Investigating focal spot position drift in a mobile imaging system equipped with a monobloc-based x-ray generator.

BACKGROUND: Misalignment or double-contouring artifacts can appear in high-resolution 3D cone beam computed tomography (CBCT) images, potentially indicating geometric accuracy issues in the projection data. Such artifacts may go unnoticed in low-resolution images and could be associated with changes in the focal spot (FS) position. PURPOSE: High-resolution 3D-CBCT imaging by a mobile imaging device with a large gantry clearance offers more versatility for clinical workflows in image-guided brachytherapy (IGBT), intraoperative radiation therapy (IORT), and spinal, as well as maxillofacial surgery. However, misalignment or double-contouring artifacts hinder workflow advancements in these domains. This paper introduces intrinsic calibration and geometrical correction methods as extensions to a well-established technique for addressing geometrical deviations resulting from factors such as gravity or mechanical inconsistencies. These extensions cover shifts and drifts of the FS depending on FS size selection, temperature, tube current, and tube potential. The proposed methods effectively mitigate artifacts in high-resolution CBCT images stemming from geometrical inaccuracies in projection data, without requiring additional equipment like a pinhole device. METHODS: Geometrical offsets and drifts of the x-ray tube FS were characterized on a mobile multi-purpose imaging system, the ImagingRing-m. A pinhole-like experiment was simulated by adjusting the movable collimation unit to a small rectangular aperture within the FS size range. The influence of filament selection, that is, FS size, temperature, the relatively low tube currents, as well as tube potential settings have been studied on two different monobloc types sharing the same x-ray tube insert. The Catphan 504 and an Alderson head phantom were used to assess resulting image artifacts. RESULTS: Switching the FS size to one different from what was used for geometrical (gravitation, mechanical variations) calibration induced the most notable position changes of the x-ray FS, resulting in double-contouring artifacts and blurring of high-resolution 3D-CBCT images. Incorporating these shifts into a geometrical correction method effectively minimized these artifacts. Thermal drifts exhibited the second largest geometrical changes, comparable to FS size shifts across the thermal operating conditions of the x-ray system. The proposed thermal drift compensation markedly reduced thermal drift effects. Tube current and potential had little impact within the range of available tube currents, eliminating the need for compensation in current applications. CONCLUSIONS: Augmenting the geometrical calibration pipeline with proposed FS drift compensations yielded significant enhancements in image quality for high-resolution reconstructions. While compensation for thermal effects posed challenges, it proved achievable. The roles of tube current and potential were found to be negligible.

A Monte Carlo based scatter removal method for non-isocentric cone-beam CT acquisitions using a deep convolutional autoencoder.

The primary cone-beam computed tomography (CBCT) imaging beam scatters inside the patient and produces a contaminating photon fluence that is registered by the detector. Scattered photons cause artifacts in the image reconstruction, and are partially responsible for the inferior image quality compared to diagnostic fan-beam CT. In this work, a deep convolutional autoencoder (DCAE) and projection-based scatter removal algorithm were constructed for the ImagingRingTM system on rails (IRr), which allows for non-isocentric acquisitions around virtual rotation centers with its independently rotatable source and detector arms. A Monte Carlo model was developed to simulate (i) a non-isocentric training dataset of ≈1200 projection pairs (primary + scatter) from 27 digital head-and-neck cancer patients around five different virtual rotation centers (DCAENONISO), and (ii) an isocentric dataset existing of ≈1200 projection pairs around the physical rotation center (DCAEISO). The scatter removal performance of both DCAE networks was investigated in two digital anthropomorphic phantom simulations and due to superior performance only the DCAENONISO was applied on eight real patient acquisitions. Measures for the quantitative error, the signal-to-noise ratio, and the similarity were evaluated for two simulated digital head-and-neck patients, and the contrast-to-noise ratio (CNR) was investigated between muscle and adipose tissue in the real patient image reconstructions. Image quality metrics were compared between the uncorrected data, the currently implemented heuristic scatter correction data, and the DCAE corrected image reconstruction. The DCAENONISO corrected image reconstructions of two digital patient simulations showed superior image quality metrics compared to the uncorrected and corrected image reconstructions using a heuristic scatter removal. The proposed DCAENONISO scatter correction in this study was successfully demonstrated in real non-isocentric patient CBCT acquisitions and achieved statistically significant higher CNRs compared to the uncorrected or the heuristic corrected image data. This paper presents for the first time a projection-based scatter removal algorithm for isocentric and non-isocentric CBCT imaging using a deep convolutional autoencoder trained on Monte Carlo composed datasets. The algorithm was successfully applied to real patient data.

Modelling of the focal spot intensity distribution and the off-focal spot radiation in kilovoltage x-ray tubes for imaging.

X-ray tubes for medical applications typically generate x-rays by accelerating electrons, emitted from a cathode, with an interelectrode electric field, towards an anode target. X-rays are not emitted from one point, but from an irregularly shaped area on the anode, the focal spot. Focal spot intensity distributions and off-focal radiation negatively affect the imaging spatial resolution and broadens the beam penumbra. In this study, a Monte Carlo simulation model of an x-ray tube was developed to evaluate the spectral and spatial characteristics of off-focal radiation for multiple photon energies. Slit camera measurements were used to determine the horizontal and vertical intensity profiles of the small and the large focal spot of a diagnostic x-ray tube. First, electron beamlet weighting factors were obtained via an iterative optimization method to represent both focal spot sizes. These weighting factors were then used to extract off-focal spot radiation characteristics for the small and large focal spot sizes at 80, 100, and 120 kV. Finally, 120 kV simulations of a steel sphere (d = 4 mm) were performed to investigate image blurring with a point source, the small focal spot, and the large focal spot. The magnitude of off-focal radiation strongly depends on the anode size and the electric field coverage, and only minimally on the tube potential and the primary focal spot size. In conclusion, an x-ray tube Monte Carlo simulation model was developed to simulate focal spot intensity distributions and to evaluate off-focal radiation characteristics at several energies. This model can be further employed to investigate focal spot correction methods and to improve cone-beam CT image quality.