Search

Introduction: Contrast‐enhanced computed tomography (CECT) is an emergent diagnostic imaging modality to identify the bleeding site and survey the abdominal cavity. The diagnostic utility of CECT for ectopic pregnancy (EP) has not been well‐investigated. The objective of this study was to evaluate the characteristics of CECT findings in patients with EP and extract specific findings that could contribute to the identification of implantation sites. Method: We conducted a retrospective study, reviewing suspected EP cases between April 2015 and March 2018 in our hospital. Clinical symptoms, blood test results, transvaginal sonography findings, and surgical and pathologic findings from the medical records were assessed. CECT images were evaluated by a certified radiologist and gynecologist retrospectively in consensus. The following were selected as positive findings for specific determination of the ectopic implantation site: the ectopic gestational sac, lateralization of the hemoperitoneum around the adnexa on either side, and extravascular leakage of the contrast agent outside the uterine cavity. Results: CECT was performed in 41 women with an EP. The ectopic implantation site was detectable on CECT in 90.2% (37/41), whereas it was noted in 70.0% (32/41) on transvaginal ultrasonography (TVS). Of nine patients with an EP with an undetectable implantation site on TVS, six were positive for the specific determination of the ectopic implantation site on CECT. Conclusion: CECT has the potential to predict ectopic implantation sites with high‐level sensitivity. As CECT is an urgent diagnostic imaging tool to be used in an emergent setting, it may be a good option for EP diagnosis when the availability of magnetic resonance imaging is limited. Synopsis: Contrast‐enhanced computed tomography has the potential to predict ectopic implantation sites and is a useful imaging tool in emergency situations. [ABSTRACT FROM AUTHOR]

This study aimed to compare tumor lesion detectability and diagnostic accuracy of whole-body magnetic resonance imaging (WB-MRI) and radioiodine-labeled meta-iodo-benzylguanidine (mIBG) imaging techniques in patients with metastatic pheochromocytoma and paraganglioma (PPGL). This retrospective study included 13 patients had pheochromocytoma and 5 had paraganglioma, who were all suspected of having metastatic tumors. Each patient underwent WB-MRI and 123I-mIBG as a pretreatment screening for 131I-mIBG therapy. Two expert reviewers evaluated WB-MRI, 123I-mIBG images, and post-therapy 131I-mIBG images for the presence of metastatic lesions in the lungs, bones, liver, lymph nodes, and other organs. Diagnostic measures for detecting metastatic lesions, including sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and receiver operating characteristics (ROC)—area under the curve (AUC), were calculated for each imaging technique. We analyzed WB-MRI images for detecting metastatic lesions, which demonstrated sensitivity, specificity, accuracy, PPV, NPV, and AUC of 82%, 97%, 90%, 96%, 86%, and 0.92, respectively. These values were 83%, 95%, 89%, 94%, 86%, and 0.90 in 123I-mIBG images and 85%, 92%, 89%, 91%, 87%, and 0.91 in post-therapy 131I-mIBG images, respectively. Our results reveal the comparable diagnostic accuracy of WB-MRI to one of the mIBG images. [ABSTRACT FROM AUTHOR]

Although magnetic resonance imaging (MRI) data of patients with multiple myeloma (MM) are used to predict prognosis, few reports have applied artificial intelligence (AI) techniques for this purpose. We aimed to analyze whole-body diffusion-weighted MRI data using three-dimensional (3D) convolutional neural networks (CNNs) and Gradient-weighted Class Activation Mapping (Grad-CAM), an explainable AI, to predict prognosis and explore the factors involved in prediction. We retrospectively analyzed the MRI data of a total of 142 patients with MM obtained from two medical centers. We defined the occurrence of progressive disease after MRI evaluation within 12 months as a poor prognosis and constructed a 3D CNN-based deep learning model to predict prognosis. Images from 111 cases were used as the training and internal validation data; images from 31 cases were used as the external validation data. Internal validation of the AI model with stratified 5-fold cross-validation resulted in a significant difference in progression-free survival (PFS) between good and poor prognostic cases (2-year PFS, 91.2% versus [vs.] 61.1%, P = 0.0002). The AI model clearly stratified good and poor prognostic cases in the external validation cohort (2-year PFS, 92.9% vs. 55.6%, P = 0.004), with an area under the receiver operating characteristic curve of 0.804. According to Grad-CAM, the MRI signals of the spleen and bones of the vertebrae and pelvis contributed to prognosis prediction. This study is the first to show that image analysis of whole-body MRI using a 3D CNN without any other clinical data is effective in predicting the prognosis of patients with MM. [ABSTRACT FROM AUTHOR]

This study aimed to compare tumor lesion detectability and diagnostic accuracy of whole-body magnetic resonance imaging (WB-MRI) and radioiodine-labeled meta-iodo-benzylguanidine (mIBG) imaging techniques in patients with metastatic pheochromocytoma and paraganglioma (PPGL). This retrospective study included 13 patients had pheochromocytoma and 5 had paraganglioma, who were all suspected of having metastatic tumors. Each patient underwent WB-MRI and 123 I-mIBG as a pretreatment screening for 131 I-mIBG therapy. Two expert reviewers evaluated WB-MRI, 123 I-mIBG images, and post-therapy 131 I-mIBG images for the presence of metastatic lesions in the lungs, bones, liver, lymph nodes, and other organs. Diagnostic measures for detecting metastatic lesions, including sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and receiver operating characteristics (ROC)-area under the curve (AUC), were calculated for each imaging technique. We analyzed WB-MRI images for detecting metastatic lesions, which demonstrated sensitivity, specificity, accuracy, PPV, NPV, and AUC of 82%, 97%, 90%, 96%, 86%, and 0.92, respectively. These values were 83%, 95%, 89%, 94%, 86%, and 0.90 in 123 I-mIBG images and 85%, 92%, 89%, 91%, 87%, and 0.91 in post-therapy 131 I-mIBG images, respectively. Our results reveal the comparable diagnostic accuracy of WB-MRI to one of the mIBG images., (© 2024. The Author(s).)

