Computer-aided detection of intracranial aneurysms in MR angiography

Abstract

Intracranial aneurysms represent a significant cause of morbidity and mortality. While the risk factors for aneurysm formation are known, the detection of aneurysms remains challenging. Magnetic resonance angiography (MRA) has recently emerged as a useful non-invasive method for aneurysm detection. However, even for experienced neuroradiologists, the sensitivity to small (<5 mm) aneurysms in MRA images is poor, on the order of 30~60% in recent, large series. We describe a fully automated computer-aided detection (CAD) scheme for detecting aneurysms on 3D time-of-flight (TOF) MRA images. The scheme locates points of interest (POIs) on individual MRA datasets by combining two complementary techniques. The first technique segments the intracranial arteries automatically and finds POIs from the segmented vessels. The second technique identifies POIs directly from the raw, unsegmented image dataset. This latter technique is useful in cases of incomplete segmentation. Following a series of feature calculations, a small fraction of POIs are retained as candidate aneurysms from the collected POIs according to predetermined rules. The CAD scheme was evaluated on 287 datasets containing 147 aneurysms that were verified with digital subtraction angiography, the accepted standard of reference for aneurysm detection. For two different operating points, the CAD scheme achieved a sensitivity of 80% (71% for aneurysms less than 5 mm) with three mean false positives per case, and 95% (91% for aneurysms less than 5 mm) with nine mean false positives per case. In conclusion, the CAD scheme showed good accuracy and may have application in improving the sensitivity of aneurysm detection on MR images.

Fig 1

The flowchart of the algorithm for the CAD of aneurysms.

Fig 2

Inner tangent sphere testing method for vessel radius calculation. Ideally speaking, a when using a sphere with radius not greater than that of the vessel, the overlapped volume is the same as the volume of the sphere; b when using a sphere with radius greater than that of the vessel, the overlapped volume is less than the volume of the sphere.

Fig 3

Four types of vessel POIs.

Fig 4

SS-field and POI collection.

Fig 5

Example of a floater POI in a MRA slice.

Fig 6

Examples of dot POI in a MIPed dotness companion image.

Fig 7

Distance to the trunk (d) and radius of the vessel (r).

Fig 8

Planeness calculation.

Fig 9

Cylinder surfaceness calculation.

Fig 10

Gaussian and mean curvatures calculation.

Fig 11

Histogram of aneurysm size and detection rate.

Fig 12

The FROC curves of the test results.