The 2022 Annual Review Issue of The Journal of Pathology, Recent Advances in Pathology, contains 15 invited reviews on research areas of growing importance in pathology. This year, the articles include those that focus on digital pathology, employing modern imaging techniques and software to enable improved diagnostic and research applications to study human diseases. This subject area includes the ability to identify specific genetic alterations through the morphological changes they induce, as well as integrating digital and computational pathology with \'omics technologies. Other reviews in this issue include an updated evaluation of mutational patterns (mutation signatures) in cancer, the applications of lineage tracing in human tissues, and single cell sequencing technologies to uncover tumour evolution and tumour heterogeneity. The tissue microenvironment is covered in reviews specifically dealing with proteolytic control of epidermal differentiation, cancer-associated fibroblasts, field cancerisation, and host factors that determine tumour immunity. All of the reviews contained in this issue are the work of invited experts selected to discuss the considerable recent progress in their respective fields and are freely available online (https://onlinelibrary.wiley.com/journal/10969896). © 2022 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Digital pathology and artificial intelligence (AI) rely on digitization of patient material as a necessary first step. AI development benefits from large sample sizes and diverse cohorts, and therefore efforts to digitize glass slides must meet these needs in an efficient and cost-effective manner. Technical innovation in whole-slide imaging has enabled high-throughput slide scanning through the coordinated increase in scanner capacity, speed, and automation. Combining these hardware innovations with automated informatics approaches has enabled more efficient workflows and the opportunity to provide higher-quality imaging data using fewer personnel. Here we review several practical considerations for deploying high-throughput scanning and we present strategies to increase efficiency with a focus on quality. Finally, we review remaining challenges and issue a call to vendors to innovate in the areas of automation and quality control in order to make high-throughput scanning realizable to laboratories with limited resources. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Advancements in technology and digitization have ushered in novel ways of enhancing tissue-based research via digital microscopy and image analysis. Whole slide imaging scanners enable digitization of histology slides to be stored in virtual slide repositories and to be viewed via computers instead of microscopes. Easier and faster sharing of histologic images for teaching and consultation, improved storage and preservation of quality of stained slides, and annotation of features of interest in the digital slides are just a few of the advantages of this technology. Combined with the development of software for digital image analysis, digital slides further pave the way for the development of tools that extract quantitative data from tissue-based studies. This review introduces digital microscopy and pathology, and addresses technical and scientific considerations in slide scanning, quantitative image analysis, and slide repositories. It also highlights the current state of the technology and factors that need to be taken into account to insure optimal utility, including preanalytical considerations and the importance of involving a pathologist in all major steps along the digital microscopy and pathology workflow.

Among well-differentiated lipomatous lesions, variability in adipocyte size has been proposed as a morphologic feature of malignancy. Specifically, normal adipose tissue and benign lipomas tend to contain adipocytes of uniform size, whereas atypical lipomatous tumor/well-differentiated liposarcoma (ALT/WDL) is described as containing adipocytes with a conspicuous variation in cell size. However, this proposed variance has never been objectively, quantitatively correlated with diagnosis. Using whole-slide scanning combined with semiautomated digital image analysis, we aimed to quantitatively test the hypothesis that variance in adipocyte size is a feature of malignancy in well-differentiated lipomatous tumors. Whole-slide scanning was performed on representative hematoxylin and eosin-stained slides selected from 130 cases representing benign (lipoma, spindle cell lipoma) and malignant lipomatous neoplasms (ALT/WDL) and morphologic mimics (normal adipose tissue, fat necrosis, fat atrophy). A previously validated, open source software package (Fiji-based Adiposoft) was used in semiautomated analysis of adipocyte size from a representative 1-cm2 portion of each slide. Median, range, and variance of cell sizes were compared across all diagnoses. Fat atrophy demonstrated smaller adipocyte cell size compared with other diagnoses. Among the remaining diagnostic groups, no significant differences were identified in adipocyte size or variance by objective quantitative morphologic analysis. However, the maximum range of adipocyte size was significantly higher in ALT/WDL than conventional lipoma and spindle cell lipoma. These data quantitate the morphology of ALT/WDL and its mimics and more specifically define the somewhat subjective \"variability\" of cell size as maximum range, rather than variance, of adipocyte size.