QAMaster: A new software framework for phantom-based computed tomography quality assurance

A challenge and solution for automatic thin slice thickness measurements on images of the Catphan phantom

Purpose. The use of the Hough transform for angle detection is quite accurate for relatively wide slice thickness. However, the Hough transform fails to accurately detect the angle for thin slice thickness. This study proposes a method for automatically measuring the thickness of thin slices on images of a Catphan phantom.Methods. In the proposed method, the angle of the phantom's orientation was determined based on the relative coordinates of the four hole objects in the phantom. After the angles of the wires were determined, the profiles of pixel values across the wire objects were constructed. Finally, their full widths at half maximum (FWHMs) were determined and multiplied bytan23° to obtain the slice thicknesses of the images. The results of the proposed method were compared to a previous method, which used the Hough transform to obtain the phantom's orientation. We used slice thicknesses ranging from 0.8 mm to 5.0 mm, and phantom angles from 0° to 10°.Results. Our proposed method detected the angle of the phantom accurately for thin slices, whereas a previous method did not accurately detect the angle. The results of the slice thickness using this current method were slightly higher (within 7.9%) compared to the previous method. However, the results of the two methods did not differ significantly (p-value > 0.05). Using different angles, the current method detected all the angles more accurately. Again, the slice thicknesses were not significantly different from the previous method (p-value > 0.05).Conclusion. The proposed method for measuring the thickness of thin slices in an image of a Catphan phantom, based on the relative coordinates of the four hole objects in the phantom, outperformed a previous method based on the Hough transform.

Free automatic software for quality assurance of computed tomography calibration, edges and radiomics metrics reproducibility

PURPOSE

To develop a QA procedure, easy to use, reproducible and based on open-source code, to automatically evaluate the stability of different metrics extracted from CT images: Hounsfield Unit (HU) calibration, edge characterization metrics (contrast and drop range) and radiomic features.

METHODS

The QA protocol was based on electron density phantom imaging. Home-made open-source Python code was developed for the automatic computation of the metrics and their reproducibility analysis. The impact on reproducibility was evaluated for different radiation therapy protocols, and phantom positions within the field of view and systems, in terms of variability (Shapiro-Wilk test for 15 repeated measurements carried out over three days) and comparability (Bland-Altman analysis and Wilcoxon Rank Sum Test or Kendall Rank Correlation Coefficient).

RESULTS

Regarding intrinsic variability, most metrics followed a normal distribution (88% of HU, 63% of edge parameters and 82% of radiomic features). Regarding comparability, HU and contrast were comparable in all conditions, and drop range only in the same CT scanner and phantom position. The percentages of comparable radiomic features independent of protocol, position and system were 59%, 78% and 54%, respectively. The non-significantly differences in HU calibration curves obtained for two different institutions (7%) translated in comparable Gamma Index G (1 mm, 1%, >99%).

CONCLUSIONS

An automated software to assess the reproducibility of different CT metrics was successfully created and validated. A QA routine proposal is suggested.

Cone-beam CT imaging with laterally enlarged field of view based on independently movable source and detector

BACKGROUND

CBCT imaging with field of views (FOVs) exceeding the size of scans acquired in the conventional imaging geometry, i.e. with opposing source and detector, is of high clinical importance for many medical fields. A novel approach for enlarged FOV scanning with one full-scan (EnFOV360) or two short-scans (EnFOV180) using an O-arm system arises from non-isocentric imaging based on independent source and detector rotations.

PURPOSE

The presentation, description, and experimental validation of this novel approach and the novel scanning techniques EnFOV360 and EnFOV180 for an O-arm system forms the scope of this work.

METHODS

We describe the EnFOV360, EnFOV180, and non-isocentric imaging techniques for the acquisition of laterally extended FOVs. For their experimental validation, scans of dedicated quality assurance as well as anthropomorphic phantoms were acquired, with the phantoms being placed both within the tomographic plane and at the longitudinal FOV border with and without lateral shifts from the gantry center. Based on this, geometric accuracy, contrast-noise-ratio (CNR) of different materials, spatial resolution, noise characteristics, as well as CT number profiles were quantitatively assessed. Results were compared to scans performed with the conventional imaging geometry.

