Physics in medicine and biology
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4D ultrafast ultrasound imaging was recently shown using a 2D matrix (i.e. fully populated) connected to a 1024-channel ultrafast ultrasound scanner. In this study, we investigate the row-column addressing (RCA) matrix approach, which allows a reduction of independent channels from N × N to N + N, with a dedicated beamforming strategy for ultrafast ultrasound imaging based on the coherent compounding of orthogonal plane wave (OPW). OPW is based on coherent compounding of plane wave transmissions in one direction with receive beamforming along the orthogonal direction and its orthogonal companion sequence. ⋯ Results in a Doppler phantom and the human humeral artery in vivo confirmed that ultrafast Doppler imaging can be achieved with reduced performances when compared against the equivalent 2D matrix. Volumetric anatomic Doppler rendering and voxel-based pulsed Doppler quantification are presented as well. OPW compound imaging using emulated RCA matrix can achieve a power Doppler with sufficient contrast to recover the vein shape and provides an accurate Doppler spectrum.
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Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves-TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. ⋯ In all cases, the direct method yielded lower noise and standard deviation than the indirect method based on OSEM. Overall, the proposed direct reconstruction offered a better bias-variance tradeoff than the indirect method applied to either OSEM and OSL-MAP. Direct parametric reconstruction as applied to in vivo dynamic PET MPI data is therefore a promising method for producing MBF maps with lower variance.
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Dosimetric errors in a magnetic resonance imaging (MRI) only radiotherapy workflow may be caused by system specific geometric distortion from MRI. The aim of this study was to evaluate the impact on planned dose distribution and delineated structures for prostate patients, originating from this distortion. A method was developed, in which computer tomography (CT) images were distorted using the MRI distortion field. ⋯ The method developed can quantify the dosimetric effects of MRI system specific distortion in a prostate MRI only radiotherapy workflow, separated from dosimetric effects originating from synthetic CT generation. No clinically relevant dose difference or structure deformation was found when 3D distortion correction and high acquisition bandwidth was used. The method could be used for any MRI sequence together with any anatomy of interest.
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Intraoperative x-ray radiography/fluoroscopy is commonly used to assess the placement of surgical devices in the operating room (e.g. spine pedicle screws), but qualitative interpretation can fail to reliably detect suboptimal delivery and/or breach of adjacent critical structures. We present a 3D-2D image registration method wherein intraoperative radiographs are leveraged in combination with prior knowledge of the patient and surgical components for quantitative assessment of device placement and more rigorous quality assurance (QA) of the surgical product. The algorithm is based on known-component registration (KC-Reg) in which patient-specific preoperative CT and parametric component models are used. ⋯ Initial application in clinical data in spine surgery demonstrated TRE of 2.7 ± 2.6 mm and 1.5 ± 0.8°. The KC-Reg algorithm offers an independent check and quantitative QA of the surgical product using radiographic/fluoroscopic views acquired within standard OR workflow. Such intraoperative assessment could improve quality and safety, provide the opportunity to revise suboptimal constructs in the OR, and reduce the frequency of revision surgery.
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Patient motion due to respiration can lead to artefacts and blurring in positron emission tomography (PET) images, in addition to quantification errors. The integration of PET with magnetic resonance (MR) imaging in PET-MR scanners provides complementary clinical information, and allows the use of high spatial resolution and high contrast MR images to monitor and correct motion-corrupted PET data. In this paper we build on previous work to form a methodology for respiratory motion correction of PET data, and show it can improve PET image quality whilst having minimal impact on clinical PET-MR protocols. ⋯ Qualitative PET reconstruction improvements and artefact reduction are assessed with visual analysis, and quantitative improvements are calculated using standardised uptake value (SUV(peak) and SUV(max)) changes in avid lesions. We demonstrate the capability of a joint PET-MR motion model to predict respiratory motion by showing significantly improved image quality of PET data acquired before the motion model data. The method can be used to incorporate motion into the reconstruction of any length of PET acquisition, with only 1 min of extra scan time, and with no external hardware required.