Radiologic Technology Overview

Principles

Definition

Radiologic technology is an applied healthcare discipline focused on the use of medical imaging modalities and radiation therapy techniques for diagnostic and therapeutic purposes. It encompasses the scientific principles, technical skills, patient care protocols, and radiation safety measures necessary to acquire high-quality diagnostic images and deliver precise therapeutic radiation, providing critical data to aid in the diagnosis and management of diseases.

Ontological type

Radiation Protection

Core Modalities

Technical Competencies

Key developments

Key Figures

Digital Imaging Consolidation era

Eric J. Hall [1] was associated with Columbia University [2] and Menlo School [3] during the Digital Imaging Consolidation era. Hall [1]'s 1995 Radiobiology for the Radiologist [4] provided a foundational overview of radiobiology for radiologists, which informed careful dose management and safe imaging practices as digital detectors and PACS reshaped radiology. Hall's influence during this era helped standardize knowledge crucial for dose monitoring and quality assurance in radiology [1]. By guiding education and practice around radiobiology in the digital era, Hall contributed to interoperable workflows and safer image utilization across institutions [1].

Dose Optimization and Safety era

Geoffrey S. Ibbott [1] is a leading figure in radiologic technology during the Dose Optimization and Safety era, with affiliations connected to The University of Texas Southwestern Medical Center [3] and Washington University in St. Louis [4]. He co-authored the 2009 study Radiologic and Nuclear Medicine Studies in the United States and Worldwide: Frequency, Radiation Dose, and Comparison with Other Radiation Sources—1950–2007 [7], whose comprehensive quantification of imaging frequency and patient-dose patterns helped advance standardized dose-tracking and safety benchmarks central to this era. Terry T. Yoshizumi [2], with ties to Duke University [5] and University of Bern [6], emerges as a prominent contributor in this period. He co-authored the same 2009 study [7], and his work on documenting dose distributions across modalities contributed to dose-awareness, benchmarking, and robust safety culture that define the era.

AI Integration in Radiology era

Savvas Nicolaou [1], affiliated with University of Maryland, Baltimore [2] and University College London [3], emerges as a notable contributor to radiology education research amid AI integration. The single paper, Influence of Artificial Intelligence on Canadian Medical Students' Preference for Radiology Specialty: ANational Survey Study [4], analyzes how AI awareness shapes medical students' interest in radiology, underscoring implications for workforce planning and curriculum development. This study [4] reveals AI literacy influences specialty choice, informing education policy discussions. These insights from Savvas Nicolaou [1] and the paper [4] help shape AI adoption, education, and workforce readiness in radiology.