This study investigates a method of time resolved 3D (4D) x-ray imaging of contrast dynamics internal to a vascular structure (e.g. intracranial aneurysm) to enable evaluation of blood flow patterns during an interventional procedure. The proposed method employs repetitive-short-pulse injection of small contrast boluses, rotational x-ray imaging with a C-arm, and retrospectively gated iterative image reconstruction. Under conditions where the passage of each contrast pulse through a vascular region is repeatable and the C-arm rotation is slow compared to the injection cycle, each flow state (spatial distribution of contrast agent at an instant) is imaged at multiple projection angles. After partitioning the projections by flow state, a sequence of 3D volumes corresponding to different states of contrast passage can be reconstructed. Feasibility was demonstrated in a patient-specific 3D-printed aneurysm phantom with 1 Hz simulated cardiac flow waveform. A custom-built power injector was programmed to produce repetitive 100ms injections of iodinated contrast agent upstream of the aneurysm, synchronized to the mid-diastolic phase of the simulated cardiac cycle (1 Hz, 0.4 mL/pulse, 20 pulses, 8 mL total). An interventional C-arm short-scan was performed with 11.3 s rotation time and 27fps frame rate. Modified PICCS reconstruction was used to generate the 4D images. The temporal evolution of contrast agent in the 4D x-ray images was visually similar to the flow patterns observed in MRI imaging and CFD simulation of the same phantom. 95% of the surface deviations between the 4D aneurysm volume and traditional 3D-DSA aneurysm volume were within -0.02 ± 0.24 mm.
Techniques aimed at the non-invasive characterization of soft tissues according to elastic properties are rapidly evolving. Virtual touch-based elastographic methods including acoustic radiation force imaging (ARFI) and optical elastography measure the peak axial displacement (PD) and time-to-peak-displacement (TTP) of tissue in response to a localized force. These measurements have been used clinically to differentiate tissues, albeit with mixed results. However, to date, the reason has not been fully understood. In this study, we apply a novel modeling approach to explore the mechanistic link between simplistic displacement measurements and tissue viscoelasticity in the application of virtual touch-based elastographic methods to staging chronic liver disease (CLD). To our knowledge, such a study has not been reported in the literature. Specifically, a numerical screening study was first conducted to identify factors that most strongly determine PD and TTP. Response surface experimental designs were then applied to these factors to produce meta-models of expected PD and TTP probability density functions (PDFs) as functions of identified factors. Results from the screening study suggest that both PD and TTP measurements are primarily influenced by three factors: the initial Young’s modulus of the tissue, the first viscoelastic Prony series time constant, and pre-compression ap- plied during acquisition. To investigate the implications of these results, stochastic inputs for these three factors associated were used to determine a robust response surface. The identified response surface methodology can be used to determine optimal cutoff values for PD and TTP that could be used in order to stage chronic liver disease.
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