A literature analysis of publications about digital pathology

Authors

Abstract

Aim Systems structured to transfer pathology slides, associated metadata, their storage, review, analysis, and enabling infrastructure into a digital platform are called Digital Pathology (DP). Our aim is to guide pathologists with a scientometric analysis of DP articles.
Materials and Methods The term “Digital pathology” to the Web of Science® (WoS, Thomson Reuters, New York, NY) Scientific Database as of August 15th, 2024. Publications, number of citations, countries, journals, document types, top authors, languages, funding agencies, and affiliations were determined.
Results The USA is the leading country in terms of both the number of publications and the number of citations. Laboratory Investigation was the most productive journal. The majority of the published articles were original articles. Pantanowitz L. published the largest number of articles. The majority of the articles were published in English.
Discussion Digital pathology literature is rapidly growing in parallel with the technological development in this field. Digital pathology has the potential to shape the future of today’s pathology. Scientometric analyses may help researchers understand this transformation from conventional methods to digital platforms.

Keywords

Introduction

The Digital Pathology Association defines Digital Pathology (DP) as an inclusive term that includes tools and systems structured to transfer pathology slides, associated metadata, their storage, review, analysis, and enabling infrastructure into a digital platform [1]. In modern pathology, DP is increasingly valuable and has been a requirement within the laboratory environment. Thanks to advances in computer systems and faster networks, pathologists now have the advantage of managing digital slide images with more ease and flexibility [2]. A combination of the acquisition, management, sharing, and interpretation of pathological data, including slides, in a digital environment is possible with DP. Whole-slide imaging scanners (WSI)- along with their improving technology- are commonly used for this purpose [3]. With the development of WSI, entire slides can be imaged and stored at high resolution permanently. So, the images can be stored and transferred for telepathology and clinical use [2, 4].
In other words, DP is a novel sub-field of pathology which allows involves capturing and analysing histopathology images generated from glass slides with scanners [5]. With developing technology, DP is integrated into clinical practice with expanding datasets, novel system algorithms, and innovative applications [6]. As DP use spreads, the diagnostic process is digitized and errors caused by human observation may be minimized. Also, protocols for oncological patients may be optimized [7].
Rapidly growing information may become a challenge for physicians in their willingness to research through an increasingly large body of literature [6]. The peer-reviewed literature is growing at an unprecedented speed, with articles published in various leading medical and related journals [8]. Particularly, in terms of DP, publications increase yearly [9].
Investigation of scientific literature may help improve public health. A useful method for literature analysis is scientometrics, also known as “Science of science”. It allows researchers to recognize gaps and a lack of knowledge in a specific field of science. Considering the increasing number of publications on DP, scientometric analysis may also help identify the different research areas and determine the most frequently cited publication in this rapidly growing field [10]. In this study, we aimed to perform a comprehensive investigation of DP literature and guide researchers for further studies in this field.

Materials and Methods

For this scientometric analysis, we entered the keyword “Digital pathology” into the Web of Science® (WoS, Thomson Reuters, New York, NY) Scientific Database as of August 15th, 2024. We preferred WoS as our main data source because it provides data analysis for publications and citations, and allows the results to be sorted according to the number of citations. Web of Science allows scientists to use its data for scientific purposes. In addition, WoS attribution data are considered more reproducible and reliable than other databases, and WoS is used as a standard by certain official organizations. This platform also enables researchers to obtain scientometric and statistical information on a specific subject. All literature data of the indexed documents were downloaded from the WoS database using the export option for scientometric network analysis, and text files were created to be processed in the VOSviewer literature analysis section.
All articles in the database were manually scanned and analyzed.
All articles relevant to the topic were included in the study. WoS is the standard database for citation analyses, as it provides more details compared with other medical databases. Then, the publications were arranged according to the number of citations. The publications were filtered according to countries, journals, document types, top authors, languages, funding agencies, and affiliations.
The data was entered into the Microsoft Excel® Program for analysis. The data was given as numbers and percentages.
And then, we also determined the top 10 mostly cited articles and analyzed them according to article information, category and study design, country, and number of times cited. Titles, abstracts, and full-texts of the articles were investigated and analyzed.
Ethical Approval
No ethical approval is needed due to the scientometric nature of the study. No animal or human studies were carried out by the authors for this article.

