Pub Date : 2023-12-26DOI: 10.18502/fbt.v11i1.14518
Niloofar Yousefi Moteghaed, Ali Fatemi, Ahmad Mostaar
Purpose: Magnetic Resonance Imaging (MRI) applications offer superior soft tissue contrast compared with Computed Tomography (CT) for accurate radiotherapy planning although MRI images suffer from poor image quality and lack electron density for radiation dose calculation. The present study aims to use the Deep Learning (DL) approach to 1) enhance the quality of MRI images and 2) generate synthetic CT images using MRI images for more accurate radiotherapy planning. Materials and Methods: In this paper, the pix2pix Generative Adversarial Network was utilized to synthesize CT images from noisy MRI images of 20 arbitrarily patients with brain disease. The standard statistical measurements investigated the accuracy comparison of the modeled Hounsfield Unit (HU) value from MRI images and referenced CT of each patient. The famous quality metrics that were used to compare synthetic CTs and referenced CTs were the Mean Absolute eError (MAE), the structural similarity index (SSIM), and the Peak Signal-to-Noise Ratio (PSNR). Results: The higher quality measurements between the synthetic pseudo-CT and the referenced CT images as PSNR and SSIM should correlate with the lower MAE value. For the overall brain among blind test data, the measured peak signal-to-noise ratio, mean absolute error, and structural similarity index values were about 16.5, 28.13, and 93.46, respectively. Conclusion: The proposed method provides an acceptable level of statistical measurements computed on the Pseudo-CT and referenced CT, and it could be concluded that the p-CT can be implemented in radiotherapy treatment planning with acceptable accuracy.
{"title":"Pseudo-Computed Tomography Generation from Noisy Magnetic Resonance Imaging with Deep Learning Algorithm","authors":"Niloofar Yousefi Moteghaed, Ali Fatemi, Ahmad Mostaar","doi":"10.18502/fbt.v11i1.14518","DOIUrl":"https://doi.org/10.18502/fbt.v11i1.14518","url":null,"abstract":"Purpose: Magnetic Resonance Imaging (MRI) applications offer superior soft tissue contrast compared with Computed Tomography (CT) for accurate radiotherapy planning although MRI images suffer from poor image quality and lack electron density for radiation dose calculation. The present study aims to use the Deep Learning (DL) approach to 1) enhance the quality of MRI images and 2) generate synthetic CT images using MRI images for more accurate radiotherapy planning. Materials and Methods: In this paper, the pix2pix Generative Adversarial Network was utilized to synthesize CT images from noisy MRI images of 20 arbitrarily patients with brain disease. The standard statistical measurements investigated the accuracy comparison of the modeled Hounsfield Unit (HU) value from MRI images and referenced CT of each patient. The famous quality metrics that were used to compare synthetic CTs and referenced CTs were the Mean Absolute eError (MAE), the structural similarity index (SSIM), and the Peak Signal-to-Noise Ratio (PSNR). Results: The higher quality measurements between the synthetic pseudo-CT and the referenced CT images as PSNR and SSIM should correlate with the lower MAE value. For the overall brain among blind test data, the measured peak signal-to-noise ratio, mean absolute error, and structural similarity index values were about 16.5, 28.13, and 93.46, respectively. Conclusion: The proposed method provides an acceptable level of statistical measurements computed on the Pseudo-CT and referenced CT, and it could be concluded that the p-CT can be implemented in radiotherapy treatment planning with acceptable accuracy.","PeriodicalId":34203,"journal":{"name":"Frontiers in Biomedical Technologies","volume":"4 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139155568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-26DOI: 10.18502/fbt.v11i1.14512
Hamid Khabiri, Mohammad Naseh Talebi, Mehdi Fakhimi Kamran, Shadi Akbari, Farzaneh Zarrin, Fatemeh Mohandesi
Purpose: Listening to music has a great impact on people's emotions and would change brain activity. In other words, music-induced emotions are trackable in electrical brain activities. Therefore, Electroencephalography can be a suitable tool to detect these induced emotions. The present study attempted to use electroencephalography in to recognize four types of emotions (happy, relaxing, stressful, and sad) induced in response to listening to music excerpts, using three classifiers. Materials and Methods: In this empirical study, electroencephalography signals were collected from 20 participants, as they were listening to pieces of selected music. The collected data were then pre-processed, and 28 linear and nonlinear features for recognizing the aforementioned emotions were extracted. Feature-space components were then reduced through a principal components analysis. Finally, the first ten components of feature-space were used as input for three classifiers based on Neural Network (NN), K-Nearest Neighbors (KNN), and Support Vector Machine (SVM) algorithms to identify the induced emotions. Results: The outputs showed that the suggested method was well capable of emotion recognition. Evaluating the music excerpts, on the self-assessment manikin scale, demonstrated that the labeling of the music tracks was accurate. The highest accuracy found among NN, KNN, and SVM algorithms were %84, %84, and %89 for happy emotions, respectively. Conclusion: The findings of this study provide useful insights into emotion classification and brain behavior related to induced emotion extraction. Happiness was the most recognizable emotion and the support vector machine had the highest performance among the classifiers. In the end, the outcomes of the proposed method demonstrate that this system is better than the previous research in EEG-based emotion recognition.
