Project outline

The digital pathology market is forecast to grow from $546 million in 2014 to $3.1 billion in 2020. This is based on an estimated of CAGR of 23.1%. This growth, combined with a decreasing number of qualified pathologists will lead to a tremendous increase in workload in pathology departments of clinical and pharmaceutical organizations. On top of this quantitative expansion there is urgent need for higher quality diagnostic information, which enables more effective and efficient treatments.

Clinical opinion leaders have indicated that these needs can best be answered by:

  1. The digitalization of pathology labs to increase the diagnostic capacity of pathology departments, and
  2. Improving the quality of diagnosis by the visualization of multi-modal pathology in 3D.

The 3DPathology project will address these needs by creating a – fast, digital, quantitative, spectroscopic, and multimodal – 3D pathology analysis system.

We foresee that this 3D quantitative digital pathology solution, based on a combination of multiple existing pathology modalities (a multitude of molecular information is incorporated in the clinical workflow), will lead to a far more personalized treatment of cancer and cardiovascular diseases. The project will also address clinical workflow integration aspects and standardization of data storage and exchange.

The envisioned digital pathology imaging system will address the analysis and interpretation of the inherently complex pathological images with a size of 100+GB per sample (mono-modal). Combined with the high throughput rate and huge sample- and system data volume (data sets in the range of Terabytes to Petabytes), technological innovations are required of a completely different level of complexity compared to other state-of-the-art medical imaging solutions (e.g. spectral CT scanners).

Five major software intensive technological challenges are identified and will be cleared in this project:

  1. Fast and automated 3D acquisition of tissue information using multiple imaging modalities;
  2. Fusion of the data acquired by different modalities (different size, different resolution in all directions, different storage format, different spectral bandwidth), which includes techniques like co-registration, alignment, reconstruction.
  3. Efficient analysis of the aligned 3D data from different imaging modalities. To enable a high quality diagnosis, the entire tissue sample needs to be analyzed in detail, complemented with patient data. Fast big data analysis algorithms (machine learning and data mining) will be developed to extract and combine the relevant data.
  4. Design of new 3D visualization and interaction technologies (equipment and algorithms), optimized for multi-modal 3D pathology.
  5. Provide an IT backbone to handle the data of tremendous size produced by the individual imaging modalities (data sets in the range of Terabytes to Petabytes).

The consortium is headed by two major European equipment suppliers (Barco and Philips), who, together with other equipment, software and service suppliers in this consortium bring complementary solutions and services to the market required to establish the complete multi-model 3D pathology pipeline envisioned (e.g. microscopes, scanners, IT infrastructures, datacenters, 3D image manipulations, research tools, diagnostics algorithms, medical training).

In addition, the three major users (dominating the market in the histology domain) are also represented in the consortium (hospitals and pathological laboratories).