46 research outputs found

    Fibroblastic Type Osteosarcoma of the Ulna: a Case Report of a Tumor in a Rare Location with Atypical Imaging Findings

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    The ulna is a rare site of origin for osteosarcoma, and purely osteolytic osteosarcomas are uncommonly noted on conventional radiographs. We present a patient with a lytic lesion of the distal ulna for which imaging findings suggested an aneurysmal bone cyst. The lesion was histologically confirmed to be a fibroblastic osteosarcoma

    Prognostic role of computed tomography analysis using deep learning algorithm in patients with chronic hepatitis B viral infection

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    Background/Aims The prediction of clinical outcomes in patients with chronic hepatitis B (CHB) is paramount for effective management. This study aimed to evaluate the prognostic value of computed tomography (CT) analysis using deep learning algorithms in patients with CHB. Methods This retrospective study included 2,169 patients with CHB without hepatic decompensation who underwent contrast-enhanced abdominal CT for hepatocellular carcinoma (HCC) surveillance between January 2005 and June 2016. Liver and spleen volumes and body composition measurements including subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and skeletal muscle indices were acquired from CT images using deep learning-based fully automated organ segmentation algorithms. We assessed the significant predictors of HCC, hepatic decompensation, diabetes mellitus (DM), and overall survival (OS) using Cox proportional hazard analyses. Results During a median follow-up period of 103.0 months, HCC (n=134, 6.2%), hepatic decompensation (n=103, 4.7%), DM (n=432, 19.9%), and death (n=120, 5.5%) occurred. According to the multivariate analysis, standardized spleen volume significantly predicted HCC development (hazard ratio [HR]=1.01, P=0.025), along with age, sex, albumin and platelet count. Standardized spleen volume (HR=1.01, P<0.001) and VAT index (HR=0.98, P=0.004) were significantly associated with hepatic decompensation along with age and albumin. Furthermore, VAT index (HR=1.01, P=0.001) and standardized spleen volume (HR=1.01, P=0.001) were significant predictors for DM, along with sex, age, and albumin. SAT index (HR=0.99, P=0.004) was significantly associated with OS, along with age, albumin, and MELD. Conclusions Deep learning-based automatically measured spleen volume, VAT, and SAT indices may provide various prognostic information in patients with CHB

    Post-neoadjuvant treatment pancreatic cancer resectability and outcome prediction using CT, 18F-FDG PET/MRI and CA 19–9

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    Background CT prediction of resectability and prognosis following neoadjuvant treatment (NAT) in patients with pancreatic ductal adenocarcinoma (PDAC) remains challenging. This study aims to determine whether addition of 18F-fluorodeoxyglucose (FDG) postiron emission tomography (PET)/MRI and carbohydrate antigen (CA) 19–9 to contrast-enhanced CT (CECT) can improve accuracy of predicting resectability compared to CECT alone and predict prognosis in PDAC patients after NAT. Methods In this retrospective study, 120 PDAC patients (65 women; mean age, 66.7 years [standard deviation, 8.4]) underwent CECT, PET/MRI, and CA 19–9 examinations after NAT between January 2013 and June 2021. Three board-certified radiologists independently rated the overall resectability on a 5-point scale (score 5, definitely resectable) in three sessions (session 1, CECT; 2, CECT plus PET/MRI─no FDG avidity and no diffusion restriction at tumor-vessel contact indicated modification of CECT scores to ≥ 3; 3, CECT plus PET plus CA 19–9─no FDG avidity at tumor-vessel contact and normalized CA 19–9 indicated modification of CECT scores to ≥ 3). Jackknife free-response receiver operating characteristic method and generalized estimating equations were used to compare pooled area under the curve (AUC), sensitivity, and specificity of three sessions. Predictors for recurrence-free survival (RFS) were assessed using Cox regression analyses. Results Each session showed different pooled AUC (session 1 vs. 2 vs. 3, 0.853 vs. 0.873 vs. 0.874, p = 0.026), sensitivity (66.2% [137/207] vs. 86.0% [178/207] vs. 84.5% [175/207], p < 0.001) and specificity (67.3% [103/153] vs. 58.8% [90/153] vs. 60.1% [92/153], p = 0.048). According to pairwise comparison, specificity of CECT plus PET/MRI was lower than that of CECT alone (adjusted p = 0.042), while there was no significant difference in specificity between CECT alone and CECT plus PET plus CA 19–9 (adjusted p = 0.081). Twenty-eight of 69 patients (40.6%) with R0 resection experienced tumor recurrence (mean follow-up, 18.0 months). FDG avidity at tumor-vessel contact on post-NAT PET (HR = 4.37, p = 0.033) and pathologically confirmed vascular invasion (HR = 5.36, p = 0.004) predicted RFS. Conclusion Combination of CECT, PET and CA 19–9 increased area under the curve and sensitivity for determining resectability, compared to CECT alone, without compromising the specificity. Furthermore, 18F-FDG avidity at tumor-vessel contact on post-NAT PET predicted RFS

