Objectives: To assess the patients and health personnel’s level of awareness on risks related to ionizing radiation during CT scan. Materials and methods: Three questionnaires were addressed to patients, prescribing ...Objectives: To assess the patients and health personnel’s level of awareness on risks related to ionizing radiation during CT scan. Materials and methods: Three questionnaires were addressed to patients, prescribing physicians, and the medical imaging staff for three hospitals respectively. This permitted us to assess their knowledge on the benefits and risks of the required medical exam, based on the dangers of being exposed to X-rays, especially induced-radiation cancer following the amount of X-rays received during a CT scan and the possibility of not receiving radiation as tools of diagnosis. Results: 150 patients, 84 referring doctors of CT scan tests and 60 medical imaging personnel were retained. For patients, only 7.1% received information on the benefits and risks of their exams, and 34.4% believed that x-rays were harmful to their health. For the prescribers, 46.7% took into account the benefits/risk ratio before prescribing a test and only 16.7% of the referring doctors have informed the patient of the risks related to X-ray. 90% of the medical imaging staff ensures that the required test is justified, and 50% informed the patient on the risks associated with their radiation exposure, and the increased risk of developing cancer. 65% of the imaging staff could not estimate the dose that the patient will receive during the medical test. 25% mentioned the dose received during the acquisition in the patient’s exam report. Conclusion: This study confirms that the referring doctors, the patients, and the radiologists have a low knowledge concerning the risks associated with radiation exposure during a CT scan assessment. We will therefore say that patients and prescribers are not aware of the doses of radiation on CT and their possible risks, even though there is a risk of developing cancer.展开更多
Deep learning (DL) has experienced an exponential development in recent years, with major impact in many medical fields, especially in the field of medical image and, respectively, as a specific task, in the segmentat...Deep learning (DL) has experienced an exponential development in recent years, with major impact in many medical fields, especially in the field of medical image and, respectively, as a specific task, in the segmentation of the medical image. We aim to create a computer assisted diagnostic method, optimized by the use of deep learning (DL) and validated by a randomized controlled clinical trial, is a highly automated tool for diagnosing and staging precancerous and cervical cancer and thyroid cancers. We aim to design a high-performance deep learning model, combined from convolutional neural network (U-Net)-based architectures, for segmentation of the medical image that is independent of the type of organs/tissues, dimensions or type of image (2D/3D) and to validate the DL model in a randomized, controlled clinical trial. We used as a methodology primarily the analysis of U-Net-based architectures to identify the key elements that we considered important in the design and optimization of the combined DL model, from the U-Net-based architectures, imagined by us. Secondly, we will validate the performance of the DL model through a randomized controlled clinical trial. The DL model designed by us will be a highly automated tool for diagnosing and staging precancers and cervical cancer and thyroid cancers. The combined model we designed takes into account the key features of each of the architectures Overcomplete Convolutional Network Kite-Net (Kite-Net), Attention gate mechanism is an improvement added on convolutional network architecture for fast and precise segmentation of images (Attention U-Net), Harmony Densely Connected Network-Medical image Segmentation (HarDNet-MSEG). In this regard, we will create a comprehensive computer assisted diagnostic methodology validated by a randomized controlled clinical trial. The model will be a highly automated tool for diagnosing and staging precancers and cervical cancer and thyroid cancers. This would help drastically minimize the time and effort that specialists put into analyzing medical images, help to achieve a better therapeutic plan, and can provide a “second opinion” of computer assisted diagnosis.展开更多
Introduction: Acute intestinal obstruction is a serious pathology, a surgical emergency for which medical imaging plays an important role in the management. We initiated this work in order to study the contribution of...Introduction: Acute intestinal obstruction is a serious pathology, a surgical emergency for which medical imaging plays an important role in the management. We initiated this work in order to study the contribution of imaging in the diagnosis of acute intestinal obstruction at the Point-G University Hospital. Patients and Methods: This was a prospective, descriptive and analytical study of 96 patients collected at the radiology and medical imaging department of CHU Point-G from January 2018 to January 2019. Results: The age of our patients varied from 11 to 86 years, with an average of 36 years old. There was a male predominance of 64.6% against 35.4% for women, i.e., a sex ratio of 1.82. Previous surgery was found in 61.5% of our patients. The pain was present in all patients. An unprepared abdominal X-ray was performed in 89.6% of patients. Hydroaerobic levels were found in 96.5% of patients. Abdominopelvic CT scans were performed on 12 patients, all of whom were diagnosed with occlusion. These positive diagnostic findings were consistent with intraoperative findings in 92% of cases. The causes were dominated by bridges in 46 patients and tumors in 9 patients. Signs of severity on CT were dominated by signs of distress of the upstream bile ducts in 8.3%. Exactly 8% of our patients spontaneously resumed transit, 91% received surgical treatment and 1% died before surgery. The outcome was favorable in 80 patients (83.3%) and poor with death in 16 patients (16.7%). Conclusion: Acute intestinal obstruction remains a serious pathology for which the X-ray of the PSA is often the only radiological examination performed in an emergency. However, abdominopelvic CT seems to us to be widely indicated thanks to its contribution both to the positive diagnosis and to the diagnosis of severity and etiology. However, this imaging technique is widely underused in our practice because of its high cost and lack of availability.展开更多
