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1. Anatomy-based quality metric of diffusion-weighted MRI data for accurate derivation of muscle fiber orientation

Author

Shusharina, Nadya, Liu, Xiaofeng, Kaza, Evangelia, Lam, Miranda, Maier, Stephan, and Woo, Jonghye

Subjects
Physics - Medical Physics
Abstract

Diffusion-weighted MRI (DW-MRI) is used to quantitatively characterize the microscopic structure of soft tissue due to the anisotropic diffusion of water in muscle. Applications such as fiber tractography or modeling of tumor spread in soft tissue require precise detection of muscle fiber orientation, which is derived from the principal eigenvector of the diffusion tensor. For clinical applications, high image quality and high signal-to-noise ratio (SNR) of DW-MRI for fiber orientation must be balanced with an appropriate scan duration. Muscles with known structural heterogeneity, e.g. bipennate muscles such as the thigh rectus femoris, provide a natural quality benchmark to determine fiber orientation at different scan parameters. Here, we analyze DW-MR images of the thigh of a healthy volunteer at different SNRs and use PCA to identify subsets of voxels with different directions of diffusion tensor eigenvectors. We propose to use the mixing index of spatial co-localization of the clustered eigenvectors as a quality metric for fiber orientation detection. Comparing acquisitions at different SNRs, we find that high SNR results in a low mixing index, reflecting a clear separation of the two compartments of the bipennate muscle on either side of the central tendon. Because the mixing index allows joint estimation of spatial and directional noise in DW-MRI as a single parameter, it will allow future quantitative optimization of DW-MRI protocols for soft tissue.

Published
2024

8. Contributors

Author

Baehring, Joachim M., primary, Bastos, Dhiego C.A., additional, Beegle, Richard, additional, Bi, Wenya Linda, additional, Blackburn, Kyle M., additional, Blumenthal, Deborah T., additional, Bourekas, Eric C., additional, Bovi, Joseph A., additional, Brennan, Nicole Petrovich, additional, Brown, Alyssa, additional, Budhu, Joshua A., additional, Burt Nabors, L., additional, Bussiere, Marc, additional, Chakravarti, Arnab, additional, Chamberlain, Marc C., additional, Chao, Samuel T., additional, Chapman, Paul H., additional, Chen, Clark C., additional, Chi, Susan, additional, Choi, Serah, additional, Christoforidis, Gregory A., additional, Clarke, Jennifer L., additional, Corrêa, Diogo Goulart, additional, da Cruz, Luiz Celso Hygino, additional, Diaz, Maria, additional, Dixit, Karan S., additional, Dodson, Sean, additional, Edwards, Ryan M., additional, Ellika, Shehanaz, additional, Ellithi, Moataz, additional, Elsamadicy, Aladine A., additional, Fecci, Peter E., additional, Ferrante, Mark A., additional, Ferraro, Nicholas C., additional, Field, Melvin, additional, Fisicaro, Ryan, additional, Fonkem, Ekokobe, additional, Fulbright, Robert K., additional, Gerstner, Elizabeth R., additional, Golby, Alexandra J., additional, Goulart, Carlos R., additional, Guenette, Jeffrey P., additional, Guiou, Michael, additional, Gupta, Nilendu, additional, Halima, Ahmed, additional, Hatef, Angel L., additional, Heverhagen, Johannes T., additional, Holodny, Andrei, additional, Hughes, Tudor Hesketh, additional, Huie, David, additional, Ilica, Ahmet Turan, additional, Ina Ly, K., additional, Ivan, Michael E., additional, Jain, Rajan, additional, Johansson, Jens, additional, Johnson, Michele H., additional, Jolesz, Ferenc A., additional, Jung, Edward W., additional, Kangarlu, Alayar, additional, Kardan, Arash, additional, Karschnia, Philipp, additional, Kaur, Gurvinder, additional, Kijewski, Marie Foley, additional, Kim, Jinsuh, additional, Kocher, Madison, additional, Komotar, Ricardo J., additional, Krol, George, additional, Kurz, Sylvia C., additional, Kwofie, Michael, additional, Lantos, Joshua, additional, Lee, Eudocia Quant, additional, Le Rhun, Emilie, additional, Lerner, Emily C., additional, Liu, Benjamin P., additional, Lo, Simon S., additional, Lobbous, Mina, additional, Loeffler, Jay S., additional, Lowe, Stephen R., additional, Luther, Evan, additional, Maier, Stephan E., additional, Majithia, Lonika, additional, Makary, Mina S., additional, Mattei, Tobias A., additional, Mayo, Zachary S., additional, Mendel, Ehud, additional, Mikkelsen, Tom, additional, Miranda, Pedro C., additional, Moffat, Bradford A., additional, Murphy, Erin S., additional, Murray, John Vincent, additional, Muzic, Raymond F., additional, Nagpal, Prashant, additional, Naidich, Michelle J., additional, Newton, Herbert B., additional, Nine, Erik B., additional, Nisnboym, Michal, additional, Noujaim, Daniel, additional, Oberheim Bush, Nancy Ann, additional, Olubiyi, Olutayo, additional, Omay, Sacit Bulent, additional, Paleologos, Nina A., additional, Patel, Kunal S., additional, Pena Pino, Isabela, additional, Poussaint, Tina Young, additional, Prabhu, Sanjay P., additional, Qin, Lei, additional, Qu, Jinrong, additional, Rebeiz, Karim, additional, Reddy, Haricharan, additional, Reeves, Benjamin C., additional, Rogers, Lisa R., additional, Satter, Martin, additional, Sattur, Mithun G., additional, Schmainda, Kathleen M., additional, Shams, Mana, additional, Shams, Sara, additional, Silvera, V. Michelle, additional, Sloan, Andrew, additional, Slone, H. Wayne, additional, Snyder, James, additional, Sodickson, Daniel K., additional, Sodickson, Aaron D., additional, Solnes, Lilja Bjork, additional, Spampinato, Maria Vittoria, additional, Srinivasan, Ethan S., additional, Suh, John H., additional, Sun, Yanping, additional, Sutton, Nicholas A., additional, Tadipatri, Ramya, additional, Tharin, Suzanne, additional, Thompson, Ryan, additional, Turner, Tia H., additional, Vaios, Eugene J., additional, Vernino, Steven, additional, Vogelbaum, Michael A., additional, Walston, Steve, additional, Waltz, Jeffrey, additional, Weicker, Michael A., additional, Welling, D. Bradley, additional, Wen, Patrick Y., additional, Wenger, Cornelia, additional, Wintermark, Max, additional, Wong, Eric T., additional, Yang, Edward, additional, Yeh, Randy, additional, Yildirim, Onur, additional, Young, Geoffrey S., additional, Young, Robert J., additional, Zaman, Rujman U., additional, and Zukas, Alicia M., additional

