Current Improvements in Temporal Bone Imaging Technology

Conditions affecting the vestibular and audiological systems impact on a person's auditory and balance functions. They can lead to symptoms such as vertigo, hearing loss, and tinnitus, thereby severely diminishing a patient's quality of life. Early and accurate diagnosis is crucial for effective management and treatment. Traditionally, clinicians have relied on audiometry and clinical assessments for diagnosis, which often fall short in specificity and sensitivity. However, temporal bone imaging has undergone significant advancements in recent years, driven by technological innovations and the demand for more precise diagnostic tools in neuro-otology and radiology. The complex anatomy of the temporal bone poses unique challenges in achieving clear and accurate imaging, making improvements in imaging technology highly valuable for healthcare professionals. Photon counting computed tomography (CT) represents a breakthrough that offers enhanced image resolution and reduced noise, providing clinicians with a comprehensive view of microstructures within the temporal bone. Additionally, the integration of artificial intelligence (AI) into temporal bone imaging has revolutionized diagnostic approaches, enabling automated segmentation and analysis that decrease misdiagnosis rates. Innovations in neuro-interventional radiology are also noteworthy, opening new avenues for managing conditions such as tinnitus through procedures like venous stenting. As these technologies continue to evolve, the intersection of machine learning, biomedical informatics, and natural language processing in processing image data continues to shape precision medicine. Understanding how these technologies can be harnessed to improve patient outcomes is a key focus of current research efforts.The primary goal of this Research Topic is to consolidate and disseminate cutting-edge research that explores recent improvements in temporal bone imaging technology. We aim to address the gaps in current knowledge by exploring advances in photon counting CT, AI-driven diagnostic tools, and novel interventional radiology procedures. By examining how machine learning and large language models can enhance diagnostic accuracy and streamline workflows, this collection seeks to highlight the transformative potential of these technologies in clinical practice. We encourage submissions that discuss novel methodologies, clinical applications, and future directions for research. Ultimately, this topic seeks to foster collaboration among researchers, clinicians, and technologists to propel the field forward and translate innovations into enhanced patient care.We welcome all article types accepted by the journal pertaining but not limited to the following themes: • Applications of AI and machine learning in imaging of the temporal bone• How AI and machine learning can improve diagnostic accuracy, and help us identify what otherwise might have been overlooked• Advancements in photon counting CT for temporal bone imaging• Novel neuro-interventional radiology techniques in neuro-otology• Improvements in neuro-interventional radiology in the management of tinnitus, such as venous stenting • The role of biomedical informatics in data integration and analysis• The utilization of natural language processing and large language models in imaging workflows• The stigmata of migraine as reflected in MRI Imaging within the context of Meniere’s Disease Topic editors: Brian John McKinnon, Makoto Kinoshita Source: https://www.frontiersin.org/research-topics/68877/current-improvements-in-temporal-bone-imaging-technology