scholarly journals Relationship between necrotic patterns in glioblastoma and patient survival: fractal dimension and lacunarity analyses using magnetic resonance imaging

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Shuai Liu ◽  
Yinyan Wang ◽  
Kaibin Xu ◽  
Zheng Wang ◽  
Xing Fan ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Fractal Dimension ◽  
Magnetic Resonance ◽  
Patient Survival ◽  
Resonance Imaging

scholarly journals Low perfusion compartments in glioblastoma quantified by advanced magnetic resonance imaging and correlated with patient survival

2019 ◽  
Vol 134 ◽  
pp. 17-24
Author(s):  
Chao Li ◽  
Jiun-Lin Yan ◽  
Turid Torheim ◽  
Mary A. McLean ◽  
Natalie R. Boonzaier ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Patient Survival ◽  
Resonance Imaging

scholarly journals Fractal dimension of phylogenetically different parts of the human cerebellum (magnetic resonance imaging study)

2020 ◽  
Vol 26 (2) ◽  
pp. 67-73
Author(s):  
N.I. Maryenko ◽  
O.Yu. Stepanenko
Keyword(s):  
Magnetic Resonance Imaging ◽  
Fractal Dimension ◽  
Magnetic Resonance ◽  
Lower Lobe ◽  
Imaging Study ◽  
Magnetic Resonance Imaging Study ◽  
Resonance Imaging ◽  
Tomographic Images ◽  
Average Value ◽  
The Brain

In recent years, fractal analysis has been increasingly used as a morphometric method, which allows to assess the complexity of the organization of quasi-fractal biological structures, including the cerebellum. The aim of the study was to determine the value of fractal dimension of phylogenetically different parts of the cerebellum by studying magnetic resonance imaging of the brain using the method of pixel dilation and to identify gender and age characteristics of individual variability of fractal dimension of the cerebellum and its external linear contour. The study was performed on the magnetic resonance images of the brain of 120 relatively healthy patients in age 18-86 years (65 women, 55 men). T2 weighted tomographic images were investigated. Fractal analysis was performed using the method of pixel dilation in the author’s modification. Fractal dimension (FD) values were determined for cerebellar tomographic images segmented with brightness values of 100 (FD100), 90 (FD90) and in the range of 100-90 (FD100-90 or fractal dimension of the outer cerebellar contour) in its upper and lower lobes, which include phylogenetically different zones. The obtained data were processed using generally accepted statistical methods. The average value of FD100 of the upper lobe of the cerebellum was 1.816±0.005, the lower lobe – 1.855±0.005. The average value of FD90 of the upper lobe of the cerebellum was 1.734±009, the lower lobe – 1.768±0.009. The average value of FD100-90 of the upper lobe of the cerebellum was 1.370±0.009, the lower lobe – 1.431±0.008. All three values of the fractal dimension of the lower lobe, which lobules have a lower phylogenetic age, are statistically significantly higher than the corresponding values of the fractal dimension of the upper lobe, have a more pronounced correlation with age than in the upper lobe. The developed research algorithm can be used to assess the condition of the cerebellum as an additional morphometric method during magnetic resonance imaging study of the brain.

scholarly journals Recurrent glioblastoma: Volumetric assessment and stratification of patient survival with early posttreatment magnetic resonance imaging in patients treated with bevacizumab

Cancer ◽  
2013 ◽  
Vol 119 (19) ◽  
pp. 3479-3488 ◽  
Author(s):  
Raymond Y. Huang ◽  
Rifaquat Rahman ◽  
Alhafidz Hamdan ◽  
Caroline Kane ◽  
Christina Chen ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Patient Survival ◽  
Recurrent Glioblastoma ◽  
Resonance Imaging ◽  
Volumetric Assessment

Utility of Early Postoperative Magnetic Resonance Imaging After Glioblastoma Resection: Implications on Patient Survival

2018 ◽  
Vol 120 ◽  
pp. e1171-e1174 ◽  
Author(s):  
Oliver D. Mrowczynski ◽  
Samer Zammar ◽  
Alexandre J. Bourcier ◽  
Sara T. Langan ◽  
Jason Liao ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Patient Survival ◽  
Resonance Imaging ◽  
Postoperative Magnetic Resonance Imaging

Magnetic resonance imaging–based 3-dimensional fractal dimension and lacunarity analyses may predict the meningioma grade

2020 ◽  
Vol 30 (8) ◽  
pp. 4615-4622
Author(s):  
Yae Won Park ◽  
Soopil Kim ◽  
Sung Soo Ahn ◽  
Kyunghwa Han ◽  
Seok-Gu Kang ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Fractal Dimension ◽  
Magnetic Resonance ◽  
Resonance Imaging ◽  
3 Dimensional

scholarly journals Morphological Metrics of Magnetic Resonance Imaging of Glioblastoma as Biomarkers of Prognosis