{"title":"Music-Induced Emotion Recognition Based on Feature Reduction Using PCA From EEG Signals","authors":"Hamid Khabiri, Mohammad Naseh Talebi, Mehdi Fakhimi Kamran, Shadi Akbari, Farzaneh Zarrin, Fatemeh Mohandesi","doi":"10.18502/fbt.v11i1.14512","DOIUrl":"https://doi.org/10.18502/fbt.v11i1.14512","url":null,"abstract":"Purpose: Listening to music has a great impact on people's emotions and would change brain activity. In other words, music-induced emotions are trackable in electrical brain activities. Therefore, Electroencephalography can be a suitable tool to detect these induced emotions. The present study attempted to use electroencephalography in to recognize four types of emotions (happy, relaxing, stressful, and sad) induced in response to listening to music excerpts, using three classifiers. Materials and Methods: In this empirical study, electroencephalography signals were collected from 20 participants, as they were listening to pieces of selected music. The collected data were then pre-processed, and 28 linear and nonlinear features for recognizing the aforementioned emotions were extracted. Feature-space components were then reduced through a principal components analysis. Finally, the first ten components of feature-space were used as input for three classifiers based on Neural Network (NN), K-Nearest Neighbors (KNN), and Support Vector Machine (SVM) algorithms to identify the induced emotions. Results: The outputs showed that the suggested method was well capable of emotion recognition. Evaluating the music excerpts, on the self-assessment manikin scale, demonstrated that the labeling of the music tracks was accurate. The highest accuracy found among NN, KNN, and SVM algorithms were %84, %84, and %89 for happy emotions, respectively. Conclusion: The findings of this study provide useful insights into emotion classification and brain behavior related to induced emotion extraction. Happiness was the most recognizable emotion and the support vector machine had the highest performance among the classifiers. In the end, the outcomes of the proposed method demonstrate that this system is better than the previous research in EEG-based emotion recognition.","PeriodicalId":34203,"journal":{"name":"Frontiers in Biomedical Technologies","volume":"13 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139155306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-25DOI: 10.18502/fbt.v11i1.14503
A. Tarighatnia, Golshan Mahmoudi, Mahnaz Kiani, Nader D. Nader
Hybrid Nanoparticles (NPs) have emerged as promising tools in cancer diagnosis and treatment, offering the potential for early detection and precise eradication of malignant cells by integrating diverse materials. However, navigating this domain's intricacies, limitations, and hurdles underscores the importance of thoughtful decision-making. This editorial provides a comprehensive exploration of the merits and challenges of nanotechnology in the context of cancer diagnosis, therapy, and theranostics. It sheds light on the current applications and delves into the promising prospects in this field. This editorial aims to foster a deeper understanding of the intricacies of designing efficient protocols for hybrid NP production, contributing to advancing cancer management strategies.