RESULTS

With EnFOV360 and EnFOV180, we increased the in-plane size of acquired FOVs from 250 × 250 mm2 obtained for the conventional imaging geometry to up to 400 × 400 mm2 for the performed measurements. Geometric accuracy was very high for all scanning techniques with mean values ≤0.21 ± 0.11 mm. CNR and spatial resolution were comparable between isocentric and non-isocentric full-scans as well as EnFOV360, whereas substantial image quality deteriorations in this respect were observed for EnFOV180. Image noise in the isocenter was lowest for conventional full-scans with 13.4 ± 0.2 HU. For laterally shifted phantom positions, noise increased for conventional scans and EnFOV360, whereas noise reductions were observed for EnFOV180. Considering the anthropomorphic phantom scans, both EnFOV360 and EnFOV180 were comparable to conventional full-scans.

CONCLUSION

Both enlarged FOV techniques have high potential for imaging laterally extended FOVs. EnFOV360 revealed an image quality comparable to conventional full-scans in general. EnFOV180 showed an inferior performance particularly regarding CNR and spatial resolution.

A comprehensive quality assurance program for four-dimensional computed tomography in radiotherapy

This study aimed to develop and validate a comprehensive, reproducible and automatic 4DCT Quality Assurance (QA) workflow (QAMotion) that evaluates image accuracy across various regular and irregular breathing patterns. Volume and amplitude deviations, CT number accuracy, and spatial integrity were used as evaluation metrics. For repeatability tests, tolerances were respected with a mean CT number deviation < 10 HU, volume deviation < 2% and diameter and amplitude deviation < 2 mm except for irregular amplitude curves for which an amplitude deviation up to 6 mm was measured. QAMotion was able to flag image artefacts for our clinical 4DCT system.

Quality assurance and long-term stability of a novel 3-in-1 X-ray system for brachytherapy

Purpose

A novel, mobile 3‐in‐1 X‐ray system featuring radiography, fluoroscopy, and cone‐beam computed tomography (CBCT) has been launched for brachytherapy recently. Currently, there is no quality assurance (QA) procedure explicitly applicable to this system equipped with innovative technologies such as dynamic jaws and motorized lasers. We developed a dedicated QA procedure and, based on its performance for a duration of 6 months, provide an assessment of the device's stability over time.

Methods

With the developed QA procedure, we assessed the system's planar and CBCT‐imaging performance by investigating geometric accuracy, CT‐number stability, contrast‐noise‐ratio, uniformity, spatial resolution, low‐contrast detectability, dynamic range, and X‐ray exposure using dedicated phantoms. Furthermore, we evaluated geometric stability by using the flexmap‐approach and investigated the device's laser‐ and jaw‐positioning accuracy with an in‐house test phantom. CBCT‐ and planar‐imaging protocols for pelvis, breast, and abdomen imaging were examined.

Results

Planar‐ and CBCT‐imaging performances were widely stable with a geometric accuracy ≤1 mm, CT‐number stability of up to 46 HU, and uniformity variations of up to 48 HU over time. For planar imaging, low‐contrast detectability and dynamic range exceeded current recommendations. Although geometric stability was considered tolerable, partly substantial positioning inaccuracies of up to more than 120 mm and −13 mm were obtained for lasers and jaws, respectively. X‐ray exposure showed small variations of ≤0.56 μGy and ≤0.76 mGy for planar‐ and CBCT‐imaging, respectively. The conductance of the QA procedure allowed a smooth evaluation of the system's overall performance.

Conclusion

We developed a QA workflow for a novel 3‐in‐1 X‐ray system allowing to assess the device's imaging and hardware performance. The system showed in general a reasonable imaging performance and stability over time, whereas improvements regarding laser and jaw accuracy are strictly required.