The Landscape of Digital Pathology in Transplantation: From the Beginning to the Virtual E-Slide

Digital dermatopathology implementation: Experience at a multisite academic institution

BACKGROUND

Technology has revolutionized not only direct patient care but also diagnostic care processes. This study evaluates the transition from glass-slide microscopy to digital pathology (DP) at a multisite academic institution, using mixed methods to understand user perceptions of digitization and key productivity metrics of practice change.

METHODS

Participants included dermatopathologists, pathology reporting specialists, and clinicians. Electronic surveys and individual or group interviews included questions related to technology comfort, trust in DP, and rationale for DP adoption. Case volumes and turnaround times were abstracted from the electronic health record from Qtr 4 2020 to Qtr 1 2023 (inclusive). Data were analyzed descriptively, while interviews were analyzed using methods of content analysis.

RESULTS

Thirty-four staff completed surveys and 22 participated in an interview. Case volumes and diagnostic turnaround time did not differ across the institution during or after implementation timelines (p = 0.084; p = 0.133, respectively). 82.5% (28/34) of staff agreed that DP improved the sign-out experience, with accessibility, ergonomics, and annotation features described as key factors. Clinicians reported positive perspectives of DP impact on patient safety and interdisciplinary collaboration.

CONCLUSIONS

Our study demonstrates that DP has a high acceptance rate, does not adversely impact productivity, and may improve patient safety and care collaboration.

Whole Slide Imaging Technology and Its Applications: Current and Emerging Perspectives

Background. Whole slide imaging (WSI) represents a paradigm shift in pathology, serving as a necessary first step for a wide array of digital tools to enter the field. It utilizes virtual microscopy wherein glass slides are converted into digital slides and are viewed by pathologists by automated image analysis. Its impact on pathology workflow, reproducibility, dissemination of educational material, expansion of service to underprivileged areas, and institutional collaboration exemplifies a significant innovative movement. The recent US Food and Drug Administration approval to WSI for its use in primary surgical pathology diagnosis has opened opportunities for wider application of this technology in routine practice. Main Text. The ongoing technological advances in digital scanners, image visualization methods, and the integration of artificial intelligence-derived algorithms with these systems provide avenues to exploit its applications. Its benefits are innumerable such as ease of access through the internet, avoidance of physical storage space, and no risk of deterioration of staining quality or breakage of slides to name a few. Although the benefits of WSI to pathology practices are many, the complexities of implementation remain an obstacle to widespread adoption. Some barriers including the high cost, technical glitches, and most importantly professional hesitation to adopt a new technology have hindered its use in routine pathology. Conclusions. In this review, we summarize the technical aspects of WSI, its applications in diagnostic pathology, training, and research along with future perspectives. It also highlights improved understanding of the current challenges to implementation, as well as the benefits and successes of the technology. WSI provides a golden opportunity for pathologists to guide its evolution, standardization, and implementation to better acquaint them with the key aspects of this technology and its judicial use. Also, implementation of routine digital pathology is an extra step requiring resources which (currently) does not usually result increased efficiency or payment.

The Puzzle of Preimplantation Kidney Biopsy Decision-Making Process: The Pathologist Perspective

Kidney transplantation is the best treatment for end-stage renal disease since it offers the greatest survival benefit compared to dialysis. The gap between the number of renal transplants performed and the number of patients awaiting renal transplants leads to a steadily increasing pressure on the scientific community. Kidney preimplantation biopsy is used as a component of the evaluation of organ quality before acceptance for transplantation. However, the reliability and predictive value of biopsy data are controversial. Most of the previously proposed predictive models were not associated with graft survival, but what has to be reaffirmed is that histologic examination of kidney tissue can provide an objective window on the state of the organ that cannot be deduced from clinical records and renal functional studies. The balance of evidence indicates that reliable decisions about donor suitability must be made based on the overall picture. This work discusses recent trends that can reduce diagnostic timing and variability among players in the decision-making process that lead to kidney transplants, from the pathologist's perspective.

