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UPLOADING DATA A step-by-step guide

Before you begin:

To upload data to the NAIMS Imaging Repository you will first need to create an account using an official email address of your institution. Your account will need to be approved by an administrator before you are given the ability to upload or download data (this may take a few days); you will be notified by email when this happens.

All uploaded images must be in DICOM, PARREC, or NIFTY format; however, automatic sorting/parsing of images is only supproted for DICOMs and PARRECs. Click here to jump to the batch upload section (DICOM/PARREC), or click here to jump to the manual upload section (NIFTY).

During the uploading process, the incoming data will be de-identified before being stored in the NAIMS-IR. Even so, it is your responsibility to ensure that you de-identify your data before uploading.

Do you already have an approved study?

Yes

Click to read about creating a study.

Unsure

Click to read about the hub page.

STEP 1: Proposal form and paperwork To upload data, you will first have to create a study. Note that only PI accounts have the ability to create new studies. If you are not a PI, you will need to get your PI to add you to an existing study and grant you upload permissions.

From the hub page, click the + CREATE A NEW STUDY button. Look for this button on the right of the window, under your 'My Studies' list. You will then be presented with the NAIMS-IR Data Submission Project Proposal online form. Here you will enter your PI contact information, aswell as additional information regarding the study.

If you would like to look at this form in advance of filling it out through the webpage, click here.

Once the Data Submission Project Proposal form is complete, you will see the study in your 'My Studies' list in the hub; however, you will not be able to upload data until it is approved. To obtain approval, the following forms will also need to be uploaded/completed from the hub page.

Copy of the most recent IRB or local ethics committee approval for your research project (if applicable)

STEP 2: Preparing your data for upload While you are waiting for your study to be approved, you can prepare your data for upload to the NAIMS-IR.

Images must be in DICOM or PHILIPS format.
The NAIMS-IR automatically sorts uploaded images by participant, visit, and sequence. To do this, we use information stored in the image header. Other image formats such as NIFTY do not contain the necessary header information for this automatic sorting process.

Make sure your images are de-identified.
It is your responsibility to ensure that there is no personally identifiable information in the data you upload to the NAIMS-IR.

Ensure the image header contains the necessary information.
Our automated image sorting is built to be compatible with a diverse range of data. Philips proprietary formats have strict header rules; however, DICOM headers can have significant differences. Because of this, the NAIMS-IR requires your DICOM image headers must satisfy the below requirements (most data should satsify these requirements by default):

Either 'Patient Name' or 'Patient ID' must contain a unique ID that identifies which subject the DICOM belongs to.
One of: 'Acquisition Date', 'Series Date', 'Study Date', or 'Content Date' must contain the date of the visit that the DICOM belongs to.
'Series Description' must contain a description of which sequence the image belongs to.
'Repetition Time' must contain an appropriate value.

Compress your images into a single archive.
When parsing your uploaded data, we use only the image header to differentiate between participants, visits, and sequences. Philips formats have the image files and header files seperate, so the NAIMS-IR requires that they both have the same FILENAME (not including the file extension). There are no restrictions on DICOM file names.

Uploaded images do not need to adhere to any particular directory structure. Simply compress the directories containing your images into a single archive. We support .zip and .tar/.tar.gz files. Any files in the uploaded archive that are not recognized as valid image formats will simply be skipped.

STEP 3: Uploading data When your study has been approved you will recieve and email notifying you. You will then be able to upload images to your study. Uploading data is done through the hub page; select your study and click the + UPLOAD IMAGES button to begin.

Follow the prompts and read the information points before continuing to the upload page.

Select the desired archive file from your computer and click the UPLOAD button to begin the transfer. Once you have started, do not close the browser window unless you wish to cancel the upload.

STEP 4: NAIMS-IR Parsing Once your data archive has been transferred to the NAIMS-IR it will be put in queue for parsing. Note that you can see the status of any uploads for a study by clicking on it in the hub page. During this process our scripts will de-identify your image files and sort them by Participant, Scan, and Sequence.

