Mohan Jayatilake - Academia.edu (original) (raw)

Papers by Mohan Jayatilake

Research Square (Research Square), Mar 29, 2024

Background: The orbitofrontal cortex (OFC) area plays a critical role in human brain functions. H... more Background: The orbitofrontal cortex (OFC) area plays a critical role in human brain functions. However, susceptibility differences between paranasal sinuses and nasal cavity tissues often cause local field variations in the OFC region during MRI, resulting in image distortions and signal loss. This paper introduces a subject-friendly neck passive shim solution aimed at enhancing field homogeneity in the brain, specifically in the OFC region. Methods: Utilizing 3D gradient-echo pulse sequences, main magnetic field (B 0 ) maps of four subjects' brains were acquired at 4T MRI. Subsequently, these maps were decomposed into spherical harmonic coefficients which were then averaged. Optimal positions for placing shim elements on a semi-cylindrical surface, which was positioned slightly above the neck and below the chin, were computed. The findings indicate a substantial enhancement in B 0 homogeneity, particularly within the OFC region, through the integration of this semi-cylindrical passive shim system in conjunction with the first and second-order active shimming. Utilizing a local dipole passive shim field shows potential for improving field homogeneity in the orbitofrontal region of human brain.

Frontiers in Oncology, Aug 16, 2023

Introduction: Gliomas are still considered as challenging in oncologic management despite the dev... more Introduction: Gliomas are still considered as challenging in oncologic management despite the developments in treatment approaches. The complete elimination of a glioma might not be possible even after a treatment and assessment of therapeutic response is important to determine the future course of actions for patients with such cancers. In the recent years radiomics has emerged as a promising solution with potential applications including prediction of therapeutic response. Hence, this study was focused on investigating whether morphometry-based radiomics signature could be used to predict therapeutic response in patients with gliomas following radiotherapy. Methods: 105 magnetic resonance (MR) images including segmented and nonsegmented images were used to extract morphometric features and develop a morphometry-based radiomics signature. After determining the appropriate machine learning algorithm, a prediction model was developed to predict the therapeutic response eliminating the highly correlated features as well as without eliminating the highly correlated features. Then the model performance was evaluated. Results: Tumor grade had the highest contribution to develop the morphometrybased signature. Random forest provided the highest accuracy to train the prediction model derived from the morphometry-based radiomics signature. An accuracy of 86% and area under the curve (AUC) value of 0.91 were achieved for the prediction model evaluated without eliminating the highly correlated features whereas accuracy and AUC value were 84% and 0.92 respectively for the prediction model evaluated after eliminating the highly correlated features. Discussion: Nonetheless, the developed morphometry-based radiomics signature could be utilized as a noninvasive biomarker for therapeutic response in patients with gliomas following radiotherapy.

Multidisciplinary cancer investigation, 2023

The diagnosis of brain tumors often involves the use of Magnetic Resonance Imaging (MRI), with th... more The diagnosis of brain tumors often involves the use of Magnetic Resonance Imaging (MRI), with the Apparent Diffusion Coefficient (ADC) being a commonly employed technique in current clinical practice. This study seeks to investigate the potential of using statistical texture analysis of MRI-ADC images to distinguish between malignant and benign brain tumors. Methods: The research utilized 980 MRI brain ADC image slices labeled as malignant and 805 labeled as benign from 252 subjects. The clinical diagnosis of each participant was verified by histopathological and radiological reports. The region of interest (ROI) was defined to extract ADC values within the tumor areas. From each ROI, statistical features including higherorder moments of ADC, mean pixel value, and texture features of Grey Level Co-occurrence Matrix (GLCM) were extracted along with patient demographic information. The mean feature values for each category were computed and analyzed using a one-tailed P value test at a 95% confidence level. Results: The average pixel value of ADC, as well as the GLCM texture features (Variance 1, Variance 2, Mean 1, Mean 2, Contrast, and Energy), were found to be significantly higher (P<0.05) for benign tumors. In Contrast, malignant tumors exhibited significantly higher values for kurtosis of ADC and GLCM texture features (Entropy, Homogeneity, and Correlation). The patient's age and other features (skewness of ADC, GLCM texture features such as Shade, Entropy, and Prominence) did not provide sufficient evidence to reject the null hypothesis (P>0.05). Conclusions: In conclusion, the aforementioned features, with the exception of the patient's age, skewness, and GLCM features such as Entropy, Shade, and Prominence can be used as potential biomarkers for distinguishing between benign and malignant brain tumors.

