Reduction of breathing irregularity-related motion artifacts in low-pitch spiral 4D CT by optimized projection binning
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RESEARCH
Open Access
Reduction of breathing irregularityrelated motion artifacts in low-pitch spiral 4D CT by optimized projection binning René Werner1*†
, Christian Hofmann2† , Eike Mücke1 and Tobias Gauer1
Abstract Background: Respiration-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. Methods: The 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. Results: AR 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. Conclusions: We 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. Keywords: 4D CT, Motion artifacts, Breathing irregularity, Artifact reduction
Background In radiotherapy (RT) treatment planning for thoracic and abdominal cancer patients, the term 4D CT refers to respiration-correlated computed tomography, and a 4D CT data set is understood as a series of 3D CT images of the patient geometry at different breathing states. Since the seminal works in this field [1–3], 4D CT has rapidly found its way into clinical practice [4] and is currently estimated to be routinely applied in approximately 70% of the RT centers in the US [5]. 4D CT information are, for instance, used to dimension the internal target
*Correspondence: [email protected] † Equal contributors 1 University Medical Center Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Germany Full list of author information is available at the end of the article
volume and to perform 4D dose calculation in the context of 4D RT quality assurance [6–9]. Very recently, 4D CT imaging has even been reported to be applied for CT ventilation image-guided RT treatment, exploiting a registration-based local lung volume change analysis in the 4D CT images and feeding this information back into treatment plan optimization [5]. All 4D CT use cases have in common that their reliability depends on 4D CT image quality and the absence of motion artifacts [6, 7, 10, 11]. However, in agreement with earlier publications [12
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