Browsing by Author "Dr. Naima Amin"

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Acerbic Fluorescent Spectroscopy of Carbon dots for Biomedical Applications
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2020) FAZAL UL NISA; CIIT/SP19-RPH-007/LHR; Dr. Naima Amin; LHR TP 6370
Carbon nanodots are well known in biomedical aspects due to their novel fluorescent properties. Nitrogen based carbon nanodots has showed the great photoluminescence and increased fluorescence quantum yield. The pH in living cells is very important as a lot of physiological systems are working in our body to keep them within a specific range. A slight change in pH can cause imbalance in cell function and growth. There are many diseases, which are associated with pH change (acidic pH) such as cancer, tuberculosis, and infections. Hence, a sensitive and selective system is needed to monitor the pH in living cells. The composition of carbon nanodots with Polypropylene glycol and 1,4- benzenediamine showed better chemical stability, high biocompatibility, intense photoluminescence. Therefore, they can be used to evaluate pH detection in living cells. The purpose of this study is to produce nitrogen-based carbon nanodots that are susceptible to show photoluminescence properties and high quantum yield. NCDs were synthesized via Microwave assisted method which is a very facile and cost-effective technique. The synthesized carbon nanodots were then characterized by using FT-IR, AFM, UV-Vis and Fluorescence spectroscopy. FT-IR spectra confirmed the presence of carboxyl functional groups on the surface of carbon nanodots. AFM results indicates that the produced carbon nanodots are spherical and have diameter in the range of 1-5 nm. All these experiments confirm that synthesized carbon nanodots possess high photoluminescence, better quantum yield henceforward they can be used for pH detection and other biomedical applications
Advancing Breast Cancer Detection: Embedding Nanoparticles into Breast Phantoms for Diagnostic Applications
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) MISBAH ASHIQ; CUI/SP24-RPH-012/LHR; Dr. Naima Amin; LHR TP 10124
In this study, a single-layer homogeneous breast tumor phantom was developed to simulate the diagnostic properties of malignant breast tissue, with the aim of enhancing breast cancer detection and diagnostic accuracy. The tumor-mimicking phantom was fabricated using an optimized gelatin-based hydrogel, incorporating additives such as NaCl, PVA, glycerin, agar, ethanol, and PEG to reproduce the physical consistency and imaging characteristics of tumor tissue. Silver oxide (Ag₂O) and iron oxide (Fe₃O₄) nanoparticles were synthesized using controlled chemical methods and characterized using FTIR, XRD, and SEM to confirm their chemical composition, crystalline structure, and surface morphology, ensuring their suitability for diagnostic imaging applications. The nanoparticles were uniformly incorporated into the tumor phantom through a premixing approach, resulting in a homogeneous distribution that simulates nanoparticle-enhanced tumor tissue. The fabricated tumor phantoms were evaluated using computed tomography (CT) to assess their effectiveness in breast cancer detection. CT imaging demonstrated increased Hounsfield Unit values due to the high atomic number of silvers in Ag₂O nanoparticles, leading to enhanced X-ray attenuation, while MRI scans revealed clear signal suppression and contrast variation in Fe₃O₄- loaded phantoms owing to their superparamagnetic properties. The results confirm that the developed single-layer homogeneous tumor phantom provides a reliable and reproducible model for evaluating nanoparticle-assisted breast cancer detection and precise diagnosis, offering a simplified yet effective platform for imaging system calibration, contrast agent assessment, and preclinical diagnostic studies.
Analyses of HyperArc Treatment Planning for Single and Multiple Brain Metastases
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2021) AYESHA SARWAR; CUI/SP20-RPH-015/LHR; Dr. Naima Amin; LHR TP 7711
HyperArc treatment plan quality was evaluated by four dosimetric indices such as RTOG, Paddick CI, Gradient Index, and New CI. From the Comparison of calculated values of indices with standard values of the dosimetric plan of HyperArc, it is confirmed that HyperArc is an advance and precise technique to treat Brain cancer. Gradient Index value showed some minor deviation of dose to the expected value of dose in the surrounding areas. However, consequences of the penetration of dose are not crucial for human tissues. Our study concluded that HyperArc is the most advanced and safest technique to treat cancer. In this treatment planning, sensitive parts of the face are most probably saved from radiation. the HyperArc is better for the treatment of NPC patients as compared to IMRT and Rapid Arc because HyperArc is good in sparing OAR, and also its coverage is better.
