X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging
September 11th, 2011
We are developing a dynamic adaptive exposure technique using our scanning beam digital X-ray system. Rather than exposing an object uniformly, the exposure is adapted depending on the opacity of the object. Here we show an experiment on an anthropomorphic phantom that resulted in a dose saving of 30%.
This experiment shows how to use the scanning beam digital x-ray system to save dose by locally adapting the exposure to the opacity of the object rather than exposing it uniformly as done conventionally. The first step is to acquire a first pass reference image and define the parameters of the adaptive exposure algorithm system. The computer then outputs a new scan map with lower dose requirements, which is loaded in the system, so an equalized image can be acquired.
Dose area product measurements show that adaptive exposure leads to dose savings in the range of 30%We are developing an imaging system called the scanning beam Digital x-ray or SPDX system that enables inverse geometry x-ray fluoroscopy. The main difference between a conventional and an inverse geometry imaging system is that we are not using a single focus spot x-ray tube that projects onto large field of view detector. Our x-ray source consists of thousands of focus spots with each coated onto a small photon counting detector to acquire a single imaging frame.
We acquire thousands of detector images with each detector image only viewing a small portion of the object inverse. Geometry imaging leads to a significant reduction of scatter in the images. This allows us to acquire these images at much lower dose.
This is in particular of advantage for larger patients as scatter scales with patient size. In pediatric patients, dose savings due scatter reduction are much less. However, inverse geometry allows for implementation of dose saving strategies that also benefit pediatric patients.
Inverse geometry enables a technique that we are calling adaptive exposure. As we are acquiring thousand of detector images, we can adapt exposure in real time, depending on the upper city of the region exposed, so we can reduce exposure in radiolucent area and maintain exposure in some more OPAC region. Therefore, we can achieve uniform image quality in the overall image and reduce dose in area that are overexposed in conventional systems.
To monitor the radiation dose, a dose area product meter is placed in front of the collimator. The patient or phantom is typically positioned relatively close to the collimator with the center of the imaging volume at about 40 centimeters from the collimator. Next, the system operating mode is selected.
Typical settings are field of view of seven inches and frame rate of 15 frames per second. The X-ray source peak voltage is set to 80 peak kilovolts and the source power to 17 kilowatts. Then turn on the SBDX system and start image acquisition.
During image acquisition, an electron beam is sequentially scanned to every focal spot position in a raster fashion. At every focal spot position, the electron beam hits the transmission target and generates x-rays. The resulting x-ray photons pass through a focusing collimator and illuminate the detector.
Thus, only a small portion of the imaging volume is projected. During illumination, the detector acquires a detector image, which is directly stored in the system memory. For each focal spot, an illumination of up to eight microseconds is desired.
However, due to thermal limitations of the target, the maximum continuous exposure is one. Microsecond and acquisition is broken up into eight one microsecond increments. In total, over about 60 milliseconds, over 40, 000 detector images are recorded at the end of image acquisition.
Be sure to record the measurement on the dose area product meter. The SBDX is intrinsically a tomosynthesis system, as the object is illuminated under different angles from each source focal spot, any plane within the imaging volume located between collator and detector can be reconstructed. Begin by setting the imagery.
Construction parameters. Select how many planes to reconstruct and their location. Next, run the image reconstruction algorithm.
The algorithm processes each detector image by first scaling the detector image for the respective reconstruction plane, and second, shifting the image according to its focal spot position before adding to the reconstruction. Next, a post-process filtering removes the pattern created by the shift and add operation. Typically, 32 planes with the spacing of 0.5 millimeters are reconstructed in a stack of reconstructed images.
Structures go in and out of focus depending on their distance from the detector. The plane selection algorithm selects the structures that are in focus in every plane, and with that information, a composite image can be formed that only shows structures and focus. This 2D image is equivalent to images obtained on a conventional system.
However, the plane selection algorithm has determined for every structure where it is in respect to a collimator. This allows us to play it as a 3D animation, Load the saved images into the adaptive exposure simulator and run the algorithm for each focal spot. The number of photons in the image is determined.
The images are then accumulated until the target number of photons is reached, or all eight rescans are added. The output of the adaptive exposure simulator is a re-scan map that details how many times each focal spot position is illuminated. This map gets merged to the operation mode file used to run the SBDX system.
After loading the updated operation mode file into the SBDX system, taken images before only now the x-ray beam will be turned on or off at the focal spot positions according to the re-scan map, reducing the total number of illuminations, run the image reconstruction algorithm on the new data to reconstruct the equalized image. Again, be sure to record the dose area product reading dose measurements with the dose area product meter demonstrated a dose savings of 30%in the equalized image using the re-scan mask. Preliminary results showed that the image quality is equivalent and that the equalized image has more visual appeal than the non equalized image.
We are exploring adaptive exposure as a technique to reduce dose and fluoroscopic procedures. Initial results show that dose savings of at least 30%are feasible at equal image quality. We are in the process of implementing adaptive exposure as a real time feature.
