The productivity gains, diagnostic benefit, and enhanced data availability to clinicians enabled by picture archiving and communication systems (PACS) are no longer in doubt. However, commercial PACS offerings are often extremely expensive initially and require ongoing support contracts with vendors to maintain them. Recently, several open-source offerings have become available that put PACS within reach of more users. However, they can be resource-intensive to install and assure that they have room for future growth—both for computational and storage capacity. An alternate approach, which we describe herein, is to use PACS built on virtual machines which can be moved from smaller to larger hardware as needed in a just-in-time manner. This leverages the cost benefits of Moore's Law for both storage and compute costs. We describe the approach and current results in this paper.

The attractions of virtual computing are many: reduced costs, reduced resources and simplified maintenance. Any one of these would be compelling for a medical imaging professional attempting to support a complex practice on limited resources in an era of ever tightened reimbursement. In particular, the ability to run multiple operating systems optimized for different tasks (computational image processing on Linux versus office tasks on Microsoft operating systems) on a single physical machine is compelling. However, there are also potential drawbacks. High performance requirements need to be carefully considered if they are to be executed in an environment where the running software has to execute through multiple layers of device drivers before reaching the real disk or network interface. Our lab has attempted to gain insight into the impact of virtualization on performance by benchmarking the following metrics on both physical and virtual platforms: local memory and disk bandwidth, network bandwidth, and integer and floating point performance. The virtual performance metrics are compared to baseline performance on “bare metal.” The results are complex, and indeed somewhat surprising.

This software tool locates and computes the intensity of radiation skin dose resulting from fluoroscopically guided interventional procedures. It is comprised of multiple modules. Using standardized body specific geometric values, a software module defines a set of male and female patients arbitarily positioned on a fluoroscopy table. Simulated X-ray angiographic (XA) equipment includes XRII and digital detectors with or without bi-plane configurations and left and right facing tables. Skin dose estimates are localized by computing the exposure to each 0.01 × 0.01 m2 on the surface of a patient irradiated by the X-ray beam. Digital Imaging and Communications in Medicine (DICOM) Structured Report Dose data sent to a modular dosimetry database automatically extracts the 11 XA tags necessary for peak skin dose computation. Skin dose calculation software uses these tags (gantry angles, air kerma at the patient entrance reference point, etc.) and applies appropriate corrections of exposure and beam location based on each irradiation event (fluoroscopy and acquistions). A physicist screen records the initial validation of the accuracy, patient and equipment geometry, DICOM compliance, exposure output calibration, backscatter factor, and table and pad attenuation once per system. A technologist screen specifies patient positioning, patient height and weight, and physician user. Peak skin dose is computed and localized; additionally, fluoroscopy duration and kerma area product values are electronically recorded and sent to the XA database. This approach fully addresses current limitations in meeting accreditation criteria, eliminates the need for paper logs at a XA console, and provides a method where automated ALARA montoring is possible including email and pager alerts.

A typical choice faced by Picture Archiving and Communication System (PACS) administrators is deciding how many PACS workstations are needed and where they should be sited. Oftentimes, the social consequences of having too few are severe enough to encourage oversupply and underutilization. This is costly, at best in terms of hardware and electricity, and at worst (depending on the PACS licensing and support model) in capital costs and maintenance fees. The PACS administrator needs tools to asses accurately the use to which her fleet is being subjected, and thus make informed choices before buying more workstations. Lacking a vended solution for this challenge, we developed our own.

Researchers in medical imaging have multiple challenges for storing, indexing, maintaining viability, and sharing their data. Addressing all these concerns requires a constellation of tools, but not all of them need to be local to the site. In particular, the data storage challenges faced by researchers can begin to require professional information technology skills. With limited human resources and funds, the medical imaging researcher may be better served with an outsourcing strategy for some management aspects. This paper outlines an approach to manage the main objectives faced by medical imaging scientists whose work includes processing and data mining on non-standard file formats, and relating those files to the their DICOM standard descendents. The capacity of the approach scales as the researcher’s need grows by leveraging the on-demand provisioning ability of cloud computing.

Radiology examinations are large. The advent of fast volume imaging is making that statement truer every year. PACS are based on the assumption of fast local networking and just-in-time image pull to the desktop. On the other hand, teleradiology has been developed on a push model to accommodate the challenges of moderate bandwidth, high-latency wide area networks (WANs). Our group faced the challenging task of creating a PACS environment that felt local, while pulling images across a 3,000-mile roundtrip WAN link. Initial tests showed WAN performance lagging local area network (LAN) performance by a factor of 30 times. A 16-month journey of explorations pulled the WAN value down to only 1.5 times slower than the LAN.

The U.S. National Press has brought to full public discussion concerns regarding the use of medical radiation, specifically x-ray computed tomography (CT), in diagnosis. A need exists for developing methods whereby assurance is given that all diagnostic medical radiation use is properly prescribed, and all patients’ radiation exposure is monitored. The “DICOM Index Tracker©” (DIT) transparently captures desired digital imaging and communications in medicine (DICOM) tags from CT, nuclear imaging equipment, and other DICOM devices across an enterprise. Its initial use is recording, monitoring, and providing automatic alerts to medical professionals of excursions beyond internally determined trigger action levels of radiation. A flexible knowledge base, aware of equipment in use, enables automatic alerts to system administrators of newly identified equipment models or software versions so that DIT can be adapted to the new equipment or software. A dosimetry module accepts mammography breast organ dose, skin air kerma values from XA modalities, exposure indices from computed radiography, etc. upon receipt. The American Association of Physicists in Medicine recommended a methodology for effective dose calculations which are performed with CT units having DICOM structured dose reports. Web interface reporting is provided for accessing the database in real-time. DIT is DICOM-compliant and, thus, is standardized for international comparisons. Automatic alerts currently in use include: email, cell phone text message, and internal pager text messaging. This system extends the utility of DICOM for standardizing the capturing and computing of radiation dose as well as other quality measures.

Academic medical centers, in general, and radiation oncology research, in particular, rely heavily on custom software tools and applications. The code development is typically the responsibility of a single individual or at most a small team. Often these individuals are not professional programmers but physicists, students, and physicians. While they possess domain expertise and algorithm knowledge, they often are not fully aware of general “safe coding” practices—nor do they need the full complexity familiar in large commercial software projects to succeed. Rather, some simple guidelines we refer to as “programming in the small” can be used.

With each medical center department creating and maintaining its own patient care-related data, nursing and house staff may find it confusing to log into all the information systems necessary to achieve a global perspective of the patient’s state. The Medical Information Network Database application provides a logically centralized Worldwide Web viewing application for the physically distributed data. In addition to coordinating data displays for histories, laboratories, pathology, radiology, and discharge summaries, the application can be configured to apply rule sets to the data and remind caregivers of follow-up tests or of possible reactions to treatment protocols. The viewing client runs on any HTML 2.0-compliant browser, although certain applet enhancements (notably for viewing radiological images) require a browser with Java abilities. With this “thin client” approach, the application can be configured to coexist with other applications (such as a PACS viewer), thus centralizing information and reducing the overall number of computers in the medical center.