OBJECTIVES: In this paper, we present an automatic method to segment four chambers by extracting a whole heart, separating the left and right sides of the heart, and spliting the atrium and ventricle regions from each heart in cardiac computed tomography angiography (CTA) efficiently. METHODS: We smooth the images by applying filters to remove noise. Next, the volume of interest is detected by using k-means clustering. In this step, the whole heart is coarsely extracted, and it is used for seed volumes in the next step. Then, we detect seed volumes using a geometric analysis based on anatomical information and separate the left and right heart regions with the power watershed algorithm. Finally, we refine the left and right sides of the heart using the level-set method, and extract the atrium and ventricle from the left and right heart regions using the split energy function. RESULTS: We tested the proposed heart segmentation method using 20 clinical scan datasets which were acquired from various patients. To validate the proposed heart segmentation method, we evaluated its accuracy in segmenting four chambers based on four error evaluation metrics. The average values of differences between the manual and automatic segmentations were less than 3.3%, approximately. CONCLUSIONS: The proposed method extracts the four chambers of the heart accurately, demonstrating that this approach can assist the cardiologist.
Angiography ; Dataset ; Heart ; Humans ; Methods* ; Noise

Tyrosine kinase (TK) inhibitors are most common used to treat chronic myeloid leukemia (CML). Several studies describe a range of adverse effects of TK inhibitors on the kidney in adult patients, including nephrotic syndrome. However, there are only a few pediatric case reports on TK inhibitor-associated nephrotic syndrome. We report a case of nephrotic syndrome associated with dasatinib, a type of TK inhibitor, in a child who suffered from both the underlying idiopathic nephrotic syndrome and CML. A 14-year-old Korean boy was diagnosed with steroid dependent nephrotic syndrome at 4 years old and CML at 11 years old. He developed a relapse of nephrotic syndrome after treatment with TK inhibitors, especially dasatinib, which he used for four months. Despite receiving steroid pulse therapy due to his underlying steroid dependent nephrotic syndrome, his proteinuria did not respond. He discontinued dasatinib medication due to the possibility to dasatinib induced nephrotic syndrome.After one week, his nephrotic syndrome improved. The case is important because if a CML patient that has been on a TK inhibitor develops a newly onset nephrotic range proteinuria, TK inhibitor-induced nephrotic syndrome should be included in the differential diagnosis.

BACKGROUND/AIMS: Computed tomography (CT) hepatic volumetry is currently accepted as the most reliable method for preoperative estimation of graft weight in living donor liver transplantation (LDLT). However, several factors can cause inaccuracies in CT volumetry compared to real graft weight. The purpose of this study was to determine the frequency and degree of resection plane-dependent error in CT volumetry of the right hepatic lobe in LDLT. METHODS: Forty-six living liver donors underwent CT before donor surgery and on postoperative day 7. Prospective CT volumetry (VP) was measured via the assumptive hepatectomy plane. Retrospective liver volume (VR) was measured using the actual plane by comparing preoperative and postoperative CT. Compared with intraoperatively measured weight (W), errors in percentage (%) VP and VR were evaluated. Plane-dependent error in VP was defined as the absolute difference between VP and VR. % plane-dependent error was defined as follows: |VP–VR|/W∙100. RESULTS: Mean VP, VR, and W were 761.9 mL, 755.0 mL, and 696.9 g. Mean and % errors in VP were 73.3 mL and 10.7%. Mean error and % error in VR were 64.4 mL and 9.3%. Mean plane-dependent error in VP was 32.4 mL. Mean % plane-dependent error was 4.7%. Plane-dependent error in VP exceeded 10% of W in approximately 10% of the subjects in our study. CONCLUSIONS: There was approximately 5% plane-dependent error in liver VP on CT volumetry. Plane-dependent error in VP exceeded 10% of W in approximately 10% of LDLT donors in our study. This error should be considered, especially when CT volumetry is performed by a less experienced operator who is not well acquainted with the donor hepatectomy plane.
Cone-Beam Computed Tomography ; Hepatectomy ; Humans ; Liver Transplantation ; Liver* ; Living Donors ; Methods ; Organ Size ; Prospective Studies ; Retrospective Studies ; Tissue Donors* ; Transplants

