02
Jul

0
Accuracy of diffusion weighted imagingmagnetic resonance

Accuracy of diffusion-weighted imagingmagnetic resonance in differentiating functional from non-functional pituitary macro-adenoma and classification of tumor consistency

Authors

Morteza Sanei Taheri, Farnaz Kimia, Mersad Mehrnahad, Hamidreza Saligheh Rad, Hamidreza Haghighatkhah1, Afshin Moradi, Anahita Fathi Kazerooni, Mohammadreza Alviri and Abdorrahim Absalan

Journal

The Neuroradiology Journal

Abstract

Objective: The purpose of this study was to determine the accuracy of selected first or second-order histogram features in differentiation of functional types of pituitary macro-adenomas.
Materials and Methods: Diffusion-weighted imaging magnetic resonance imaging was performed on 32 patients (age meanstandard deviation ¼ 43.09  11.02 years; min ¼ 22 and max ¼ 65 years) with pituitary macro-adenoma (10 with functional and 22 with non-functional tumors). Histograms of apparent diffusion coefficient were generated from regions of interest and selected first or second-order histogram features were extracted. Collagen contents of the surgically resected tumors were examined histochemically using Masson trichromatic staining and graded as containing <1%, 1–3%, and >3% of collagen.
Results: Among selected first or second-order histogram features, uniformity (p ¼ 0.02), 75th percentile (p ¼ 0.03), and tumor smoothness (p ¼ 0.02) were significantly different between functional and non-functional tumors. Tumor smoothness > 5.7  109 (area under the curve ¼ 0.75; 0.56–0.89) had 70% (95% confidence interval ¼ 34.8 93.3%) sensitivity and 33.33% (95% confidence interval ¼ 14.6–57.0%) specificity for diagnosis of functional tumors. Uniformity 179.271 had a sensitivity of 60% (95% confidence interval ¼ 26.2–87.8%) and specificity of 90.48% (95% confidence interval ¼ 69.6–98.8%) with area under the curve ¼ 0.76; 0.57–0.89. The 75th percentile >0.7 had a sensitivity of 80% (95% confidence interval ¼ 44.4–97.5%) and specificity of 66.67% (95% confidence interval ¼ 43.0–85.4%) for categorizing tumors to functional and non-functional types (area under the curve ¼ 0.74; 0.55–0.88). Using these cut-offs, smoothness and uniformity are suggested as negative predictive indices (non functional tumors) whereas 75th percentile is more applicable for diagnosis of functional tumors.
Conclusion: First or second-order histogram features could be helpful in differentiating functional vs non-functional pituitary macro-adenoma tumors.

Keywords

Pituitary adenoma, tumor consistency, apparent diffusion coefficient, magnetic resonance imaging

 

02
Jul

0
MRI of Glioma Brain Tumors

An Efficient Framework for Accurate Arterial Input Selection in DSC-MRI of Glioma Brain Tumors

Authors

Rahimzadeh H, Fathi Kazerooni A, Deevband M. R, Saligheh Rad H.

Journal

Journal Biomed Phys Eng

Abstract

Objective: Automatic and accurate arterial input function (AIF) selection has an essential role for quantification of cerebral perfusion hemodynamic parameters using dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI).
The purpose of this study is to develop an optimal automatic method for arterial input function determination in DSC-MRI of glioma brain tumors by using a new preprocessing method.
Materials and Methods: For this study, DSC-MR images of 43 patients with glioma brain tumors were retrieved retrospectively. Our proposed AIF selection framework consisted an effcient pre-processing step, through which non-arterial curves such as tumorous, tissue, noisy and partial-volume affected curves were excluded, followed by AIF selection through agglomerative hierarchical (AH) clustering method. The performance of automatic AIF clustering was compared with manual AIF selection performed by an experienced radiologist, based on curve shape parameters, i.e. maximum peak (MP), full-width-at-half-maximum (FWHM), M (=MP/ (TTP × FWHM)) and root mean square error (RMSE).
Results: Mean values of AIFs shape parameters were compared with those derived from manually selected AIFs by two-tailed paired t-test. The results showed statistically insignificant differences in MP, FWHM, and M parameters and lower RMSE, approving the resemblance of the selected AIF with the gold standard. The intraclass correlation coefficient and coefficients of variation percent showed a better agreement between manual AIF and our proposed AIF selection than previously proposed methods.
Conclusion: The results of current work suggest that by using efficient preprocessing steps, the accuracy of automatic AIF selection could be improved and this method appears promising for efficient and accurate clinical applications.