文摘Objectives: To assess the patients and health personnel’s level of awareness on risks related to ionizing radiation during CT scan. Materials and methods: Three questionnaires were addressed to patients, prescribing physicians, and the medical imaging staff for three hospitals respectively. This permitted us to assess their knowledge on the benefits and risks of the required medical exam, based on the dangers of being exposed to X-rays, especially induced-radiation cancer following the amount of X-rays received during a CT scan and the possibility of not receiving radiation as tools of diagnosis. Results: 150 patients, 84 referring doctors of CT scan tests and 60 medical imaging personnel were retained. For patients, only 7.1% received information on the benefits and risks of their exams, and 34.4% believed that x-rays were harmful to their health. For the prescribers, 46.7% took into account the benefits/risk ratio before prescribing a test and only 16.7% of the referring doctors have informed the patient of the risks related to X-ray. 90% of the medical imaging staff ensures that the required test is justified, and 50% informed the patient on the risks associated with their radiation exposure, and the increased risk of developing cancer. 65% of the imaging staff could not estimate the dose that the patient will receive during the medical test. 25% mentioned the dose received during the acquisition in the patient’s exam report. Conclusion: This study confirms that the referring doctors, the patients, and the radiologists have a low knowledge concerning the risks associated with radiation exposure during a CT scan assessment. We will therefore say that patients and prescribers are not aware of the doses of radiation on CT and their possible risks, even though there is a risk of developing cancer.
文摘Deep learning (DL) has experienced an exponential development in recent years, with major impact in many medical fields, especially in the field of medical image and, respectively, as a specific task, in the segmentation of the medical image. We aim to create a computer assisted diagnostic method, optimized by the use of deep learning (DL) and validated by a randomized controlled clinical trial, is a highly automated tool for diagnosing and staging precancerous and cervical cancer and thyroid cancers. We aim to design a high-performance deep learning model, combined from convolutional neural network (U-Net)-based architectures, for segmentation of the medical image that is independent of the type of organs/tissues, dimensions or type of image (2D/3D) and to validate the DL model in a randomized, controlled clinical trial. We used as a methodology primarily the analysis of U-Net-based architectures to identify the key elements that we considered important in the design and optimization of the combined DL model, from the U-Net-based architectures, imagined by us. Secondly, we will validate the performance of the DL model through a randomized controlled clinical trial. The DL model designed by us will be a highly automated tool for diagnosing and staging precancers and cervical cancer and thyroid cancers. The combined model we designed takes into account the key features of each of the architectures Overcomplete Convolutional Network Kite-Net (Kite-Net), Attention gate mechanism is an improvement added on convolutional network architecture for fast and precise segmentation of images (Attention U-Net), Harmony Densely Connected Network-Medical image Segmentation (HarDNet-MSEG). In this regard, we will create a comprehensive computer assisted diagnostic methodology validated by a randomized controlled clinical trial. The model will be a highly automated tool for diagnosing and staging precancers and cervical cancer and thyroid cancers. This would help drastically minimize the time and effort that specialists put into analyzing medical images, help to achieve a better therapeutic plan, and can provide a “second opinion” of computer assisted diagnosis.
文摘Introduction: Acute intestinal obstruction is a serious pathology, a surgical emergency for which medical imaging plays an important role in the management. We initiated this work in order to study the contribution of imaging in the diagnosis of acute intestinal obstruction at the Point-G University Hospital. Patients and Methods: This was a prospective, descriptive and analytical study of 96 patients collected at the radiology and medical imaging department of CHU Point-G from January 2018 to January 2019. Results: The age of our patients varied from 11 to 86 years, with an average of 36 years old. There was a male predominance of 64.6% against 35.4% for women, i.e., a sex ratio of 1.82. Previous surgery was found in 61.5% of our patients. The pain was present in all patients. An unprepared abdominal X-ray was performed in 89.6% of patients. Hydroaerobic levels were found in 96.5% of patients. Abdominopelvic CT scans were performed on 12 patients, all of whom were diagnosed with occlusion. These positive diagnostic findings were consistent with intraoperative findings in 92% of cases. The causes were dominated by bridges in 46 patients and tumors in 9 patients. Signs of severity on CT were dominated by signs of distress of the upstream bile ducts in 8.3%. Exactly 8% of our patients spontaneously resumed transit, 91% received surgical treatment and 1% died before surgery. The outcome was favorable in 80 patients (83.3%) and poor with death in 16 patients (16.7%). Conclusion: Acute intestinal obstruction remains a serious pathology for which the X-ray of the PSA is often the only radiological examination performed in an emergency. However, abdominopelvic CT seems to us to be widely indicated thanks to its contribution both to the positive diagnosis and to the diagnosis of severity and etiology. However, this imaging technique is widely underused in our practice because of its high cost and lack of availability.
