You can also consider one of the many tools out there that are much easier to use than Slicer for batch volume reconstruction (faster, easier to use, possibly more robust).
You can find a list of some of the most popular ones (incomplete, I am sure) here: https://na-mic.github.io/ProjectWeek/PW27_2018_Boston/Projects/DICOMVolumeReconstruction/.
A number of them (including Slicer converters) are set up in this dockerfile: https://github.com/QIICR/dcmheat/blob/master/docker/Dockerfile (just noticed the corresponding container on Docker Hub is broken, I need to fix that).
How they compare to each other and which specific one to recommend remains the open question (for me at least). As we make progress with the project referenced above, hopefully we will be able to recommend one specific tool, or say that all/subset of them are equivalent for practical purposes.