Published
2022
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10. Three‐dimensional printing of MRI‐visible phantoms and MR image‐guided therapy simulation

Author

Mitsouras, Dimitris, Lee, Thomas C, Liacouras, Peter, Ionita, Ciprian N, Pietilla, Todd, Maier, Stephan E, and Mulkern, Robert V

Subjects
Engineering, Biomedical Engineering, Biomedical Imaging, Bioengineering, Detection, screening and diagnosis, 4.2 Evaluation of markers and technologies, Cervical Vertebrae, Cryosurgery, Equipment Design, Equipment Failure Analysis, Humans, Magnetic Resonance Imaging, Phantoms, Imaging, Printing, Three-Dimensional, Reproducibility of Results, Sensitivity and Specificity, Surgery, Computer-Assisted, T-2 decay, T-1 decay, CPMG, multiexponential, phantom, 3D printing, Image-guided therapy, T1 decay, T2 decay, Nuclear Medicine & Medical Imaging, Biomedical engineering
Abstract

PurposeTo demonstrate the use of anatomic MRI-visible three-dimensional (3D)-printed phantoms and to assess process accuracy and material MR signal properties.MethodsA cervical spine model was generated from computed tomography (CT) data and 3D-printed using an MR signal-generating material. Printed phantom accuracy and signal characteristics were assessed using 120 kVp CT and 3 Tesla (T) MR imaging. The MR relaxation rates and diffusion coefficient of the fabricated phantom were measured and 1 H spectra were acquired to provide insight into the nature of the proton signal. Finally, T2 -weighted imaging was performed during cryoablation of the model.ResultsThe printed model produced a CT signal of 102 ± 8 Hounsfield unit, and an MR signal roughly 1/3rd that of saline in short echo time/short repetition time GRE MRI (456 ± 36 versus 1526 ± 121 arbitrary signal units). Compared with the model designed from the in vivo CT scan, the printed model differed by 0.13 ± 0.11 mm in CT, and 0.62 ± 0.28 mm in MR. The printed material had T2 ∼32 ms, T2*∼7 ms, T1 ∼193 ms, and a very small diffusion coefficient less than olive oil. MRI monitoring of the cryoablation demonstrated iceball formation similar to an in vivo procedure.ConclusionCurrent 3D printing technology can be used to print anatomically accurate phantoms that can be imaged by both CT and MRI. Such models can be used to simulate MRI-guided interventions such as cryosurgeries. Future development of the proposed technique can potentially lead to printed models that depict different tissues and anatomical structures with different MR signal characteristics. Magn Reson Med 77:613-622, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Published
2017

