The Digital Future Of Pathology

Pathology is the motor that drives healthcare to understand diseases. Digital technologies could push the field into becoming more efficient and more scalable. They could transform the job of pathologists into a more creative and data-driven profession while allowing patients to receive diagnoses faster and more accurately. Let’s see what the digital future of pathology looks like!

The foundation of medicine, pathology, has barely changed for over 150 years

Although the whole edifice of medicine rests on the pathologist’s diagnosis, the field has not experienced any significant change for the last 150 years; said Thomas Fuchs, Director of Computational Pathology Lab at Memorial Sloan Kettering Cancer Center and Founder of Paige.AI, which is building machine learning algorithms to help digitise pathology, at the NVIDIA GPU Tech Conference a few years ago.

“Approximately 90 percent of the work is still done on various stains with methodologies that doctors came up with more than a hundred years ago.” – he added.

Although there has been some significant progress in the field – more on it a little later -, this field is still notoriously manual-labour intensive. The entire process of analysing stains is highly subjective and could signify a cumbersome process. For example, in the case of a prostate biopsy, pathologists have to scrutinize around 48 slides. Also, the results depend on the specialty, the personal judgment and, more often than not, even on the mental state of the pathologist – lowering the levels of accuracy.

Pathologists are doing enormous work and spend too much time searching for old slides, images, and case information in the archives of hospitals. While retrospective data use is possible in pathology – Fuchs mentioned that there are perfectly utilisable slides even from the 1930s! –, this amazing resource cannot be leveraged efficiently enough as you have to look up decades-old tumor slides manually. In the 21st century, the age of digital assistants making appointments in restaurants or hair salons, it is painful to even hear about that.

Pathologists are scarce assets

No surprise that pathologists’ are “limited assets” everywhere, and their number is predicted to decrease worldwide. According to one study, by 2030 the number of active pathologists may have dropped by 30 percent compared to 2010 levels. In some parts of the globe, the shortage of pathologists is shocking.

The poster you see below highlights these facts. Based on 2021 figures and presented in the first half of 2022, this work by Andrey Bychkov MD, PhD makes it obvious at a glance how amazing the disparities are on a global scale. He told The Medical Futurist that the work hasn’t stopped and an updated version will follow within a few weeks (ramified numbers + more countries) in a Hi-Res format, so keep an eye on his page for the latest data.

The situation isn’t rosy even in the “green” countries. The College of American Pathologists reports a “perceived shortage“. In the United States, practising pathologists will begin to retire at an increasing rate, far faster than the current replacement rate. At the same time, the number of cases is increasing, and pathologists are forced to take on more and more. And as you see above, the US is in much better shape than most of the other countries.

How could digital technology change the status quo?

The digitisation of pathology labs makes the specialty more efficient, the specimen more reproducible, and the work of pathologists less cumbersome. Digital whole-slide imaging (WSI) allows the capture and visualisation of the entire tissue on a slide, as opposed to the narrow field of view that a microscope provides. It could make pathology more accurate and reduce its subjectivity.

A digitised slide could spare an enormous amount of time for physicians. Within the hospital, it often happens that various tissues are delivered from the lab to the surgeon and then back again to the pathologist. Sending over a digitised slide is both safer and faster. Moreover, it allows computerised quantitative analytics, speedier image search, and slide retrieval when it comes to old cases. It reduces the barriers between hospitals, regions, and countries facilitating consultations and referrals.

Not to speak about the possibility of easing the burden caused by the shortage of pathologists worldwide. Just imagine how many hospitals around the world could benefit from digitised pathology labs when they could share their slides in a cloud and retrieve all the information from it. Of course, we are not looking at the accessibility, the privacy issues or the political feasibility of such an experiment here; those are other topics.

AI has arrived in pathology labs

These past few years have brought some grand breakthroughs, which are discussed in detail in this article.

The first major milestone was September 2021 – the date when the first AI-based pathology product – Paige Prostate, a clinical-grade AI solution for prostate cancer detection – received FDA clearance for clinical use. It was followed by a CE mark for the Paige Breast Lymph Node Detection within a year.

This was followed by a rapid-fire of similar announcements. Ibex’s collaboration with Roche and the launch of their Galen platform’s use in Swiss clinics, and the company getting a CE mark on their AI solution for detecting gastric cancer. Proscia entering an extended partnership with Siemens Healthineers allowing the latter to enter the digital pathology segment.

Google’s Verily teamed up with Lumea, the aim of the cooperation is to improve prostate cancer diagnosis and prognosis. Roche entered into a collaboration with Bristol Myers Squibb to develop and deploy two new digital pathology algorithms. PreciseDx, a Mount Sinai Health System spin-off, has developed artificial intelligence-enabled digital pathology technology to detect Parkinson’s disease.

In the digitising side of the field, Pranama was chosen as the archival scanning partner of the Mayo Clinic to digitize 5 million clinical pathology slides.

The use of digital technologies, first of all, AI could help make the field “more robust, more producible, and it could really push the field from a purely qualitative to a quantitative area,” noted Fuchs in an interview with The Medical Futurist.

So, let’s see the array of new technologies which could support pathology’s bright future!

1) Digitised workflow – from electronic microscopes to the cloud

The role of the pathology laboratory is to use blood, fluid or tissue to provide accurate, timely and relevant information useful in making diagnoses, and to guide and monitor therapy. After macroscopic evaluation of the masses in the digitised pathology lab, the process of whole slide imaging takes place. After the slices are prepared, an electronic microscope digitalises the samples for further analysis with the help of various scanning solutions. A variety of digital products are already available on the market for migrating the entire workflow of pathologists from the manual to the digital. Whole-slide imaging solutions, such as the Nanozoomer, scanners, software, storage systems, clouds and communication systems work together to ease the work in the labs.