Once parsing is complete, you should see an interactable list of the participants, scans, and sequences that have been extracted from your image data and added to your study on the study page. Additionally, you will see a new entry in the 'upload history' on the left of the study page. Here you can click on a button to view the data receipt for this upload.

The data receipt will list each file that was extracted from your uploaded archive, and provide a summary of the data that was extracted from it. If there were any errors parsing any of your files, you will also be able to view them here. Please review the data receipt after an upload to make sure your files were parsed successfully.

STEP 4: Adding additional clinical information Once a study in the NAIMS-IR has been populated with participants and scans, additional clinical information can be uploaded by clicking the + UPLOAD CLINICAL DATA button from the study page.

Some clinical data is not stored in the header of the image files and therefore needs to uploaded to the NAIMS-IR separately (eg. EDSS, MS Type, cognitive test scores). While all clinical measures are optional, we encourage you to upload whichever measures you have available.

To upload clinical measures, we will provide you with a template .csv spreadsheet for your study. You will then fill it out with the available clinical information, and upload the spreadsheet back to the NAIMS-IR.

Below is an example of what the template spreadsheet could look like for a study with 3 participants, each with 2 scan vists.

Repository ID	Original ID	Scan Visit Date (yyyy-mm-dd)
MyStudy_1	ABC-001-01	2019-01-10
MyStudy_1	ABC-001-01	2019-02-17
MyStudy_2	ABC-001-02	2019-01-07
MyStudy_2	ABC-001-02	2019-02-14
MyStudy_3	ABC-001-03	2019-01-29
MyStudy_3	ABC-001-03	2019-03-04

Each row corresponds to a participant's scan visit. For each scan (row), you can add a correpsonding clinical visit date (this may be the same date as the scan), and the clinical measures that were collected on that day. Note that not all scan visits need to have a correpsonding clinical visit.

Furthermore, you can add clinical visits that do not correspond to any scan visit. To do this, you will have to manually add an extra row for the participant with an empty 'Scan Visit Date'. Below is an example of a row that we could add to the example above for a clinical visit that was 3 months prior to the first scan.

Repository ID	Original ID	Scan Visit Date (yyyy-mm-dd)	Clinical Visit Date (yyyy-mm-dd)
MyStudy_1	ABC-001-01		2018-10-11
MyStudy_1	ABC-001-01	2019-01-10
MyStudy_1	ABC-001-01	2019-02-17
MyStudy_2	ABC-001-02	2019-01-07
MyStudy_2	ABC-001-02	2019-02-14
MyStudy_3	ABC-001-03	2019-01-29
MyStudy_3	ABC-001-03	2019-03-04

Putting this all together, below is an example of what the spreadsheet could look like after it has been filled out. Note that not all columns are shown in this example; the real spreadsheet contains many more clinical measures then just EDSS.

Repository ID	Original ID	Scan Visit Date (yyyy-mm-dd)	Clinical Visit Date (yyyy-mm-dd)	EDSS
MyStudy_1	ABC-001-01		2018-10-11	2.0
MyStudy_1	ABC-001-01	2019-01-10	2019-01-10	2.0
MyStudy_1	ABC-001-01	2019-02-17	2019-02-18	2.5
MyStudy_2	ABC-001-02	2019-01-07	2019-01-10	1.5
MyStudy_2	ABC-001-02	2019-02-14	2019-02-14	1.5
MyStudy_3	ABC-001-03	2019-01-29	2019-01-30	1.5
MyStudy_3	ABC-001-03	2019-03-04	2019-03-06	2.0

Here are a few more things you should note:

All clinical measures are optional. Don't worry if you can't fill out every column in the spreadsheet we provide. Simply leave these cells blank.
You can add additional columns. The columns present in the template are 'suggested clinical values' that the NAIMS-IR is capable of automatically parsing. These values are used when other users are looking at your data (for example, filtering for people of a specific MS type).

If there are additional clinical measures that you think would be useful to others, you can add additional custom columns to the spreadsheet. These values can't be used to filter data on the data search page, but will still be provided to people who download the data.