Need a way to provide patient/ volume level annotations

Describe the solution you'd like
In addition to segmentation we can do using slicer, I would like to provide volume level annotations as sex, disease severity, tumor location, disease location, etc. This would be the result of a classification models. it could also be helpful while selecting the data to train, as we can add annotations as difficulty,

Describe alternatives you've considered
I have tried to reuse the drop down menu of scoring in slicer since it is not used ( no way to trigger scoring from slicer). This needs code changes on the slicer code as:
1- After pressing submit label to do another call to update label info --> calling the datastore method
2 - To retrieve values when we do inference after pressing "next sample"

Start by tracing the Slicer scoring dropdown, the datastore method, and the inference flow after selecting “next sample.” Determine how volume-level annotations would be stored, updated after submission, and retrieved for training-data selection; done means the requested annotations persist and are available during inference.