Computerized Medical Image Analysis for Optimization of Cancer
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Zulqarnain Nazir; CIIT/FA23-RPH-041/LHR; Dr. Naima Amin; LHR TP 10116
The medical imaging has a significant role in the diagnosis and management of cancer, but the images produced by medical imaging modalities like MRI and CT usually contain noise, low contrast, and visual artifacts. These artifacts may conceal valuable tumor data and complicate the correct interpretation of clinicians. This thesis is aimed at enhancing medical image quality by means of computerized analysis of images so as to aid in enhancing the evaluation of cancers. Images of different patients acquired by MRI and CT were utilized in standard DICOM format in this study. Ten image enhancement procedures have been used in this study including sharpening, noise reduction, edge retention, contrast enhancement and visualization in three dimensions. The tools that were utilized to complete the analysis were RadiAnt DICOM Viewer and 3D Slicer, which provided the visualization options of the images, multiplanar reconstruction, tumor segmentation, and quantitative analysis. The results shows that image clarity and contrast and noise reduction are greatly enhanced by the use of appropriate enhancement methods. These enhancements contribute to the better visualization of tumor borders and the adjacent organs, resulting in more accurate segmentation and analysis. The improved quality of images also means that repeat scans can be reduced hence the cost and patient exposure can be minimized. On the whole, this study indicates that computerized medical image analysis may be used as a quality tool in streamlining the cancer imaging process and assisting in better diagnosis and treatment planning.
Deep Learning Model for Identifying Organ at Risk Toxicity in Thorax Carcinomas Caused by Radiation Therapy
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2021) Muhammad Mutayyab Ilyas; SP19-RPH-012; Dr. Naima Amin; LHR TP 7253
To assist doctors in making individualized treatment decisions, a machine learning algorithm that can accurately predict toxicity could be used. Patients undergoing thoracic radiation treatment often have organ at risk (OAR) toxicity, which may have a major effect on their health. The use of radiation therapy to treat thorax cancer has been shown to be beneficial. Toxins associated with treatment, on the other hand, are a different story. Treatment-related toxicity is a significant issue because cancer spreads to healthy cells and organs in close proximity. The use of radionics in therapy control strategies has been studied in a number of research features extracted from computed tomography (CT), magnetic resonance imaging (MRI), or dosimetric features collected by 3D dose distributions (DD). Convolutional Neural Networks (CNN) are being used to investigate the toxicity of organs in danger. Image processing, treatment planning, treatment delivery, and post-therapy follow-up are all feasible with a deep learning model. As well as by optimising Using convolution filters during the training stage, a deep learning-based prediction model may discover and fine-tune variables for particular categorization issues. The potential of a deep learning-based estimate technique to reduce the radiation treatment hazard rate is a significant benefit. Furthermore, using convolution methods, the attributes may be obtained automatically (CNN). The objective of this study is to create and test a 3D CNN-based toxicity prediction model. CT images, radiation treatment DD, and contours will be used to extract low and large temporal spatial features utilising (3D) filters, especially in low and large temporal spatial characteristics. The comparative test will demonstrate that the planned model is capable of forecasting OAR toxicity properly. Research into more specific criteria for places that are closely connected to OAR Toxicity might improve the model even further.
