. DOI: 10.3760/cma.j.issn.1673-4165.2017.03.014
[5]
Ghoneim A, Straiton J, Pollard C, et al. Imaging of cerebral venous thrombosis[J]. Clin Radiol, 2020, 75(4): 254-264. DOI: 10.1016/j.crad.2019.12.009.
[6]
Hoang TPT, Perazzini C, Ngo DHA, et al. Cerebral venous thrombosis: report of 2 cases of hemorrhagic venous infarction[J]. Radiol Case Rep, 2020, 15(8): 1295-1300. DOI: 10.1016/j.radcr.2020.05.009.
[7]
Li XX, Qian HR, Liang QP, et al. Value of 3.0 T magnetic resonance imaging sequences in diagnosis of contusion of brain and sequence optimization[J]. J Pract Med Techniques, 2015, 22(4): 362-364.
[8]
Moenninghoff C, Kraff O, Maderwald S, et al. Diffuse axonal injury at ultra-high field MRI[J]. PLoS One, 2015, 10(3): e0122329. DOI: 10.1371/journal.pone.0122329.
[9]
Liu XY, Cui JZ, Wang Y, et al. Application of diffusion tensor imaging in prognosis evaluation in patients with moderate and severe diffuse axonal injury[J]. Chin J Trauma, 2018, 38(1): 30-34. DOI: 10.3760/cma.j.issn.1001-8050.2018.01.008.
[10]
Wang Y, Zeng XH, Li GX, et al. Analysis of the causes of imaging mis-diagnosis of chronic intracerebral hematoma and its differential diagnosis[J]. Radiol Pratice, 2008, 23(5): 494-497.
[11]
Mouchtouris N, Chalouhi N, Chitale A, et al. Management of cerebral cavernous malformations:from diagnosis to treatment[J]. Sci World J, 2015, 2015: 808314. DOI: 10.1155/2015/808314.
[12]
Chen SN, Sun YY, Wang YY, et al. Recent advance in cerebral amyloid angiopathy related inflammation[J]. Chin J Neuromed, 2016, 15(1): 101-104. DOI: 10.3760/cma.j.issn.1671-8925.2016.01.022.
[13]
Renard D. Cerebral microbleeds: a magnetic resonance imaging review of common and less common causes[J]. Eur J Neurol, 2018, 25(3): 441-450. DOI: 10.1111/ene.13544.
[14]
Haller S, Vernooij MW, Kuijer JPA, et al. Cerebral microbleeds: imaging and clinical significance[J]. Radiology, 2018, 287(1): 11-28. DOI: 10.1148/radiol.2018170803.
[15]
Isiklar I, Leeds NE, Fuller GN, et al. Intracranial metastatic melanoma: correlation between MR imaging characteristics and melanin content[J]. AJR Am J Roentgenol, 1995, 165(6): 1503-1512. DOI: 10.2214/ajr.165.6.7484597.
[16]
Ma Y, Gui Q, Lang S. Intracranial malignant melanoma: a report of 7 cases[J]. Oncol Lett, 2015, 10(4): 2171-2175. DOI: 10.3892/ol.2015.3537.
[17]
Hamidi H, Faizi FR, Rasouly N, et al. CT and MRI Features of pediatric-aged colloid cysts: report of two cases[J]. Case Rep Radiol, 2017, 2017: 2467085. DOI: 10.1155/2017/2467085.
[18]
Wajima D, Yonezawa T, Masui K, et al. Relationship between clinical features and T2-weighted magnetic resonance images in symptomatic rathke cleft cysts[J]. World Neurosurg, 2016, 88: 421-427. DOI: 10.1016/j.wneu.2015.10.018.
[19]
Sridhar K, Vij M. Melanotic intracranial epidermoid: case report and description of a new subtype[J]. Neurol India, 2018, 66(3): 763-766. DOI: 10.4103/0028-3886.232336.
[20]
Wang LJ, Pan ZL, Zhao XW. MR imaging characteristics of cerebellopontine angle medulloblastoma[J]. J Pract Radiol, 2016, 32(4): 506-509. DOI: 10.3969/j.issn.1002-1671.2016.04.004.
[21]
Li XS, Yu SN, Xing J, et al. MRI findings and pathological control of primary intracerebral lymphoma[J]. Chin J Lab Diagn, 2017, 21(8): 1311-1314.
[22]
Wang Y, Zhang B, Luo JY, et al. Features of conventional and functional MRI of primary central nervous system lymphoma[J]. Chin J Interv Imaging Ther, 2017, 14(10): 618-622. DOI: 10.13929/j.1672-8475.201707033.