11. Multicomponent T2 relaxation studies of the avian egg

Author

Mitsouras, Dimitris, Mulkern, Robert V, and Maier, Stephan E

Subjects
Engineering, Biomedical Engineering, Animals, Biomarkers, Chickens, Egg White, Egg Yolk, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Ovum, Phantoms, Imaging, Signal Processing, Computer-Assisted, T-2-decay, CPMG, multiexponential, egg white, yolk, latebra, MR phantom, T2-decay, Nuclear Medicine & Medical Imaging, Biomedical engineering
Abstract

PurposeTo investigate the tissue-like multiexponential T2 signal decays in avian eggs.MethodsTransverse relaxation studies of raw, soft-boiled and hard-boiled eggs were performed at 3 Tesla using a three-dimensional Carr-Purcell-Meiboom-Gill imaging sequence. Signal decays over a TE range of 11 to 354 ms were fitted assuming single- and multicomponent signal decays with up to three separately decaying components. Fat saturation was used to facilitate spectral assignment of observed decay components.ResultsEgg white, yolk and the centrally located latebra all demonstrate nonmonoexponential T2 decays. Specifically, egg white exhibits two-component decays with intermediate and long T2 times. Meanwhile, yolk and latebra are generally best characterized with triexponential decays, with short, intermediate and very long T2 decay times. Fat saturation revealed that the intermediate component of yolk could be attributed to lipids. Cooking of the egg profoundly altered the decay curves.ConclusionAvian egg T2 decay curves cover a wide range of decay times. Observed T2 components in yolk and latebra as short as 10 ms, may prove valuable for testing clinical sequences designed to measure short T2 components, such as myelin-associated water in the brain. Thus we propose that the egg can be a versatile and widely available MR transverse relaxation phantom.

Published
2016

14. Avian egg latebra as brain tissue water diffusion model

Author

Maier, Stephan E, Mitsouras, Dimitris, and Mulkern, Robert V

Subjects
Engineering, Biomedical Engineering, 1.1 Normal biological development and functioning, Underpinning research, Animals, Biomimetic Materials, Body Water, Brain Chemistry, Chickens, Diffusion, Diffusion Magnetic Resonance Imaging, Egg Yolk, Equipment Design, Equipment Failure Analysis, Lipids, Models, Biological, Models, Chemical, Phantoms, Imaging, Reproducibility of Results, Sensitivity and Specificity, diffusion, biexponential diffusion, multiexponential diffusion, non-Gaussian diffusion, magnetization transfer, egg, Latebra, membrane, lipid, coagulation, Nuclear Medicine & Medical Imaging, Biomedical engineering
Abstract

PurposeSimplified models of non-monoexponential diffusion signal decay are of great interest to study the basic constituents of complex diffusion behavior in tissues. The latebra, a unique structure uniformly present in the yolk of avian eggs, exhibits a non-monoexponential diffusion signal decay. This model is more complex than simple phantoms based on differences between water and lipid diffusion, but is also devoid of microscopic structures with preferential orientation or perfusion effects.MethodsDiffusion scans with multiple b-values were performed on a clinical 3 Tesla system in raw and boiled chicken eggs equilibrated to room temperature. Diffusion encoding was applied over the ranges 5-5,000 and 5-50,000 s/mm(2). A low read-out bandwidth and chemical shift was used for reliable lipid/water separation. Signal decays were fitted with exponential functions.ResultsThe latebra, when measured over the 5-5,000 s/mm(2) range, exhibited independent of preparation clearly biexponential diffusion, with diffusion parameters similar to those typically observed in in vivo human brain. For the range 5-50,000 s/mm(2), there was evidence of a small third, very slow diffusing water component.ConclusionThe latebra of the avian egg contains membrane structures, which may explain a deviation from a simple monoexponential diffusion signal decay, which is remarkably similar to the deviation observed in brain tissue.

