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Michael ES, Hennel F, Pruessmann KP. Motion-compensated diffusion encoding in multi-shot human brain acquisitions: Insights using high-performance gradients. Magn Reson Med 2024; 92:556-572. [PMID: 38441339 DOI: 10.1002/mrm.30069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 12/12/2023] [Accepted: 02/09/2024] [Indexed: 06/02/2024]
Abstract
PURPOSE To evaluate the utility of up to second-order motion-compensated diffusion encoding in multi-shot human brain acquisitions. METHODS Experiments were performed with high-performance gradients using three forms of diffusion encoding motion-compensated through different orders: conventional zeroth-order-compensated pulsed gradients (PG), first-order-compensated gradients (MC1), and second-order-compensated gradients (MC2). Single-shot acquisitions were conducted to correlate the order of motion compensation with resultant phase variability. Then, multi-shot acquisitions were performed at varying interleaving factors. Multi-shot images were reconstructed using three levels of shot-to-shot phase correction: no correction, channel-wise phase correction based on FID navigation, and correction based on explicit phase mapping (MUSE). RESULTS In single-shot acquisitions, MC2 diffusion encoding most effectively suppressed phase variability and sensitivity to brain pulsation, yielding residual variations of about 10° and of low spatial order. Consequently, multi-shot MC2 images were largely satisfactory without phase correction and consistently improved with the navigator correction, which yielded repeatable high-quality images; contrarily, PG and MC1 images were inadequately corrected using the navigator approach. With respect to MUSE reconstructions, the MC2 navigator-corrected images were in close agreement for a standard interleaving factor and considerably more reliable for higher interleaving factors, for which MUSE images were corrupted. Finally, owing to the advanced gradient hardware, the relative SNR penalty of motion-compensated diffusion sensitization was substantially more tolerable than that faced previously. CONCLUSION Second-order motion-compensated diffusion encoding mitigates and simplifies shot-to-shot phase variability in the human brain, rendering the multi-shot acquisition strategy an effective means to circumvent limitations of retrospective phase correction methods.
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Affiliation(s)
- Eric Seth Michael
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Franciszek Hennel
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Klaas Paul Pruessmann
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
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Starekova J, Geng R, Wang Z, Zhang Y, Uboha NV, Pirasteh A, Hernando D. Precision of liver and pancreas apparent diffusion coefficients using motion-compensated gradient waveforms in DWI. Magn Reson Imaging 2024; 110:161-169. [PMID: 38641212 PMCID: PMC11098682 DOI: 10.1016/j.mri.2024.04.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 04/16/2024] [Accepted: 04/16/2024] [Indexed: 04/21/2024]
Abstract
BACKGROUND Diffusion weighted imaging (DWI) with optimized motion-compensated gradient waveforms reduces signal dropouts in the liver and pancreas caused by cardiovascular-associated motion, however its precision is unknown. We hypothesized that DWI with motion-compensated DW gradient waveforms would improve apparent diffusion coefficient (ADC)-repeatability and inter-reader reproducibility compared to conventional DWI in these organs. METHODS In this IRB-approved, prospective, single center study, subjects recruited between October 2019 and March 2020 were scanned twice on a 3 T scanner, with repositioning between test and retest. Each scan included two respiratory-triggered DWI series with comparable acquisition time: 1) conventional (monopolar) 2) motion- compensated diffusion gradients. Three readers measured ADC values. One-way ANOVA, Bland-Altman analysis were used for statistical analysis. RESULTS Eight healthy participants (4 male/4 female), with a mean age of 29 ± 4 years, underwent the liver and pancreas MRI protocol. Four patients with liver metastases (2 male/2 female) with a mean age of 58 ± 5 years underwent the liver MRI protocol. In healthy participants, motion-compensated DWI outperformed conventional DWI with mean repeatability coefficient of 0.14 × 10-3 (CI:0.12-0.17) vs. 0.31 × 10-3 (CI:0.27-0.37) mm2/s for liver, and 0.11 × 10-3 (CI:0.08-0.15) vs. 0.34 × 10-3 (CI:0.27-0.49) mm2/s for pancreas; and with mean reproducibility coefficient of 0.20 × 10-3 (CI:0.18-0.23) vs. 0.51 × 10-3 (CI:0.46-0.58) mm2/s for liver, and 0.16 × 10-3 (CI:0.13-0.20) vs. 0.42 × 10-3 (CI:0.34-0.52) mm2/s for pancreas. In patients, improved repeatability was observed for motion-compensated DWI in comparison to conventional with repeatability coefficient of 0.51 × 10- 3 mm2/s (CI:0.35-0.89) vs. 0.70 × 10-3 mm2/s (CI:0.49-1.20). CONCLUSION Motion-compensated DWI enhances the precision of ADC measurements in the liver and pancreas compared to conventional DWI.
