First clinical evaluation of breathing controlled four-dimensional computed tomography imaging

Background and Purpose

Four-dimensional computed tomography (4DCT) has become an essential part of radiotherapy planning but is often affected by artifacts. A new breathing controlled 4DCT (i4DCT) algorithm has been introduced. This study aims to present the first clinical data and to evaluate the achieved image quality, projection data coverage and beam-on time.

Material & Methods

The analysis included i4DCT data for 129 scans of patients with thoracic tumors. Projection data coverage and beam-on time were evaluated. Additionally, image quality was exemplarily discussed and rated by ten clinical experts with a 5-score-scale for 30 patients with large variations in their breathing pattern (‘challenging subgroup’). Rated images were reconstructed amplitude- and phase-based.

Results

Expert scoring revealed that 78% (amplitude-based) and 63% (phase-based) of the challenging subgroup were artifact-free (rating ≥4). For the entire cohort, average beam-on time per couch position was 4.9 ± 1.6 s. For the challenging subgroup, time increased slightly but not significantly compared to the remaining patients (5.1 s vs. 4.9 s; p = 0.64). Median projection data coverage was 93% and 94% for inhalation and exhalation, respectively, for the entire cohort. The comparison for the subgroup and the remaining patients revealed a small but significant decrease of the median coverage values for the challenging cases (inhalation: 90% vs. 94%, p = 0.02; exhalation: 93% vs. 94%, p = 0.02).

Conclusions

This first clinical evaluation of i4DCT shows very promising results in terms of image quality and projection data coverage. The results agree with and support the results of previous i4DCT phantom studies.

Comparison of intelligent 4D CT sequence scanning and conventional spiral 4D CT: a first comprehensive phantom study

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.