ArticleNeuroradiology2013
Three-dimensional susceptibility-weighted imaging at 7 T using fractal-based quantitative analysis to grade gliomas.
Article in Neuroradiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.
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Who cites it
33 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Ultra-High-Field MRI in the Diagnosis and Management of Gliomas: A Systematic Review.Frontiers in neurology · 2022Pooled it
- Fractal and Machine Learning Analyses of MALDI-TOF Mass Spectrometry Data in Glioblastoma.Computational and structural biotechnology journal · 2026Article
- Intra-tumoral susceptibility signals in brain gliomas: where do we stand?Frontiers in radiology · 2025Review
- An update on susceptibility-weighted imaging in brain gliomas.European radiology · 2024Review
- Computational Fractal-Based Analysis of MR Susceptibility-Weighted Imaging (SWI) in Neuro-Oncology and Neurotraumatology.Advances in neurobiology · 2024Article
- Multifractal Analysis of Brain Tumor Interface in Glioblastoma.Advances in neurobiology · 2024Article
- Fractals in Neuroimaging.Advances in neurobiology · 2024Article
- Fractal Dimension Analysis in Neurological Disorders: An Overview.Advances in neurobiology · 2024Review
- Fractals, Pattern Recognition, Memetics, and AI: A Personal Journal in the Computational Neurosurgery.Advances in neurobiology · 2024Article
- Computational Fractal-Based Neurosurgery.Advances in experimental medicine and biology · 2024Review
- Fractal-Based Morphometrics of Glioblastoma.Advances in neurobiology · 2024Article
- Performance comparison of different medical image fusion algorithms for clinical glioma grade classification with advanced magnetic resonance imaging (MRI).Scientific reports · 2023Article
- Chitinase-3 like-protein-1, matrix metalloproteinase -9 and positive intracranial arterial remodelling.Frontiers in aging neuroscience · 2023Article
- SWI by 7T MR Imaging for the Microscopic Imaging Diagnosis of Astrocytic and Oligodendroglial Tumors.AJNR. American journal of neuroradiology · 2022Article
- Development of a Cranial Suture Traction Therapy Program for Facial Asymmetry Correction Using the New Delphi Technique.Medicina (Kaunas, Lithuania) · 2022Article
- Spherical coordinates transformation pre-processing in Deep Convolution Neural Networks for brain tumor segmentation in MRI.Medical & biological engineering & computing · 2022Article
- Foundations of Multiparametric Brain Tumour Imaging Characterisation Using Machine Learning.Acta neurochirurgica. Supplement · 2022Article
- Shape matters: morphological metrics of glioblastoma imaging abnormalities as biomarkers of prognosis.Scientific reports · 2021Article
- Improved susceptibility weighted imaging at ultra-high field using bipolar multi-echo acquisition and optimized image processing: CLEAR-SWI.NeuroImage · 2021Article
- High-resolution Structural Magnetic Resonance Imaging and Quantitative Susceptibility Mapping.Magnetic resonance imaging clinics of North America · 2021Review
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionSusceptibility-weighted imaging (SWI) with high- and ultra-high-field magnetic resonance is a very helpful tool for evaluating brain gliomas and intratumoral structures, including microvasculature. Here, we test whether objective quantification of intratumoral SWI patterns by applying fractal analysis can offer reliable indexes capable of differentiating glial tumor grades.
methodsThirty-six patients affected by brain gliomas (grades II-IV, according to the WHO classification system) underwent MRI at 7 T using a SWI protocol. All images were collected and analyzed by applying a computer-aided fractal image analysis, which applies the fractal dimension as a measure of geometrical complexity of intratumoral SWI patterns. The results were subsequently statistically correlated to the histopathological tumor grade.
resultsThe mean value of the fractal dimension of the intratumoral SWI patterns was 2.086 ± 0.413. We found a trend of higher fractal dimension values in groups of higher histologic grade. The values ranged from a mean value of 1.682 ± 0.278 for grade II gliomas to 2.247 ± 0.358 for grade IV gliomas (p = 0.013); there was an overall statistically significant difference between histopathological groups.
conclusionThe present study confirms that SWI at 7 T is a useful method for detecting intratumoral vascular architecture of brain gliomas and that SWI pattern quantification by means of fractal dimension offers a potential objective morphometric image biomarker of tumor grade.
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