Reduction of breathing irregularity-related motion artifacts in low-pitch spiral 4D CT by optimized projection binning

Abstract

BackgroundRespiration-correlated CT (4D CT) is the basis of radiotherapy treatment planning of thoracic and abdominal tumors. Current clinical 4D CT images suffer, however, from artifacts due to unfulfilled assumptions concerning breathing pattern regularity. We propose and evaluate modifications to existing low-pitch spiral 4D CT reconstruction protocols to counteract respective artifacts.MethodsThe proposed advanced reconstruction (AR) approach consists of two steps that build on each other: (1) statistical analysis of the breathing signal recorded during CT data acquisition and extraction of a patient-specific reference breathing cycle for projection binning; (2) incorporation of an artifact measure into the reconstruction. 4D CT data of 30 patients were reconstructed by standard phase- and local amplitude-based reconstruction (PB, LAB) and compared with images obtained by AR. The number of artifacts was evaluated and artifact statistics correlated to breathing curve characteristics.ResultsAR reduced the number of 4D CT artifacts by 31% and 27% compared to PB and LAB; the reduction was most pronounced for irregular breathing curves.ConclusionsWe described a two-step optimization of low-pitch spiral 4D CT reconstruction to reduce artifacts in the presence of breathing irregularity and illustrated that the modifications to existing reconstruction solutions are effective in terms of artifact reduction.Electronic supplementary materialThe online version of this article (doi:10.1186/s13014-017-0835-7) contains supplementary material, which is available to authorized users.

Intelligent 4D CT sequence scanning (i4DCT): First scanner prototype implementation and phantom measurements of automated breathing signal‐guided 4D CT

“…The motion insert position corresponding to the two breathing cycles with >100% and <50% amplitude (relative to the base cycle) did, therefore, not correspond to the insert position at neighboring breathing cycles and z-positions, respectively-leading to visible double structure artifacts. Issues related to the >100% breathing cycle were reduced by the implemented reference curvebased projection binning, 7 during which projection data corresponding to breathing signal amplitudes above the reference curve height were not used for reconstruction. Moreover, based on the parameterization of i4DCT, 15 the <50% amplitude breathing cycle was not considered during reconstruction after i4DCT projection data acquisition.…”

“…The projection data are then used for retrospective image reconstruction, exploiting either phase-or amplitude-based reference curve-based projection binning. 7…”

“…They are used, for example, to define the internal target volume 2,3 and to incorporate spatio-temporal information into dose calculation and optimization. 4,5 However, since its introduction into the clinical environment, it has been reported that the images often contain so-called 4D CT artifacts (Yamamoto et al 6 : 90% of analyzed clinical 4D CT data with at least one artifact; Werner et al 7 : clinical 4D CT images contain, on average, five artifacts). From an application perspective, it is known that the artifacts negatively affect reliability of 4D CT-extracted information and the related clinical 4D RT workflow.…”

Intelligent 4D CT sequence scanning (i4DCT): Concept and performance evaluation

“…The respiratory signal is then retrospectively analyzed and correlated with the acquired projection or image data. The thereby “tagged” CT data are finally, according to the assigned breathing signal information, sorted or reconstructed into breathing state‐specific 3D CT volumes . The inherent problem of retrospective breathing curve analysis is that insufficient projection data coverage for reconstruction of image slices at desired breathing states, due to patient breathing irregularity or general violation of the so‐called data sufficiency condition (DSC), becomes evident only after data acquisition, that is, during treatment planning.…”

Intelligent 4D CT Sequence Scanning (i4DCT)

“…The thereby "tagged" CT data are finally, according to the assigned breathing signal information, sorted or reconstructed into breathing state-specific 3D CT volumes. 13 The inherent problem of retrospective breathing curve analysis is that insufficient projection data coverage for reconstruction of image slices at desired breathing states, due to patient breathing irregularity or general violation of the so-called data sufficiency condition (DSC), 15 becomes evident only after data acquisition, that is, during treatment planning. Yet, insufficient data coverage inevitably leads to image artifacts.…”