IgG4-related aortitis mimicking acute aortic and coronary syndromes, multimodality imaging–pathology correlation: a case report - Takeaways - MDSpire

IgG4-related aortitis mimicking acute aortic and coronary syndromes, multimodality imaging–pathology correlation: a case report

  • By

  • Laura Victoria Torres-Araujo

  • Valente Fernandez-Badillo

  • Antonio Jordan-Rios

  • Rodrigo Gopar-Nieto

  • Silvia Jimenez-Becerra

  • Jesus A. Cotes-Millan

  • Daniel Sierra Lara-Martinez

  • Benjamin I. Hernandez-Mejia

  • Moises Jimenez-Santos

  • Sergio A. Criales-Vera

  • June 4, 2026

  • 0 min

Share

  • 1

    IgG4-related aortitis can mimic acute aortic and coronary syndromes, complicating diagnosis in patients with chest pain.

  • 2

    A 64-year-old man with prior NSTEMI presented with severe chest pain and was diagnosed with high-risk NSTEMI.

  • 3

    Imaging revealed a large pericardial effusion and crescentic ascending aortic wall thickening, suggesting intramural hematoma.

  • 4

    Despite surgical intervention, the patient died intraoperatively, with histopathology confirming IgG4-related aortitis.

  • 5

    Current diagnostic algorithms often overlook inflammatory aortitides like IgG4-RD, leading to misclassification and delayed diagnosis.

Original Source(s)

IgG4-related aortitis mimicking acute aortic and coronary syndromes, multimodality imaging–pathology correlation: a case report

  • by Laura Victoria Torres-Araujo, Valente Fernandez-Badillo, Antonio Jordan-Rios, Rodrigo Gopar-Nieto, Silvia Jimenez-Becerra, Jesus A. Cotes-Millan, Daniel Sierra Lara-Martinez, Benjamin I. Hernandez-Mejia, Moises Jimenez-Santos, Sergio A. Criales-Vera

  • June 4, 2026

Related Content

Development and validation of a predictive model for postoperative delirium in patients undergoing cardiac surgery

The correlation between the atherogenic index of plasma and aortic valve calcification in the general population: a retrospective observational cohort study

Development and validation of a clinical prediction model for postoperative atrial fibrillation after lung cancer surgery: a machine-learning–based study