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InSight – an automated 3D cancer detection platform
Histopathological approaches have remained the same for the past 200 years despite the limitations resulting in detrimental implications: (i) The specimen preparation (cutting to prepare thin tissue slices) is extremely laborious. (ii) Due to the laborious work, only 2% of the tissue sample is prepared and analyzed in 2D. (iii) The low sample amount and the generated 2D images limit the extractable information. These limitations culminate in a false negative cancer detection rate of up to 28%. Failure to detect up to 28% of cancer cells is unacceptable. By combining technology from biomedicine, mechanical engineering, and food science, we have developed a game changing interdisciplinary solution that mitigates the bottlenecks associated with 3D tissue sample preparation, enabling the generation of spatial images within 2 days.
With our existing automated prototype, our overarching aim is to drastically improve the detection accuracy of cells of interest and revolutionize the way tumors and diseased tissue are detected by moving histopathology into the digital domain. There are three parts required to achieve this digital revolution:
(i) Rapid and automated whole-tissue preparation (lipid removal and staining), required for 3D image generation, in the same amount of time as 2D approaches.
(ii) Imaging of the entire tissue sample in 3D with existing open-source UZH spatial imaging microscopes, in the same amount of time as 2D approaches.
(iii) Computer vision software to assist physicians in examining the 3D images.
With the first steps we were able to partially speed up the clearing and staining phase of murine and human lymph node tissue samples, enabling the rapid generation of a 3D digital image within 2 days. To this end, we began to develop an automated platform called "Insight “consisting of a robotic platform, automated injection system and an integrated pulsed electric field (PEF) system (Figure 2). Pulsed electric fields apply severe treatment conditions (high electric field strengths) to the tissue without damaging it (ohmic heating effects). Thus, lipid removal is accelerated and the diffusion of dye molecules following an automated injection system is accelerated. The InSight pipeline (Figure 2) can provide whole-tissue information in a similar time frame as the classical 2D histopathology pipeline (~2 days). From the rapid quantification of tissue samples in their entirety, a more accurate diagnosis and more information regarding the spatial arrangement of cells in 3D is expected.
With our existing automated prototype, our overarching aim is to drastically improve the detection accuracy of cells of interest and revolutionize the way tumors and diseased tissue are detected by moving histopathology into the digital domain. There are three parts required to achieve this digital revolution: (i) Rapid and automated whole-tissue preparation (lipid removal and staining), required for 3D image generation, in the same amount of time as 2D approaches. (ii) Imaging of the entire tissue sample in 3D with existing open-source UZH spatial imaging microscopes, in the same amount of time as 2D approaches. (iii) Computer vision software to assist physicians in examining the 3D images.
With the first steps we were able to partially speed up the clearing and staining phase of murine and human lymph node tissue samples, enabling the rapid generation of a 3D digital image within 2 days. To this end, we began to develop an automated platform called "Insight “consisting of a robotic platform, automated injection system and an integrated pulsed electric field (PEF) system (Figure 2). Pulsed electric fields apply severe treatment conditions (high electric field strengths) to the tissue without damaging it (ohmic heating effects). Thus, lipid removal is accelerated and the diffusion of dye molecules following an automated injection system is accelerated. The InSight pipeline (Figure 2) can provide whole-tissue information in a similar time frame as the classical 2D histopathology pipeline (~2 days). From the rapid quantification of tissue samples in their entirety, a more accurate diagnosis and more information regarding the spatial arrangement of cells in 3D is expected.
Challenges: Finding a solution to improve and speed-up the penetration and diffusion of staining molecules into biological tissue.
The 3D staining we have achieved so far with the injection and PEF technique is still not optimal and requires a more in-depth study of how to speed up the penetration of the staining solution and improve its diffusion within the tissue. This can be addressed either mechanically or chemically.
Factors that may hinder the spread of staining:
• tissue density
• porosity of the tissue
• lipid amount in the tissue
• concentration and gradients of staining molecules in the tissue
Scope of work:
We are looking for a talented student in the biomedical, chemical, biological, health science (or similar) field who would like to contribute to the development of our innovative technique to improve 3D histology for cancer diagnosis. The overall goal of the project is to develop an automated, rapid and efficient platform for 3D histopathology. You will work in an interdisciplinary, young and dynamic environment in collaboration with other students and supervisors. You will be expected to help solve the problem of limited penetration of cancer staining molecules into human biopsy or postmortem tissue by thinking of innovative solutions in chemistry, physics, mechanics, etc. If successful, your contribution will help enable our platform to be launched in the market as we will be able to solve the challenge of incomplete and slow labeling of tissue in its three dimensions.
Specific tasks
• Studying and testing possible ways of improving tissue permeability and staining penetration to get better efficiency and speed for 3D staining
• Performing experiments (tissue clearing, tissue staining, testing parameters)
Challenges: Finding a solution to improve and speed-up the penetration and diffusion of staining molecules into biological tissue. The 3D staining we have achieved so far with the injection and PEF technique is still not optimal and requires a more in-depth study of how to speed up the penetration of the staining solution and improve its diffusion within the tissue. This can be addressed either mechanically or chemically. Factors that may hinder the spread of staining: • tissue density • porosity of the tissue • lipid amount in the tissue • concentration and gradients of staining molecules in the tissue Scope of work: We are looking for a talented student in the biomedical, chemical, biological, health science (or similar) field who would like to contribute to the development of our innovative technique to improve 3D histology for cancer diagnosis. The overall goal of the project is to develop an automated, rapid and efficient platform for 3D histopathology. You will work in an interdisciplinary, young and dynamic environment in collaboration with other students and supervisors. You will be expected to help solve the problem of limited penetration of cancer staining molecules into human biopsy or postmortem tissue by thinking of innovative solutions in chemistry, physics, mechanics, etc. If successful, your contribution will help enable our platform to be launched in the market as we will be able to solve the challenge of incomplete and slow labeling of tissue in its three dimensions.
Specific tasks • Studying and testing possible ways of improving tissue permeability and staining penetration to get better efficiency and speed for 3D staining • Performing experiments (tissue clearing, tissue staining, testing parameters)