    Prediction of microvascular invasion of hepatocellular carcinoma: value of volumetric iodine quantification using preoperative dual-energy computed tomography

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    Abstract Background To investigate the potential value of volumetric iodine quantification using preoperative dual-energy computed tomography (DECT) for predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC). Methods This retrospective study included patients with single HCC treated through surgical resection who underwent preoperative DECT. Quantitative DECT features, including normalized iodine concentration (NIC) to the aorta and mixed-energy CT attenuation value in the arterial phase, were three-dimensionally measured for peritumoral and intratumoral regions: (i) layer-by-layer analysis for peritumoral layers (outer layers 1 and 2; numbered in close order from the tumor boundary) and intratumoral layers (inner layers 1 and 2) with 2-mm layer thickness and (ii) volume of interest (VOI)-based analysis with different volume coverage (tumor itself; VOIO1, tumor plus outer layer 1; VOIO2, tumor plus outer layers 1 and 2; VOII1, tumor minus inner layer 1; VOII2, tumor minus inner layers 1 and 2). In addition, qualitative CT features, including peritumoral enhancement and tumor margin, were assessed. Qualitative and quantitative CT features were compared between HCC patients with and without MVI. Diagnostic performance of DECT parameters of layers and VOIs was assessed using receiver operating characteristic curve analysis. Results A total of 36 patients (24 men, mean age 59.9 ± 8.5 years) with MVI (n = 14) and without MVI (n = 22) were included. HCCs with MVI showed significantly higher NICs of outer layer 1, outer layer 2, VOIO1, and VOIO2 than those without MVI (P = 0.01, 0.04, 0.02, 0.02, respectively). Among the NICs of layers and VOIs, the highest area under the curve was obtained in outer layer 1 (0.747). Qualitative features, including peritumoral enhancement and tumor margin, and the mean CT attenuation of each layer and each VOI were not significantly different between HCCs with and without MVI (both P > 0.05). Conclusions Volumetric iodine quantification of peritumoral and intratumoral regions in arterial phase using DECT may help predict the MVI of HCC

    Individual participant data meta-analysis of LR-5 in LI-RADS version 2018 versus revised LI-RADS for hepatocellular carcinoma diagnosis

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    Background A simplification of the Liver Imaging Reporting and Data System (LI-RADS) version 2018 (v2018), revised LI-RADS (rLI-RADS), has been proposed for imaging-based diagnosis of hepatocellular carcinoma (HCC). Single-site data suggest that rLI-RADS category 5 (rLR-5) improves sensitivity while maintaining positive predictive value (PPV) of the LI-RADS v2018 category 5 (LR-5), which indicates definite HCC. Purpose To compare the diagnostic performance of LI-RADS v2018 and rLI-RADS in a multicenter data set of patients at risk for HCC by performing an individual patient data meta-analysis. Materials and Methods Multiple databases were searched for studies published from January 2014 to January 2022 that evaluated the diagnostic performance of any version of LI-RADS at CT or MRI for diagnosing HCC. An individual patient data meta-analysis method was applied to observations from the identified studies. Quality Assessment of Diagnostic Accuracy Studies version 2 was applied to determine study risk of bias. Observations were categorized according to major features and either LI-RADS v2018 or rLI-RADS assignments. Diagnostic accuracies of category 5 for each system were calculated using generalized linear mixed models and compared using the likelihood ratio test for sensitivity and the Wald test for PPV. Results Twenty-four studies, including 3840 patients and 4727 observations, were analyzed. The median observation size was 19 mm (IQR, 11–30 mm). rLR-5 showed higher sensitivity compared with LR-5 (70.6% [95% CI: 60.7, 78.9] vs 61.3% [95% CI: 45.9, 74.7]; P < .001), with similar PPV (90.7% vs 92.3%; P = .55). In studies with low risk of bias (n = 4; 1031 observations), rLR-5 also achieved a higher sensitivity than LR-5 (72.3% [95% CI: 63.9, 80.1] vs 66.9% [95% CI: 58.2, 74.5]; P = .02), with similar PPV (83.1% vs 88.7%; P = .47). Conclusion rLR-5 achieved a higher sensitivity for identifying HCC than LR-5 while maintaining a comparable PPV at 90% or more, matching the results presented in the original rLI-RADS study