Design of Silver Nanoprobe to Construct Sandwich Immunosensor for Early Diagnosis of Dengue Biomarker
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2020) Maryam Awan; CIIT/SP18-RPH-001/LHR; Dr. Naima Amin; LHR TP 6068
Dengue, a viral disease caused by a Flavivirus belonging to family Flaviviridae, is a serious threat to human health in tropical and subtropical regions worldwide. Life-threatening diseases can be caused in human by these parasites and viruses. According to an estimation, Mosquitos transmit diseases to more than seven hundred million people per year. There has been many efforts to control mosquito borne diseases but these disease are still being flourished and are a major concern around the world. For example, Malaria, stays a major reason for deaths particularly amongst infants and children. According to a report, about 1 million deaths and 300-500 million cases of infection are due to malaria. Herein, an antibody functionalized silver-nanoparticle (Ab-Ag NPs) is designed as trace tag for simple, fast, highly sensitive and selective detection of dengue biomarker NS1 using a sandwich type immunosensor. After interacting with capture antibodies modified pencil graphite electrode in the presence of NS1, AbAgNPs can be immobilized on electrode surface via hydrogen-bonding interactions between NS1 and antibody. Well defined and sharp electrochemical signal by the oxidation of Ag NPs present on the detection dengue NS1 antibody is translated into specific detection of NS1. A proportional increase in the faradic current for the oxidation of silver is observed by increasing concentration of analyte NS1. A wide linear range of 3-300 ng/mL with limit of detection 0.5 ng/mL is achieved. The specificity studies evaluating possible interference with analog analytes have been carried out. The NS1 detection experiments are also extended to human serum samples. The designed sandwich type immunosensor strategy with extra-ordinary selectivity and sensitivity may find potential in clinical applications in rapid and early detection of dengue virus. After the formation of samples, different characterization techniques have been used to study their morphological, electrical and structural properties. The detailed information about structure and surface morphology of samples was determined using X-ray fraction (XRD), Raman spectroscopy, Scanning electron microscopy (SEM) and by doing xi electrochemical analysis such as electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV).
Development of Metal Oxide Nanoparticle-Enriched Breast Phantom for Optimization of Radiation in Cancer Therapy
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) NISAR AHMAD; CIIT/FA23-RPH-032/LHR; Dr. Naima Amin; LHR TP 9858
In this study, a multi-layered breast tumor phantom was successfully developed to closely mimic the anatomical and radiological properties of real breast tissues, aiming to enhance the precision and effectiveness of radiotherapy. Four distinct tissue-mimicking layers: skin, fat, lobule and tumor were synthesized using optimized gelatin-based hydrogels, incorporating additives such as NaCl, PVA, glycerin, agar, ethanol, and PEG to replicate tissue-specific characteristics. Iron oxide (Fe₃O₄) nanoparticles were synthesized via the hydrothermal method and characterized using FTIR, XRD, SEM, DLS, and zeta potential analyses, confirming their crystalline structure, morphology, and colloidal stability. Two embedding strategies: premixing and direct injection were employed to incorporate nanoparticles into the tumor layer. The phantoms were irradiated using a 6 MeV photon beam from a linear accelerator (LINAC) with a total dose of 40 Gy. Post-irradiation evaluation using CT and MRI imaging demonstrated a clear contrast at the tumor site; CT scans showed variations in Hounsfield Units indicating localized attenuation, while MRI revealed signal suppression in nanoparticle-loaded regions. The successful fabrication and imaging results confirm that the developed breast phantom not only simulates real breast tissue but also serves as a reliable model for evaluating nanoparticle-based radiation dose enhancement in cancer therapy.
Dosimetric analysis of Rapid Arc (VMAT) treatment planning in head and neck cancer for quality assurance treatment
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2020) ATIKA FAROOQ; CUI/FA18 -RPH-041/LHR; Dr. Naima Amin; LHR TP 6095
neck cancer ,Diametric analysis of Rapid Arc (VMAT) treatment planning in head and neck cancer for quality assurance treatment Aim: Evaluate the plan of simultaneous integrated boost (SIB) fixed intensity modulated radiation therapy (IMRT) and SIB Rapid Arc using dosimetric indices. Material and Method: Twenty-nine patients of nasopharyngeal carcinoma (NPC) were taken for the plan evaluation of SIB rapid arc and SIB IMRT. The plan is evaluated by using conformity index (CI), target coverage (TC), gradient index (GI), external volume Index (EI), homogenity index (HI), dose heterogeneity index (DHI), standard deviation (SD) and unified dosimetric index (UDI). The dose of each planning target volume (PTV) is evaluated by using a mean and median dose of PTVs. The organ at risk dose (OAR) is evaluated by using the mean and maximum dose of OAR. The result is considered statistically significant, if p0.05. Result: CI, TC, GI, EI, and UDI is same for both rapid arc and IMRT. DHI of PTV 54 is better for IMRT as compared to rapid arc and DHI of PTV 60, and PTV 70 is same for both rapid arc and IMRT. HI, SD and sparing of OAR is better for rapid arc as compared to IMRT, The dose of PTV 54 and PTV 60 overdose. The dose of PTV 70 is within the limits of prescribed dose for both rapid arc and IMRT. Conclusion: Rapid arc homogenity, sparing of OAR and SD is better than IMRT. The consumption of time and monitor unit is reduced in the case of rapid arc. Hence, rapid arc is better than IMRT for the treatment of NPC.
