This work focuses on the structural similarity (SSIM) index as a tool for optimization of the perceived visual image quality obtainable by continuous scanning 2D LA-ICPMS bioimaging, but also other mass spec imaging techniques may benefit from this approach. This index quantifies the differences between a distorted image and a reference image based on parameters associated with luminance, contrast, and noise. Since reference images are not normally available, a protocol was developed to virtually apply distortion-related information introduced by the LA-ICPMS imaging system to a reference image of one's choice. Distortion-related information in the form of blur and noise was experimentally retrieved from line scans across a laser milled knife edge on custom-prepared gelatin standards (mimicking proteinaceous biomatrixes). Distorted images were generated via computational procedures developed earlier, warranting objective image quality assessment via the SSIM indices. We illustrate the potential of this approach for image quality optimization for a suite of LA-ICPMS imaging conditions.