Histology for nephrology, from pre-implantation to post-transplant kidney biopsy. Lesson learned from ReBIrth (Renal BIopsy for Kidney Transplantation Therapy)

A meeting entitled Renal BIopsy for Kidney Transplantation Therapy (ReBIrth) took place on May 31st, 2022 in Bologna, Italy. The meeting drew together nephrologists, surgeons, and pathologists and recognized as experts in the field of kidney transplantation in Italy. In this paper, we present our experience working with kidney transplants in the current era of immunosuppression therapy. The primary aim is to report the histopathological characteristics of failed kidney allografts after a consensus of experts reviewed the cases on a wholeslide imaging digital platform. Regardless of the cases discussed, digital pathology was reliable in identifying all the morphological and immunohistochemical features required to improve the correct use of immunosuppressive therapy to prevent graft failure and optimize patient management.

European Society for Organ Transplantation (ESOT)-TLJ 3.0 Consensus on Histopathological Analysis of Pre-Implantation Donor Kidney Biopsy: Redefining the Role in the Process of Graft Assessment

The ESOT TLJ 3.0. consensus conference brought together leading experts in transplantation to develop evidence-based guidance on the standardization and clinical utility of pre-implantation kidney biopsy in the assessment of grafts from Expanded Criteria Donors (ECD). Seven themes were selected and underwent in-depth analysis after formulation of PICO (patient/population, intervention, comparison, outcomes) questions. After literature search, the statements for each key question were produced, rated according the GRADE approach [Quality of evidence: High (A), Moderate (B), Low (C); Strength of Recommendation: Strong (1), Weak (2)]. The statements were subsequently presented in-person at the Prague kick-off meeting, discussed and voted. After two rounds of discussion and voting, all 7 statements reached an overall agreement of 100% on the following issues: needle core/wedge/punch technique representatively [B,1], frozen/paraffin embedded section reliability [B,2], experienced/non-experienced on-call renal pathologist reproducibility/accuracy of the histological report [A,1], glomerulosclerosis/other parameters reproducibility [C,2], digital pathology/light microscopy in the measurement of histological variables [A,1], special stainings/Haematoxylin and Eosin alone comparison [A,1], glomerulosclerosis reliability versus other histological parameters to predict the graft survival, graft function, primary non-function [B,1]. This methodology has allowed to reach a full consensus among European experts on important technical topics regarding pre-implantation biopsy in the ECD graft assessment.

Validation of Remote Digital Pathology based diagnostic reporting of Frozen Sections from home

Background

Despite the promising applications of whole-slide imaging (WSI) for frozen section (FS) diagnosis, its adoption for remote reporting is limited.

Objective

To assess the feasibility and performance of home-based remote digital consultation for FS diagnosis.

Material & Method

Cases accessioned beyond regular working hours (5 pm-10 pm) were reported simultaneously using optical microscopy (OM) and WSI. Validation of WSI for FS diagnosis from a remote site, i.e. home, was performed by 5 pathologists. Cases were scanned using a portable scanner (Grundium Ocus®40) and previewed on consumer-grade computer devices through a web-based browser (http://grundium.net). Clinical data and diagnostic reports were shared through a google spreadsheet. The diagnostic concordance, inter- and intra-observer agreement for FS diagnosis by WSI versus OM, and turnaround time (TAT), were recorded.

Results

The overall diagnostic accuracy for OM and WSI (from home) was 98.2% (range 97%-100%) and 97.6% (range 95%-99%), respectively, when compared with the reference standard. Almost perfect inter-observer (k = 0.993) and intra-observer (k = 0.987) agreement for WSI was observed by 4 pathologists. Pathologists used consumer-grade laptops/desktops with an average screen size of 14.58 inches (range = 12.3-17.7 inches) and a network speed of 64 megabits per second (range: 10-90 Mbps). The mean diagnostic assessment time per case for OM and WSI was 1:48 min and 5:54 min, respectively. Mean TAT of 27.27 min per case was observed using WSI from home. Seamless connectivity was observed in approximately 75% of cases.

Conclusion

This study validates the role of WSI for remote FS diagnosis for its safe and efficient adoption in clinical use.