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Affiliation(s)
- Jitka Starekova
- Department of Radiology, University of Wisconsin, Madison, WI, USA.
| | - Ruiqi Geng
- Department of Radiology, University of Wisconsin, Madison, WI, USA; Department of Medical Physics, University of Wisconsin, Madison, WI, USA.
| | - Zihan Wang
- Department of Radiology, University of Wisconsin, Madison, WI, USA.
| | - Yuxin Zhang
- Department of Radiology, University of Wisconsin, Madison, WI, USA; Department of Medical Physics, University of Wisconsin, Madison, WI, USA.
| | - Nataliya V Uboha
- Division of Hematology, Medical Oncology and Palliative Care, Department of Medicine, University of Wisconsin, School of Medcine and Public Health, Madison, WI, USA; Carbone Cancer Center, University of Wisconsin, Madison, WI, USA.
| | - Ali Pirasteh
- Department of Radiology, University of Wisconsin, Madison, WI, USA; Department of Medical Physics, University of Wisconsin, Madison, WI, USA.
| | - Diego Hernando
- Department of Radiology, University of Wisconsin, Madison, WI, USA; Department of Medical Physics, University of Wisconsin, Madison, WI, USA.
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McTavish S, Van AT, Peeters JM, Weiss K, Harder FN, Makowski MR, Braren RF, Karampinos DC. Partial Fourier in the presence of respiratory motion in prostate diffusion-weighted echo planar imaging. MAGMA (NEW YORK, N.Y.) 2024:10.1007/s10334-024-01162-x. [PMID: 38743376 DOI: 10.1007/s10334-024-01162-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 03/05/2024] [Accepted: 04/24/2024] [Indexed: 05/16/2024]
Abstract
PURPOSE To investigate the effect of respiratory motion in terms of signal loss in prostate diffusion-weighted imaging (DWI), and to evaluate the usage of partial Fourier in a free-breathing protocol in a clinically relevant b-value range using both single-shot and multi-shot acquisitions. METHODS A controlled breathing DWI acquisition was first employed at 3 T to measure signal loss from deep breathing patterns. Single-shot and multi-shot (2-shot) acquisitions without partial Fourier (no pF) and with partial Fourier (pF) factors of 0.75 and 0.65 were employed in a free-breathing protocol. The apparent SNR and ADC values were evaluated in 10 healthy subjects to measure if low pF factors caused low apparent SNR or overestimated ADC. RESULTS Controlled breathing experiments showed a difference in signal coefficient of variation between shallow and deep breathing. In free-breathing single-shot acquisitions, the pF 0.65 scan showed a significantly (p < 0.05) higher apparent SNR than pF 0.75 and no pF in the peripheral zone (PZ) of the prostate. In the multi-shot acquisitions in the PZ, pF 0.75 had a significantly higher apparent SNR than 0.65 pF and no pF. The single-shot pF 0.65 scan had a significantly lower ADC than single-shot no pF. CONCLUSION Deep breathing patterns can cause intravoxel dephasing in prostate DWI. For single-shot acquisitions at a b-value of 800 s/mm2, any potential risks of motion-related artefacts at low pF factors (pF 0.65) were outweighed by the increase in signal from a lower TE, as shown by the increase in apparent SNR. In multi-shot acquisitions however, the minimum pF factor should be larger, as shown by the lower apparent SNR at low pF factors.
