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Stabinska, J.

Publications and source records attributed to Stabinska, J..

2 recordsLinked to original sources

The Proton Resonance Enhancement for CEST imaging and Shift Exchange (PRECISE) family of RF pulse shapes for Chemical Exchange Saturation Transfer MRI

PurposeTo optimize a 100 msec pulse for producing CEST MRI contrast and evaluate in mice. MethodsA gradient ascent algorithm was employed to generate a family of 100 point, 100 msec pulses for use in CEST pulse trains ( PRECISE). Gradient ascent optimizations were performed for exchange rates (kca) = 500 s-1, 1,500 s-1, 2,500 s-1, 3,500 s-1 and 4,500 s-1 and offsets ({Delta}{omega}) = 9.6, 7.8, 4.2 and 2.0 ppm. 7 PRECISE pulse shapes were tested on an 11.7 T scanner using a phantom containing three representative CEST agents with peak saturation B1 = 4 T. The pulse producing the most contrast in phantoms was then evaluated for CEST MRI pH mapping of the kidneys in healthy mice after iopamidol administration. ResultsThe most promising pulse in terms of contrast performance across all three phantoms was the 9.6 ppm, 2500 s-1 optimized pulse with [~]2.7 x improvement over Gaussian and [~]1.3xs over Fermi pulses. This pulse also displayed a large improvement in contrast over the Gaussian pulse after administration of iopamidol in live mice. ConclusionA new 100 msec pulse was developed based on gradient ascent optimizations which produced better contrast compared to standard Gaussian and Fermi pulses in phantoms. This shape also showed a substantial improvement for CEST MRI pH mapping in live mice over the Gaussian shape and appears promising for a wide range of CEST applications.

bioengineering↗

Image Downsampling Expedited Adaptive Least-squares (IDEAL) fitting improves intravoxel incoherent motion (IVIM) analysis in the human kidney

PurposeTo improve the reliability of intravoxel incoherent motion model (IVIM) parameter estimation for the diffusion-weighted imaging in the kidney using a novel Image Downsampling Expedited Adaptive Least-squares (IDEAL) approach. MethodsThe robustness of IDEAL was investigated using simulated diffusion-weighted MRI data corrupted with different levels of Rician noise. Subsequently, the performance of the proposed method was tested by fitting bi- and triexponential IVIM model to in vivo renal DWI data acquired on a clinical 3 Tesla MRI scanner and compared to conventional approaches (Fixed D* and Segmented fitting). ResultsThe numerical simulations demonstrated that the IDEAL algorithm provides robust estimates of the IVIM parameters in the presence of noise as indicated by relatively low absolute percentage bias (sMdPB [%]) and normalized root-mean-square error (RMSE [%]). The analysis of the in vivo data showed that the IDEAL-based IVIM parameter maps were less noisy and more visually appealing than those obtained using the Fixed D* and Segmented methods. Further, the use of IDEAL for the triexponential IVIM modelling resulted in reduced cortical and medullary coefficients of variation (CVs) for all IVIM parameters when compared with Fixed D*, reflecting greater accuracy of this method. ConclusionThe proposed fitting algorithm yields more robust IVIM parameter estimates and is less susceptible to poor SNR than the conventional fitting approaches. Thus, the IDEAL approach has the potential to improve the reliability of renal DW-MRI analysis for clinical applications.

biophysics↗