Digital Slide and Simulation-Based Learning in Pre-Implantation Kidney Biopsies

Although controversial, procurement kidney biopsies and histology are commonly used in kidney allocation from deceased donors. The long series of models developed for this question, incorporating a variety of clinical and histologic variables, failed to properly predict the long-term graft survival. This failure could be explained by many factors, including the lack of expertise in terms of skilled available nephropathologists in the urgent setting of biopsies assessment. Simulation-based learning is a form of experiential learning that provides learners with a real-world-like opportunity to develop and practice their knowledge and skills but in a simulated environment. Digital pathology with whole-slide imaging is a powerful tool for knowledge delivering, as it offers the opportunity to facilitate meeting of general pathologists with experts, with availability of second opinion consultation and tailored training on specific cases. In the back of these considerations, we report on the content of the web-meeting “Digital slide and simulation-based learning in pre-implantation kidney” which was fully dedicated to the evaluation of pre-implantation kidney biopsy, with a very practical approach and a direct interaction between two expert renal transplant pathologists and the audience of general pathologists.

Application of digital pathology and machine learning in the liver, kidney and lung diseases

The development of rapid and accurate Whole Slide Imaging (WSI) has paved the way for the application of Artificial Intelligence (AI) to digital pathology. The availability of WSI in the recent years allowed the rapid development of various AI technologies to blossom. WSI-based digital pathology combined with neural networks can automate arduous and time-consuming tasks of slide evaluation. Machine Learning (ML)-based AI has been demonstrated to outperform pathologists by eliminating inter- and intra-observer subjectivity, obtaining quantitative data from slide images, and extracting hidden image patterns that are relevant to disease subtype and progression. In this review, we outline the functionality of different AI technologies such as neural networks and deep learning and discover how aspects of different diseases make them benefit from the implementation of AI. AI has proven to be valuable in many different organs, with this review focusing on the liver, kidney, and lungs. We also discuss how AI and image analysis not only can grade diseases objectively but also discover aspects of diseases that have prognostic value. In the end, we review the current status of the integration of AI in pathology and share our vision on the future of digital pathology.

Perspective of a Pathologist on Benchmark Strategies for Artificial Intelligence Development in Organ Transplantation

Transplant pathology of donors is a highly specialized field comprising both the evaluation of organ donor biopsy for the oncological risk transmission and to guide the organ allocation. Timing is critical in transplant procurement since organs must be recovered as soon as possible to ensure the best possible outcome for the recipient. To all this is added the fact that the evaluation of a donor causes difficulties in many cases and the impact of these assessments is paramount, considering the possible recovery of organs that would have been erroneously discarded or, conversely, the possibly correct discarding of donors with unacceptable risk profiles. In transplant pathology histology is still the gold standard for diagnosis dictating the subsequent decisions and course of clinical care. Digital pathology has played an important role in accelerating healthcare progression and nowadays artificial intelligence powered computational pathology can effectively improve diagnostic needs, supporting the quality and safety of the process. Mapping the shape of the journey would suggest a progressive approach from supervised to semi/unsupervised models, which would involve training these models directly for clinical endpoints. In machine learning, this generally delivers better performance, compensating for a potential lack in interpretability. With planning and enough confidence in the performance of learning-based methods from digital pathology and artificial intelligence, there is great potential to augment the diagnostic quality and correlation with clinical endpoints. This may improve the donor pool and vastly reduce diagnostic and prognostic errors that are known but currently are unavoidable in transplant donor pathology.

The Independent Effects of Procurement Biopsy Findings on Ten-Year Outcomes of Extended Criteria Donor Kidney Transplants

Introduction

Methods

Results

Conclusion

Computer-assisted evaluation enhances the quantification of interstitial fibrosis in renal implantation biopsies, measures differences between frozen and paraffin sections, and predicts delayed graft function

Background

(Pre-)Implantation biopsies provide important data on the quality of donor kidneys. Interstitial fibrosis, as a known predictor for kidney disease progression, is an essential feature of this evaluation. However, the assessment of frozen sections of implantation biopsies is challenging and can result in the disposal of candidate organs. We sought to apply digital image analysis (DIA) to quantify the differences between frozen and paraffin sections when evaluating interstitial fibrosis, identify factors that influence these variations and test the predictive value of the computerised measures.

Methods

We quantified the differences between frozen and paraffin sections in the same biopsy samples by measuring Sirius red-stained interstitial areas (SRIA) in DIA. We compared them to the original reports, and retrospectively correlated our findings to clinical data, graft function and outcome in 73 patients.

