The authors like to thank Stefanie Sauer, pharmacist at the Department of Pharmacy Heidelberg University Hospital, for her contributions to the MRI phantom. In addition, we would like to thank NORAS MRI products GmbH (H&#246;chberg, Germany) and especially Daniel Gareis for providing a prototype of the 16-channel multipurpose coil. Furthermore, we are grateful for the kind cooperation with SIEMENS Healthcare GmbH (Erlangen, Germany) and especially Mathias Nittka for their assistance in the sequence setup.

1. Phantom Preparation
<ol>
	<li>Determine the implant volume (e.g., by using the water displacement method). 
	NOTE: The volume of the CCT-T sample and the Z-T sample measured 0.65 mL and 0.73 mL, respectively.</li>
	<li>Fix the implant position in the middle of a non-ferromagnetic, plastic, waterproof box by using a thin thread. Use a box that is larger than the expected MRI artifacts. 
	NOTE: If no rough estimates of the artifact volumes of the implant and/or pulse sequence of interest are available, perform a test scan by placing the phantom in a box, approximately 10x larger than the phantom, filled with water. The artifact volumes in this study ranged from 7.3 mL (for the CCT-T sample) and 0.09 mL (for the Z-T sample).</li>
	<li>Carefully melt a mixture of semisynthetic fat (58.8%), water (40%), and macrogol-8-stearate (1.2%), using a water bath at 50 &#176;C. 
	NOTE: For the samples in this study, we used a 500 mL mixture for the embedding of each sample.
	<ol>
		<li>When the mixture becomes fluid, stop heating and start with slow stirring, and stop heating. Ensure that there is no separation of the fat and water phases.</li>
	</ol>
	</li>
	<li>As soon as clotting begins, slowly start embedding the implant with the mixture. For this, pour the embedding mixture slowly into the phantom box with the implant. 
	NOTE: Pouring must be performed slowly to avoid air inclusion.</li>
	<li>Place the phantom box with the embedded implant into the refrigerator at 4 &#176;C overnight for desiccation. The next day, remove any residual fluid parts by decantation.</li>
</ol>
2. MRI Examination
<ol>
	<li>Place the phantom (box with the embedded implant) in the MRI in the same orientation as in the in vivo situation. Position the middle of the phantom in the isocenter of the MRI.</li>
	<li>For measurements, use a coil which allows for a homogeneous signal distribution within the imaging volume without severe and obvious signal drops (e.g., a head coil).</li>
	<li>When planning the MRI scans at the MRI console, ensure that the phantom box, including some air at the edges of the box, is within the imaging volume.</li>
	<li>Next, perform the MRI examination.</li>
</ol>
3. Image Analysis and Post-processing
<ol>
	<li>Export the images without any loss of quality (e.g., by compression) from the MRI console (e.g., using the DICOM format). Import the images in an MRI post-processing software which allows for placing the region of interests (ROI), evaluating ROI signal intensities, a threshold-based segmentation, and a quantification of the segmentation volumes (see Table of Materials).</li>
	<li>To define the threshold for pile-up artifacts and check for a homogeneous signal distribution within the imaging volume, place lines perpendicular to each other and adjacent to the outer border of the visible artifact on the slice with the maximum artifact size (Figure 1a). 
	NOTE: Pile-up artifacts are displacement artifacts, presenting with areas with artificially high signal intensities. They occur in the slice direction and the readout direction.
	<ol>
		<li>Place a background ROI (ROIBackground) with 10 mm in diameter outside each of the four intersection points (Figure 1a). Place the lines and the background regions of interests using the segmentation editor.</li>
		<li>Measure the mean signal intensity and standard deviation (SD) of all voxels within these 4 ROIBackground values and for each ROIBackground separately. Use the tool Material Statistics in the project view.</li>
		<li>Ensure that the mean signal intensity of each ROI&#173;Background is within the range of &#177; 1.5 SD of the mean signal of each of the other 3 counterparts to guarantee a homogeneous signal distribution.</li>
		<li>Calculate the threshold for pile-up artifacts by adding 3 SD of ROIBackground to the mean signal intensity of all voxels of these 4 ROIBackground values. Perform a semiautomatic threshold-based segmentation of pile-up artifacts by selecting all voxels with the signal intensities larger than the threshold adjacent to the signal loss artifact in every slice. Use the masking tool of the segmentation editor to visualize the predefined signal intensity range and restrict the segmentation to it.</li>
	</ol>
	</li>
	<li>To define the threshold for signal loss artifacts, place 4 regions of interests (ROIs) in air-containing regions (ROIAir; each 10 mm in diameter) at the corners of the phantom box and measure the mean signal intensity and SD of all voxels within these 4 ROIAir as described in step 3.2, using the segmentation editor and &#34;Material Statistics&#34;, respectively. 
	NOTE: Signal loss artifacts present with voxels having artificial low signal intensities. They are caused by dephasing and displacement artifacts.
	<ol>
		<li>Place an ROI in the core of the signal loss artifact (ROICore) defined by the largest connected area of low signal intensities (Figure 1a). Manually increase the size of the ROICore until the largest possible size within the signal loss artifact whose mean signal intensity is lower than the mean ROIAir + 3x of the respective SD is found. Finally, measure the mean signal intensity and SD of the ROICore.</li>
		<li>Calculate the signal intensity threshold for signal loss artifacts by adding 3 SD of the ROICore to the mean of the ROICore. Perform a semiautomatic threshold-based segmentation of signal loss artifacts by selecting all voxels connected to the ROICore with signal intensities below the threshold.</li>
		<li>Use the masking tool of the segmentation editor to visualize the predefined signal intensity range and restrict the segmentation to it. If possible, use the &#34;Fill&#34; function in the tap &#34;Selection&#34; of the segmentation editor to include all voxels within the segmentation that are not yet selected. If applicable, manually add the additional unequivocal signal loss artifacts to the segmentation.</li>
	</ol>
	</li>
	<li>Subtract the physical implant volume from the calculated artifact volume to obtain the true artifact volume. Repeat the analysis at least 3x. A time interval of at least two weeks should separate the multiple reads to exclude a learning bias.</li>
</ol>

