Christian Hofmann

Optimized projection binning for improved helical amplitude- and phase-based 4DCT reconstruction in the presence of breathing irregularity

Respiration-correlated CT (4DCT) forms the basis of clinical 4D radiotherapy workflows for patients with thoracic and abdominal lesions. 4DCT image data, however, often suffers from motion artifacts due to unfulfilled assumptions during reconstruction and image/projection data sorting. In this work and focusing on low-pitch helical scanning protocols, two questionable assumptions are addressed: (1) the need for regular breathing patterns and (2) a constant correlation between the external breathing signal acquired for image/projection sorting and internal motion patterns. To counteract (1), a patient-specific upper breathing signal amplitude threshold is introduced to avoid artifacts due to unusual deep inspiration (helpful for both amplitude- and phase-based reconstruction). In addition, a projection data binning algorithm based on a statistical analysis of the patients breathing signal is proposed to stabilize phase-based sorting. To further alleviate the need for (2), an image artifact metric is incorporated into and minimized during the reconstruction process. The optimized reconstruction is evaluated using 30 clinical 4DCT data sets and demonstrated to significantly reduce motion artifacts.

Metal artifact reduction of CT scans to improve PET/CT

In recent years, different metal artifact reduction methods have been developed for CT. These methods have only recently been introduced for PET/CT even though they could be beneficial for interpretation, segmentation, and quantification of the PET/CT images. In this study, phantom and patient scans were analyzed visually and quantitatively to measure the effect on PET images of iterative metal artifact reduction (iMAR) of CT data. Methods: The phantom consisted of 2 types of hip prostheses in a solution of 18F-FDG and water. 18F-FDG PET/CT scans of 14 patients with metal implants (either dental implants, hip prostheses, shoulder prostheses, or pedicle screws) and 68Ga-labeled prostate-specific membrane antigen (68Ga-PSMA) PET/CT scans of 7 patients with hip prostheses were scored by 2 experienced nuclear medicine physicians to analyze clinical relevance. For all patients, a lesion was located in the field of view of the metal implant. Phantom and patients were scanned in a PET/CT scanner. The standard low-dose CT scans were processed with the iMAR algorithm. The PET data were reconstructed using attenuation correction provided by both standard CT and iMAR-processed CT. Results: For the phantom scans, cold artifacts were visible on the PET image. There was a 30% deficit in 18F-FDG concentration, which was restored by iMAR processing, indicating that metal artifacts on CT images induce quantification errors in PET data. The iMAR algorithm was useful for most patients. When iMAR was used, the confidence in interpretation increased or stayed the same, with an average improvement of 28% ± 20% (scored on a scale of 0%–100% confidence). The SUV increase or decrease depended on the type of metal artifact. The mean difference in absolute values of SUVmean of the lesions was 3.5% ± 3.3%. Conclusion: The iMAR algorithm increases the confidence of the interpretation of the PET/CT scan and influences the SUV. The added value of iMAR depends on the indication for the PET/CT scan, location and size/type of the prosthesis, and location and extent of the disease.

Dependence of subject-specific parameters for a fast helical CT respiratory motion model on breathing rate: an animal study

To determine if the parameters relating lung tissue displacement to a breathing surrogate signal in a previously published respiratory motion model vary with the rate of breathing during image acquisition. An anesthetized pig was imaged using multiple fast helical scans to sample the breathing cycle with simultaneous surrogate monitoring. Three datasets were collected while the animal was mechanically ventilated with different respiratory rates: 12 bpm (breaths per minute), 17 bpm, and 24 bpm. Three sets of motion model parameters describing the correspondences between surrogate signals and tissue displacements were determined. The model error was calculated individually for each dataset, as well asfor pairs of parameters and surrogate signals from different experiments. The values of one model parameter, a vector field denoted [Formula: see text] which related tissue displacement to surrogate amplitude, determined for each experiment were compared. The mean model error of the three datasets was 1.00  ±  0.36 mm with a 95th percentile value of 1.69 mm. The mean error computed from all combinations of parameters and surrogate signals from different datasets was 1.14  ±  0.42 mm with a 95th percentile of 1.95 mm. The mean difference in [Formula: see text] over all pairs of experiments was 4.7%  ±  5.4%, and the 95th percentile was 16.8%. The mean angle between pairs of [Formula: see text] was 5.0  ±  4.0 degrees, with a 95th percentile of 13.2 mm. The motion model parameters were largely unaffected by changes in the breathing rate during image acquisition. The mean error associated with mismatched sets of parameters and surrogate signals was 0.14 mm greater than the error achieved when using parameters and surrogate signals acquired with the same breathing rate, while maximum respiratory motion was 23.23 mm on average.

Technical considerations for automated low-pitch spiral 4D CT scanning protocol selection

Respiration-correlated CT (4D CT) represents the basis of radiotherapy treatment planning for thoracic and abdominal tumor patients. A common approach is low-pitch spiral 4D CT. Similar to standard spiral 3D CT, CT projection data are continuously acquired while the patient couch is moving through the gantry. To ensure sufficient projection data coverage for 4D CT reconstruction, the so-called 4D CT data sufficiency condition (DSC) has to be fulfilled: For a fixed pitch factor and gantry rotation time, the patient breathing rate must be above a certain threshold; otherwise, artifacts impair image quality. For the current Siemens 4D CT scanner generation, three 4D CT protocols can be selected manually, associated with DSC thresholds of 6, 9 and 12 breaths per minute (BPM). Due to, e.g., a limited achievable z-range during scanning with lower BPM protocols, these options are, however, often not selected in practice. As a result, a high fraction of artifact-affected 4D CT data are reported. Aiming to optimize respective 4D CT workflows and improve image quality, this study systematically investigates the influence of parameters to be considered for automated scanning protocol selection and their interrelation (e.g. severity of artifacts due to DSC violation vs. clinically required z-scan range).

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

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.