Results

Frozen sections display a broader interstitial area than paraffin sections, in some cases up to one-third more (mean difference + 7.8%, range − 7 to 29%). No donor-related factors (age or gender, cold ischemia time, or non-heart-beating donor) influenced significantly this difference. Compared to the original assessment of frozen vs paraffin sections in optical microscopy, the DIA of interstitial fibrosis shows a higher consistency (ICC 0.69). Our approach further allows to distinguish SRIA in paraffin sections as an independent predictor for delayed graft function (OR = 1.1; p = 0.028).

Conclusions

DIA is superior to and more consistent than routine optic microscopy for interstitial fibrosis evaluation. This method could improve implantation biopsy diagnostics and help to reduce disposal of organs.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s40620-022-01315-y.

Artificial intelligence applications for pre-implantation kidney biopsy pathology practice: a systematic review

BACKGROUND

Transplant nephropathology is a highly specialized field of pathology comprising both the evaluation of organ donor biopsy for organ allocation and post-transplant graft biopsy for assessment of rejection or graft damage. The introduction of digital pathology with whole-slide imaging (WSI) in clinical research, trials and practice has catalyzed the application of artificial intelligence (AI) for histopathology, with development of novel machine-learning models for tissue interrogation and discovery. We aimed to review the literature for studies specifically applying AI algorithms to WSI-digitized pre-implantation kidney biopsy.

METHODS

A systematic search was carried out in the electronic databases PubMed-MEDLINE and Embase until 25th September, 2021 with a combination of the key terms "kidney", "biopsy", "transplantation" and "artificial intelligence" and their aliases. Studies dealing with the application of AI algorithms coupled with WSI in pre-implantation kidney biopsies were included. The main theme addressed was detection and quantification of tissue components. Extracted data were: author, year and country of the study, type of biopsy features investigated, number of cases, type of algorithm deployed, main results of the study in terms of diagnostic outcome, and the main limitations of the study.

RESULTS

Of 5761 retrieved articles, 7 met our inclusion criteria. All studies focused largely on AI-based detection and classification of glomerular structures and to a lesser extent on tubular and vascular structures. Performance of AI algorithms was excellent and promising.

CONCLUSION

All studies highlighted the importance of expert pathologist annotation to reliably train models and the need to acknowledge clinical nuances of the pre-implantation setting. Close cooperation between computer scientists and practicing as well as expert renal pathologists is needed, helping to refine the performance of AI-based models for routine pre-implantation kidney biopsy clinical practice.

Deceased Donor Procurement Biopsy Practices, Interpretation, and Histology-Based Decision Making: A Survey of U.S. Transplant Centers

Introduction

Methods

Results

Conclusion

Frozen section telepathology service: Efficiency and benefits of an e-health policy in South Tyrol

Objective/Background

Telepathology has been widely adopted to allow intraoperative pathology examinations to be performed remotely and for obtaining second opinion teleconsultation. In the Italian northern region of South Tyrol, the widespread geographical distances and consequent cost for the health system of having a travelling pathologist cover intraoperative consultations in peripheral hospitals was a key driver for the implementation of a telepathology system.

Methods

In 2010, four Menarini D-Sight whole slide scanners to digitize entire pathology slides were placed in the peripheral hospitals of Merano, Bressanone, Brunico, and in the hub hospital of Bolzano. Digital workstations were also installed to allow pathologists to remotely perform intraoperative consultations with digital slides. This study reviews the outcome after 12 years of telepathology for this intended clinical use.

Results

After an initial validation phase with 100 cases which yielded a sensitivity of 65% (CI 43–84%) and specificity of 100% (CI 95–100%), there were 2058 intraoperative consultations handled by telepathology. The cases evaluated were mainly breast sentinel lymph nodes, followed by urological, gynecological and general surgical pathology frozen section specimens. There were no false-positive cases and 165 (8%) false-negative cases, yielding an overall sensitivity and specificity of 65% (CI 61–69%) and 100% (CI 99–100%), respectively.

Conclusion

Telepathology is reliable for remote intraoperative diagnosis and, despite technical issues and initial acquaintance issues, proved beneficial for patient care in satellite hospitals, improved standardization, promoted innovation, and resulted in cost savings for the health system.

