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Page 12 of 16                                        Brunsing et al. Hepatoma Res 2020;6:59  I  http://dx.doi.org/10.20517/2394-5079.2020.50

















               Figure 6. MRI multiarterial phase acquisition (Arterial phase 1-5): the multiphase acquisition in a single breath hold allows capturing
               the optimally timed arterial phase for HCC detection (in this example, arterial phase 5). A 8 mm observation with nonrim APHE is
               seen in segment 6, confirmed as a suspicious observation due to restricted diffusion (arrows). MRI: magnetic resonance imaging; HCC:
               hepatocellular carcinoma; APHE: arterial phase hyperenhancement; DWI: diffusion weighted imaging


               Objective assessment and wide-spread implementation of AMRI may require the development of new,
               exam-specific billing codes, like what was done for MR Elastography in 2019. Other countries will likely
               have to weigh the efficacy, availability, and relative costs to determine the feasibility of AMRI in practice.


               While increasing sensitivity by using AMRI addresses one of the problems of surveillance US, it does not
                                                                         [60]
               solve the problem of poor compliance with surveillance programs . The reasons for poor compliance
               are complicated and not entirely understood. Contributing factors in the United States may include
                                              [60]
               wait times and access to specialists . It is not clear if a surveillance modality that requires intravenous
               contrast and screening like MRI would pose an additional barrier for patient compliance. There is the
               potential that the higher sensitivity of AMRI would allow for less frequent surveillance, perhaps from
                                                                                              [61]
               twice a year (the current standard) to only once a year, as has been previously proposed . However,
               increasing the surveillance interval remains a theoretical benefit of AMRI and it is unclear if this would
                                [62]
               improve compliance . The impact of AMRI on surveillance compliance should be included in prospective
               comparative studies.

               No study to date has directly compared the different AMRI approaches, and head-to-head studies will be
               needed to determine the optimal approach. It is possible that no one approach will be best in all patients,
               and tailored strategies may be needed.


               FUTURE DIRECTION: MEETING CHALLENGES OF MRI WITH NEW TECHNOLOGY
               Existing data suggests that AMRI techniques maintain the high sensitivity of complete MRI examinations,
                                                                        [63]
               however there remains room for improvement and innovation . Human and technical factors can
               contribute to artifacts and undermine image quality, reducing sensitivity for malignancy, especially small
               lesions. MRI is extremely versatile with many ways to collect data during image acquisition and continuous
               development of tools for image reconstruction.

               Recent advances [64-70]  that allow acquisition of multiple arterial phases in a single breath hold are finding
               their way into clinical practice, increasing the chances of capturing an optimally timed arterial phase, when
               HCC most commonly shows the highest degree of APHE [Figure 6].

               Motion artifacts commonly degrade liver MRI quality. Free-breathing MRI tools are being developed
               for dynamic post-contrast imaging [71,72] , HBP imaging [73,74] , and DWI [75-77] , as are tools to address cardiac
               motion, which is particularly problematic in the left lobe of the liver [78-81] .


               There is great interest in applying artificial intelligence to improve MRI image quality, image registration,
               and workflow [73,82-84]  all of which are active areas of investigation.
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