Anuradhapura Medical Journal, May 1, 2023

ISMRM Annual Meeting

JCO clinical cancer informatics, 2023

Background: Apparent Diffusion Coefficient (ADC) of Magnetic Resonance Imaging (MRI) is an indisp... more Background: Apparent Diffusion Coefficient (ADC) of Magnetic Resonance Imaging (MRI) is an indispensable imaging technique in clinical neuroimaging that quantitatively assesses the diffusivity of water molecules within tissues using Diffusion-weighted imaging (DWI). This study focuses on developing a robust Machine Learning (ML) model to predict the aggressiveness of gliomas according to World Health Organization (WHO) grading by analyzing patients’ demographics, higher-order moments, and Grey Level Co-occurrence Matrix (GLCM) texture features of ADC. Methods: A population of 722 labeled MRI-ADC brain image slices from 88 human subjects was selected, where gliomas are labeled as glioblastoma multiforme (WHO-IV), high-grade glioma (WHO-III), and low-grade glioma (WHO I-II). Images were acquired using 3T-MR systems and a region of interest (ROI) was delineated over tumor areas. Skewness, kurtosis, and statistical texture features of GLCM (mean, variance, energy, entropy, contrast, hom...

The precise determination and analysis of T1 is crucial for diagnosis, prognosis, and monitoring ... more The precise determination and analysis of T1 is crucial for diagnosis, prognosis, and monitoring therapeutic response in a variety of diseases such as Acute Myeloid Leukaemia either by comparing the native T1 values in longitudinal studies or by quantifying the physiological parameters in MRI. Therefore, in this study we optimize the accuracy of T1 using the derived uncertainty evaluation expression with the fixed two-flip angles and assess the error of T1 measurement in bone marrow of five Acute Myeloid Leukaemia (AML) patients. MR image data was collected and MATLAB software was used in the image processing and data analysis. For quantitative MRI data analysis, Regions of Interest (ROI) on multiple image slices were drawn encompassing vertebral bodies of L3, L4 and L5. Both the T1 and the uncertainty of T1 were evaluated using the T1 maps obtained. Then the accurate bone marrow mean value of T1 out of five subjects was estimated as 760.3 (ms) at 3T. However, the reported T1 value ...

Introduction: Local susceptibility-induced field variations can lead to inhomogeneities that caus... more Introduction: Local susceptibility-induced field variations can lead to inhomogeneities that cause artifacts such as image distortion and signal loss. In addition to active shimming, localized passive shimming has been used to reduce field deviations over desired regions of interest for high field MRI [1, 2]. For passive shimming, it is advantageous to position shim elements away from the subject to reduce discomfort. Positions for the shim elements can be computed using methods introduced by Romeo and Hoult [4]. Determining the correct magnetic susceptibility and dimensions for the shim pieces is essential for generation of the desired shim fields. In this work, we introduce a method to determine the requisite magnetic susceptibility and dimensions for the shim elements and verify the accuracy of our technique using simulation.

All the data was obtained from the National Hospital of Sri Lanka (NHSL) and the Teaching Hospita... more All the data was obtained from the National Hospital of Sri Lanka (NHSL) and the Teaching Hospital Anuradhapura under the supervision of the Ethical Review Board of NHSL and the Faculty of Medicine, University of peradeniya.

Lecture Notes in Computational Vision and Biomechanics, 2014

Traditional Chinese Medicine, 2007

The application of Diffusion Weighted Imaging (DWI) in cancer identification and discrimination i... more The application of Diffusion Weighted Imaging (DWI) in cancer identification and discrimination is increase singly interest within last decade. DWI has significant advantages, as it does not require contrast medium and provides qualitative and quantitative information that can be helpful for lesion assessment. Therefore, this study presents the utility of skewness and kurtosis of Apparent Diffusion Coefficient (ADC) to distinguish between benign and malignant brain lesions. All the Magnetic Resonance Imaging (MRI) scans were performed with a 3 Tesla Siemens Skyra MR system using a head coil. The sample consists of six subjects with locally advanced brain lesion. The Echo-Planar Imaging pulse sequence was used to acquire axial DW MRI data with a flip angle = \(90^{\circ }\), Time of Echo/Time of Repetition (TE/TR) = 98/6400 ms, Field of View (FOV) = 256 mm, matrix size = 256 \(\times \) 256, slice thickness of 1 mm and two levels of diffusion sensitization (\({\text {b} = 0 \text { a...