2021 ◽  
Author(s):  
Lee Curtin ◽  
Paula Whitmire ◽  
Haylye White ◽  
Maciej M. Mrugala ◽  
Leland S. Hu ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Fractal Dimension ◽  
Magnetic Resonance ◽  
Morphological Characteristics ◽  
Standard Of Care ◽  
Tumor Location ◽  
Primary Brain Tumor ◽  
Resonance Imaging ◽  
Current Standard ◽  
Fluid Attenuated Inversion Recovery

AbstractMorphological characteristics have been linked to outcomes across a variety of cancers. Lacunarity is a quantitative morphological measure of how shapes fill space while fractal dimension is a morphological measure of the complexity of pixel arrangement. Glioblastoma is the most aggressive primary brain tumor with a short expected survival given the current standard-of-care treatment. Due to the sensitive location of the tumor, there is a heavy reliance on imaging to assess the state of the disease in the clinic. In this project, we computed lacunarity and fractal dimension values for glioblastoma-induced abnormalities on gadolinium-enhanced T1-weighted magnetic resonance imaging (T1Gd MRI) as well as T2-weighted (T2) and fluid-attenuated inversion recovery (FLAIR) MRIs. In our patient cohort (n=402), we aim to connect these morphological metrics calculated on pretreatment MRI with the survival of patients with GBM. We calculated lacunarity and fractal dimension across all MRI slices on necrotic regions (n=390) and abnormalities on T1Gd MRI (n=402), as well as on enhancing abnormalities present on T2/FLAIR MRI (n=257). We also explored the relationship between these metrics and age at diagnosis, as well as abnormality volume. We found statistically significant relationships to outcome across all three imaging subtypes, with the shape of T2/FLAIR abnormalities showing the strongest relationship with overall survival. The link between morphological and survival metrics could be driven by underlying biological phenomena, tumor location or microenvironmental factors that should be further explored.

scholarly journals Fractal dimension of the cortex and white matter of human cerebellum (magnetic resonance imaging study)

2020 ◽  
pp. 69-74
Author(s):  
N. I. Maryenko ◽  
O. Yu. Stepanenko
Keyword(s):  
Magnetic Resonance Imaging ◽  
Fractal Dimension ◽  
White Matter ◽  
Magnetic Resonance ◽  
Cerebellar Cortex ◽  
Fractal Analysis ◽  
Granular Layer ◽  
Resonance Imaging ◽  
Human Cerebellum ◽  
Cerebellar Tissue

The cerebellum is a typical structure with fractal properties, so fractal analysis is one of the main morphometric techniques that allow a comprehensive assessment of its morphofunctional state; the development of methods for differential measurement of the fractal dimension of various components of cerebellar tissue is necessary for complex morphological examination of the cerebellum using fractal analysis. The aim of the study was to develop an algorithm for differential fractal analysis and to determine the values of the fractal dimension of the cortex and white matter of human cerebellum using the study of magnetic resonance imaging scans. Digital T2 weighted magnetic resonance imaging scans of 30 conditionally healthy persons were used in the study. Fractal analysis of the distinct components of the cerebellar tissue was performed using the pixel dilation method. The fractal dimension values for all threshold brightness values (from 0 to 255) were determined. The confidence interval of the fractal dimension values based on the average values of the fractal dimension of the entire range of brightness values was calculated. Algorithms for image preprocessing were developed for an individual study of the different components of the cerebellum: cerebellar tissue as a whole, white matter, molecular and granular layers of the cortex. A differential fractal analysis technique has been developed to assess individual components of the cerebellar tissue. The values of the fractal dimension of white matter, granular and molecular layers of the cerebellar cortex were determined. The values of the fractal dimension of cerebellar tissue as a whole and the fractal dimension of the cerebellar cortex as a whole were the biggest. These values exceed the value of the fractal dimension of white matter. The average value of the fractal dimension (FD) for the threshold value of 80 (white matter) was 1.318±0.050, for the value of 90 (white matter and the granular layer of the cortex) was 1.568±0.028, for the value of 100 (cerebellar tissue as a whole) was 1.694±0.010. The average FD of the granular layer of the cortex (brightness range 81-90) was 1.377±0.020, the FD of the molecular layer of the cortex (brightness range 91-100) was 1.353±0.020, the average FD of the cerebellar cortex as a whole (brightness range 81-100) was 1.564±0.018. The obtained data can be used as diagnosis criteria to assess the morphofunctional state of the cerebellum using magnetic resonance imaging.

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