Advances in Digital Pathology

Advances in Digital Pathology

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Research advances in technology are increasingly being utilized to automate and digitize healthcare processes. These advancements have helped speed up clinical diagnosis and treatment, thus improving patient outcomes. One such technology is digital imaging, which has transformed the field of pathology by enabling high-throughput scanning of samples collected from patients.  

The traditional way of preparing a tissue sample for pathology investigation is as follows: A histotechnologist segments the sample into thin slices and then mounts them onto glass slides. These are processed to improve the final image quality. The prepared slides are then sent to the pathologist who examines the samples under a microscope to confirm a diagnosis. 

While these steps are mostly still followed, digitization has transformed pathology and clinical research at the final step by converting the glass slide prepared for microscopy into a digitized image.

Digital pathology

What is Digital Pathology? Definition

Digital pathology is the digitization of prepared slides, which facilitates the acquisition, management, and interpretation of pathology information. The glass slides that were traditionally viewed under a microscope are now scanned to produce high-quality digital images that can be viewed on a screen. 

The microscope here is replaced by a digital pathology scanner, which captures high-definition images of a slide as a whole (whole slide imaging) and transmits the captured images directly to the pathologist's screen.

The pathologist can then share these images quickly and easily with the rest of the medical team instead of having to transport the slides from one clinical setting to another. This improves turnaround time, lab efficiency, and ultimately, patient outcomes.

Digital Pathology Scanners

A histology scanner or digital pathology scanner is a piece of equipment that can handle around 1,000 glass slides at a time, depending on their size, to capture images and transmit them to an attached computer’s screen. 

The scanners need to be stored within the lab on a countertop, where no vibrations from other lab equipment such as centrifuges or stirrers can blur the image quality. These scanners are integrated with a digital pathology camera or slide viewer, an attached monitor, and an image management system or software application. 

Digital pathology scanners can be chosen according to their routine application in the lab. For example, if a pathologist needs images with high magnification (40X), they can choose a machine that achieves a higher degree of magnification. 

Image acquisition through digital scanning is thus accelerated in digital pathology systems, improving turnaround time for clinical diagnosis and lab information management systems (LIS or LIMS). Though the diagnostic aspect remains the same, digital pathology has increased lab efficiency, decreased lab costs, and improved lab workflows. 

Today’s digital pathology scanners can capture and process images within a minute, adjust them to multiple magnifications, and handle large volumes of slides.

The best digital pathology scanner is customizable to a lab’s needs. Here are two examples of that customization that a lab can utilize:

  • complete automation (where the end-to-end process of capturing images of the whole slide to transmitting them to a computer is fully automated)
  • semi-automation (where the pathologist loads the slides and views them to manually select the best viewing regions on the slide) 

The scanner should also be compatible with the laboratory information systems so that the pathology images can be acquired, labeled, and stored automatically.

Digital pathology workflow

Digital Pathology Image Analysis Software

Through digital image analysis, pathology labs leverage artificial intelligence (AI)-based analytical tools and algorithms to improve a pathologist’s workflow and decrease human errors that may arise during sample processing. 

Analysis of acquired images is semi-automated through digital pathology software, which allows a pathologist to investigate a slide by directly annotating the digital image with measurements made within the software. 

Image acquisition management within the software and pattern analysis on digitized images enable the interpretation of pathology information for clinical diagnosis. Pathologists can evaluate and compare their diagnoses with historical data that is stored in the cloud and processed within the same image analysis software. 

Diagnostic digital pathology thus supports reproducible interpretations, empirical measurements, and increased confidence in the pathologist’s findings. 

Digital pathology systems

Benefits of Digital Pathology

Digital pathology systems are increasingly being adopted by anatomic pathology labs for numerous reasons: 

  • Taking pathology digital simplifies the process of image-sharing through digital pathology software, allowing collaborations among a team of pathologists to accelerate diagnosis times. Digital images can also be transmitted online to other team members for a second opinion. 
  • Digital pathology images can be instantly, securely, and permanently stored on the cloud. This improves accessibility for peer consults, for example, yet keeps the confidential patient information safe from theft, fire, and other events. 
  • Digital pathology solutions include analysis tools within the software that can be deployed to empirically measure, for example, levels of a specific tissue biomarker that indicates disease. 
  • Image analysis software enables robust investigation through AI-guided accurate diagnosis. Cloud storage also allows pathologists to compare their results to historical specimens, or to compare multiple specimens side-by-side, improving the predictive power of software algorithms.
  • There is no risk of misidentification since slides are labeled with a barcode that is matched to a patient’s information. 
  • Patients receive their diagnoses faster despite their increasing numbers.
  • Pathologists can improve their expertise by interacting with big data collected from the samples. 
  • A digital pathology workflow provides a foundation for automation, thus allowing pathologists to implement better flexibility in their work schedules. 
  • The image acquisition software and workflow can be integrated into the laboratory’s information management system (LIS or LIMS).
  • A secure digital archive of the patient’s sample is kept instead of having to keep a slide or frozen section that takes up valuable physical storage space.
  • Physical samples are subject to degradation whereas digital ones are not.

The Future of Digital Pathology

The U.S. healthcare system is facing increasing challenges due to the sheer volume of data that is generated during diagnostic processes. 

Sophisticated and innovative digital pathology solutions are needed to cope with the increasing demands of hospitals’ diagnostic workflows. Advances in machine learning and big data processing will be increasingly incorporated into many areas, including diagnostic digital pathology. Complex image analyses, such as multiplex analysis (which measures more than one marker within the same tissue sample), can be deployed by digital pathology solutions to delineate signal intensities between different markers. This kind of quantitation is difficult to achieve manually, under the microscope, due to the diffusion of some stains specific to different markers in a tissue sample. 

Another exciting prospect for digital pathology systems lies in their potential to be combined with other clinical diagnostic methods to improve the prognostic value of a diagnosis. For example, the read-out of a biomarker expression calculated by a digital pathology image analysis software can be compared with protein expression levels calculated from a mass spectrometric analysis of the same tissue sample. This allows diversification in diagnostic tools that can complement one other’s functionalities to improve the clinical diagnosis workflow. 

Finally, the availability of image acquisition management systems, coupled with the rapid strides being made in regulatory policies for data sharing, both offer exciting prospects. Digital pathology has ushered in a positive change from the classical methods with computer-based virtual microscopy, cloud-based data storage, and the many tools available that use AI and machine learning to support pathologists in their work.

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