PAC system is extending increasingly from the now well-established radiology applications into a hospital-wide PACS. New challenges are accompanying its spread into other clinical fields. With awareness of the importance of PAC systems among various medical experts, this system has been enhanced through the PAC system's pipeline, and simplification of image display for analysis via an interaction with the user. Generally PAC system consists of medical image, patients' data acquisition, storage, and display subsystems integrated by digital networks and application software. PAC system facilitates the systematic utilization of medical imaging for patient care. However, even though PAC system consist of medical image, data acquisition, storage and display subsystems, most of available PAC system does not have image analysis as required by the clinical expert. If the PAC system do have this element, it need interaction or interference from the clinical expert as user, and the PAC system storage mostly is an unstructured storage with no analysis element and report modules. And unfortunately in most cases, for the web-based PAC system, there are delayed in retrieval and visualize the required image from outside of the hospital. Most of the PACS with function of 3D display, it did not communicate information clearly and efficiently to users (clinical expert). Most of the visualization did not visual accurate information as required by the clinical expert. These listed constraints limited the clinical expert perspective regarding his/her decision.

From market validation observation we concluded that most of the PAC system available in market does not have medical image processing functions for the purposes of decision analysis with minimum user interaction. Research towards this limitation has been conducted in accordance with the needs of clinical experts. Among these studies are: (i) angiography image processing for stenosis position detection and measurement of its dimensions, (ii) echocardiography image processing for detection of ventricular cardiac abnormalities (walls and volume) and (iii) 2D angiography images reconstructed to 3D images for display purposes and to identify the location of artery tree.

With the result of these studies, the PAC system will integrate with extra modules, which are: i) 3D reconstruction function from single image angiogram with identification of the stenosis location, ii) Identification of abnormality heart wall chamber, iii) 3D reconstruction echocardiography left and right ventricular heart, and iv) 3D fused within CTA, angiography and MRI.

As stated above, the common limitation for the web-based PAC system is the delayed in retrieval and visualize the required image from outside of the hospital/clinics. To overcome this limitation, we proposed a technique and integrated a related function for faster transmission of the processed image without sacrifice any importance information. And to complete the PAC system so that the new PAC system able to compete with current PAC system that available in market, we link the PACS with our Patients Clinical Record Database with report modules as required by the medical expert.

The outputs of all those said researches will be integrated with the PAC system where each research output has been tested and validate by numbers of cardiac expert, the patients clinical record database has been tested in UKMMC and the PAC system currently being beta tested in a Private Clinic in Kelang, Selangor, Malaysia. Eventually the PAC system with the Patients Clinical Record Database will be integrated with these image analysis and 3D image visualization and it is plan to be tested in Veterinary Hospital of Universiti Putra Malaysia.

To forward this project to commercialization activity, we have distributed questioners to Clinics in area Bangi (Selangor, Malaysia) and Nilai (Negeri Sembilan, Malaysia). There are 58 Medical, Veterinary and Dental Clinics received the questioner (currently we expand the distribution towards Serdang and Kajang (Selangor, Malaysia). Out of 58 clinics; a) 16% interested to collaborate and looking forward to see PAC system, b)8% interested with the PAC system but do not willing to have any demo, c) 44% not interested but open for demo of system, d) 28% not interested and not willing to have demo system and e) 4% return the form without answered for that particular question.

To secure and protect the ownership, each research output has been submitted for Patent filed in Malaysia and with three chosen country, where 2 of the patent filed has been granted in Malaysia. We also copyrighted each module. This project has been selected by Universiti Putra Malaysia to be commercialized by a startup company seeded by UPM (CASD Medical Private Limited) under program INNOHUB.

We realize to implement the complete PAC system in Hospital there are 10 main problems exist that we might need to overcome or try to minimize the consequences. These problems are; i) Integration with the Hospital Information System. Although a lack of inter-vendor device and IT integration can often make the problem worse, the market is improving as providers and meaningful use demand greater integration. Unfortunately, still, many radiologists and PACS administrators prefer to make full use of hospital IT to configure their own systems and achieve a bit more autonomy, ii) Every system has downtime where we need to establish alternate workflows. Both scheduled and unscheduled, but they need not have to be too serious to minimize the effect on patient care, iii) Non-standardized hanging protocol display is a common and pesky challenge for PACS users. Images from different modalities are not organized by default even though each of them generally will be transmitted through DICOM format getaway, each study takes a little longer to read. As the number of scanners increases and the sample of vendors expands, the problem grows worse, iv) Integration problems concern hardware, from digitizing pre-DICOM modalities to integrating systems for advanced image reconstruction. Add-ons like a DICOM converter can help squeeze out additional value from older CT, angiography and fluoroscopy systems, v) As with downtime, failures are unavoidable, there is a need to demonstrate strong support activities, vi) Effective training can be a cost-effective way to demonstrate to administrators and physicians many of PACS' underused and undervalued features. Training wil help to expose staff to what the system can do to make their jobs easier and more efficient, vii) The migration of data to the new PACS is often the most challenging part of the process, both in negotiating the release of data from the current PACS and in sorting out all the data entry errors that have accumulated over the lifespan of the system, viii) As other specialties realize the value of PACS, the system is slowly being taken out of radiologists' hands. PACS has become a mission-critical enterprise-wide tool used by nearly all specialties. With this change, decision-making for PACS-related purchases, upgrades and configurations has, in some cases, shifted from radiologists to a more central process, ix) Hiring a certified public ergonomist to evaluate the department's workstations can ease radiologists' repetitive stress symptoms and contribute substantially to productivity. Despite accelerating advances in technology, many interface tools have changed little since the introduction of PACS, and finally x) Like business continuity, disaster recovery can prevent a painful experience from becoming fatal. Many hospitals opt for either redundant servers, cloud storage or both. At the very least, preparation for downtime can spare physicians and patients from experiencing significant losses.

To minimize the consequences of the listed 10 main problems, this project (in early stage) targeting potential customers among the owner of the small private clinics where the numbers of patients is less and the bureaucracy of the administration is limited.


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