Advantages of Using a Web-based Digital Platform for Kidney Preimplantation Biopsies

Background:

In the setting of kidney transplantation, histopathology of kidney biopsies is a key element in the organ assessment and allocation. Despite the broad diffusion of the Remuzzi–Karpinski score on preimplantation kidney biopsies, scientific evidence of its correlation to the transplantation outcome is controversial. The main issues affecting the prognostic value of histopathology are the referral to general on-call pathologists and the semiquantitative feature of the score, which can raise issues of interpretation. Digital pathology has shown very reliable and effective in the oncological diagnosis and treatment; however, the spread of such technologies is lagging behind in the field of transplantation. The aim of our study was to create a digital online platform where whole-slide images (WSI) of preimplantation kidney biopsies could be uploaded and stored.

Methods:

We included 210 kidney biopsies collected between January 2015 and December 2019 from the joint collaboration of the transplantation centers of Padua and Verona. The selected slides, stained with hematoxylin and eosin, were digitized and uploaded on a shared web platform. For each case, the on-call pathologists' Remuzzi grades were obtained from the original report, together with the clinical data and the posttransplantation follow-up.

Results:

The storage of WSI of preimplantation kidney biopsies would have several clinical, scientific, and educational advantages. The clinical utility relies on the possibility to consult online expert pathologists and real-time quality checks of diagnosis. From the perspective of follow-up, the archived digitized biopsies can offer a useful comparison to posttransplantation biopsies. In addition, the digital online platform is a precious tool for multidisciplinary meetings aimed both at the clinical discussion and at the design of research projects. Furthermore, this archive of readily available WSI is an important educational resource for the training of professionals.

Conclusions:

Finally, the web platform lays the foundation for the introduction of artificial intelligence in the field of transplantation that would help create new diagnostic algorithms and tools with the final aim of increasing the precision of organ assessment and its predictive value for transplant outcome.

Variations in deceased donor kidney procurement biopsy practice patterns: A survey of U.S. organ procurement organizations

BACKGROUND

Procurement biopsies have become a common practice in the evaluation and allocation of deceased donor kidneys in the United States despite questions about their value and reproducibility. We sought to determine the extent of OPO-level differences in criteria used to decide which deceased donor kidneys undergo a procurement biopsy and to assess the degree of variability in procurement biopsy technique and interpretation across OPOs.

METHODS

Each of the country's 58 OPOs were invited to participate in the survey. OPOs were divided into two groups based on organ availability ratio and deceased donor kidney discard rate.

RESULTS AND CONCLUSIONS

Fifty-out-of-fifty-eight invited OPOs (86% response rate) responded to the survey between November 2020 and December 2020. Thirty (60%) OPOs reported that they have formal criteria for performing kidney procurement biopsy, but for 29 of these OPOs, transplant centers can request biopsy on kidneys that do not meet criteria. OPOs used a total of seven different variables and 12 different numerical thresholds to define impaired kidney function that would prompt a procurement biopsy. Additionally, wide variability was seen in biopsy technique and procedures for biopsy interpretation and reporting of findings to transplant programs. These findings identify a clear opportunity for standardization of procurement biopsies to best practices.

Resolution-based distillation for efficient histology image classification

Developing deep learning models to analyze histology images has been computationally challenging, as the massive size of the images causes excessive strain on all parts of the computing pipeline. This paper proposes a novel deep learning-based methodology for improving the computational efficiency of histology image classification. The proposed approach is robust when used with images that have reduced input resolution, and it can be trained effectively with limited labeled data. Moreover, our approach operates at either the tissue- or slide-level, removing the need for laborious patch-level labeling. Our method uses knowledge distillation to transfer knowledge from a teacher model pre-trained at high resolution to a student model trained on the same images at a considerably lower resolution. Also, to address the lack of large-scale labeled histology image datasets, we perform the knowledge distillation in a self-supervised fashion. We evaluate our approach on three distinct histology image datasets associated with celiac disease, lung adenocarcinoma, and renal cell carcinoma. Our results on these datasets demonstrate that a combination of knowledge distillation and self-supervision allows the student model to approach and, in some cases, surpass the teacher model's classification accuracy while being much more computationally efficient. Additionally, we observe an increase in student classification performance as the size of the unlabeled dataset increases, indicating that there is potential for this method to scale further with additional unlabeled data. Our model outperforms the high-resolution teacher model for celiac disease in accuracy, F1-score, precision, and recall while requiring 4 times fewer computations. For lung adenocarcinoma, our results at 1.25× magnification are within 1.5% of the results for the teacher model at 10× magnification, with a reduction in computational cost by a factor of 64. Our model on renal cell carcinoma at 1.25× magnification performs within 1% of the teacher model at 5× magnification while requiring 16 times fewer computations. Furthermore, our celiac disease outcomes benefit from additional performance scaling with the use of more unlabeled data. In the case of 0.625× magnification, using unlabeled data improves accuracy by 4% over the tissue-level baseline. Therefore, our approach can improve the feasibility of deep learning solutions for digital pathology on standard computational hardware and infrastructures.