{"title":"Current Challenges and New Opportunities of Hybrid Nanoparticles for Diagnosis and Treatment of Cancer","authors":"A. Tarighatnia, Golshan Mahmoudi, Mahnaz Kiani, Nader D. Nader","doi":"10.18502/fbt.v11i1.14503","DOIUrl":"https://doi.org/10.18502/fbt.v11i1.14503","url":null,"abstract":"Hybrid Nanoparticles (NPs) have emerged as promising tools in cancer diagnosis and treatment, offering the potential for early detection and precise eradication of malignant cells by integrating diverse materials. However, navigating this domain's intricacies, limitations, and hurdles underscores the importance of thoughtful decision-making. This editorial provides a comprehensive exploration of the merits and challenges of nanotechnology in the context of cancer diagnosis, therapy, and theranostics. It sheds light on the current applications and delves into the promising prospects in this field. This editorial aims to foster a deeper understanding of the intricacies of designing efficient protocols for hybrid NP production, contributing to advancing cancer management strategies.","PeriodicalId":34203,"journal":{"name":"Frontiers in Biomedical Technologies","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139159478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Purpose: The mortality rate of fetuses due to heart defects is a major concern for clinicians. The fetus's heart is monitored non-invasively using the abdominal Electrocardiogram (ECG) of the mother. Most of the methods in literature diagnose fetal arrhythmia based on fetal heart rate. However, there are various challenges in fetal heart rate monitoring and arrhythmia detection. Therefore, very few methods are explored for fetal arrhythmia classification and have not achieved promising results.
Materials and Methods: In this article, a fetal arrhythmia classification method is investigated. The method has exploited the transfer learning principle where DenseNet architecture is utilized to learn fetal ECG patterns. Fetal ECG (fECG) signal extracted from the mothers abdominal has been processed for denoising and heartbeats are segmented using signal processing techniques. The extracted heartbeats have transformed into 2D fECG images to re-train the pre-trained DenseNet architecture.
Results: The proposed method has been evaluated on the publicly available Non-Invasive Fetal Arrhythmia Database (NIFADB) of Physionet and achieved 98.56% classification accuracy, thus outperforming other existing methods.
Conclusion: The arrhythmia in a fetus can be detected using a non-invasive fetal ECG. Due to the faster convergence of the learning algorithm, the proposed method offers better fetal diagnosis in real-time.
{"title":"Fetal ECG Arrhythmia Detection Based on DensNet Transfer Learning","authors":"Rajeev Kumar Rai, Ashutosh Singh, Ranjeet Srivastva, Gyanendra Kumar","doi":"10.18502/fbt.v10i4.13723","DOIUrl":"https://doi.org/10.18502/fbt.v10i4.13723","url":null,"abstract":"Purpose: The mortality rate of fetuses due to heart defects is a major concern for clinicians. The fetus's heart is monitored non-invasively using the abdominal Electrocardiogram (ECG) of the mother. Most of the methods in literature diagnose fetal arrhythmia based on fetal heart rate. However, there are various challenges in fetal heart rate monitoring and arrhythmia detection. Therefore, very few methods are explored for fetal arrhythmia classification and have not achieved promising results.
 Materials and Methods: In this article, a fetal arrhythmia classification method is investigated. The method has exploited the transfer learning principle where DenseNet architecture is utilized to learn fetal ECG patterns. Fetal ECG (fECG) signal extracted from the mothers abdominal has been processed for denoising and heartbeats are segmented using signal processing techniques. The extracted heartbeats have transformed into 2D fECG images to re-train the pre-trained DenseNet architecture.
 Results: The proposed method has been evaluated on the publicly available Non-Invasive Fetal Arrhythmia Database (NIFADB) of Physionet and achieved 98.56% classification accuracy, thus outperforming other existing methods.
 Conclusion: The arrhythmia in a fetus can be detected using a non-invasive fetal ECG. Due to the faster convergence of the learning algorithm, the proposed method offers better fetal diagnosis in real-time.","PeriodicalId":34203,"journal":{"name":"Frontiers in Biomedical Technologies","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135246618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-29DOI: 10.18502/fbt.v10i4.13731
Zahra Farzanegan, Fatemeh Sadat Sadeghpour
Purpose: Considering the high prevalence of breast cancer and the radiation sensitivity of breast tissue, it is necessary to optimize the treatment process of this tumor, especially when using radiation therapy methods.
The present study was conducted to investigate the effect and complications of new anti-estrogens on the effectiveness of breast cancer treatment.
