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Diagnostic Value of Fractal Analysis for the Differentiation of Brain Tumors Using 3-Tesla Magnetic Resonance Susceptibility-Weighted Imaging.
Di Ieva, Antonio; Le Reste, Pierre-Jean; Carsin-Nicol, Béatrice; Ferre, Jean-Christophe; Cusimano, Michael D.
Affiliation
  • Di Ieva A; ‡Australian School of Advanced Medicine, Department of Neurosurgery, Macquarie University Hospital, Sydney, New South Wales, Australia; §Garvan Institute of Medical Research, Sydney, New South Wales, Australia; ¶Department of Neurosurgery, University Hospital Pontchaillou, Rennes, France; ‖Department of Neuroradiology, University Hospital Pontchaillou, Rennes, France; #Division of Neurosurgery, St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada.
Neurosurgery ; 79(6): 839-846, 2016 Dec.
Article in En | MEDLINE | ID: mdl-27332779
BACKGROUND: Susceptibility-weighted imaging (SWI) of brain tumors provides information about neoplastic vasculature and intratumoral micro- and macrobleedings. Low- and high-grade gliomas can be distinguished by SWI due to their different vascular characteristics. Fractal analysis allows for quantification of these radiological differences by a computer-based morphological assessment of SWI patterns. OBJECTIVE: To show the feasibility of SWI analysis on 3-T magnetic resonance imaging to distinguish different kinds of brain tumors. METHODS: Seventy-eight patients affected by brain tumors of different histopathology (low- and high-grade gliomas, metastases, meningiomas, lymphomas) were included. All patients underwent preoperative 3-T magnetic resonance imaging including SWI, on which the lesions were contoured. The images underwent automated computation, extracting 2 quantitative parameters: the volume fraction of SWI signals within the tumors (signal ratio) and the morphological self-similar features (fractal dimension [FD]). The results were then correlated with each histopathological type of tumor. RESULTS: Signal ratio and FD were able to differentiate low-grade gliomas from grade III and IV gliomas, metastases, and meningiomas (P < .05). FD was statistically different between lymphomas and high-grade gliomas (P < .05). A receiver-operating characteristic analysis showed that the optimal cutoff value for differentiating low- from high-grade gliomas was 1.75 for FD (sensitivity, 81%; specificity, 89%) and 0.03 for signal ratio (sensitivity, 80%; specificity, 86%). CONCLUSION: FD of SWI on 3-T magnetic resonance imaging is a novel image biomarker for glioma grading and brain tumor characterization. Computational models offer promising results that may improve diagnosis and open perspectives in the radiological assessment of brain tumors. ABBREVIATIONS: FD, fractal dimensionSR, signal ratioSWI, susceptibility-weighted imaging.
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Collection: 01-internacional Database: MEDLINE Main subject: Brain Neoplasms / Magnetic Resonance Imaging / Fractals / Glioma / Lymphoma / Meningioma Type of study: Diagnostic_studies / Observational_studies / Prognostic_studies Limits: Adult / Aged / Female / Humans / Male / Middle aged Language: En Journal: Neurosurgery Year: 2016 Document type: Article Affiliation country: Canada Country of publication: United States
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Collection: 01-internacional Database: MEDLINE Main subject: Brain Neoplasms / Magnetic Resonance Imaging / Fractals / Glioma / Lymphoma / Meningioma Type of study: Diagnostic_studies / Observational_studies / Prognostic_studies Limits: Adult / Aged / Female / Humans / Male / Middle aged Language: En Journal: Neurosurgery Year: 2016 Document type: Article Affiliation country: Canada Country of publication: United States