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167 results on '"Odéen, Henrik"'

1. Treatment Efficacy Prediction of Focused Ultrasound Therapies Using Multi-parametric Magnetic Resonance Imaging

Author

Singh, Amanpreet, Adams-Tew, Samuel, Johnson, Sara, Odeen, Henrik, Shea, Jill, Johnson, Audrey, Day, Lorena, Pessin, Alissa, Payne, Allison, Joshi, Sarang, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Ali, Sharib, editor, van der Sommen, Fons, editor, Papież, Bartłomiej Władysław, editor, Ghatwary, Noha, editor, Jin, Yueming, editor, and Kolenbrander, Iris, editor

Published
2025
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2. Physics Informed Neural Networks for Estimation of Tissue Properties from Multi-echo Configuration State MRI

Author

Adams-Tew, Samuel I., Odéen, Henrik, Parker, Dennis L., Cheng, Cheng-Chieh, Madore, Bruno, Payne, Allison, Joshi, Sarang, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Linguraru, Marius George, editor, Dou, Qi, editor, Feragen, Aasa, editor, Giannarou, Stamatia, editor, Glocker, Ben, editor, Lekadir, Karim, editor, and Schnabel, Julia A., editor

Published
2024
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6. Histology to 3D In Vivo MR Registration for Volumetric Evaluation of MRgFUS Treatment Assessment Biomarkers

Author

Zimmerman, Blake E., Johnson, Sara L., Odéen, Henrik A., Shea, Jill E., Factor, Rachel E., Joshi, Sarang C., and Payne, Allison H.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Physics - Medical Physics
Abstract

Advances in imaging and early cancer detection have increased interest in magnetic resonance (MR) guided focused ultrasound (MRgFUS) technologies for cancer treatment. MRgFUS ablation treatments could reduce surgical risks, preserve organ tissue/function, and improve patient quality of life. However, surgical resection and histological analysis remain the gold standard to assess cancer treatment response. For non-invasive ablation therapies such as MRgFUS, the treatment response must be determined through MR imaging biomarkers. However, current MR biomarkers are inconclusive and have not been rigorously evaluated against histology via accurate registration. Existing registration methods rely on anatomical features to directly register in vivo MR and histology. For MRgFUS applications in anatomies such as liver, kidney, or breast, anatomical features independent from treatment features are often insufficient to perform direct registration. We present a novel MR to histology registration workflow that utilizes intermediate imaging and does not rely on these independent features. The presented workflow yields an overall registration accuracy of 1.00 +/- 0.13 mm. The developed registration pipeline is used to evaluate a common MRgFUS treatment assessment biomarker against histology. Evaluating MR biomarkers against histology using this registration pipeline will facilitate validating novel MRgFUS biomarkers to improve treatment assessment without surgical intervention., Comment: 12 pages, 5 figures, 2 tables

Published
2020

7. Learning Multiparametric Biomarkers for Assessing MR-Guided Focused Ultrasound Treatment of Malignant Tumors

Author

Zimmerman, Blake E., Johnson, Sara, Odéen, Henrik, Shea, Jill, Foote, Markus D., Winkler, Nicole, Joshi, Sarang C., and Payne, Allison

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Machine Learning, Physics - Medical Physics, Statistics - Machine Learning
Abstract

Noninvasive MR-guided focused ultrasound (MRgFUS) treatments are promising alternatives to the surgical removal of malignant tumors. A significant challenge is assessing the viability of treated tissue during and immediately after MRgFUS procedures. Current clinical assessment uses the nonperfused volume (NPV) biomarker immediately after treatment from contrast-enhanced MRI. The NPV has variable accuracy, and the use of contrast agent prevents continuing MRgFUS treatment if tumor coverage is inadequate. This work presents a novel, noncontrast, learned multiparametric MR biomarker that can be used during treatment for intratreatment assessment, validated in a VX2 rabbit tumor model. A deep convolutional neural network was trained on noncontrast multiparametric MR images using the NPV biomarker from follow-up MR imaging (3-5 days after MRgFUS treatment) as the accurate label of nonviable tissue. A novel volume-conserving registration algorithm yielded a voxel-wise correlation between treatment and follow-up NPV, providing a rigorous validation of the biomarker. The learned noncontrast multiparametric MR biomarker predicted the follow-up NPV with an average DICE coefficient of 0.71, substantially outperforming the current clinical standard (DICE coefficient = 0.53). Noncontrast multiparametric MR imaging integrated with a deep convolutional neural network provides a more accurate prediction of MRgFUS treatment outcome than current contrast-based techniques., Comment: 11 pages, 12 figures

Published
2019
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16. Validation of single reference variable flip angle (SR‐VFA) dynamic T1 mapping with T2* correction using a novel rotating phantom.