Background: Sarcopenia is defined as the loss of skeletal muscle mass and is associated with negative clinical outcomes. This study aimed to establish sex-specific cutoff values for the skeletal muscle area (SMA) and skeletal muscle index (SMI) at the third lumbar vertebral (L3) level using computed tomography (CT) imaging to identify sarcopenia in healthy Korean liver donors. Methods: This retrospective study included 659 healthy liver donors (408 men and 251 women) aged 20 to 60 years who had undergone abdominal CT examinations between January 2017 and December 2018. Assessment of body composition was performed with an automated segmentation technique using a deep-learning system. Sex-specific SMA and SMI distributions were assessed, and cutoff values for determining sarcopenia were defined as values at either two standard deviations (SDs) below the mean reference value or below the fifth percentile. Results: Using the SD definition, cutoff values for SMA and SMI were 117.04 cm2 and 39.33 cm2/m2, respectively, in men and 71.39 cm2 and 27.77 cm2/m2, respectively, in women. Using the fifth percentile definition, cutoff values for SMA and SMI were 126.88 cm2 and 40.96 cm2/m2, respectively, in men and 78.85 cm2 and 30.60 cm2/m2, respectively, in women. Conclusion Our data provide sex-specific cutoff values for the SMA and SMI at the L3 level measured by CT imaging in a healthy Korean population, which may be applicable for identifying sarcopenia in this population.

Background: Sarcopenia is defined as the loss of skeletal muscle mass and is associated with negative clinical outcomes. This study aimed to establish sex-specific cutoff values for the skeletal muscle area (SMA) and skeletal muscle index (SMI) at the third lumbar vertebral (L3) level using computed tomography (CT) imaging to identify sarcopenia in healthy Korean liver donors. Methods: This retrospective study included 659 healthy liver donors (408 men and 251 women) aged 20 to 60 years who had undergone abdominal CT examinations between January 2017 and December 2018. Assessment of body composition was performed with an automated segmentation technique using a deep-learning system. Sex-specific SMA and SMI distributions were assessed, and cutoff values for determining sarcopenia were defined as values at either two standard deviations (SDs) below the mean reference value or below the fifth percentile. Results: Using the SD definition, cutoff values for SMA and SMI were 117.04 cm2 and 39.33 cm2/m2, respectively, in men and 71.39 cm2 and 27.77 cm2/m2, respectively, in women. Using the fifth percentile definition, cutoff values for SMA and SMI were 126.88 cm2 and 40.96 cm2/m2, respectively, in men and 78.85 cm2 and 30.60 cm2/m2, respectively, in women. Conclusion Our data provide sex-specific cutoff values for the SMA and SMI at the L3 level measured by CT imaging in a healthy Korean population, which may be applicable for identifying sarcopenia in this population.

Gastric cancer remains a significant global health concern, coercing the need for advancements in imaging techniques for ensuring accurate diagnosis and effective treatment planning. Artificial intelligence (AI) has emerged as a potent tool for gastric-cancer imaging, particularly for diagnostic imaging and body morphometry. This review article offers a comprehensive overview of the recent developments and applications of AI in gastric cancer imaging. We investigated the role of AI imaging in gastric cancer diagnosis and staging, showcasing its potential to enhance the accuracy and efficiency of these crucial aspects of patient management. Additionally, we explored the application of AI body morphometry specifically for assessing the clinical impact of gastrectomy. This aspect of AI utilization holds significant promise for understanding postoperative changes and optimizing patient outcomes. Furthermore, we examine the current state of AI techniques for the prognosis of patients with gastric cancer. These prognostic models leverage AI algorithms to predict long-term survival outcomes and assist clinicians in making informed treatment decisions.However, the implementation of AI techniques for gastric cancer imaging has several limitations. As AI continues to evolve, we hope to witness the translation of cutting-edge technologies into routine clinical practice, ultimately improving patient care and outcomes in the fight against gastric cancer.