Purpose of the Report: To elucidate the PET/CT findings of pegfilgrastim-induced aortitis (PFIA) and compare them with those of other large-vessel vasculitis., Methods: We enrolled 45 patients diagnosed with the following: PFIA, n = 8; Takayasu arteritis (TA), n = 12; giant cell arteritis (GCA), n = 6; and immunoglobulin G4-related aortitis (IgG4-A), n = 19. Records of PET/CT performed before treatment initiation were collected. The aorta and its branches were divided into 16 anatomic regions. Presence of abnormal 18 F-FDG uptake in each region was determined and measured., Results: The 18 F-FDG-positive areas of PFIA were distributed in the regions of the ascending aorta to the suprarenal abdominal aorta, cervical branches of the aorta, and external iliac arteries, similar to those of TA. However, TA had a higher proportion of 18 F-FDG-positive areas than PFIA in almost all anatomic regions. These areas of GCA were widespread throughout the entire aorta and the upper and lower limbs, whereas those of IgG4-A were observed from the abdominal aorta to iliac arteries. SUV max , SUV peak , metabolic volume, and total lesion glycolysis were higher in GCA than in PFIA, TA, and IgG4-A., Conclusions: Pegfilgrastim-induced aortitis distribution on PET/CT was frequently observed in the aorta, cervical branches, and extra iliac arteries. The low proportion of 18 F-FDG-positive areas in PFIA was different from that of TA, GCA, and IgG4-A. These findings may help identify and differentiate various aortitis types in clinical practice., Competing Interests: Conflicts of interest and sources of funding: none declared., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Purpose: To evaluate the feasibility of renal artery-based segmentation of kidneys with renal cell carcinoma (RCC), based on three-dimensional (3D) software for the simulation of segmental artery clamping (SAC), and to correlate it with RENAL nephrometry score., Methods: Fifty RCCs (< 4 cm) identified from a pathological database search between January 2015 and January 2018 were included retrospectively. On computed tomography (CT) images, the relevant kidney, tumor, and renal artery were annotated semi-automatically on the commercial workstation, and renal artery-based segmentation was performed using 3D Voronoi diagrams. Simulation of SAC was performed by a radiologist and urologist in consensus. The volume of the whole kidney and tumor and estimated rescued volume for possible SAC cases were calculated. The correlation between possible SAC and RENAL nephrometry score was investigated. The reproducibility of the calculation of each volume and the interrater reliability of SAC simulation were assessed., Results: In the anatomical analysis, 44 patients had a single main renal artery and six had two main renal arteries, and of these, an early division pattern was observed in 11 cases. In the 3D simulation software, 22 out of 50 cases (44 %) were determined as possible SAC. The agreement of the SAC simulation was excellent (kappa = 0.96). RENAL nephrometry score was significantly different in the anterior/posterior and exophytic/endophytic components between possible and impossible SAC groups., Conclusions: Renal artery-based segmentation of kidneys with RCC on CT images using 3D simulation software is feasible for effectively estimating the possibility of SAC with high reproducibility., Competing Interests: All authors declares that they have no conflict of interest in publication of the article., (© 2022 The Authors.)

Objectives: To clarify the ultrasonographic features of immunoglobulin G4 (IgG4)-related dacryoadenitis and sialadenitis (IgG4-DS) and their usefulness in clinical diagnostic sessions., Methods: By re-evaluating 96 consecutive patients with IgG4-related disease, we identified 54 patients (male:female = 37:17; median age, 69.5 years) who underwent lacrimal or submandibular gland (LG or SG, respectively) ultrasonography and computed tomography (CT). Their clinical and ultrasonographic features were retrospectively analysed. Radio-pathological correlations were also examined in LG (23 cases) and SG lesions (20 cases). Additionally, the diagnostic accuracy of CT for LG/SG lesions was evaluated., Results: Abnormal ultrasonographic findings were detected in 33 (LGs) and 38 (SGs) patients, and most of them were observed bilaterally. All lesions were well demarcated and demonstrated diffuse low-echoic areas (rocky pattern) or multiple low-echoic nodules surrounded by high-echoic linear shadows (cobblestone pattern) corresponding to intra-lobular inflammation and inter-lobular fibrosis. Moreover, 42% (LGs; 14/33) and 42% (SGs; 16/38) patients had glandular lesions without clinical symptoms associated with the affected glands. The diagnostic accuracy of CT was ∼80% for LG and 55% for SG., Conclusions: Ultrasonographic findings in IgG4-DS included diffuse or nodular low-echoic areas with linear high-echoic structures corresponding to inflamed lobules and inter-lobular fibrosis. These findings can help detect IgG4-DS., (© Japan College of Rheumatology 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)