Berichte Aus Dem Julius Kuhn Institut, Jun 27, 2012

Einleitung Die Bekämpfung des Apfelschorfes im ökologischen Obstbau ist die kosten-und zeitaufwen... more Einleitung Die Bekämpfung des Apfelschorfes im ökologischen Obstbau ist die kosten-und zeitaufwendigste Pflanzenschutzmaßnahme. Kupferpräparate wirken innerhalb der für den ökologischen Anbau zugelassenen Mittel vergleichsweise gut und sind derzeit nicht zu ersetzen. Vor dem Hintergrund des geplanten EU-weiten Verbots von Kupfer als Pflanzenschutzmittel (ab 2016) ist jedoch die Entwicklung neuer Pflanzenschutzmittel anzustreben. Ziel des Projektes ist es, Verfahren die zur Abtötung bzw. Schwächung der Überdauerungsorgane im Falllaub führen zu entwickeln, um somit den Infektionsdruck im Frühjahr zu verringern. Die auf diese Weise abgeschwächte Wirkung der Primärinfektionen soll den Bedarf an fungiziden Maßnahmen reduzieren und/oder die Effizienz bisher unzureichender Fungizide aus dem Bereich des ökologischen Pflanzenschutzes verstärken.

Falllaubzerstorende Masnahmen im Sinne einer offensiven Bekampfung des Apfelschorfes, Venturia in... more Falllaubzerstorende Masnahmen im Sinne einer offensiven Bekampfung des Apfelschorfes, Venturia inaequalis, fuhren zu einer Abtotung oder Schwachung pilzlicher Strukturen, die im Fruhjahr fur die epidemiologisch entscheidenden primaren Infektionen verantwortlich sind. Die Projektidee war, durch die Verwendung mikrobiologischer Nahrmedien und von Enzymen die naturlichen Mikroben zu fordern und einen zusatzlichen enzymatischen Blattabbau zu erreichen. Bei der Blattzersetzung und insbesondere beim Ascosporenpotential waren durch die applizierten Medien deutliche Effekte zu verzeichnen, wobei eine Korrelation zwischen Zersetzungsrad und vermindertem Ascosporenpotential die Ausnahme war. 19 Medien bewirkten eine uberwiegend deutliche Reduktion des Ascosporenpotentials mit einer Verringerung von bis zu 93 %. Die zellwandabbauenden Enzyme hatten alleine eine deutliche und zusammen mit einigen Medien eine verbesserte Wirkung. Eine direkte Forderung der Askosporenausschleuderung war geringfugig durch einen Extrakt aus Saponaria officinalis und durch einen Rhamnus frangula-Rindenextrakt zu erzielen, wahrend eine schwache Hemmung durch Citrus-Extrakt und eine starke Hemmung durch Kupfer, zuckerartige Stoffe und spezifische Inhibitoren vorlag. In Gewachshausversuchen zur direkten Schorfbekampfung zeigten Extrakte aus Inula viscosa, Quillaja saponaria-Rinde, Citrus-species und S. officinalis eine deutliche Wirkung. ELOT-VIS, CHITOPLANT, COMCAT, LEBERMOOSER, SILIOPLANT und FZB 24 hatten bei den gewahlten Zeitabstanden zur Infektion keine ausreichende Wirkung. Kombinationen aus Quillaja-Saponin und Netzschwefel reduzierten den Schorfbefall sehr stark. In einem Versuch zur Regenstabilitat wiesen der Citrus-Extrakt und das Quillaja-Saponin bereits bei einer simulierten Regenmenge von 5 mm Schwachen in der Wirkung auf. Kombinationen von Citrus-extrakt mit GREEMAX und BIOPLUSS als Haftmittel waren in ihrer Wirkung vergleichbar mit einer Mittelmenge Kupferoxychlorid entsprechend 400 g Reinkupfer je ha.