It will make sending slides and data for consultation much easier so providing virtual pathology services at remote sites and facilitating discussions and second opinions will undoubtedly become a booming area. Although we will always have someone looking at tissues through an electronic microscope – the interpretative reporting will be carried out in front of pulsating screens rather than next to microscopes.

However, the digitised workflow also comes with limitations that need to be solved in the future for a seamless operation. As pathology images require very high resolution and image quality is key, files have enormous sizes. Storage of huge datasets remains a challenge as well as their transport through various computer systems.

2) Deep learning for automation

The digitisation of pathology resources opens the door for the utilization of the massive potential of artificial intelligence in the field. However, the first step for that is digitisation. Fuchs says that they have been digitising slides for the better part of the past decade at Memorial Sloan Kettering. According to this study, the pace is an average of 140,000 slides per month. Their inventory contains some 3.6 million images and growing.

And size does matter in the case of datasets. In fact, he added, “no one wants to use algorithms trained on small data sets, that would be like training your self-driving car in a parking lot.” Nevertheless, once the data sets are large enough, deep learning algorithms will be for pathologists as if they have hit the bonus.

They could be used for the classification of digitised pathology slides – similar to the practice used in radiology. Just as Facebook recognizes faces in photos, these image recognition systems identify slides with precancerous or cancerous cells and group them accordingly.

Anyhow, the process enables pathologists to spend more time on cases requiring more attention and to set aside simpler slides with benign tumors. Thus, they will have more time on their hands, which might bring another solution to the lack of pathologists worldwide.

3) AI for better augmentation, prognosis, and prediction

Pathologists use many techniques for augmenting tissues and samples to make specific abnormal mutations visible. For example, molecular tests have been used for many years to illuminate proteins. Deep learning algorithms will be able to do something similar with digitised images in the future. AI could spot certain linkages which are not visible to the human eye.

For example, augmentation could integrate computer-quantified histology data from a slide with data from other sources, such as DNA sequencing, helping pathologists to make conclusions with higher accuracy and confidence. Another use of augmentation is counting and differentiating cell types to help with the staging of tumors.

These methods also give more room for prognosis and predictions. The latter is the most positive addition of deep learning algorithms. Fuchs says that in the future when you have a three-cent H&E slide, an AI algorithm could tell you there is an indication caused by a specific mutation. That could lead the specialist to sequence precisely that, and come up with a targeted treatment for the patient.

When formulating a diagnosis, algorithms could be of tremendous help. A study showed that the combination of a deep learning system’s predictions with the human pathologist’s diagnoses for identifying metastatic breast cancer resulted in an 85 percent reduction in human error rate! That is simply amazing!

4) Biotechnology for precision medicine

Various digital technologies will improve the point-of-care testing (PoCT) options of pathology departments in the future. Just as portable diagnostic devices are making it possible to diagnose patients wherever they are, such tools enable the examination of tissues, fluids and other samples near the patient’s location, in the surgery or clinic at the time of consultation to facilitate prompt clinical decision making regarding patient management. Various blood glucose meters, urine test strips, and pregnancy tests fall into the category of PoCT, but their range will significantly widen in the future.

Some start-ups are already raising the stakes. The UK-based start-up, Oxford Nanopore Technologies offer real-time, out-of-the-lab DNA and RNA sequencing with their MinION device. It enabled researchers to carry out offline DNA sequencing of environmental samples on Antarctica using only a hand-held device. Mind-blowing, isn’t it?

Molecular analysis will enable more precise diagnosis in the future, and revolutionise how we define several diseases. It will also give precious information on how patients respond to treatment and what the prognosis is. The pathologist will help interpret the results and choose which molecules to be evaluated.

5) Pathology and radiology

There are several similarities between the two medical fields. They are both necessary for the diagnostic process, and they both represent qualitative science based on the opinion of medical experts. Lately, there are also common features in how they are digitised. Pathologists and radiologists both look at anatomies through imaging devices – although one of them at the cellular level, the other one at the organ level. Moreover, due to the rapid changes in digital imaging methods in the last few years, both fields are transforming faster than any other medical specialties.

Fuchs explained that pathology will be fundamentally different in 10 years, but he does not believe that, for example, the fears of AI taking jobs resonate the same way in pathology as it does in radiology. He thinks that radiology, dermoscopy, and other disciplines might be more scared because these are rather screening steps. However, as soon as you see something in radiology or dermoscopy, you have to look at the pathology. So that’s the ground truth. After all, everything is based on that diagnosis. Thus, the human will always be there, looking at the microscope. No matter whether there is an AI or any other technology collaborating with it.

Pathology is heading towards the cosmos

However, all the above-enumerated factors will definitely change the specialty – but Fuchs believes it is going to be more exciting for pathologists. The Medical Futurist agrees. If imaging methods are powerful enough to analyze individual cells, pathology could become an entirely different branch of medical sciences. A new chapter could start for traditional pathology that goes down to the level of individual cells instead of looking at the organism as a whole. At this point, radiology and pathology might even overlap/merge to some degree as one will have to know both areas.

Both physicians and patients will benefit from this transformation. With better tools, medical professionals will have a better chance to save lives and patients will have a better chance to survive. Pathology, it’s a little bit like cosmology. When astronomers look for exoplanets that we don’t yet fully understand or know, the better telescopes they can use, the more we will learn.

Learn more about the technological future of medical specialties from our latest e-book!

The post The Digital Future Of Pathology appeared first on The Medical Futurist.

Source link