Author

Malmberg, Michael A., Odéen, Henrik, Hofstetter, Lorne W., Hadley, J. Rock, and Parker, Dennis L.

Subjects
ANGLES, AGAR, ROTATIONAL motion, SPEED
Abstract

Purpose: To validate single reference variable flip angle (SR‐VFA) dynamic T1 mapping with and without T2* correction against inversion recovery (IR) T1 measurements. Methods: A custom cylindrical phantom with three concentric compartments was filled with variably doped agar to produce a smooth spatial gradient of the T1 relaxation rate as a function of angle across each compartment. IR T1, VFA T1, and B1+ measurements were made on the phantom before rotation, and multi‐echo stack‐of‐radial dynamic images were acquired during rotation via an MRI‐compatible motor. B1+‐corrected SR‐VFA and SR‐VFA‐T2* T1 maps were computed from the sliding window reconstructed images and compared against rotationally registered IR and VFA T1 maps to determine the percentage error. Results: Both VFA and SR‐VFA‐T2* T1 maps fell within 10% of IR T1 measurements for a low rotational speed, with a mean accuracy of 2.3% ± 2.6% and 2.8% ± 2.6%, respectively. Increasing rotational speed was found to decrease the accuracy due to increasing temporal smoothing over ranges where the T1 change had a nonconstant slope. SR‐VFA T1 mapping was found to have similar accuracy as the SR‐VFA‐T2* and VFA methods at low TEs (˜<2 ms), whereas accuracy degraded strongly with later TEs. T2* correction of the SR‐VFA T1 maps was found to consistently improve accuracy and precision, especially at later TEs. Conclusion: SR‐VFA‐T2* dynamic T1 mapping was found to be accurate against reference IR T1 measurements within 10% in an agar phantom. Further validation is needed in mixed fat–water phantoms and in vivo. [ABSTRACT FROM AUTHOR]

Published
2024
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18. The influence of bone model geometries on the determination of skull acoustic properties.

Author

Marchant, Joshua K., Clinard, Samuel R., Odéen, Henrik, Parker, Dennis L., and Christensen, Douglas A.

Subjects
GEOMETRIC modeling, ATTENUATION coefficients, SKULL, SPEED of sound, COMPUTED tomography, COMPACT bone, COST functions
Abstract

In this study, we investigated the impact of various simulated skull bone geometries on the determination of skull speed of sound and acoustic attenuation values via optimization using transmitted pressure amplitudes beyond the bone. Using the hybrid angular spectrum method (HAS), we simulated ultrasound transmission through four model sets of different geometries involving sandwiched layers of diploë and cortical bone in addition to three models generated from CT images of ex‐vivo human skull‐bones. We characterized cost‐function solution spaces for each model and, using optimization, found that when a model possessed appreciable variations in resolvable layer thickness, the predefined attenuation coefficients could be found with low error (RMSE < 0.01 Np/cm). However, we identified a spatial frequency cutoff in the models' geometry beyond which the accuracy of the property determination begins to fail, depending on the frequency of the ultrasound source. There was a large increase in error of the attenuation coefficients determined by the optimization when the variations in layer thickness were above the identified spatial frequency cutoffs, or when the lateral variations across the model were relatively low in amplitude. For our limited sample of three CT‐image derived bone models, the attenuation coefficients were determined successfully. The speed of sound values were determined with low error for all models (including the CT‐image derived models) that were tested (RMSE < 0.4 m/s). These results illustrate that it is possible to determine the acoustic properties of two‐component models when the internal bone structure is taken into account and the structure satisfies the spatial frequency constraints discussed. [ABSTRACT FROM AUTHOR]

Published
2023
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28. Simultaneous proton resonance frequency T1 ‐ MR shear wave elastography for MR‐guided focused ultrasound multiparametric treatment monitoring.