Materials and Methods: Articles were searched in PubMed, Science direct, Embassy, Cochran, and Scopus databases using the keywords Cancer AND Anti-estrogen, Breast Cancer AND anti-estrogen AND mice, Breast cancer And anti-estrogen AND rat. The authors reviewed the abstract and full text of the articles and the relevant studies were selected for systematic review.
Results: The anti-estrogens used in the reviewed studies included TAM, RAL, SS1020, SS1010, GW5638, OSP, 4-OHTAM, and TOR. Anti-estrogen-related side effects included liver and uterine complications, especially in the case of using TAM anti-estrogen (54%). Moreover, uterine hypertrophy was observed using GW5638, RAL, and SS1010 anti-estrogens; while it happened with a lower percentage than TAM, 16%, 14%, and 13%, respectively. Side effects were significantly reduced by reducing the prescribed dose. So that this reduction for TAM is from 54% to 33%. In relation to the effect of antiestrogens on tumor treatment, the most effective and least complications were related to the antiestrogen "SS1020".
Conclusion: Based on the results of reviewed studies, SS1020, which has no estrogenic and genotoxic activity, was safe and the most effective anti-estrogen against breast cancer in animals and also in humans.
目的:考虑到乳腺癌的高患病率和乳腺组织的辐射敏感性，有必要优化该肿瘤的治疗过程，特别是在使用放射治疗方法时。
本研究旨在探讨新型抗雌激素药物对乳腺癌治疗效果的影响及并发症。
材料和方法:文章在PubMed, Science direct, Embassy, Cochran和Scopus数据库中检索，关键词为Cancer and Anti-estrogen and mouse, Breast Cancer and Anti-estrogen and mouse, Breast Cancer and Anti-estrogen and rat。作者对文章的摘要和全文进行审阅，并选择相关研究进行系统综述。
结果:研究中使用的抗雌激素包括TAM、RAL、SS1020、SS1010、GW5638、OSP、4-OHTAM和TOR。抗雌激素相关副作用包括肝脏和子宫并发症，特别是在使用TAM抗雌激素的情况下(54%)。此外，使用GW5638、RAL和SS1010抗雌激素可观察到子宫肥大;而这一比例低于TAM，分别为16%、14%和13%。通过减少处方剂量，副作用明显减少。TAM从54%减少到33%在抗雌激素治疗肿瘤的效果方面，抗雌激素“SS1020”疗效最好，并发症最少。结论:基于所回顾的研究结果，SS1020无雌激素和遗传毒性活性，是动物和人类抗乳腺癌最安全、最有效的雌激素。
{"title":"The New Anti-Estrogens with Anti-Cancer Properties for Breast Cancer","authors":"Zahra Farzanegan, Fatemeh Sadat Sadeghpour","doi":"10.18502/fbt.v10i4.13731","DOIUrl":"https://doi.org/10.18502/fbt.v10i4.13731","url":null,"abstract":"Purpose: Considering the high prevalence of breast cancer and the radiation sensitivity of breast tissue, it is necessary to optimize the treatment process of this tumor, especially when using radiation therapy methods.
 The present study was conducted to investigate the effect and complications of new anti-estrogens on the effectiveness of breast cancer treatment.
 Materials and Methods: Articles were searched in PubMed, Science direct, Embassy, Cochran, and Scopus databases using the keywords Cancer AND Anti-estrogen, Breast Cancer AND anti-estrogen AND mice, Breast cancer And anti-estrogen AND rat. The authors reviewed the abstract and full text of the articles and the relevant studies were selected for systematic review.
 Results: The anti-estrogens used in the reviewed studies included TAM, RAL, SS1020, SS1010, GW5638, OSP, 4-OHTAM, and TOR. Anti-estrogen-related side effects included liver and uterine complications, especially in the case of using TAM anti-estrogen (54%). Moreover, uterine hypertrophy was observed using GW5638, RAL, and SS1010 anti-estrogens; while it happened with a lower percentage than TAM, 16%, 14%, and 13%, respectively. Side effects were significantly reduced by reducing the prescribed dose. So that this reduction for TAM is from 54% to 33%. In relation to the effect of antiestrogens on tumor treatment, the most effective and least complications were related to the antiestrogen \"SS1020\".
