Implementing the DICOM Standard for Digital Pathology.

Our goal is to provide an overview of machine learning methods and artificial intelligence in digital pathology image analysis. We also highlight novel visualization tools to interpret quantitative image-based pathomics data that is extracted from whole slide images to describe diverse phenotypic characteristics of cancer in a spectrum of tissues. Image analysis of tissues is based on the identification and classification of tissue, architectural elements, cells, nuclei, and other histologic features. We report emerging digital pathology image analysis applications to study several types and subtypes of cancer to complement traditional histopathologic evaluation. WSIs typically contain hundreds of thousands to millions of objects within a heterogeneous histologic landscape. Therefore, Pathomics represents an incredibly powerful emerging approach to classify cellular interactions and signaling by identifying relevant spatial relationships. The quantification of the intrinsic variability of different phenotypes and behavior in cancer is useful in analyzing and predicting clinical outcomes and treatment response.

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The Emergence of Pathomics

This white paper explores the technical challenges and solutions for acquiring (capturing) and managing enterprise images, particularly those involving visible light applications. The types of acquisition devices used for various general-purpose photography and specialized applications including dermatology, endoscopy, and anatomic pathology are reviewed. The formats and standards used, and the associated metadata requirements and communication protocols for transfer and workflow are considered. Particular emphasis is placed on the importance of metadata capture in both order- and encounter-based workflow. The benefits of using DICOM to provide a standard means of recording and accessing both metadata and image and video data are considered, as is the role of IHE and FHIR.

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Technical Challenges of Enterprise Imaging: HIMSS-SIIM Collaborative White Paper

An efficient architecture to support digital pathology in standard medical imaging repositories

Dual-Personality DICOM-TIFF for whole slide images: A migration technique for legacy software

Introduction/ Background In recent years different technological solutions have emerged for the scanning or digitization of histological and cytological slides in pathology, from several manufacturers. High resolution scanning is usually based in tile (small fragment) or stripes (longitudinal areas) that are combined or stitched together to create a high magnification (usually equivalent to 20x to 40x magnification) global image. Thus, a large digital slide can be displayed using specific viewers to simulate the functions of a conventional microscope. A pyramid of images is a common solution. But each scanner manufacturer optimizes the process of collecting, managing and storing images in its own format, making difficult the interconnection between systems and the ability to share images between different formats, and, generally a heavy process of image conversion and a loss of information is needed. Aims The objective is to present the process performed on proprietary image formats of histological and cytological slides in pathology to convert them the be compliant with the Digital Imaging and Communication in Medicine (DICOM) standard, according to 145 and 122 supplements, and their subsequent storage in a Picture Archiving and Communication System (PACS). Methods Python was chosen as programming platform due to its versatility and available tools. Furthermore, for future projects, Python can be used to apply signal analysis on digital images. A Pentium Core i3 4GB RAM, 1TB server with Ubuntu 14.04.3 LTS Server was used. In the server, a developer platform Eclipse Version 3.8.1 allowed the installation of PyDev for Eclipse 4.3.0 and Eclipse Jgit 1.3.0 plugins. It has been connected to a Github repository to manage developing versions. The solutions has been structured into a Python package to obtain images coming from proprietary images to be standardized to an image compliant with DICOM supplement 145, and sending them to the PACS. Results In order to test compatibility, David A. Clunie’s dicom3tools was used. This allowed verification of all Tags of the generated files, indicating those who are required according to each image, and also it offers information of those tags where included data does not match the standard and those with values that do not correspond to that standard. This tool helped to finally obtain a result of 0% errors in all generated files. Regarding storage tests, two different PACS were used. First, in collaboration with T-systems Company, an open source dcm4chee DICOM Archive 2 (dcm4che.org), and second, in collaboration with IRE Rayos X company, a commercial IRE Store Channel 4.3 was also used in several tests. After some tests with commercial and open source PACS, we could obtain the following c onclusions: In the negotiation phase, the PACS did not recognize the predetermined configuration stated in supplement 145. The solution was changing SOP to “VL Microscopic Image Storage”. Each level of the pyramid will be stored as an instance inside the same series, and each tile as a frame inside a multi-frame object. The dcm4che.org PACS offers a WADO service that allows accessing each frame separately, inside the same object, which can be useful for the implementation of slide viewers in pathology. Acknowledgment : This work has been supported by the AIDPATH project, an EU 7FP IAPP Marie Curie action, contract number 612471

http://www.diagnosticpathology.eu/content/index.php/dpath/article/download/175/302

A. Sanchez

Papers

Standardization Of Pathology Whole Slide Images According To DICOM 145 Supplement And Storage In PACs