Published
2014

15. Human prostate MRI at ultrahigh‐performance gradient: A feasibility study.

Author

Zhu, Ante, Tarasek, Matthew, Hua, Yihe, Fiveland, Eric, Maier, Stephan E., Mazaheri, Yousef, Fung, Maggie, Westin, Carl‐Fredrik, Yeo, Desmond T. B., Szczepankiewicz, Filip, Tempany, Clare, Akin, Oguz, and Foo, Thomas K. F.

Subjects
PROSTATE, MAGNETIC resonance imaging, NEURAL stimulation, WAIST circumference, FEASIBILITY studies
Abstract

Purpose: To demonstrate the technical feasibility and the value of ultrahigh‐performance gradient in imaging the prostate in a 3T MRI system. Methods: In this local institutional review board–approved study, prostate MRI was performed on 4 healthy men. Each subject was scanned in a prototype 3T MRI system with a 42‐cm inner‐diameter gradient coil that achieves a maximum gradient amplitude of 200 mT/m and slew rate of 500 T/m/s. PI‐RADS V2.1–compliant axial T2‐weighted anatomical imaging and single‐shot echo planar DWI at standard gradient of 70 mT/m and 150 T/m/s were obtained, followed by DWI at maximum performance (i.e., 200 mT/m and 500 T/m/s). In comparison to state‐of‐the‐art clinical whole‐body MRI systems, the high slew rate improved echo spacing from 1020 to 596 μs and, together with a high gradient amplitude for diffusion encoding, TE was reduced from 55 to 36 ms. Results: In all 4 subjects (waist circumference = 81–91 cm, age = 45–65 years), no peripheral nerve stimulation sensation was reported during DWI. Reduced image distortion in the posterior peripheral zone prostate gland and higher signal intensity, such as in the surrounding muscle of high‐gradient DWI, were noted. Conclusion: Human prostate MRI at simultaneously high gradient amplitude of 200 mT/m and slew rate of 500 T/m/s is feasible, demonstrating that improved gradient performance can address image distortion and T2 decay–induced SNR issues for in vivo prostate imaging. [ABSTRACT FROM AUTHOR]

Published
2024
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16. Human prostate MRI at ultrahigh‐performance gradient: A feasibility study

Author

Zhu, Ante, primary, Tarasek, Matthew, additional, Hua, Yihe, additional, Fiveland, Eric, additional, Maier, Stephan E., additional, Mazaheri, Yousef, additional, Fung, Maggie, additional, Westin, Carl‐Fredrik, additional, Yeo, Desmond T. B., additional, Szczepankiewicz, Filip, additional, Tempany, Clare, additional, Akin, Oguz, additional, and Foo, Thomas K. F., additional

Published
2023
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28. Truly reproducible uniform estimation of the ADC with multi‐b diffusion data— Application in prostate diffusion imaging.

Author

Kuczera, Stefan, Langkilde, Fredrik, and Maier, Stephan E.

Subjects
PROSTATE, DIFFUSION magnetic resonance imaging, MEDICAL protocols, CURVE fitting, CLINICAL medicine
Abstract

Purpose: The ADC is a well‐established parameter for clinical diagnostic applications, but lacks reproducibility because it is also influenced by the choice diffusion weighting level. A framework is evaluated that is based on multi‐b measurement over a wider range of diffusion‐weighting levels and higher order tissue diffusion modeling with retrospective, fully reproducible ADC calculation. Methods: Averaging effect from curve fitting for various model functions at 20 linearly spaced b‐values was determined by means of simulations and theoretical calculations. Simulation and patient multi‐b image data were used to compare the new approach for diffusion‐weighted image and ADC map reconstruction with and without Rician bias correction to an active clinical trial protocol probing three non‐zero b‐values. Results: Averaging effect at a certain b‐value varies for model function and maximum b‐value used. Images and ADC maps from the novel procedure are on‐par with the clinical protocol. Higher order modeling and Rician bias correction is feasible, but comes at the cost of longer computation times. Conclusions: Application of the new framework makes higher order modeling more feasible in a clinical setting while still providing patient images and reproducible ADC maps of adequate quality. [ABSTRACT FROM AUTHOR]