 Conclusion: Based on the results of reviewed studies, SS1020, which has no estrogenic and genotoxic activity, was safe and the most effective anti-estrogen against breast cancer in animals and also in humans.","PeriodicalId":34203,"journal":{"name":"Frontiers in Biomedical Technologies","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135246743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-29DOI: 10.18502/fbt.v10i4.13720
Mohsen Kohanpour, Sobhan Aarabi, Seyed Amir Hossein Batouli, Soodeh Moallemian, Mohammad Ali Oghabian
Purpose: Olfactory system is a vital sensory system in mammals, giving them the ability to connect with their environment. Anosmia, or the complete loss of olfaction ability, which could be caused by injuries, is an interesting topic for inspectors with the aim of diagnosing patients. Sniffing test is currently utilized to examine if an individual is suffering from anosmia; however, functional Magnetic Resonance Imaging (fMRI) provides unique information about the structure and function of the different areas of the human brain, and therefore this noninvasive method could be used as a tool to locate the olfactory-related regions of the brain.
Materials and Methods: In this study, by recruiting 31 healthy and anosmic individuals, we investigated the neural Blood Oxygenation Level Dependent (BOLD) responses in the olfactory cortices following two odor stimuli, rose and eucalyptus, by using a 3T MR scanner.
Results: Comparing the two groups, we observed a network of brain areas being more active in normal individuals when smelling the odors. In addition, a number of brain areas also showed an activation decline during the odor stimuli, which is hypothesized as a resource allocation deactivation.
Conclusion: This study illustrated alterations in the brain activity between normal individuals and anosmic patients when smelling odors, and could potentially help for a better anosmia diagnosis in the future.
{"title":"A Different Olfactory Perception in Anosmic Patients: Evidence from Functional MRI","authors":"Mohsen Kohanpour, Sobhan Aarabi, Seyed Amir Hossein Batouli, Soodeh Moallemian, Mohammad Ali Oghabian","doi":"10.18502/fbt.v10i4.13720","DOIUrl":"https://doi.org/10.18502/fbt.v10i4.13720","url":null,"abstract":"Purpose: Olfactory system is a vital sensory system in mammals, giving them the ability to connect with their environment. Anosmia, or the complete loss of olfaction ability, which could be caused by injuries, is an interesting topic for inspectors with the aim of diagnosing patients. Sniffing test is currently utilized to examine if an individual is suffering from anosmia; however, functional Magnetic Resonance Imaging (fMRI) provides unique information about the structure and function of the different areas of the human brain, and therefore this noninvasive method could be used as a tool to locate the olfactory-related regions of the brain.
 Materials and Methods: In this study, by recruiting 31 healthy and anosmic individuals, we investigated the neural Blood Oxygenation Level Dependent (BOLD) responses in the olfactory cortices following two odor stimuli, rose and eucalyptus, by using a 3T MR scanner.
 Results: Comparing the two groups, we observed a network of brain areas being more active in normal individuals when smelling the odors. In addition, a number of brain areas also showed an activation decline during the odor stimuli, which is hypothesized as a resource allocation deactivation.
 Conclusion: This study illustrated alterations in the brain activity between normal individuals and anosmic patients when smelling odors, and could potentially help for a better anosmia diagnosis in the future.","PeriodicalId":34203,"journal":{"name":"Frontiers in Biomedical Technologies","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135246742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-29DOI: 10.18502/fbt.v10i4.13730
Parth Pandey, Himanshu Pandey, Khushi Srivastava
Purpose: Human Immunodeficiency Virus (HIV) continues to be a disease that kills thousands of individuals each year. The HIV infection is incurable. However, HIV infection has turned into a treatable chronic health condition because of improved access to efficient HIV prevention, diagnosis, treatment, and care. Transmission Electron Microscopy’s (TEM) ability to directly visualize virus particles and distinguish ultrastructure morphology at the nanometer scale, makes it useful in HIV-1 research where it is used for assessing the actions of inhibitors that obstruct the maturation and morphogenesis phases of the virus lifecycle. Hence with its use, the disease's serious stage can be avoided by receiving an early diagnosis.
