Effect of acoustic noise reduction technology on image quality: a multivendor study.

The purpose of this study was to clarify the appropriate use of a combination of pulse sequences and acoustic noise reduction technology in general-purpose brain magnetic resonance imaging. Five pulse sequences commonly used in brain magnetic resonance imaging examinations-turbo spin-echo T2-weighted imaging, T1-weighted fluid-attenuated inversion recovery, T2-weighted fluid-attenuated inversion recovery, diffusion-weighted imaging, and magnetic resonance angiography-were performed on healthy participants at three vendors where acoustic noise reduction technology was available. The results showed that acoustic noise reduction technology reduced sound pressure levels and altered image quality in all pulse sequences across all vendors' magnetic resonance imaging scanners. Although T2-weighted imaging and T1-weighted fluid-attenuated inversion recovery resulted in little image quality degradation, T2-weighted fluid-attenuated inversion recovery, diffusion-weighted imaging, and magnetic resonance angiography had significant image degradation. Therefore, acoustic noise reduction technology should be used with caution.

[Characteristic of the image by image reconstruction method applied to successive approximation method].

In recent years, an applied successive approximation method has emerged as a new reconstruction technique of the computed tomography (CT). The CT unit of our hospital is equipped with an adaptive statistical iterative reconstruction (ASiR) which applies this method. This time, we have investigated the feature of the images through the ASiR. A subtraction of the filtered back projection (FBP) image from the ASiR image of various phantoms took place, and the structure marginal region was evaluated by varying the blend rate of ASiR and the display field of view (DFOV). By varying the CT value difference with the surroundings (using iodinated contrast medium) the structure marginal region of the subtraction image was evaluated. Modulation transfer function (MTF) and noise power spectrum (NPS) measurements were carried out to make evaluations. The result was that the CT value of the marginal unit structure was elevated with an increase of the blend ratio of ASiR and DFOV. When the CT value difference with surroundings was high, an edge was formed in the structure near the marginal region, and when it was low, a slowdown in the peripheral zone was observed. The value of MTF and NPS showed the change. The formation of the edge and slowdown in the peripheral zone can be seen in clinical images, we fully need to understand this result and make use of it in the clinical field.

[Method of measuring modulation transfer function in computed tomography using slit method with air gap phantom].

There are several methods for measuring modulation transfer function (MTF) in computed tomography (CT) images. The aluminum slit method, scanning a phantom consisting of a thin aluminum foil sandwiched by flat plastic slabs, is a standard method for measuring field of view (FOV) in clinical CT scan. But this method requires extreme caution when handling metal foil of high precision. Therefore, we devised a more simple method named air gap slit (AS) method. This new technique is based on the aluminum slit method but use air gap instead of metal foil between phantoms. The MTF was calculated from a reversed profile curve of air slit which indicated minimum CT number. The aim of this study was to investigate a possibility of AS method evaluating MTF. We investigated fluctuation of MTF and FOV in clinical CT scan compared with the aluminum slit method. The result showed that the fluctuation of MTF was caused by statistics noise and is more affected by a bone kernel than standard kernel when reconstructing. Also, the MTF value in AS method was slightly higher than in aluminum slit method and did not correspond with. AS method is a useful method for measurement of MTF in clinical CT scan. When we use this method, we have to take into consideration the noise influence of data.