In the dictionary appears the CancerL, CancerR please clarify which of these is correct. 1. If you provide more than one studio/sessions cancer was diagnosed strictly latter the last studio. 2. If you provide more than one studio/sessions cancer was diagnosed latter or in the last studio. 3. The input for the challenge 1 is one or more studios/sessions, with at least one Left Right 3. The input for the challenge 1 is just one studios/sessions, with at least one Left Right

Created by Kiko Albiol kikoalbiol
> i think that is possible, right? that in america sometimes cancer can be cured. This statement concerns one of the aspects that we are discussing. We'll get back to you shortly.
In Sub-challenge 2, we provide a sequence of exams (the time points) for a given patient. If an exam has the value of cancerL set to 1, this means that the left breast of the patient has developed a cancer within one year from the date of the exam (the definition is given in the [exams metadata dictionary](https://www.synapse.org/#!Synapse:syn6181938)). In both Sub-challenge 1 and 2, we ask the predictions to be made at the exam level and not at the breast or image level. Assuming that your method makes a prediction at the image level, you need to aggregate the results obtained for the images that you have processed from a given exam. The value of cancerL and cancerR is given for each exam. As Gustavo mentioned, we are still discussing some aspects of Sub-Challenge 2. Once done, we will make sure to update the description of the challenge. Hope this helps.
Yes this is the cuestion: For JUST a patient I have 10 time points and is marked with 'CancerL'. What does it means? What I think is that the disease was **developed strictly** in the year within the last time point. The ambiguities arrises when the clinical informations show that there was a previous diagnose. Thanks
i think kiko's question is different. he is asking if there are 10 time points, is a sample is positive if 1) at least half are positives. 2) the last one is positive, 3) at least one is positive, 4) the first one is positive, but at some where, say time 5, it becomes negative. ** i think that is possible, right? that in america sometimes cancer can be cured.
A new version of the [image crosswalk file](https://www.synapse.org/#!Synapse:syn7113506) that contains the fields *laterality* and *view* is now available.
Hi Kiko, Yes, we plan to include the view used to image the breast in the images crosswalk file so that participants don't have to read it from the DICOM files. We may also provide the DICOM metadata as a text file to make it easier for the participants to access them.
Yes, of course CC, MLO, is what I mean. Laterality is well expressed, but if you need to make a first review to prepare a good strategy, you should never will open the DICOM file to get this information. If you plan to make analisia based on laterality R L your DB is OK, but shape and other features are CC MLO dependent.
Hi Kiko, By orientation, do you mean the view used to image the breast (CC, MLO, etc.)? The orientation of the breast of the image is also determined by the laterality available in [images_crosswalk_pilot.tsv](https://www.synapse.org/#!Synapse:syn6174179) (the base of left/right breast is aligned on the left/right side of the images).
Thanks Gustavo the question is really about the data. As I have tried to explain, in the IMAGEs fiel image_XXXXX.tsv there is no information about the orientation. If you need to plan an strategy, this information should be relevant in order to classify images without the need of opening every DICOM file. Most of the other relevant information can be accessed once you decide to explore a set, but not before. Thanks a lot. I understand the effort to make this works.
Hi Kiko, sorry for the delay in responding. Your questions are making us trying to improve the statement of the Challenge questions, so we are taking more time than we would have liked to answer. We'll get back to you shortly.

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