Author

Odéen, Henrik, Hofstetter, Lorne W., Payne, Allison H., Guiraud, Ludovic, Dumont, Erik, and Parker, Dennis L.

Subjects
PROTON magnetic resonance, SHEAR waves, IMAGING phantoms, ELASTOGRAPHY, THERMODYNAMIC cycles
Abstract

Purpose: To develop an efficient MRI pulse sequence to simultaneously measure multiple parameters that have been shown to correlate with tissue nonviability following thermal therapies. Methods: A 3D segmented EPI pulse sequence was used to simultaneously measure proton resonance frequency shift (PRFS) MR thermometry (MRT), T1 relaxation time, and shear wave velocity induced by focused ultrasound (FUS) push pulses. Experiments were performed in tissue mimicking gelatin phantoms and ex vivo bovine liver. Using a carefully designed FUS triggering scheme, a heating duty cycle of approximately 65% was achieved by interleaving FUS ablation pulses with FUS push pulses to induce shear waves in the tissue. Results: In phantom studies, temperature increases measured with PRFS MRT and increases in T1 correlated with decreased shear wave velocity, consistent with material softening with increasing temperature. During ablation in ex vivo liver, temperature increase measured with PRFS MRT initially correlated with increasing T1 and decreasing shear wave velocity, and after tissue coagulation with decreasing T1 and increasing shear wave velocity. This is consistent with a previously described hysteresis in T1 versus PRFS curves and increased tissue stiffness with tissue coagulation. Conclusion: An efficient approach for simultaneous and dynamic measurements of PRSF, T1, and shear wave velocity during treatment is presented. This approach holds promise for providing co‐registered dynamic measures of multiple parameters, which correlates to tissue nonviability during and following thermal therapies, such as FUS. [ABSTRACT FROM AUTHOR]

Published
2023
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35. Technical Note: Quantification of blood‐spinal cord barrier permeability after application of magnetic resonance‐guided focused ultrasound in spinal cord injury

Author

Cross, Chloe G., primary, Payne, Allison H., additional, Hawryluk, Gregory W., additional, Haag‐Roeger, Riley, additional, Cheeniyil, Rahul, additional, Brady, Dalton, additional, Odéen, Henrik, additional, Minoshima, Satoshi, additional, Cross, Donna J., additional, and Anzai, Yoshimi, additional

Published
2021
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36. A k‐space‐based method to measure and correct for temporal B0 field variations in MR temperature imaging.

Author

Parker, Dennis L., Payne, Allison, and Odéen, Henrik

Subjects
MAGNETIC resonance imaging, IMAGING phantoms, TEMPERATURE measurements, MAGNETIC fields
Abstract

Purpose: Present a method to use change in phase in repeated Cartesian k‐space measurements to monitor the change in magnetic field for dynamic MR temperature imaging. Methods: The method is applied to focused ultrasound heating experiments in a gelatin phantom and an ex vivo salt pork sample, without and with simulated respiratory motion. Results: In each experiment, phase variations due to B0 field drift and respiration were readily apparent in the measured phase difference. With correction, the SD of the temperature over time was reduced from 0.18°C to 0.14°C (no breathing) and from 0.81°C to 0.22°C (with breathing) for the gelatin phantom, and from 0.68°C to 0.13°C (no breathing) and from 1.06°C to 0.17°C (with breathing) for the pork sample. The accuracy in nonheated regions, assessed as the RMS error deviation from 0°C, improved from 1.70°C to 1.11°C (no breathing) and from 4.73°C to 1.47°C (with breathing) for the gelatin phantom, and from 5.95°C to 0.88°C (no breathing) and from 13.40°C to 1.73°C (with breathing) for the pork sample. The correction did not affect the temperature measurement accuracy in the heated regions. Conclusion: This work demonstrates that phase changes resulting from variations in B0 due to drift and respiration, commonly seen in MR thermometry applications, can be measured directly from 3D Cartesian acquisition methods. The correction of temporal field variations using the presented technique improved temperature accuracy, reduced variability in nonheated regions, and did not reduce accuracy in heated regions. [ABSTRACT FROM AUTHOR]

Published
2022
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40. Effects of T2* on accuracy and precision of dynamic T1 measurements using the single reference variable flip angle method: a simulation study.

