Multi-echo MR thermometry using iterative separation of baseline water and fat images

PURPOSE: To perform multi-echo water/fat separated proton resonance frequency (PRF)-shift temperature mapping. METHODS: State-of-the-art, iterative multi-echo water/fat separation algorithms produce high-quality water and fat images in the absence of heating but are not suitable for real-time imaging due to their long compute times and potential errors in heated regions. Existing fat-referenced PRF-shift temperature reconstruction methods partially address these limitations but do not address motion or large time-varying and spatially inhomogeneous B0 shifts. We describe a model-based temperature reconstruction method that overcomes these limitations by fitting a library of separated water and fat images measured before heating directly to multi-echo data measured during heating, while accounting for the PRF shift with temperature. RESULTS: Simulations in a mixed water/fat phantom with focal heating showed that the proposed algorithm reconstructed more accurate temperature maps in mixed tissues compared to a fat-referenced thermometry method. In a porcine phantom experiment with focused ultrasound heating at 1.5 Tesla, temperature maps were accurate to within 1∘ C of fiber optic probe temperature measurements and were calculated in 0.47 s per time point. Free-breathing breast and liver imaging experiments demonstrated motion and off-resonance compensation. The algorithm can also accurately reconstruct water/fat separated temperature maps from a single echo during heating. CONCLUSIONS: The proposed model-based water/fat separated algorithm produces accurate PRF-shift temperature maps in mixed water and fat tissues in the presence of spatiotemporally varying off-resonance and motion

Subject-specific liver motion modeling in MRI : A feasibility study on spatiotemporal prediction

A liver motion model based on registration of dynamic MRI data, as previously proposed by the authors, was extended with temporal prediction and respiratory signal data. The potential improvements of these extensions with respect to the original model were investigated. Additional evaluations were performed to investigate the limitations of the model regarding temporal prediction and extreme breathing motion. Data were acquired of four volunteers, with breathing instructions and a respiratory belt. The model was built from these data using spatial prediction only and using temporal forward prediction of 300 ms to 1200 ms, using the extended Kalman filter. From temporal prediction of 0 ms to 1200 ms ahead, the Dice coefficient of liver overlap decreased with 0.85%, the median liver surface distance increased with 20.6% and the vessel misalignment increased with 20%. The mean vessel misalignment was 2.9 mm for the original method, 3.42 mm for spatial prediction with a respiratory signal and 4.01 mm for prediction of 1200 ms ahead with a respiratory signal. Although the extension of the model to temporal prediction yields a decreased prediction accuracy, the results are still acceptable. The use of the breathing signal as input to the model is feasible. Sudden changes in the breathing pattern can yield large errors. However, these errors only persist during a short time interval, after which they can be corrected automatically. Therefore, this model could be useful in a clinical setting

Subject-specific liver motion modeling in MRI : A feasibility study on spatiotemporal prediction

A liver motion model based on registration of dynamic MRI data, as previously proposed by the authors, was extended with temporal prediction and respiratory signal data. The potential improvements of these extensions with respect to the original model were investigated. Additional evaluations were performed to investigate the limitations of the model regarding temporal prediction and extreme breathing motion. Data were acquired of four volunteers, with breathing instructions and a respiratory belt. The model was built from these data using spatial prediction only and using temporal forward prediction of 300 ms to 1200 ms, using the extended Kalman filter. From temporal prediction of 0 ms to 1200 ms ahead, the Dice coefficient of liver overlap decreased with 0.85%, the median liver surface distance increased with 20.6% and the vessel misalignment increased with 20%. The mean vessel misalignment was 2.9 mm for the original method, 3.42 mm for spatial prediction with a respiratory signal and 4.01 mm for prediction of 1200 ms ahead with a respiratory signal. Although the extension of the model to temporal prediction yields a decreased prediction accuracy, the results are still acceptable. The use of the breathing signal as input to the model is feasible. Sudden changes in the breathing pattern can yield large errors. However, these errors only persist during a short time interval, after which they can be corrected automatically. Therefore, this model could be useful in a clinical setting

Diffusion-weighted MRI with ADC mapping for response prediction and assessment of oesophageal cancer:A systematic review

Purpose: The aim was to perform a systematic review on the value of diffusion-weighted MRI (DW-MRI) with apparent diffusion coefficient (ADC) mapping in the prediction and assessment of response to chemo- and/or radiotherapy in oesophageal cancer. Materials and methods: A systematic search was performed on Pubmed, Embase, Medline and Cochrane databases. Studies that evaluated the ADC for response evaluation before, during or after chemo- and/or radiotherapy were included. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) was used to assess the quality of the included studies. Results: Fourteen studies, comprising 516 patients, in which the response to treatment in oesophageal cancer was evaluated on ADC maps were included. Acquisition parameter settings for DW-MRI and ROI placement varied substantially. The reference standard was RECIST or endoscopic assessment in eight non-surgery studies and histopathology after surgery in six studies. A high pre-treatment ADC significantly correlated with good response in three out of 12 studies; conversely, one study reported a significantly higher pre-treatment ADC in poor responders. In five out of eight studies good responders showed a significantly larger relative increase in ADC two weeks after the onset of treatment (range 23–59%) than poor responders (range 1.5–17%). After chemo- and/or radiotherapy ADC results varied considerably, amongst others due to large variation in the interval between completion of therapy and DW-MRI. Conclusion: DW-MRI for response evaluation to chemo- and/or radiotherapy in oesophageal cancer shows variable methods and results. A large relative ADC increase after two weeks of treatment seems most predictive for good response

