In this issue of Academic Radiology , authors’ Scholtz et al investigate whether computed tomography (CT) radiation dose could be decreased without compromising image quality using a combination of techniques. Specifically, they retrospectively compared oncology patients scanned first on their institutions’ second-generation 120 kV 128-slice CT, and then, on a third-generation CT using automated tube voltage adaptation (TVA) in conjunction with an advanced modeled iterative reconstruction (ADMIRE), an upgrade. Their principal findings were that radiation dose was decreased by nearly 35% on average, with an associated improvement in image quality as evidenced by increased signal-to-noise ratio and contrast-to-noise ratio. This study is important for several reasons.
First, at a broad level, this article tackles one of the most scrutinized aspects of imaging: radiation exposure. Along with reimbursement issues and the job market, this is one of today’s “hottest” topics for our field–and, of these three, arguably the one over which we have the most control. Initially, pediatric radiation led the call to image As Low As Reasonably Achievable (ALARA). According to the United States Nuclear Regulatory Commission, Title 10, Section 20.1003, of the Code of Federal Regulations (10 CFR 20.1003), ALARA “means making every reasonable effort to maintain exposures to ionizing radiation as far below the dose limits as practical…taking into account the state of technology,” among other things . Thus, authors Scholtz et al should be congratulated for their efforts in investigating state-of-art technologies to minimize ionizing radiation exposure in medical imaging. They are addressing an important public health and safety issue.
Subsequent to As Low As Reasonably Achievable (ALARA), in 2009, the American College of Radiology (ACR) and Radiological Society of North American (RSNA) formed the Joint Task Force on Adult Radiation Protection and launched its Image Wisely, a campaign initiated with the stated “objective of lowering the amount of radiation used in medically necessary imaging studies and eliminating unnecessary procedures.” . The campaign mascot is an owl, and the campaign is wise in many respects, not the least of which is that it provides the useful reminder about the importance for multidisciplinary work in our field. The campaign is not ACR and RSNA radiologists acting alone, but rather in collaboration with the American Association of Physicists in Medicine and the American Society of Radiologic Technologists. The latter two organizations are known as our allied health professionals associations for a reason—we need to work together to optimize taking care of patients through imaging. In the case of research by Scholtz et al, for example, the successful implementation of automated TVA in conjunction with ADMIRE at any institution would require supervision by a medical physicist and training of the radiologic technologists before the radiologist herself could even begin image interpretation.
Second, at the patient level, the article by Scholtz et al is spot on the current era of personalized medicine. According to the United Stated Food and Drug Administration (FDA), this term means “tailoring of medical treatment to the individual characteristics, needs, and preferences of a patient during all stages of care, including prevention, diagnosis, treatment, and follow-up.” . For cross-sectional imaging involving ionizing radiation, this would mean optimizing and/or minimizing tube voltage in accordance with a patient’s anatomy, not only during diagnosis but also during follow-up, the latter constituting the cohort in Scholtz et al’s article. Automated TVA does this automatically, as the name suggests and therefore is not only laborsaving for the radiation technologist but also beneficial to the patient.
By definition, the stochastic effects of ionizing radiation cannot be precisely predicted; therefore, every effort to minimize radiation exposure is worthwhile. This may be particularly true in certain oncological patient populations, for example, those with Hodgkin’s lymphoma (HL), in which the generally young age and favorable prognosis must be weighed against the multiple serial follow-up CT examinations and their associated ionizing radiation . If automated TVA were implemented, not only would each individual CT convey less radiation but also the cumulative long-term “savings” could be impressive. For example, consider that in results of Scholtz et al, the average size-specific dose estimate (SSDE) on the first scanner without automated TVA was 15.2 mGy, compared with 9.9 mGy on the second scanner with automated TVA. For an HL patient who achieves remission, the National Comprehensive Cancer Network (NCCN) guidelines recommend surveillance CTs q6-12 months for 2–3 years, corresponding with 6–12 CTs. If an HL patient was scanned without automated TVA and received an average SSDE of 15.2 mGy, then this would translate into 91.2–182.4 mGy. In comparison, if an HL patient was scanned with the automated TVA and received an average SSDE of 9.9 mGy, then this would translate into 59.4–118.8 mGy. The latter would represent a significant interval decrease in accumulated ionizing radiation, potentially impactful on the patient’s risk of future radiation-induced cancer.
In the 1970s, when CT was “the new kid on the block,” even the initial two-slice model led to radical improvements in diagnosis given the rendered cross-sectional images. As a result, the use of CT increased at an exponential rate. In 1980, 3 million CTs were performed; in 2006, 62 million CTs were performed, leading authors Brenner et al to note in their 2007 NEJM article that, “although the risks for any one person are not large, the increasing exposure to radiation in the population may be a public health issue in the future.” . As the saying goes, the future is now–authors’ Scholtz et al are addressing this important health issue with their current research, published in this volume of Academic Radiology .
References
1. (USNRC) USNRC. ALARA. http://www.nrc.gov/reading-rm/basic-ref/glossary/alara.html2015 . [cited 2015 June 22, 2015].
2. RSNA Aa. Image Wisely. http://www.imagewisely.org/About-Us . [cited 2015 June 22, 2015].
3. (FDA) USFaDA. Personalized Medicine. http://www.fda.gov/scienceresearch/specialtopics/personalizedmedicine/default.htm2015 . [cited 2015 June 22, 2015].
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