Web-based tissue microarray image data analysis: Initial validation testing through prostate cancer Gleason grading

Tissue microarray technology promises to enhance tissue-based molecular research by allowing improved conservation of tissue resources and experimental reagents, improved internal experimental control, and increased sample numbers per experiment, Organized, well-validated collection and analysis of the voluminous image data produced by tissue microarray technology is critical to maximize its value. Web-based technology for visual analysis and searchable storage of microarray image data could provide optimal flexibility for research groups in meeting this goal, but this approach has not been examined scientifically. Toward this goal, a prostate tissue microarray block containing 432 tissue cores (0.6 mm diameter) was constructed. Moderately compressed (200 kb).jpg images of each tissue spot were acquired and were saved using a naming convention developed by the SPORE Prostate Tissue Microarray Collaborative Group. Four hundred three tissue array spot images were uploaded into a database developed for this study and were converted to .fpx format to decrease Internet transmission limes for high-resolution image data. In phase T of the image analysis portion of the study, testing and preliminary analysis of the Web technology was performed by 2 pathologists (M.A.R. and G.S.B.). In phase II, 2 pathologists (J.I.E. and T.M.W.) with no previous exposure to this technology and no knowledge of the structure of the study were presented a set of 130 sequential tissue spot images via the Web on their office computers. In phase III, the same pathologists were presented a set of 193 images, including all 130 from phase II and 63 others, with image presentation order randomized. With each zoomable tissue spot image, each pathologist was presented with a nested set of questions regarding overall interpretability of the image, presence or absence of cancer, and predominant and second most frequent Gleason grade. In phases II and III of the study, 319 of 323 (99%) image presentations using this Web technology were rated interpretable. Comparing the 2 pathologists' readings in phases II and III, Gleason grade determinations by each pathologist were identical in 179 of 221 (81%,) determinations and were within 1 point of each other in 221 of 221 (100%) determinations, a performance rate similar to if not better than that previously reported for direct microscopic Gleason grading. Interobserver comparison of Gleason score determinations and intraobserver comparisons for Gleason grade and score also showed a pattern of uniformity similar to those reported in direct microscope-based Gleason grading studies. Interobserver (7.5%) and intraobserver (5% and 3%) variability in determining whether diagnosable cancer was present point out the existence of a "threshold effect" that has rarely been studied but may provide a basis for identification of features that are most amenable to improved diagnostic standardization. In summary, storage and analysis of tissue microarray spot images using Web-based technology is feasible and practical, and the quality of images obtained using the techniques described here appears adequate for most tissue-based pathology research applications.