    CT/MRI and CEUS LI-RADS Major Features Association with Hepatocellular Carcinoma: Individual Patient Data Meta-Analysis

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    Background The Liver Imaging Reporting and Data System (LI-RADS) assigns a risk category for hepatocellular carcinoma (HCC) to imaging observations. Establishing the contributions of major features can inform the diagnostic algorithm. Purpose To perform a systematic review and individual patient data meta-analysis to establish the probability of HCC for each LI-RADS major feature using CT/MRI and contrast-enhanced US (CEUS) LI-RADS in patients at high risk for HCC. Materials and Methods Multiple databases (MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and Scopus) were searched for studies from January 2014 to September 2019 that evaluated the accuracy of CT, MRI, and CEUS for HCC detection using LI-RADS (CT/MRI LI-RADS, versions 2014, 2017, and 2018; CEUS LI-RADS, versions 2016 and 2017). Data were centralized. Clustering was addressed at the study and patient levels using mixed models. Adjusted odds ratios (ORs) with 95% CIs were determined for each major feature using multivariable stepwise logistic regression. Risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) (PROSPERO protocol: CRD42020164486). Results A total of 32 studies were included, with 1170 CT observations, 3341 MRI observations, and 853 CEUS observations. At multivariable analysis of CT/MRI LI-RADS, all major features were associated with HCC, except threshold growth (OR, 1.6; 95% CI: 0.7, 3.6; P = .07). Nonperipheral washout (OR, 13.2; 95% CI: 9.0, 19.2; P = .01) and nonrim arterial phase hyperenhancement (APHE) (OR, 10.3; 95% CI: 6.7, 15.6; P = .01) had stronger associations with HCC than enhancing capsule (OR, 2.4; 95% CI: 1.7, 3.5; P = .03). On CEUS images, APHE (OR, 7.3; 95% CI: 4.6, 11.5; P = .01), late and mild washout (OR, 4.1; 95% CI: 2.6, 6.6; P = .01), and size of at least 20 mm (OR, 1.6; 95% CI: 1.04, 2.5; P = .04) were associated with HCC. Twenty-five studies (78%) had high risk of bias due to reporting ambiguity or study design flaws. Conclusion Most Liver Imaging Reporting and Data System major features had different independent associations with hepatocellular carcinoma; for CT/MRI, arterial phase hyperenhancement and washout had the strongest associations, whereas threshold growth had no association. © RSNA, 2021 Online supplemental material is available for this article

    The role of intraoperative ultrasonography in the diagnosis and management of focal hepatic lesions

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    Intraoperative ultrasonography (IOUS) has been widely utilized in hepatic surgery both as a diagnostic technique and in the course of treatment. Since IOUS involves direct-contact imaging of the target organ, it can provide high spatial resolution without interference from the surrounding structures. Therefore, IOUS may improve the detection, characterization, localization, and local staging of hepatic tumors. IOUS is also a real-time imaging modality capable of providing interactive information and valuable guidance in a range of procedures. Recently, contrast-enhanced IOUS, IOUS elastography, and IOUS-guided hepatic surgery have attracted increasing interest and are expected to lead to the broader implementation of IOUS. Herein, we review the various applications of IOUS in the diagnosis and management of focal hepatic lesions

    A comparison of seminal vesicle size on CT between autosomal dominant polycystic kidney disease (ADPKD) patients and normal subjects

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    Background: Extrarenal manifestations are common in autosomal dominant polycystic kidney disease (ADPKD). Although seminal vesicles can also be involved in patients with ADPKD, little is known about the size differences of the seminal vesicles between ADPKD patients and normal subjects. Purpose: To determine whether the size of seminal vesicles in ADPKD patients is larger than that in normal subjects with the use of three-dimensional (3D) CT. Material and Methods: Using a retrospective case-control study design, we reviewed the findings of 696 male patients with an age range of 20-69 years who underwent contrast enhanced multi-detector computed tomography (MDCT) imaging of the kidney in our institution from August 2007 to July 2008. A total of 68 male patients with ADPKD comprised the study group. Another 68 age-matched non-ADPKD male patients comprised the control group. The size of bilateral seminal vesicles was assessed by measurement of the short dimension on axial, coronal, and sagittal images by the use of a picture archiving and communication system (PACS). Results: The mean width of seminal vesicles in ADPKD patients was 1.70 +/- 0.40 cm (axial images), 1.86 +/- 0.45 cm (coronal), and 1.59 +/- 0.39 cm (sagittal). For control group subjects, the mean width was 1.53 +/- 0.29 cm (axial), 1.68 +/- 0.43 cm (coronal), and 1.48 +/- 0.31 cm (sagittal). The mean size differences between the ADPKD and control groups for the measured widths on axial and coronal images were statistically significant (P = 0.01 and P = 0.02, respectively). The width as measured on axial images showed a decrease with age in the control group subjects (linear trend, P = 0.005), but no significant decrease was noted in ADPKD patients. Conclusion: The seminal vesicles were demonstrated to be larger in ADPKD patients as compared with normal subjects as determined with the use of 3D CT.Grantham JJ, 2008, NEW ENGL J MED, V359, P1477Vora N, 2008, AM J KIDNEY DIS, V51, P307, DOI 10.1053/j.ajkd.2007.09.010Arora SS, 2007, AM J ROENTGENOL, V189, P130, DOI 10.2214/AJR.06.1345TORRES VE, 2007, LANCET, V369, P287KIM SH, 2003, RADIOLOGY ILLUSTRATE, P174Belet U, 2002, UROLOGY, V60, P138Hayakawa T, 1998, TOHOKU J EXP MED, V186, P193HOEKSTRA TH, 1997, FERTIL STERIL, V68, pS35GABOW PA, 1993, NEW ENGL J MED, V329, P332ALPERN MB, 1991, RADIOLOGY, V180, P79SECAF E, 1991, AM J ROENTGENOL, V156, P989SILVERMAN PM, 1985, COMPUT RADIOL, V9, P379

    Newly developed sarcopenia after liver transplantation, determined by a fully automated 3D muscle volume estimation on abdominal CT, can predict post-transplant diabetes mellitus and poor survival outcomes

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    Abstract Background Loss of muscle mass is the most common complication of end-stage liver disease and negatively affects outcomes for liver transplantation (LT) recipients. We aimed to determine the prognostic value of a fully automated three-dimensional (3D) muscle volume estimation using deep learning algorithms on abdominal CT in patients who underwent liver transplantation (LT). Methods This retrospective study included 107 patients who underwent LT from 2014 to 2015. Serial CT scans, including pre-LT and 1- and 2-year follow-ups were performed. From the CT scans, deep learning-based automated body composition segmentation software was used to calculate muscle volumes in 3D. Sarcopenia was calculated by dividing average skeletal muscle area by height squared. Newly developed-(ND) sarcopenia was defined as the onset of sarcopenia 1 or 2 years after LT in patients without a history of sarcopenia before LT. Patients’ clinical characteristics, including post-transplant diabetes mellitus (PTDM) and Model for end-stage liver disease score, were compared according to the presence or absence of sarcopenia after LT. A subgroup analysis was performed in the post-LT sarcopenic group. The Kaplan–Meier method was used for overall survival (OS). Results Patients with ND-sarcopenia had poorer OS than those who did not (P = 0.04, hazard ratio [HR], 3.34; 95% confidence interval [CI] 1.05 – 10.7). In the subgroup analysis for post-LT sarcopenia (n = 94), 34 patients (36.2%) had ND-sarcopenia. Patients with ND-sarcopenia had significantly worse OS (P = 0.002, HR 7.12; 95% CI 2.00 – 25.32) and higher PTDM occurrence rates (P = 0.02, HR 4.93; 95% CI 1.18 – 20.54) than those with sarcopenia prior to LT. Conclusion ND-sarcopenia determined by muscle volume on abdominal CT can predict poor survival outcomes and the occurrence of PTDM for LT recipients
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