<ol><li>Matsumoto, M., Koike, S., Kashima, S., Awai, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Geographic+distribution+of+CT%2C+MRI+and+PET+devices+in+Japan%3A+a+longitudinal+analysis+based+on+national+census+data%5BTitle%5D)+AND+%22PLoS+ONE%22%5BJournal%5D)">Geographic distribution of CT, MRI and PET devices in Japan: a longitudinal analysis based on national census data.</a> PLoS ONE. 10 (5), (2015).</li>
<li>Cram, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Total+knee+arthroplasty+volume%2C+utilization%2C+and+outcomes+among+medicare+beneficiaries%5BTitle%5D)+AND+%22JAMA%22%5BJournal%5D)">Total knee arthroplasty volume, utilization, and outcomes among medicare beneficiaries.</a> JAMA. 308 (12), 1227-1236 (1991).</li>
<li>Jordan, R. A., Micheelis, W. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aJordan%2C+RA+%22F%C3%BCnfte+Deutsche+Mundgesundheitsstudie+%28DMS+V%29%22">Fünfte Deutsche Mundgesundheitsstudie (DMS V)</a>. , Deutscher Zahnärzte Verlag DÄV. Köln. (2016).</li>
<li>Steiner, C., Andrews, R., Barrett, M., Weiss, A. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aSteiner%2C+C+%22HCUP+projections+mobility%2Forthopedic+procedures+2003+to+2012%22">HCUP projections mobility/orthopedic procedures 2003 to 2012</a>. , U.S. Agency for Healthcare Research and Quality. Rockville. Report #2012-03 (2012).</li>
<li>Kremers, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Prevalence+of+total+hip+and+knee+replacement+in+the+United+States%5BTitle%5D)+AND+%22The+Journal+of+Bone+and+Joint+Surgery%22%5BJournal%5D)">Prevalence of total hip and knee replacement in the United States.</a> The Journal of Bone and Joint Surgery. 97 (17), 1386-1397 (2015).</li>
<li>Schenck, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+role+of+magnetic+susceptibility+in+magnetic+resonance+imaging%3A+MRI+magnetic+compatibility+of+the+first+and+second+kinds%5BTitle%5D)+AND+%22Medical+Physics%22%5BJournal%5D)">The role of magnetic susceptibility in magnetic resonance imaging: MRI magnetic compatibility of the first and second kinds.</a> Medical Physics. 23 (6), 815-850 (1996).</li>
<li>Filli, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Material-dependent+implant+artifact+reduction+using+SEMAC-VAT+and+MAVRIC%3A+a+prospective+MRI+phantom+study%5BTitle%5D)+AND+%22Investigative+Radiology%22%5BJournal%5D)">Material-dependent implant artifact reduction using SEMAC-VAT and MAVRIC: a prospective MRI phantom study.</a> Investigative Radiology. 52 (6), 381(2017).</li>
<li>Klinke, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Artifacts+in+magnetic+resonance+imaging+and+computed+tomography+caused+by+dental+materials%5BTitle%5D)+AND+%22PloS+ONE%22%5BJournal%5D)">Artifacts in magnetic resonance imaging and computed tomography caused by dental materials.</a> PloS ONE. 7 (2), (2012).</li>
<li>Lee, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Usefulness+of+IDEAL+T2-weighted+FSE+and+SPGR+imaging+in+reducing+metallic+artifacts+in+the+postoperative+ankles+with+metallic+hardware%5BTitle%5D)+AND+%22Skeletal+Radiology%22%5BJournal%5D)">Usefulness of IDEAL T2-weighted FSE and SPGR imaging in reducing metallic artifacts in the postoperative ankles with metallic hardware.</a> Skeletal Radiology. 42 (2), 239-247 (2013).</li>
<li>Zho, S. -Y., Kim, M. -O., Lee, K. -W., Kim, D. -H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Artifact+reduction+from+metallic+dental+materials+in+T1-weighted+spin-echo+imaging+at+3.0+tesla%5BTitle%5D)+AND+%22Journal+of+Magnetic+Resonance+Imaging%22%5BJournal%5D)">Artifact reduction from metallic dental materials in T1-weighted spin-echo imaging at 3.0 tesla.</a> Journal of Magnetic Resonance Imaging. 37 (2), 471-478 (2013).</li>
<li>Fritz, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Compressed+sensing+SEMAC%3A+8-fold+accelerated+high+resolution+metal+artifact+reduction+MRI+of+Cobalt-Chromium+knee+arthroplasty+implants%5BTitle%5D)+AND+%22Investigative+Radiology%22%5BJournal%5D)">Compressed sensing SEMAC: 8-fold accelerated high resolution metal artifact reduction MRI of Cobalt-Chromium knee arthroplasty implants.</a> Investigative Radiology. 51 (10), 666(2016).</li>
<li>Aguiar, M., Marques, A., Carvalho, A., Cavalcanti, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Accuracy+of+magnetic+resonance+imaging+compared+with+computed+tomography+for+implant+planning%5BTitle%5D)+AND+%22Clinical+Oral+Implants+Research%22%5BJournal%5D)">Accuracy of magnetic resonance imaging compared with computed tomography for implant planning.</a> Clinical Oral Implants Research. 19 (4), 362-365 (2008).</li>
<li>Talbot, B. S., Weinberg, E. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((MR+imaging+with+metal-suppression+sequences+for+evaluation+of+total+joint+arthroplasty%5BTitle%5D)+AND+%22RadioGraphics%22%5BJournal%5D)">MR imaging with metal-suppression sequences for evaluation of total joint arthroplasty.</a> RadioGraphics. 36 (1), 209-225 (2015).</li>
<li>Ai, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((SEMAC-VAT+and+MSVAT-SPACE+sequence+strategies+for+metal+artifact+reduction+in+1.5T+magnetic+resonance+imaging%5BTitle%5D)+AND+%22Investigative+Radiology%22%5BJournal%5D)">SEMAC-VAT and MSVAT-SPACE sequence strategies for metal artifact reduction in 1.5T magnetic resonance imaging.</a> Investigative Radiology. 47 (5), 267-276 (2012).</li>
<li>Smeets, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Artefacts+in+multimodal+imaging+of+titanium%2C+zirconium+and+binary+titanium-zirconium+alloy+dental+implants%3A+an+in+vitro+study%5BTitle%5D)+AND+%22Dento+Maxillo+Facial+Radiology%22%5BJournal%5D)">Artefacts in multimodal imaging of titanium, zirconium and binary titanium-zirconium alloy dental implants: an in vitro study.</a> Dento Maxillo Facial Radiology. 46 (2), 20160267(2016).</li>
<li>Nawabi, D. H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((MRI+predicts+ALVAL+and+tissue+damage+in+metal-on-metal+hip+arthroplasty%5BTitle%5D)+AND+%22Clinical+Orthopaedics+and+Related+Research%22%5BJournal%5D)">MRI predicts ALVAL and tissue damage in metal-on-metal hip arthroplasty.</a> Clinical Orthopaedics and Related Research. 472 (2), 471-481 (2014).</li>
<li>Cooper, H. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Early+reactive+synovitis+and+osteolysis+after+total+hip+arthroplasty%5BTitle%5D)+AND+%22Clinical+Orthopaedics+and+Related+Research%22%5BJournal%5D)">Early reactive synovitis and osteolysis after total hip arthroplasty.</a> Clinical Orthopaedics and Related Research. 468 (12), 3278-3285 (2010).</li>
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Tim Hilgenfeld, Franz S. Schwindling, and Alexander Juerchott received funding from a postdoctoral fellowship of the Medical Faculty of the University of Heidelberg. The study was supported in part by the Dietmar-Hopp-Stiftung (project no. 23011228). The authors have stated explicitly that there are no conflicts of interest in connection with this article.