BACKGROUND/AIMS: Clinical validation is required to determine whether Doppler measurements are comparable before and after administering ultrasound contrast agent (USCA). The purpose of this study is to explore whether the use of USCA affects spectral Doppler analysis in recipients of liver transplantation (LT). METHODS: For this study, 36 patients were examined using Doppler ultrasonography (US) along with a contrast-enhanced US for surveillance of vascular complications after LT. The following spectral Doppler US parameters were measured before and after administration of USCA: peak systolic velocity, end-diastolic velocity, resistive index, and systolic acceleration time of the graft hepatic artery; peak flow velocity of the graft portal vein; and peak flow velocity and venous pulsatility index of the graft hepatic vein. RESULTS: The mean peak systolic and end-diastolic velocities of the hepatic artery and the peak flow velocity of the portal and hepatic veins were increased after intravenously administration of the USCA, ranging from 10% to 13%. However, the changes were not statistically significant (P=0.097, 0.103, 0.128, and 0.190, respectively). There were no significant differences in other measured parameters, including the resistive index (P=0.205) and systolic acceleration time (P=0.489) of the hepatic artery and venous pulsatility index (P=0.494) of the hepatic vein. CONCLUSIONS: The measured velocities of graft hepatic vessels tended to increase after administration of USCA, but without statistical significance. The comparison of serial Doppler parameters with or without injection of USCA is valid during Doppler surveillance in recipients of LT.
Acceleration ; Contrast Media* ; Doppler Effect ; Hepatic Artery ; Hepatic Veins ; Humans ; Liver Transplantation* ; Liver* ; Microbubbles ; Portal Vein ; Transplants ; Ultrasonography* ; Ultrasonography, Doppler

OBJECTIVE: To evaluate the usefulness of an automated system for quantification and discrimination of usual interstitial pneumonia (UIP) and nonspecific interstitial pneumonia (NSIP). MATERIALS AND METHODS: An automated system to quantify six regional high-resolution CT (HRCT) patterns: normal, NL; ground-glass opacity, GGO; reticular opacity, RO; honeycombing, HC; emphysema, EMPH; and consolidation, CONS, was developed using texture and shape features. Fifty-four patients with pathologically proven UIP (n = 26) and pathologically proven NSIP (n = 28) were included as part of this study. Inter-observer agreement in measuring the extent of each HRCT pattern between the system and two thoracic radiologists were assessed in 26 randomly selected subsets using an interclass correlation coefficient (ICC). A linear regression analysis was used to assess the contribution of each disease pattern to the pulmonary function test parameters. The discriminating capacity of the system between UIP and NSIP was evaluated using a binomial logistic regression. RESULTS: The overall ICC showed acceptable agreement among the system and the two radiologists (r = 0.895 for the abnormal lung volume fraction, 0.706 for the fibrosis fraction, 0.895 for NL, 0.625 for GGO, 0.626 for RO, 0.893 for HC, 0.800 for EMPH, and 0.430 for CONS). The volumes of NL, GGO, RO, and EMPH contribute to forced expiratory volume during one second (FEV1) (r = 0.72, beta values, 0.84, 0.34, 0.34 and 0.24, respectively) and forced vital capacity (FVC) (r = 0.76, beta values, 0.82, 0.28, 0.21 and 0.34, respectively). For diffusing capacity (DLco), the volumes of NL and HC were independent contributors in opposite directions (r = 0.65, beta values, 0.64, -0.21, respectively). The automated system can help discriminate between UIP and NSIP with an accuracy of 82%. CONCLUSION: The automated quantification system of regional HRCT patterns can be useful in the assessment of disease severity and may provide reliable agreement with the radiologists' results. In addition, this system may be useful in differentiating between UIP and NSIP.
Female ; Humans ; Idiopathic Pulmonary Fibrosis/pathology/radiography ; Logistic Models ; Lung Diseases, Interstitial/pathology/*radiography ; Male ; Middle Aged ; Pattern Recognition, Automated/*methods ; Respiratory Function Tests ; Severity of Illness Index ; *Tomography, X-Ray Computed

