Understanding the Implications, Benefits, Challenges of 3D Pathology

Comparing 3D and 2D Pathology

To begin, LifeScienceIntelligence asked Reder to explain the premise of 3D pathology and compare it to 2D pathology.

2D Pathology Challenges

Reder gave LifeScienceIntelligence an overview of 2D pathology, which, to date, is the standard of care at many healthcare facilities.

“Traditionally in pathology, tissue is taken from a patient; then it's embedded in paraffin wax, and only a thin slice is cut from the tissue — about four microns in thickness,” shared Reder. “Then it's put on a glass slide, stained, and viewed under a traditional microscope like those found in high school biology or undergraduate biology courses. While that is the foundation of diagnosis in many parts of drug development, it comes with a few inherent downsides.”

He explains that one of the undeniable drawbacks is the limited or lost data during this process. The complex, 3D tissue must be reduced to an arguably simpler 2D slide.

The other challenge is the energy expended on digitizing 2D slides, done by many healthcare centers and researchers. “The downside for them is they're going through all this trouble of embedding in wax, cutting aside, and other manual labor that requires high skill level which can be hard to find,” explained Reder.

Despite all the labor and energy expended on 2D pathology, many centers and industry leaders still do not have the data they want in the form they want at the end of this process.

Benefits of 3D Pathology

“3D pathology is excellent for visualizing and quantifying structures that exist uniquely in 3D like vessels, nerves, fibrosis, and complex cellular environments like the tumor microenvironment,” began Reder. “Some of these types of biology and questions can only be answered in 3D because the two-dimensional cut just doesn't tell the whole story.”

Unlike 2D pathology, 3D pathology can provide a better picture of the patient’s situation, allowing providers to identify concerns that would otherwise be undetectable in 2D pathology. 

Challenges of 3D Pathology

It may seem like a no-brainer to use 3D pathology for people just learning about the technology. However, as technology advances, so do the concurrent challenges. Reder explained that the drawbacks — and the weight they carry — depend on the situation’s complexity.

“It can take longer to prepare the tissue because healthcare professionals have to prepare it in 3D rather than 2D — the chemistry and physics are just a little bit longer,” he noted.

That is the most basic of the challenges with 3D pathology. Beyond that, understanding and managing the data collected with 3D pathology poses an additional hurdle. “Providers have these interesting new types of data in many cases that no one's ever seen. So trying to wrap their head around what this three-dimensional microscopy data mean can be another challenge, but there are solutions to it,” added Reder.

Benefits of 3Deep Imager and AI Tools

Reder highlighted the features of the 3Deep imager and the associated AI tools during his conversation with LifeScienceIntelligence.

Digitizing the Pathology

To address the issue of digitizing the pathology, Reder and his team have incorporated features in their system to streamline and ease the digitization process. “This technology takes the tissue, steams it with fluorescent dyes, and makes it transparent,” he explained.

The process of making the tissue transparent is called chemical clarification. According to Reder, they “use a chemical called ethyl cinnamate, or cinnamon oil, a component of fragrances. It’s non-toxic — actually food grade — and it makes tissue transparent.”

The chemical clarification process allows researchers and clinicians to see the entirety of the tissue instead of the surface alone. In addition, it will enable the researchers to streamline and industrialize the process.

“Researchers can 3D print sample holders and lay in tens or even hundreds of biopsies or pieces of tissue, load them into the 3D imager, and then press go,” said Reder. “We have an automated pipeline to entirely image the tissue and have this beautiful data set ready in the cloud. That's one of the key leaps we've made at Alpenglow. We've built cloud-based bioinformatics pipelines and AI analysis algorithms because what ends up happening is investigators have all this great information, but these datasets are huge.”

Cost Savings

Despite the advanced features of 3D pathology and AI technology, Reder notes that he and his team have developed ways to minimize spending and save money for the researchers using this biotechnology.

According to a 2021 publication in JAMA Network Open, annual healthcare spending for the most prevalent cancers is $156.2 billion. Of all the services this accounts for, pathology and lab testing accounts for 30.9% of the service, which implies that it is also responsible for a large proportion of the costs.

“The more data produced, either higher resolution or larger pieces of tissue, the more expensive it is because producing more data means computing. It also takes longer,” explained Reder. “My team and I built the first microscope for imaging in 3D, which has what we call Scout-and-Zoom. We can quickly scout through the tissue at low resolution and then zoom in on only the most important parts in the tissue at high resolution. That enables our partners to quickly screen through huge amounts of tissue and hone in on only the most important details for higher-resolution imaging. So that means they can save time and access this information that wouldn't be possible before.”

Impact on Health Equity

LifeScienceIntelligence was curious how a technology like this would impact health equity and access to care. “Our partners in Puerto Rico CorePlus highlight these benefits. They're in somewhat of an underserved setting in Puerto,” remarked Reder.

“They do a lot of business there, and their pathologists work incredibly hard, but it's a challenge to meet all the demand for the population they serve, so they've incorporated AI tools to assist them in some of that diagnosis,” he continued. “Alpenglow’s tools take that to the next generation. We digitize tissue directly, which solves many challenges in low-resource settings as they no longer have to recruit talented, uniquely skilled histotechnologists to prepare the tissue.”

According to a 2019 commentary in JAMA Network Open, the pathology workforce in the United States declined 17% in the 10 years between 2007 and 2017. With that in mind, the tools described by Reder can help clinics with limited resources or availability of professionals keep up with their high demands.

Beyond not having to recruit and expend energy on preparing the slides and technology, Reder explains that digitizing the slide allows easier, secure data sharing. This data-sharing feature can lead to improved collaboration between healthcare professionals, which can help provide more equitable care.

Reder added, “the final way is the incorporation of AI. These tools assist with diagnosis or predict things that the human mind can't do, like ‘what's the prognosis? What's the calculated survival for this disease? Or will a patient respond to this drug?’”

This provides a unique predictive power that no pathologist, regardless of their educational background or experience, can accurately predict.

Looking Ahead
“Right now, Alpenglow’s solution is for research use only, and in the future, we would aim to have a clinical implementation,” shared Reder. “But it's still a research use-only tool in the near term.”

As this tool and other similar 3D pathology tools are incorporated into research, it will be up to healthcare professionals and researchers to weigh the benefits of these tools with their potential challenges. Future research may include enhancing the technology and testing its impacts in clinical care settings.