LITERATURE UPDATE


and treatment of cancer that are mainly address by CPath tools. With ever-growing developments in deep learning and computer vision algorithms, and the ease of the data flow from digital pathology, currently CPath is witnessing a paradigm shift. Despite the sheer volume of engineering and scientific works being introduced for cancer image analysis, there is still a considerable gap of adopting and integrating these algorithms in clinical practice. This raises a significant question regarding the direction and trends that are undertaken in CPath. In this article the authors provide a


comprehensive review of more than 800 papers to address the challenges faced in problem design all the way to the application and implementation viewpoints. They have catalogued each paper into a model-card by examining the key works and challenges faced to layout the current landscape in CPath. They hope this helps the community to locate relevant works and facilitate understanding of the field’s future directions.


In a nutshell, they oversee the CPath developments in cycle of stages which are required to be cohesively linked together to address the challenges associated with such multidisciplinary science. They overview this cycle from different perspectives of data-centric, model- centric, and application-centric problems. Finally, they sketch remaining challenges and provide directions for future technical developments and clinical integration of CPath.


Biomedical laboratory scientists and technicians in digital pathology - Is there a need for professional development? Jensen CL, Thomsen LK, Zeuthen M et al. Digit Health. 2024 Mar 15; 10: 20552076241237392. doi: 10.1177/20552076241237392. eCollection 2024


Digital pathology (DP) is moving into Danish pathology departments at high pace. Conventionally, biomedical laboratory scientists (BLS) and technicians have prepared tissue sections for light microscopy, but workflow alterations are required for the new digital era with whole-slide imaging (WSI); digitally assisted image analysis (DAIA) and artificial intelligence (AI). Here, the authors aim to explore the role of BLS in DP and assess a potential need for professional development.


The authors investigated the roles of BLS in the new digital era through qualitative interviews at Danish Pathology Departments in 2019/2020 before


DP implementation (supported by a questionnaire); and in 2022 after DP implementation. Additionally, senior lecturers from three Danish University Colleges reported on how DP was integrated into the 2023 Bachelor’s Degree educational curricula for BLS students.


At some Danish pathology departments, BLS were involved in the implementation process of DP and their greatest concerns were lack of physical laboratory requirements (69%) and implementation strategies (63%). BLS were generally positive towards working with DP; however, some expressed concern about extended working hours for scanning. Work-task transfers from pathologists were generally greeted positively from both management and pathologists; however, at follow-up interviews after DP implementation, job transfers had not been effectuated. At Danish university colleges, DP had been integrated systematically in the curricula for BLS students, especially WSI. Involving BLS in DP implementation and development may benefit the process, as BLS have a hands-on workflow perspective with a focus on quality assurance. Several new work opportunities for BLS may occur with DP including WSI, DAIA and AI, and therefore new qualifications are warranted, which must be considered in future undergraduate programmes for BLS students or postgraduate programmes for BLS.


Standardizing digital biobanks: integrating imaging, genomic, and clinical data for precision medicine Brancato V, Esposito G, Coppola L et al. J Transl Med. 2024 Feb 5; 22 (1): 136. doi: 10.1186/s12967-024-04891-8.


Advancements in data acquisition and computational methods are generating a large amount of heterogeneous biomedical data from diagnostic domains such as clinical imaging, pathology, and next-generation sequencing (NGS), which help characterise individual differences in patients. However, this information needs to be available and suitable to promote and support scientific research and technological development, supporting the effective adoption of the precision medicine approach in clinical practice.


Digital biobanks can catalyse this


process, facilitating the sharing of curated and standardised imaging data, clinical, pathological and molecular data, crucial to enable the development of a comprehensive and personalised


WWW.PATHOLOGYINPRACTICE.COM MAY 2024


data-driven diagnostic approach in disease management and fostering the development of computational predictive models.


This work aims to frame this perspective, first by evaluating the state of standardisation of individual diagnostic domains and then by identifying challenges and proposing a possible solution towards an integrative approach that can guarantee the suitability of information that can be shared through a digital biobank. Analysis of the state of the art shows the presence and use of reference standards in biobanks and, generally, digital repositories for each specific domain. Despite this, standardisation to guarantee the integration and reproducibility of the numerical descriptors generated by each domain (eg radiomic, pathomic and -omic features) is still an open challenge. Based on specific use cases and scenarios, an integration model, based on the JSON format, is proposed that can help address this problem. Ultimately, this work shows how, with specific standardisation and promotion efforts, the digital biobank model can become an enabling technology for the comprehensive study of diseases and the effective development of data-driven technologies at the service of precision medicine.


Expectations and Experiences Among Clinical Staff Regarding Implementation of Digital Pathology: A Qualitative Study at Two Departments of Pathology Koefoed-Nielsen H, Kidholm K, Frederiksen MH, Mikkelsen MLN. J Imaging Inform Med. 2024 Mar 28. doi: 10.1007/s10278-024-01087-w. Online ahead of print.


This study aims to assess and evaluate the individual expectations and experiences regarding the implementation of digital pathology (DIPA) among clinical staff in two of the pathology departments in the Region of Southern Denmark before and during the implementation in their department.


Seventeen semi-structured interviews based upon McKinsey 7-S framework were held both prior to and during implementation with both managers and employees at the two pathology departments. The interviewees were pathologists, medical doctors in internship in pathology (interns), biomedical laboratory scientists (BLS), secretaries, and a project lead. Using deductive and inductive coding resulted in five overall themes and appertaining sub-themes.


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