Virtual Versus Light Microscopy Usage among Students: A Systematic Review and Meta-Analytic Evidence in Medical Education

Background: The usage of whole-slide images has recently been gaining a foothold in medical education, training, and diagnosis. Objectives: The first objective of the current study was to compare academic performance on virtual microscopy (VM) and light microscopy (LM) for learning pathology, anatomy, and histology in medical and dental students during the COVID-19 period. The second objective was to gather insight into various applications and usage of such technology for medical education. Materials and methods: Using the keywords “virtual microscopy” or “light microscopy” or “digital microscopy” and “medical” and “dental” students, databases (PubMed, Embase, Scopus, Cochrane, CINAHL, and Google Scholar) were searched. Hand searching and snowballing were also employed for article searching. After extracting the relevant data based on inclusion and execution criteria, the qualitative data were used for the systematic review and quantitative data were used for meta-analysis. The Newcastle Ottawa Scale (NOS) scale was used to assess the quality of the included studies. Additionally, we registered our systematic review protocol in the prospective register of systematic reviews (PROSPERO) with registration number CRD42020205583. Results: A total of 39 studies met the criteria to be included in the systematic review. Overall, results indicated a preference for this technology and better academic scores. Qualitative analyses reported improved academic scores, ease of use, and enhanced collaboration amongst students as the top advantages, whereas technical issues were a disadvantage. The performance comparison of virtual versus light microscopy meta-analysis included 19 studies. Most (10/39) studies were from medical universities in the USA. VM was mainly used for teaching pathology courses (25/39) at medical schools (30/39). Dental schools (10/39) have also reported using VM for teaching microscopy. The COVID-19 pandemic was responsible for the transition to VM use in 17/39 studies. The pooled effect size of 19 studies significantly demonstrated higher exam performance (SMD: 1.36 [95% CI: 0.75, 1.96], p < 0.001) among the students who used VM for their learning. Students in the VM group demonstrated significantly higher exam performance than LM in pathology (SMD: 0.85 [95% CI: 0.26, 1.44], p < 0.01) and histopathology (SMD: 1.25 [95% CI: 0.71, 1.78], p < 0.001). For histology (SMD: 1.67 [95% CI: −0.05, 3.40], p = 0.06), the result was insignificant. The overall analysis of 15 studies assessing exam performance showed significantly higher performance for both medical (SMD: 1.42 [95% CI: 0.59, 2.25], p < 0.001) and dental students (SMD: 0.58 [95% CI: 0.58, 0.79], p < 0.001). Conclusions: The results of qualitative and quantitative analyses show that VM technology and digitization of glass slides enhance the teaching and learning of microscopic aspects of disease. Additionally, the COVID-19 global health crisis has produced many challenges to overcome from a macroscopic to microscopic scale, for which modern virtual technology is the solution. Therefore, medical educators worldwide should incorporate newer teaching technologies in the curriculum for the success of the coming generation of health-care professionals.


Introduction
The advent of the COVID-19 pandemic and physical distancing posed an unprecedented challenge to the world of medical education. How do you teach medicine, a human-centered subject that requires active interaction and engagement with people, without face-to-face contact? In response to this challenge, medical schools worldwide have implemented various changes such as online lectures and virtual classrooms in their education during the last two years to adapt to the new norm [1][2][3].

Whole-Slide Imaging (WSI)
Even before the pandemic, however, digital pathology using digital whole-slide imaging (WSI) was steadily gaining a foothold in medical education, training, and diagnosis [4,5]. Cumulative validations of the outstanding diagnostic concordance between WSI and glassslide diagnoses prompted constant development and establishment of guidelines regarding WSI, thus progressively broadening the scope of its use [6,7]. Following the release of the guideline on the validation of WSI for diagnostic purposes by the Pathology and Laboratory Quality Center for Evidence-Based Guidelines of the College of American Pathologists (CAP) in 2013, WSI later gained approval from the Food and Drug Administration (FDA) for its use in primary diagnosis in 2017 and continues to be updated, the latest being the Guideline Update from the College of American Pathologists in Collaboration with the American Society for Clinical Pathology and the Association for Pathology Informatics in 2022 [6,8].
WSI technology is readily utilized by virtual microscopy (VM), a computerized conversion of light microscopy images in full resolution and their presentation over a computer network [9]. VM software can reproduce a digitized, high-resolution image of a traditional glass slide and allows the users to highlight, annotate, pan, and zoom. With the ease of use, added features, and reliability, interest in the exciting potential of VM continues to be on the rise [7,10,11].

