Diagnostic Performance of Increased Signal Intensity Within the Resection Cavity on Fluid-Attenuated Inversion Recovery Sequences for Detection of Progression in Patients with Glioma

Purpose The aim of this study was to depict the signal intensity pattern of the normal oculomotor nerve demonstrated on contrast-enhanced three-dimensional fluid-attenuated inversion recovery images. Materials and methods Eighty-one patients were included in the study. Contrast-enhanced three-dimensional fluid-attenuated inversion recovery images with magnetisation-prepared rapid acquisition were reconstructed and evaluated in the coronal plane. The signal intensity of the cisternal segment of the oculomotor nerve was graded into a visual scale of 1 to 5 as compared to the white matter, grey matter and the pituitary stalk. The signal intensity ratio of the oculomotor nerve was consequently measured. Results By using the visual scale, more than half of the oculomotor nerves showed higher signal intensity than the grey matter signal on contrast-enhanced three-dimensional fluid-attenuated inversion recovery images (59.3–80.2%). It can demonstrate a signal intensity similar to the pituitary stalk (14.8%) by visualisation. None of them showed signal intensity equal to the normal white matter signal. By signal intensity measurement, the mean signal intensity ratio of oculomotor nerves to white matter equals 1.54±0.20 (95% confidence interval (CI) 1.51–1.57); mean signal intensity ratio to grey matter equals 1.16±0.15 (95% CI 1.14–1.18); mean signal intensity ratio to the pituitary stalk equals 0.68±0.10 (95% CI 0.64–0.70). Conclusions The normal oculomotor nerve visualised on contrast-enhanced three-dimensional fluid-attenuated inversion recovery images has a higher signal intensity than the white matter and may have a signal intensity similar to the grey matter or the pituitary stalk. The high signal intensity of the oculomotor nerve in contrast-enhanced three-dimensional fluid-attenuated inversion recovery should not be misinterpreted as a pathology.

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Diagnostic Ability of Fluid-Attenuated Inversion Recovery MR Imaging to Detect Remnant or Recurrent Meningiomas after Resection

The Neuroradiology Journal ◽

10.1177/197140091202500202 ◽

2012 ◽

Vol 25 (2) ◽

pp. 163-171 ◽

Cited By ~ 3

Author(s):

H. Mori ◽

A. Kunimatsu ◽

O. Abe ◽

H. Sasaki ◽

H. Takao ◽

...

Keyword(s):

Qualitative Analysis ◽

Tumor Progression ◽

Evaluation Criteria ◽

Region Of Interest ◽

Inversion Recovery ◽

Recurrent Tumor ◽

Resection Cavity ◽

Fluid Attenuated Inversion Recovery ◽

Remnant Tumor

It has been suggested that a difference in signal intensity (SI) between the resection cavity and normal cerebrospinal fluid (CSF) on fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) in partially resected gliomas indicates subsequent or coincident tumor progression. We considered that this would hold true for resected meningiomas as well. Hence, we aimed to assess whether or not such a difference in the SI during the follow-up evaluation helps predict residual or recurrent tumor in resected meningiomas. We evaluated 63 patients with resected meningiomas. The SI within the resection cavity observed on FLAIR images was qualitatively and quantitatively assessed during follow-up. Qualitative analysis comprised visual comparison of the SI in the resection cavity with that of normal CSF by neuroradiologists. The SI in the resection cavity was quantitatively assessed by region of interest (ROI) analysis and normalized against the background noise and CSF SI. Normalized SI recorded during follow-up was compared with that recorded immediately after resection. Tumor progression was defined as a 20% or greater increase in the diameter of the longest residual or recurrent meningioma (Response Evaluation Criteria in Solid Tumors). The sensitivity and specificity of the elevated SI in the resection cavity for indicating residual or recurrent tumor were calculated. Qualitative analysis by FLAIR MRI showed that patients with remnant tumor following surgery had a prolonged SI increase in the resection cavity. Further, SI increase could not always be observed before recurrence, and both SI increase and regrowth remnant/recurrence could be detected in the same MRI examination. In resected meningiomas, leakage of tumor elements into the resection cavity, presumably tumor cells, manifests as an SI increase on FLAIR images and indicates residual or recurrent tumor. However, unlike the previous reports on partially resected gliomas, we concluded that the SI change does not always precede tumor progression or recurrence.

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Automated White Matter Hyperintensity Detection in Multiple Sclerosis Using 3D T2 FLAIR

International Journal of Biomedical Imaging ◽

10.1155/2014/239123 ◽

2014 ◽

Vol 2014 ◽

pp. 1-7 ◽

Cited By ~ 5

Author(s):

Yi Zhong ◽

David Utriainen ◽

Ying Wang ◽

Yan Kang ◽

E. Mark Haacke

Keyword(s):

Multiple Sclerosis ◽

White Matter ◽

Gray Matter ◽

Signal Intensity ◽

High Spatial Frequency ◽

Inversion Recovery ◽

White Matter Hyperintensity ◽

Mr Images ◽

Automated Algorithm ◽

Fluid Attenuated Inversion Recovery

White matter hyperintensities (WMH) seen on T2WI are a hallmark of multiple sclerosis (MS) as it indicates inflammation associated with the disease. Automatic detection of the WMH can be valuable in diagnosing and monitoring of treatment effectiveness. T2 fluid attenuated inversion recovery (FLAIR) MR images provided good contrast between the lesions and other tissue; however the signal intensity of gray matter tissue was close to the lesions in FLAIR images that may cause more false positives in the segment result. We developed and evaluated a tool for automated WMH detection only using high resolution 3D T2 fluid attenuated inversion recovery (FLAIR) MR images. We use a high spatial frequency suppression method to reduce the gray matter area signal intensity. We evaluate our method in 26 MS patients and 26 age matched health controls. The data from the automated algorithm showed good agreement with that from the manual segmentation. The linear correlation between these two approaches in comparing WMH volumes was found to beY=1.04X+1.74 (R2=0.96). The automated algorithm estimates the number, volume, and category of WMH.

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