Using the pretrained parameters of a 2D CNN won’t work out of the box, as the depth dimension is missing e.g. in the kernels.
You could try to create this dimension, e.g. by repeating the filters, but I’m not sure, if this would be helpful.
Would it be possible to use each slice as a 2D image first and apply a standard transfer learning approach?
This would make the workflow easier and could give you a signal, if your 3D model would benefit from the pretrained parameters.