4D CT imaging is a cornerstone of 4D radiotherapy treatment. Clinical 4D CT data are, however, often affected by severe artifacts. The artifacts are mainly caused by breathing irregularity and retrospective correlation of breathing phase information and acquired projection data, which leads to insufficient projection data coverage to allow for proper reconstruction of 4D CT phase images. The recently introduced 4D CT approach i4DCT (intelligent 4D CT sequence scanning) aims to overcome this problem by breathing signal-driven tube control. The present motion phantom study describes the first in-depth evaluation of i4DCT in a real-world scenario. Twenty-eight 4D CT breathing curves of lung and liver tumor patients with pronounced breathing irregularity were selected to program the motion phantom. For every motion pattern, 4D CT imaging was performed with i4DCT and a conventional spiral 4D CT mode. For qualitative evaluation, the reconstructed 4D CT images were presented to clinical experts, who scored image quality. Further quantitative evaluation was based on established image intensity-based artifact metrics to measure (dis)similarity of neighboring image slices. In addition, beam-on and scan times of the scan modes were analyzed. The expert rating revealed a significantly higher image quality for the i4DCT data. The quantitative evaluation further supported the qualitative: While 20% of the slices of the conventional spiral 4D CT images were found to be artifact-affected, the corresponding fraction was only 4% for i4DCT. The beam-on time (surrogate of imaging dose) did not significantly differ between i4DCT and spiral 4D CT. Overall i4DCT scan times (time between first beam-on and last beam-on event, including scan breaks to compensate for breathing irregularity) were, on average, 53% longer compared to spiral CT. Thus, the results underline that i4DCT significantly improves 4D CT image quality compared to standard spiral CT scanning in the case of breathing irregularity during scanning.

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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, CTnumber 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.

Purpose: 4D CT imaging is an integral part of 4D radiotherapy workflows. However, 4D CT data often contain motion artifacts that mitigate treatment planning. Recently, breathing-adapted 4D CT (i4DCT) was introduced into clinical practice, promising artifact reduction in in-silico and phantom studies. Here, we present an image quality comparison study, pooling clinical patient data from two centers: a new i4DCT and a conventional spiral 4D CT patient cohort.Methods: The i4DCT cohort comprises 129 and the conventional spiral 4D CT cohort 417 4D CT data sets of lung and liver tumor patients. All data were acquired for treatment planning. The study consists of three parts: illustration of image quality in selected patients of the two cohorts with similar breathing patterns; an image quality expert rater study; and automated analysis of the artifact frequency.Results: Image data of the patients with similar breathing patterns underline artifact reduction by i4DCT compared to conventional spiral 4D CT. Based on a subgroup of 50 patients with irregular breathing patterns, the rater study reveals a fraction of almost artifact-free scans of 89% for i4DCT and only 25% for conventional 4D CT; the quantitative analysis indicated a reduction of artifact frequency by 31% for i4DCT.Conclusion: The results demonstrate 4D CT image quality improvement for patients with irregular breathing patterns by breathing-adapted 4D CT in this first corresponding clinical data image quality comparison study.

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BackgroundCBCT 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.PurposeThe 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.MethodsWe 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.ResultsWith 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.ConclusionBoth 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.

Purpose Auxiliary devices such as immobilization systems should be considered in synthetic CT (sCT)-based treatment planning (TP) for MRI-only brain radiotherapy (RT). A method for auxiliary device definition in the sCT is introduced, and its dosimetric impact on the sCT-based TP is addressed. Methods T1-VIBE DIXON was acquired in an RT setup. Ten datasets were retrospectively used for sCT generation. Silicone markers were used to determine the auxiliary devices’ relative position. An auxiliary structure template (AST) was created in the TP system and placed manually on the MRI. Various RT mask characteristics were simulated in the sCT and investigated by recalculating the CT-based clinical plan on the sCT. The influence of auxiliary devices was investigated by creating static fields aimed at artificial planning target volumes (PTVs) in the CT and recalculated in the sCT. The dose covering 50% of the PTV (D50) deviation percentage between CT-based/recalculated plan (∆D50[%]) was evaluated. Results Defining an optimal RT mask yielded a ∆D50[%] of 0.2 ± 1.03% for the PTV and between −1.6 ± 3.4% and 1.1 ± 2.0% for OARs. Evaluating each static field, the largest ∆D50[%] was delivered by AST positioning inaccuracy (max: 3.5 ± 2.4%), followed by the RT table (max: 3.6 ± 1.2%) and the RT mask (max: 3.0 ± 0.8% [anterior], 1.6 ± 0.4% [rest]). No correlation between ∆D50[%] and beam depth was found for the sum of opposing beams, except for (45° + 315°). Conclusion This study evaluated the integration of auxiliary devices and their dosimetric influence on sCT-based TP. The AST can be easily integrated into the sCT-based TP. Further, we found that the dosimetric impact was within an acceptable range for an MRI-only workflow.