Cerebral Hypoxia: Its Role in Age-Related Chronic and Acute Cognitive Dysfunction

Postoperative cognitive dysfunction (POCD) has been reported with widely varying frequency but appears to be strongly associated with aging. Outside of the surgical arena, chronic and acute cerebral hypoxia may exist as a result of respiratory, cardiovascular, or anemic conditions. Hypoxia has been extensively implicated in cognitive impairment. Furthermore, disease states associated with hypoxia both accompany and progress with aging. Perioperative cerebral hypoxia is likely underdiagnosed, and its contribution to POCD is underappreciated. Herein, we discuss the various disease processes and forms in which hypoxia may contribute to POCD. Furthermore, we outline hypoxia-related mechanisms, such as hypoxia-inducible factor activation, cerebral ischemia, cerebrovascular reserve, excitotoxicity, and neuroinflammation, which may contribute to cognitive impairment and how these mechanisms interact with aging. Finally, we discuss opportunities to prevent and manage POCD related to hypoxia.

Comparison of Diagnostic Effects of T2-Weighted Imaging, DWI, SWI, and DTI in Acute Cerebral Infarction

Objective: To achieve precision medicine, the use of imaging methods to help the clinical detection of cerebral infarction is conducive to the clinical development of a treatment plan and increase of the cure rate and improvement of the prognosis of patients.Methods: In this work, T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), susceptibility-weighted imaging (SWI), and diffusion tensor imaging (DTI) examinations were performed on 34 patients with clinically diagnosed cerebral infarction to measure the difference in signal intensity between the lesion and its mirror area and make a comparative analysis by means of the Student-Newman-Keuls method.Results: The detection rate of T2WI was 79% (27/34), the detection rate of DWI was 97% (33/34), the detection rate of SWI was 88% (30/34), and the detection rate of DTI was 94% (32/34).Conclusion: The imaging performance was in the order DWI > DTI > SWI > T2WI for the diagnosis of cerebral infarction, and combined imaging is better than single imaging.

Applications of Computational Methods in Biomedical Breast Cancer Imaging Diagnostics: A Review

With the exponential increase in new cases coupled with an increased mortality rate, cancer has ranked as the second most prevalent cause of death in the world. Early detection is paramount for suitable diagnosis and effective treatment of different kinds of cancers, but this is limited to the accuracy and sensitivity of available diagnostic imaging methods. Breast cancer is the most widely diagnosed cancer among women across the globe with a high percentage of total cancer deaths requiring an intensive, accurate, and sensitive imaging approach. Indeed, it is treatable when detected at an early stage. Hence, the use of state of the art computational approaches has been proposed as a potential alternative approach for the design and development of novel diagnostic imaging methods for breast cancer. Thus, this review provides a concise overview of past and present conventional diagnostics approaches in breast cancer detection. Further, we gave an account of several computational models (machine learning, deep learning, and robotics), which have been developed and can serve as alternative techniques for breast cancer diagnostics imaging. This review will be helpful to academia, medical practitioners, and others for further study in this area to improve the biomedical breast cancer imaging diagnosis.