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No risk of deterioration of staining quality or breakage of slides, no fading or stored slides, shorter sign-out time, access from any device, better flexibility, easy image sharing in clinical communication • Better archiving, sharing, and easy retrieval; faster turnaround times, reduced cost of equipment, lab maintenance, and auxiliary techniques (less immunohistochemistry).
Advantages of VM use for medical educational are observed as well. Learners benefit from VM through remote teaching, multiple user access, the comfort of use amongst the modern "digital native" generation with prior computer knowledge, and better interaction between teachers and students by viewing the same image at the same time [17,20]. A meta-analysis by Wilson et al. also found that learners prefer VM to conventional light microscopy as well [13].
One notable advantage of using VM worth acknowledging is the benefit of access to slide images without restricting time and space. This unique characteristic of VM came into the spotlight upon facing the lockdowns during the coronavirus global health crisis.
To ensure undisrupted quality education for students, lecturers adjusted their teaching methods to social distancing and disease-prevention regulations accordingly. In addition, the massive shift in medical education towards remote learning and digitization of the learning materials granted researchers an abundant opportunity and data to investigate VM more deeply. With the already known benefits of using digital slides, additional positive effects such as self-paced learning, improved tissue recognition due to better access to slides, improved understanding, and better academic performance have been reported during COVID-19 lockdown-adapted online classes [2,21,22].
In this review, we aim to compare the academic performance of medical students by using VM technology to learn the microscopic aspect of the disease. In addition, this study intends to include recent data on VM and WSI to present the most updated synthesis on VM and to explore any differences in usage, benefits, and drawbacks of VM that may have been newly discovered during the COVID-19 era.

Materials and Methods
This review reports the systematic findings according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines [23]. The systematic review protocol was registered in the prospective register of systematic reviews (PROSPERO; https://www.crd.york.ac.uk/prospero (accessed on 21 September 2020)) with registration number CRD42020205583.
The review questions were "Does virtual or digital microscopy enhance student exam performance?" along with secondary qualitative assessment: "Is virtual microscopy a reliable and a better method for teaching and learning in medical education?" and "What are the student preferences for this newer technology?"

Literature Review
One author (NN) performed a literature search to identify if any systematic reviews were available or protocols registered as to our study objective. We identified three similar reviews [13,14,24]. However, these reviews had major limitations, such as not including studies that measured the efficacy of VM during or after the COVID-19 pandemic period. One of these previous studies included both medical students and pathology residents [24]. Its literature search was performed in a limited number of databases and failed to report comprehensive search criteria. Furthermore, these studies had narrow selection criteria, including only the pathology course at medical school, despite existing papers demonstrating VM or LM use in cytopathology, anatomy, histology, or hematopathology courses in medical, dental, and veterinary schools.

Eligibility Criteria
Only original research articles assessing the performance of LM and VM through the process of any data type-academic scores, student feedback, questionnaires, and surveys-were included for this review. Additionally, we included articles assessing the performance or perception of medical or dental students using VM or traditional LM. Articles were included irrespective of use for pathology, histology, anatomy or histopathology. The meta-analysis included comparative studies of LM versus VM or crossover studies. Studies with data on the students' performance measured as a percentage or score on a definitive scale and clear mention of method of evaluating students' perceptions were included. Studies published in English were included (or others if the translation in English was available).
Studies mentioning a VM resource or description of the technology used in medical or dental schools were also included. Along with this information, studies describing VM use due to the transition toward online teaching during COVID-19 were included.

