Publications & Research
The Medical Imaging and Technology Alliance (MITA), a division of the National Electrical Manufacturers Association (NEMA), is the leading organization and collective voice of medical imaging equipment, radiation therapy and radiopharmaceutical manufacturers, innovators and product developers. It represents companies whose sales comprise more than 90 percent of the global market for medical imaging technology including those that produce:
- Medical X-ray equipment
- Computed tomography (CT) scanners
- Nuclear imaging
- Radiation therapy equipment
- Magnetic resonance imaging (MRI)
- Imaging information systems
Medical imaging technology is manufactured by numerous companies with operations located throughout the United States, and is utilized in tens of thousands of hospitals, clinics, urgent care centers and physicians’ and dentists’ offices. One state where the manufacturing of high technology equipment like medical imaging equipment is particularly important is Pennsylvania. This study examines the role of medical imaging equipment in the Pennsylvania economy, and quantifies its “economic footprint.”
Medical Imaging Technology Industry Supports Nearly 12,000 Jobs and Generates Over $2.5 Billion in Total Economic Activity in PennsylvaniaJuly 2015
Washington, D.C. – The Medical Imaging & Technology Alliance (MITA), a division of National Electrical Manufacturers Association (NEMA), today announced that the medical imaging technology industry supports an estimated 11,746 jobs and generates approximately $2.83 billion in total economic activity in Pennsylvania, with an additional 5,100 direct and indirect jobs elsewhere in the United States, according to a new economic impact analysis commissioned by the organization.
“This research illustrates the tremendous economic impact of the medical imaging technology industry in Pennsylvania,” said NEMA President and CEO Kevin J. Cosgriff. “Medical imaging jobs are important throughout the Commonwealth as these jobs pay on average more than $100,000 annually in wages and benefits. They are a key part of the tax base of many Pennsylvania localities. Unfortunately, by diverting resources that could otherwise be applied towards the development of new technologies, the medical device excise tax is an ongoing threat to this booming industry sector. We are grateful for the support of Congressmen Chaka Fattah and Brendan Boyle, whose districts support nearly 2,000 jobs linked to the medical imaging sector, for their support of device tax repeal in the House, along with other Pennsylvania lawmakers who have endorsed policies that promote economic growth and medical innovation.”
The analysis evaluated the direct impact of the manufacture and use of medical imaging equipment and technology in Pennsylvania, the impact of activity generated by suppliers to the industry, and the impact induced by the spending of industry and supplier employees. It found the production of medical imaging technology and its use in hospitals and other medical facilities yields over $1.6 billion in direct economic output in the state. Additionally, the people and firms involved in the industry provide about $404 million in revenues to the federal, state and local governments, of which about $74 million go to state and local Pennsylvania governments.
“Medical imaging plays a crucial role in human health and contributes in significant – and ever more important ways – to our nation’s economic strength and global competitiveness,” said Mary Woolley, President and CEO of Research!America. “As this report makes clear, Pennsylvania is helping to grow this important industry. Fueling 12,000 jobs, $970 million in wages, and more than $2.8 billion in economic activity, Pennsylvania’s medical imaging technology companies are not only boosting economic progress, they are driving medical progress.”
The jobs directly created by the industry have average wages and benefits of over $101,000, while those supplying goods and services have average wages topping $74,600 per year. Manufacturers in Pennsylvania are leading the development of many innovative medical imaging devices, including diagnostic tools for detecting, diagnosing and monitoring cancer and other diseases, which have been shown to improve health outcomes and lower long-term health costs.
The analysis was conducted by John Dunham and Associates using data provided by Dun & Bradstreet, Inc., industry sources and the Pennsylvania state government. It utilizes an economic modeling framework known as IMPLAN, which is based on the national income accounts generated by the US Department of Commerce.
The Medical Imaging & Technology Alliance (MITA), a division of NEMA, is the collective voice of medical imaging equipment, radiation therapy and radiopharmaceutical manufacturers, innovators and product developers. It represents companies whose sales comprise more than 90 percent of the global market for medical imaging technology. For more information, visit www.medicalimaging.org. Follow MITA on Twitter @MITAToday.
