Personalized treatment of acute stroke: diagnostics with 3D virtual histology

Every minute counts when someone is having an acute stroke. If the cause is a vascular blockage caused by a blood clot (thrombus) in the brain, detailed insights into the thrombus composition is critical to remove or dissolve it successfully and help restore blood flow. But that’s often easier said than done when "time is brain".

A team from Empa (the Swiss Federal Laboratories for Materials Science and Technology), the University Hospital in Geneva and the Hirslanden Clinic is currently developing a diagnostic procedure that can be used to start a tailored therapy in a timely manner.

In this MEDICA-tradefair.com interview, Empa researcher Dr. Robert Zboray explains how the process works and details the next steps in development.

Dr. Zboray, you have combined different laboratory technologies to obtain a more precise diagnosis of thrombi. What techniques did you use?

Dr. Robert Zboray: We examined extracted thrombi, meaning blood clots taking from patients via high-resolution X-ray imaging. We used nano/micro computed tomography to scrutinize the samples down to the micrometer-range. Along with a phase-contrast method, we generated a three-dimensional image of the thrombi. This means we essentially facilitated a 3D virtual histology of thrombi with no stained tissue sections, as is usually the case with a 2D procedure.

Our method thus enables a non-invasive, yet high-contrast and high-resolution 3D characterization of thrombi.

Simultaneously, our colleagues at the University Hospital in Geneva examined the same samples using scanning electron microscopes. Taken together, all the procedures delivered a very coherent picture of the thrombi we examined. Both techniques complement each other well and are suitable for research purposes.

Did this combination of methods deliver new insights?

Dr. Zboray: Our micro-CT revealed something peculiar. The reference results from our colleagues in Geneva subsequently confirmed our suspicion: a thrombus not only consists of blood cells and fibrin networks – as was previously assumed-, but can also exhibit calcium deposits, as is known from vessel walls in arterial calcification. This insight is interesting as it may impact the choice of treatment option.

Why is it so important to learn more about blood clots?

Dr. Zboray: Mechanical thrombectomy (MTB) is a minimally invasive procedure, in which a neurosurgeon uses a stent to remove a clot from a patient's artery. Unlike with artery blockage, the stents in this setting are not used to widen blocked or narrowed coronary arteries. Many factors affect the removal of a thrombus. The biophysical properties of the blood clot play a role: are red or white blood cells predominating, or what is the proportion of fibrin fibers? This information shows the prospect of the thrombus adhering to the stent, what type of stent should be used or whether the thrombus can even be treated entirely with medication. Knowing these factors is important for the choice of treatment method. The current process to locate blood clots and determine their composition provides only rough indicators.

Phase-contrast micro computed tomography is still in the development stage. What are the current challenges?

Dr. Zboray: We were able to show that our phase-contrast microCT method is non-invasive and works without interference.

However, our method is only geared for ex vivo use. Meanwhile, our objective is to transfer findings from our high-resolution process to clinical CT settings since there is a correlation between clinical and laboratory findings. As a result of these correlations, the current state of digitalization and machine learning allows the data to be modeled in such a way that an algorithm could be better at reading out the detailed information from clinical CT scans in the future.

For now, we must apply our method to a larger cohort to then compare our results with conventional CT processes and to also collect enough data for the development of an algorithm. Our goal is to use machine learning to facilitate a better analysis of clinical CT images, similar to how radiomics already assesses medical images.

At some point down the road, we want to not only examine radiomic features but to also combine genetic or molecular analyses. In doing so, we could derive which biomarkers promote thrombus growth and deduce where the blood clot originated. Of course, this would also affect the treatment methodology and pave the way for personalized medicine.

Let’s assume that the methodology becomes daily clinical practice. What are the technical requirements for clinical facilities to apply this special diagnostic procedure?

Dr. Zboray: They would not require a major medical equipment acquisition, such as buying a new CT scanner, for example. All it takes is our algorithm. You could use it on the CT images, and it would match this data with its “laboratory data” to determine the type of thrombus, thus enabling the neurosurgeon to select the respective treatment method. It’s fairly easy to integrate this strategy into daily clinical practice.

With that being said, we actually aim to complement and don’t plan to fully replace the present methodology.