[23]
Zhang GY, Ma L, Wang D, et al. Diagnostic value of DWI on brain anaplastic ependymoma with glioblastoma multiforme[J]. Chin J Magn Reson Imaging, 2017, 8(11): 812-816. DOI: 10.12015/issn.1674-8034.2017.11.003.
[24]
Patel SH, Poisson LM, Brat DJ, et al. T2-FLAIR mismatch, an imaging biomarker for IDH and 1p/19q status in lower-grade gliomas: a TCGA/TCIA project[J]. Clin Cancer Res, 2017, 23(20): 6078-6085. DOI: 10.1158/1078-0432.CCR-17-0560.
[25]
Hao FL. The research progress of IVIM, DTI, DKI in the classification of gnomas[J]. J Med Imaging, 2018, 28(12): 2104-2106.
[26]
Luo BN. Imaging signs analysis and diagnosis of meningioma[J]. Guangdong Med J, 2017, 38(24): 3708-3712.
[27]
Zheng F, Chen XZ. Status of artificial intelligence in meningioma image[J]. Chin J Magn Reson Imaging, 2020, 11(10): 934-936. DOI: 10.12015/issn.1674-8034.2020.10.025.
[28]
Haroche J, Cohen-Aubart F, Amoura Z. Erdheim-chester disease[J]. Blood, 2020 , 135(16): 1311-1318. DOI: 10.1182/blood.2019002766.
[29]
Starkebaum G, Hendrie P. Erdheim-chester disease[J]. Best Pract Res Clin Rheumatol, 2020, 34(4): 101510. DOI: 10.1016/j.berh.2020.101510.
[30]
aidya T, Mahajan A, Rane S. Multimodality imaging manifestations of Rosai-Dorfman disease[J]. Acta Radiol Open, 2020, 9(8): 2058460120946719. DOI: 10.1177/2058460120946719.
[31]
Oliveira AM, Paulino MV, Vieira APF, et al. Imaging patterns of toxic and metabolic brain disorders[J]. Radiographics, 2019, 39(6): 1672-1695. DOI: 10.1148/rg.2019190016.
[32]
Dragoumi P, O'Callaghan F, Zafeiriou DI. Diagnosis of tuberous sclerosis complex in the fetus[J]. Eur J Paediatr Neurol, 2018, 22(6): 1027-1034. DOI: 10.1016/j.ejpn.2018.08.005.
[33]
Pinto AL, Chen L, Friedman R, et al. Sturge-weber syndrome: brain magnetic resonance imaging and neuropathology findings[J]. Pediatr Neurol, 2016, 58: 25-30. DOI: 10.1016/j.pediatrneurol.2015.11.005.
[34]
Wang JW, Wang M, Wang DH, et al. The application value of susceptibility weighted imaging in measuring brain iron deposition in the clinical assessment of Parkinson's disease[J]. J Pract Radiol, 2016, 2(4): 493-496. DOI: 10.3969/j.issn.1002-1671.2016.04.001.
[35]
Zhong W, Huang Z, Tang X. A study of brain MRI characteristics and clinical features in 76 cases of Wilson's disease[J]. J Clin Neurosci, 2019, 59: 167-174. DOI: 10.1016/j.jocn.2018.10.096.
[36]
Kim D, Choi YJ, Song Y, et al. Thin-section MR imaging for carotid cavernous fistula[J]. AJNR Am J Neuroradiol, 2020, 41(9): 1599-1605. DOI: 10.3174/ajnr.A6757.
[37]
Li J, Jin M, Sun X, et al. Imaging of moyamoya disease and moyamoya syndrome: current status[J]. J Comput Assist Tomogr, 2019, 43(2): 257-263. DOI: 10.1097/RCT.0000000000000834.
[38]
Claus E, Seynaeve P, Ceuppens J, et al. Intracranial solitary fibrous tumor[J]. J Belg Soc Radiol, 2017, 101(1): 11. DOI: 10.5334/jbr-btr.1213.
[39]
Zhanlong M, Haibin S, Xiangshan F, et al. Variable solitary fibrous tumor locations: CT and MR imaging features[J]. Medicine (Baltimore), 2016, 95(13): e3031. DOI: 10.1097/MD.0000000000003031.
[40]
Tuberculosis Branch of Chinese Medical Association. Intracranial tuberculosis imaging credit type expert consensus[J]. Chin J Tuberc Respir Dis, 2015, 38(11): 805-809. DOI: 10.3760/cma.j.issn.1001-0939.2015.11.003.

PREV MRI findings of recurrent ovarian endometrioid adenofibroma with pedicle torsion: a case report
NEXT Imaging research progress in mild cognitive impairment using convolutional neural networks
  



Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn