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1.
J Vasc Interv Radiol ; 34(12): 2128-2136, 2023 12.
Article in English | MEDLINE | ID: mdl-37652299

ABSTRACT

PURPOSE: To evaluate the effectiveness of track embolization using gelatin sponge slurry in percutaneous ultrasound (US)-guided liver biopsy. MATERIALS AND METHODS: Among the 543 patients who underwent percutaneous US-guided liver biopsies between September 2018 and August 2021, 338 who did not undergo track embolization and 105 who underwent track embolization were included in the analysis. All procedures were performed with 18-gauge coaxial core biopsy needles. Patients' laboratory data were reviewed. Patients in both groups were subdivided into the following 2 groups: (a) those with targeted biopsy for a focal liver lesion and (b) those with nontargeted biopsy for a liver parenchyma. Moreover, postbiopsy events, such as transfusion and transarterial embolization, were assessed. To minimize selection bias, propensity score matching (PSM) was performed. RESULTS: After PSM, all factors that could affect bleeding risk were well-matched and well-balanced between the 2 groups (P > .474). In the non-track embolization group, 17 (16.2%) patients experienced major or minor bleeding-related adverse events (AEs). In contrast, in the track embolization group, only 5 (4.8%) patients experienced major or minor bleeding-related AEs, which was significantly lower than that in the non-track embolization group (P = .007). All 5 (4.8%) cases of major bleeding-related AEs were observed in the non-track embolization group (P = .024). CONCLUSIONS: In this study, a retrospective analysis was performed using PSM for percutaneous US-guided liver biopsy. Track embolization using gelatin sponge slurry is significantly superior in the prevention of bleeding-related AEs after US-guided liver biopsy.


Subject(s)
Gelatin , Hemorrhage , Female , Humans , Gelatin/adverse effects , Retrospective Studies , Propensity Score , Hemorrhage/etiology , Hemorrhage/prevention & control , Liver/diagnostic imaging , Liver/pathology , Image-Guided Biopsy/adverse effects , Image-Guided Biopsy/methods
2.
Abdom Radiol (NY) ; 48(8): 2585-2595, 2023 08.
Article in English | MEDLINE | ID: mdl-37204510

ABSTRACT

PURPOSE: To evaluate the efficacy of low-dose CT (LDCT) with deep learning image reconstruction (DLIR) for the surveillance of pancreatic cystic lesions (PCLs) compared with standard-dose CT (SDCT) with adaptive statistical iterative reconstruction (ASIR-V). METHODS: The study enrolled 103 patients who underwent pancreatic CT for follow-up of incidentally detected PCLs. The CT protocol included LDCT in the pancreatic phase with 40% ASIR-V, DLIR at medium (DLIR-M) and high levels (DLIR-H), and SDCT in the portal-venous phase with 40% ASIR-V. The overall image quality and conspicuity of PCLs were qualitatively assessed using five-point scales by two radiologists. The size of PCLs, presence of thickened/enhancing walls, enhancing mural nodules, and main pancreatic duct dilatation were reviewed. CT noise and cyst-to-pancreas contrast-to-noise ratio (CNR) were measured. Qualitative and quantitative parameters were analyzed using the chi-squared test, one-way ANOVA, and t-test. Additionally, interobserver agreement was analyzed using the kappa and weighted-kappa statistics. RESULTS: The volume CT dose-indexes in LDCT and SDCT were 3.0 ± 0.6 mGy and 8.4 ± 2.9 mGy, respectively. LDCT with DLIR-H showed the highest overall image quality, the lowest noise, and the highest CNR. The PCL conspicuity in LDCT with either DLIR-M or DLIR-H was not significantly different from that in SDCT with ASIR-V. Other findings depicting PCLs also revealed no significant differences between LDCT with DLIR and SDCT with ASIR-V. Moreover, the results revealed good or excellent interobserver agreement. CONCLUSION: LDCT with DLIR has a comparable performance with SDCT for the follow-up of incidentally detected PCLs.


Subject(s)
Deep Learning , Pancreatic Cyst , Humans , Radiation Dosage , Tomography, X-Ray Computed/methods , Pancreas/diagnostic imaging , Image Processing, Computer-Assisted , Pancreatic Cyst/diagnostic imaging , Radiographic Image Interpretation, Computer-Assisted/methods , Algorithms
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