Design of HL7 FHIR Profiles for Pathology Reports Integrated with Pathology Images.

This paper describes the development of Health Level Seven Fast Healthcare Interoperability Resource (FHIR) profiles for pathology reports integrated with whole slide images and clinical data to create a pathology research database. A report template was designed to collect structured reports, enabling pathologists to select structured terms based on a checklist, allowing for the standardization of terms used to describe tumor features. We gathered and analyzed 190 non-small-cell lung cancer pathology reports in free text format, which were then structured by mapping the itemized vocabulary to FHIR observation resources, using international standard terminologies, such as the International Classification of Diseases, LOINC, and SNOMED CT. The resulting FHIR profiles were published as an implementation guide, which includes 25 profiles for essential data elements, value sets, and structured definitions for integrating clinical data and pathology images associated with the pathology report. These profiles enable the exchange of structured data between systems and facilitate the integration of pathology data into electronic health records, which can improve the quality of care for patients with cancer.

Creating a Medical Imaging Workflow Based on FHIR, DICOMweb, and SVG.

This paper proposes a web-based workflow scheme for the organization of medical images using FHIR and DICOM servers equipped with standard RESTful APIs. In our integrated workflow, the client systems (including order placer, scheduler, imaging modality, viewer, and report creator) use standard FHIR and DICOMweb APIs. The proposed scheme also facilitates the creation of reports formatted as standard FHIR resources. This paper leverages W3C Scalable Vector Graphics (SVG) to record the image graphic annotations, and encapsulates the SVG image annotation in FHIR observation. FHIR DiagnosticReports and Observations are used to encapsulate reports, findings, and annotations, thereby facilitating the implementation and integration of the scheme within existing structures. The proposed scheme also provides the potential to make it possible to convert results of Computer Aided Detection/Diagnosis from medical images into FHIR DiagnosticReports and Observations to be stored on a FHIR server. The resulting web-based solution uses FHIR XML and/or JSON data to record and exchange information related to imaging workflow. It can also be used to store imaging reports, findings, and annotations linked to the images using the DICOM WADO-RS protocol. As a result, it is possible to integrate all information that is created in medical imaging workflow. Finally, the proposed scheme is easily integrated with other FHIR systems.

Recognizing the Differentiation Degree of Human Induced Pluripotent Stem Cell-Derived Retinal Pigment Epithelium Cells Using Machine Learning and Deep Learning-Based Approaches.

Induced pluripotent stem cells (iPSCs) can be differentiated into mesenchymal stem cells (iPSC-MSCs), retinal ganglion cells (iPSC-RGCs), and retinal pigmental epithelium cells (iPSC-RPEs) to meet the demand of regeneration medicine. Since the production of iPSCs and iPSC-derived cell lineages generally requires massive and time-consuming laboratory work, artificial intelligence (AI)-assisted approach that can facilitate the cell classification and recognize the cell differentiation degree is of critical demand. In this study, we propose the multi-slice tensor model, a modified convolutional neural network (CNN) designed to classify iPSC-derived cells and evaluate the differentiation efficiency of iPSC-RPEs. We removed the fully connected layers and projected the features using principle component analysis (PCA), and subsequently classified iPSC-RPEs according to various differentiation degree. With the assistance of the support vector machine (SVM), this model further showed capabilities to classify iPSCs, iPSC-MSCs, iPSC-RPEs, and iPSC-RGCs with an accuracy of 97.8%. In addition, the proposed model accurately recognized the differentiation of iPSC-RPEs and showed the potential to identify the candidate cells with ideal features and simultaneously exclude cells with immature/abnormal phenotypes. This rapid screening/classification system may facilitate the translation of iPSC-based technologies into clinical uses, such as cell transplantation therapy.

BlueLight: An Open Source DICOM Viewer Using Low-Cost Computation Algorithm Implemented with JavaScript Using Advanced Medical Imaging Visualization.

Recently, WebGL has been widely used in numerous web-based medical image viewers to present advanced imaging visualization. However, in the scenario of medical imaging, there are many challenges of computation time and memory consumption that limit the use of advanced image renderings, such as volume rendering and multiplanar reformation/reconstruction, in low-cost mobile devices. In this study, we propose a client-side rendering low-cost computation algorithm for common two- and three-dimensional medical imaging visualization implemented by pure JavaScript. Particularly, we used the functions of cascading style sheet transform and combinate with Digital Imaging and Communications in Medicine (DICOM)-related imaging to replace the application programming interface with high computation to reduce the computation time and save memory consumption while launching medical imaging interpretation on web browsers. The results show the proposed algorithm significantly reduced the consumption of central and graphics processing units on various web browsers. The proposed algorithm was implemented in an open-source web-based DICOM viewer BlueLight; the results show that it has sufficient rendering performance to display 3D medical images with DICOM-compliant annotations and has the ability to connect to image archive via DICOMweb as well.Keywords: WebGL, DICOMweb, Multiplanar reconstruction, Volume rendering, DICOM, JavaScript, Zero-footprint.

Deep Learning-Based Computer-Aided Diagnosis of Rheumatoid Arthritis with Hand X-ray Images Conforming to Modified Total Sharp/van der Heijde Score.

