Semiautomated detection of cerebral microbleeds in magnetic resonance images.

Cerebral microbleeds (CMBs) are increasingly being recognized as an important biomarker for neurovascular diseases. So far, all attempts to count and quantify them have relied on manual methods that are time-consuming and can be inconsistent. A technique is presented that semiautomatically identifies CMBs in susceptibility weighted images (SWI). This will both reduce the processing time and increase the consistency over manual methods. This technique relies on a statistical thresholding algorithm to identify hypointensities within the image. A support vector machine (SVM) supervised learning classifier is then used to separate true CMB from other marked hypointensities. The classifier relies on identifying features such as shape and signal intensity to identify true CMBs. The results from the automated section are then subject to manual review to remove false-positives. This technique is able to achieve a sensitivity of 81.7% compared with the gold standard of manual review and consensus by multiple reviewers. In subjects with many CMBs, this presents a faster alternative to current manual techniques at the cost of some lost sensitivity.

Imaging the vessel wall in major peripheral arteries using susceptibility-weighted imaging.

PURPOSE: To demonstrate a novel contrast mechanism for imaging the vessel wall and vessel wall calcification using susceptibility-weighted imaging (SWI). MATERIALS AND METHODS: Eighteen subjects were imaged with multidetector computed tomography (MDCT) and high-resolution SWI at 3T. The SWI imaging parameters were optimized to allow for the best visualization of the femoral artery lumen and the arterial wall in magnitude and phase images, respectively. SWI-filtered phase data were used to evaluate the diamagnetic susceptibility of vessel wall and of putative vessel wall calcification. Imaging was performed using TE = 15.6 msec (in-phase for fat); TR = 25 msec, flip angle (FA) = 10 degrees , bandwidth (BW) = 80 Hz/pixel, resolution = 0.5 x 0.5 mm in-plane and 1.0 mm through-plane, an acquisition matrix of 512 x 384 x 64 (for read, phase, and slice-select directions), and a total scan time of 8 minutes. RESULTS: Nineteen calcifications were identified in CT and SWI and they correlated well in both size and position. The contrast-to-noise ratio between the blood signal in the lumen of the artery and arterial wall was 11.7:1 and 7.4:1 in magnitude and in phase images, respectively. CONCLUSION: SWI provides a novel means to visualize vessel wall and recognize the presence of calcification.

Susceptibility-weighted imaging: clinical angiographic applications.

By combining filtered phase and magnitude information to create a novel and intrinsic source of contrast, susceptibility-weighted imaging (SWI) has shown great promise in clinical angiography and venography. SWI has contributed to new insights into traumatic brain injury, the role of calcification in atherosclerosis, and the possible relationship between blood settling and deep venous thrombosis. A further contribution from SWI to deep venous thrombosis research (and also stroke) involves its application to the noninvasive measurement of oxygen saturation in the brain and in other tissues. Altogether, SWI offers manifold and diverse avenues for further research using angiographic and venographic techniques.