During image acquisition, our algorithm will automatically perform thresholding. Therefore, many of the steps shown here will be invisible to the user. Our current results are encouraging and we are looking forward to investigating our technique Further.
In particular, we will have to show in clinical trials that the diagnostic value of our images is equivalent or better than conventional images.
Overview
This study develops a dynamic adaptive exposure technique using a scanning beam digital X-ray system, which adapts exposure based on object opacity. The experiment on an anthropomorphic phantom demonstrated a 30% dose saving.
Key Study Components
Area of Science
- Medical Imaging
- X-ray Technology
- Radiation Dose Management
Background
- Conventional X-ray systems expose objects uniformly, leading to unnecessary radiation dose.
- Inverse geometry imaging reduces scatter, allowing for lower dose imaging.
- Adaptive exposure techniques can enhance image quality while minimizing radiation exposure.
- Real-time adaptation of exposure based on object opacity is a novel approach.
Purpose of Study
- To develop a scanning beam digital X-ray system that enables adaptive exposure.
- To demonstrate dose savings while maintaining image quality.
- To explore the benefits of adaptive exposure in various patient populations.
Methods Used
- Acquisition of reference images to define adaptive exposure parameters.
- Implementation of a dose area product meter to monitor radiation dose.
- Sequential scanning of focal spots to generate X-ray images.
- Image reconstruction algorithms to create equalized images from detector data.
Main Results
- Adaptive exposure resulted in a 30% reduction in radiation dose.
- Image quality was equivalent to that of conventional systems.
- Equalized images showed improved visual appeal compared to non-equalized images.
- Real-time adaptation allowed for uniform image quality across varying opacities.
Conclusions
- The scanning beam digital X-ray system effectively reduces radiation dose through adaptive exposure.
- This technique can benefit larger patients and pediatric populations.
- Further exploration of adaptive exposure may enhance imaging practices in clinical settings.
Frequently Asked Questions
Executive Industry Relevance
Radiation dose management in fluoroscopic imaging presents a critical challenge in interventional cardiology, particularly for pediatric populations undergoing repeated procedures. Adaptive exposure techniques that dynamically modulate X-ray output based on tissue opacity offer a pathway to reduce unnecessary exposure while preserving diagnostic image quality. This approach supports mechanistic de-risking in preclinical and translational imaging workflows by enabling safer, repeatable longitudinal studies in disease models.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Scientific Value: Enables longitudinal imaging of disease progression in small animal models with reduced cumulative radiation burden.
- Operational Value: Supports repeated imaging sessions required for pharmacokinetic and pharmacodynamic studies without exceeding safety thresholds.
Screening & Assay Development
- Scientific Value: Facilitates high-resolution, low-dose imaging for tracking contrast agent distribution in vascular permeability assays.
- Operational Value: Improves reproducibility in quantitative imaging endpoints by minimizing dose-induced biological variability.
Translational & Preclinical Research
- Scientific Value: Enhances predictive confidence in cardiovascular safety studies by enabling serial monitoring of cardiac function and structural changes.
- Operational Value: Reduces attrition in toxicology studies by mitigating radiation-induced confounding factors in longitudinal imaging.
Pipeline & Workflow Integration
The technique integrates into discovery biology workflows where non-invasive imaging informs target engagement and pathway modulation, particularly in cardiovascular and metabolic disease models.
- Discovery Biology: Supports hypothesis testing through serial imaging of disease models to assess target-mediated phenotypic changes.
- Screening: Enables assay-ready imaging systems with consistent, low-dose output for reliable compound effect quantification.
- Analytics: Provides quantitative, normalized image intensities suitable for statistical comparison across treatment groups.
- Translational Research: Bridges discovery and preclinical phases by maintaining imaging fidelity across species scaling from rodents to larger models.
- Enterprise Reuse: Represents a platform-capable imaging modality adaptable across multiple therapeutic areas requiring longitudinal fluoroscopic or tomosynthetic imaging.
Operational & Enterprise Impact
- Scientific Value: Predictive confidence through reduced mechanistic ambiguity from radiation artifacts in longitudinal studies.
- Operational Value: Standardization and reproducibility via controlled, adaptive exposure protocols.
- Strategic Value: Improved go/no-go decisions by minimizing false positives/negatives from dose-related biological noise.
- Portfolio Impact: Risk-adjusted prioritization enabled by cleaner, more translatable imaging biomarkers.
Implementation Considerations
- Expertise in medical physics and X-ray system operation for protocol setup and calibration.
- Instrumentation including scanning beam digital X-ray systems with adaptive exposure control and dose area product metrology.
- Cross-team standardization between imaging, pharmacology, and toxicology units for consistent dose tracking.
- Adaptation considerations across model systems, particularly adjusting thresholds for varying tissue opacity in pediatric versus adult analogs.
- Practical limitation: current implementation requires user interaction for adaptive exposure mapping, limiting throughput until full automation is realized.