Materials and Methods: Through the dedicated use of computer vision frameworks and machine learning techniques, we have developed an optimized low-computational-cost 8-layer Convolutional Neural Network (CNN) backbone capable of classifying HIV-1 virions at various stages of maturity and morphogenesis. The dataset including TEM images of HIV-1 viral life cycle phases is analysed and augmented through various techniques to make the framework robust in real-time. The CNN layers then extract pertinent disease traits from TEM images and utilise them to provide diagnostic predictions.
Results: It was discovered that the framework performed with an accuracy of 99.76% on the training set, 85.83% on the validation set, and 91.33% on the test set, after being trained on a wide range of micrographs which comprised of different experimental samples and magnifications.
Conclusion: The suggested network's performance was compared to that of other state-of-the-art networks, and it was discovered that the proposed model was undisputed for classifying TEM images of unseen HIV-1 virion and required less time to train and tweak its weights. The framework can operate more effectively than machine learning algorithms that consume a lot of resources and can be deployed with limited computation and memory resource requirements.
{"title":"HivNet: Studying in Depth the Morphology of HIV-1 Virion Using Deep Learning","authors":"Parth Pandey, Himanshu Pandey, Khushi Srivastava","doi":"10.18502/fbt.v10i4.13730","DOIUrl":"https://doi.org/10.18502/fbt.v10i4.13730","url":null,"abstract":"Purpose: Human Immunodeficiency Virus (HIV) continues to be a disease that kills thousands of individuals each year. The HIV infection is incurable. However, HIV infection has turned into a treatable chronic health condition because of improved access to efficient HIV prevention, diagnosis, treatment, and care. Transmission Electron Microscopy’s (TEM) ability to directly visualize virus particles and distinguish ultrastructure morphology at the nanometer scale, makes it useful in HIV-1 research where it is used for assessing the actions of inhibitors that obstruct the maturation and morphogenesis phases of the virus lifecycle. Hence with its use, the disease's serious stage can be avoided by receiving an early diagnosis.
 Materials and Methods: Through the dedicated use of computer vision frameworks and machine learning techniques, we have developed an optimized low-computational-cost 8-layer Convolutional Neural Network (CNN) backbone capable of classifying HIV-1 virions at various stages of maturity and morphogenesis. The dataset including TEM images of HIV-1 viral life cycle phases is analysed and augmented through various techniques to make the framework robust in real-time. The CNN layers then extract pertinent disease traits from TEM images and utilise them to provide diagnostic predictions.
 Results: It was discovered that the framework performed with an accuracy of 99.76% on the training set, 85.83% on the validation set, and 91.33% on the test set, after being trained on a wide range of micrographs which comprised of different experimental samples and magnifications.
 Conclusion: The suggested network's performance was compared to that of other state-of-the-art networks, and it was discovered that the proposed model was undisputed for classifying TEM images of unseen HIV-1 virion and required less time to train and tweak its weights. The framework can operate more effectively than machine learning algorithms that consume a lot of resources and can be deployed with limited computation and memory resource requirements.","PeriodicalId":34203,"journal":{"name":"Frontiers in Biomedical Technologies","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135198891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-29DOI: 10.18502/fbt.v10i4.13721
Shiva Rahbar Yazdi, Saman Dalvand, Mohammad Ali Broomand, Hamed Zamani, Mohammad Hossein Zare, Hamidreza Masjedi
Purpose: The purpose of this study was to evaluate the risk of gonad cancer induction in adults with pelvic cancer (bladder, rectum, endometriosis) after radiation therapy.
Materials and Methods: In two fractions of radiotherapy, Thermo Luminescence Dosimeters (TLDs) measured the peripheral dose to the testis and ovary. With 3D planning, all patients received a 45 Gy total dose in four fields in the prone position. Researchers investigated the doses produced by linear accelerators operating at 18 MeV.
Results: The mean Excess Relative Risk (ERR) was measured based on the BEIR IIV models. Right pelvic radiotherapy of men was 0.795 ± 0.168 and 0.675 ± 0.134, and for women was 1.015 ± 0.561 and 0.884 ± 0.468 after 5 and 10 years of treatment, respectively. Left pelvic radiotherapy was 0.855 ± 0.172, 0.725 ± 0.138 for men and 0.880 ± 0.464, 0.722 ± 0.342 for women respectively (95% confidence interval). These values for women were higher (p < 0.05).