The number of patients with metallic implants and the number of MRI examinations is currently increasing1,2,3. In the past, MRI examinations were avoided after joint replacements. Today, however, MRI is not only requested for imaging such patients but should also allow for the evaluation of complications directly adjacent to joint arthroplasty. Thus, the MRI safety and MRI suitability of implants, as well as the robust pulse sequences for metal artifact suppression, are becoming increasingly important13. For the evaluation of MRI suitability in terms of artifact volume, we present a comprehensive, time-efficient protocol. It allows for a reliable, three-dimensional evaluation of signal loss and pile-up artifacts as an indicator of slice distortions for fat-suppressed and non-fat-suppressed T1- and T2-weighted pulse sequences.
For some protocol steps, special attention is necessary to achieve the best possible result. After melting the embedding substance and before embedding the implant, it is very important to stir the embedding substance long enough while it starts cooling down and its aggregate state changes (fluid to solid), as its fat and water phases easily separate, even in the presence of an emulsifying agent. Furthermore, it is important to slowly fill the phantom box with the embedding substance to avoid air bubbles. This is crucial because air and signal loss artifacts both result in zero signal, which would lead to an overestimation of the artifact.
A high and homogeneous signal is necessary to allow for an accurate evaluation of the artifact volume. If the highest signal-to-noise ratio (SNR) is achieved by surface coils, it is crucial to test beforehand that the sensitivity of the profile and the coil positioning allows for a homogeneous signal within the phantom (as described above), so that the threshold-based segmentation can run without any segmentation errors.
Compared with other studies analyzing large implants (e.g., hip or knee replacements or spondylodesis), this protocol used small implants, in some cases causing artifact volumes far below 1 mL. Even under such challenging conditions, we could detect significant differences in the artifact volumes between different samples and different pulse sequences. Thus, a high measurement accuracy of this protocol can be assumed, allowing for an accurate evaluation of the MRI artifact volume of complex implants with regard to their material composition and shape. Moreover, the protocol can be applied to compare the vulnerability of different pulse sequences to metal-induced artifacts caused by a given implant.
Numerous methods with different complexity have been suggested for the evaluation of metallic artifacts. For the comparison of different pulse sequences, Fritz et al. used a qualitative ranking to evaluate the vulnerability of each sequence11. Others, such as Zho et al., determined in plane artifact (signal loss and pile-up) volumes by measuring the greatest distance and through plane artifacts by counting the number of slices being affected by artifacts10. Both methods, however, do not consider the full artifact volume, which may result in the under- or overestimation of artifact volume. That also applies to some studies that used manual segmentation11. Because this is a very time-consuming approach, often only one or two central slices are evaluated on a visual basis, neglecting the remaining artifact proportions.
For in vitro studies, authors often use agarose or gelatin as the embedding substance14,15. Both materials can be handled easily and guarantee enough signal in T2- and T1-weighted images. However, they do not allow for the evaluation of fat-suppressed sequences in any weighting. This represents a major drawback, since fat suppression has a profound impact on the artifact volume and is used regularly to identify implant-related complications (e.g., edema and fluid collections adjacent to the implant in cases of infection, particle disease, or aseptic lymphocyte-dominated vasculitis-associates lesion)13,16,17.
Some limitations of this protocol must be acknowledged. First, it does not allow in vivo quantification of the artifact volume, as the differentiation of the complete artifact volume requires a homogeneous background signal. For in vivo evaluations, other methods, such as measuring the magnetic susceptibility, can be used. Second, this protocol allows for the detection of pile-up artifacts (as an indicator of slice distortions) only directly adjacent to the signal loss artifact. However, additional slice distortions can be expected beyond the signal loss artifact as well. That is why it is likely that the amount of distortions is underestimated.
In conclusion, this protocol can help to standardize future studies evaluating the MRI artifact volume of implants and the vulnerability of pulse sequences to metallic artifacts. This might help to optimize the MRI suitability of implants and sequence techniques to finally improve patient care.