Exclusion Criteria
Studies that described VM used for pathological diagnosis or involving perceptions of pathology residents were excluded from this review. Literature reviews (systematic, meta-analyses, narrative), editorial letters, book chapters, and case reports were excluded. Publications in which the modality of WSI was unclear/unspecified or no data (qualitative or quantitative) in the form of survey or comparison were available were also excluded.

Search Criteria and Database
A comprehensive database search was performed on 15 December 2021 and again on 15 March 2022 (to include updates) from the date of inception in Scopus, PubMed, CINAHL, Web of Science, Embase, Cochrane Library and Google Scholar. Various search terms such as "virtual microscopy/microscop*," "digital microscopy/microscop*," "virtual slides," "whole slide imaging," "students," and "medical education" in combinations of Boolean operators and truncation were used to ensure comprehensive inclusion of relevant articles. Search criteria were adjusted to the selected database. In addition, we manually searched recent reviews or eligible studies to identify any potential studies.

Article Screening and Eligibility Evaluation
For a fair screening process, two teams (SM, SN, and ShN; JW, TC, and SH) of researchers independently performed title and abstract screening based on study inclusion criteria. In addition, we performed a full-text analysis if the potentially relevant article's abstract did not contain sufficient information. The inclusion and exclusion criteria were used to select the eligible studies and access the full-text articles. Zotero software was used as the reference manager to import the search results from the database and exclude duplicates [25]. Google Sheets was used to screen the articles and register a primary reason for exclusion. Disagreements were resolved by collective discussion involving both teams, which ensured that appropriate publications were selected according to the eligibility criteria.

Extraction of Qualitative and Quantitative Data
One author (SM) independently extracted the available data from the eligible studies, followed by the second author (SN) reviewing the extracted data. Finally, we designed a standardized data collection Google sheet to organize the qualitative and quantitative data.
For each selected study, the following information was extracted (when available): year and country of publication, which variable was analyzed (performance, perception or both), number of participants, students' educational level, type of equipment and software used to assess WSI, types of workstation, digital slide accessibility, equipment training, LM availability and its specification, number and Scope of used samples, and how the students' performance and/or perception were assessed and their results. The outcome of interest for this meta-analysis was focused on estimating overall exam performance based on discipline and subject.

Quality Assessment
Two authors independently (SM and RN) used the original version of the Newcastle Ottawa Scale (NOS) for the quality appraisal of the included studies [26]. The NOS scale is a star-based system that evaluates the study based on three major perspectives: the selection of the study groups, comparability of the groups, and the ascertainment of either the exposure or outcome of interest for non-RCTs. For case-control studies, a study was awarded a maximum of one star for each numbered item within the selection and exposure categories. A maximum of two stars were given for comparability. For cohort studies, a study was awarded a maximum of one star for each numbered item within the selection and outcome categories. For comparability, a maximum of two stars were given (see Supplementary File S1). Finally, each study was categorized as good, fair or poor quality. A subgroup quantitative analysis of the studies was done after classifying them as good, fair or poor quality according to Agency for Health Research and Quality (AHRQ) standards (see Supplementary File S2). Any discrepancies were resolved by discussion with the third reviewer (SN).

Statistical Analyses
The Google sheet was cleaned and organized to conduct qualitative and quantitative analysis. Qualitative results were organized and included in the systematic review, whereas the quantitative data were analyzed further to estimate the overall better educational technique (VM versus LM). Review Manager version 5.4 calculated mean differences, pooled effect size, and heterogeneity. Only the studies with data on comparative exam scores went to the quantitative analytical stage (meta-analyses). Since the overall analysis demonstrated considerable heterogeneity, the random effect model to generate forest plots and publication bias was used. The choice of a random effect model was made due to the heterogeneity that was observed for different countries, different year of study, different faculty, different discipline, different teaching technique, different technical setup, and pre/COVID-19. Included studies used different scales to measure the same outcome, i.e., the units for the outcome of interest were different across studies. For such cases, the mean differences (MD) cannot be directly pooled and analyzed. Thus, MD was divided by the respective standard deviations (SDs) to yield a statistic known as the standardized mean difference (SMD) [27]. Therefore, the extracted data were computed and organized as continuous data followed by an inverse variance analysis method to estimate the SMD and 95% confidence interval. The heterogeneity was assessed using Higgins square I 2 or Q-statistic. I 2 can be interpreted as minimal (0-40%), moderate (30-60%), substantial (50-90%) and considerable (75-100%) [28]. Begg and Mazumdar's rank correlation and Egger's test were used to confirm the publication bias [29]. Subgroup analyses according to the subject (pathology, histology or histopathology) and faculty (medical or dental) were also performed.
In the qualitative data review of included articles, themes that referred to the applications, advantages, and disadvantages of VM were identified. In addition, perceptions, surveys, or questionnaire data related to student experiences with VM were extracted from the Google sheet.

