29F with headache • Xray of the Week
Figure 1. What is the important finding on this CT scan.
Figure 2. CT scan of cerebral arteriovenous malformation. Arterial venous malformation in the left posterior periventricular region with draining veins extending to the internal cerebral veins
A. Axial non contrast CT showing subtle density in left parietal lobe (red arrow).
B. Coronal CT with contrast showing AVM nidus (green arrow)
C. Coronal CT brain with contrast showing AVM nidus (yellow arrow).
D. Axial CT brain with contrast showing AVM nidus (red arrow).
E. Sagittal CT brain with contrast showing AVM draining vein (green arrow)
F. Sagittal CT brain with contrast showing AVM with draining vein (yellow arrow).
Cerebral arteriovenous malformations (AVMs) are abnormal fistulas between feeding arteries and draining veins without a capillary bed. They can cause intracranial hemorrhage due to the high flow that goes into veins. As other vascular malformations, they can be found incidentally or present with seizures and chronic headaches depending on size, location and vessel involvement (1, 2). AVMs can be associated with genetic conditions or be sporadic. The incidence ranges from 1.12-1.42 cases per 100,000 with about 37% of new cases presenting with a hemorrhage (5). The most well-known classification system for AVMs is the Spetzler-Martin grading scale (3).
Although digital subtraction angiography (DSA) is the gold standard in diagnosing cerebral AVMs, a non-contrast CT (NCCT) is usually done first due to patients presenting for a suspected intracranial hemorrhage. CT and MRI are usually the initial modalities done on patients with AVMs. On NCCT, AVMs may appear as serpentine hyperattenuating structures and even curvilinear or speckled calcifications (5, 6). Conventional CTA can identify AVMs but has some limitations due to its static nature not allowing for flow-related changes. For this reason, DSA is superior and depicts AVMs with greater detail and information due to its spatial and temporal resolution. Also, MRI with an MRA can be more advantageous compared to a CTA due to better visualization of parenchymal changes (6). Sometimes small AVMs may be difficult to detect on any imaging modality if there is a hemorrhage, during which the hematoma can compress the AVM nidus. Here it is recommended that imaging be performed again 4-6 weeks after the hematoma (5). T1w and T2w-MR along with fluid-attenuated inversion recovery (FLAIR) sequences may also be used (5). Particularly, susceptibility-weighted imaging (SWI) is good at evaluating draining venous structures better than MRA and MRI. On SWI, AVMs may appear as a hyperintense venous signal (5).
Treatment modalities include endovascular embolization, surgical resection, and radiosurgical intervention. The risk of hemorrhage is high and randomized studies comparing these modalities are needed in ruptured AVMs and to determine if observation or surgical intervention provides better outcomes in unruptured AVMs (6).
1. Ozpinar A, Mendez G, Abla AA. Epidemiology, genetics, pathophysiology, and prognostic classifications of cerebral arteriovenous malformations. Handb Clin Neurol. 2017;143:5-13. doi:10.1016/B978-0-444-63640-9.00001-1
2. Hofmeister C, Stapf C, Hartmann A, et al. Demographic, morphological, and clinical characteristics of 1289 patients with brain arteriovenous malformation. Stroke. 2000;31(6):1307-1310. doi:10.1161/01.str.31.6.1307
3. Spetzler RF, & Martin NA (1986). A proposed grading system for arteriovenous malformations. Journal of Neurosurgery, 65(4), 476-483. doi:10.3171/jns.1986.65.4.0476
4. Abecassis IJ, Xu DS, Batjer HH, Bendok BR. Natural history of brain arteriovenous malformations: a systematic review. Neurosurg Focus. 2014;37(3):E7. doi:10.3171/2014.6.FOCUS14250
5. Mossa-Basha M, Chen J, Gandhi D. Imaging of cerebral arteriovenous malformations and dural arteriovenous fistulas. Neurosurgery Clinics of North America. 2012 Jan;23(1):27-42. doi:10.1016/j.nec.2011.09.007
6. Asif K, Leschke J, Lazzaro MA. Cerebral arteriovenous malformation diagnosis and management. Semin Neurol. 2013;33(5):468-475. doi:10.1055/s-0033-1364212
Neal Joshi is a medical student and aspiring diagnostic radiologist at Rowan University School of Osteopathic Medicine in New Jersey. Prior to medical school, he did research with mouse models for Parkinson’s disease and L-DOPA induced dyskinesias. He also did an internship at Kessler Institute for Rehabilitation in a stroke lab analyzing MR images in ischemic stroke patients with hemispatial neglect. During his time at Rowan, he did research with animal models for traumatic brain injury with an emphasis on electrophysiology of neurons. He graduated from William Paterson University where he completed his studies in biology and biopsychology. Apart from medical school, Neal loves to read, skateboard, go on hikes, and spend time with his friends.
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Kevin M. Rice, MD is the president of Global Radiology CME
Dr. Rice is a radiologist with Renaissance Imaging Medical Associates and is currently the Vice Chief of Staff at Valley Presbyterian Hospital in Los Angeles, California. Dr. Rice has made several media appearances as part of his ongoing commitment to public education. Dr. Rice's passion for state of the art radiology and teaching includes acting as a guest lecturer at UCLA. In 2015, Dr. Rice and Natalie Rice founded Global Radiology CME to provide innovative radiology education at exciting international destinations, with the world's foremost authorities in their field. In 2016, Dr. Rice was nominated and became a semifinalist for a "Minnie" Award for the Most Effective Radiology Educator.
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