Objective: Muscle quantity and quality can be measured with an automated system on CT. However, the effects of contrast phases on the muscle measurements have not been established, which we aimed to investigate in this study. Materials and Methods: Muscle quantity was measured according to the skeletal muscle area (SMA) measured by a convolutional neural network-based automated system at the L3 level in 89 subjects undergoing multiphasic abdominal CT comprising unenhanced phase, arterial phase, portal venous phase (PVP), or delayed phase imaging. Muscle quality was analyzed using the mean muscle density and the muscle quality map, which comprises normal and low-attenuation muscle areas (NAMA and LAMA, respectively) based on the muscle attenuation threshold. The SMA, mean muscle density, NAMA, and LAMA were compared between PVP and other phases using paired t tests. Bland-Altman analysis was used to evaluate the inter-phase variability between PVP and other phases. Based on the cutoffs for low muscle quantity and quality, the counts of individuals who scored lower than the cutoff values were compared between PVP and other phases. Results: All indices showed significant differences between PVP and other phases (p < 0.001 for all). The SMA, mean muscle density, and NAMA increased during the later phases, whereas LAMA decreased during the later phases. Bland-Altman analysis showed that the mean differences between PVP and other phases ranged -2.1 to 0.3 cm2 for SMA, -12.0 to 2.6 cm2 for NAMA, and -2.2 to 9.9 cm2 for LAMA.The number of patients who were categorized as low muscle quantity did not significant differ between PVP and other phases (p ≥ 0.5), whereas the number of patients with low muscle quality significantly differed (p ≤ 0.002). Conclusion SMA was less affected by the contrast phases. However, the muscle quality measurements changed with the contrast phases to greater extents and would require a standardization of the contrast phase for reliable measurement.

Objective: The clinical relevance of myosteatosis has not been well evaluated in patients with pancreatic ductal adenocarcinoma (PDAC), although sarcopenia has been extensively researched. Therefore, we evaluated the prognostic value of muscle quality, including myosteatosis, in patients with resectable PDAC treated surgically. Materials and Methods: We retrospectively evaluated 347 patients with resectable PDAC who underwent curative surgery (mean age ± standard deviation, 63.6 ± 9.6 years; 202 male). Automatic muscle segmentation was performed on preoperative computed tomography (CT) images using an artificial intelligence program. A single axial image of the portal phase at the inferior endplate level of the L3 vertebra was used for analysis in each patient. Sarcopenia was evaluated using the skeletal muscle index, calculated as the skeletal muscle area (SMA) divided by the height squared. The mean SMA attenuation was used to evaluate myosteatosis. Diagnostic cutoff values for sarcopenia and myosteatosis were devised using the Contal and O’Quigley methods, and patients were classified according to normal (nMT), sarcopenic (sMT), myosteatotic (mMT), or combined (cMT) muscle quality types. Multivariable Cox regression analyses were conducted to assess the effects of muscle type on the overall survival (OS) and recurrence-free survival (RFS) after surgery. Results: Eighty-four (24.2%), 73 (21.0%), 75 (21.6%), and 115 (33.1%) patients were classified as having nMT, sMT, mMT, and cMT, respectively. Compared to nMT, mMT and cMT were significantly associated with poorer OS, with hazard ratios (HRs) of 1.49 (95% confidence interval, 1.00–2.22) and 1.68 (1.16–2.43), respectively, while sMT was not (HR of 1.40 [0.94–2.10]). Only mMT was significantly associated with poorer RFS, with an HR of 1.59 (1.07–2.35), while sMT and cMT were not. Conclusion Myosteatosis was associated with poor OS and RFS in patients with resectable PDAC who underwent curative surgery.