Year: 2025
Type: article
Abstract: Purpose: A first demonstrator system for clinical dark-field chest radiography was recently constructed. Due to its scanning acquisition, conventional exposure regulation systems are not possible. This study presents the adaptation of exposure to each patient individually, using a conventional radiograph as a reference. Additionally, an alternative approach for individual exposure planning based on the patient's body mass index (BMI) is proposed. Methods: Using exposure settings from a conventional radiography system with automatic exposure control (AEC), a patient-specific equivalent attenuator thickness was calculated with polyoxymethylene (POM) as a surrogate material. The tube current at the dark-field system was adapted to reach the target detector dose based on this thickness. This approach was verified with both phantom measurements and patient examinations. The correlation between patient body parameters (weight, BMI, upper bust girth, and under-bust girth) and desired tube current was also evaluated. Results: A calibration curve was found to transfer individual exposure settings from a conventional device to the dark-field system. Achieved detector doses for both phantom and patient examinations were within permitted ranges. A strong correlation was found between each body parameter and the desired tube current, with BMI showing the strongest correlation ( r = 0 . 87 , p < 1 0 − 29 ). Conclusions: An exposure planning approach was successfully implemented at the first clinical dark-field chest radiography system, delivering a detector dose within the required range for different patient sizes. A conventional radiograph with AEC is necessary for this implementation. The strong correlation between BMI and tube current offers an alternative approach for patient-specific exposure control.
Source: Physica Medica
Institutions: TUM Klinikum, Technical University of Munich, Philips (Germany)
Language: English
Topic: Radiation Dose and Imaging
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $2,780
Funders: Institute for Advanced Study, Karlsruhe Institute of Technology, Australian Government, Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung, Technische Universität München, European Research Council, Institute for Advanced Study, Technische Universität München, H2020 European Research Council
Awards: G3426928738, G6560524197, G6763132700
OpenAlex ID: W4411197766
