There have been some exciting developments in work to expand the number of markers that can be measured in tissue. The constraints are cost and regulatory acceptance. Multiplexing of proteins in soluble samples (e.g. serum, plasma, urine) have advanced to true high-throughput, with arrays of ELISA-related technologies. However, tissue multiplexing remains difficult.

Immunofluorescence can easily do 3-4 antibodies on a tissue, and quantum dot approaches promise more, but quantum dots are unlikely to be run in the clinic for a number of reasons. Immunofluorescence in general suffers from two disadvantages — regulatory and tissue context. There are a total of 16 IHC based FDA clearances for protein expression with digital imaging using brightfield, and none using fluorescence (FISH doesn’t count). In companion diagnostics development, pharma cannot afford the risk to be first, waiting on clearance and acceptance for a novel technology. There are enough difficulties and risk along the long road of therapeutic development, adding in an unproven regulatory path on a companion diagnostics won’t help. The other difficult with immunofluorescence is the lack of the tissue context. Despite claims to the contrary (watch for these in presentations!), there are no antibodies that will perfectly bind to tumor with no other unwanted binding effect. If you happen to have one, immediately start your own biotech company, you have the holy grail of tumor targets in your hand. Thus any approach that looks to mask tumor with an antibody will require QA by a technician and then a pathologist. We do this regularly at Flagship in our digital pathology services. In brightfield with whole slide images this pathology review of image analysis is fast and cost-effective.

There are at least three emerging technologies to keep an eye on in tissue multiplexing.

20/20 Gene Systems in Maryland have a novel approach called L-IHC (layered IHC), where they sequentially pull off an antibody onto a absorbed layer, with a DNA probe that can hybridize to a fluorochrome.

GE has an approach that was presented at Pathology Informatics where they sequentially bind a fluorochrome-labeled antigen, image, remove, and bind the next one, image, remove, all on the same slide.

And finally, at Flagship we have just launched a new technology called FACTS (Feature Analysis on Consecutive Tissue Sections), where we utilize thin histology sections with image registration techniques from radiology to multiplex from 4 to 8 markers. I suspect we will hear more about multiplexing with digital pathology at Path Visions next week. The new techniques are exciting, with the end goal being an expansion of usage of tissue-based IVDMIAs.

Steve Potts, PhD CEO of Flagship Biosciences gave a great webinar last week on the right time to use image analysis in regulated pathology.   Steve was faced with the challenge of trying to convey a meaningful message to a diverse audience from both the biopharma and clinical markets.   He kept everyone engaged on this detailed, ever evolving topic which provided information on FDA, CLIA, CAP/ASCO, and GLP regulatory guidelines.  Steve did this well, and kept us laughing throughout the presentation.

Navigating regulatory guidelines for image analysis and digital pathology will never be easy, however there are several ways you can effectively use these technologies today while safe guarding yourself.  Steve provides a lot of information and resources in his powerpoint that can help organizations work through and understand just how to do this.

As for when is the “right time”?  Well, you’ll have to download the recorded webinar and Steve’s powerpoint slides to find out!  Thank you Steve for your time and for presenting on this important topic!

Download the Video

Download the presentation

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By Steve Potts, PhD

The formal training of pathologists has an impressive history, and pathology boards for both medical and veterinary pathologists are very difficult professional exams. As digital pathology slowly makes it way from a early adopter technology to mainstream, there will be an increased need for training of the “digital” pathologists, both in working remotely with digital slides (which is fairly quick to pick up) to image analysis (which takes more time and specialization). The vendors of digital pathology scanners generally offer basic and generic software training, and have done a good job of educating the pathologists in how to use the tools. However, much more work needs to be done across the industry in improving training opportunities for pathologists using quantitative analysis, both in the research and clinical markets.

The challenge of image analysis training in the clinical environment is illustrated by a question I had from the audience at a talk I gave recently on Validation of Image Analysis in GLP and CLIA environments. Someone asked,

We use the ER/PR algorithms from the manufacturer on Ki67 out of the box, and we want to know how to validate them?

The problem with this simplistic approach is that Ki-67 has a binary thresholding criteria rather than multilevel in ER/PR, and the Ki-67 staining patterns are generally much different in the nuclei than ER/PR and usually require tuning changes in how the software scores. And Ki-67 is a very simple marker! The best validation process is useless unless the pathologist knows how the algorithms work, and has a generally good understanding of image analysis concepts. While we are working actively on better validation approaches for image analysis for both clinical and GLP preclinical environments, real world training in image analysis must come first.

So prior to our plans for image analysis validation services, we first need to make training of image analysis more accessible to pathologists as well as imaging scientists and support personnel at pathology centers. This is a difficult activity for vendors to do, as it really should be taught by a combination of pathologists and image analysis experts. So many image analysis results heavily depend on the condition of the tissue in staining, fixation, or other histology steps, the pathologist needs to be involved in training to be able to point out some of these things. IHC overstaining is the precise reason that pathologists need to work closely with histotechnologists in determining the exact antibody dilution to use with each stain.  Close communication avoids other artifact pitfalls that affect pathology endpoints and analytical consistencies. Some antibody vendors actually customize their IHC processes to make the antibody stains much darker, which might(?) be helpful to the human eye, but is poor for image analysis, where lighter staining is usually much better. If I had a dollar for every time someone has asked for an algorithm that will work on overstained IHC slides, well, I could buy a couple more slide scanners.

The other reason it is difficult for vendors is that under strict medical device manufacturing guidelines, particularly in the clinical environment, vendors need to stick to discussing and training on the markers for which they are cleared. This means training on the familiar three amigos ER/PR/HER2, and usually on only the subtype of breast cancer for which they have been validated and cleared. There is much more to this limitation than can be addressed here, but it clearly limits for good reason clinical IHC software vendors conducting broad training in image analysis.

The other challenge in training pathologists is time. Due to the heavy workload of many pathologists, there is often little time to devote to attendance at a two-day course either onsite or at the scanner vendor location. The histologist and the lab manager may go, but usually the pathologist simply cannot get the time free in his or her schedule.

To respond to this need, Flagship Biosciences is offering a once-a-week, six week image analysis course online, scheduled each Thursday. It is co-led by an image analysis expert and a board-certified pathologist, which makes for a fascinating interaction. Each session only lasts 2 hours (we may cut it to 90 minutes in the future, this is the limit that people can absorb information), and it gives a week in between for attendees to try out the concepts, see what worked and didn’t work, and come back with questions. We will start with basic cell and area measurement, and move toward more advanced, sophisticated software-aided approaches as the courses progress. We hope that after a pathologist and a pathology lab knows how the algorithms work and how to relook at their IHC approaches for quantitation, the next steps will be image analysis validation training.

It will be interesting to see if image analysis becomes something every pathologist is familiar with and can run, or will be the domain of pathology specialists. I hope for the former, but I am betting on the latter.