Dosimetric Parameter’s Measurement for Different Radiation Beams to Develop a Precise Treatment Plan of Radiation Therapy
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2023) ARZOO ASHRAF CUI/FA21-RPH-031/LHR; CUI/FA21-RPH-031/LHR; Dr. Naima Amin; LHR TP 8595
Radiation therapy is a form of high energy gamma rays which can destroy or prevent the spread of cancer. It has been long known that patients treated with ionizing radiation carry a risk of developing a second cancer in their lifetimes. Factors that contribute to the restate of cancer (or may be called second cancer) includes improved cancer survival rate by using high radiations as well as emerging treatment modalities. These modalities such as intensity-modulated radiation treatment (IMRT). They can potentially elevate secondary exposures to healthy tissues distant from the target volume. In this study, cancer is treated with high-energy radiations. To provide radiation to the organ, external beam radiotherapy is performed. The target volume has been selected is the pelvic organ. The surrounding tissues and OARs of the pelvic organs include the bladder, rectum, small bowl, and LT and RT femoral heads. As a result, the goal of this work is to evaluate and compute the impact of high energy photons on these pelvic surrounding tissues. By using radiation beams for constant half value layer (HVL) and field size we determine the PDD and observe the path of radiation. Also we have check the variation in different parameters for closed applicators and diaphragm limited. For this we calculated values for different depths and field size and observe the PDD. A high energy through linear accelerator is used to strike the target in cancer treatment. Thus Mathematical & biological model (LQM) is used as a tool to calculate the Biological Effective Dose (BED) and Biological Equivalent Dose (EQD2) with dose per fraction for different Organs at Risk (OAR’s) nearer to the pelvic. The LQ model is further examined in the context of tumor control probability (TCP) models. Then we use the Radiobiological considerations can be utilized in a variety of therapeutic settings, and all physicians should be aware of the potential advantages of incorporating a quantitative radiobiological approach into their practice. Moreover, the aim of this study is to provide an understanding of the principles and methods related to scattered doses in surrounding organs to check and optimize the dose plan in radiation therapy by summarizing a large collection of dosimetry and clinical studies.
Dosimetry Audit for Precise Radiotherapy Treatment Planning by Using High-Energy Electron Beam (6-22 MeV)
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2024) Sufia Kiran; CIIT/SP22-RPH-030/LHR; Dr. Naima Amin; LHR TP 10000
It has been long known that patients treated with ionizing radiation carry a risk of developing a second cancer in their lifetimes. Factors that contribute to the restate of cancer (or may be called second cancer) includes improved cancer survival rate by using high radiations as well as emerging treatment modalities. These modalities such as electron beam therapy or external beam radiation therapy. They can potentially elevate secondary exposures to healthy tissues distant from the target volume. The standard Linear-Quadratic (LQ) survival model for electron beam radiotherapy is reviewed with particular emphasis on studying how diﬀerent schedules of radiation treatment planning may be aﬀected by diﬀerent tumour repopulation kinetics. The LQ model is further examined in the context of tumour control probability (TCP) models. A high energy electron (6-22) MeV through linear accelerator is used to strike the target in cancer treatment. In general, radiotherapy has different energy of electron used for cancer treatment which depends on the various factors such as general patient health and history and the stage of the cancer. The crucial problem in the radiotherapy in cancer treatment is that electron beam did not know the difference between healthy and cancerous cell. External beam radiotherapy is used to deliver the radiations to the organ. In this study, beast organ selected as a target volume. The breast organs include surrounding tissues/OARs such as brain, lungs, liver, breast, thyroid and colon. Thus, the purpose of this study is to analyze and calculate the effect of high energy electrons on these surrounding tissues of breast. Thus mathematical & biological model, (LQM) is used as a tool to calculate the Biological Effective Dose (BED) with dose per fraction 1.8 for nearer to the pelvic. Moreover, the aim of this study is to provide an understanding of the principles and methods related to scattered doses (electron beam) in surrounding organs to check and optimize the dose plan in radiation therapy by summarizing a large collection of dosimetry and clinical studies
Fabrication Of Body Equivalent Tissue Phantom For The Evaluation Of Breast Cancer By Radiation Therapy