Author

Malmberg, Michael A., Odéen, Henrik, and Parker, Dennis L.

Subjects
*MONTE Carlo method, *ERROR analysis in mathematics, *MEASUREMENT errors
Abstract

Purpose: To study in simulation and in theory the accuracy and precision of dynamic T1 measurements obtained using the previously published single‐reference variable flip angle (SR‐VFA) technique, with a focus on the effects of dynamic changes in T2* on the calculation. Methods: Monte Carlo simulations were performed over 1000 noisy iterations for the VFA method, the SR‐VFA method, and a proposed method, SR‐VFA with a T2* correction (SR‐VFA‐T2*). Dynamic T1 estimates were calculated analytically for each method, with signals modeled by the steady‐state spoiled gradient echo equation. The mean and standard deviation of these estimates were calculated and compared to truth, while varying repetition time (TR), baseline and dynamic T1, echo time (TE), baseline and dynamic T2*, flip angles, and the number of averages on baseline scans. Additionally, the variance of T1 in the SR‐VFA and SR‐VFA‐T2* methods was derived analytically based on the theory of propagation of errors. This equation was used to produce an inverse‐variance weighted linear combination to improve T1 mapping precision in the SR‐VFA‐T2* method. Flip angle sensitivity of dynamic T1 precision in the SR‐VFA and SR‐VFA‐T2* methods was also performed. Results: Substantial bias can be produced by the SR‐VFA method when the ratio of the T2* decay of the dynamic signal versus that of the baseline signals deviates from 1, with a 0.01 deviation leading to approximately a 1% bias in cases of high SNR and TR ≫ T1. This bias can be corrected by estimating the baseline and dynamic T2* values in this ratio via multiecho measurements. The bias and precision of the SR‐VFA‐T2* method, when normalized to scan time, is found to rival and sometimes improve upon the two flip angle VFA method when an inverse variance weighted linear combination is applied across its multiecho T1 maps. The analytic variance equation presented is found to be accurate within 1% relative to the Monte Carlo simulations over a broad parameter space. Flip angle ranges that maximize SR‐VFA and SR‐VFA‐T2*T1 precision over a broad parameter space are given, and each is defined relative to TR and T1. Conclusions: Multiecho SR‐VFA‐T2* T1 mapping is found in simulation and theory to be a promising alternative to the VFA method that maintains speed of the SR‐VFA method with accuracy and precision similar to the VFA method. [ABSTRACT FROM AUTHOR]

Published
2022
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42. International Society for Therapeutic Ultrasound Conference 2016

