Proposal of objective morphological classification system for hepatocellular carcinoma using preoperative multiphase computed tomography.

BACKGROUND: To establish a preoperative morphological classification system for hepatocellular carcinoma using multiphase computed tomography. METHODS: All consecutive patients who were diagnosed with hepatocellular carcinoma between 2004 and 2009 were enrolled, for a total of 232 patients. The concavity and convexity of each outer contour of hepatocellular carcinoma acquired from multiphase computed tomography were analyzed, and the area and depth of each indentation were quantified. The indentation area to tumor area ratio (s:S) and the s:S ratio multiplied by the indentation depth to indentation base ratio (s:S × d:t) were used as feature values reflecting the individual shapes. RESULTS: Using a hierarchical cluster analysis, the shapes were classified into three groups: Type I (smooth: n = 158), Type II (jagged: n = 63), and Type III (rough: n = 11). The 5-year survival rates for Types I, II, and III were 64, 53, and 0 %, respectively (I vs. II, P = 0.038; I vs. III, P = 0.001; II vs. III, P = 0.002). The 5-year disease-free survival rates for Types I, II, and III were 27, 23, and 0 %, respectively (I vs. III, P = 0.0003 and II vs. III, P = 0.008). Microscopic portal venous invasion was significantly more likely with Type III than with Type I or II (P < 0.001 and P = 0.001, respectively). CONCLUSIONS: The newly developed semiautomatic computed tomography-based morphological classification system appears to provide a promising additional criterion for the prognostic categorization of patients with hepatocellular carcinoma.

T2 mapping of muscle activity using ultrafast imaging.

Measuring exercise-induced muscle activity is essential in sports medicine. Previous studies proposed measuring transverse relaxation time (T(2)) using muscle functional magnetic resonance imaging (mfMRI) to map muscle activity. However, mfMRI uses a spin-echo (SE) sequence that requires several minutes for acquisition. We evaluated the feasibility of T(2) mapping of muscle activity using ultrafast imaging, called fast-acquired mfMRI (fast-mfMRI), to reduce image acquisition time. The current method uses 2 pulse sequences, spin-echo echo-planar imaging (SE-EPI) and true fast imaging with steady precession (TrueFISP). SE-EPI images are used to calculate T(2), and TrueFISP images are used to obtain morphological information. The functional image is produced by subtracting the image of muscle activity obtained using T(2) at rest from that produced after exercise. Final fast-mfMRI images are produced by fusing the functional images with the morphologic images. Ten subjects repeated ankle plantar flexion 200 times. In the fused images, the areas of activated muscle in the fast-mfMRI and SE-EPI images were identical. The geometric location of the fast-mfMRI did not differ between the morphologic and functional images. Morphological and functional information from fast-mfMRI can be applied to the human trunk, which requires limited scan duration. The difference obtained by subtracting T(2) at rest from T(2) after exercise can be used as a functional image of muscle activity.

Effects of MR image noise on estimation of short T2 values from T2 -weighted image series.

We examined how the noise from magnetic resonance (MR) imaging affects the calculation of T(2) in skeletal muscle, a tissue with short T(2) values. The measured pixel intensity of the MR image (: the magnitude image) was the superimposed signal which was composed of the MR signal and the noise, and we demonstrated that noise from a magnitude image matches the DC component of the T(2) decay curve. In materials with long T(2) values, the noise has no influence on the selective echo time (TE) in calculating T(2). However, in materials with short T(2) values, noise clearly influences the selective TE. In this study, we proposed a T(2) effective signal-ratio, T(2)SR, as an index for determining whether the noise of the magnitude image can be ignored in calculating T(2). When T(2)SR and the signal-to-noise ratio (SNR), an index of image quality, were compared as indices to evaluate the influence of noise in the calculation of T(2), T(2)SR was useful and SNR was not. The use of multiple spin echo (MSE) technique shortened imaging time, but required detailed understanding of the MSE. Our results indicated that T(2) can be calculated correctly for skeletal muscle and other tissues with short T(2) even when the receiver coil has a low SNR and few measurement points are available.

[Visualizing muscle activation by fusing fast MR images].

The purpose of this study was to conduct fast-acquired muscle functional magnetic resonance imaging (fast-mfMRI). Fast-mfMRI is a method of fusing fast MR images in order to visualize muscle activity. Exercise selectively increases the signal intensities (SI) of active muscles in T2-weighted magnetic resonance (MR) images. A fast-mfMRI image is a fusion of two types of images: an anatomic image acquired by the TrueFISP method and a functional image acquired by the SE-EPI (spin-echo echo-planar-imaging) method. MR images of four healthy males were recorded at rest before and after plantar flexion. The Gain of the MR signal remained constant from before the flexion exercise (at rest) to after the exercise. The data on the area of muscle activity could be extracted by adapting a threshold value obtained by a functional image at rest to the functional image after the exercise. By uniting the data on the area of muscle activity with the anatomic images after the exercise, we constructed a fused image rich in anatomical information and effective in visualizing muscle activity. These fast-mfMRI images can be acquired in 14 seconds. Our results suggest that fast-mfMRI has the potential to measure muscle activity in the trunk, where conventional mfMRI has been ineffective.