Results

A total of 1440 articles were published about DP on the WoS database. Our results revealed that the USA is the leading country in terms of both the number of publications (n = 615) and the number of citations (n = 8100). However, when the number of citations per publication was calculated, Spain was at the top of the list (n = 13.6).
Laboratory Investigation journal published the most of the articles on digital pathology (n = 110, 7.6%) while Archives of Pathology Laboratory Medicine journal was the leading journal in terms of total citations (n = 879). When citations per publication were considered Histopathology journal was on top. Characteristics of the most popular journals according to digital pathology publications are given in Table 1.
The majority of the published articles were original articles (n = 549, 38.1%), followed by meeting abstracts (n = 477, 33.1%) and proceeding papers (n = 169,11,7%). In terms of authors, Pantanowitz L. was the most productive author (n = 39, 2.7%), followed by Treanor D (n = 38, 2.6%) and Madabhushi A (n = 30, 2%). English was the language mostly used by authors (n = 1403, 97.4%). German and Spanish were the next popular languages (n = 28, 1.9% and n = 4,0.2%, respectively).
National Institutes of Health, USA, and the United States Department of Health and Human Services provided the greatest financial support for digital pathology (n = 96, 6.6% for both). When affiliations were investigated, it was determined that the Pennsylvania Commonwealth System of Higher Education has done the largest number of publications (n = 71, 5.1%). Types of articles, top authors, languages, funding agencies, and affiliations are given in Table 2.
Top 10 cited articles on digital pathology are summarized in Table 3.

Discussion

Digital Pathology is a rapidly growing discipline in pathology practice and education. Literature about DP also grows in concordance with technology. Advancements in microscope technology have enabled the acquisition of WSI, increasing the use of virtual slides in histopathologic study [11]. Additionally, it has been shown that DP has numerous advantages in pathology education. In a study by Neal et al., 32 diagnoses with digital slides and 32 with light microscopy were used in an examination applied to 21 dermatology residents. It was determined that diagnostic accuracy was higher with digital pathology (22/32) when compared with light microscopy (18/32) [12]. This result demonstrates how efficiently DP will revolutionize the future of pathology. They also propose preparation of trainees not only to maintain proficiency in microscopy, but also to prepare them for a digital future [12]. Artificial intelligence combined with DP allows more accurate analysis of digital images, hence variabilities related to manual assessment may be minimized [13]. This combination has the potential to revolutionize histopathology [14]. Artificial intelligence and DP together may provide a deeper and more accurate interpretation of information within images [7].
Digital pathology can also contribute to biomarker studies for various types of cancer [15]. Pathologists should be familiar with DP since they might have inadequate experience with programming [6]. With widespread use of DP, challenges such as increased workload, case complexity, financial constraints, and staffing shortages may be minimized [16].
In a previous study, the U.S. has significant research results in digital pathology, with the top 10 publishing institutions all coming from the U.S [9]. This finding is compatible with our results that the US is the leading country in DP, and also, out of the 10 most cited articles, 6 of them are from the USA. In another study, artificial intelligence-based tumor pathology between 1999 and 2021 was investigated, and Madabhushi A. was found to be the most productive researcher [17]. In our study, Pantanowitz L. was found to be the most productive researcher, and Madabhushi A. took third place. In the aforementioned study, Harvard Medical School was the most productive institution [17]. In our study, the Pennsylvania Commonwealth System of Higher Education was found to be the institution that gave the greatest support to DP. According to our results, the USA leads DP literature in both the number of articles and institutions. Shen et al. reported that China was evolving in this field rapidly [17]. Our results revealed that China took cixth place in the number of articlec on DP. Accordingly, Şenel et al. reported that all twenty most productive institutions were from developed countries when telepathology, a subdiscipline of DP, was considered [18]. In a scientometric analysis and literature review performed in Africa, the researchers stated that innovation within the DP promises enhanced healthcare access and improved diagnostic accuracy. However, there are still numerous challenges (infrastructure deficiencies, a dearth of local expertise, and regulatory challenges) to overcome. Particularly in underdeveloped or developing countries, international support is required until they become self- sufficient in this regard [19].

Limitations

Our study has several limitations, as in other scientometric analyses. Firstly, the investigation of the DP articles does not reflect the exact situation of the literature on DP. Some alterations may occur according to different researchers in different periods since scientometric analyses have time time- dependent nature. Even though abstracts and, when necessary, full-texts of the articles were analysed independently by authors, some highly cited publications may be overlooked. There is also a possibility that the database from which the information was obtained may have left some articles out of the system. The fact that our study relies solely on WoS and possible underestimation of non-indexed but impactful literature (e.g., conference proceedings, preprints) are other limitations of our study.

Conclusion

Digital pathology is a discipline that combines digitizing histopathology slides using whole-slide scanners and the analysis of these digitized WSI using computational approaches. Even though numerous challenges exist, the implementation of artificial intelligence into DP is promising for pathologists [20]. Understanding scientometric analysis of DP may guide pathologists today and in the near future, not only for knowledge but also for determining gaps in the literature. Hence, authors can have an idea about which points they should focus on for their future studies.

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