Author

Fowlkes, Brian, Ghanouni, Pejman, Sanghvi, Narendra, Coussios, Constantin, Lyon, Paul C., Gray, Michael, Mannaris, Christophoros, Victor, Marie de Saint, Stride, Eleanor, Cleveland, Robin, Carlisle, Robert, Wu, Feng, Middleton, Mark, Gleeson, Fergus, Aubry, Jean-Franҫois, Pauly, Kim Butts, Moonen, Chrit, Vortman, Jacob, Sharabi, Shirley, Daniels, Dianne, Last, David, Guez, David, Levy, Yoav, Volovick, Alexander, Grinfeld, Javier, Rachmilevich, Itay, Amar, Talia, Zibly, Zion, Mardor, Yael, Harnof, Sagi, Plaksin, Michael, Weissler, Yoni, Shoham, Shy, Kimmel, Eitan, Naor, Omer, Farah, Nairouz, Paeng, Dong-Guk, Xu, Zhiyuan, Snell, John, Quigg, Anders H., Eames, Matthew, Jin, Changzhu, Everstine, Ashli C., Sheehan, Jason P., Lopes, Beatriz S., Kassell, Neal, Looi, Thomas, Khokhlova, Vera, Mougenot, Charles, Hynynen, Kullervo, Drake, James, Slayton, Michael, Amodei, Richard C., Compton, Keegan, McNelly, Ashley, Latt, Daniel, Kearney, John, Melodelima, David, Dupre, Aurelien, Chen, Yao, Perol, David, Vincenot, Jeremy, Chapelon, Jean-Yves, Rivoire, Michel, Guo, Wei, Ren, Guoxin, Shen, Guofeng, Neidrauer, Michael, Zubkov, Leonid, Weingarten, Michael S., Margolis, David J., Lewin, Peter A., McDannold, Nathan, Sutton, Jonathan, Vykhodtseva, Natalia, Livingstone, Margaret, Kobus, Thiele, Zhang, Yong-Zhi, Schwartz, Michael, Huang, Yuexi, Lipsman, Nir, Jain, Jennifer, Chapman, Martin, Sankar, Tejas, Lozano, Andres, Yeung, Robert, Damianou, Christakis, Papadopoulos, Nikolaos, Brokman, Omer, Zadicario, Eyal, Brenner, Ori, Castel, David, Wu, Shih-Ying, Grondin, Julien, Zheng, Wenlan, Heidmann, Marc, Karakatsani, Maria Eleni, Sánchez, Carlos J. Sierra, Ferrera, Vincent, Konofagou, Elisa E., Yiannakou, Marinos, Cho, HongSeok, Lee, Hwayoun, Han, Mun, Choi, Jong-Ryul, Lee, Taekwan, Ahn, Sanghyun, Chang, Yongmin, Park, Juyoung, Ellens, Nicholas, Partanen, Ari, Farahani, Keyvan, Airan, Raag, Carpentier, Alexandre, Canney, Michael, Vignot, Alexandre, Lafon, Cyril, Delattre, Jean-yves, Idbaih, Ahmed, Odéen, Henrik, Bolster, Bradley, Jeong, Eun Kee, Parker, Dennis L., Gaur, Pooja, Feng, Xue, Fielden, Samuel, Meyer, Craig, Werner, Beat, Grissom, William, Marx, Michael, Weber, Hans, Taviani, Valentina, Hargreaves, Brian, Tanaka, Jun, Kikuchi, Kentaro, Ishijima, Ayumu, Azuma, Takashi, Minamihata, Kosuke, Yamaguchi, Satoshi, Nagamune, Teruyuki, Sakuma, Ichiro, Takagi, Shu, Santin, Mathieu D., Marsac, Laurent, Maimbourg, Guillaume, Monfort, Morgane, Larrat, Benoit, François, Chantal, Lehéricy, Stéphane, Tanter, Mickael, Samiotaki, Gesthimani, Wang, Shutao, Acosta, Camilo, Feinberg, Eliza R., Kovacs, Zsofia I., Tu, Tsang-Wei, Papadakis, Georgios Z., Reid, William C., Hammoud, Dima A., Frank, Joseph A., Kovacs, Zsofia i., Kim, Saejeong, Jikaria, Neekita, Bresler, Michele, Qureshi, Farhan, Xia, Jingjing, Tsui, Po-Shiang, Liu, Hao-Li, Plata, Juan