Purpose: The aim of this study were to compare electron density (ED), obtained by dual energy computed tomography (DECT), between hepatocellular carcinoma (HCC) and hemangioma, and to assess the differential diagnostic performance of ED between HCC and hemangioma. Methods: A total of 46 patients (27 men and 19 women; mean age, 65.7±14.0 years) diagnosed with HCC or hemangioma who underwent upper abdominal DECT between October 2021 and December 2022 were included. ED of each lesion was measured. Relative ED (rED), which is normalized by the ED of background liver parenchyma, was calculated. ED and rED of HCC and hemangioma were statistically analyzed. Results: The HCC group showed significantly higher ED (48.1±5.2) and rED (80.0±7.3) than the hemangioma group (43.7±4.1, 69.7±7.2, respectively) (p<0.01). The area under the curve of rED was greater than that of ED, but no significant difference was found (p=0.153). Conclusion: ED may help in the differential diagnosis between HCC and hemangioma.

Purpose: The aim of this study was to compare the physical properties of small focal spot imaging with deep learning reconstruction (DLR) and small or large focal spot imaging with hybrid iterative reconstruction (IR) in chest-abdominal plain computed tomography. Method: In small focal spot imaging using DLR and hybrid IR, tube currents were set at 350 mA. For the large focal spot imaging using hybrid IR, the tube current was set at 360, 400, 450, and 500 mA. The spatial frequencies with 50% task transfer function (TTF) for delrin and acrylic were calculated to compare spatial resolution properties for lung and soft tissue in the chest. Additionally, the low-contrast object-specific contrast-to-noise ratio (CNR_LO) was measured as noise property was measured for a 7-mm module with a CT value contrast of 10 HU in the abdomen. Result: Spatial frequencies with 50% TTF for delrin and acrylic were found to be greater in small focal spot imaging using DLR compared to those in small and large focal spot imaging using hybrid IR. Moreover, the CNR_LO obtained from small focal spot imaging with DLR was also nearly equivalent to that of large focal spot imaging with hybrid IR at tube currents of 450 and 500 mA. Conclusion: In chest-abdominal plain computed tomography, small focal spot imaging with DLR has been demonstrated to exhibit greater spatial resolution properties compared to small and large focal spot imaging with hybrid IR, with equivalent or better noise performance.

In cardiac magnetic resonance (CMR) for myocardial infarction, there have been quite a few cases of obscure image contrast between subendocardial lesion and left ventricular (LV) blood pool on late gadolinium enhancement (LGE) images. This study was motivated by confirmation of usefulness of post-contrast T₁map for detection of subendocardial infarction. From June 2017 to May 2018, forty-eight consecutive patients who underwent contrast-enhanced CMR to assess myocardial infarction were reviewed. We measured the contrast ratio (CR) between the infarcted myocardium and LV blood pool on LGE and on post-contrast T₁map images, and compared them. The CR (mean±standard deviation) was −0.04±0.11 for LGE images and 0.02±0.04 for post-contrast T₁map images (P<0.05). These results suggest that the post-contrast T₁map, which uses the difference in T₁ value as image contrast rather than magnitude image, can clearly depict the boundary between the infarcted myocardium and LV blood pool. The addition of post-contrast T₁map to image interpretation might provide valuable information in the evaluation of subendocardial infarction.

We used the Voronoi diagram of a computed tomography (CT) application (i.e., CT liver volume measurement) to depict the liver area, and we obtained depictions of the hepatic segments as a three-dimensional (3D) image based on clinical data; this information can be used for the patient's education and for surgical planning. The hepatic segments use the inter-relationships among the eight subsegments illustrated by Couinaud, those indicated by the portal veins and those provided by hepatic veins. The liver has dual portal and arterial innervation, with the thick portal vein intertwined with thin arteries similar to the intertwining of ivy plants. Couinaud divided the liver into eight segments (S1 to S8) based on portal vein casts. The Voronoi diagram estimates the dominant region of the portal vein, divides the liver into segments, and produces 3D images and multiplanar reconstruction (MPR) images in color. To support understanding of Couinaud’s eight hepatic segments (which are explained only in the illustration of the frontal view of the liver), using 3D images created by the Voronoi diagram, we created 3D stereo color anatomical charts of the liver that Couinaud's eight hepatic segments can be confirmed from multiple directions. In addition, we created the MPR color anatomical charts of the liver (S1 to S8) that can be confirmed by color from three directions: axial images, coronal images, and sagittal images in the same way. We converted the data of this anatomical chart into an electronic file that provides a tool that can be easily used in radiological examinations, and we were able to make improvements based on requests from users.

This is a case of a male patient in his 70s undergoing endocrine therapy for castration-resistant prostate cancer. On follow-up, he underwent whole-body bone scintigraphy for bone metastasis surveillance, and incidental cardiac uptake was identified. The findings were reported by the radiologist to the urologist, which was followed by a cardiac consultation. Late gadolinium enhancement magnetic resonance imaging did not detect typical patterns suggestive of cardiac amyloidosis. However, pyrophosphate scintigraphy identified cardiac uptake. These findings were indicative of transthyretin amyloid cardiomyopathy, and we confirmed the diagnosis by endomyocardial biopsy. In about 0.4–2.0 percentage of elderly patients, incidental cardiac uptake in bone scintigraphy has been reported. Bone scintigraphy is the most commonly utilized techniques among all scintigraphies. Thus, it is crucial that radiologists recognize and report the findings to establish a diagnosis of transthyretin amyloid cardiomyopathy.

Size-specific dose estimates (SSDEs) are dose indices that account for differences in body shape in computed tomography (CT) scans, allowing the evaluation of approximate absorbed doses in any cross section that could not be obtained with the volume CT dose index (CTDI_vol). When using automatic exposure control (AEC), CTDI_vol is modulated in the body axis direction, but the value displayed after the examination is the mean CTDI_vol for the entire scan, and it is expected that the SSDE value will change depending on which value is used in the calculation. In this study, using a human body phantom, we examined the influence of whether the mean CTDI_vol or the modulation value for each slice is used to calculate the SSDE on local organ dose evaluation. A program to calculate water equivalent diameter according to the procedure in the American Association of Physicists in Medicine Report No. 220 was developed and compared. As a result, SSDE calculated using the mean CTDI_vol (local-SSDE_mean) overestimated organ doses in the lung region by 18%–56% compared with those calculated by a web system for evaluating CT exposure doses (WAZA-ARIv2, Japan). In contrast, local-SSDE_modulated, which was calculated using the modulated value of the CTDI_vol, was able to estimate the organ dose with a relative error of 10%–13%. The average local-SSDE over the entire body axis direction was not significantly different between the two methods, regardless of which method was used for CTDI_vol. If the mean CTDI_vol is stored in the Digital Imaging and Communications in Medicine (DICOM) header tag (0018, 9345) of the CT image and the modulated CTDI_vol value is not available for each slice, the calculated local SSDE will contain many errors and will not correctly reflect the organ doses at the scan region. In such cases, it is available to use the method of evaluating local organ doses by multiplying the SSDE, which is the average of the SSDE for the entire scan, by a factor for each organ.