MRI has become an indispensable diagnostic tool. As a result, the number of MRI systems used in routine diagnostics is further increasing1. At the same time, the number of patients with implants is increasing as well2,3. In 2012, for instance, more than 1 million knee and joint replacements have been performed in the USA alone4. The prevalence of such implants was about 7 million in 2010, which corresponds to more than 10% of females in the age group 80-89 years5. As a result, the image quality and the diagnostic significance of MRI examinations are often impaired by artifacts due to metallic implants, resulting in a decreased diagnostic accuracy. Therefore, the MRI suitability of implants and the artifact vulnerability of pulse sequences are becoming increasingly important. Numerous approaches have been published to evaluate these characteristics. Due to strong discrepancies in the used evaluation methods, however, the respective results are hard to compare.
An evaluation of the MRI suitability of materials can be performed by calculating their magnetic susceptibility6. However, the vulnerability of different pulse sequences to artifacts cannot be compared with that approach for a given implant. Vice versa, the artifact volumes for a given pulse sequence can only be roughly estimated for different implants. In addition, the analysis is often performed with artificially shaped implants7,8. As the material volume and shape have an influence on the artifact size6, these features should be taken into account as well. As an alternative to magnetic susceptibility, the artifact size can be evaluated. Frequently, studies only rely on the qualitative evaluation of the artifact size9 or focus on the two-dimensional artifact size only covering one slice of the implant artifact10,11. Moreover, manual segmentation approaches are often used, which is not only time-consuming but also prone to intra- and inter-reader differences11. Finally, protocols often do not allow to test for non-fat-saturated and fat-saturated sequences at the same time12. This, however, would be desirable, since the applied fat suppression technique profoundly affects the artifact size.
Here, we present a protocol which allows for the reliable, semiautomatic, threshold-based, three-dimensional quantification of signal loss and pile-up artifacts of the entire implant, or all slices containing visible implant artifacts. Furthermore, it allows for testing T1- and T2-weighted images with or without fat-saturation. The protocol can be used to evaluate the MRI suitability of different implants or the vulnerability of different pulse sequences to metallic artifacts for a given implant.

<table><tbody><tr><td>Aqua B. Braun Ecotainer</td><td>B. Braun Melsungen AG, Melsungen, Germany</td><td></td><td></td></tr><tr><td>Semisynthetic fat: Witepsol W25</td><td>Caelo Caesar &amp;amp; Loretz GmbH, Hilder, Germany</td><td>4051</td><td></td></tr><tr><td>Macrogol-8-stearate</td><td>Caelo Caesar &amp;amp; Loretz GmbH, Hilder, Germany</td><td>3023</td><td></td></tr><tr><td>Plastic box: not specified</td><td></td><td></td><td></td></tr><tr><td>Implants: Nobel Replace</td><td>Nobel Biocare, Z&amp;uuml;rich, Switzerland</td><td></td><td></td></tr><tr><td>Water bath Haake S5P</td><td>Thermo Scientific, Waltham, MA, USA</td><td></td><td></td></tr><tr><td>Measuring cylinder Blaubrand Eterna, Class A, Boro 3.3</td><td>BRAND GmbH + Co Kg, Wertheim, Germany</td><td>32708</td><td></td></tr><tr><td>Coil: Variety</td><td>Noras MRI products GmbH, H&amp;ouml;chberg, Germany</td><td></td><td></td></tr><tr><td>MRI: Magnetom Trio</td><td>Siemens Healthcare GmbH, Erlangen, Germany</td><td></td><td></td></tr><tr><td>Postprocesing software: Amira 6.4</td><td>Thermo Scientific, Waltham, MA, USA</td><td></td><td></td></tr></tbody></table>

protocol for the evaluation of mri artifacts caused by metal implants to assess the suitability of implants and the vulnerability of pulse sequences

As the number of magnetic resonance imaging (MRI) scanners and patients with medical implants is constantly growing, radiologists increasingly encounter metallic implant-related artifacts in MRI, resulting in reduced image quality. Therefore, the MRI suitability of implants in terms of artifact volume, as well as the development of pulse sequences to reduce image artifacts, are becoming more and more important. Here, we present a comprehensive protocol which allows for a standardized evaluation of the artifact volume of implants on MRI. Furthermore, this protocol can be used to analyze the vulnerability of different pulse sequences to artifacts. The proposed protocol can be applied to T1- and T2-weighted images with or without fat-suppression and all passive implants. Furthermore, the procedure enables the separate and three-dimensional identification of signal loss and pile-up artifacts. As previous investigations differed greatly in evaluation methods, the comparability of their results was limited. Thus, standardized measurements of MRI artifact volumes are necessary to provide better comparability. This may improve the development of the MRI suitability of implants and better pulse sequences to finally improve patient care.

