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Detection of Hemorrhagic Hypointense Foci in the Brain on Susceptibility-Weighted Imaging

Posted Aug 31, 2007 Updated Apr 7, 2023
By Masuma Akter MD , Toshinori Hirai MD , Yasuhiro Hiai RT , Mika Kitajima MD , Masanori Komi RT , Ryuji Murakami MD , Hirofumi Fukuoka MD , Akira Sasao MD , Ryo Toya MD , E. Mark Haacke PhD , Mutsumasa Takahashi MD , Teruyuki Hirano MD , Yutaka Kai MD , Motohiro Morioka MD , Kiyotoshi Hamasaki MD , Jun-ichi Kuratsu MD , Yasuyuki Yamashita MD
8 min read

Rationale and Objectives

To determine the sensitivity of susceptibility-weighted imaging (SWI) for depicting hemorrhagic hypointense foci of the brain in comparison with gradient-recalled echo (GRE)- and GRE-type single-shot echo-planar imaging (GREI, GRE-EPI), and to assess the basic characteristics of the susceptibility effect by using a phantom.

Materials and Methods

We prospectively examined 16 patients (9 males, 7 females, aged 10–74 years, mean 43 years) with hypointense foci using SWI, GREI, and GRE-EPI at a 1.5-T magnetic resonance (MR) unit. The contrast-to-noise ratio (CNR), sensitivity to small hypointese foci, and artifacts were evaluated. To assess the basic characteristics of SWI, we performed a phantom study using different concentrations of superparamagnetic iron oxide (SPIO).

Results

The CNR of lesions was significantly greater for SWI than the other images ( P < .0001). SWI detected the greatest number of small hypointense foci, even in the near-skull-base and infratentorial regions. Quantitative and qualitative analyses in our clinical and phantom studies demonstrated that the degree of artifacts was similar with SWI and GREI.

Conclusion

SWI was best for detecting small hemorrhagic hypointense foci. Artifacts of SWI were similar to GREI.

The detection of hemorrhage and its breakdown products is important for the diagnosis, management, and prognostic prediction for a variety of intracranial diseases ( ). Cerebral microhemorrhage may be a marker of cerebral small-vessel disease and cerebral amyloid angiopathy and might indicate a higher risk for future intracerebral hemorrhage after thrombolysis or the use of antithrombotic drugs ( ). The detection of hemorrhage on magnetic resonance (MR) images is useful for the grading of gliomas ( ). In patients with diffuse axonal injury, the presence of hemorrhage may result in a poor prognosis ( ).

Among various imaging techniques for depicting intracranial microhemorrhage, two-dimensional T2*-weighted gradient-recalled echo imaging (GREI) is considered a reliable technique ( ). In the detection of small hemorrhagic foci in the supratentorial white matter, however, GRE-type single-shot echo-planar imaging (GRE-EPI) may be more sensitive than GREI ( ).

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Materials and methods

Clinical Study

Patients

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MR Imaging

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Table 1

Imaging Parameters of GREI, GRE-EPI, and SWI

GRE GRE-EPI SWI TR/TE/excitations 500/15/1 1000/46/1 56/40/1 Flip angle 15° 90° 25° Matrix 192 × 256 148 × 256 192 × 256 Field of view (mm) 200 × 265 200 × 265 200 × 265 Section thickness (mm) 5 5 10 ⁎ Slice gap (mm) 1 1 0 Acquisition type 2D 2D 3D Acquisition time 3 min, 27 s 4 s 4 min, 20 s

Note. SWI: susceptibility-weighted imaging, GREI: gradient-recalled echo imaging, GRE-EPI: GRE-type single-shot echo-planar imaging

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Image Interpretation

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Quantitative Analysis

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Qualitative Analysis

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Phantom Study

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Figure 1, Schema of a phantom consisting of 8 plastic chambers with different iron concentrations. Chambers No. 1-8 were filled with 2% wt/wt agar containing different iron concentrations (0, 0.1, 0.2, 0.4, 0.6, 0.8, 1.2, 1.6 mmol/L) of superparamagnetic iron oxide (SPIO). They were embedded in a 2% wt/wt agar bath.

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Quantitative Analysis

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Qualitative Analysis

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Results

Clinical Study

Quantitative Analysis

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Figure 2, Comparison of the contrast-to-noise ratio (CNR) of hypointense foci in the clinical study. The mean CNR ± standard deviation was 24.2 ± 10.1 for GRI-EPI, 29.1 ± 14.3 for GREI, and 60.9 ± 18.7 for SWI. SWI manifested significantly higher CNRs than GREI and GRE-EPI ( P < .0001). SWI: susceptibility-weighted imaging, GREI: gradient-recalled echo imaging, GRE-EPI: GRE-type single-shot echo-planar imaging.

