Digital pathology at UMC: A step toward more accurate diagnosis

In modern medicine, accurate and timely diagnosis plays a pivotal role in effective treatment. Digital pathology is becoming an inevitable trend, bringing significant advances in diagnostic practice. At University Medical Center Ho Chi Minh City (UMC), this advanced technology not only optimizes workflows but also enhances the reliability of test results, helping deliver maximum benefits to patients.

1. Introduction to digital pathology

1.1. Definition and importance

Digital pathology (DP) is the process of converting traditional histopathology slides into high-resolution digital formats [1, 2]. Instead of using optical microscopes, pathologists can examine, analyze, and share digital images of entire glass slides through whole slide imaging (WSI) on dedicated computer screens [1, 3]. This transformation is significant in modern medicine, helping improve the accuracy, efficiency, and accessibility of histopathological diagnostic services [1].

1.2. The transition from traditional to digital pathology

For more than a century, traditional pathology has relied on examining glass slides under a microscope [2]. Although effective, this approach has inherent limitations, including the need for physical storage and transportation of slides, time-consuming case preparation and review, and limited access to specialists in remote or resource-limited areas [3, 4].

The advent of the digital era has provided a revolutionary solution to these limitations. WSI technology uses sophisticated scanners to create comprehensive digital replicas of entire glass slides [2, 5]. These digitized images recreate the experience of using a conventional microscope, allowing pathologists to zoom in and out and navigate specimens digitally at different magnifications [2, 5]. This transition not only optimizes diagnostic workflows but also opens up new possibilities for analyzing and sharing pathological information [1, 3].

2. Benefits of digital pathology

The adoption of digital pathology offers numerous significant benefits, positively affecting multiple aspects of medical practice.

2.1. Improving diagnostic accuracy and efficiency

Digital pathology significantly improves diagnostic accuracy and efficiency. By digitizing slides, pathologists can analyze high-resolution images and detect minute details that may be overlooked under conventional microscopes [1, 3]. Integrated image analysis tools, including artificial intelligence (AI) and machine learning (ML), can help identify pathological features, quantify biomarkers, and classify cellular structures with greater reliability, reducing interobserver variability [2, 3]. One study reported that AI systems could achieve an accuracy of up to 99.45% in classifying certain types of cancer [6].

2.2. Enhancing accessibility and remote consultation (telepathology)

Telepathology is one of the most prominent benefits of digital pathology, enabling pathologists to consult and diagnose remotely without geographical limitations [1, 3]. This is particularly important in rural areas or locations with a shortage of specialists, helping ensure that patients everywhere can access high-quality diagnostic services [3, 7]. Consultations can take place rapidly, even in real time, accelerating treatment decisions, especially in urgent cancer cases [7].

2.3. Applying artificial intelligence (AI) to analysis and prediction

The integration of AI with digital pathology has ushered in a new era in medical diagnostics. AI algorithms can analyze large volumes of data, detect complex patterns, and generate insights that extend beyond human capabilities [1, 3, 8]. AI can automate repetitive tasks such as cell counting, tissue segmentation, and identification of pathological features, reducing workloads and improving efficiency for pathologists [2, 3].

Some notable AI applications include:

Image recognition and classification: AI can analyze cellular structures and detect subtle changes that may indicate pathological conditions [1].
Analyzing specimens for abnormalities: AI algorithms can identify abnormal patterns that may be overlooked by the human eye, such as in the diagnosis of skin cancer [1].
Predictive and prognostic modeling: AI can predict disease progression by analyzing associations between cellular characteristics and patient outcomes, supporting personalized treatment decisions [1].

2.4. Optimizing workflows and reducing turnaround time

Digital pathology optimizes workflows in pathology laboratories. Digitization eliminates the need to manage and transport physical slides, saving time and reducing costs [3, 4]. Digital slides can be stored electronically, retrieved easily, and shared, substantially improving workflow efficiency [1, 2]. One study found that digital pathology significantly reduced case review time, saving an average of 38–71 seconds per case [1].

3. Implementing digital pathology at academic medical centers

Implementing digital pathology at major medical centers such as University Medical Center Ho Chi Minh City (UMC) requires a systematic process and substantial investment.

3.1. Infrastructure and system integration

Successful implementation of digital pathology requires appropriate digital infrastructure, including:

Whole slide scanners: These are the core devices used to convert physical slides into high-resolution digital images [2, 3].
Image management and storage systems: Because WSI image files are very large, robust storage solutions—on servers or in the cloud—and image management systems are needed to ensure easy retrieval [3, 5].
Dedicated displays and computers: Pathologists require high-resolution monitors and powerful computers to view and analyze digital images [3].
Information technology (IT) network infrastructure: High-speed internet connectivity and sufficient bandwidth are necessary to transmit and access image data efficiently [3].
Integration with the laboratory information system (LIS): Seamless integration of digital pathology with the LIS helps synchronize patient data and make it readily accessible, optimizing workflows [1].

