Readout segmented echo planar imaging (readout segmentation of long variable echo-trains, RESOLVE) is a method of dividing the k-space in the readout direction and sampling signals from multiple shots. Compared to the conventional single-shot echo planar imaging, echo space is shortened by dividing, and distortion of images is reduced, but there is a disadvantage that the imaging time is increased. To shorten the imaging time, readout partial Fourier (RPF) method was developed. In this study, it is evaluated how the apparent diffusion coefficient (ADC) value and uniformity of images are affected by RPF. In addition, signal intensity, noise, and signal-to-noise ratio of diffusion-weighted imaging were evaluated as factors influencing the ADC value and uniformity of images, and the artifacts of images were observed. When the data acquisition ratio decreased due to the RPF, the ADC value increased and the uniformity of images decreased. We had better to find special indices for the ADC map when we use RPF.

Magnetic resonance neurography (MRN) has been used to evaluate abnormal conditions of entire nerves and nerve bundles. A fat-suppressed 3D turbo spin echo (TSE) sequence is one of the imaging techniques for MRN, which has been widely adopted at 1.5 T. However, MRN of the brachial plexus using a 3D TSE sequence with short-term inversion recovery (STIR) reduces the effect of fat suppression at 3.0 T. Moreover, the use of spectral pre-saturation with inversion recovery (SPIR) does not result in uniform fat suppression due to the inhomogeneity of the static magnetic field. On the other hand, it is well known that the visibility of the brachial plexus using a 3D TSE sequence greatly changes with the equivalent echo time (TE_equiv). Therefore, we optimized the fat suppression technique and TE_equiv so that the 3D TSE sequence, using a combination of STIR with SPIR and an optimal TE_equiv (from 73 to 110 ms), achieved better visualization of the brachial plexus without residual fat.

RapidPlan, a knowledge-based planning software, uses a model library containing the dose-volume histogram (DVH) of previous treatment plans, and it automatically provides optimization objectives based on a trained model to future patients for volumetric modulated arc therapy treatment planning. However, it is unknown how DVH outliers registered in models influence the resulting plans. The purpose of this study was to investigate the effect of DVH outliers on the resulting quality of RapidPlan knowledge-based plans generated for patients with prostate cancer. First, 123 plans for patients with prostate cancer were used to populate the initial model (model_all). Next, model_all-20 and model_all-40 were created by excluding DVH outliers of bladder optimization contours 20 and 40 patients from model_all, respectively. These models were used to create plans for a 20-patient. The plans created using model_all-40 showed reductions of D_30% and D_50% in the bladder wall dose, and the DVH shape excluding outliers were affected. However, there were no significant differences in monitor units, target doses, or bladder wall doses between each treatment plan. Thus, we have shown that removal of DVH outliers from models does not affect the quality of plans created by the model.

Synthetic magnetic resonance imaging (MRI) can create different contrast weighted images by quantifying the T₁, T₂, and proton density values of the subjects from a single series of scan data. It has not been clarified how the signal to noise ratio (SNR) of the synthesized image varies depending on imaging parameters. We investigated the change of SNR in synthesized MR images by the experiment using self-made phantom. The SNR ratio of synthesized image by synthetic MRI showed the same tendency as the theoretical values due to parameter change in N_y, N_x, slice thickness, number of excitations. However, as for BW, the SNR ratio tended to be different from the theoretical values in some cases. In addition, it was suggested that the SNR of the composite image has relevance to the quantitative accuracy of the T₁, T₂, and proton density values. We thought that this is due to the image acquisition process by synthetic MRI.

Purpose: The dosimetric error due to immobilization devices has been highlighted by the AAPM Task Group 176. We developed a novel low-radiation-absorbent immobilization adaptor (HMA), which can be used with a Styrofoam headrest for head and neck region in radiotherapy. The purpose of this study was to investigate the impact of the HMA on the dose distribution and compare with a commercially released plastic adapter. Methods: Computed tomography (CT) simulation and dose calculation on a treatment planning system (TPS) were performed by the use of HMA and the plastic adapter with a cylindrical phantom. Both the adapters were placed on the phantom upside and the attenuation rate was measured. Gantry angles were changed at every 1°interval from 0°to 50°for measurements. The measured dose was normalized by the value of 90°. The treatment equipment was TrueBeam (Varian medical systems); X-ray energies were set on 4, 6 and 10 MV, respectively. The measured attenuation rates were also compared with calculation results of TPS. Results: The highest differences on attenuation rate of both the adapters were observed at a gantry angle of 32.0°; the differences were 3.0% at 4 MV, 2.7% at 6 MV and 3.0% at 10 MV, respectively, and lower absorption was HMA. TPS calculation results of monitor unit for the HMA were within 1.0% in each energy. Conclusion: The HMA was able to provide absorption dose and calculation errors lower than a commercially released adapter. It can also provide more accurate dose delivery for radiotherapy in head and neck because of the low absorption characteristics.

This study aimed to evaluate the effect of pulmonary arteriovenous computed tomography (CT) value and CT value difference on the pulmonary arteriovenous automatic extraction ability of a medical workstation. We classified patients who previously underwent contrast-enhanced CT as those with a pulmonary arteriovenous CT value difference of <50 Hounsfield unit (HU) and ≥100 HU. The groups were further divided into four subgroups each, with a total of eight groups, based on low pulmonary arteriovenous CT values of 200 or more and <250 HU, 250 or more and <300 HU, 300 or more and <350 HU, and 350 HU or more. A radiographer conducted a visual evaluation, and we judged whether it could extract pulmonary arteries A1–A10 and pulmonary veins V1–V10 without errors. When the CT value difference was <50 HU, the low pulmonary arteriovenous CT value of 200 or more and <250 HU significantly decreased the extraction ability compared with the ≥350 HU group (p<0.05), but when the CT value difference was ≥100 HU, no difference in the CT value was found. The pulmonary arteriovenous CT value and CT value difference affect the pulmonary arteriovenous automatic extraction ability of the medical workstation, but revision by the creator is necessary because misrecognition is included even if a CT value and CT value difference is high.

We developed a simplified tool for measuring image quality of medical liquid-crystal displays (LCDs) using a commercially available color digital camera. This tool implemented as a plug-in software for ImageJ (open-source image processing program) was designed to compute modulation transfer functions (MTFs) and Wiener spectra (WS) of monochrome and color LCDs from LCD photographed images captured by a camera. The intensities of the red (R), green (G), and blue (B) signals of the unprocessed image data depend on the spectral sensitivity of the image sensor used in the camera. In order to evaluate image quality based on LCD luminance, the plug-in software calibrates the RGB signals from the camera using measured luminance of the LCD and converts them into grayscale signals that correspond to the luminance of the LCD. The MTFs and WS are determined based on the line response from a one-pixel line image and the one-dimensional noise profiles acquired by scanning the uniform image using numerically synthesized slit, respectively. With this plug-in software for ImageJ, we are able to readily compute MTFs and WS of both monochrome and color LCDs from unprocessed image data of cameras. Our simplified tool is helpful to evaluate and understand the physical performance of LCDs for a large number of display users in hospitals and medical centers.