3-T direct MR arthrography of the wrist: value of finger trap distraction to assess intrinsic ligament and triangular fibrocartilage complex tears.

PURPOSE: To determine the value of applying finger trap distraction during direct MR arthrography of the wrist to assess intrinsic ligament and triangular fibrocartilage complex (TFCC) tears. MATERIALS AND METHODS: Twenty consecutive patients were prospectively investigated by three-compartment wrist MR arthrography. Imaging was performed with 3-T scanners using a three-dimensional isotropic (0.4 mm) T1-weighted gradient-recalled echo sequence, with and without finger trap distraction (4 kg). In a blind and independent fashion, two musculoskeletal radiologists measured the width of the scapholunate (SL), lunotriquetral (LT) and ulna-TFC (UTFC) joint spaces. They evaluated the amount of contrast medium within these spaces using a four-point scale, and assessed SL, LT and TFCC tears, as well as the disruption of Gilula's carpal arcs. RESULTS: With finger trap distraction, both readers found a significant increase in width of the SL space (mean Δ = +0.1mm, p ≤ 0.040), and noticed more contrast medium therein (p ≤ 0.035). In contrast, the differences in width of the LT (mean Δ = +0.1 mm, p ≥ 0.057) and UTFC (mean Δ = 0mm, p ≥ 0.728) spaces, as well as the amount of contrast material within these spaces were not statistically significant (p = 0.607 and ≥ 0.157, respectively). Both readers detected more SL (Δ = +1, p = 0.157) and LT (Δ = +2, p = 0.223) tears, although statistical significance was not reached, and Gilula's carpal arcs were more frequently disrupted during finger trap distraction (Δ = +5, p = 0.025). CONCLUSION: The application of finger trap distraction during direct wrist MR arthrography may enhance both detection and characterisation of SL and LT ligament tears by widening the SL space and increasing the amount of contrast within the SL and LT joint spaces.

Determination of displacement, stress- and strain-distribution in the human heart: a FE-model on the basis of MR imaging.

The determination of characteristic cardiac parameters, such as displacement, stress and strain distribution are essential for an understanding of the mechanics of the heart. The calculation of these parameters has been limited until recently by the use of idealised mathematical representations of biventricular geometries and by applying simple material laws. On the basis of 20 short axis heart slices and in consideration of linear and nonlinear material behaviour we have developed a FE model with about 100,000 degrees of freedom. Marching Cubes and Phong's incremental shading technique were used to visualise the three dimensional geometry. In a quasistatic FE analysis continuous distribution of regional stress and strain corresponding to the endsystolic state were calculated. Substantial regional variation of the Von Mises stress and the total strain energy were observed at all levels of the heart model. The results of both the linear elastic model and the model with a nonlinear material description (Mooney-Rivlin) were compared. While the stress distribution and peak stress values were found to be comparable, the displacement vectors obtained with the nonlinear model were generally higher in comparison with the linear elastic case indicating the need to include nonlinear effects.

Practical signal-to-noise ratio quantification for sensitivity encoding: Application to coronary MR angiography.

Purpose: To develop and evaluate a practical method for the quantification of signal-to-noise ratio (SNR) on coronary MR angiograms (MRA) acquired with parallel imaging.Materials and Methods: To quantify the spatially varying noise due to parallel imaging reconstruction, a new method has been implemented incorporating image data acquisition followed by a fast noise scan during which radio-frequency pulses, cardiac triggering and navigator gating are disabled. The performance of this method was evaluated in a phantom study where SNR measurements were compared with those of a reference standard (multiple repetitions). Subsequently, SNR of myocardium and posterior skeletal muscle was determined on in vivo human coronary MRA.Results: In a phantom, the SNR measured using the proposed method deviated less than 10.1% from the reference method for small geometry factors (<= 2). In vivo, the noise scan for a 10 min coronary MRA acquisition was acquired in 30 s. Higher signal and lower SNR, due to spatially varying noise, were found in myocardium compared with posterior skeletal muscle.Conclusion: SNR quantification based on a fast noise scan is a validated and easy-to-use method when applied to three-dimensional coronary MRA obtained with parallel imaging as long as the geometry factor remains low.