Automatic CT-based finite element model generation for temperature-based death time estimation: feasibility study and sensitivity analysis.

Temperature-based death time estimation is based either on simple phenomenological models of corpse cooling or on detailed physical heat transfer models. The latter are much more complex but allow a higher accuracy of death time estimation, as in principle, all relevant cooling mechanisms can be taken into account.Here, a complete workflow for finite element-based cooling simulation is presented. The following steps are demonstrated on a CT phantom: Computer tomography (CT) scan Segmentation of the CT images for thermodynamically relevant features of individual geometries and compilation in a geometric computer-aided design (CAD) model Conversion of the segmentation result into a finite element (FE) simulation model Computation of the model cooling curve (MOD) Calculation of the cooling time (CTE) For the first time in FE-based cooling time estimation, the steps from the CT image over segmentation to FE model generation are performed semi-automatically. The cooling time calculation results are compared to cooling measurements performed on the phantoms under controlled conditions. In this context, the method is validated using a CT phantom. Some of the phantoms' thermodynamic material parameters had to be determined via independent experiments.Moreover, the impact of geometry and material parameter uncertainties on the estimated cooling time is investigated by a sensitivity analysis.

Reduced k-space acquisition to accelerate MR imaging of moving interventional instruments: a phantom study.

PURPOSE: The goal of this study was to investigate the impact of reduced k-space sampling rates on the visualization of a moving MR-compatible puncture needle and to demonstrate the feasibility of keyhole imaging in interventional magnetic resonance imaging (MRI). MATERIAL AND METHODS: All experiments were performed in an open 1.0 Tesla MRI. MR images of a moving puncture needle were taken with different keyhole sampling rates from 15-100%, in 10% increments. The needle was submerged in a water-filled basin and was imaged in motion with a T1-weighted gradient-echo sequence with an initial acquisition rate of 1.4 s per image. An apparatus operated by a compressor unit enabled needle rotation and ensured reproducible needle movements. The median forward velocity of the needle tip was 2 cm/s. To evaluate the depiction of the needle, artifact diameter of the needle, contrast-to-noise ratio (CNR), and needle tip profiles (delineation) were measured. RESULTS: The needle position was determined with an longitudinal error of 3 mm and a transverse error of 0.8 mm with respect to the needle's orientation and the theoretically calculated trajectory. No significant correlation was found between the CNR and velocity. A reduction of k-space update rates caused neither a significant reduction of CNR nor a significant increase in artifact diameter or blurring of the needle profile. CONCLUSION: The application of keyhole imaging with update rates of greater than 15% is sufficient for the MR guidance of interventions with an signal-to-noise ratio >9 of the surrounding tissue and a target accuracy of >1 mm. Keyhole imaging can increase temporal resolution while ensuring unimpaired spatial resolution and image quality of the depicted instrument.