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Affiliation(s)
- Sean McTavish
- Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany.
| | - Anh T Van
- Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany
| | | | | | - Felix N Harder
- Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany
| | - Marcus R Makowski
- Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany
| | - Rickmer F Braren
- Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany
| | - Dimitrios C Karampinos
- Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany
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Führes T, Saake M, Lorenz J, Seuss H, Bickelhaupt S, Uder M, Laun FB. Feature-guided deep learning reduces signal loss and increases lesion CNR in diffusion-weighted imaging of the liver. Z Med Phys 2024; 34:258-269. [PMID: 37543450 PMCID: PMC11156785 DOI: 10.1016/j.zemedi.2023.07.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 07/13/2023] [Accepted: 07/16/2023] [Indexed: 08/07/2023]
Abstract
PURPOSE This research aims to develop a feature-guided deep learning approach and compare it with an optimized conventional post-processing algorithm in order to enhance the image quality of diffusion-weighted liver images and, in particular, to reduce the pulsation-induced signal loss occurring predominantly in the left liver lobe. METHODS Data from 40 patients with liver lesions were used. For the conventional approach, the best-suited out of five examined algorithms was chosen. For the deep learning approach, a U-Net was trained. Instead of learning "gold-standard" target images, the network was trained to optimize four image features (lesion CNR, vessel darkness, data consistency, and pulsation artifact reduction), which could be assessed quantitatively using manually drawn ROIs. A quality score was calculated from these four features. As an additional quality assessment, three radiologists rated different features of the resulting images. RESULTS The conventional approach could substantially increase the lesion CNR and reduce the pulsation-induced signal loss. However, the vessel darkness was reduced. The deep learning approach increased the lesion CNR and reduced the signal loss to a slightly lower extent, but it could additionally increase the vessel darkness. According to the image quality score, the quality of the deep-learning images was higher than that of the images obtained using the conventional approach. The radiologist ratings were mostly consistent with the quantitative scores, but the overall quality ratings differed among the readers. CONCLUSION Unlike the conventional algorithm, the deep-learning algorithm increased the vessel darkness. Therefore, it may be a viable alternative to conventional algorithms.
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Affiliation(s)
- Tobit Führes
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
| | - Marc Saake
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Jennifer Lorenz
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Hannes Seuss
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany; Department of Radiology, Klinikum Forchheim - Fränkische Schweiz, Forchheim, Germany
| | - Sebastian Bickelhaupt
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Michael Uder
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Frederik Bernd Laun
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
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Raspe J, Harder FN, Rupp S, McTavish S, Peeters JM, Weiss K, Makowski MR, Braren RF, Karampinos DC, Van AT. Retrospective Motion Artifact Reduction by Spatial Scaling of Liver Diffusion-Weighted Images. Tomography 2023; 9:1839-1856. [PMID: 37888738 PMCID: PMC10610678 DOI: 10.3390/tomography9050146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 09/27/2023] [Accepted: 09/29/2023] [Indexed: 10/28/2023] Open
Abstract
Cardiac motion causes unpredictable signal loss in respiratory-triggered diffusion-weighted magnetic resonance imaging (DWI) of the liver, especially inside the left lobe. The left liver lobe may thus be frequently neglected in the clinical evaluation of liver DWI. In this work, a data-driven algorithm that relies on the statistics of the signal in the left liver lobe to mitigate the motion-induced signal loss is presented. The proposed data-driven algorithm utilizes the exclusion of severely corrupted images with subsequent spatially dependent image scaling based on a signal-loss model to correctly combine the multi-average diffusion-weighted images. The signal in the left liver lobe is restored and the liver signal is more homogeneous after applying the proposed algorithm. Furthermore, overestimation of the apparent diffusion coefficient (ADC) in the left liver lobe is reduced. The proposed algorithm can therefore contribute to reduce the motion-induced bias in DWI of the liver and help to increase the diagnostic value of DWI in the left liver lobe.
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Affiliation(s)
- Johannes Raspe
- School of Medicine and Health, Technical University of Munich, 81675 Munich, Germany (D.C.K.); (A.T.V.)
