MeVis Medical Solutions (Germany)

The article is dedicated to the 100th anniversary of the famous Russian ophthalmologist Skald L. Shapovalov, his life path and main scientific achievements.

In the management of patients with chronic liver disease, the assessment of liver function is essential for treatment planning. Gd-EOB-DTPA-enhanced MRI allows for both the acquisition of anatomical information and regional liver function quantification. The objective of this study was to demonstrate and evaluate the diagnostic performance of two fully automatically generated imaging-based liver function scores that take the whole liver into account. T1 images from the native and hepatobiliary phases and the corresponding T1 maps from 195 patients were analyzed. A novel artificial-intelligence-based software prototype performed image segmentation and registration, calculated the reduction rate of the T1 relaxation time for the whole liver (rrT1liver) and used it to calculate a personalized liver function score, then generated a unified score—the MELIF score—by combining the liver function score with a patient-specific factor that included weight, height and liver volume. Both scores correlated strongly with the MELD score, which is used as a reference for global liver function. However, MELIF showed a stronger correlation than the rrT1liver score. This study demonstrated that the fully automated determination of total liver function, regionally resolved, using MR liver imaging is feasible, providing the opportunity to use the MELIF score as a diagnostic marker in future prospective studies.

Automated lung lobe segmentation methods often fail for challenging and clinically relevant cases with incomplete fissures or substantial amounts of pathology. We present a fast and intuitive method to interactively correct a given lung lobe segmentation or to quickly create a lobe segmentation from scratch based on a lung mask.A given lobar boundary is converted into a mesh by principal component analysis of 3D lobar boundary markers to obtain a plane where nodes correspond to the position of the markers. An observer can modify the mesh by drawing on 2D slices in arbitrary orientations. After each drawing, the mesh is immediately adapted in a 3D region around the user interaction.For evaluation we participated in the international lung lobe segmentation challenge LObe and lung analysis 2011 (LOLA11). Two observers applied the method to correct a given lung lobe segmentation obtained by a fully automatic method for all 55 CT scans of LOLA11. On average observer 1/2 required 8 ± 4/25 ± 12 interactions per case and took 1:30 ± 0:34/3:19 ± 1:29 min. The average distances to the reference segmentation were improved from an initial 2.68 ± 14.71 mm to 0.89 ± 1.63/0.74 ± 1.51 mm. In addition, one observer applied the proposed method to create a segmentation from scratch. This took 3:44 ± 0:58 minutes on average per case, applying an average of 20 ± 3 interactions to reach an average distance to the reference of 0.77 ± 1.14 mm.Thus, both the interactive corrections and the creation of a segmentation from scratch were feasible in a short time with excellent results and only little interaction. Since the mesh adaptation is independent of image features, the method can successfully handle patients with severe pathologies, provided that the human operator is capable of correctly indicating the lobar boundaries.