BackgroundLate Gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging can be used to visualise regions of fibrosis and scarring in the left atrium (LA) myocardium. This can be important for treatment stratification of patients with atrial fibrillation (AF) and for assessment of treatment after radio frequency catheter ablation (RFCA). In this paper we present a standardised evaluation benchmarking framework for algorithms segmenting fibrosis and scar from LGE CMR images. The algorithms reported are the response to an open challenge that was put to the medical imaging community through an ISBI (IEEE International Symposium on Biomedical Imaging) workshop.MethodsThe image database consisted of 60 multicenter, multivendor LGE CMR image datasets from patients with AF, with 30 images taken before and 30 after RFCA for the treatment of AF. A reference standard for scar and fibrosis was established by merging manual segmentations from three observers. Furthermore, scar was also quantified using 2, 3 and 4 standard deviations (SD) and full-width-at-half-maximum (FWHM) methods. Seven institutions responded to the challenge: Imperial College (IC), Mevis Fraunhofer (MV), Sunnybrook Health Sciences (SY), Harvard/Boston University (HB), Yale School of Medicine (YL), King’s College London (KCL) and Utah CARMA (UTA, UTB). There were 8 different algorithms evaluated in this study.ResultsSome algorithms were able to perform significantly better than SD and FWHM methods in both pre- and post-ablation imaging. Segmentation in pre-ablation images was challenging and good correlation with the reference standard was found in post-ablation images. Overlap scores (out of 100) with the reference standard were as follows: Pre: IC = 37, MV = 22, SY = 17, YL = 48, KCL = 30, UTA = 42, UTB = 45; Post: IC = 76, MV = 85, SY = 73, HB = 76, YL = 84, KCL = 78, UTA = 78, UTB = 72.ConclusionsThe study concludes that currently no algorithm is deemed clearly better than others. There is scope for further algorithmic developments in LA fibrosis and scar quantification from LGE CMR images. Benchmarking of future scar segmentation algorithms is thus important. The proposed benchmarking framework is made available as open-source and new participants can evaluate their algorithms via a web-based interface.

The motivation of the segmentation challenge is to quantitatively analyze global and regional cardiac function from cine magnetic resonance (MR) images, clinical parameters such as ejection fraction (EF), left ventricle myocardium mass (MM), and stroke volume (SV) are required. Calculations of these parameters depend upon accurate delineation of endocardial and epicardial contours of the left ventricle (LV). Manual delineation is time-consuming and tedious and has high inter-observer variability. Thus, fully automatic LV segmentation is desirable.The automatic segmentation of the LV in cine MR typically faces four challenges: 1) the overlap between the intensity distributions within the cardiac regions; 2) the lack of edge information; 3) the shape variability of the endocardial and epicardial contours across slices and phases; and 4) the inter-subject variability of these factors. A number of methods have been proposed for (semi-) automatic LV segmentation, including using a probability atlas [1], dynamic programming [2-3], fuzzy clustering [4], a deformable model [5], an active appearance model [6], a variational and level set [7-10], graph cuts [11-12] and an image-driven approach [13]. For a complete review of recent literature describing cardiac segmentation techniques, see [14]. Although the segmentation results have improved, accurate LV segmentation is still acknowledged as a difficult problem.The goals of this contest are to compare LV segmentation methods by providing an evaluation system, and a database of images and expert contours. Comparing segmentation results across research studies can be difficult due to unspecified differences in the method or implementation of evaluation metrics. This contest will provide open-source code for contour evaluation. Furthermore, the database will provide a set of images such that confounding segmentation differences due to image quality or pathology could be eliminated.

1. The fixation orientations adopted by the eye, head, and chest were examined when all three were allowed to participate in gaze shifts to visual targets. The objective was to discover whether there are invariant, neurally determined laws governing these orientations that might provide clues to the processes of perception and motor control. This is an extension of the classical studies of eye-only saccades that determined that there is only one eye orientation for each gaze direction (Donders' law) and that the rotations necessary to take the eye from a reference orientation to all other orientations adopted are about axes that lie in a plane (Listing's law). 2. The three-dimensional orientations of the static eyes, head, and chest were measured after each gaze shift to a visual target, the targets having been fixed at positions ranging from 0 to 135 degrees to the left and right of center and 45 degrees up and down. These measurements were taken of seven human subjects by means of the search coil technique with coils attached to the sternum, head, and right eye. Orientations were plotted as quaternion vectors so that those orientations obeying Donders' law formed a surface and those obeying Listing's law formed a plane. 3. The orientations adopted by the eye, head, and chest were found to be a small subset of those possible under the biomechanical and task-imposed constraints. Thus there is a neurally implemented restriction, specifically of the rotation of the eye relative to space (i.e., the orientation variable es) and to the head (eh); also of the rotation of the head relative to space (hs) and to the chest (hc), and the rotation of the chest relative to space (cs). Plotted as quaternion vectors, the data for each orientation variable formed a characteristic surfacelike shape. In the case of es, hs, and hc these were twisted surfaces, whereas for eh the surface was planar and for cs it was nearly linear. Thus to a first approximation each of the orientation variables conformed to Donders' law. 4. The eye adopted a pointing (gaze) direction that has the ratio of vertical to horizontal components generally greater than one when fixating each of the corner targets. The chest, by contrast, moved almost entirely in the horizontal direction, whereas the head performed an intermediate role. 5. The es-, hs-, and hc-fitted surfaces and cs-fitted lines were titled remarkably little from the vertical axis (i.e., the gravity direction) despite larger tilts being possible.(ABSTRACT TRUNCATED AT 400 WORDS)

The combination of quantitative parameters of presynaptic DAT and postsynaptic D(2) receptor binding demonstrates superior diagnostic power in the differentiation of patients with IPS and non-IPS than the established approach based on D(2) binding alone. Striatal D(2) receptor binding and the combination of DAT and IBZM binding asymmetries are the factors contributing most in separating these diagnostic groups.