Post Vaccination Inflammatory Changes (USA)

This case was a 46 year old lady. Who came to our institution due to swelling and inflammation in the left axilla? These are the mammograms. Very dense breasts with no suspicious lesions. However, in the axilla we detected some interstitial pattern. If we move to the terminal, we can see clearly an asymmetry in both oxylus because there is an edema and inflammation. And now if we focus on the left breast, we confirm. This pattern of inflammation, this is lymphangitis, and the patient reported a previous history of anti COVID-19 vaccination 3 days before them. The swelling. So this was edema and inflammation due to the vaccination.

Basic 2 Digital Breast Tomosynthesis and Contrast Enhanced Mammography Prof. Dr. Luis Pina Breast Imaging Department (Radiología mamaria) Clínica Universidad de Navarra, Pamplona / Spain SIEMENS 03_Basic_2, PID3633 * 1/1/2022 F PID3633 Series Navigator INSIGHT_2D PID3633 Add Study 1/1/2022 (Study date) Current MG, 1/1/2022 n.a ., 3 mont ... Combo RCC INSIGHT 2D_RMLO INSIGHT_2D_RCC Viewing Favorite Layouts US MR DYN MR.Dyna ... MR.Empty ReportFlow BASIC Printing Tools Findings MR 2:54 PM Clinical information 46-year-old female Swelling and inflammation in the left axilla Recent Anti-Covid-19 vaccination LCC RMLO Healthineers INSIGHT_2D_RMLO LMLO Current Current Slice 12/ 29 Slice 22 / 29 Slice 5 / 29 Slice 19 / 33 Slice thickness: 1.00 mm Selected ReportFlow Pathology Post vaccination inflammatory changes Conclusion OBT is able to verify the mammographic pattern as a benign interstitial lymphangitic edema. Siemens Healthcare GmbH, 2022 Sometimes IN2D images (= synthetic mammograms) are shown while verbally referring to the conventional mammograms. The products/features (mentioned herein) are not commercially available in all countries. Their future availability cannot be guaranteed. Results from case studies are not predictive of results in other cases. Results in other cases may vary. The statements by Siemens' customers described herein are based on results that were achieved in the customer's unique setting. Since there is no "typical" setting and many variables exist (e.g ., hospital size, samples mix, case mix, level of IT adoption) there can be no guarantee that other customers will achieve the same results. Dr. Luis Pina is employed by an institution that receives financial support from Siemens Healthineers for collaborations.