With the above-mentioned protocol, we evaluated the artifact volume of 2 different dental implants made of Titanium (T; see the Table of Materials) supporting different crowns [porcelain-fused-to-metal non-precious alloy (CCT-T) and monolithic zirconia (Z-T); Figure 1b and 1c]. The CCT-T sample represents a highly paramagnetic material composition predicting large artifacts (Cobalt 61%, Chrome 21%, and Tungsten 11%; CCT). The crown material of the Z-T sample represents a low paramagnetic material (Zirconia 92%; Z). Furthermore, four different, non-fat-saturated, T2-weighted sequences were evaluated to compare their vulnerability to metal artifacts. Specifically, the techniques of multiple slab acquisition with a view-angle-tilting gradient based on a sampling perfection with application-optimized contrasts using different flip angle evolutions (MSVAT-SPACE), slice encoding for metal artifact correction (SEMAC), and their conventional counterparts SPACE and turbo spin echo (TSE) were evaluated (see Table 1 for the detailed sequence parameters). MRI scans were performed on a 3T MRI system (see the Table of Materials) and a 16-channel multipurpose surface coil was used. The variation of the pulse sequence parameters has a strong impact on the artifact size. Thus, pulse sequence parameters were chosen as close as possible to those used in the in vivo dental MRI scans to increase the transferability of the results. The analysis was performed 3x by two independent raters. For multiple comparisons, a two-way analysis of variances and post hoc Tukey tests were used.
The data analysis reveals differences between both samples and the applied sequences. In all sequences, the combined artifact volumes (the sum of the signal loss and pile-up) of the CCT-T sample were larger compared to the Z-T sample (P &#60;0.001; Figure 2 and Figure 3). Within the same sequence, the artifact volume of the CCT-T sample was 19.3x (SEMAC) to 39.6x (MSVAT-SPACE) larger than the artifact volume of the Z-T counterpart.
The choice of pulse sequence had a significant impact on the artifact volume as well (Figure 2 and Figure 3). Regarding the CCT-T sample, the smallest artifact volumes were observed for TSE and SEMAC, and the largest artifacts for SPACE (P &#60;0.001). In addition, MSVAT-SPACE significantly reduced the artifact volume compared to SPACE (P &#60;0.001; 3.8 vs. 7.3 mL). In contrast, no significant differences were observed between MSVAT-SPACE, TSE, and SEMAC for the Z-T sample. The artifact volume for Z-T was largest in SPACE and was significantly reduced by MSVAT-SPACE (P &#60;0.05; 0.26 vs. 0.1 mL).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/57394/57394fig1v2.jpg" /> 
Figure 1: ROI positioning and implant samples. (a) This panel shows a typical positioning of the regions of interests (ROIs) for measuring the thresholds for pile-up artifacts and signal distribution (ROIB = ROIBackground) and signal loss artifacts (ROIA = ROIAir; ROIC = ROICore). The blue contour resembles the result of the semiautomatic segmentation for signal loss artifacts within that slice. The small red areas correspond to the result of pile-up artifacts. (b and c) These panels show images of used dental implants supporting different single crowns. Cobalt-Chromium-Tungsten-Titanium (CCT-T); Zirconia-Titanium (Z-T). <a href="/files/ftp_upload/57394/57394fig1v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/57394/57394fig2v2.jpg" /> 
Figure 2: Artifact volume measurements. (a and b) These are bar graphs showing the mean values with the standard deviations of the three-dimensional artifact volume of the entire implant samples for all 4 evaluated sequences after subtracting the physical implant volume. If applicable, separate standard deviation error bars are given for signal loss and pile-up artifacts. * P &#8804; 0.05; ** P&#8804; 0.001 <a href="/files/ftp_upload/57394/57394fig2v2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/57394/57394fig3.jpg" /> 
Figure 3: Appearance of artifacts. These panels render the artifact volumes of the entire implants (upper row). The blue colored areas represent signal loss artifacts and the red colored areas represent pile-up artifacts. The panels show the colored source images (lower row) for all evaluated T2-weighted sequences. Panel (a) is of the Cobalt-Chromium-Tungsten-Titanium (CCT-T) sample and panel (b) is of the Zirconia-Titanium (Z-T) sample. <a href="/files/ftp_upload/57394/57394fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table fo:font-size="7" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Sequence</td>
			<td>TR/TE 
			[ms]</td>
			<td>Voxel size 
			[mm3]</td>
			<td>FOV 
			[mm2]</td>
			<td>Matrix</td>
			<td>Readout 
			Bandwidth 
			[Hz/Px]</td>
			<td>Slices</td>
			<td>Slice 
			encoding&#160; 
			steps or 
			oversampling 
			[%]</td>
			<td>VAT</td>
			<td>Time 
			[min:sec]</td>
		</tr>
		<tr>
			<td>SPACE</td>
			<td>2,500/131</td>
			<td>0.55 x 0.55 x 0.55</td>
			<td>140 x 124</td>
			<td>256 x 256</td>
			<td>501</td>
			<td>72</td>
			<td>55.6</td>
			<td>No</td>
			<td>14:02</td>
		</tr>
		<tr>
			<td>MSVAT-SPACE</td>
			<td>2,500/199</td>
			<td>0.55 x 0.55 x 0.55</td>
			<td>140 x 84</td>
			<td>256 x 256</td>
			<td>528</td>
			<td>72</td>
			<td>55.6</td>
			<td>Yes</td>
			<td>6:04</td>
		</tr>
		<tr>
			<td>TSE</td>
			<td>5,100/44</td>
			<td>0.59 x 0.59 x 1.5</td>
			<td>150 x 150</td>
			<td>256 x 256</td>
			<td>592</td>
			<td>25</td>
			<td>No</td>
			<td>No</td>
			<td>3:36</td>
		</tr>
		<tr>
			<td>SEMAC</td>
			<td>5,100/45</td>
			<td>0.59 x 0.59 x 1.5</td>
			<td>150 x 150</td>
			<td>256 x 256</td>
			<td>592</td>
			<td>25</td>
			<td>4</td>
			<td>Yes</td>
			<td>6:19</td>
		</tr>
	</tbody>
</table>
Table 1: Parameters of all used sequences.

Watch this Scientific Journal Video about Protocol for the Evaluation of MRI Artifacts Caused by Metal Implants to Assess the Suitability of Implants and the Vulnerability of Pulse Sequences at JoVE.c

Protocol for the Evaluation of MRI Artifacts Caused by Metal Implants to Assess the Suitability of Implants and the Vulnerability of Pulse Sequences

We describe a standardized method to evaluate magnetic resonance imaging artifacts caused by implants to estimate the suitability of the implants for magnetic resonance imaging and/or the vulnerability of different pulse sequences to metallic artifacts simultaneously.

As the number of magnetic resonance imaging (MRI) scanners and patients with medical implants is constantly growing, radiologists increasingly encounter ...

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9.8K Views.  Heidelberg University Hospital. We describe a standardized method to evaluate magnetic resonance imaging artifacts caused by implants to estimate the suitability of the implants for magnetic resonance imaging and/or the vulnerability of different pulse sequences to metallic artifacts simultaneously.