INTRODUCTION: Rheumatoid arthritis (RA) is a systemic autoimmune disease; early diagnosis and treatment are crucial for its management. Currently, the modified total Sharp score (mTSS) is widely used as a scoring system for RA. The standard screening process for assessing mTSS is tedious and time-consuming. Therefore, developing an efficient mTSS automatic localization and classification system is of urgent need for RA diagnosis. Current research mostly focuses on the classification of finger joints. Due to the insufficient detection ability of the carpal part, these methods cannot cover all the diagnostic needs of mTSS. METHOD: We propose not only an automatic label system leveraging the You Only Look Once (YOLO) model to detect the regions of joints of the two hands in hand X-ray images for preprocessing of joint space narrowing in mTSS, but also a joint classification model depending on the severity of the mTSS-based disease. In the image processing of the data, the window level is used to simulate the processing method of the clinician, the training data of the different carpal and finger bones of human vision are separated and integrated, and the resolution is increased or decreased to observe the changes in the accuracy of the model. RESULTS: Integrated data proved to be beneficial. The mean average precision of the proposed model in joint detection of joint space narrowing reached 0.92, and the precision, recall, and F1 score all reached 0.94 to 0.95. For the joint classification, the average accuracy was 0.88, and the accuracy of severe, mild, and healthy reached 0.91, 0.79, and 0.9, respectively. CONCLUSIONS: The proposed model is feasible and efficient. It could be helpful for subsequent research on computer-aided diagnosis in RA. We suggest that applying the one-hand X-ray imaging protocol can improve the accuracy of mTSS classification model in determining mild disease if it is used in clinical practice.

Realizing digital signatures for medical imaging and reporting in a PACS environment.

According to Taiwan's legislation pertaining to the protection of electronic data, the creators of electronic medical records (EMR) are solely responsible for the security of EMR. However, actual implementations that fulfill the security standards and requirements for electronic medical record systems are still lacking. Most EMR created from picture archive and communication system are not considered secure, as security protection mechanisms have not yet been granted legal status. This paper describes the details of establishing a digital signature system using Taiwan health professional cards. A digital signature system has been included to ensure quality assurance (QA) operations are controlled by technicians, and reporting capabilities have been provided for radiologist. Six imaging modalities and eight types of radiology reports have also been included in the system. Results indicate that the process of creating QA signatures does not have an adverse effect on the workflow of the facility, requiring less time for the signing and verification of radiology reports. This system has already been used routinely online in a real clinical setting for more than 2 years.

Use of a rich internet application solution to present medical images.

Browser with Rich Internet Application (RIA) Web pages could be a powerful user interface for handling sophisticated data and applications. Then the RIA solutions would be a potential method for viewing and manipulating the most data generated in clinical processes, which can accomplish the main functionalities as general picture archiving and communication system (PACS) viewing systems. The aim of this study is to apply the RIA technology to present medical images. Both Digital Imaging and Communications in Medicine (DICOM) and non-DICOM data can be handled by our RIA solutions. Some clinical data that are especially difficult to present using PACS viewing systems, such as ECG waveform, pathology virtual slide microscopic image, and radiotherapy plan, are as well demonstrated. Consequently, clinicians can use browser as a unique interface for acquiring all the clinical data located in different departments and information systems. And the data could be presented appropriately and processed freely by adopting the RIA technologies.

Embedding a hiding function in a portable electronic health record for privacy preservation.

The objective of this study was to develop a method to hide information in a portable electronic health record (PEHR). In compliance with HIPAA guidelines, a hiding function for personal identifiers in a PEHR was implemented by recognizing and hiding techniques. The method emphasizes the feasibility of embedding a hiding function in a PEHR. The hiding function could be executed to hide identifiers in offline mode. The present study showed that embedding the hiding function in a PEHR is a practical way not only satisfies data confidentiability needs, but also meets patient's personal privacy requirements. The effects of executing the hiding function would be the same as through de-identification or anonymization process.

Applying a presentation content manifest for signing clinical documents.

In this paper, we demonstrate how to digitally sign a content manifest of a presentable clinical document that contains multiple clinical data with presentations. Only one signature is needed for an entire clinical document with multiple data resources, which can reduce the computation time during signing and verifying processes. In the radiology field, a report may contain text descriptions, images, and annotations that are stored separately in different data resources. The manifest signature would be a proper means for integrity checking for all the clinical data within the manifest. The manifest signature can be extended with a trusted third party to add a digital time signature for long-term verifiability. The performance of the manifest signing compared with that of a traditional digital signing was evaluated. The new manifest signature can be used for signing different types of presentable clinical documents, such HL7 CDA documents and DICOM image reports.

Privacy preservation and information security protection for patients' portable electronic health records.

As patients face the possibility of copying and keeping their electronic health records (EHRs) through portable storage media, they will encounter new risks to the protection of their private information. In this study, we propose a method to preserve the privacy and security of patients' portable medical records in portable storage media to avoid any inappropriate or unintentional disclosure. Following HIPAA guidelines, the method is designed to protect, recover and verify patient's identifiers in portable EHRs. The results of this study show that our methods are effective in ensuring both information security and privacy preservation for patients through portable storage medium.

A web-based solution for viewing large-sized microscopic images.

This paper demonstrates a pure web-based solution enabling the presentation of scanned pathologic microscopic images on the web. For each slide, an entire specimen is scanned, and a high-resolution digital image (in the order of giga-pixels) is reconstructed. These huge images are then tiled into many 256 x 256-pixel blocks with different resolutions, and information about the blocks of each scanned slide is included in an extensible markup language metafile. Based on the data, a virtual microscopy system is created for viewing the scanned pathologic slides on web. The functionalities (changing viewing resolution, location adjustment, and multimedia annotation presentation) of our virtual slide viewing system are accomplished using pure hypertext markup language (HTML) and JavaScript. We show that there is no need to add plug-in components to browsers in order to handle virtual slides on the web. In a heterogeneous healthcare environment, methods using pure HTML and JavaScript to deal with pathologic content are more appropriate than using proprietary technologies supported only by specific browsers.