C., Sveinsson, Bragi, Salgaonkar, Vasant A., Adams, Matthew, Diederich, Chris, Ozhinsky, Eugene, Bucknor, Matthew D., Rieke, Viola, Mikhail, Andrew, Severance, Lauren, Negussie, Ayele H., Wood, Bradford, de Greef, Martijn, Schubert, Gerald, Ries, Mario, Poorman, Megan E., Dockery, Mary, Chaplin, Vandiver, Dudzinski, Stephanie O., Spears, Ryan, Caskey, Charles, Giorgio, Todd, Costa, Marcia M., Papaevangelou, Efthymia, Shah, Anant, Rivens, Ian, Box, Carol, Bamber, Jeff, ter Haar, Gail, Burks, Scott R., Nagle, Matthew, Nguyen, Ben, Milo, Blerta, Le, Nhan M., Song, Shaozhen, Zhou, Kanheng, Nabi, Ghulam, Huang, Zhihong, Ben-Ezra, Shmuel, Rosen, Shani, Mihcin, Senay, Strehlow, Jan, Karakitsios, Ioannis, Le, Nhan, Schwenke, Michael, Demedts, Daniel, Prentice, Paul, Haase, Sabrina, Preusser, Tobias, Melzer, Andreas, Mestas, Jean-Louis, Chettab, Kamel, Gomez, Gustavo Stadthagen, Dumontet, Charles, Werle, Bettina, Marquet, Fabrice, Bour, Pierre, Vaillant, Fanny, Amraoui, Sana, Dubois, Rémi, Ritter, Philippe, Haïssaguerre, Michel, Hocini, Mélèze, Bernus, Olivier, Quesson, Bruno, Livneh, Amit, Adam, Dan, Robin, Justine, Arnal, Bastien, Fink, Mathias, Pernot, Mathieu, Khokhlova, Tatiana D., Schade, George R., Wang, Yak-Nam, Kreider, Wayne, Simon, Julianna, Starr, Frank, Karzova, Maria, Maxwell, Adam, Bailey, Michael R., Lundt, Jonathan E., Allen, Steven P., Sukovich, Jonathan R., Hall, Timothy, Xu, Zhen, May, Philip, Lin, Daniel W., Constans, Charlotte, Deffieux, Thomas, Aubry, Jean-Francois, Park, Eun-Joo, Ahn, Yun Deok, Kang, Soo Yeon, Park, Dong-Hyuk, Lee, Jae Young, Vidal-Jove, J., Perich, E., Ruiz, A., Jaen, A., Eres, N., del Castillo, M. Alvarez, Myers, Rachel, Kwan, James, Coviello, Christian, Rowe, Cliff, Crake, Calum, Finn, Sean, Jackson, Edward, Pouliopoulos, Antonios, Li, Caiqin, Tinguely, Marc, Tang, Meng-Xing, Garbin, Valeria, Choi, James J., Folkes, Lisa, Stratford, Michael, Nwokeoha, Sandra, Li, Tong, Farr, Navid, D’Andrea, Samantha, Gravelle, Kayla, Chen, Hong, Lee, Donghoon, Hwang, Joo Ha, Tardoski, Sophie, Ngo, Jacqueline, Gineyts, Evelyne, Roux, Jean-Pau, Clézardin, Philippe, Conti, Allegra, Magnin, Rémi, Gerstenmayer, Matthieu, Lux, François, Tillement, Olivier, Mériaux, Sébastien, Penna, Stefania Della, Romani, Gian Luca, Dumont, Erik, Sun, Tao, Power, Chanikarn, Miller, Eric, Sapozhnikov, Oleg, Tsysar, Sergey, Yuldashev, Petr V., Svet, Victor, Li, Dongli, Pellegrino, Antonio, Petrinic, Nik, Siviour, Clive, Jerusalem, Antoine, Yuldashev, Peter V., Cunitz, Bryan W., Dunmire, Barbrina, Inserra, Claude, Guedra, Matthieu, Mauger, Cyril, Gilles, Bruno, Solovchuk, Maxim, Sheu, Tony W. H., Thiriet, Marc, Zhou, Yufeng, Neufeld, Esra, Baumgartner, Christian, Payne, Davnah, Kyriakou, Adamos, Kuster, Niels, Xiao, Xu, McLeod, Helen, Dillon, Christopher, Payne, Allison, Khokhova, Vera