Published
2023
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31. List of Contributors

Author

Ankenbrandt, William, primary, Arrillaga-Romany, Isabel, additional, Atsina, K.K., additional, Badve, Chaitra A., additional, Baehring, J.M., additional, Baldassarre, Randall Lawrence, additional, Bi, Wenya Linda, additional, Black, Peter M., additional, Boehm, Ingrid B., additional, Bolles, Genevieve, additional, Bourekas, Eric C., additional, Brennan, Nicole Petrovich, additional, Bussiere, Marc, additional, Cha, Soonmee, additional, Chakravarti, Arnab, additional, Chamberlain, Marc C., additional, Chang, Susan M., additional, Chapman, Paul H., additional, Chen, Clark C., additional, Chi, Susan N., additional, Chourmouzi, D., additional, Christoforidis, Gregory A., additional, Chukwueke, Ugonma, additional, Clarke, Jennifer L., additional, Collins, John M., additional, da Cruz, L. Celso Hygino, additional, Dolati, Parviz, additional, Drevelegas, A., additional, Drevelegas, K., additional, Eisele, Sylvia, additional, Ellika, Shehanaz, additional, Ferrante, Mark A., additional, Ferraro, Nicholas C., additional, Fisicaro, Ryan, additional, Golby, Alexandra J., additional, Goulart, Carlos R., additional, Guiou, Michael, additional, Gupta, Nilendu, additional, Hata, Nobuhiko, additional, Hearshen, David, additional, Henson, John W., additional, Heverhagen, Johannes T., additional, Holodny, Andrei, additional, Hughes, Tudor Hesketh, additional, Ichise, Masanori, additional, Ivan, Michael E., additional, Jain, Rajan, additional, Jolesz, Ferenc A., additional, Jordan, Justin T., additional, Daniel, Kacher, additional, Kangarlu, Alayar, additional, Kardan, Arash, additional, Kijewski, Marie Foley, additional, Kimura, Margareth, additional, Kissel, John T., additional, Komotar, Ricardo J., additional, Krol, George, additional, Kumthekar, Priya, additional, Lantos, Joshua, additional, Le Rhun, Emilie, additional, Lev, Michael H., additional, Loeffler, Jay S., additional, Maier, Stephan E., additional, Majithia, Lonika, additional, Mattei, Tobias A., additional, McCullough, Brendan J., additional, Mendel, Ehud, additional, Mikkelsen, Tom, additional, Miloushev, Vesselin Z., additional, Miranda, Pedro C., additional, Monje, Michelle, additional, Nagpal, Prashant, additional, Nakanote, Ken Alexander, additional, Newton, Herbert B., additional, Nine, Erik B., additional, Oberheim Bush, Nancy Ann, additional, Olubiyi, Olutayo, additional, Omay, S.B., additional, Paleologos, Nina, additional, Papanicolaou, N., additional, Patel, Kunal S., additional, Poussaint, Tina Young, additional, Prabhu, Sanjay P., additional, Qu, Jinrong, additional, Raizer, Jeffrey J., additional, Reddy, Haricharan, additional, Rizvi, Tanvir, additional, Rogers, Lisa R., additional, Satter, Martin, additional, Sattur, Mithun G., additional, Schiff, David, additional, Schmainda, Kathleen, additional, Schweitzer, Andrew D., additional, Silvera, Victoria Michelle, additional, Slone, H. Wayne, additional, Snyder, James, additional, Sodickson, Aaron D., additional, Sodickson, Daniel K., additional, Solnes, Lilja Bjork, additional, Spampinato, Maria Vittoria, additional, Sun, Yanping, additional, Taillibert, Sophie, additional, Talos, Ion-Florin, additional, Tharin, Suzanne, additional, Vagal, Achala, additional, Vernino, Steven, additional, Vogelbaum, Michael A., additional, Vossough, Arastoo, additional, Walston, Steve, additional, Warfield, Simon K., additional, Weicker, Michael A., additional, Welling, D. Bradley, additional, Wenger, Cornelia, additional, Wen, Patrick Y., additional, Wintermark, Max, additional, Wong, Eric T., additional, Xinou, E., additional, Yang, Edward, additional, Yeh, Randy, additional, Young, Geoffrey S., additional, Young, Robert J., additional, and Zukas, Alicia M., additional

Published
2016
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