FLAIR lesion segmentation: Application in patients with brain tumors and acute ischemic stroke

Artzi, Moran; Aizenstein, Orna; Jonas-Kimchi, Tali; Myers, Vicki; Hallevi, Hen; Bashat, Dafna Ben

doi:10.1016/j.ejrad.2013.05.029

Cited by 43 publications

(19 citation statements)

References 17 publications

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“…The Gaussian high-pass filter and median-pass filter were applied for image sharpening and noise reduction. Otsu's method 21,22 was consequently applied to define the appropriate global threshold for the segmentation of PTO from normal brain tissues and tumours. The analysis was conducted independently by two teams of neurosurgeons and neuroradiologists under the guidance of a senior neuroradiologist.…”

Section: Image Processmentioning

confidence: 99%

Segmentation of peritumoral oedema offers a valuable radiological feature of cerebral metastasis

Zhou¹,

Yang²,

Yao³

et al. 2016

BJR

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Chengcheng Zhou and Zixiao Yang contributed equally to this study.Objective: Peritumoral oedema (PTO) is commonly observed on MRI in malignant brain tumours including brain metastasis (bMET) and glioblastoma multiforme (GBM). This study aimed to differentiate bMET from GBM by comparing the volume ratio of PTO to tumour lesion (R vol ).Methods: 56 patients with solitary bMET or GBM were enrolled, and MRI was analyzed by a semi-automatic methodology based on MATLAB (Mathworks, Natick, MA). The PTO volume (V oedema ) was segmented for quantification using T 2 fluid-attenuated inversion-recovery images, while the tumour volume was quantified with enhanced T 1 images. The quantitative volume of the tumour, PTO and the ratio of PTO to tumour were interpreted using SPSS® (IBM Corp., New York, NY; formerly SPSS Inc., Chicago, IL) by considering different locations and pathologies. Results: The tumour volumes of supratentorial GBM, supratentorial bMET (supra-bMET) and infratentorial bMET were 32.22 6 21.9, 18.45 6 17.28 and 11.40 6 5.63 ml, respectively. The corresponding V oedema were 44.08 6 25.84, 73.20 6 40.35 and 23.74 6 7.78 ml, respectively. The V oedema difference between supratentorial and infratentorial lesions is significant (p-value 5 0.002). SuprabMET has a smaller tumour volume (p-value 5 0.032), but a larger PTO (p-value 5 0.007). The ratio of V oedema to the tumour volume in bMET is statistically higher than that in GBM (p-value 5 0.015). The cut-off ratio for identifying bMET from GBM is 3.9, with a specificity and sensitivity of 90.0% and 68.8%, respectively. Conclusion: Segmentation is an efficient method to quantify irregular PTO. bMET possesses more extensive oedema with smaller tumour volume than does GBM. The R vol is a valuable index to distinguish bMET from GBM. Advances in knowledge: This study presents a new method for the quantitation of PTO to differentiate bMET from GBM.

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Section: Image Processmentioning

confidence: 99%

Segmentation of peritumoral oedema offers a valuable radiological feature of cerebral metastasis

Zhou¹,

Yang²,

Yao³

et al. 2016

BJR

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“…Future volumetric MR images can potentially quantify the measurement. 22 Finally, the autoregulation of cerebral perfusion after stent placement was dynamic; the most appropriate timing of examinations to predict hyperperfusion deserves more detailed investigation.…”

mentioning

confidence: 99%

Stenotic Transverse Sinus Predisposes to Poststenting Hyperperfusion Syndrome as Evidenced by Quantitative Analysis of Peritherapeutic Cerebral Circulation Time

Lin

Chang

Tsai

et al. 2014

American Journal of Neuroradiology

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BACKGROUND AND PURPOSE:Hyperperfusion syndrome is a devastating complication of carotid stent placement. The shortening of cerebral circulation time after stent placement is seen as a good indicator of the development of hyperperfusion syndrome. The purpose of our study was to evaluate whether patients with ipsilateral transverse sinus stenosis are prone to having shortened cerebral circulation time after stent placement, subsequently leading to the possible development of hyperperfusion syndrome.

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“…20 Manual correction was performed when necessary. Normalized images of FLAIR (nFLAIR) and postcontrast T1WI (nT1WIϩGd) were calculated relative to NAWM.…”

Section: Lesion Classificationmentioning

confidence: 99%

Classification of High-Grade Glioma into Tumor and Nontumor Components Using Support Vector Machine

Blumenthal¹,

Artzi

Liberman

et al. 2017

AJNR Am J Neuroradiol

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BACKGROUND AND PURPOSE:Current imaging assessment of high-grade brain tumors relies on the Response Assessment in NeuroOncology criteria, which measure gross volume of enhancing and nonenhancing lesions from conventional MRI sequences. These assessments may fail to reliably distinguish tumor and nontumor. This study aimed to classify enhancing and nonenhancing lesion areas into tumor-versus-nontumor components.

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FLAIR lesion segmentation: Application in patients with brain tumors and acute ischemic stroke

Cited by 43 publications

References 17 publications

Segmentation of peritumoral oedema offers a valuable radiological feature of cerebral metastasis

Segmentation of peritumoral oedema offers a valuable radiological feature of cerebral metastasis

Stenotic Transverse Sinus Predisposes to Poststenting Hyperperfusion Syndrome as Evidenced by Quantitative Analysis of Peritherapeutic Cerebral Circulation Time

Classification of High-Grade Glioma into Tumor and Nontumor Components Using Support Vector Machine

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