Purpose: This study aimed to propose a mathematical model to describe motion blur in hepatobiliary-phase magnetic resonance images. Methods: Simulated images were constructed based on the mathematical model of motion blur, and this model was then validated by comparing the simulated images with the magnetic resonance images obtained using a dynamic phantom. The mathematical model employed a convolution integral that combined the stationary-state signal distribution and the probability density distribution of the positional shifts during acquisition. The stationary signal distribution was obtained from the magnetic resonance images of a bottle phantom, and the probability density distribution was derived from sinusoidal motion mimicking respiratory movement. Both visual and quantitative evaluations were performed between the simulated images based on the mathematical model and the magnetic resonance images acquired using the dynamic phantom. Results: The simulated and acquired magnetic resonance images exhibited similar shapes. The difference in the lengths of the respective high-intensity regions was 0.7 mm. Conclusion: The proposed mathematical model effectively represents motion blur in magnetic resonance images.

Purpose: At our institution, the method previously used for bladder filling in prostate cancer radiation therapy involved drinking 500 ml of water and voiding 30 minutes prior to treatment. However, achieving consistent bladder volume had been challenging. We therefore developed and evaluated a new protocol. Methods: The new method involves drinking 200 ml of water 2 hours before treatment, followed by voiding, and then drinking another 200 ml of water 1 hour prior. Bladder volumes during treatment planning computed tomography (CT) and during treatment were measured using an ultrasound device and compared between the method previously used at our institution and the new method. Ten patients were evaluated for each protocol. Results: The mean bladder volumes at the time of planning CT and during treatment were 247.4±99.6 ml and 315.7±158.2 ml, respectively, with the method previously used at our institution, and 201.5±33.0 ml and 192.6±37.2 ml, respectively, with the new method. The new protocol resulted in more consistent bladder volumes. Conclusion: The newly developed protocol achieved bladder volumes within the range of 100–250 ml, improved reproducibility at the time of treatment, and is expected to enhance workflow efficiency.

Purpose: Accurate quantification of body fat distribution is essential in preventive medicine due to its public health outcomes. Specifically, visceral fat area measured from abdominal computed tomography (CT) serves as a key diagnostic criterion for obesity-related metabolic disorders. This study evaluated the efficacy of zero-shot segmentation capabilities of the Segment Anything Model (SAM) and its medical variant (MedSAM) for adipose tissue delineation on abdominal CT images. Methods: Segmentation of the subcutaneous and visceral fat compartments was performed using point prompts on abdominal images. For a comprehensive evaluation, we compared the foundation models with a supervised U-Net architecture trained specifically for this task. The analysis utilized the publicly available annotated abdominal adipose tissue CT image dataset, which contained expert-annotated ground truth labels for adipose tissue compartments. Results: The average Dice scores for visceral fat segmentation were 0.59 for SAM, 0.29 for MedSAM, and 0.93 for the U-Net. These findings indicate that while SAM achieved moderate performance, MedSAM exhibited limited effectiveness for this task. Both foundation models showed substantial performance gaps compared to the task-specific supervised approach. Conclusion: The findings revealed limitations in the zero-shot segmentation capabilities of SAM and MedSAM for specialized medical imaging tasks, particularly for adipose tissue quantification in abdominal CT. Although foundation models offer theoretical advantages in generalizability and deployment efficiency, their performance in specialized medical applications requires significant enhancement through task-specific fine-tuning, and optimized prompt engineering strategies. Further studies are required to enhance the clinical utility of these models for reliable and accessible fat segmentation.

Purpose: The purpose of this study was to compare true non-contrast (TNC) images and virtual non-contrast (VNC) images obtained using photon-counting detector computed tomography (PCD-CT) and to evaluate the accuracy of VNC images in the assessment of hepatic lesions. Methods: The study included 79 patients who underwent contrast-enhanced CT and were diagnosed with hepatic lesions. The hepatic lesions consisted of 19 cases of hepatocellular carcinoma, 22 cases of metastatic liver tumors, 20 cases of hemangiomas, and 18 cases of cysts. CT values and standard deviations of hepatic lesions and background liver parenchyma were measured on TNC images and on VNC images reconstructed from equilibrium-phase scans. Using the measured values, the contrast-to-noise ratio (CNR) of hepatic lesions was calculated, and CT values and CNRs of the lesions were compared between true TNC and VNC images. Results: The CT values of hepatic lesions on TNC and VNC images were 37.5±15.1 and 38.7±16.1 HU, respectively, while those of background liver parenchyma were 61.2±5.91 and 64.3±6.02 HU, respectively; all demonstrated good agreement. The correlation coefficients of CT values between TNC and VNC images were 0.898 for hepatic lesions and 0.933 for background liver parenchyma. Furthermore, when analyzed by lesion type, no significant differences were observed in CT values and CNRs (p>0.05). Conclusion: The accuracy of VNC images for liver lesions was very high, and for typical hepatic lesions in particular, the findings suggest that TNC images may be omitted.

Purpose: A number of interventional radiology (IVR) procedures in hepatology have been performed in the past, mainly transcatheter arterial embolization and transcatheter arterial chemoembolization. Radiation used for fluoroscopy during the procedure plays an extremely important role in hepatology IVR procedures, and the evaluation of the physician’s lens radiation dose, Hp(3), during these procedures is extremely important. Methods: In this study, the lens radiation exposure of 4 physicians engaged in interventional hepatology procedures was measured. A lens-specific dosimeter was attached near the left eye, and the estimated dose was recorded over a period of almost 5 years (October 2017–August 2022). Annual estimated doses were calculated from the accumulated doses, compared to the lens equivalent dose limits and threshold doses, and the average dose per procedure was calculated by the number of procedures performed. Results: Although no physician exceeded the lens equivalent dose limit of 20 mSv/year, there were physicians who exceeded 10 mSv/year, which was calculated by dividing the threshold dose of 0.5 Gy for cataracts by a 50-year work period. Conclusion: In interventional hepatology procedures, the exposure to the lens of the physician cannot be ignored, and it is important to take thorough protective measures to reduce exposure, not only for the main physician but also for the second assistant.