A. No, the vendor’s quality control program is carefully crafted with the specific design of the hardware and software in mind and should be followed. Service and manufacturer personnel are trained according to these manufacturer procedures and are best able to assist you using these vendor QC tests. Show Preview
Q. Can the ACR QC manual replace the vendor recommended QC program?
A. No, the vendor’s quality control program is carefully crafted with the specific design of the hardware and software in mind and should be followed. Service and manufacturer personnel are trained according to these manufacturer procedures and are best able to assist you using these vendor QC tests. In addition, failure to maintain the system using the QC protocols, procedures, and frequencies recommended by the manufacturer may result in voiding of warranties and may be in violation of your purchase or service agreement. The ACR QC manual can be used as a supplement to manufacturer QC for troubleshooting purposes but should not be used to determine if the machine is within its operating specifications.
Q. How do the vendors establish their QC program?
A. Manufacturer QC programs are based on the FDA-recognized international consensus standards IEC 61223-3-5 and 61223-2-6 for Acceptance and Constancy testing. IEC standards are developed as an international collaborative effort between manufacturers, regulators, and academic scientists.
Q. What if a scanner does not pass a specification recommended by the ACR in their QC manual or a specification that the medical physicist designed?
A. First, repeat the test to confirm the result. Next, consult the vendor’s Technical Manual. If the same type of test is provided in the vendor’s technical manual run the test as specified by the vendor and apply the vendor’s specification. If the vendor’s specification is passing and the clinical images do not have a clinically significant image quality issue, corrective action is likely not needed. If the vendor-provided test result is outside the vendor’s specification, or there is believed to be a clinically significant degradation of image quality the images used for diagnosis, your Service engineer should be contacted.
If the vendor does not provide specifications for a particular test, then the ACR or medical physicist’s test result should be benchmarked and monitored over time. Please note additional testing outside of the vendor specifications may not be supported by the manufacturer.
Q. My machine passes all the vendor specifications, but when I apply my clinical protocol to the ACR phantom I get a failing result. What could be the problem?
A. Some elements of a clinical protocol, such as the reconstruction algorithm, may make assumptions that apply to human anatomy but may cause distortion in phantom images. For example, beam hardening or scatter corrections may perform differently in phantoms than in patient and distort CT numbers or lead to artifacts. The hardness of the x-ray beam can also vary among scanner models,
shifting CT numbers relative to non-vendor specifications. In addition, specifications that involve adaptive aspects of clinical protocols, such as iterative reconstruction or size-specific calibration files, can depend on precise interaction of phantom, test object, and protocol.
Q. For pediatric bodies, my system produces CTDI values using the 32cm phantom. The ACR instructions use the 16cm phantom. Can you clarify this difference?
A. The manufacturer reports dose according the most recent IEC standard (60601-2-44 v 3.1), which states the 32cm should be used for all body CTDI values. It is our understanding the ACR will update their instructions to reflect this update in the future.
Q. The ACR QC Manual beam width test contains a note stating: “It has been the experience of the ACR CTAP Physics Subcommittee that most scanners can be calibrated to meet these tighter standards.” Is this the case?
A. No. Service engineers are unable to alter manufacturer specifications and, in fact, for each installation must attest on FDA form 2579 that the assembled components were installed according to manufacturer specifications.
