Background:Accurate digital pathology image analysis depends on high-quality images. As such, it is imperative to obtain digital images with high resolution for downstream data analysis. While hematoxylin and eosin (H&E)-stained tissue section slides from solid tumors contain three-dimensional information, these data have been ignored in digital pathology. In addition, in cytology and bone marrow aspirate smears, the three-dimensional nature of the specimen has precluded efficient analysis of such morphologic data. An individual image snapshot at a single focal distance is often not sufficient for accurate diagnoses and multiple whole-slide images at different focal distances are necessary for diagnostics.Materials and Methods:We describe a novel computational pipeline and processing program for obtaining a super-resolved image from multiple static images at different z-planes in overlapping but separate frames. This program, MULTI-Z, performs image alignment, Gaussian smoothing, and Laplacian filtering to construct a final super-resolution image from multiple images.Results:We applied this algorithm and program to images of cytology and H&E-stained sections and demonstrated significant improvements in both resolution and image quality by objective data analyses (24% increase in sharpness and focus).Conclusions:With the use of our program, super-resolved images of cytology and H&E-stained tissue sections can be obtained to potentially allow for more optimal downstream computational analysis. This method is applicable to whole-slide scanned images.

Introduction Rapid technological advancements in clinical molecular genetics have increased our diagnostic and prognostic capabilities in health care. Understanding these assays, as well as how they may change over time, is critical for pathologists, clinicians, and translational researchers alike. Methods This review provides a practical summary and basic reference for current molecular genetic technologies, as well as new testing methodologies that are in use, gaining momentum, or anticipated to contribute more broadly in the future. Results Here, we discuss DNA and RNA based methodologies including classic assays such as the polymerase chain reaction (PCR), Sanger sequencing, and microarrays, to more cutting‐edge next‐generation sequencing (NGS) based assays and emerging molecular technologies such as cell‐free DNA (cfDNA) or circulating tumor DNA (ctDNA), and NGS‐based detection of infectious disease organisms. Conclusion This review serves as a basic foundation for knowledge in current and emerging clinical molecular genetic technologies.

Artificial intelligence (AI) is having an increasing impact on the field of pathology, as computation techniques allow computers to perform tasks previously performed by people. Here, we offer a simple and practical guide to AI methods used in pathology, such as digital image analysis, next-generation sequencing, and natural language processing. We not only provide a comprehensive review, but also discuss relevant history and future directions of AI in pathology. We additionally provide a short tabular dictionary of AI terminology which will help practicing pathologists and researchers to understand this field.

Post-transplant lymphoproliferative disorders (PTLD) are diseases occurring in immunocompromised patients after hematopoietic stem cell transplantation (HCT) or solid organ transplantation (SOT). Although PTLD occurs rarely, it may be associated with poor outcomes. In most cases, PTLD is driven by Epstein-Barr virus (EBV) infection. Few studies have investigated the mutational landscape and gene expression profile of PTLD. In our study, we performed targeted deep sequencing and RNA-sequencing (RNA-Seq) on 16 cases of florid follicular hyperplasia (FFH) type PTLD and 15 cases of other PTLD types that include: ten monomorphic (M-PTLD), three polymorphic (P-PTLD), and two classic Hodgkin lymphoma type PTLDs (CHL-PTLD). Our study identified recurrent mutations in JAK3 in five of 15 PTLD cases and one of 16 FFH-PTLD cases, as well as 16 other genes that were mutated in M-PTLD, P-PTLD, CHL-PTLD and FFH-PTLD. Digital image analysis demonstrated significant differences in single cell area, major axis, and diameter when comparing cases of M-PTLD and P-PTLD to FFH-PTLD. No morphometric relationship was identified with regards to a specific genetic mutation. Our findings suggest that immune regulatory pathways play an essential role in PTLD, with the JAK/STAT pathway affected in many PTLDs.