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Qualitative Analysis

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Figure 3, Comparison of qualitative evaluation of lesions equal to or larger than 5 mm. In terms of lesion detection, the mean score ± standard deviation (SD) was 2.8 ± 0.5 for GRI-EPI, 2.9 ± 0.6 for GREI, and 3.0 ± 0 for SWI. There were no significant differences in the mean scores of the three imaging techniques. For lesion delineation, the mean score ± SD was 2.2 ± 0.6 for GRI-EPI, 3.0 ± 0 for GREI, and 2.4 ± 0.4 for SWI. GREI had significantly higher scores than the other techniques. There was no significant difference between GRE-EPI and SWI with respect to the mean scores. For artifacts, the mean score ± SD was 1.8 ± 0.7 for GRI-EPI, 3.0 ± 0 for GREI, and 2.8 ± 0.8 for SWI. GREI and SWI had significantly higher scores (less severe artifacts) than GRE-EPI; there was no significant difference between SWI and GREI.

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Table 2

Comparison of Number of Small Lesion (<5.0 mm) Detected by the Three Sequences

GREI GRE-EPI SWI Only by GREI Only by GRE-EPI Only by SWI Supratentorial 287 303 419 5 0 116 Near skull base 18 11 30 2 0 15 Infratentorial 28 25 51 2 0 28

Note. SWI: susceptibility-weighted imaging, GREI: gradient-recalled echo maging, GRE-EPI: GRE-type single-shot echo-planar imaging.

Figure 4, A 62-year-old man with multiple cavernous angiomas. Upper and lower images in left and middle portions are continuous two 5-mm-thick GREI and GRE-EPI images, respectively. An image in right portion is a 10-mm-thick SW image corresponding to the level of the GREI and GRE-EPI images. ( A ) Small hypointense foci are more clearly seen on the SW image. The delineation of the lesion (diameter > 5 mm) near the left trigone of the lateral ventricle ( arrows ) exhibits a ‘blooming’ effect on GRE-EPI and SW images. A small hypointense lesion adjacent to this lesion is seen only on GRE images ( arrowhead ). Delineation of the lesion on GRE, GRE-EPI, and SWI images was scored as grade 3, 0, and 0, respectively. Small arrows indicate areas that had been operated previously. ( B ) In regions adjacent to the skull base or the posterior fossa, small hypointense foci are more pronounced on the SWI image. GRE, GRE-EPI, and SWI images were scored for artifacts as grade 3, 1, and 2, respectively.

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Phantom Study

Quantitative Analysis

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Figure 5, SPIO concentration-standardized CNR curves. GRE-EPI manifested the largest standardized CNRs at low SPIO concentrations, followed by SWI. GREI had the lowest standardized CNRs at low SPIO concentrations.

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Qualitative Analysis

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Figure 6, Phantom with eight plastic chambers containing different concentrations of SPIO. At low SPIO concentrations, GRE-EPI and SWI showed hypointensity in the chambers more clearly than GRE. In chambers at 0.2 mmol/L, GRE-EPI, SWI, and GREI were scored as grade 3, 2, and 1, respectively. With respect to the degree of overall artifacts, GRE-EPI was more severe than the other imaging techniques. Moderate distortion on the outer margin of the agar bath is seen only on GRE-EPI. Small hypointense dots in the agar bath (small bubbles) are more pronounced on SWI.

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Discussion

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Conclusion

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References

  • 1. Greenberg S., O’Donnell H., Schaefer P., et. al.: MRI detection of new hemorrhages: Potential marker of progression in cerebral amyloid angiopathy. Neurology 1999; 22: pp. 1135-1138.

  • 2. Kidwell C.S., Saver J.L., Villablanca J.P., et. al.: Magnetic resonance imaging detection of microbleeds before thrombolysis: An emerging application. Stroke 2002; 33: pp. 95-98.

  • 3. Nighoghossian N., Hermier M., Adeleine P., et. al.: Old microbleeds are a potential risk factor for cerebral bleeding after ischemic stroke. Stroke 2002; 33: pp. 735-742.

  • 4. Koennecke H.C.: Cerebral microbleeds on MRI: Prevalence, associations, and potential clinical implications. Neurology 2006; 66: pp. 165-171.