Q. Can you clarify the scope of “Acceptance testing”?
A. Acceptance testing encompasses testing carried out after new equipment has been installed, or major modifications have been made to existing equipment, in order to verify compliance with contractual specifications. This testing should be con
X-ray phase-contrast micro-tomography (XPCMT) is an important method for the non-destructive acquisition of internal information from samples composed of low-Z elements. During the development of XPCMT, its spatial resolution has gradually been improved; however, insufficient attention has been directed towards the improvement of its time resolution. The low time resolution of XPCMT restricts its applications in fast dynamic processes, such as the fermentation process and alloy growth. In this paper, we demonstrate a fast XPCMT method developed by combining the compressed sensing (CS) theory with XPCMT. This method allows for the accurate reconstruction of images using undersampled XPCMT data, thus achieving higher time resolution and simultaneously reducing the dose delivered to the samples; the latter is especially beneficial in medical applications. The CS-XPCMT algorithm was validated using experimental data from two samples, Fructus Foeniculi and a live ant, collected at the X-ray imaging and biomedical application beamline of the Shanghai Synchrotron Radiation Facility. The results for Fructus Foeniculi demonstrate that the CS-XPCMT algorithm yields good reconstruction accuracy for incomplete and undersampled data. Furthermore, the results for the live ant demonstrate that the CS-XPCMT algorithm is capable of performing fast XPCMT and is a potential method for the realisation of dynamic XPCMT, given appropriately upgraded experimental devices.
We examined Medicare national coverage determinations for medical interventions to determine whether or not they have become more restrictive over time. National coverage determinations address whether particular big-ticket medical items, services, treatment procedures, and technologies can be paid for under Medicare. We found that after we adjusted for the strength of evidence and other factors known to influence the determinations of the Centers for Medicare and Medicaid Services (CMS), the evidentiary bar for coverage has risen. More recent coverage determinations (from mid-March 2008 through August 2012) were twenty times less likely to be positive than earlier coverage determinations (from February 1999 through January 2002). Furthermore, coverage during the study period was increasingly and positively associated both with the degree of consistency of favorable findings in the CMS reviewed clinical evidence and with recommendations made in clinical guidelines. Coverage policy is an important payer tool for promoting the appropriate use of medical interventions, but CMS’s rising evidence standards also raise questions about patients’ access to new technologies and about hurdles for the pharmaceutical and device industries as they attempt to bring innovations to the market.
Essential Questions for Consideration in the Design of INTERVENTIONAL X-RAY EQUIPMENT Intended for Pediatric UseJanuary 2015
This document is intended to capture the consensus reached between Image Gently (IG) and the MITA FLUOROSCOPY Interventional Working Group (IWG) to develop a position paper on a list of essential questions that should be considered in the design of INTERVENTIONAL X-RAY equipment intended for pediatric use.
This list of essential questions seeks to increase awareness of design considerations for manufacturers with a goal of improving pediatric imaging. This list is not intended to be used or interpreted as being a standard document and does not represent a list of requirements or components and hence is not appropriate for use as a checklist or other similar manner. Further, the rationales in this document represent examples of possible approaches and are not prescriptive or definitive answers. Manufacturers may have different conclusions and/or provide alternative solutions. All questions may not be applicable in all instances. It is anticipated that no manufacturer will answer affirmatively for all questions.
This work fits in the collaborative iterative process initiated in November 2012 between IG and the IWG to drive the management of radiation dose and image quality on interventional x-ray equipment used on pediatric patients. These essential questions and rationales were initiated by experienced pediatric end users and reviewed by manufacturer representatives.
99mTc is the most widely used radionuclide in nuclear medicine. The reactor stoppages that occurred in recent years illustrated the vulnerability of the availability of radiotracers for imaging. With many of the reactors due for shutdown over the next 5–10 y, alternative routes to producing the 99Mo/99mTc pair are being explored. This brief review examines how we have reached this situation and what the near and distant future holds for securing the availability of these radioisotopes.
Ultrasound images are difficult to segment due to presence of speckle noise and the boundaries of abnormal regions are also difficult to recognize due to similarity. It is important to segment the image for correct and effective diagnosis. Manual method of segmentation is good but not effective for segmentation of large data sets, due to this an automatic or computerized segmentation is motivated. An automatic region growing segmentation for ultrasound images is presented in this work. An automatic selection of seed is adopted because of time consumption, poor accuracy and need of human interaction in manual seed selection. In ultrasound images, identification of the boundaries of abnormal regions is impossible but automatic seed selection provides accurate location of abnormal regions. The proposed method outperforms the existing state-of-the-art techniques based on the texture features and visual results.