Keywords

Perfusion, Dynamic Susceptibility Contrast Enhanced MRI, Arterial Input Function, Cluster Analysis

 

02
Jul

0
Apparent Diffusion Coefficient ,ADC

Apparent Diffusion Coefficient (ADC) and First-Order Histogram Statistics in Differentiating Malignant Vs. Benign Meningioma in Adults

Authors

Hamidreza Saligheh Rad, Mojtaba Safari, Anahita Fathi Kazerooni, Yashar Moharamzad and Morteza Sanei Taheri

Journal

Iran J Radiol

Abstract

Background: Apparent diffusion coefficient (ADC) measured by diffusion-weighted MRI and first-order histogram (FOH) extracted features, as markers of tumor heterogeneity, have been implicated in differentiating grade of the intracranial tumors.
Objective: To examine whether ADC, normalized ADC (NADC), and FOH features such as entropy, kurtosis, and uniformity can differentiate benign vs. malignant meningioma.
Materials and Methods: MRI with diffusion-weighted (DW) imaging sequence of 62 patients with histologically-proven meningioma (37 benign and 25 malignant/atypical) were included. After co-registration of ADC maps to their corresponding anatomical MRI (post-contrast T1-weighted (T1C) images) and delineation of the tumors border by selecting regions of interest (ROIs) on T1C images, a mask of tumor was created and overlaid on the corresponding ADC map. Then, FOH features were extracted.
Results: Mean (± standard deviation (SD)) ADC values in benign and malignant subgroups were respectively 1.05 (± 0.23) and 0.99 (± 0.29) 10-3 mm2/s, and P = 0.69. NADC ratios were not statistically significant between benign (0.5 ± 0.09) and malignant (0.5 ± 0.07) meningioma groups (P = 0.89). Mean values of entropy (6.36 vs. 6.44), kurtosis (5.77 vs. 5.45), and uniformity (536.8 vs. 304.18) were comparable between benign and malignant meningioma subgroups. Receiver operating characteristic (ROC) curve analysis did not yield the significant area under the curve results to show acceptable diagnostic accuracy for any of the measured variables.
Conclusion: ADC, NADC, and statistical features of tumor heterogeneity by FOH method measured by DW-MRI were not able to differentiate benign vs. malignant/atypical meningiomas.

Keywords

Diffusion Magnetic Resonance Imaging, Meningioma, Apparent Diffusion Coefficient, Histogram, Tumor

 

02
Jul

0
Liquid Calibration Phantoms in Ultra Low Dose QCT

Liquid Calibration Phantoms in Ultra-Low-Dose QCT for the Assessment of Bone Mineral Density

Authors

Malakeh Malekzadeh, Shahrokh Abbasi-Rad, Joyce H Keyak, Mahnaz Nabil, Mojgan Asadi, Nazanin Mobini, Parisa Naghdi, Hamid Emadi, Hamidreza Saligheh Rad and Mohammad Bagher Shiran

Journal

Journal of Clinical Densitometry

Abstract

Cortical bone is affected by metabolic diseases. Some studies have shown that lower cortical bone mineral density (BMD) is related to increases in fracture risk which could be diagnosed by quantitative computed tomography (QCT). Nowadays, hybrid iterative reconstruction-based (HIR) computed tomography (CT) could be helpful to quantify the peripheral bone tissue. A key focus of this paper is to evaluate liquid calibration phantoms for BMD quantification in the tibia and under hybrid iterative reconstruction-based-CT with the different hydrogen dipotassium phosphate (K2HPO4) concentrations phantoms. Methodology: Four ranges of concentrations of K2HPO4 were made and tested with 2 exposure settings. Accuracy of the phantoms with ash gravimetry and intermediate K2HPO4 concentration as hypothetical patients were evaluated. The correlations and mean differences
between measured equivalent QCT BMD and ash density as a gold standard were calculated. Relative percentage error (RPE) in CT numbers of each concentration over a 6-mo period was reported. Results: The correlation values (R2 was close to 1.0), suggested that the precision of QCT-BMD measurements using standard and ultra-low dose settings were similar for all phantoms. The mean differences between QCT-BMD and the ash density for low concentrations (about 93 mg/cm3) were lower than high concentration phantoms with 135 and 234 mg/cm3 biases. In regard to accuracy test for hypothetical patient, RPE was up to 16.1% for the low concentration (LC) phantom for the case of high mineral content. However, the lowest RPE (0.4 to 1.8%) was obtained for the high concentration (HC) phantom, particularly for the high mineral content case. In addition, over 6 months, the K2HPO4 concentrations increased 25% for 50 mg/cm3 solution and 0.7 % for 1300 mg/cm3 solution in phantoms. Conclusion: The excellent linear correlations between the QCT equivalent density and the ash density gold standard indicate that QCT can be used with submilisivert radiation dose. We conclude that using liquid calibration phantoms with a range of mineral content similar to that being measured will minimize bias. Finally, we suggest performing BMD measurements with ultra-low dose scan concurrent with iterative-based reconstruction to reduce radiation exposure.

