Improving the Outlook for Myelodysplastic Syndrome

Preparing for Prime Time Several limitations must be mitigated before C-Path becomes clinically available—most important, the use of whole-slide versus TMA images. “Each TMA image captures only a minute portion of the full tumor volume, which is much smaller than the multiple whole-slide images used in routine diagnostic pathology,” explained study coauthor Ankur R. Sangoi, M.D., a Stanford University School of Medicine pathologist who practices at El Camino Hospital in Mountain View, Calif. “It is likely that we could have derived a more powerful prognostic model by analyzing whole-slide images, because these might allow the generation of additional higher-level features such as measurements of tumor heterogeneity,” Sangoi explained. Fortunately, C-Path is not specific to TMA image processing and can be adapted to whole-slide examination. Larger study participation at different institutions is also in the works, explained study coauthor Marc J. van de Vijver, M.D., Ph.D., who heads the NKI division of diagnostic oncology. To train C-Path at each new hospital, the team anticipates pathologists’ recalibrating the system with 50–60 hospital-specific images in about 1 hour. Samples specific to each institution will better reflect handling, sampling, and storage techniques that differ from place to place. Along with more diverse study groups, the team hopes to improve C-Path’s ability to analyze breast neoplasia earlier than stage I and to integrate other important information with morphological data. “We are working on several projects to incorporate molecular biomarker and genomics data into C-Path,” Beck explained. “Breast cancer biomarkers include HER2 and triple-negative status; relevant genomics data include copy number abnormalities and gene prognostic signatures.” The last essential step for translating C-Path to clinical medicine will require a substantial contribution from the pathology community, van de Vijver explained. That step, which will help close the technological gulf between radiologists and pathologists, sounds simple, but it will take time and practice in using digital images. “Even today, most pathology diagnoses are made from images viewed directly on a light microscope. Digital slide scanners are not routinely used,” van de Vijver said. “Innovative leadership among pathologists will be critical for facilitating widespread implementation of quantitative digital systems in pathology laboratories.” Greater accuracy and automation can improve clinical pathology, both here and “in parts of the world where expert pathologists may be in short supply,” said study coauthor Torsten O. Nielsen, M.D., Ph.D., codirector of the UBC/VGH Genetic Pathology Evaluation Centre. Nielsen and his coauthors envision building a library of C-Path images from multiple cancer types, optimized to predict clinical outcomes and directly guide treatment decisions.