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Congress: ECR25
Poster Number: C-11998
Type: Poster: EPOS Radiologist (educational)
Authorblock: P. Cifrian Casuso, A. Guitián Pinilla, Á. Sánchez Mulas, C. A. López López, D. Castanedo Vázquez, A. Somoano, S. Revuelta Gómez, A. Sánchez-Gabin, M. Arroyo Olmedo; Santander/ES
Disclosures:
Pilar Cifrian Casuso: Nothing to disclose
Angela Guitián Pinilla: Nothing to disclose
Álvaro Sánchez Mulas: Nothing to disclose
César Antonio López López: Nothing to disclose
David Castanedo Vázquez: Nothing to disclose
Alejandra Somoano: Nothing to disclose
Silvia Revuelta Gómez: Nothing to disclose
Aranzanzu Sánchez-Gabin: Nothing to disclose
Marina Arroyo Olmedo: Nothing to disclose
Keywords: Anatomy, Neuroradiology brain, Vascular, CT, CT-Angiography, MR, Education, Embolism / Thrombosis, Haemorrhage, Ischaemia / Infarction
Learning objectives To explore how Artificial Intelligence (AI) can revolutionize the early detection of cerebral venous thrombosis (CVT). To identify the benefits and limitations of using AI algorithms in medical image interpretation. To describe the key signs AI must detect, the common pitfalls it must identify, and critical radiological scenarios that should alert AI systems. To present clinical cases where AI was pivotal in early identification of CVT.
Read more Background Cerebral venous thrombosis (CVT), though rare, predominantly affects young individuals between 20 and 40 years of age. Despite its low prevalence, the condition can lead to fatal outcomes if left undiagnosed. However, with timely and accurate identification, CVT can be treated effectively using straightforward therapies such as anticoagulation, drastically improving patient prognosis. The importance of diagnosing CVT lies not only in its life-saving potential but also in the unique opportunity to intervene early and prevent severe complications. [fig 2] At the same time,...
Read more Findings and procedure details A. Key Radiological Signs IA must detect1. Dural Sinus ThrombosisDural sinus thrombosis is the most common form of CVT, involving the dural venous sinuses that drain blood from the brain to the internal jugular veins. Direct Signs: Cord Sign: Hyperattenuating thrombosed vein or sinus on non-contrast CT, representing acute thrombus. Empty Delta Sign: Hypoattenuating thrombus surrounded by enhancing dural sinuses on contrast-enhanced CT. Parenchymal Findings: Vasogenic edema or venous infarcts in the regions drained by the affected sinuses, such as the frontal or parietal lobes...
Read more Conclusion Artificial Intelligence (AI) has the potential to revolutionize the diagnosis and management of cerebral venous thrombosis (CVT), a condition that presents unique challenges due to its subtle and varied imaging findings. By focusing on essential radiological features, AI can detect key signs such as the “cord sign” or “empty delta sign”, recognize ischemic infarcts or hemorrhages in non-arterial distributions, and identify atypical hemorrhages in veins like Labbé’s or Trolard’s. Additionally, AI’s ability to consider bilateral thalamic edema, a hallmark of...
Read more References Ulivi L, Squitieri M, Cohen H, Cowley P, Werring DJ. Cerebral venous thrombosis: a practical guide. Pract Neurol.2020;20(5):356-367. Ferro JM, Canhão P, Stam J, Bousser MG, Barinagarrementeria F. Prognosis of cerebral vein and dural sinus thrombosis: results of the International Study on Cerebral Vein and Dural Sinus Thrombosis (ISCVT). Stroke.2004;35(3):664-670. Trivedi RF, Raju PK, Kanamalla US. Imaging of cerebral venous thrombosis. J Clin Imaging Sci. 2012;2:32. Saposnik G, Barinagarrementeria F, Brown RD, et al. Diagnosis and management of cerebral venous thrombosis: a statement for healthcare professionals from the American Heart Association/American...
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