Magnetic resonance imaging evaluation of the median nerve using histogram analysis in carpal tunnel syndrome

Baykara, Murat; Koca, Tuba Tülay; Demirel, Adnan; Berk, Ejder

doi:10.5152/nsn.2018.11280

Cited by 5 publications

(7 citation statements)

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“…The entropy is a measure of the distribution of elements in an image [42]. In the present study, the fact that the entropy, standard deviation and variance values were high indicated that the distribution within the ROI became increasingly irregular [13]. It was determined in the present study that the corpus callosum MRI of the patients with FND was different when compared to that of the healthy controls when examined via histogram analysis.…”

Section: Discussionmentioning

confidence: 52%

“…Texture analysis is basically a technique that analyzes the signal properties, in other words, the position and density of the pixels and the gray level intensity in digital images [13]. Transformbased, structure-based, and statistics-based methods were developed to obtain textural properties using digital images [14].…”

Section: Introductionmentioning

confidence: 99%

“…Histogram-based texture analysis (HA) entails the calculation of all pixels of image densities in the region of interest (ROI) using a full statistical analysis [12]. Recently, these techniques have frequently been used to distinguish normal and abnormal structures [13], to characterize tumors [15], to guide the radiotherapeutic treatment [16], and to identify various biomarkers [17][18][19].…”

Section: Introductionmentioning

confidence: 99%

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Magnetic resonance imaging histogram analysis of corpus callosum in a functional neurological disorder

Baykara¹,

Baykara²,

Mermi³

et al. 2021

Turk J Med Sci

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Background/aim: The aim of the present study was to examine and compare the corpus callosum (CC) via histogram analysis (HA) on T1-weighted MR images of patients diagnosed with Functional Neurological Disorder (FND) and healthy controls. Materials and methods: The study group included 19 female patients diagnosed with FND and the control group included 20 healthy subjects. All participants were scanned with a 1.5 T MR scanner. High-resolution structural image of the entire brain was obtained with sagittal 3D spiral fast spin echo T1 weighted images. The gray level intensity, standard deviation of the histogram, entropy, uniformity, skewness, and kurtosis values were determined with texture analysis. Student's t test was used to compare the group data. p<0.05 was accepted as statistically significant. Results: It was determined that the mean gray level intensity, standard deviation of the histogram, entropy calculated by the maximum, median and variance and size M %values were higher in patients with FND. Kurtosis and U %values were lower in patients with FND. Conclusion: In the present study, analysis of CC with T1 weighted MR image histogram analysis demonstrated significant differences between FND patients and healthy controls. The study findings indicated that HA is a beneficial technique for demonstrating textural variations between CCs of patients with FND and healthy controls using MR images.

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Section: Discussionmentioning

confidence: 52%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Magnetic resonance imaging histogram analysis of corpus callosum in a functional neurological disorder

Baykara¹,

Baykara²,

Mermi³

et al. 2021

Turk J Med Sci

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“…Histogram analysis, one of the texture analysis methods, is widely used for tumor characterization, determination of normal and abnormal tissues, guiding radiotherapy, diagnosing interstitial lung disease, and deciding various prognostic factors [5][6][7][8][9]. The digital medical images consist of units called pixels.…”