Keywords

cortical bone, hybrid iterative reconstruction, quantitative computed tomography, tibia, ultra-low dose.

 

25
Jun

0
Methodological

The Use of Proton MR Spectroscopy in Epilepsy: A Methodological Review

Authors

Neda Mohammadi Mobarakeh, Fatemeh Fadaie, Mohammad Reza Nazem Zadeh, Jafar Mehvari Habibabadi, Hamidreza Saligheh Rad.

Journal

Frontiers in Biomedical Technologies

Abstract

Magnetic Resonance Spectroscopy (MRS) has at least two major roles in the evaluation of epileptic patients.
First, MRS can help to understand the interaction between seizures and metabolic function. Thus, MRS is particularly interesting for basic science studies of seizures and epilepsy. Second, MRS can explain the nature of seizure control and/or provide localization information by measuring metabolic changes. So MRS can be used as a powerful complementary technique to structural MRI for diagnosis and assessment of response to therapy, and measurement of disease progression. The aim of this paper is to review the methodological aspects of 1H-MRS publications between 1994 to 2016, which utilized 1H-MRS in lateralizing the epileptogenic zone in lesional and non-lesional Temporal Lobe Epilepsy (TLE), Extra-Temporal Lobe Epilepsy (ETLE), and generalized epileptic patients to help the spectroscopist, magnetic resonance imaging technologists, and radiologists to improve the overall diagnostic sensitivity in epileptic patients.

Keywords

Proton Magnetic Resonance Spectroscopy; Epilepsy; Temporal Lobe Epilepsy; Juvenile Myoclonic Epilepsy; Generalized Epilepsy.

 

25
Jun

0
Accurate Differentiation of Dyssynergic Defecation Patients from Normal Subjects Based on Abnormal Anorectal Angle in MR Defecography

Accurate Differentiation of Dyssynergic Defecation Patients from Normal Subjects Based on Abnormal Anorectal Angle in MR Defecography

Abstract

Objective: We aimed to study the kinematic indices of the pelvic floor, anorectal angle and the descent of perinea, and the differing movement, in dyssynergic defecation patients in comparison with healthy controls, based on MR defecography.
Materials and Methods: Twenty-two individuals involved with dyssynergic defecation constipation and fourteen healthy asymptomatic subjects fell into this study. In four dynamic pelvic floor MRI indices, namely paradox (unusual change of anorectal angle), perineal descent during straining, perineal ascent, and narrowing of anorectal angle at squeeze, were measured in patients and healthy subjects. Paradox Index had the highest sensitivity (95.45%) and specificity (92.86%) for detection of dyssynergic defecation, with an R2 value of near 1 (0.902). The sensitivity and specificity of other indices were not high; therefore, no significant improvement could be achieved using other indices along with Paradox Index. Negative Predictive Value (92.85%) and Positive Predictive Value (95.45%) were only high in Paradox Index.
Conclusion: Paradox Index was indicated to be the best finding of MR defecography for identifying dyssynergic defecation patients from healthy controls. Hence, MR defecography could be exploited as an authentic tool to manifest the patients the paradoxical function and the relevant muscles of pelvic floor, which could enhance their imagination of the correct defecation pattern during their treatment.

25
Jun

0
extending the application of a magnetic Peg three-part drug release device on a graphene substrate for the removal of gram-positive and gram-negative bacteria and cancerous and pathologic cells

Extending the application of a magnetic PEG three-part drug release device on a graphene substrate for the removal of Gram-positive and Gram-negative bacteria and cancerous and pathologic cells

Abstract

Objective: In this study, novel graphene oxide (GO)-based nanocomposites are presented. In fact, we have tried to replace the carboxyl groups on the surface of GO with amine groups to allow the biocompatible poly(ethylene glycol) bis(carboxymethyl) ether (average Mn 600) polymer to bond through an amide bond.
Materials and Methods: The synthesis was conducted accurately according to final characterization experiments (Raman, X-ray diffraction [XRD], atomic force microscopy [AFM], X-ray photoelectron spectroscopy [XPS], thermogravimetric analysis [TGA], etc). The antimicrobial property of this nanocomposite was examined in Escherichia coli (ATCC 25922) as Gramnegative and Staphylococcus aureus (ATCC 25923) as Gram-positive bacterial species. Besides, curcumin (CUR) was added to the produced nanocomposite both as a promising anticancer drug and an antioxidant, the toxicity of which was then assessed on cellular-based HepG2 and pC12.
Results: An intense increase in toxicity was detected by MTT assay.
Conclusion: It can mainly be concluded that the nanocomposite synthesized in this study is capable of delivering drugs with antibacterial properties.