Video: Protocol for the Evaluation of MRI Artifacts Caused by Metal Implants to Assess the Suitability of Implants and the Vulnerability of Pulse Sequences

Microwave-driven Synthesis of Iron Oxide Nanoparticles for Fast Detection of Atherosclerosis

A fast and reproducible microwave-driven protocol has been developed for the synthesis of neridronate-functionalized nanoparticles. Starting from the synthesis of hydrophobic nanoparticles, our method is based on an adaptation from thermal decomposition method to microwave driven synthesis. The new methodology produces a decrease in the reaction times in comparison with traditional procedures. Moreover, the use of the microwave technology increases the reproducibility of the reactions, something important from the point of view of clinical applications. The novelty of this iron oxide nanoparticle is the attachment of Neridronate. The use of this molecule leads a bisphosphonate moiety towards the outside of the nanoparticle that provides Ca2+ binding properties in vitro and selective accumulation in vivo in the atheroma plaque. The protocol allows the synthesis and plaque detection in about 3 hr since the initial synthesis from organic precursors. Their accumulation in the atherosclerotic area in less than 1 hr provides a contrast agent particularly suitable for clinical applications.

Microwave technology enables extremely fast synthesis of iron oxide nanoparticles for atherosclerosis plaque characterization. The use of an aminobisphosphonate in the external side of the nanoparticle provides a fast accumulation in the atherosclerotic area.

A fast and reproducible microwave-driven protocol has been developed for the synthesis of neridronate-functionalized nanoparticles. Starting from the ...

Bioengineering

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Breast cancer is the most common cause of cancer among women worldwide. Early detection of breast cancer has a critical role in improving the quality of life and survival of breast cancer patients. In this paper a new approach for the detection of breast cancer is described, based on tracking the mammary architectural elements using diffusion tensor imaging (DTI). 
The paper focuses on the scanning protocols and image processing algorithms and software that were designed to fit the diffusion properties of the mammary fibroglandular tissue and its changes during malignant transformation. The final output yields pixel by pixel vector maps that track the architecture of the entire mammary ductal glandular trees and parametric maps of the diffusion tensor coefficients and anisotropy indices. 
The efficiency of the method to detect breast cancer was tested by scanning women volunteers including 68 patients with breast cancer confirmed by histopathology findings. Regions with cancer cells exhibited a marked reduction in the diffusion coefficients and in the maximal anisotropy index as compared to the normal breast tissue, providing an intrinsic contrast for delineating the boundaries of malignant growth. Overall, the sensitivity of the DTI parameters to detect breast cancer was found to be high, particularly in dense breasts, and comparable to the current standard breast MRI method that requires injection of a contrast agent. Thus, this method offers a completely non-invasive, safe and sensitive tool for breast cancer detection.

We describe how to obtain parametric and vector maps of the diffusion tensor of the breast using magnetic resonance imaging. The protocol and final output following imaging processing are tailored for tracking breast architectural features and detecting breast malignancy.

Breast cancer is the most common cause of cancer among women worldwide. Early detection of breast cancer has a critical role in improving the quality of ...

Medicine

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease

Quantitative magnetic resonance imaging (qMRI) describes the development and use of MRI to quantify physical, chemical, and/or biological properties of living systems. Neuromuscular diseases often exhibit a temporally varying, spatially heterogeneous, and multi-faceted pathology. The goal of this protocol is to characterize this pathology using qMRI methods. The MRI acquisition protocol begins with localizer images (used to locate the position of the body and tissue of interest within the MRI system), quality control measurements of relevant magnetic field distributions, and structural imaging for general anatomical characterization. The qMRI portion of the protocol includes measurements of the longitudinal and transverse relaxation time constants (T1 and T2, respectively). Also acquired are diffusion-tensor MRI data, in which water diffusivity is measured and used to infer pathological processes such as edema. Quantitative magnetization transfer imaging is used to characterize the relative tissue content of macromolecular and free water protons. Lastly, fat-water MRI methods are used to characterize fibro-adipose tissue replacement of muscle. In addition to describing the data acquisition and analysis procedures, this paper also discusses the potential problems associated with these methods, the analysis and interpretation of the data, MRI safety, and strategies for artifact reduction and protocol optimization.

Neuromuscular diseases often exhibit a temporally varying, spatially heterogeneous, and multi-faceted pathology. The goal of this protocol is to characterize this pathology using non-invasive magnetic resonance imaging methods.

Quantitative magnetic resonance imaging (qMRI) describes the development and use of MRI to quantify physical, chemical, and/or biological properties of ...

A Multicenter MRI Protocol for the Evaluation and Quantification of Deep Vein Thrombosis

We evaluated a magnetic resonance venography (MRV) approach with gadofosveset to quantify total thrombus volume changes as the principal criterion for treatment efficacy&#160;in a multicenter randomized study comparing edoxaban monotherapy with a heparin/warfarin regimen for acute, symptomatic lower extremities deep vein thrombosis (DVT) treatment. We also used a direct thrombus imaging approach (DTHI, without the use of a contrast agent) to quantify fresh thrombus. We then sought to evaluate the reproducibility of the analysis methodology and applicability of using 3D magnetic resonance venography and direct thrombus imaging for the quantification of DVT in a multicenter trial setting. From 10 randomly selected subjects participating in the edoxaban Thrombus Reduction Imaging Study (eTRIS), total thrombus volume in the entire lower extremity deep venous system was quantified bilaterally. Subjects were imaged using 3D-T1W gradient echo sequences before (direct thrombus imaging, DTHI) and 5 min after injection of 0.03 mmol/kg of gadofosveset trisodium (magnetic resonance venography, MRV). The margins of the DVT on corresponding axial, curved multi-planar reformatted images were manually delineated by two observers to obtain volumetric measurements of the venous thrombi. MRV was used to compute total DVT volume, whereas DTHI was used to compute volume of fresh thrombus. Intra-class correlation (ICC) and Bland Altman analysis were performed to compare inter and intra-observer variability of the analysis. The ICC for inter and intra-observer variability was excellent (0.99 and 0.98, p &#60;0.001, respectively) with no bias on Bland-Altman analysis for MRV images. For DTHI images, the results were slightly lower (ICC = 0.88 and 0.95 respectively, p &#60;0.001), with bias for inter-observer results on Bland-Altman plots. This study showed feasibility of thrombus volume estimation in DVT using MRV with gadofosveset trisodium, with good intra- and inter-observer reproducibility in a multicenter setting.