- School of Natural Sciences, Technical University of Munich, 85748 Garching, Germany
| | - Felix N. Harder
- School of Medicine and Health, Technical University of Munich, 81675 Munich, Germany (D.C.K.); (A.T.V.)
| | - Selina Rupp
- School of Medicine and Health, Technical University of Munich, 81675 Munich, Germany (D.C.K.); (A.T.V.)
| | - Sean McTavish
- School of Medicine and Health, Technical University of Munich, 81675 Munich, Germany (D.C.K.); (A.T.V.)
| | | | - Kilian Weiss
- Philips GmbH Market DACH, 22335 Hamburg, Germany
| | - Marcus R. Makowski
- School of Medicine and Health, Technical University of Munich, 81675 Munich, Germany (D.C.K.); (A.T.V.)
| | - Rickmer F. Braren
- School of Medicine and Health, Technical University of Munich, 81675 Munich, Germany (D.C.K.); (A.T.V.)
| | - Dimitrios C. Karampinos
- School of Medicine and Health, Technical University of Munich, 81675 Munich, Germany (D.C.K.); (A.T.V.)
| | - Anh T. Van
- School of Medicine and Health, Technical University of Munich, 81675 Munich, Germany (D.C.K.); (A.T.V.)
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Führes T, Saake M, Szczepankiewicz F, Bickelhaupt S, Uder M, Laun FB. Impact of velocity- and acceleration-compensated encodings on signal dropout and black-blood state in diffusion-weighted magnetic resonance liver imaging at clinical TEs. PLoS One 2023; 18:e0291273. [PMID: 37796773 PMCID: PMC10553293 DOI: 10.1371/journal.pone.0291273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 08/24/2023] [Indexed: 10/07/2023] Open
Abstract
PURPOSE The study aims to develop easy-to-implement concomitant field-compensated gradient waveforms with varying velocity-weighting (M1) and acceleration-weighting (M2) levels and to evaluate their efficacy in correcting signal dropouts and preserving the black-blood state in liver diffusion-weighted imaging. Additionally, we seek to determine an optimal degree of compensation that minimizes signal dropouts while maintaining blood signal suppression. METHODS Numerically optimized gradient waveforms were adapted using a novel method that allows for the simultaneous tuning of M1- and M2-weighting by changing only one timing variable. Seven healthy volunteers underwent diffusion-weighted magnetic resonance imaging (DWI) with five diffusion encoding schemes (monopolar, velocity-compensated (M1 = 0), acceleration-compensated (M1 = M2 = 0), 84%-M1-M2-compensated, 67%-M1-M2-compensated) at b-values of 50 and 800 s/mm2 at a constant echo time of 70 ms. Signal dropout correction and apparent diffusion coefficients (ADCs) were quantified using regions of interest in the left and right liver lobe. The blood appearance was evaluated using two five-point Likert scales. RESULTS Signal dropout was more pronounced in the left lobe (19%-42% less signal than in the right lobe with monopolar scheme) and best corrected by acceleration-compensation (8%-10% less signal than in the right lobe). The black-blood state was best with monopolar encodings and decreased significantly (p < 0.001) with velocity- and/or acceleration-compensation. The partially M1-M2-compensated encoding schemes could restore the black-blood state again. Strongest ADC bias occurred for monopolar encodings (difference between left/right lobe of 0.41 μm2/ms for monopolar vs. < 0.12 μm2/ms for the other encodings). CONCLUSION All of the diffusion encodings used in this study demonstrated suitability for routine DWI application. The results indicate that a perfect value for the level of M1-M2-compensation does not exist. However, among the examined encodings, the 84%-M1-M2-compensated encodings provided a suitable tradeoff.
