Unenhanced CT of abdominal and pelvic hemorrhage

1999 ◽  
Vol 20 (2) ◽  
pp. 94-107 ◽  
Author(s):  
Douglas S Katz ◽  
Michael J Lane ◽  
Robert E Mindelzun
Author(s):  
Kelvin Allenson ◽  
Laura Moore

Trauma related injury is the leading cause of non-obstetric maternal death.  The gravid uterus is at risk for injury, particularly during motor vehicle accidents.  Resuscitative endovascular balloon occlusion of the aorta (REBOA) is a means of controlling pelvic hemorrhage in the setting of trauma.  We report the use of REBOA in a hemodynamically unstable, multiply-injured young woman with viable intrauterine pregnancy.


1995 ◽  
Vol 165 (4) ◽  
pp. 1018-1018 ◽  
Author(s):  
H J Ro ◽  
H K Ha ◽  
H S Kim ◽  
K S Shinn

Medicina ◽  
2021 ◽  
Vol 57 (1) ◽  
pp. 63
Author(s):  
Sung Nam Moon ◽  
Jung-Soo Pyo ◽  
Wu Seong Kang

Background and objective: The early detection of underlying hemorrhage of pelvic trauma has been a critical issue. The aim of this study was to systematically determine the diagnostic accuracy of computed tomography (CT) for detecting severe pelvic hemorrhage. Materials and Methods: Relevant articles were obtained by searching PubMed, EMBASE, and Cochrane databases through 28 November 2020. Diagnostic test accuracy results were reviewed to obtain the sensitivity, specificity, diagnostic odds ratio, and summary receiver operating characteristic curve of CT for the diagnosis in pelvic trauma patients. The positive finding on CT was defined as the contrast extravasation. As the reference standard, severe pelvic hemorrhage was defined as an identification of bleeding at angiography or by direct inspection using laparotomy that required hemostasis by angioembolization or surgery. A subgroup analysis was performed according to the CT modality that is divided by the number of detector rows. Result: Thirteen eligible studies (29 subsets) were included in the present meta-analysis. Pooled sensitivity of CT was 0.786 [95% confidence interval (CI), 0.574–0.909], and pooled specificity was 0.944 (95% CI, 0.900–0.970). Pooled sensitivity of the 1–4 detector row group and 16–64 detector row group was 0.487 (95% CI, 0.215–0.767) and 0.915 (95% CI, 0.848–0.953), respectively. Pooled specificity of the 1–4 and 16–64 detector row groups was 0.956 (95% CI, 0.876–0.985) and 0.906 (95% CI, 0.828–0.951), respectively. Conclusion: Multi-detector CT with 16 or more detector rows has acceptable high sensitivity and specificity. Extravasation on CT indicates severe hemorrhage in patients with pelvic trauma.


2021 ◽  
Vol 67 ◽  
pp. 101812
Author(s):  
Christina M. Theodorou ◽  
Lauren E. Coleman ◽  
Stephanie N. Mateev ◽  
Jessica K. Signoff ◽  
Edgardo S. Salcedo

Author(s):  
Salvatore Gitto ◽  
Renato Cuocolo ◽  
Ilaria Emili ◽  
Laura Tofanelli ◽  
Vito Chianca ◽  
...  

AbstractThis study aims to investigate the influence of interobserver manual segmentation variability on the reproducibility of 2D and 3D unenhanced computed tomography (CT)- and magnetic resonance imaging (MRI)-based texture analysis. Thirty patients with cartilaginous bone tumors (10 enchondromas, 10 atypical cartilaginous tumors, 10 chondrosarcomas) were retrospectively included. Three radiologists independently performed manual contour-focused segmentation on unenhanced CT and T1-weighted and T2-weighted MRI by drawing both a 2D region of interest (ROI) on the slice showing the largest tumor area and a 3D ROI including the whole tumor volume. Additionally, a marginal erosion was applied to both 2D and 3D segmentations to evaluate the influence of segmentation margins. A total of 783 and 1132 features were extracted from original and filtered 2D and 3D images, respectively. Intraclass correlation coefficient ≥ 0.75 defined feature stability. In 2D vs. 3D contour-focused segmentation, the rates of stable features were 74.71% vs. 86.57% (p < 0.001), 77.14% vs. 80.04% (p = 0.142), and 95.66% vs. 94.97% (p = 0.554) for CT and T1-weighted and T2-weighted images, respectively. Margin shrinkage did not improve 2D (p = 0.343) and performed worse than 3D (p < 0.001) contour-focused segmentation in terms of feature stability. In 2D vs. 3D contour-focused segmentation, matching stable features derived from CT and MRI were 65.8% vs. 68.7% (p = 0.191), and those derived from T1-weighted and T2-weighted images were 76.0% vs. 78.2% (p = 0.285). 2D and 3D radiomic features of cartilaginous bone tumors extracted from unenhanced CT and MRI are reproducible, although some degree of interobserver segmentation variability highlights the need for reliability analysis in future studies.


2008 ◽  
Vol 190 (2) ◽  
pp. W125-W127 ◽  
Author(s):  
Alessandro Furlan ◽  
Michael P. Federle ◽  
Donald M. Yealy ◽  
Timothy D. Averch ◽  
Karen Pealer

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