The goal of this study is to use magnetic resonance venography with long-circulating gadolinium-based contrast agent and direct thrombus imaging for quantitative evaluation of DVT volume in a multicenter, clinical trial setting. Inter- and intra-observer variability assessments were conducted, and reproducibility of the protocol was determined.

We evaluated a magnetic resonance venography (MRV) approach with gadofosveset to quantify total thrombus volume changes as the principal criterion for ...

Quantitative MRI of Endothelial Permeability and (Dys)function in Atherosclerosis

Cardiovascular diseases are the leading causes of death worldwide. A permeable/leaky and dysfunctional endothelium is considered the earliest marker of vascular damage and thought to drive atherosclerosis. A method to identify these changes in vivo would be desirable in the clinic. Magnetic resonance imaging (MRI)-based tools and other technologies have enabled a profound understanding of the role of the endothelium in cardiovascular diseases and risk in vivo. There is, however, a need for reproducible and simple approaches for extracting quantifiable data reflective of endothelial damage from a single imaging study. A non-invasive, easy-to-implement, and quantitative MRI workflow was developed to acquire and analyze images that allow the quantification of two imaging biomarkers of arterial endothelial damage (leakiness/permeability and dysfunction). Here, the protocol describes the application of this method in the brachiocephalic artery of atherosclerotic ApoE-/- mice using a clinical MRI scanner. First, late gadolinium enhancement (LGE) and Modified Look-Locker Inversion Recovery (MOLLI) T1 mapping protocols to quantify endothelial leakage using an albumin-binding probe are described. Second, anatomic, and quantitative blood flow sequences to measure endothelial dysfunction, in response to acetylcholine are described. Importantly, the method outlined here allows the acquisition of high-spatial-resolution 3D images with large volumetric coverage enabling accurate segmentation of vessel wall structures to improve inter- and intra-observer variability and to increase reliability and reproducibility. Additionally, it provides quantitative data without the need for high-temporal resolution for complex kinetic modeling, making it model-independent and even allowing for imaging of highly mobile vessels (coronary arteries). Therefore, the approach simplifies and expedites data analysis. Finally, this method can be implemented on different scanners, can be extended to image different arterial beds, and is clinically applicable for use in humans. This method could be used to diagnose and treat patients with atherosclerosis by adopting a precision-medicine approach.

Quantitative MRI of Endothelial Permeability and Dysfunction in Atherosclerosis

We have developed an accurate, non-invasive, and easy-to-use method to quantify endothelial permeability and dysfunction in the arteries using Magnetic Resonance Imaging (MRI), named qMETRIC. This technique enables assessing vascular damage and cardiovascular risk associated with atherosclerosis in preclinical models and humans.

Cardiovascular diseases are the leading causes of death worldwide. A permeable/leaky and dysfunctional endothelium is considered the earliest marker of ...

Cardiac Magnetic Resonance for the Evaluation of Suspected Cardiac Thrombus: Conventional and Emerging Techniques

We present the conventional cardiac magnetic resonance (CMR) protocol for evaluating a suspected thrombus and highlight emerging techniques.&#160;The appearance of a mass on certain magnetic resonance (MR) sequences can help differentiate a thrombus from competing diagnoses such as a tumor. T1 and T2 signal characteristics of a thrombus are related to the evolution of hemoglobin properties. A thrombus typically does not enhance following contrast administration, which also helps differentiation from a tumor. We also highlight the emerging role of T1 mapping in the evaluation of a thrombus, which can add another level of support in diagnosis. Prior to any CMR exam, patient screening and interviews are critical to ensure safety and to optimize patient comfort. Effective communication during the exam between the technologist and the patient promotes proper breath holding technique and higher quality images. Volumetric post processing and structured reporting are helpful to ensure that the radiologist answers the ordering services&#39; question and communicates these results effectively. Optimal pre-MR safety evaluation, CMR exam execution, and post exam processing and reporting allow for delivery of high quality radiological service in the evaluation of a suspected cardiac thrombus.

The goal of this article is to describe how cardiac magnetic resonance can be used for the evaluation and diagnosis of a suspected cardiac thrombus. The method presented will describe data acquisition as well as the pre-procedure and post-procedure protocol.

We present the conventional cardiac magnetic resonance (CMR) protocol for evaluating a suspected thrombus and highlight emerging techniques.&#160;The ...

Reliable Acquisition of Electroencephalography Data during Simultaneous Electroencephalography and Functional MRI

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), EEG-fMRI, combines the complementary properties of scalp EEG (good temporal resolution) and fMRI (good spatial resolution) to measure neuronal activity during an electrographic event, through hemodynamic responses known as blood-oxygen-level-dependent (BOLD) changes. It is a non-invasive research tool that is utilized in neuroscience research and is highly beneficial to the clinical community, especially for the management of neurological diseases, provided that proper equipment and protocols are administered during data acquisition. Although recording EEG-fMRI is apparently straightforward, the correct preparation, especially in placing and securing the electrodes, is not only important for safety but is also critical in ensuring the reliability and analyzability of the EEG data obtained. This is also the most experience-demanding part of the preparation. To address these issues, a straightforward protocol that ensures data quality was developed. This article provides a step-by-step guide for acquiring reliable EEG data during EEG-fMRI using this protocol that utilizes readily available medical products. The presented protocol can be adapted to different applications of EEG-fMRI in research and clinical settings, and may be beneficial to both inexperienced and expert operators.

This article provides a straightforward protocol for acquiring good quality electroencephalography (EEG) data during simultaneous EEG and functional magnetic resonance imaging by utilizing readily available medical products.

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), EEG-fMRI, combines the complementary properties of scalp EEG ...

