Multimodality Imaging Diagnosis in Infective Endocarditis

Exploring Unusual Cardiac Complications: Chorda Tendinea Rupture and Pulmonary Valve Vegetation in Infective Endocarditis-A Comprehensive Review

Infective endocarditis (IE) is a severe infection of the endocardium, frequently involving heart valves, and is associated with significant morbidity and mortality. At the same time, traditional complications of IE, such as valvular dysfunction and embolic events, are well-documented, and uncommon cardiac manifestations, such as chorda tendinea rupture and pulmonary valve vegetation, present unique diagnostic and management challenges. This comprehensive review explores the pathophysiology, clinical presentation, diagnostic strategies, and management approaches for IE's chorda tendinea rupture and pulmonary valve vegetation. Through a detailed examination of the literature and discussion of clinical scenarios, we highlight the importance of recognizing these rare complications and discuss the implications for clinical practice. Additionally, we identify knowledge gaps and propose areas for future research to enhance further our understanding and management of these unusual cardiac complications in IE. This review aims to provide clinicians with valuable insights to improve patient care and outcomes in the challenging setting of infective endocarditis.

Dual-Time-Point 18F-FDG PET/CT in Infective Endocarditis: Impact of Delayed Imaging in the Definitive Diagnosis of Endocarditis

Infective endocarditis (IE) is a major public health condition due to the associated high morbidity and mortality. Our objective was to evaluate the utility of dual-time 2-deoxy-2-[18F] fluoro-D-glucose (18F-FDG) Positron Emission Tomography/Computed Tomography (PET/CT) imaging in the diagnosis of active IE in patients with suspected native valve endocarditis (NVE) and prosthetic valve endocarditis (PVE). For this purpose, a retrospective study was carried out, including patients suspicious of NVE or PVE who underwent a dual-time-point 18F-FDG PET/CT. A final diagnosis was established by the Endocarditis Team after patient follow-up using all the available findings. Sixty-nine patients were assessed. A final diagnosis of NVE was established in 3 patients of the 34 by 18F-FDG PET/CT and in the case of PVE was established in 20 patients of the 35. A statistically significant association was found when evaluating the association between PET diagnosis at early acquisition and final diagnosis of IE (χ2 = 30.198, p < 0.001) and PET diagnosis at delayed acquisition for final diagnosis of IE (χ2 = 9.412, p = 0.002). Delayed PET/CT imaging determined the IE diagnosis in 16/58 of the studies. In conclusion, delayed 18F-FDG PET/CT imaging seems to be useful in improving the definitive diagnosis of IE.

Exploring the Intersection of Geophysics and Diagnostic Imaging in the Health Sciences

To develop diagnostic imaging approaches, this paper emphasizes the transformational potential of merging geophysics with health sciences. Diagnostic imaging technology improvements have transformed the health sciences by enabling earlier and more precise disease identification, individualized therapy, and improved patient care. This review article examines the connection between geophysics and diagnostic imaging in the field of health sciences. Geophysics, which is typically used to explore Earth's subsurface, has provided new uses of its methodology in the medical field, providing innovative solutions to pressing medical problems. The article examines the different geophysical techniques like electrical imaging, seismic imaging, and geophysics and their corresponding imaging techniques used in health sciences like tomography, magnetic resonance imaging, ultrasound imaging, etc. The examination includes the description, similarities, differences, and challenges associated with these techniques and how modified geophysical techniques can be used in imaging methods in health sciences. Examining the progression of each method from geophysics to medical imaging and its contributions to illness diagnosis, treatment planning, and monitoring are highlighted. Also, the utilization of geophysical data analysis techniques like signal processing and inversion techniques in image processing in health sciences has been briefly explained, along with different mathematical and computational tools in geophysics and how they can be implemented for image processing in health sciences. The key findings include the development of machine learning and artificial intelligence in geophysics-driven medical imaging, demonstrating the revolutionary effects of data-driven methods on precision, speed, and predictive modeling.