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Affiliation(s)
- Tobit Führes
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Marc Saake
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | | | - Sebastian Bickelhaupt
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Michael Uder
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Frederik Bernd Laun
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
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Geng R, Zhang Y, Rice J, Muehler MR, Starekova J, Rutkowski DR, Uboha NV, Pirasteh A, Roldán-Alzate A, Guidon A, Hernando D. Motion-robust, blood-suppressed, reduced-distortion diffusion MRI of the liver. Magn Reson Med 2023; 89:908-921. [PMID: 36404637 PMCID: PMC9792444 DOI: 10.1002/mrm.29531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 10/30/2022] [Accepted: 10/31/2022] [Indexed: 11/22/2022]
Abstract
PURPOSE To evaluate feasibility and reproducibility of liver diffusion-weighted (DW) MRI using cardiac-motion-robust, blood-suppressed, reduced-distortion techniques. METHODS DW-MRI data were acquired at 3T in an anatomically accurate liver phantom including controlled pulsatile motion, in eight healthy volunteers and four patients with known or suspected liver metastases. Standard monopolar and motion-robust (M1-nulled, and M1-optimized) DW gradient waveforms were each acquired with single-shot echo-planar imaging (ssEPI) and multishot EPI (msEPI). In the motion phantom, apparent diffusion coefficient (ADC) was measured in the motion-affected volume. In healthy volunteers, ADC was measured in the left and right liver lobes separately to evaluate ADC reproducibility between the two lobes. Image distortions were quantified using the normalized cross-correlation coefficient, with an undistorted T2-weighted reference. RESULTS In the motion phantom, ADC mean and SD in motion-affected volumes substantially increased with increasing motion for monopolar waveforms. ADC remained stable in the presence of increasing motion when using motion-robust waveforms. M1-optimized waveforms suppressed slow flow signal present with M1-nulled waveforms. In healthy volunteers, monopolar waveforms generated significantly different ADC measurements between left and right liver lobes ( p = 0 . 0078 $$ p=0.0078 $$ , reproducibility coefficients (RPC) = 470 × 1 0 - 6 $$ 470\times 1{0}^{-6} $$ mm 2 $$ {}^2 $$ /s for monopolar-msEPI), while M1-optimized waveforms showed more reproducible ADC values ( p = 0 . 29 $$ p=0.29 $$ , RPC = 220 × 1 0 - 6 $$ \mathrm{RPC}=220\times 1{0}^{-6} $$ mm 2 $$ {}^2 $$ /s for M1-optimized-msEPI). In phantom and healthy volunteer studies, motion-robust acquisitions with msEPI showed significantly reduced image distortion ( p < 0 . 001 $$ p<0.001 $$ ) compared to ssEPI. Patient scans showed reduction of wormhole artifacts when combining M1-optimized waveforms with msEPI. CONCLUSION Synergistic effects of combined M1-optimized diffusion waveforms and msEPI acquisitions enable reproducible liver DWI with motion robustness, blood signal suppression, and reduced distortion.
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Affiliation(s)
- Ruiqi Geng
- Department of Radiology, University of Wisconsin-Madison, WI, USA,Department of Medical Physics, University of Wisconsin-Madison, WI, USA
| | - Yuxin Zhang
- Department of Radiology, University of Wisconsin-Madison, WI, USA,Department of Medical Physics, University of Wisconsin-Madison, WI, USA
| | - James Rice
- Department of Radiology, University of Wisconsin-Madison, WI, USA,Department of Mechanical Engineering, University of Wisconsin-Madison, WI, USA
| | | | - Jitka Starekova
- Department of Radiology, University of Wisconsin-Madison, WI, USA
| | - David R. Rutkowski
- Department of Radiology, University of Wisconsin-Madison, WI, USA,Department of Mechanical Engineering, University of Wisconsin-Madison, WI, USA
| | - Nataliya V. Uboha
- Division of Hematology and Oncology, Department of Medicine, University of Wisconsin-Madison, WI, USA,UW Carbone Cancer Center, WI, USA
| | - Ali Pirasteh
- Department of Radiology, University of Wisconsin-Madison, WI, USA,Department of Medical Physics, University of Wisconsin-Madison, WI, USA
| | - Alejandro Roldán-Alzate
- Department of Radiology, University of Wisconsin-Madison, WI, USA,Department of Mechanical Engineering, University of Wisconsin-Madison, WI, USA
| | | | - Diego Hernando
- Department of Radiology, University of Wisconsin-Madison, WI, USA,Department of Medical Physics, University of Wisconsin-Madison, WI, USA,Department of Electrical and Computer Engineering, University of Wisconsin-Madison, WI, USA,Department of Biomedical Engineering, University of Wisconsin-Madison, WI, USA
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Yang T, Li Y, Ye Z, Yao S, Li Q, Yuan Y, Song B. Diffusion Weighted Imaging of the Abdomen and Pelvis: Recent Technical Advances and Clinical Applications. Acad Radiol 2023; 30:470-482. [PMID: 36038417 DOI: 10.1016/j.acra.2022.07.018] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 07/20/2022] [Accepted: 07/23/2022] [Indexed: 01/25/2023]
Abstract
Diffusion weighted imaging (DWI) serves as one of the most important functional magnetic resonance imaging techniques in abdominal and pelvic imaging. It is designed to reflect the diffusion of water molecules and is particularly sensitive to the malignancies. Yet, the limitations of image distortion and artifacts in single-shot DWI may hamper its widespread use in clinical practice. With recent technical advances in DWI, such as simultaneous multi-slice excitation, computed or reduced field-of-view techniques, as well as advanced shimming methods, it is possible to achieve shorter acquisition time, better image quality, and higher robustness in abdominopelvic DWI. This review discussed the recent advances of each DWI approach, and highlighted its future perspectives in abdominal and pelvic imaging, hoping to familiarize physicians and radiologists with the technical improvements in this field and provide future research directions.