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2021) ABDUL MUGHNI; CUI/FA18-RPH-048/LHR; LHR TP 7245; Dr. Naima Amin
Preparing a phantom is a highly specialized testing object utilized in medical physics for dosimetry and evaluation of the effect of the dose distribution on cancer cells. The phantom is the best cancer investigational tool for the Medical Physicist. We will be preparing these phantoms to use as our training model. The phantom will be prepared like a real part of the human body tissues. The body or particular organ tissue-equivalent phantom was designed to minimize uncertainties in dosage measurements and treatment plan and also find the track followed by the high energy photon beam. After the preparation of our phantom, we investigate the center and surface doses by the radio-chromic film, it will be helpful in future research. The gel phantom will be irritated with the help of a photon beam and an electron beam of different energies. In this research, we will explore the diffusion of radiation in the irradiated part of the phantom and its effect on normal healthy cells of the phantom. These radiations aim to destroy a cancer cell's DNA. These radiation treatments usually include risks for adjacent healthy tissues within a f ew millimeters. Estimating ionizing radiation is important before cancer therapy. Breast cancer is reinduced by inappropriate radiation usage. Estimation of the radiation dosage may be made more precise for future treatment of any malignancy when the patient is repeatedly irradiated. The main difficulty in radiation treatment is providing a specified dosage to normal tissues. A severe lesion in healthy tissues may impede genome replication and transcription an d, if not corrected, lead to mutations that endanger the survival of cells or organs. Another aspect of this project is to revise the estimation and study of the dose calculation for further cancer treatment to keep safe the human body cells
Fabrication of Breast Cancer Phantom for the Estimation of Radiation Dose in Breast Cancer Radiotherapy
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2022) Sahar Khalid; CIIT/FA20-RPH-008/LHR; Dr. Naima Amin; LHR TP 7975
A Gel-based breast tumor phantom was fabricated to estimate radiation dose in breast cancer radiotherapy. The materials used have similar properties to real tumor tissues. Vegetable oil was used as a source of fats and lipids in the Phantom, while Gelatinwas used as a source of protein to make equivalent breast tumor tissues. NaCl was added to increase the Phantom's conductivity. Different characterization techniques were used to analyze the equivalency of tumor phantom with real breast tumor tissues. The bonding characteristic in FTIR spectra shows different organic compositions in the Phantom. X- ray diffraction was used for structural properties to find crystalline structure in the Phantom. It shows the highest crystalline structure peak at [200] planes due to the presence of NaCl. The swelling test helped to swell the tumor phantom with the right water content equivalent to real tumor tissues. The swelling ratiowas increased until 35 minutes later, and the sample started to degrade. Degradation was used to check the life span of a phantom. 40 Gy of Radiation dose was given to the tumor phantom, which led to the breakage of ester bonds in the Phantom, similar to the breakage of phospholipids in the cell membrane of breast tumor cells after the radiation was given.
METAL NANOPARTICLES DECORATED 2D NANO-MATERIALS FOR BIOSENSING APPLICATIONS
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Ameer Hashim; CIIT/FA23-RPH-043/LHR; Dr. Naima Amin; LHR TP 9866
This thesis aims to develop a novel fluorescence-based sensor for UA detection by integrating MX/CoNFs composites with Rhodamine dye. The sensor is designed to exhibit high sensitivity, selectivity, and stability, overcoming limitations of traditional enzymatic assays. This work begins with the synthesis of MXene nanosheets and CoNFs, followed by the fabrication of the nanocomposite. Comprehensive characterization techniques such as UV-Vis spectroscopy, SEM, XRD, and fluorescence spectroscopy were employed to confirm the structural and optical properties of the materials. The fluorescence sensing mechanism is based on the quenching of Rhodamine fluorescence by the MX/CoNFs nanocomposite, and its subsequent recovery upon the introduction of UA. This “turn-off” response is utilized to quantify UA levels. Various parameters affecting sensor performance, including dye concentration, quenching efficiency, sensitivity, and selectivity against interfering substances, were systematically optimized. The developed sensor is promising a good candidate for practical applications in clinical diagnostics. This work highlights the potential of MXene-based nanohybrids in biosensing and contributes to the growing field of fluorescence spectroscopy for biochemical detection.
MIP based Electrochemical Identification of Rutin using Lead Pencil as An Electrode Source.
