COVID-19 infection localization and severity grading from chest X-ray images.

The immense spread of coronavirus disease 2019 (COVID-19) has left healthcare systems incapable to diagnose and test patients at the required rate. Given the effects of COVID-19 on pulmonary tissues, chest radiographic imaging has become a necessity for screening and monitoring the disease. Numerous studies have proposed Deep Learning approaches for the automatic diagnosis of COVID-19. Although these methods achieved outstanding performance in detection, they have used limited chest X-ray (CXR) repositories for evaluation, usually with a few hundred COVID-19 CXR images only. Thus, such data scarcity prevents reliable evaluation of Deep Learning models with the potential of overfitting. In addition, most studies showed no or limited capability in infection localization and severity grading of COVID-19 pneumonia. In this study, we address this urgent need by proposing a systematic and unified approach for lung segmentation and COVID-19 localization with infection quantification from CXR images. To accomplish this, we have constructed the largest benchmark dataset with 33,920 CXR images, including 11,956 COVID-19 samples, where the annotation of ground-truth lung segmentation masks is performed on CXRs by an elegant human-machine collaborative approach. An extensive set of experiments was performed using the state-of-the-art segmentation networks, U-Net, U-Net++, and Feature Pyramid Networks (FPN). The developed network, after an iterative process, reached a superior performance for lung region segmentation with Intersection over Union (IoU) of 96.11% and Dice Similarity Coefficient (DSC) of 97.99%. Furthermore, COVID-19 infections of various shapes and types were reliably localized with 83.05% IoU and 88.21% DSC. Finally, the proposed approach has achieved an outstanding COVID-19 detection performance with both sensitivity and specificity values above 99%.

Optimizing pain care delivery in outpatient facilities: experience in NCI, Cairo, Egypt.

As a result of increasing waiting lists of patients attending National Cancer Institute of Cairo, we are faced to provide high-quality pain care service through our outpatient pain clinic. The program description presented here shows the capacity of a 24 hours/7 days outpatient cancer pain management service to provide rapidly accessible, high-quality care to patients with complex pain and palliative care symptom burdens. In addition, this model avoids inpatient hospital admissions. Pain clinics of cancer are committed to helping patients and families identify and implement the treatments necessary to achieve optimum functional ability and the best possible quality of life. These clinics also help to communicate and work with the family physician, surgeon, and other physicians associated with patient treatment. Cancer pain is complex in its causes, and affects all parts of the body. It involves the tissues, body systems , and the mind. Being multidimensional, it is never adequately addressed with unidimensional treatment. Pain management must extend beyond physical approaches to include the psychological, social, and even spiritual aspects of the patient. Effective integrated treatment fosters self awareness and teaches appropriate and effective self care. With time, complex issues are managed, pain is reduced, and the patient moves toward peak physical and psychological functioning. These goals can be achieved by providing the highest quality pain management services. Patients attending the clinic get treated medically for their physical ailments. Their emotional and psychological problems also need to be attended with an atmosphere of love and care. The mission of the highest quality service is to obtain customer satisfaction with reduction of cost in a multidisciplinary (or better interdisciplinary) approach. This can be reached by proper identification of the customers either internal or external, assessing their needs, and implementing plans for their satisfaction. In addition, monitoring the improvement of such plans is an integral part of the quality process. Importantly, the facility provides comprehensive care with professionals available 24 hours/7 days. On-call teams assigned to manage pain and other treatment modalities comprises of staff supervised by the primary cancer clinicians; this arrangement facilitates reaching this goal. This study will illustrate our experience through 25 years, trying to provide the highest care of patients with cancer pain on an outpatient basis.