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Affiliation(s)
- Ting Yang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Ying Li
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Zheng Ye
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Shan Yao
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Qing Li
- MR Collaborations, Siemens Healthcare, Shanghai, China
| | - Yuan Yuan
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Bin Song
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China; Department of Radiology, Sanya People's Hospital, Sanya, Hainan, China.
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Simchick G, Hernando D. Precision of region of interest-based tri-exponential intravoxel incoherent motion quantification and the role of the Intervoxel spatial distribution of flow velocities. Magn Reson Med 2022; 88:2662-2678. [PMID: 35968580 PMCID: PMC9529845 DOI: 10.1002/mrm.29406] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 06/27/2022] [Accepted: 07/18/2022] [Indexed: 11/08/2022]
Abstract
PURPOSE The purpose of this work was to obtain precise tri-exponential intravoxel incoherent motion (IVIM) quantification in the liver using 2D (b-value and first-order motion moment [M1 ]) IVIM-DWI acquisitions and region of interest (ROI)-based fitting techniques. METHODS Diffusion MRI of the liver was performed in 10 healthy volunteers using three IVIM-DWI acquisitions: conventional monopolar, optimized monopolar, and optimized 2D (b-M1 ). For each acquisition, bi-exponential and tri-exponential full, segmented, and over-segmented ROI-based fitting and a newly proposed blood velocity SDdistribution (BVD) fitting technique were performed to obtain IVIM estimates in the right and left liver lobes. Fitting quality was evaluated using corrected Akaike information criterion. Precision metrics (test-retest repeatability, inter-reader reproducibility, and inter-lobar agreement) were evaluated using Bland-Altman analysis, repeatability/reproducibility coefficients (RPCs), and paired sample t-tests. Precision was compared across acquisitions and fitting methods. RESULTS High repeatability and reproducibility was observed in the estimations of the diffusion coefficient (Dtri = [1.03 ± 0.11] × 10-3 mm2 /s; RPCs ≤ 1.34 × 10-4 mm2 /s), perfusion fractions (F1 = 3.19 ± 1.89% and F2 = 16.4 ± 2.07%; RPCs ≤ 2.51%), and blood velocity SDs (Vb,1 = 1.44 ± 0.14 mm/s and Vb,2 = 3.62 ± 0.13 mm/s; RPCs ≤ 0.41 mm/s) in the right liver lobe using the 2D (b-M1 ) acquisition in conjunction with BVD fitting. Using these methods, significantly larger (p < 0.01) estimates of Dtri and F1 were observed in the left lobe in comparison to the right lobe, while estimates of Vb,1 and Vb,2 demonstrated high interlobar agreement (RPCs ≤ 0.45 mm/s). CONCLUSIONS The 2D (b-M1 ) IVIM-DWI data acquisition in conjunction with BVD fitting enables highly precise tri-exponential IVIM quantification in the right liver lobe.