3.2. The whole slide imaging (WSI) process

The WSI process involves several key steps:

Specimen preparation: Tissue specimens are processed, thinly sectioned, and stained on glass slides, following a process similar to conventional pathology [2].
Slide scanning: The slides are then placed in a WSI scanner. The scanner captures thousands of small, high-magnification images and stitches them together into a single digital image of the entire slide [2, 5].
Quality control: The digital images are checked to ensure that they are free of defects such as blurring, out-of-focus areas, or missing tissue regions [1].

3.3. Quality assurance and error management

Quality assurance is essential in digital pathology. Laboratories need to establish a quality assurance program (QAP) and conduct continuous quality control (QC) throughout the digitization process [1]. This includes:

Pre-scanning checks: Ensure that slides are clean and dry, barcodes are legible, and coverslips are properly positioned [1].
Post-scanning checks: Approximately 10% of digital slides are reviewed to detect defects such as blurring or artifacts. If errors are identified, the slides are rescanned [1].
Pathologist feedback: Pathologists can report low-quality slides and request rescanning or review using a conventional microscope [1].

4. Who can benefit from digital pathology?

Digital pathology benefits a wide range of users and fields in medicine.

4.1. Primary diagnosis

Digital pathology is increasingly used for primary histopathological diagnosis [3]. Pathologists can review and diagnose specimens directly from digital images, eliminating the need for optical microscopes [3]. This can accelerate diagnosis, particularly in urgent cases [1]. However, the transition requires time for adaptation and training so that pathologists can become comfortable and confident diagnosing in a digital environment [3].

4.2. Interdisciplinary consultation and multidisciplinary team (MDT) meetings

Digital pathology systems facilitate both in-house and remote consultations [3]. Pathologists can easily share digital images with colleagues to obtain second opinions or collaborate on complex cases without being limited by physical distance [1, 7]. During multidisciplinary team (MDT) meetings, WSI images allow specialists from different fields—including pathology, radiology, surgery, and oncology—to review and discuss patient cases together and make optimal management decisions [3].

4.3. Medical research and education

Digital pathology is an invaluable tool for medical research and education.

Research: Digitized slides create large datasets that can be used to train machine learning algorithms, develop new biomarkers, and improve understanding of disease mechanisms [2]. Combining digital pathology with omics data, including genomics and proteomics, provides a more comprehensive view of disease and paves the way for personalized medicine [2, 3].
Education: Medical students and trainees can access extensive libraries of digital slides, including rare cases, from anywhere in the world [2, 7]. This enhances the learning experience and prepares them to face a wide range of diagnostic challenges [2].

5. Strengths of University Medical Center Ho Chi Minh City (UMC) in digital pathology

As one of Vietnam’s leading hospitals, University Medical Center Ho Chi Minh City (UMC) continues to invest in and develop advanced medical technologies, including digital pathology. Although current research literature does not directly address UMC, its role and standing as a major medical center suggest several important strengths in this field.

Investment in advanced technology and modern equipment

As a major and reputable medical center, UMC places strong emphasis on investing in modern medical equipment, including high-quality WSI scanners and robust computer and IT network infrastructure to support digital pathology. Advanced digital infrastructure provides a foundation for effectively implementing digital diagnostic solutions, ensuring image quality and rapid processing to meet growing diagnostic demands [1, 3].

A team of highly trained specialists

UMC focuses on the training and professional development of its medical staff. As digital pathology continues to advance, pathologists at UMC are expected to acquire the knowledge and skills needed to work with digital systems, including the use of image-viewing software, data analysis, and integration of AI tools into diagnostic workflows [1, 3]. A well-trained team of specialists is essential to realizing the full potential of this technology.

Commitment to improving diagnostic quality and patient care

With a mission to provide high-quality healthcare services, UMC is committed to adopting advanced solutions such as digital pathology to improve diagnostic quality and treatment effectiveness. Implementing digital pathology can help UMC shorten diagnostic turnaround times, improve accuracy, facilitate specialized consultations, and support personalized treatment, thereby achieving better patient outcomes [2, 3]. UMC also has the potential to take a leading role in advancing digital pathology research and education in Vietnam, contributing to the overall development of the country’s medical sector.

6. The future and prospects of digital pathology

Digital pathology is advancing rapidly and promises significant developments in the future.

6.1. Advances in AI and automation

The future of digital pathology will see further advances in AI algorithms. As more data become available, AI systems will not only help detect abnormalities but also predict disease progression with greater accuracy [1]. AI will continue to automate routine tasks, allowing pathologists to focus on more complex cases [2].

6.2. Integration with electronic health records (EHRs) and personalized medicine

Integrating digital pathology with electronic health records (EHRs) is an important step toward delivering comprehensive patient care [1, 3]. When pathological data are combined with medical histories, clinicians can gain a more complete understanding of a patient’s condition [1]. This will enable interactive systems that support seamless, real-time data exchange and provide comprehensive insights into each patient’s healthcare journey [1].