Search Results and Study Characteristics
A total of 1627 studies were identified from the selected database search. After removal of 676 duplicates, there were 951 eligible studies, of which those conducted before year 2019 were further excluded. Thus, a final number of 263 articles were screened for title and abstract and 39 full-text articles were reviewed to be included in the systematic review. The meta-analysis of the performance comparison of VM versus LM included 19 studies (see flowchart in Figure 1).

Search Results and Study Characteristics
A total of 1627 studies were identified from the selected database search. After removal of 676 duplicates, there were 951 eligible studies, of which those conducted before year 2019 were further excluded. Thus, a final number of 263 articles were screened for title and abstract and 39 full-text articles were reviewed to be included in the systematic review. The meta-analysis of the performance comparison of VM versus LM included 19 studies (see flowchart in Figure 1). The included articles were published from 2019 to 2022, and originated from North America, South America, Europe, Australia, the United Kingdom and Asia. Most (10/39) were from medical universities in the USA. VM was mostly used for teaching pathology (25/39) at medical schools (30/39). Dental schools (10/39) also reported using VM for teaching microscopy. The most commonly used VM software reported by the studies (6/39) was Aperio ImageScope [30]. Only three studies in this review collected data using a randomized controlled trial protocol, whereas most collected data were based on group performance comparison without randomization. COVID-19 was responsible for transition to VM use in 17/39 studies. A detailed synthesis of included studies in this review is provided in Table 1. BEST slice cloud-based library A thematic analysis of the qualitative comments strongly indicated that online histopathology teaching was instrumental, more comfortable to engage in and better structured compared to face-to-face teaching. Compared to the prior cohort completing the same curriculum the mean overall mark was significantly improved. Study compared results of assignments and exams between VM group and LM group and a questionnaire survey was used to collect feedback. Results showed an increase laboratory final test grades increased and the feedback of the questionnaire was positive, indicating that students were satisfied with the system. This study concluded that VM is an efficient and feasible teaching technology and improves students' academic performance. Majority students were reported to be enthusiastic about using VM. Some of the benefits of VM as cited by the students were the ease of usage, annotations, the superior quality of images, accessibility to slides outside of lab time, in class internet access to additional learning material, promotion of self-learning and efficient use of their study time. Performance score analysis showed a statistically significant improvement of grades in the VM arm. Results showed a significantly higher acceptance rate and a significantly better histopathological diagnosis ability among dental students using the virtual slide learning than those using the glass-slide learning for the oral pathology laboratory course.VM with digitized virtual slides may gradually replace the real microscopy with glass slides for the learning of oral pathology laboratory course. Custom histology software-Virtuelle Mikroskopie The study concluded that the implementation of a curricular histology course in an online-format is technically realizable, effective and well accepted among students. The study also reported that availability and prior experience with digitized specimen in VM facilitates transition into an online-only setting. NanoZoomer S60 digital whole slide scanner The study reported positive subjective feedback related to handling, suitability, learning effectiveness, and pleasure using the tools for VM. Although no statistically significant differences were found between groups for academic performance, VM proved to be adequate to the Brazilian medical education in light of Brazilian social contexts and COVID-19 pandemic. The VM group had a significantly higher satisfaction score towards the learning tool than the LM group. The knowledge acquisition of the VM group was equal to the LM group as they were shown to have a similar improvement in the test scores, comprehension level and learning ability. The study revealed a significant improvement in test scores for VM. The study concluded that further research to enhance understanding of the aspects of the e-learning environment towards the formulation of policies for higher-quality education is needed. VM use improved student attitudes towards histology content and had a positive impact on student-faculty rapport. Students self-reporting an increased comfortability and understanding with differential diagnosis suggested a strengthening of self-efficacy skills. Statistically significant positive correlations were found with use of VM suggesting that increased use of these resources was more common in students with higher exam scores in the class. This study reported that a combination of both electronic materials (VM) and textbooks was commonly used by students with electronic resources being used regularly by the majority of students. No statistically relevant differences were found between the approaches of dentistry versus general medicine students. Cooperation amongst students for individual presentations was seen to be beneficial by a majority of dentistry students. A majority of students preferred VM over LM and agreed that DM was effective for the course purpose. For the diagnosis exercise, all participants managed to answer correctly using VM compared to LM. Thus, indicating that VM should certainly be integrated as a teaching tool to enhance the learning process within the dental curriculum.
Using Table 1, we performed thematic analyses for the advantages/disadvantages reported by various studies on using VM or LM. Thematic analyses revealed various codes describing the advantages and disadvantages from the included articles (Supplementary  Table S1). The top themes highlighting advantages that emerged were improvements in academic performance of the students, ease of use of VM, a positive student perception and acceptability of VM, and enhanced cooperation and student collaboration. In addition, one of the generated themes highlighted a positive impact on the teaching faculty.
Technical and internet issues while accessing the slides were the main disadvantages [22,33,38,41,44,57,67]. Few studies reported less interaction and impaired social connections along with a lack of faculty feedback as main disadvantages [22,41,44].

