Studies in Health Technology and Informatics

Cloud computing is a recent and fast growing area of development in healthcare. Ubiquitous, on-demand access to virtually endless resources in combination with a pay-per-use model allow for new ways of developing, delivering and using services. Cloud computing is often used in an “OMICS-context”, e.g. for computing in genomics, proteomics and molecular medicine, while other field of application still seem to be underrepresented. Thus, the objective of this scoping review was to identify the current state and hot topics in research on cloud computing in healthcare beyond this traditional domain.

https://link.springer.com/content/pdf/10.1186%2Fs12911-015-0145-7.pdf

A scoping review of cloud computing in healthcare

Personal Health Records (PHRs) should remain the lifelong property of patients, who should be able to show them conveniently and securely to selected caregivers and institutions. In this paper, we present My PHR Machines, a cloud-based PHR system taking a radically new architectural solution to health record portability. In My PHR Machines, health-related data and the application software to view and/or analyze it are separately deployed in the PHR system. After uploading their medical data to My PHR Machines, patients can access them again from remote virtual machines that contain the right software to visualize and analyze them without any need for conversion. Patients can share their remote virtual machine session with selected caregivers, who will need only a Web browser to access the pre-loaded fragments of their lifelong PHR. We discuss a prototype of My PHR Machines applied to two use cases, i.e., radiology image sharing and personalized medicine.

Scalable and Secure Sharing of Personal Health Records in Cloud Computing using Attribute–Based Encryption

PACS and Imaging Informatics: Basic Principles and Applications

In 2018, clinics and hospitals were hit with numerous attacks leading to significant data breaches and interruptions in medical services. An attacker with access to medical records can do much more than hold the data for ransom or sell it on the black market. 
In this paper, we show how an attacker can use deep-learning to add or remove evidence of medical conditions from volumetric (3D) medical scans. An attacker may perform this act in order to stop a political candidate, sabotage research, commit insurance fraud, perform an act of terrorism, or even commit murder. We implement the attack using a 3D conditional GAN and show how the framework (CT-GAN) can be automated. Although the body is complex and 3D medical scans are very large, CT-GAN achieves realistic results which can be executed in milliseconds. 
To evaluate the attack, we focused on injecting and removing lung cancer from CT scans. We show how three expert radiologists and a state-of-the-art deep learning AI are highly susceptible to the attack. We also explore the attack surface of a modern radiology network and demonstrate one attack vector: we intercepted and manipulated CT scans in an active hospital network with a covert penetration test. 
Demo video: this https URL
Source code: this https URL

CT-GAN: Malicious Tampering of 3D Medical Imagery using Deep Learning

Picture Archiving and Communication Systems (PACS) have been widely deployed in healthcare institutions, and they now constitute a normal commodity for practitioners. However, its installation, maintenance, and utilization are still a burden due to their heavy structures, typically supported by centralized computational solutions. In this paper, we present Dicoogle, a PACS archive supported by a document-based indexing system and by peer-to-peer (P2P) protocols. Replacing the traditional database storage (RDBMS) by a documental organization permits gathering and indexing data from file-based repositories, which allows searching the archive through free text queries. As a direct result of this strategy, more information can be extracted from medical imaging repositories, which clearly increases flexibility when compared with current query and retrieval DICOM services. The inclusion of P2P features allows PACS internetworking without the need for a central management framework. Moreover, Dicoogle is easy to install, manage, and use, and it maintains full interoperability with standard DICOM services.

/pdf/dicoogle-an-open-source-peer-to-peer-pacs-2ziu581hqu.pdf

Dicoogle - an open source peer-to-peer PACS.

The interoperability of services and the sharing of health data have been a continuous goal for health professionals, patients, institutions, and policy makers. However, several issues have been hindering this goal, such as incompatible implementations of standards (e.g., HL7, DICOM), multiple ontologies, and security constraints. Cross-enterprise document sharing (XDS) workflows were proposed by Integrating the Healthcare Enterprise (IHE) to address current limitations in exchanging clinical data among organizations. To ensure data protection, XDS actors must be placed in trustworthy domains, which are normally inside such institutions. However, due to rapidly growing IT requirements, the outsourcing of resources in the Cloud is becoming very appealing. This paper presents a software proxy that enables the outsourcing of XDS architectural parts while preserving the interoperability, confidentiality, and searchability of clinical information. A key component in our architecture is a new searchable encryption (SE) scheme-Posterior Playfair Searchable Encryption (PPSE)-which, besides keeping the same confidentiality levels of the stored data, hides the search patterns to the adversary, bringing improvements when compared to the remaining practical state-of-the-art SE schemes.

XDS-I Outsourcing Proxy: Ensuring Confidentiality While Preserving Interoperability

Clustering of distinct PACS archives using a cooperative peer-to-peer network

The anterior cruciate ligament tear is a common medical condition that is treated using arthroscopy by pulling a tissue graft through a tunnel opened with a drill. The correct anatomical position and orientation of this tunnel are crucial for knee stability, and drilling an adequate bone tunnel is the most technically challenging part of the procedure. This paper presents the first guidance system based solely on intra-operative video for guiding the drilling of the tunnel. Our solution uses small, easily recognizable visual markers that are attached to the bone and tools for estimating their relative pose. A recent registration algorithm is employed for aligning a pre-operative image of the patient’s anatomy with a set of contours reconstructed by touching the bone surface with an instrumented tool. Experimental validation using ex-vivo data shows that the method enables the accurate registration of the pre-operative model with the bone, providing useful information for guiding the surgeon during the medical procedure. Experiments also demonstrate that the guided drilling of the tunnel leads to errors as low as 2.5 mm in the footprint and $$1.8^\circ $$
 in orientation, which compares favourably to other works in the field.
 The high accuracy and short time overhead evinced by the experimental validation combined with no additional incisions or capital equipment make this video-based computer-aided arthroscopy solution an appealing alternative to the existing approaches.

Video-based computer navigation in knee arthroscopy for patient-specific ACL reconstruction.

ion allowing access to infrastructure resources (e.g. storage, computation, server, data center) on-demand and paid according to the required quality-of-service (QoS). • Platform layer: Known as Platform as a Service (PaaS) extends the IaaS layer by hiding the IaaS complexity. PaaS is accessed as one big system and not by accessing individual virtual machines. Therefore, it provides an abstraction where the virtual machines are automatically managed by the cloud service provider. Offering reliable services by default such as storage, databases and signalization. • Application layer: Layer usually entitled as Software as a Service (SaaS) where the applications hosted on the Cloud are deployed on local computers typically through web-browser. On this layer, the payment is associated with the application itself and not with the platform or infrastructure below it. Typically, this layer is where developers build their applications. The services themselves have long been referred to as Software as a Service (SaaS) and Cloud does not change that (Michael Armbrust, 2009). Nevertheless, Cloud Computing allows the application providers the choice of deploying their product as SaaS without providing a data center.

/pdf/current-trends-in-archiving-and-transmission-of-medical-4r9xdqau6i.pdf

Luís S. Ribeiro

Papers

Dicoogle - an open source peer-to-peer PACS.

XDS-I Outsourcing Proxy: Ensuring Confidentiality While Preserving Interoperability

Clustering of distinct PACS archives using a cooperative peer-to-peer network

Video-based computer navigation in knee arthroscopy for patient-specific ACL reconstruction.

Current Trends in Archiving and Transmission of Medical Images