Conclusion: Estimating the second cancer risk of untargeted organs is crucial in radiotherapy. The out-of-field doses can be minimized by using a linear accelerator with a single energy mode and proper shields.
{"title":"Gonads Exposure to Scattered Radiation and Associated Second Cancer Risk from Pelvic Radiotherapy","authors":"Shiva Rahbar Yazdi, Saman Dalvand, Mohammad Ali Broomand, Hamed Zamani, Mohammad Hossein Zare, Hamidreza Masjedi","doi":"10.18502/fbt.v10i4.13721","DOIUrl":"https://doi.org/10.18502/fbt.v10i4.13721","url":null,"abstract":"Purpose: The purpose of this study was to evaluate the risk of gonad cancer induction in adults with pelvic cancer (bladder, rectum, endometriosis) after radiation therapy.
 Materials and Methods: In two fractions of radiotherapy, Thermo Luminescence Dosimeters (TLDs) measured the peripheral dose to the testis and ovary. With 3D planning, all patients received a 45 Gy total dose in four fields in the prone position. Researchers investigated the doses produced by linear accelerators operating at 18 MeV.
 Results: The mean Excess Relative Risk (ERR) was measured based on the BEIR IIV models. Right pelvic radiotherapy of men was 0.795 ± 0.168 and 0.675 ± 0.134, and for women was 1.015 ± 0.561 and 0.884 ± 0.468 after 5 and 10 years of treatment, respectively. Left pelvic radiotherapy was 0.855 ± 0.172, 0.725 ± 0.138 for men and 0.880 ± 0.464, 0.722 ± 0.342 for women respectively (95% confidence interval). These values for women were higher (p < 0.05).
 Conclusion: Estimating the second cancer risk of untargeted organs is crucial in radiotherapy. The out-of-field doses can be minimized by using a linear accelerator with a single energy mode and proper shields.","PeriodicalId":34203,"journal":{"name":"Frontiers in Biomedical Technologies","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135199191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-29DOI: 10.18502/fbt.v10i4.13727
Sara Ghanavati, Nahid Makiabadi, Sajad Keshavarz, Hosein Ghiasi
Purpose: Shielding against radiation in radiotherapy and radiology requires deep knowledge of radiation physics and shielding design methods. The application of nanoparticles in the photon and neutron dose moderation has been proven in the literature.
Materials and Methods: Effective neutron mass removal cross-section (ΣR/ρ) was for the ordinary concrete doped with 50nm in diameter nanosphers mixture of Fe2O3(5%), WO3(5%), B4H (5%), Pb2O3(5%) was estimated with MCNP5 Monte Carlo (MC) code and N-XCOM computational program. An 18MV linac room made of the nanoparticles dopped ordinarily simulated. Additionally, the room was considered with three legs in the maze and photoneutron and capture γ-ray Dose Equivalent (DE) were estimated at the modeled rooms maze.
Results: Total ΣR/ρ with energies 100 keV-2000keV was estimated using MC and N-XCOM as 0.02802-0.02687 cm2/gand 0.02810- 0.02687 cm2/g, respectively. Total ΣR/ρ of the neutron for the pure ordinary concrete was estimated by MC code and N-XCOM with energies 100 keV-2000keV as 0.02802-0.02687 cm2/g and 0.02810- 0.02687 cm2/g. Borated Polyethylene (BPE) and Lead required thickness calculated as 7.43×10-06 mm and 4.73×10-06 mm for the capture γ-ray shielding.
{"title":"Characterization of the Radiation Contamination in an 18MV Linac Treatment Room Made of some Nanoparticles Mixture","authors":"Sara Ghanavati, Nahid Makiabadi, Sajad Keshavarz, Hosein Ghiasi","doi":"10.18502/fbt.v10i4.13727","DOIUrl":"https://doi.org/10.18502/fbt.v10i4.13727","url":null,"abstract":"Purpose: Shielding against radiation in radiotherapy and radiology requires deep knowledge of radiation physics and shielding design methods. The application of nanoparticles in the photon and neutron dose moderation has been proven in the literature.