A., Sinilshchikov, Ilya, Andriyakhina, Yulia, Rybyanets, Andrey, Shvetsova, Natalia, Berkovich, Alex, Shvetsov, Igor, Shaw, Caroline J., Civale, John, Giussani, Dino, Lees, Christoph, Ozenne, Valery, Toupin, Solenn, Salgaonkar, Vasant, Kaye, Elena, Monette, Sebastien, Maybody, Majid, Srimathveeravalli, Govindarajan, Solomon, Stephen, Gulati, Amitabh, Bezzi, Mario, Jenne, Jürgen W., Lango, Thomas, Müller, Michael, Sat, Giora, Tanner, Christine, Zangos, Stephan, Günther, Matthias, Dinh, Au Hoang, Niaf, Emilie, Bratan, Flavie, Guillen, Nicolas, Souchon, Rémi, Lartizien, Carole, Crouzet, Sebastien, Rouviere, Olivier, Han, Yang, Payen, Thomas, Palermo, Carmine, Sastra, Steve, Olive, Kenneth, van Breugel, Johanna M., van den Bosch, Maurice A., Fellah, Benjamin, Le Bihan, Denis, Hernandez-Garcia, Luis, Cain, Charles A., Lyka, Erasmia, Elbes, Delphine, Li, Chunhui, Tamano, Satoshi, Jimbo, Hayato, Yoshizawa, Shin, Fujiwara, Keisuke, Itani, Kazunori, Umemura, Shin-ichiro, Stoianovici, Dan, Zaini, Zulfadhli, Takagi, Ryo, Zong, Shenyan, Watkins, Ron, Pascal-Tenorio, Aurea, Jones, Peter, Butts-Pauly, Kim, Bouley, Donna, Chen, Yazhu, Lin, Chung-Yin, Hsieh, Han-Yi, Wei, Kuo-Chen, Garnier, Camille, Renault, Gilles, Seifabadi, Reza, Wilson, Emmanuel, Eranki, Avinash, Kim, Peter, Lübke, Dennis, Huber, Peter, Georgii, Joachim, Dresky, Caroline V., Haller, Julian, Yarmolenko, Pavel, Sharma, Karun, Celik, Haydar, Li, Guofeng, Qiu, Weibao, Zheng, Hairong, Tsai, Meng-Yen, Chu, Po-Chun, Webb, Taylor, Vyas, Urvi, Walker, Matthew, Zhong, Jidan, Waspe, Adam C., Hodaie, Mojgan, Yang, Feng-Yi, Huang, Sin-Luo, Zur, Yuval, Assif, Benny, Aurup, Christian, Kamimura, Hermes, Carneiro, Antonio A., Rothlübbers, Sven, Schwaab, Julia, Houston, Graeme, Azhari, Haim, Weiss, Noam, Sosna, Jacob, Goldberg, S. Nahum, Barrere, Victor, Jang, Kee W., Lewis, Bobbi, Wang, Xiaotong, Suomi, Visa, Edwards, David, Larrabee, Zahary, Hananel, Arik, Rafaely, Boaz, Debbiny, Rasha Elaimy, Dekel, Carmel Zeltser, Assa, Michael, Menikou, George, Mouratidis, Petros, Pineda-Pardo, José A., de Pedro, Marta Del Álamo, Martinez, Raul, Hernandez, Frida, Casas, Silvia, Oliver, Carlos, Pastor, Patricia, Vela, Lidia, Obeso, Jose, Greillier, Paul, Zorgani, Ali, Catheline, Stefan, Solovov, Vyacheslav, Vozdvizhenskiy, Michael O., Orlov, Andrew E., Wu, Chueh-Hung, Sun, Ming-Kuan, Shih, Tiffany T., Chen, Wen-Shiang, Prieur, Fabrice, Pillon, Arnaud, Cartron, Valerie, Cebe, Patrick, Chansard, Nathalie, Lafond, Maxime, Seya, Pauline Muleki, Bera, Jean-Christophe, Boissenot, Tanguy, Fattal, Elias, Bordat, Alexandre, Chacun, Helene, Guetin, Claire, Tsapis, Nicolas, Maruyama, Kazuo, Unga, Johan, Suzuki, Ryo, Fant, Cécile, Rogez, Bernadette, Afadzi, Mercy, Myhre, Ola Finneng, Vea, Siri, Bjørkøy, Astrid, Yemane, Petros Tesfamichael, van Wamel, Annemieke, Berg, Sigrid, Hansen, Rune, Angelsen, Bjørn, and Davies, Catharina

