Purpose Unilateral axillary lymphadenopathy is known to occur after coronavirus disease (COVID-19) vaccination. Post-vaccination lymphadenopathy may mimic the metastatic lymph nodes in breast cancer, and it is challenging to distinguish between them. This study investigated whether the localization of axillary lymphadenopathy on magnetic resonance imaging (MRI) could be used to distinguish reactive lymphadenopathy after COVID-19 vaccines from metastatic nodes. Materials and methods We retrospectively examined preoperative MRI images of 684 axillae in 342 patients who underwent breast cancer surgery from June to October 2021. Lymphadenopathy was defined as cortical thickening or short axis ≥ 5 mm. The axilla was divided into ventral and dorsal parts on the axial plane using a perpendicular line extending from the most anterior margin of the muscle group, including the deltoid, latissimus dorsi, or teres major muscles, relative to a line along the lateral chest wall. We recorded the presence or absence of axillary lymphadenopathy in each area and the number of visible lymph nodes. Results Of 80 axillae, 41 and 39 were included in the vaccine and metastasis groups, respectively. The median time from the last vaccination to MRI was 19 days in the vaccine group. The number of visible axillary lymph nodes was significantly higher in the vaccine group (median, 15 nodes) than in the metastasis group (7 nodes) (P < 0.001). Dorsal lymphadenopathy was observed in 16 (39.0%) and two (5.1%) axillae in the vaccine and metastasis groups, respectively (P < 0.001). If the presence of both ventral and dorsal lymphadenopathy is considered indicative of vaccine-induced reaction, this finding has a sensitivity of 34.1%, specificity of 97.4%, and positive and negative predictive values of 93.3％ and 58.5%, respectively. Conclusion The presence of deep axillary lymphadenopathy may be an important factor for distinguishing post-vaccination lymphadenopathy from metastasis. The number of axillary lymph nodes may also help.

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Background: Segmental arterial mediolysis (SAM) is a rare, nonatherosclerotic, noninflammatory arteriopathy of unknown etiology, rarely involving omental artery (OA). No case reports have described left OA bleeding successfully treated with transarterial embolization (TAE) with coils. This report describes two cases of SAM-affected left OA bleeding successfully embolized using isolation technique with coils, recognizing the potential for the greater omentum to have arterial collateral network between OAs. Case presentation: Case 1. A 55-year-old male with no significant past medical history presented with an acute abdomen. Contrast-enhanced computed tomography (CT) revealed possible hemorrhagic ascites involving the left portion of the greater omentum and dilated, stenotic change of the left OA with a possible hematoma. SAM-associated left OA bleeding was suspected. Given its acute-angled branching from a splenic artery or branch and long, tortuous catheter-trajectory, we used a triaxial catheter system. Left OA angiography revealed the proximal dilated, stenotic change and a distal pseudoaneurysm. Isolation was successfully performed with coils. Because he had no abdominal pain or progressive anemia, he was discharged on hospital day 5. Neither recurrence nor new SAM-associated findings were observed during two-years of follow-up. Case 2. A 60-year-old-man with no significant past medical history presented with an acute abdomen. CT revealed similar finding as Case 1. SAM-associated left OA bleeding was suspected. Left OA angiography revealed proximal dilated, stenotic change with distal occlusion. Despite having no signs of active bleeding, review of the CT and angiography findings suggested the left OA as the bleeding site. Given proximal embolization at this point could lead to incomplete hemostasis or rebleeding via the arterial collateral network between OAs, an attempt was made to navigate the microcatheter into the distal side beyond the occlusion. Distal left OA angiography confirmed that the distal OA over the occlusion was intact and directly communicated with a right OA arising from right gastroepiploic artery. The SAMassociated lesion was successfully isolated with coils. Because he had no abdominal pain or progressive anemia, he was transported to another hospital on hospital day 3. Neither recurrence nor new SAM-associated findings were observed during two-years follow-up.

To develop a deep learning (DL)-based algorithm to predict the presence of stromal invasion of breast cancer on digital breast tomosynthesis (DBT). Materials and Methods:The institutional review board approved this retrospective study and waived the requisite to obtain the informed consent from the patients. Initially, 499 patients (mean age of 50.5 years, ranging from 29 to 90 years) who were referred to our hospital suggestive of breast cancer and performed DBT between March 1, 2019 and August 31, 2019, were enrolled in this study. Out of the 499 patients, 140 patients who were performed surgery with diagnosed breast cancer were nally selected. Based on the pathological reports, 140 patients were divided to be categorized as 20 patients with non-invasive cancer and 120 patients with invasive cancer. Xception architecture was used for the DL model to differentiate non-invasive cancer and invasive cancer. Diagnostic performance of the DL model was assessed by accuracy, sensitivity, speci city, and areas under the receiver operating characteristic curve (AUC). Results:The average accuracy, sensitivity, speci city, and AUC were 0.897, 0.909, 0.758, and 0.749, respectively. Conclusion:The proposed DL model trained on DBT images is useful to predict the presence of stromal invasion of breast cancer.