 Materials and Methods: Effective neutron mass removal cross-section (ΣR/ρ) was for the ordinary concrete doped with 50nm in diameter nanosphers mixture of Fe2O3(5%), WO3(5%), B4H (5%), Pb2O3(5%) was estimated with MCNP5 Monte Carlo (MC) code and N-XCOM computational program. An 18MV linac room made of the nanoparticles dopped ordinarily simulated. Additionally, the room was considered with three legs in the maze and photoneutron and capture γ-ray Dose Equivalent (DE) were estimated at the modeled rooms maze.
 Results: Total ΣR/ρ with energies 100 keV-2000keV was estimated using MC and N-XCOM as 0.02802-0.02687 cm2/gand 0.02810- 0.02687 cm2/g, respectively. Total ΣR/ρ of the neutron for the pure ordinary concrete was estimated by MC code and N-XCOM with energies 100 keV-2000keV as 0.02802-0.02687 cm2/g and 0.02810- 0.02687 cm2/g. Borated Polyethylene (BPE) and Lead required thickness calculated as 7.43×10-06 mm and 4.73×10-06 mm for the capture γ-ray shielding.","PeriodicalId":34203,"journal":{"name":"Frontiers in Biomedical Technologies","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135246466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-29DOI: 10.18502/fbt.v10i4.13726
Mohammad Hossein Jamshidi, Aida Karami, Jalal Ordoni, Salar Bijari
Purpose: The danger of radiation at low doses continues linearly, and without a threshold, investigations concluded that although the risk of cancer from Computed Tomography (CT) scans is low, it is not zero.
This study aims to determine the patient's radiation dose and estimate the Lifetime Attributable Risk (LAR) of cancer incidence for a single chest CT scan in children.
Materials and Methods: We divided 1,105 children into four age groups: 0 years, 5 years, 10 years, and 15 years. Dosimetric data of chest CT scan were plugged in VirtualDoseCT software, and organ dose and effective dose were calculated. The cancer risk based on organ dose is estimated according to the BEIR VII report.
Results: The highest dose in boys was related to lung (5.13 - 6.8 mSv) and heart (5.27-5.97 mSv), and in girls, lung (4.98 - 5.91 mSv), breast (4.24 - 5.21 mSv), and heart (4.9 - 5.71 mSv) had the highest dose. The highest LAR (per 100,000) was obtained for the breast in the age group of 0 years (61.01), followed by the breast for the age group of 5 years (46.16) and lung in the age group of 0 years (43.32) in girls.
Conclusion: This study shows a better concept of radiation dose in the chest CT scan in children and how much effective dose and organ dose values increase the cancer risk.
{"title":"Estimation of Lifetime Attributable Risk (LAR) of Cancer Associated with Chest Computed Tomography Procedures in Children","authors":"Mohammad Hossein Jamshidi, Aida Karami, Jalal Ordoni, Salar Bijari","doi":"10.18502/fbt.v10i4.13726","DOIUrl":"https://doi.org/10.18502/fbt.v10i4.13726","url":null,"abstract":"Purpose: The danger of radiation at low doses continues linearly, and without a threshold, investigations concluded that although the risk of cancer from Computed Tomography (CT) scans is low, it is not zero.
 This study aims to determine the patient's radiation dose and estimate the Lifetime Attributable Risk (LAR) of cancer incidence for a single chest CT scan in children.
 Materials and Methods: We divided 1,105 children into four age groups: 0 years, 5 years, 10 years, and 15 years. Dosimetric data of chest CT scan were plugged in VirtualDoseCT software, and organ dose and effective dose were calculated. The cancer risk based on organ dose is estimated according to the BEIR VII report.
 Results: The highest dose in boys was related to lung (5.13 - 6.8 mSv) and heart (5.27-5.97 mSv), and in girls, lung (4.98 - 5.91 mSv), breast (4.24 - 5.21 mSv), and heart (4.9 - 5.71 mSv) had the highest dose. The highest LAR (per 100,000) was obtained for the breast in the age group of 0 years (61.01), followed by the breast for the age group of 5 years (46.16) and lung in the age group of 0 years (43.32) in girls.
 Conclusion: This study shows a better concept of radiation dose in the chest CT scan in children and how much effective dose and organ dose values increase the cancer risk.","PeriodicalId":34203,"journal":{"name":"Frontiers in Biomedical Technologies","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135245910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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