Mika Kortesniemi’s research while affiliated with Helsinki University Central Hospital and other places

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Publications (1)


Figure 1. Overall patient risk including radiation risk and clinical risk as a function of dose. Dashed lines represent the optimum target. The units of both axes are arbitrary. Two examples of individual imaging procedures, each represented with three corresponding risk value datapoints, demonstrate different degrees of accuracy in meeting the optimisation target. 
Figure 2. Overall patient risk including radiation risk and clinical risk as a function of dose illustrated for a cohort of patients. Dashed lines represent the optimum target. Each individual imaging procedure is represented with three corresponding risk values. The minimum of the total risk across the population is noted by an arrow, reflecting the accuracy by which the optimisation is achieved for this cohort. The units on the axes are arbitrary. The 25-75 percentile range of total risk values in the cohort encompassing the minimum population risk, demonstrated by the solid horizontal line, represents the precision by which the optimisation is achieved. 
Medical imaging dose optimisation from ground up: Expert opinion of an international summit
  • Article
  • Full-text available

May 2018

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601 Reads

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49 Citations

Journal of Radiological Protection

Ehsan Samei

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Hannu Jarvinen

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Mika Kortesniemi

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As in any medical intervention, there is either a known or an anticipated benefit to the patient from undergoing a medical imaging procedure. This benefit is generally significant as demonstrated by the manner in which medical imaging has transformed clinical medicine. At the same time, when it comes to imaging that deploys ionizing radiation, there is a potential associated risk from radiation. Radiation risk has been recognized as a key liability in the practice of medical imaging, creating a motivation for radiation dose optimization. The level of radiation dose and risk in imaging is varied but is generally low. Thus, from epidemiological perspective, this makes the estimation of the precise level of associated risk highly uncertain. However, in spite of the low magnitude and high uncertainty of this risk, its possibility cannot be easily refuted. Therefore, given the moral obligation of healthcare providers, "first do no harm," there is an ethical obligation to mitigate this risk. How to precisely achieve this goal scientifically and practically within a coherent system has been lacking. To address this need, in 2016, the International Atomic Energy Agency (IAEA) organized a summit to clarify the role of Diagnostic Reference Levels to optimize imaging dose [1,2], summarized into an initial report [3]. Through a consensus building exercise, the summit further concluded that the imaging optimization goal goes beyond dose alone, and should include image quality as a means to include both the benefit and the safety of the exam. The present, second report details the deliberation of the summit on imaging optimization.

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Citations (1)


... In addition, to maximize the clinical utility of CT imaging, an understanding and characterization of image quality parameters are imperative. 3 In clinical practice, the quality of CT images is contingent upon multiple parameters, including spatial resolution 4 and noise power spectrum. 5 Spatial resolution serves as a critical metric for assessing the discernibility of adjacent structures within an image. ...

Reference:

A method for measuring spatial resolution based on clinical chest CT sequence images
Medical imaging dose optimisation from ground up: Expert opinion of an international summit

Journal of Radiological Protection