LV statistical shape modelling challenge: myocardial infarctionOrganisers: Pau Medrano-Gracia, XingYu Zhang, Avan Suinesiaputra and Alistair Young Contact and application*: ssm2015@auckland.ac.nz Statistical shape modelling has been shown to be a powerful tool for visualising geometric and functional patterns of variation not only in the heart but in all organs. Biologically the heart presents great anatomical and functional variation making the encoding of these differences an interesting challenge in itself. After a myocardial infarction, the heart remodels to maintain physiological constraints. We hypothesise that a probabilistic model of the LV can predict a patient’s disease status. A challenge to model the statistical shape of the left ventricle (LV) is therefore proposed this year aiming to create a probabilistic model and detect myocardial infarction. The training dataset will comprise one hundred (100) cases with myocardial infarction and an additional one hundred (100) asymptomatic cases from the DETERMINE and MESA datasets respectively, contributed to the Cardiac Atlas Project (www.cardiacatlas.org). Shapes will be provided as corresponding Cartesian point sets in cardiac MRI magnet coordinates at end-diastole (ED) and end-systole (ES). Classification labels indicating disease (0 = normal, 1 = infarcted) will be provided for the training dataset. No images will be provided. The goals are to:
The participants’ methods will be tested in a different set of 200 cases, again containing 100 asymptomatic cases and 100 infarcted cases. Classification accuracy and related measures of agreement will be calculated (specificity, sensitivity, etc.). It is expected that the probabilistic models can be easily visualised but there is no restriction on the type of decomposition used to partition the shape space (i.e. can be linear or non-linear). Both supervised and non-supervised classification methods can be submitted (if there are enough of both a comparison might be made). A peer-reviewed paper summarising the findings of this challenge will be submitted to an appropriate journal. 
Results Extract from the collation paper: Statistical shape modeling of the left ventricle: myocardial infarct classification challenge Classifications results from the validation dataset achieved a median 93% specificity, sensitivity and accuracy (Table 2). Accuracy ranged from 73 to 98%. Table 2. Participants methods were tested in a separate validation set. All values are %.
Application & Results To apply, you will need to agree to and sign the following data-usage agreement document:
Please e-mail the completed form to ssm2015@auckland.ac.nz Results template available here. Please download, fill out both sheets, replace name of the file with the first author's name (as in the data-usage agreement) and send to ssm2015@auckland.ac.nz no later than 22 July. Please note that you must be registered in order to participate.
Important Notes Upon application, you will receive a link to the dataset. The TAR file contains a compressed Zip file with all the models and labels for 200 models. MESA models correspond to normal cases whereas DETERMINE models correspond to patients with myocardial infarction. The key (labels) is available in the CSV file. Notes: (1) Points are corresponding across patients but are in the original DICOM coordinates. Two phases are available, at end-systole (ES) and end-diastole (ED). Points are stored in the 'vertices' files in (x,y,z) format. (2) Details on the procedure to fit these finite-element models can be found here: http://pubs.rsna.org/doi/abs/10.1148/radiology.216.2.r00au14597 (3) Because of the sampling of these finite-element models, some points are repeated (especially in the apical area). Depending on your processing pipeline, you might need to filter these out first. (4) For more information on MESA and DETERMINE: http://www.cardiacatlas.org/web/guest/data-access (5) A triangular mesh file is included specifying the connectivity of the vertices to create a surface. This is the same for both the endocardial and epicardial surfaces since the same finite-element model was used. This may be useful for visualisation. (6) We have applied the bias correction to correct for image-protocol shape bias between MESA and DETERMINE. A full reference can be found here: Medrano-Gracia, Pau, et al. "Atlas-based analysis of cardiac shape and function: correction of regional shape bias due to imaging protocol for population studies." J Cardiovasc Magn Reson 15 (2013): 80. Therefore all models are free from shape bias due to imaging protocol and can be directly compared. (7) The following indices correspond to points approximately in the middle of the septum, pointing toward the centre of the right ventricle (same for both surfaces): 226 227 228 229 230 231 232 233 234 498 499 500 501 502 503 504 505 762 763 764 765 766 767 768 769 |
Important dates 21/06/2015 - Abstract and registration Please register the title/abstract in the OCS submission system
Please submit your paper describing the methodology and preliminary results (if available). See page "Paper Submission" for details. The program committee (PC) will decide whether the paper is accepted. 22/07/2015 - Challenge results due (challenge participants only) If accepted, you may refine/(re)submit the results. By this date, we expect the final list of cases and their classification (see results template). If accepted, there is a chance to incorporate feedback from reviewers. 09/10/2015 - STACOM 2015 workshop | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