Subjects
Meeting Abstracts
Published
2017

48. Evaluation of a Three-Dimensional MR Acoustic Radiation Force Imaging Pulse Sequence Using a Novel Unbalanced Bipolar Motion Encoding Gradient

Author

de Bever, Joshua T., Odéen, Henrik, Todd, Nick, Farrer, Alexis I., and Parker, Dennis L.

Subjects
Reproducibility of Results, Signal Processing, Computer-Assisted, Image Enhancement, Magnetic Resonance Imaging, Sensitivity and Specificity, Article, Motion, Imaging, Three-Dimensional, Image Interpretation, Computer-Assisted, Cadaver, Elasticity Imaging Techniques, Humans, Female, Algorithms
Abstract

MR guided focused ultrasound procedures require accurate focal spot localization in three dimensions. This study presents a three-dimensional (3D) pulse sequence for acoustic radiation force imaging (ARFI) that efficiently localizes the focal spot by means of ultrasound induced tissue displacement over a large field-of-view.A novel unbalanced bipolar motion encoding gradient was implemented to maximize time available for motion encoding, reduce echo times, and allow for longer echo train lengths. Two advanced features, kz reduction factor (KZRF) and kz -level interleaving, were implemented to reduce tissue heating. Studies in gelatin phantoms compared the location of peak displacement and temperature measured by 3D MR thermometry. MR-ARFI induced tissue heating was evaluated through a parametric study of sequence parameters and MR thermometry measurements during repeated application of ARFI sonication patterns. Sequence performance was characterized in the presence of respiration and tissue inhomogeneity.The location of peak displacement and temperature rise agreed within 0.2 ± 0.1 mm and 0.5 ± 0.3 mm in the transverse and longitudinal direction, respectively. The 3D displacement maps were acquired safely, and the KZRF and kz -level interleaving features reduced tissue heating by 51%. High quality displacement maps were obtained despite respiration and tissue inhomogeneities.This sequence provides a safe, accurate, and simple approach to localizing the focal spot in three dimensions with a single scan. Magn Reson Med 76:803-813, 2016. © 2015 Wiley Periodicals, Inc.

Published
2015

49. Sampling strategies for subsampled segmented EPI PRF thermometry in MR guided high intensity focused ultrasound

Author

Odéen, Henrik, Todd, Nick, Diakite, Mahamadou, Minalga, Emilee, Payne, Allison, and Parker, Dennis L.

Subjects
Imaging, Three-Dimensional, Echo-Planar Imaging, Phantoms, Imaging, Thermography, Temperature, High-Intensity Focused Ultrasound Ablation, Magnetic Resonance Physics, Magnetic Resonance Imaging, Interventional, Algorithms
Abstract

To investigate k-space subsampling strategies to achieve fast, large field-of-view (FOV) temperature monitoring using segmented echo planar imaging (EPI) proton resonance frequency shift thermometry for MR guided high intensity focused ultrasound (MRgHIFU) applications.Five different k-space sampling approaches were investigated, varying sample spacing (equally vs nonequally spaced within the echo train), sampling density (variable sampling density in zero, one, and two dimensions), and utilizing sequential or centric sampling. Three of the schemes utilized sequential sampling with the sampling density varied in zero, one, and two dimensions, to investigate sampling the k-space center more frequently. Two of the schemes utilized centric sampling to acquire the k-space center with a longer echo time for improved phase measurements, and vary the sampling density in zero and two dimensions, respectively. Phantom experiments and a theoretical point spread function analysis were performed to investigate their performance. Variable density sampling in zero and two dimensions was also implemented in a non-EPI GRE pulse sequence for comparison. All subsampled data were reconstructed with a previously described temporally constrained reconstruction (TCR) algorithm.The accuracy of each sampling strategy in measuring the temperature rise in the HIFU focal spot was measured in terms of the root-mean-square-error (RMSE) compared to fully sampled "truth." For the schemes utilizing sequential sampling, the accuracy was found to improve with the dimensionality of the variable density sampling, giving values of 0.65 °C, 0.49 °C, and 0.35 °C for density variation in zero, one, and two dimensions, respectively. The schemes utilizing centric sampling were found to underestimate the temperature rise, with RMSE values of 1.05 °C and 1.31 °C, for variable density sampling in zero and two dimensions, respectively. Similar subsampling schemes with variable density sampling implemented in zero and two dimensions in a non-EPI GRE pulse sequence both resulted in accurate temperature measurements (RMSE of 0.70 °C and 0.63 °C, respectively). With sequential sampling in the described EPI implementation, temperature monitoring over a 192×144×135 mm3 FOV with a temporal resolution of 3.6 s was achieved, while keeping the RMSE compared to fully sampled "truth" below 0.35 °C.When segmented EPI readouts are used in conjunction with k-space subsampling for MR thermometry applications, sampling schemes with sequential sampling, with or without variable density sampling, obtain accurate phase and temperature measurements when using a TCR reconstruction algorithm. Improved temperature measurement accuracy can be achieved with variable density sampling. Centric sampling leads to phase bias, resulting in temperature underestimations.

Published
2014

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