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Zahra Munir; CIIT/SP22-RPH-013/LHR; Dr. Naima Amin; LHR TP 9999
In response to the increasing demand for rapid and user-friendly procedures in research laboratories and hospitals, this study introduces a novel and direct electropolymerization method for monitoring Rutin in biological samples and pharmaceutical formulations. A molecularly imprinted pencil graphite electrode was employed, and electropolymerized in situ to create a Molecularly Imprinted Polymer (MIP) network. The electropolymerization process involved Rutin as the template, pyrrole as the monomer, and SnS2/rGO. Experimental parameters were fine-tuned using Differential Pulse Voltammetry (DPV) to optimize MIP efficacy. DPV investigations demonstrated a proportional increase in the peak oxidation signal with decreasing Rutin concentrations, showcasing the sensitivity of the developed method. Rutin concentrations ranging from 0.05nM to 100 µM could be accurately measured, boasting an impressive low detection limit of 0.01 nM. The proposed sensor exhibited exceptional detection capabilities in biological samples spiked with Rutin, highlighting acceptable recovery rates. This innovative electrochemical approach, combining molecular imprinting with electropolymerization, not only offers a sensitive and selective method for Rutin detection but also presents a versatile platform for monitoring other bioactive compounds. The simplicity, efficiency, and low detection limit make it a promising tool for routine analysis in diverse healthcare and pharmaceutical applications.
Pattern Recognition and Deep Learning Models for Cancer Detection
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2023) Mishal Tahir; CIIT\FA21-RPH-020/LHR; Dr. Naima Amin; LHR TP 8591
Cancer, a leading cause of death worldwide, poses challenges due to late-stage detection and inaccurate imaging techniques. Precise and effective screening is crucial for early detection and treatment. Various low-cost and accurate imaging techniques are used, but difficulties arise when experts struggle to interpret certain image areas, leading to missed cancer diagnoses. To address this, computer-based software utilizing deep learning models and algorithms has been developed. Traditional approaches have evolved into computerized tools that analyze, diagnose, and predict symptoms. This study conducted a comparative analysis of three detection models of different frameworks for binary and multi-class image classification using image processing techniques. Despite their distinct inputs, model network architecture Convolutional Neural Networks (CNN). The data were split into sets: training, validation, and testing, and the evaluation involved learning curves of training and validation loss and accuracy as well as a comparison of training, validation, and test accuracies to check the model performances. The results showed the accuracy of all models of predicting unknown images of cancerous or non-cancerous. The Difference in input data and model learning rate could be the reason for variation in test results. Computer language, python, and the platform, Pycharm IDE have been used for tasks performed.
Precise Edge Detection of diseased cell by using MATLAB
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2020) MOAZ BIN NAVEED , MUNEEB SALIM; FA16-BPH-079 , FA16-BPH-025; Dr. Naima Amin; LHR TP 5929
Edge Detection mainly aims at detecting the points in an image which is digital where its brightness change or in other terms ,the one which has discontinuous.it is the basic tool in the case of image processing and machine learning. In our project we collect the DICOM images of the brain affected by a disease known as multiple sclerosis (MS) disease. Different parts of the brain are affected by the MS diseases. This research is particularly designed to diagnose the brain disorder and analysis of the existence of abnormality in the surrounding or adjacent areas of the targeted tissues (abnormal part). This research will be helpful for radiologists for the treatment of abnormality in the targeted area(Lesions) and also in the adjacent areas. It will be helpful for the treatment of abnormality in the different tissues of the body.
Radiation Analysis for Cancer Treatment Indicates Biological Alterations in the Surrounding Tissues
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2024) AMINA SAEED; CUI/SP23-RPH-017/LHR; Dr. Naima Amin; LHR TP 9637
It has been long known that patients treated with ionizing radiation carry a risk of developing a second cancer in their lifetimes. A high-energy electron beam 6 MeV through linear accelerator is used to strike the target in cancer treatment. External beam radiotherapy is used to deliver the radiations to the organ. In this study, breast organ selected as a target volume. The breast organs include surrounding tissues/OARs such as brain, lungs, liver, breast, heart. Thus, the purpose of this study is to analyze and calculate the effect of high-energy electrons on these surrounding tissues of breast. This damage is very important to analyze to the functionality of organs. Surrounding tissues affected by the direct and indirect radiation. Both radiation produce chemical changes in DNA. In this study, we investigate the chemical changes at DNA level to analyze the functionality of organ and the effect of radiation in surrounding tissues. More precise dosimetry can be develop by analysis the effect of radiation in target and surrounding tissues for further treatment.