Tuberculosis (TB) is a dreaded bacterial infection that affects human lungs. It has been known to... more Tuberculosis (TB) is a dreaded bacterial infection that affects human lungs. It has been known to mankind since ancient ages. Tuberculosis ImageCLEF 2018 proposes a set of tasks based on Computed Tomography (CT) scan images of patients’ lungs. They are: multi-drug resistance (MDR) detection, tuberculosis type (TBT) classification and severity scoring (SVR). In this work, two different methods are presented to solve these problems. Texture analysis based methods (3D Modeling and Slice extraction approach) were used to generate feature values from CT scans and different classifiers were tested. 3D Modeling approach calculates seven statistical features of Mean, Skewness, Kurtosis, Homogeneity, Energy, Entropy and Fractal Dimension. And Slice extraction approach calculates 96 dimensional feature vector based on Contrast, Correlation, Energy, Homogeneity, Entropy and Mean. In accordance with the ranking given by the organizers, this approach was ranked 1 for multi-drug resistance detect...

Background: Diffusion-weighted (DW) imaging is a well-recognized magnetic resonance imaging (MRI)... more Background: Diffusion-weighted (DW) imaging is a well-recognized magnetic resonance imaging (MRI) technique that is being routinely used in brain examinations in modern clinical radiology practices. This study focuses on extracting demographic and texture features from MRI Apparent Diffusion Coefficient (ADC) images of human brain tumors, identifying the distribution patterns of each feature and applying Machine Learning (ML) techniques to differentiate malignant from benign brain tumors.Methods: This prospective study was carried out using 1599 labeled MRI brain ADC image slices, 995 malignant, 604 benign from 195 patients who were radiologically diagnosed and histopathologically confirmed as brain tumor patients.The demographics, mean pixel values, skewness, kurtosis, features of Grey Level Co-occurrence Matrix (GLCM), mean, variance, energy, entropy, contrast, homogeneity, correlation, prominence and shade, were extracted from MRI ADC images of each patient.At the feature selecti...

2:00PM A1.00002 Electron Spin Qubits in Si/SiGe Quantum Dots MARK ERIKSSON, University of Wiscons... more 2:00PM A1.00002 Electron Spin Qubits in Si/SiGe Quantum Dots MARK ERIKSSON, University of Wisconsin-Madison-It is intriguing that silicon, the central material of modern classical electronics, also has properties well suited to quantum electronics. Recent advances in Si/SiGe quantum devices have enabled the creation of high-quality silicon quantum dots, also known as artificial atoms. Motivated in part by the potential for very long spin coherence times in this material, we are pursuing the development of individual electron spin qubits in silicon quantum dots. I will discuss recent demonstrations of single-shot spin measurement in a Si/SiGe quantum dot spin qubit, and the demonstration of spin-relaxation times longer than one second in such a system. These and similar measurements depend on a knowledge of tunnel rates between quantum dots and nearby reservoirs or between pairs of quantum dots. Measurements of such rates provide an opportunity to revisit classic experiments in quantum mechanics. At the same time, the unique features of the silicon conduction band lead to novel and unexpected effects, demonstrating that Si/SiGe quantum dots provide a highly controlled experimental system in which to study ideas at the heart of quantum physics.

Optimal image quality for Magnetic Resonance Imaging (MRI) at high fields requires a homogeneous ... more Optimal image quality for Magnetic Resonance Imaging (MRI) at high fields requires a homogeneous RF (B1) field; however, the dielectric properties of the human brain result in B1 field inhomogeneities and signal loss at the periphery of the head. These result from constructive and destructive RF interactions of complex wave behaviour, which become worse with increasing magnetic field strength. Placement of a shim object with high-dielectric constant adjacent to the body has been proposed as a method for reducing B1 inhomogeneity by altering wave propagation within the volume of interest. Selecting the appropriate permittivity and quantity of material for the shim is essential. Whereas previous work has determined the dielectric properties of the shim empirically, this work introduces an improved theoretical framework for determining the requisite dielectric constant of the passive shim material directly by increasing the axial or minimizing the radial propagation constant.