Above, we can see how quickly the SNR improves as we approach 20 exposures in the stack. Beyond it however, there are only minor SNR improvements visible, particularly on the very faint spiral arm fine details (appearing above the noise floor). The result of diminishing returns is clearly presented above.
Everything is better with numbers so I thought it would be a good idea to measure the SNR of these images. I did this by using the NoiseEvaluation script in PixInsight and multiplying the resulting values by 65,535 to convert to 16-bit pixel value. I then divided the Mean of the images (found using the Statistics process) by their corresponding noise values to find an estimate for SNR. Below is a graph displaying the results:
Interesting as this may seem, I wonder if the rule holds as closely for more expansive targets (large nebulae that cover most of the image) and for other filters that are more permissive of light (e.g. Luminance). Definitely something to test!