On the accuracy and precision of PLANET for multiparametric MRI using phase-cycled bSSFP imaging

PURPOSE: In this work we demonstrate how sequence parameter settings influence the accuracy and precision in T1 , T2 , and off-resonance maps obtained with the PLANET method for a single-component signal model. In addition, the performance of the method for the particular case of a two-component relaxation model for white matter tissue was assessed. METHODS: Numerical simulations were performed to investigate the influence of sequence parameter settings on the accuracy and precision in the estimated parameters for a single-component model, as well as for a two-component white matter model. Phantom and in vivo experiments were performed for validation. In addition, the effects of Gibbs ringing were investigated. RESULTS: By making a proper choice for sequence parameter settings, accurate and precise parameter estimation can be achieved for a single-component signal model over a wide range of relaxation times at realistic SNR levels. Due to the presence of a second myelin-related signal component in white matter, an underestimation of approximately 30% in T1 and T2 was observed, predicted by simulations and confirmed by measurements. Gibbs ringing artifacts correction improved the precision and accuracy of the parameter estimates. CONCLUSION: For a single-component signal model there is a broad "sweet spot" of sequence parameter combinations for which a high accuracy and precision in the parameter estimates is achieved over a wide range of relaxation times. For a multicomponent signal model, the single-component PLANET reconstruction results in systematic errors in the parameter estimates as expected

Visualizing type IV endoleak using magnetic resonance imaging with a blood pool contrast agent

Growing evidence suggests that graft porosity hampers aneurysm shrinkage in patients who have been treated with the original Excluder device. To our knowledge, this suspected porosity has never been visualized in such patients. We present three patients treated with the original Excluder device whose aneurysms did not shrink in the first 2 years after treatment. Computed tomography (CT) angiography and late phase CT did not show endoleak. We performed late phase magnetic resonance imaging with a blood pool agent to visualize graft porosity. Our cases illustrate the usability of a new contrast agent and a new imaging strategy for visualizing slow-flow endoleaks that can not be imaged using currently used imaging techniques with conventional contrast agents.status: publishe

Investigation of the influence of B0 drift on the performance of the PLANET method and an algorithm for drift correction

PURPOSE: The PLANET method was designed to simultaneously reconstruct maps of T1 and T2 , the off-resonance, the RF phase, and the banding free signal magnitude. The method requires a stationary B0 field over the course of a phase-cycled balanced SSFP acquisition. In this work we investigated the influence of B0 drift on the performance of the PLANET method for single-component and two-component signal models, and we propose a strategy for drift correction. METHODS: The complex phase-cycled balanced SSFP signal was modeled with and without frequency drift. The behavior of the signal influenced by drift was mathematically interpreted as a sum of drift-dependent displacement of the data points along an ellipse and drift-dependent rotation around the origin. The influence of drift on parameter estimates was investigated experimentally on a phantom and on the brain of healthy volunteers and was verified by numerical simulations. A drift correction algorithm was proposed and tested on a phantom and in vivo. RESULTS: Drift can be assumed to be linear over the typical duration of a PLANET acquisition. In a phantom (a single-component signal model), drift induced errors of 4% and 8% in the estimated T1 and T2 values. In the brain, where multiple components are present, drift only had a minor effect. For both single-component and two-component signal models, drift-induced errors were successfully corrected by applying the proposed drift correction algorithm. CONCLUSION: We have demonstrated theoretically and experimentally the sensitivity of the PLANET method to B0 drift and have proposed a drift correction method

Visualizing type IV endoleak using magnetic resonance imaging with a blood pool contrast agent

Growing evidence suggests that graft porosity hampers aneurysm shrinkage in patients who have been treated with the original Excluder device. To our knowledge, this suspected porosity has never been visualized in such patients. We present three patients treated with the original Excluder device whose aneurysms did not shrink in the first 2 years after treatment. Computed tomography (CT) angiography and late phase CT did not show endoleak. We performed late phase magnetic resonance imaging with a blood pool agent to visualize graft porosity. Our cases illustrate the usability of a new contrast agent and a new imaging strategy for visualizing slow-flow endoleaks that can not be imaged using currently used imaging techniques with conventional contrast agents