Neuroscience

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla

The overall goal of this article is to demonstrate a state-of-the-art ultrahigh field (UHF) magnetic resonance (MR) protocol of the brain at 7.0 Tesla in multiple sclerosis (MS) patients. MS is a chronic inflammatory, demyelinating, neurodegenerative disease that is characterized by white and gray matter lesions. Detection of spatially and temporally disseminated T2-hyperintense lesions by the use of MRI at 1.5 T and 3 T represents a crucial diagnostic tool in clinical practice to establish accurate diagnosis of MS based on the current version of the 2017 McDonald criteria. However, the differentiation of MS lesions from brain white matter lesions of other origins can sometimes be challenging due to their resembling morphology at lower magnetic field strengths (typically 3 T). Ultrahigh field MR (UHF-MR) benefits from increased signal-to-noise ratio and enhanced spatial resolution, both key to superior imaging for more accurate and definitive diagnoses of subtle lesions. Hence, MRI at 7.0 T has shown encouraging results to overcome the challenges of MS differential diagnosis by providing MS-specific neuroimaging markers (e.g., central vein sign, hypointense rim structures and differentiation of MS grey matter lesions). These markers and others can be identified by other MR contrasts other than T1 and T2 (T2*, phase, diffusion) and substantially improve the differentiation of MS lesions from those occurring in other neuroinflammatory conditions such as neuromyelitis optica and Susac syndrome. In this article, we describe our current technical approach to study cerebral white and grey matter lesions in MS patients at 7.0 T using different MR acquisition methods. The up-to-date protocol includes the preparation of the MR setup including the radio-frequency coils customized for UHF-MR, standardized screening, safety and interview procedures with MS patients, patient positioning in the MR scanner and acquisition of dedicated brain scans tailored for examining MS.

Here, we present a protocol to acquire magnetic resonance (MR) images of multiple sclerosis (MS) patient brains at 7.0 Tesla. The protocol includes preparation of the setup including the radio-frequency coils, standardized interview procedures with MS patients, subject positioning in the MR scanner and MR data acquisition.

The overall goal of this article is to demonstrate a state-of-the-art ultrahigh field (UHF) magnetic resonance (MR) protocol of the brain at 7.0 Tesla in ...

Cardiac Magnetic Resonance Imaging

Source: Frederick W. Damen and <a href="https://www.jove.com/author/Craig+J._Goergen">Craig J. Goergen</a>, Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana
In this video, high field, small-bore magnetic resonance imaging (MRI) with physiological monitoring is demonstrated to acquire gated cine loops of the murine cardiovascular system. This procedure provides a basis for assessing left-ventricular function, visualizing vascular networks, and quantifying motion of organs due to respiration. Comparable small animal cardiovascular imaging modalities include high-frequency ultrasound and micro-computed tomography (CT); however, each modality is associated with trade-offs that should be considered. While ultrasound does provide high spatial and temporal resolution, imaging artifacts are common. For example, dense tissue (i.e., the sternum and ribs) can limit imaging penetration depth, and hyperechoic signal at the interface between gas and liquid (i.e., pleura surrounding the lungs) can blur contrast in nearby tissue. Micro-CT in contrast does not suffer from as many in-plane artifacts, but does have lower temporal resolution and limited soft-tissue contrast. Furthermore, micro-CT uses X-ray radiation and often requires the use of contrast agents to visualize vasculature, both of which are known to cause side effects at high doses including radiation damage&#160; and renal injury. Cardiovascular MRI provides a nice compromise between these techniques by negating the need for ionizing radiation and providing the user with the ability to image without contrast agents (although contrast agents are often used for MRI).
This data was acquired with a triggering Fast Low Angle SHot (FLASH) MRI sequence that was gated off of the R-peaks in the cardiac cycle and expiratory plateaus in respiration. These physiological events were monitored through subcutaneous electrodes and a pressure-sensitive pillow that was secured against the abdomen. To ensure the mouse was properly warmed, a rectal temperature probe was inserted and used to control the output of a MRI-safe heating fan. Once the animal was inserted into the bore of the MRI scanner and navigation sequences were run to confirm positioning, the gated FLASH imaging planes were prescribed and data acquired. Overall, high field MRI is a powerful research tool that can provide soft tissue contrast for the study of small animal disease models.

Cardiac MRI: Principle and Imaging

Source: Frederick W. Damen and Craig J. Goergen, Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana
In this video, high ...

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Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI scanners were crude, but advances in digital computing and electronics led to their advancement over any other technique for precise imaging, especially in discovering tumors. Compared to other diagnostic imaging techniques like computed tomography and X-ray, MRI does not expose patients to radiation.
The drawbacks of MRI scans include their much higher cost and patient discomfort with the procedure. The MRI scanner subjects the patient to such powerful electromagnets that the scan room must be shielded. The patient must be enclosed in a metal tube-like device for the duration of the scan, sometimes as long as thirty minutes, which can be uncomfortable and impractical for ill patients. The machine is also so noisy that, even with earplugs, patients can become anxious or fearful. These problems have been overcome somewhat with the development of &#34;open&#34;&#160;MRI scanning, which does not require the patient to be entirely enclosed in a metal tube. Patients with iron-containing metallic implants (internal sutures, some prosthetic devices, pacemakers and so on) cannot undergo MRI scanning because it can dislodge these implants.
Different images are formed depending on the time taken between the sequence of magnetic pulses and the receipt and interpretation of the signal. A T1-weighted image has fatty tissues appearing brighter due to their enhanced signal while suppressing water signals, making it appear darker. In contrast, the T2-weighted image shows an enhanced water signal. Further, using MRI contrast media or dyes, like gadolinium, helps improve the quality of the images. Usually injected into the patient&#39;s vein, the gadolinium contrast dyes contain strongly paramagnetic gadolinium (Gd), which has positive magnetic susceptibility. When placed in a magnetic field, it is not directly seen in the MRI result but helps shorten the T1 values in tissues, where it accumulates, which allows the tissues to appear brighter in T1-weighted images.
Functional MRIs (fMRI), which detect the concentration of blood flow in certain body parts, are increasingly being used to study the activity in parts of the brain during various body activities. This has helped scientists learn more about the locations of different brain functions and more about brain abnormalities and diseases. More recently, 4D flow MRI provides 3D blood flow images and hemodynamics, with the fourth dimension being time, allowing cardiovascular disease assessment through the 3D coverage of the anatomy and velocity.
This content is derived from <a href="https://openstax.org/books/anatomy-and-physiology/pages/1-7-medical-imaging">Openstax, Anatomy and Physiology, Section 1.7: Medical Imaging</a>

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which ...