Digital pathology plays a pivotal role in personalized medicine. By leveraging AI’s predictive capabilities and integrating EHR data, healthcare providers can tailor treatment plans to individual patients based on their pathological characteristics and comprehensive medical histories [1, 3].

6.3. Challenges and ethical considerations

Despite its many benefits, implementing digital pathology also presents several challenges:

High initial costs: Investing in WSI scanners, data storage, and IT infrastructure can require substantial upfront expenditure [2, 3].
Big data management: The enormous size of digital image files requires robust data management solutions for efficient storage and retrieval [3].
Standardization and interoperability: The lack of uniform standards for image formats and data protocols can make integration across different systems and organizations difficult [2, 3].
Training and skills development: Pathologists need training to use digital tools effectively and interpret information generated by AI [1, 3].
Ethical and legal issues: Data privacy, patient consent, responsible use of AI, and legal liability in cases of diagnostic error are important challenges that need to be addressed [1, 3].

7. Frequently asked questions (FAQ)

What is digital pathology? Digital pathology is the process of digitizing traditional histopathology slides into high-resolution digital images, allowing them to be viewed, analyzed, and shared on computers instead of using optical microscopes [1, 2].
Will digital pathology completely replace traditional microscopes? At present, digital pathology supports and complements traditional microscopy rather than replacing it entirely. Although it offers many advantages, certain cases or image features may still require examination under an optical microscope [1, 3].
How does AI help with digital pathology? AI automates repetitive tasks, improves diagnostic accuracy by detecting complex patterns, supports biomarker quantification, and provides models for predicting disease prognosis [1, 2].
How do patients benefit from digital pathology? Patients may benefit from faster diagnosis, greater accuracy, easier access to remote expert opinions, and personalized treatment plans supported by comprehensive data integration [1, 3].
How has UMC implemented digital pathology? As a leading hospital, University Medical Center Ho Chi Minh City (UMC) invests in modern infrastructure, trains specialists, and applies standardized processes for slide digitization, AI integration, and telepathology to improve diagnostic quality and patient care [1, 3].

8. References

[1] Kiran, N., Sapna, FNU., Kiran, FNU. et al. (2023). Digital Pathology: Transforming Diagnosis in the Digital Age. Cureus, 15(9). https://pmc.ncbi.nlm.nih.gov/articles/PMC10547926/.
[2] Fatima, G., Alhmadi, H., Mahdi, A.A., Hadi, N., Fedacko, J., Magomedova, A., Parvez, S., Raza, A.M. (2024). Transforming Diagnostics: A Comprehensive Review of Advances in Digital Pathology. Cureus, 16(10). https://pmc.ncbi.nlm.nih.gov/articles/PMC11573928/.
[3] Hanna, M.G., Ardon, O. (2023). Digital pathology systems enabling quality patient care. Genes Chromosomes Cancer, 62(11), 685–697. https://pmc.ncbi.nlm.nih.gov/articles/PMC11265285/.
[4] Jahn, S.W., Plass, M., Moinfar, F. (2020). Digital Pathology: Advantages, Limitations and Emerging Perspectives. J Clin Med, 9(11):3697. https://pmc.ncbi.nlm.nih.gov/articles/PMC7698715/.
[5] Iwuajoku, V., Ekici, K., Haas, A. et al. (2025). An equivalency and efficiency study for one year digital pathology for clinical routine diagnostics in an accredited tertiary academic center. Virchows Arch 487, 3–12. https://pmc.ncbi.nlm.nih.gov/articles/PMC12289765/.
[6] Battazza, A., Brasileiro, F.C.d.S., Tasaka, A.C., Bulla, C., Ximenes, P.P., Hosomi, J.E., da Silva, P.F., da Silva, L.F., de Moura, F.B.C., Rocha, N.S. (2024). Integrating telepathology and digital pathology with artificial intelligence: An inevitable future. Vet World, 17(8), 1667–1671. https://pmc.ncbi.nlm.nih.gov/articles/PMC11422627/.
[7] Cocuz, I.G., Niculescu, R., Popelea, M.C., Cocuz, M.E., Sabău, A.H., Tinca, A.C., Cozac-Szoke, A.R., Chiorean, D.M., Budin, C.E., Cotoi, O.S. (2025). Current Trends and Future Directions of Digital Pathology and Artificial Intelligence in Dermatopathology: A Scientometric-Based Review. Diagnostics (Basel), 15(17):2196. https://pmc.ncbi.nlm.nih.gov/articles/PMC12428701/.
[8] Singh, N.N., Tandon, A., Jayasankar, P. (2025). Strength, weakness, opportunities and challenges (SWOC) experience of histopathology image analysis, enhanced by artificial intelligence. J Oral Biol Craniofac Res, 15(5), 1057–1063. https://pmc.ncbi.nlm.nih.gov/articles/PMC12305316/.

The information above is for reference purposes only and is not intended as medical advice. Please contact your doctor for detailed medical consultation.