Significance of Noise Reduction in Magnetic Resonance Imaging for Precise Diagnosis of Normal and Abnormal Tissues
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2020) Muhammad Awais Sardar; FA18-RPH-037; Dr. Naima Amin; LHR TP 6361
Over the past few decades with the invention and use of different medical imaging techniques like CT, MRI, Digital X-Ray and Angiography, its importance has already been proven by the ability of these techniques to diagnose and treat diseases. Medical images are usually low in quality, especially when it comes to image contrast
To Investigate the Absorbed Dose and Consequences of Radiation Therapy in the Surrounding of Cancerous Cell by using High Energy Electron Beam
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2022) Muhammad Haroon Yaqoob; CIIT/FA20-RPH-016/LHR; Dr. Naima Amin; LHR TP 7979
It has been long seen that patient given through ionizing radiation bring a chance of emerging a second cancer in their periods. Causes that contribute to the restate of cancer (or may be called second cancer) contains improved cancer being rate by using high radiations as well as developing treatment sense modality. They could enhance healthy tissues that were set aside from the goal volume for secondary experiences. In this paper, the Linear-Quadratic existence model for outside beam radiation therapy is examined through a focus on just how various radiation treatment development strategies can be impacted via various cancer repopulation kinetics. Tumor control probability (TCP) models are used to further analyze the LQ model. A high energy electron beam 6 MeV through linear accelerator is used to strike the target in cancer treatment. In general, radiotherapy has different energy of electron used for cancer treatment which depends on the various factors such as general patient health and history and the stage of the cancer. The major difficulty in the radiation in cancer treatment is that electron beam did not recognize the distinction between healthy and diseased cell. External beam radiotherapy is used to deliver the radiations to the organ. Pelvic organ selected as a target volume. The pelvic organs include surrounding tissues/ organ at risk (OARs) such as per bladder, rectum, small bowl, Left and Right femoral heads. Thus, the purpose of this learning is to analyze and calculate the consequence of high energy electrons on these surrounding tissues of pelvic. Thus Mathematical & biological model, Linear quadratic model (LQM) is used as a tool to calculate the Biological Effective Dose (BED) and Biological Equivalent Dose (EQD2) with dose per fraction 2 for different Organs at Risk (OAR’s) nearer to the pelvic. Moreover, the aim of this analysis is to require a kind of the principles and methods connected to scattered doses (electron beam) surrounding organ to check and optimize the dose plan in radiation therapy by brief a big compilation of dosimetry and medical surveys.
Utilization of Photoluminescence for the Detection of pH Change in Biological Systems.
(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2023) NASHRAH ARSHAD; CIIT/FA21-RPH-027/LHR; LHR TP 8593; Dr. Naima Amin
Carbon nanodots are well known in the biomedical industry due to their unique fluorescent characteristics. The photoluminescence and fluorescence quantum yield of nitrogen-based carbon nanodots are excellent. The pH in living cells is very important as a lot of physiological systems are working in our body to keep them within a specific range. As a light change in pH can cause imbalance in cell function and growth. There are many diseases, which are associated with pH change (acidic pH) such as cancer, tuberculosis, and infections. Hence, a sensitive and selective system is needed to monitor the pH in living cells. The composition of carbon nanodots with Polyethylene glycol and showed better chemical stability, high biocompatibility, intense photoluminescence. Therefore, they can be used to evaluate pH detection in living cells. The purpose of this study is to produce nitrogen-based carbon nanodots that are susceptible to photoluminescence properties and high quantum yield. NCDs were synthesized via the Hydrothermal method which is a very facile and cost-effective technique. The synthesised carbon nanodots were evaluated employing FT-IR, UV-Vis, and Fluorescence spectroscopy. Carboxyl functional groups were found to be present on the surface of carbon nanodots, according to FT-IR spectra. Particle size results indicate that the produced carbon nanodots are spherical and have diameters in the range of 255 d.nm. All these experiments confirm that synthesized carbon nanodots possess high photoluminescence, better quantum yield hence forward they can be used for pH detection and other biomedical applications