  • 5. Bagley L.J., Grossman R.I., Judy K.D., et. al.: Gliomas: Correlation of magnetic susceptibility artifact with histologic grade. Radiology 1997; 202: pp. 511-516.

  • 6. Paterakis K., Karantanas A.H., Komnos A., Volikas Z.: Outcome of patients with diffuse axonal injury: The significance and prognostic value of MRI in the acute phase. J Trauma 2000; 49: pp. 1071-1075.

  • 7. Atlas S.W., Mark A.S., Grossman R.I., et. al.: Intracranial hemorrhage: Gradient-echo MR imaging at 1.5 T. Radiology 1988; 168: pp. 803-807.

  • 8. Seidenwurm D., Meng T.K., Kowalski H.K.: Intracranial hemorrhagic lesions: Evaluation with spin-echo and gradient-refocused MR imaging at 0.5 and 1.5 T. Radiology 1989; 172: pp. 189-194.

  • 9. Liang L., Korogi Y., Sugahara T., et. al.: Detection of intracranial hemorrhage with susceptibility-weighted MR sequences. AJNR Am J Neuroradiol 1999; 20: pp. 1527-1534.

  • 10. Reichenbach J.R., Venkatesan R., Schillinger D.J., et. al.: Small vessels in the human brain: MR venography with deoxyhemoglobin as an intrinsic contrast agent. Radiology 1997; 204: pp. 272-277.

  • 11. Reichenbach J.R., Barth M., Haacke E.M., et. al.: High-resolution MR venography at 3.0 T. J Comput Assist Tomogr 2000; 24: pp. 949-957.

  • 12. Lee B.C., Vo K.D., Kido D.K., et. al.: MR high-resolution blood oxygenation level dependent venography of occult (low-flow) vascular lesions. AJNR Am J Neuroradiol 1999; 20: pp. 1239-1242.

  • 13. Tong K.A., Ashwal S., Holshouser B.A., et. al.: Hemorrhagic shearing lesions in children and adolescents with post traumatic diffuse axonal injury: Improved detection and initial results. Radiology 2003; 227: pp. 332-339.

  • 14. Wycliffe N.D., Choe J., Holshouser B., et. al.: Reliability in detection of hemorrhage in acute stroke by a new three-dimensional gradient recalled echo susceptibility-weighted imaging technique compared to computed tomography: A retrospective study. J Magn Reson Imaging 2004; 20: pp. 372-377.

  • 15. Sehgal V., Delproposto Z., Haacke E.M., et. al.: Susceptibility-weighted imaging to visualize blood products and improve tumor contrast in the study of brain masses. J Magn Reson Imaging 2006; 24: pp. 41-51.

  • 16. Greer D.M., Koroshetz W.J., Cullen S., et. al.: Magnetic resonance imaging improves detection of intracerebral hemorrhage over computed tomography after intra-arterial thrombolysis. Stroke 2004; 35: pp. 491-495.

  • 17. Sehgal V., Delproposto Z., Haacke E.M., et. al.: Clinical applications of neuroimaging with susceptibility-weighted imaging. J Magn Reson Imaging 2005; 22: pp. 439-450.

  • 18. Gomori J.M., Grossman R.I.: Mechanisms responsible for the MR appearance and evolution of intracranial hemorrhage. Radiographics 1988; 8: pp. 427-440.

  • 19. Kim J.K., Kucharczyk W., Henkelman R.M.: Cavernous hemangiomas: Dipolar susceptibility artifacts at MR imaging. Radiology 1993; 187: pp. 735-741.

  • 20. Xu Y., Haacke E.: A new iterative phase correction method for segmented EPI to reduce image distortion.2005. abstract 290.

  • 21. Trattnig S., Pinker K., Ba-Ssalamah A., Nobauer-Huhmann I.M.: The optimal use of contrast agents at high field MRI. Eur Radiol 2006; 16: pp. 1280-1287.

  • 22. Henkelman M., Kucharczyk W.: Optimization of gradient-echo MR for calcium detection. AJNR Am J Neuroradiol 1994; 15: pp. 465-472.

  • 23. Yamada M., Imakita S., Sakuma T.: Intracranial calcification on gradient-echo phase image: Depiction of diamagnetic susceptibility. Radiology 1996; 198: pp. 171-178.

  • 24. Lin W., Mukherjee P., An H., et. al.: Improving high-resolution MR bold venographic imaging using a T1 reducing contrast agent. J Magn Reson Imaging 1999; 10: pp. 118-123.

Academic Radiology, Volume 14, Issue 9
Journals General Radiology
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