Section: Introductionmentioning

confidence: 99%

MRI histogram analysis of optic nerves in children with type 1 neurofibromatosis

Eroğlu¹,

Baykara²

2022

Journal of Surgery and Medicine

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Background/Aim: Type 1 neurofibromatosis (NF1) is the most common neurocutaneous disease affecting numerous systems. Optic pathway glioma (OPG) is a common tumor in children with NF1 and often has variable clinical presentations. In this study, histogram analysis parameters of optic nerves were measured in the magnetic resonance images (MRI) of children with NF1 and compared with a control group. Methods: This case-control study consisted of three groups: Ten patients with NF1 without optic pathway glioma (bilateral optic nerve, n: 20), four patients with NF1 with bilateral optic pathway glioma (n: 8), and nineteen healthy controls (n: 38). ROIs were placed on bilateral pre-chiasmatic optic nerves in the images. With histogram analysis, average gray level intensity (mean), the standard deviation, minimum, median, and maximum intensity, uniformity, entropy, kurtosis, variance, skewness, size% M, size% U, size% L, and percentiles were measured. Results: Mean, median, 3%, 5%, 10%, 25%, and 75% values were higher in NF1 patients with optic pathway glioma (NF1-OPG) than in NF1 patients without optic pathway glioma (NF1-woOPG), and the control group (P<0.001). The same values were significantly higher in the NF1-woOPG group compared to the control group (P<0.001). The minimum, maximum, 1%, 90%, 95%, 97%, and 99% values were significantly higher in the NF1-OPG and NF1-woOPG groups than the control group (P<0.001). The entropy value was significantly higher in the NF1-OPG group than the NF1-woOPG and control groups (5.73, 4.93, and 5.25, respectively, P=0.016). Conclusion: MRI histogram analysis revealed significant differences between NF1-OPG, NF1-woOPG, and healthy individuals in terms of optic nerves. Thus, we think that it can be used to monitor the optic nerves of children with NF1.

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“…The position and intensity features of the pixels in the images are analyzed by texture analysis techniques (Murat Baykara, Koca, Demirel, Berk, & and, 2018). These techniques, including histogram analysis based on statistics, are increasingly used in many studies that investigate structural differences (Murat Baykara et al, 2018;Castellano et al, 2004), diagnose diseases (Murat Baykara et al, 2018;Castellano et al, 2004), identifying diagnostic and prognostic biomarkers (Alic, Niessen, & Veenland, 2014;Molina et al, 2016a;Yang, Rao, Martinez, Veeraraghavan, & Rao, 2015), characterize tumors (Tixier et al, 2012;Yang et al, 2015), and guiding treatment (Molina et al, 2016b;Yang et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Texture analysis of dorsal striatum in functional neurological (conversion) disorder

Baykara

2021

Brain Imaging and Behavior

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In this study, it was aimed to evaluate the dorsal striatum nuclei of patients diagnosed with Functional Neurological Disorder by tissue analysis method from magnetic resonance imaging images and to compare them with healthy controls.Study groups consisted of 20 female patients and 20 healthy women. The brains of patients and controls were scanned for high-resolution images with a 1.5 T scanner using the sagittal plane and 3D spiral fast spin echo sequence. Using the texture analysis method, mean, standard deviation, minimum, maximum, median, variance, entropy, size %L, size %U, size %M, kurtosis, skewness and homogeneity values of the dorsal striatum nuclei were calculated from the images. The data were compared with comparison tests according to Kolmogorov-Smirnov test results.There was no statistically signi cant difference between paired regions in terms of texture analysis ndings in the cross-sectional images of the participants. In patients, mean, standard deviation, minimum, maximum, median, variance and entropy values for the putamen nucleus, and mean, standard deviation, minimum, maximum, median, variance, entropy and kurtosis values for the caudate nucleus were found signi cantly higher than controls. Additional receiver operating characteristic curve and logistic regression analyzes were performed.The implications of the results of the study are that there are signi cant microstructural changes in the dorsal striatum nuclei of patients and their re ection on brain images. Texture analysis is a useful technique to show tissue changes in the dorsal striatum of patients using images. It is highly recommended to use tissue analysis to identify and evaluate potentially affected areas of the brain in new studies.

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Magnetic resonance imaging evaluation of the median nerve using histogram analysis in carpal tunnel syndrome

Cited by 5 publications

References 0 publications

Magnetic resonance imaging histogram analysis of corpus callosum in a functional neurological disorder

Magnetic resonance imaging histogram analysis of corpus callosum in a functional neurological disorder

MRI histogram analysis of optic nerves in children with type 1 neurofibromatosis

Texture analysis of dorsal striatum in functional neurological (conversion) disorder

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