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From the Viewbox and Department of Radiology UMass Medical School에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 From the Viewbox and Department of Radiology UMass Medical School 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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Episode 29: Imaging of Ovarian Masses

24:11
 
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Manage episode 288473452 series 2895175
From the Viewbox and Department of Radiology UMass Medical School에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 From the Viewbox and Department of Radiology UMass Medical School 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
Classifying and categorizing ovarian masses can feel like a daunting task for radiology trainees. In this episode Dr. Alan Goldstein will discuss with us his approach to these lesions to help simplify the process. First, a few mimics and pitfalls will be presented. Then Dr. Goldstein will break down the three basic types of ovarian tumors with an emphasis on imaging features: 1. First, make sure the mass is truly ovarian in origin (A) Appendiceal mucocele, peritoneal inclusion cyst, hydrosalpinx, subserosal fibroid, endometrioma, metastasis 2. Then break it down (A) Epithelial tumors (cystic with solid components) - Benign - Borderline - Malignant (B) Sex cord stromal tumors (solid with cystic components) - Fibroma - Other stuff (C) Germ cells tumors (bizarre masses in young patients) - Dermoid cyst - Other stuff Hosts: Christopher Cerniglia, DO, ME, FAOCR. Associate Professor of Radiology, Division of Musculoskeletal Imaging & Intervention, UMMS Dept of Radiology. Hao Lo, MD, MBA. Associate Professor of Radiology, Division of Emergency Radiology, UMMS Dept of Radiology. Guest: Alan Goldstein, MD. Assistant Professor of Radiology & Division Chief of Abdominal Imaging, UMMS Dept of Radiology. Resources: ACR Ovarian-Adnexal Reporting and Data System (O-RADS). Multiple links at: https://www.acr.org/Clinical-Resources/Reporting-and-Data-Systems/O-Rads Foti P, Attina G, Spadola S, et al. MR imaging of ovarian masses: classification and differential diagnosis. Insights Imaging. 2016 Feb; 7(1): 21-41. More advanced: Halankar J, Lo G, and Metser U. MRI classification and characterization of complex ovarian masses. Applied Radiology. https://www.appliedradiology.com/articles/mri-classification-and-characterization-of-complex-ovarian-masses
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31 에피소드

Artwork
icon공유
 
Manage episode 288473452 series 2895175
From the Viewbox and Department of Radiology UMass Medical School에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 From the Viewbox and Department of Radiology UMass Medical School 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
Classifying and categorizing ovarian masses can feel like a daunting task for radiology trainees. In this episode Dr. Alan Goldstein will discuss with us his approach to these lesions to help simplify the process. First, a few mimics and pitfalls will be presented. Then Dr. Goldstein will break down the three basic types of ovarian tumors with an emphasis on imaging features: 1. First, make sure the mass is truly ovarian in origin (A) Appendiceal mucocele, peritoneal inclusion cyst, hydrosalpinx, subserosal fibroid, endometrioma, metastasis 2. Then break it down (A) Epithelial tumors (cystic with solid components) - Benign - Borderline - Malignant (B) Sex cord stromal tumors (solid with cystic components) - Fibroma - Other stuff (C) Germ cells tumors (bizarre masses in young patients) - Dermoid cyst - Other stuff Hosts: Christopher Cerniglia, DO, ME, FAOCR. Associate Professor of Radiology, Division of Musculoskeletal Imaging & Intervention, UMMS Dept of Radiology. Hao Lo, MD, MBA. Associate Professor of Radiology, Division of Emergency Radiology, UMMS Dept of Radiology. Guest: Alan Goldstein, MD. Assistant Professor of Radiology & Division Chief of Abdominal Imaging, UMMS Dept of Radiology. Resources: ACR Ovarian-Adnexal Reporting and Data System (O-RADS). Multiple links at: https://www.acr.org/Clinical-Resources/Reporting-and-Data-Systems/O-Rads Foti P, Attina G, Spadola S, et al. MR imaging of ovarian masses: classification and differential diagnosis. Insights Imaging. 2016 Feb; 7(1): 21-41. More advanced: Halankar J, Lo G, and Metser U. MRI classification and characterization of complex ovarian masses. Applied Radiology. https://www.appliedradiology.com/articles/mri-classification-and-characterization-of-complex-ovarian-masses
  continue reading

31 에피소드

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