Applications of Fractal Analysis in Brain Images Interpretation

A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Neurotechnology and Neuroimaging".

Deadline for manuscript submissions: closed (20 December 2020) | Viewed by 8916

Special Issue Editor

Special Issue Information

In the last decade, constant progress in neuroimaging has graced us with an additional type of illustration that is frequently used as scientific real evidence in discovering and interpreting the evolution of specific diseases. Therefore, brain images have epistemically special significance, while they are also liable to be viewed as akin to photographs of brain activity itself.

As a result of this, it is necessary to develop algorithms based on recognized methods. The proposed algorithms will be used in image processing in brain computed tomography image analysis.

Image fabrication and obtaining results are possible because some components of the brain, such as the blood vessel network or the neural network, have a fractal arrangement, which makes it easy to analyze their structure in order to provide predictions or treatments as accurately as possible to patients afflicted with a serious brain disease.

In recent years, approaches in this category have demonstrated admirable outcomes, superior to those obtained by standard methods in different areas. Today, specialized investigators are trying different new techniques for in-depth analysis to enhance the performance of detection systems in neoplasm screening by computed tomography, including both identification and localization of abnormalities known as mini-tumors in the medical field (even though they can be about the size of some pixels), which some inexperienced radiologists may fail to observe.

Identifying malignant nodosities or cerebral cancer constituents from computerized tomography exploration is a difficult load and time-consuming for specialist radiology physicians, such as liver doctors, lung doctors or neurologists. The same thing also happens when examining images obtained through the magnetic resonance (MR) technique.

Very rapid diagnosis of cancer constituents by screening allows immediate medical interventions to reduce mortality rate. Fractal analysis of medical images may be useful for this purpose. Calculations of the fractal dimensions, the Hurst exponent, and lacunarity of pathological and healthy tissue samples can be performed using qualified methods.

Further, there is accumulating evidence that brain magnetic resonance imaging may be useful in staging and monitoring disease progression (staging biomarker), and also possibly as a means to monitor pathophysiological aspects of disease and associated response to treatments, i.e., theranostic marker. More so, magnetic resonance imaging has the potential to serve as a biomarker for Parkinson's and Alzheimers diseases.

In conjunction, these investigations will contribute to our current understanding of neurological disorders and their evolution in particular, or neuroscience in general.

To facilitate this service immediately, the aforementioned techniques and methods highlighted should be refined in the proposed papers submitted to the Special Issue, which aims to bring together cutting-edge research on the brain advanced image processing, as well as self-representation in brain research, in a quantitative rather than qualitative manner.

Finally, we will accept scientifically rigorous and novel original papers about the processes discussed above and neuroimaging data, as well as reviews and meta-analyses in the field.

Prof. Dr. Viorel-Puiu Paun
Guest Editor

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Keywords

  • brain images
  • computed tomography
  • radiology
  • magnetic resonance
  • fractal analysis
  • multifractal analysis
  • fractal dimension
  • lacunarity
  • box counting algorithm
  • complex systems
  • time scale
  • pattern recognition
  • brain disease
  • neurological disorders
  • biomarker for Parkinson’s and Alzheimer’s diseases

Published Papers (3 papers)

