We investigate the effects of common types of image manipulation and image degradation on the perceived image quality (IQ) of digital pathology slides. The reference images in our study were digital images of animal pathology samples (gastric fundic glands of a dog and liver of a foal) stained with haematoxylin and eosin. The following 5 types of artificial manipulations were applied to the images, each very subtle (though visually discernible) and always one at a time: blurring, gamma modification, adding noise, change in color saturation, and JPG compression. Three groups of subjects: pathology experts (PE), pathology students (PS) and imaging experts (IE), assessed 6 IQ attributes in 72 single-stimulus trials. The following perceptual IQ attribute ratings were collected: overall IQ, blur disturbance, quality of contrast, noise disturbance, and quality of color saturation. Our results indicate that IQ ratings vary quite significantly with expertise, especially, PE and IE tend to judge IQ according to different criteria. In particular, IE seem notably more sensitive to noise than PE who, on the other side, tend to be sensitive to manipulations in color and gamma parameters. It remains an important question for future research to examine the impact of IQ on the diagnostic performance of PE. That should support our present findings in suggesting directions for further development of the numerical IQ metrics for digital pathology data.