22
May

0
Generation of MR-Based Attenuation Correction Map of PET Images in the Brain Employing Joint Segmentation of Skull and Soft-Tissue from Single Short-TE MR Imaging Modality

Generation of MR-Based Attenuation Correction Map of PET Images in the Brain Employing Joint Segmentation of Skull and Soft-Tissue from Single Short-TE MR Imaging Modality

Generation of MR-Based Attenuation Correction Map of PET Images in the Brain Employing Joint Segmentation of Skull and Soft-Tissue from Single Short-TE MR Imaging Modality

 

Anahita Fathi Kazerooni, Mohammad Hadi A’arabi, Mohammadreza Ay and Hamidreza Saligheh Rad

 

Abstract

Recently introduced PET/MRI scanners present significant advantages in comparison with PET/CT, including better soft-tissue contrast, lower radiation dose, and truly simultaneous imaging capabilities. However, the lack of an accurate method for generation of MR-based attenuation map (μμ-map) at 511 keV is hampering further development and wider acceptance of this technology. Here, we present a new method for the MR-based attenuation correction map (μμ-map), employing a proposed short echo-time (STE) MR imaging technique along with the nearly automatic segmentation. This method repeatedly applies active contours inhomogeneity correction, multi-class spatial fuzzy clustering (SFCM), followed by shape analysis, to classify the images into cortical bone, air, and soft tissue classes. The proposed segmentation method returned sensitivity of 81 % for cortical bone and above 90 % for soft tissue and air. These results suggest that this technique is accurate, efficient, and robust for discriminating bony structures from the neighboring air and soft tissue in STE-MR images, which is suitable for generating MR-based μμ-maps.

 

Keywords

PET/MRI, Short echo-time (STE) MRI, Attenuation correction, Inhomogeneity correction, Shape analysis, Spatial fuzzy clustering . 

 

22
May

0
Diffusion-Map: A Novel Visualizing Biomarker for Diffusion Tensor Imaging of Human Brain White Matter

Diffusion-Map: A Novel Visualizing Biomarker for Diffusion Tensor Imaging of Human Brain White Matter

Diffusion-Map: A Novel Visualizing Biomarker for Diffusion Tensor Imaging of Human Brain White Matter

 

Mohammad Hadi Aarabi, Hamidreza Saligheh Rad

 

Abstract

Rich information about brain tissue microstructure and composition is yielded by MRI-based measurement of the local diffusion tensor (DT) of water molecules in neural fibers, whose axons are running in myelinated fiber tracts. Diffusion tensor imaging (DTI) possesses high-dimensional and complex structure, so that detecting available pattern information and its analysis based on conventional linear statistics and classification methods become inefficient. Classification, segmentation, compression or visualization of the data could be facilitated through dimension reduction. The previously proposed methods mostly rely on complex low dimensional manifold embedding of the high-dimensional space, which are not able to deal with complex and high dimensional data. The purpose of this paper is to propose a new method for meaningful visualization of brain white matter using diffusion tensor data to map the six-dimensional tensor to a three dimensional space, employing Markov random walk and diffusion distance algorithms, leading to a new distance-preserving map for the DTI data with lower dimension and higher throughput information.

 

Keywords

Fractional Anisotropy, Diffusion Tensor Imaging, Mean Diffusivity, Kernel Principal Component Analysis, Markov Random Walk .

 

19
May

0
Space vector modulation based on classification method in three-phase multi-level voltage source inverters

Space vector modulation based on classification method in three-phase multi-level voltage source inverters

Space vector modulation based on classification method in three-phase multi-level voltage source inverters

 

H Saligheh Rad and A Bakhshai

 

Conference

Proceedings of 9th – Iranian Conference on Electrical Engineering, (ICEE’01), May 2001.

 

Abstract

Space vector modulation (SVM) is commonly in digital implementations of three phase PWM modulators. This paper proposes a general approach to determining sectors and durations associated with SVM in multi-level inverters. The algorithm is exact, fast, and applicable to any number of levels. It is based on a vector classification technique, which allows determination of the switching sequences and the calculation the switching instants in m-level inverters. The proposed technique reduces software complexity, decreases the computation time, and increases the accuracy of the positioning of the switching instants, when compared with the conventional implementation of the SVM in multi-level converters. Results are given for a 3-level inverter.

 

Keywords

Voltage, Support vector machines, Pulse width modulation inverters, Support vector machine classification, Space vector pulse width modulation, Pulse width modulation converters, Classification algorithms, Space technology, Digital modulation, Switching converters .