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Research

12 pages, 600 KiB  
Article
Corticospinal Tract and Related Grey Matter Morphometric Shape Analysis in ALS Phenotypes: A Fractal Dimension Study
Brain Sci. 2021, 11(3), 371; https://doi.org/10.3390/brainsci11030371 - 14 Mar 2021
Cited by 7 | Viewed by 2220
Abstract
A pathological hallmark of amyotrophic lateral sclerosis (ALS) is corticospinal tract (CST) degeneration resulting in upper motor neuron (UMN) dysfunction. No quantitative test is available to easily assess UMN pathways. Brain neuroimaging in ALS promises to potentially change this through identifying biomarkers of [...] Read more.
A pathological hallmark of amyotrophic lateral sclerosis (ALS) is corticospinal tract (CST) degeneration resulting in upper motor neuron (UMN) dysfunction. No quantitative test is available to easily assess UMN pathways. Brain neuroimaging in ALS promises to potentially change this through identifying biomarkers of UMN dysfunction that may accelerate diagnosis and track disease progression. Fractal dimension (FD) has successfully been used to quantify brain grey matter (GM) and white matter (WM) shape complexity in various neurological disorders. Therefore, we investigated CST and whole brain GM and WM morphometric changes using FD analyses in ALS patients with different phenotypes. We hypothesized that FD would detect differences between ALS patients and neurologic controls and even between the ALS subgroups. Neuroimaging was performed in neurologic controls (n = 14), and ALS patients (n = 75). ALS patients were assigned into four groups based on their clinical or radiographic phenotypes. FD values were estimated for brain WM and GM structures. Patients with ALS and frontotemporal dementia (ALS-FTD) showed significantly higher CST FD values and lower primary motor and sensory cortex GM FD values compared to other ALS groups. No other group of ALS patients revealed significant FD value changes when compared to neurologic controls or with other ALS patient groups. These findings support a more severe disease process in ALS-FTD patients compared to other ALS patient groups. FD value measures may be a sensitive index to evaluate GM and WM (including CST) degeneration in ALS patients. Full article
(This article belongs to the Special Issue Applications of Fractal Analysis in Brain Images Interpretation)
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15 pages, 3996 KiB  
Article
Using Fractal Dimension Analysis with the Desikan–Killiany Atlas to Assess the Effects of Normal Aging on Subregional Cortex Alterations in Adulthood
Brain Sci. 2021, 11(1), 107; https://doi.org/10.3390/brainsci11010107 - 14 Jan 2021
Cited by 9 | Viewed by 2511
Abstract
Normal aging is associated with functional and structural alterations in the human brain. The effects of normal aging and gender on morphological changes in specific regions of the brain are unknown. The fractal dimension (FD) can be a quantitative measure of cerebral folding. [...] Read more.
Normal aging is associated with functional and structural alterations in the human brain. The effects of normal aging and gender on morphological changes in specific regions of the brain are unknown. The fractal dimension (FD) can be a quantitative measure of cerebral folding. In this study, we used 3D-FD analysis with the Desikan–Killiany (DK) atlas to assess subregional morphological changes in adulthood. A total of 258 participants (112 women and 146 men) aged 30–85 years participated in this study. Participants in the middle-age group exhibited a decreased FD in the lateral frontal lobes, which then spread to the temporal and parietal lobes. Men exhibited an earlier and more significant decrease in FD values, mainly in the right frontal and left parietal lobes. Men exhibited more of a decrease in FD values in the subregions on the left than those in the right, whereas women exhibited more of a decrease in the lateral subregions. Older men were at a higher risk of developing mild cognitive impairment (MCI) and exhibited age-related memory decline earlier than women. Our FD analysis using the DK atlas-based prediagnosis may provide a suitable tool for assessing normal aging and neurodegeneration between groups or in individual patients. Full article
(This article belongs to the Special Issue Applications of Fractal Analysis in Brain Images Interpretation)
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15 pages, 5640 KiB  
Communication
Tractography-Based Analysis of Morphological and Anatomical Characteristics of the Uncinate Fasciculus in Human Brains
Brain Sci. 2020, 10(10), 709; https://doi.org/10.3390/brainsci10100709 - 06 Oct 2020
Cited by 8 | Viewed by 3120
Abstract
(1) Background: The uncinate fasciculus (UF) is a white matter bundle connecting the prefrontal cortex and temporal lobe. The functional role of the uncinate fasciculus is still uncertain. The role of the UF is attributed to the emotional empathy network. The present study [...] Read more.
(1) Background: The uncinate fasciculus (UF) is a white matter bundle connecting the prefrontal cortex and temporal lobe. The functional role of the uncinate fasciculus is still uncertain. The role of the UF is attributed to the emotional empathy network. The present study aimed to more accurately the describe anatomical variability of the UF by focusing on the volume of fibers and testing for correlations with sex and age. (2) Material and Methods: Magnetic resonance imaging of adult patients with diffusion tensor imaging (DTI) was performed on 34 patients. The total number of fibers, volume of UF, and number of tracts were processed using DSI studio software. The DSI studio allows for mapping of different nerve pathways and visualizing of the obtained results using spatial graphics. (3) Results: The total number of UF tracts was significantly higher in the right hemisphere compared to the left hemisphere (right M ± SD = 52 ± 24; left: 39 ± 25, p < 0.05). A hook-shaped UF was the most common variant (91.7%). The UF volumes were larger in men (1410 ± 150.7 mm3) as compared to women (1325 ± 133.2 mm3) (p < 0.05). The mean fractional anisotropy (FA) values of the UF were significantly larger on the left side 0.597, while the right UF had an average of 0.346 (p < 0.05). Patients older than 50 years old had a significantly higher value of mean diffusivity (MD) (p = 0.034). In 73.5% of patients, a greater number of fibers terminated in the inferior part of the inferior frontal gyrus. (4) Conclusions: The morphological characteristics of the UF, unlike the shape, are associated with sex and are characterized by hemispheric dominance. These findings confirm the results of the previous studies. Future research should examine the potential correlation among the UF volume, number of fibers, and total brain volume in both sexes and patient psychological state. Full article
(This article belongs to the Special Issue Applications of Fractal Analysis in Brain Images Interpretation)
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