Quality Assessment of Included Studies Using NOS
The final included articles were predominantly of cross-sectional design, and thus an adapted version of the NOS scale was applied for quality assessment of cross-sectional studies. Others were evaluated using the original NOS scale. To evaluate each study, a n asterisk was assigned to any of the fulfilled criteria in the selected scale parameter. Table 2 represents the summary of quality assessment using the NOS scale for cohort studies. Table 3 represents the summary of quality assessment using the NOS scale for crosssectional studies (total nine articles). Table 4 represents the summary of quality assessment using the NOS scale for randomized controlled studies (total three articles). Table 5 represents the summary of quality assessment using the NOS scale for casecontrol studies (total seven articles).

Discussion
In this review article, the authors compared the utility of VM for teaching medical subjects in medical and dental schools. The results of our qualitative and quantitative analyses show a comparison of student performance after using VM technology. The digitization of glass slides undoubtedly enhances the ease of teaching and learning of microscopic aspects of disease. Additionally, the COVID-19 global health crisis has produced many challenges to overcome from a macroscopic to microscopic scale, for which modern virtual technology has been the solution [1].
The authors performed a systematic review considering how to remove existing literature limitations. A well-designed study criterion to include more studies, including the articles published during COVID-19 pandemic to analyze available evidence on the usage of VM for the learning process for medical and dental school learners compared to the traditional LM, was developed.
The results from the systematic review clearly show a preference for using VM. In contrast, the meta-analysis results statistically prove that overall student performance on the examination is better when using such technology for learning.
As the use of virtual learning platforms and virtual meeting spaces proliferated, educators of undergraduate and preclinical sciences adapted to using VM with remote

