Automatic registration produces clearer 3D liver images

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 - automatic registration
Postregistered axial arterial image of 45-year-old man with treated hepatocellular carcinoma shows accentuation of blurring of lesion margins.
Source: American Journal of Roentgenology. 2015;204: 287-296

Computer-aided image registration is an effective means of reducing interphasic hepatic image displacement and aids in the detection of lesions, according to a study published in the February edition of the American Journal of Roentgenology.

The research team, led by Dinesh K. Sundarakumar, MD, with the Department of Radiology at the University of Washington, studied MR images of 25 cirrhotic patients with treated hepatocellular carcinoma (HCC) and at least one small hepatic cyst.

Sundarakumar and team used an automated 3D deformable registration algorithm to create MRI subtraction images using venous phase images as the baseline.

“The purpose of this study was to quantify the displacement of the liver between the different dynamic phases in a multiphasic examination, measure the improvement in displacement after registration using anatomic landmarks, and quantify the improvements in image quality and reader confidence for evaluating treated HCC,” they wrote.

The small cysts were used as landmarks in the registration process to gauge imaging effectiveness. Initially, the images showed considerable hepatic displacement between breath-holds in all patients but the images were improved through automatic registration.

Results of the study showed that the total cyst displacement on the unenhanced, arterial and delayed phase images was reduced by registration from 4.0, 3.2 and 4.6 mm, respectively, on pre-registered images to 2.4, 1.6 and 1.3 mm, respectively, on post-registered images.

Additionally, the HCC lesion conspicuity grade rose from 3.4 to 4.4 after registration.

“When compared with landmark- or surface-based registration, the registration method used in this study is robust for a highly mobile and deformable organ such as the liver,” the authors wrote. “The feature-based registration methods used are based on similarities between corresponding points in the images.”

Sundarakumar and colleagues concluded that professional, fully automated registration algorithms significantly reduce displacement in 3D MRI contrast images.

“This capability has potential implications for the detection and characterization of small (≤ 2 cm) and subcapsular lesions, which are traditionally difficult to evaluate with subtraction because of artifacts,” they wrote. “These preliminary results suggest registration may be helpful in routine liver MRI, particularly for follow-up of HCCs after ablation.”