Precision transplant pathology

PURPOSE OF REVIEW

Transplant pathology contributes substantially to personalized treatment of organ allograft recipients. Rapidly advancing next-generation human leukocyte antigen (HLA) sequencing and pathology are enhancing the abilities to improve donor/recipient matching and allograft monitoring.

RECENT FINDINGS

The present review summarizes the workflow of a prototypical patient through a pathology practice, highlighting histocompatibility assessment and pathologic review of tissues as areas that are evolving to incorporate next-generation technologies while emphasizing critical needs of the field.

SUMMARY

Successful organ transplantation starts with the most precise pratical donor-recipient histocompatibility matching. Next-generation sequencing provides the highest resolution donor-recipient matching and enables eplet mismatch scores and more precise monitoring of donor-specific antibodies (DSAs) that may arise after transplant. Multiplex labeling combined with hand-crafted machine learning is transforming traditional histopathology. The combination of traditional blood/body fluid laboratory tests, eplet and DSA analysis, traditional and next-generation histopathology, and -omics-based platforms enables risk stratification and identification of early subclinical molecular-based changes that precede a decline in allograft function. Needs include software integration of data derived from diverse platforms that can render the most accurate assessment of allograft health and needs for immunosuppression adjustments.

Digital pathology for second opinion consultation and donor assessment during organ procurement: Review of the literature and guidance for deployment in transplant practice

Telepathology has been an important application for second opinion consultation ever since the introduction of digital pathology. However, little is known regarding teleconsultation for second opinion in transplantation. There is also limited literature on telepathology during organ donor procurement, typically utilized when general pathologists on-call request back-up to help assess donor biopsies for organ suitability or to diagnose newly discovered tumors with urgent time constraints. In this review, we searched Pubmed/Embase and websites of transplant organizations to collect and analyze published evidence on teleconsultation for donor evaluation and organ procurement. Of 2725 records retrieved using the key terms 'telepathology', 'second opinion' and 'transplantation', 26 suitable studies were included. Most records were from North America and included validation studies of telepathology being used for remote frozen section interpretation of donor biopsies with whole slide imaging. The data from these published studies supports the transition towards digital teleconsultation in transplant settings where consultations among pathologists are still handled by pathologists being called on site, via telephone and/or email.

Whole Slide Imaging and Its Applications to Histopathological Studies of Liver Disorders

Histological analysis of hepatic tissue specimens is essential for evaluating the pathology of several liver disorders such as chronic liver diseases, hepatocellular carcinomas, liver steatosis, and infectious liver diseases. Manual examination of histological slides on the microscope is a classically used method to study these disorders. However, it is considered time-consuming, limited, and associated with intra- and inter-observer variability. Emerging technologies such as whole slide imaging (WSI), also termed virtual microscopy, have increasingly been used to improve the assessment of histological features with applications in both clinical and research laboratories. WSI enables the acquisition of the tissue morphology/pathology from glass slides and translates it into a digital form comparable to a conventional microscope, but with several advantages such as easy image accessibility and storage, portability, sharing, annotation, qualitative and quantitative image analysis, and use for educational purposes. WSI-generated images simultaneously provide high resolution and a wide field of observation that can cover the entire section, extending any single field of view. In this review, we summarize current knowledge on the application of WSI to histopathological analyses of liver disorders as well as to understand liver biology. We address how WSI may improve the assessment and quantification of multiple histological parameters in the liver, and help diagnose several hepatic conditions with important clinical implications. The WSI technical limitations are also discussed.