Discussion
In this review article, the authors compared the utility of VM for teaching medical subjects in medical and dental schools. The results of our qualitative and quantitative analyses show a comparison of student performance after using VM technology. The digitization of glass slides undoubtedly enhances the ease of teaching and learning of microscopic aspects of disease. Additionally, the COVID-19 global health crisis has produced many challenges to overcome from a macroscopic to microscopic scale, for which modern virtual technology has been the solution [1].
The authors performed a systematic review considering how to remove existing literature limitations. A well-designed study criterion to include more studies, including the articles published during COVID-19 pandemic to analyze available evidence on the usage of VM for the learning process for medical and dental school learners compared to the traditional LM, was developed.
The results from the systematic review clearly show a preference for using VM. In contrast, the meta-analysis results statistically prove that overall student performance on the examination is better when using such technology for learning.
As the use of virtual learning platforms and virtual meeting spaces proliferated, educators of undergraduate and preclinical sciences adapted to using VM with remote students [2]. The use of VM in education is not unprecedented, of course, but its application and scope has significantly expanded over the last two years [21,32,36,68,69]. Much like modern students are more likely to have experience editing a digital photograph than developing an analogue photograph, the technology offers a more intuitive experience to the novice user. Clinical medicine, too, has shown VM to be a ready solution for histopathology diagnosis, supported by double-blind evidence of no inferiority to traditional modalities of diagnosis [70][71][72].
Various researchers around the globe have highlighted the advantages of such digital technologies when used for histopathology diagnosis, including diagnosis for such specialties as dermatology, neurology, gastrointestinal, cancer pathology and hematological diagnosis [73][74][75][76][77][78]. The advent of newer artificial intelligence (AI) and machine learning technologies that are being embedded into digital pathology and VM software have extended a pathologist's diagnostic capabilities beyond the scope of the tissue section on a glass slide [79].
The newer applications and ever-increasing usage of VM software and WSI systems propel the need to integrate such technologies for medical education, especially at the undergraduate level, as students may encounter such technology during their residency years and during medical practice.
VM has gained increasing interest in the last four decades. The benefits over traditional LM include the practical, such as storage and maintenance of slides on a hard drive with backup, and the user experience, where an entire classroom can work with a single slide. For many years, however, this resource had severe limitations due to limited data storage and image magnification technology. Using WSI technology, starting in the early 2000s, VM has allowed the user to choose the magnification of the image with the stroke of a mouse and with less technical skill than traditional LM [9,17].
Results of this systematic review highlighted findings with a focus on advantages of VM use for both students and medical teachers. Most of the included articles mentioned various advantages, such as ease of use of digital slides. Easy access and constant availability with online access were the top advantages, whereas cost of implementation was the most discussed disadvantage of VM. The current COVID-19 pandemic has clearly given a boost to the field, so more robust real-world data from larger-scale VM implementations can be expected soon.
While students have largely returned to in-person learning in the pandemic's third year, many of the innovations and remote learning adaptations of the pandemic are being integrated rather than discarded [80]. Prevailing tides of change in the digital era were already moving academic histopathology away from traditional LM in favor of a modern approach [19]. Digitizing the workspace has been a welcome improvement for learners. In one survey of pathology students utilizing VM in a remote clerkship, respondents reported greater interest and understanding of the material [22]. While some larger organizations have been able to produce and maintain their own VM database, smaller organizations have been able to benefit from the free access many institutions have offered.
An interesting aspect of the review findings in this study were the areas of VM use in medical education. Various VM-based learning activities have been employed by medical educators. Such activities include active learning activities such as group discussions, collaborative discussions, podcasts and clinical case discussions. In this review, the results show an overall positive impact of VM in a digitized learning environment and evidence indicates high acceptability and adaptability by medical learners.
Educators at the University of Eastern Finland initiated a curricular reform for histology education focused on development of a student-centered WSI platform [66]. A "gamification" histology learning model was developed that is based on incorporation of game mechanics and game theory into education [81,82].
Introduction of such a learning system into dental and medical histology courses stimulated learning and improved student satisfaction [66].
Another interesting application of VM by Sakthi-Velavan et al. involved the blending of histology content using podcasts into an integrated curriculum [32]. VM-based podcasts are narrative recordings of digital histology images. Results of the study showed a positive association between podcast viewing and improved overall class performance. The students reported a better learning experience after using the podcast-based VM. The findings align with the current review and previous studies on exploring the effectiveness of VM podcastbased teaching in medical schools [83].
During the COVID-19 pandemic, educators were forced to transition to an online distance learning pedagogy. Westfälische-Wilhelms-University, Germany and the University of California San Francisco are a couple of many such universities that successfully transitioned the entire VM-based courses to a completely online distance learning histology and pathology curriculum. Researchers at these universities used customized VM university databases and reported that the implementation of a curricular histology course in an online format was technically realizable, effective and well accepted among students. While distance learning models are insufficient for career progression in pathology, VM can still be adapted to enhance collaboration and microscopic learning of disease [40,41].
High costs of WSI scanners and VM software pose a significant challenge for adoption of digital microscopy in medical schools. Ample alternative options are available for implementation of VM for teaching and learning microscopy. Such resources include free online websites or cloud-based servers that can be accessed via the internet freely for educational purpose. Results from the analysis of the studies included in this review highlight the use of such free websites and cloud-based servers for VM resources [20,31,36,38,43].
One of the most used VM apps in this review was Aperio ImageScope, which allows viewing online or local network WSI [30]. The Biolucida viewer [84] is another such VM viewer that connects to the digital slide cloud library at the University of Iowa and can be viewed freely worldwide without any cost involved. The University of Michigan Virtual Slide Box [85] and Virtual Pathology at the University of Leeds [86] offer many WS images that can be viewed over the internet by any available web browser.
Another interesting aspect of VM implementation in medical education is the development of competence in students. American accreditation agencies such as the Accreditation Council for Graduate Medical Education (ACGME) [87] and Liaison Committee on Medical Education (LCME) [88] have outlined core skills that need to be addressed by medical schools to meet the required educational standards, including medical knowledge, patient care, communication skills, professionalism, lifelong learning and social context of health care [89]. Due to the accreditation body requirements along with the ongoing transition towards remote or distance learning, implementation of VM can help in addressing such competence and ensuring development of competent physicians for the society [9,20].

Limitations of this Review
A significant limitation of our study is the presence of a considerable level of heterogeneity. This could be due to the methodological (differences in study design, risk of bias, etc.) and statistical (variation in intervention effects or results) differences from the diverse geographical population with different cultures. For example, Lee et al. (2020) reported academic scores as percentages to compare LM and VM groups. However, Chen et al. (2019) reported academic scores on a five point scale to compare the academic improvement by using the VM. The quality of published articles can be further improved by standardizing of the research design and methodology for such an educational intervention. The NOS scale resulted in only four studies with a high score (six or seven stars) and 15 studies had a score above three stars. A total of 24 out of 39 studies had poor research design according to the NOS scale. As most educators and medical schools around the world use a wide spectrum of teaching methods along with diverse curricular designs, results for educational intervention impact will continue to be heterogeneous.
Nonetheless, this meta-analysis provides strong evidence that students prefer VM over LM (although it cannot be replaced completely) and exam performance also increased by using VM. The heterogeneity of results and different outcomes posed could be resolved in the future by introducing more subgroup analysis that would still need some homogeneous data set to work on.

Conclusions
This review highlights various advantages of VM compared to traditional LM for medical education. Most studies in this meta-analysis were pilot projects and first-time implementation of digital technology at various medical universities. Globally, VM and WSI technology have undoubtedly reshaped pathology teaching and learning in medical and dental schools. Use of VM in medical education has provided a venue for stimulated learning, improved student satisfaction and an overall better learning experience. Easy access to educational content and constant availability with online access are amongst the top advantages, whereas cost of implementation and access to the internet are still the most discussed disadvantages of such technology.
Availability of numerous free online VM resources has fueled global access to educational materials geared towards learning microscopy of normal tissue and pathological features of various human diseases. The ongoing COVID-19 pandemic has further fueled the need for digitization of teaching methods, particularly increased use of VM in medical education worldwide. As much of the current work on VM usage outcomes is from early technology implementation, a certain degree of enthusiastic bias in favor of VM is inevitable.
Funding: This research received no external funding.

Supplementary Materials:
The following supporting information can be downloaded at https: //www.mdpi.com/article/10.3390/diagnostics13030558/s1. Table S1: Themes depicting advantages/disadvantages of VM in comparison to LM; File S1: Newcastle-Ottawa Quality assessment scale case control studies; File S2: Thresholds for converting the Newcastle-Ottawa scales to AHRQ standards.

Conflicts of Interest:
The authors declare no conflict of interest.