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Affiliation(s)
- Gregory Simchick
- Radiology, University of Wisconsin-Madison, Madison, WI, United States
- Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
| | - Diego Hernando
- Radiology, University of Wisconsin-Madison, Madison, WI, United States
- Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
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10
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McTavish S, Van AT, Peeters JM, Weiss K, Makowski MR, Braren RF, Karampinos DC. Motion compensated renal diffusion weighted imaging. Magn Reson Med 2022; 89:144-160. [PMID: 36098347 DOI: 10.1002/mrm.29433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 07/15/2022] [Accepted: 08/10/2022] [Indexed: 11/09/2022]
Abstract
PURPOSE To assess the effect of respiratory motion and cardiac driven pulsation in renal DWI and to examine asymmetrical velocity-compensated diffusion encoding waveforms for robust ADC mapping in the kidneys. METHODS The standard monopolar Stejskal-Tanner pulsed gradient spin echo (pgse) and the asymmetric bipolar velocity-compensated (asym-vc) diffusion encoding waveforms were used for coronal renal DWI at 3T. The robustness of the ADC quantification in the kidneys was tested with the aforementioned waveforms in respiratory-triggered and breath-held cardiac-triggered scans at different trigger delays in 10 healthy subjects. RESULTS The pgse waveform showed higher ADC values in the right kidney at short trigger delays in comparison to longer trigger delays in the respiratory triggered scans when the diffusion gradient was applied in the feet-head (FH) direction. The coefficient of variation over all respiratory trigger delays, averaged over all subjects was 0.15 for the pgse waveform in the right kidney when diffusion was measured in the FH direction; the corresponding coefficient of variation for the asym-vc waveform was 0.06. The effect of cardiac driven pulsation was found to be small in comparison to the effect of respiratory motion. CONCLUSION Short trigger delays in respiratory-triggered scans can cause higher ADC values in comparison to longer trigger delays in renal DWI, especially in the right kidney when diffusion is measured in the FH direction. The asym-vc waveform can reduce ADC variation due to respiratory motion in respiratory-triggered scans at the cost of reduced SNR compared to the pgse waveform.
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Affiliation(s)
- Sean McTavish
- Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Anh T Van
- Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Munich, Germany
| | | | | | - Marcus R Makowski
- Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Rickmer F Braren
- Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Dimitrios C Karampinos
- Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Munich, Germany
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11
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Führes T, Saake M, Lorenz J, Seuss H, Stemmer A, Benkert T, Uder M, Laun FB. Reduction of the cardiac pulsation artifact and improvement of lesion conspicuity in flow‐compensated diffusion images in the liver—A quantitative evaluation of postprocessing algorithms. Magn Reson Med 2022; 89:423-439. [PMID: 36089798 DOI: 10.1002/mrm.29427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 08/05/2022] [Accepted: 08/08/2022] [Indexed: 11/10/2022]
Abstract
PURPOSE To enhance image quality of flow-compensated diffusion-weighted liver MRI data by increasing the lesion conspicuity and reducing the cardiac pulsation artifact using postprocessing algorithms. METHODS Diffusion-weighted image data of 40 patients with liver lesions had been acquired at 1.5 T. These data were postprocessed with 5 different algorithms (weighted averaging, p-mean, percentile, outlier exclusion, and exception set). Four image properties of the postprocessed data were evaluated for optimizing the algorithm parameters. These properties were the lesion to tissue contrast-to-noise ratio (CNR), the reduction of the cardiac pulsation artifact, the data consistency, and the vessel darkness. They were combined into a total quality score ( Q total , $$ {Q}_{\mathrm{total}}, $$ set to 1 for the trace-weighted reference image), which was used to rate the image quality objectively. RESULTS The weighted averaging algorithm performed best according to the total quality score ( Q total = 1.111 ± 0.067 $$ {Q}_{\mathrm{total}}=1.111\pm 0.067 $$ ). The further ranking was outlier exclusion algorithm ( Q total = 1.086 ± 0.061 $$ {Q}_{\mathrm{total}}=1.086\pm 0.061 $$ ), p-mean algorithm ( Q total = 1.045 ± 0.049 $$ {Q}_{\mathrm{total}}=1.045\pm 0.049 $$ ), percentile algorithm ( Q total = 1.012 ± 0.049 $$ {Q}_{\mathrm{total}}=1.012\pm 0.049 $$ ), and exception set algorithm ( Q total = 0.957 ± 0.027 $$ {Q}_{\mathrm{total}}=0.957\pm 0.027 $$ ). All optimized algorithms except for the exception set algorithm corrected the pulsation artifact and increased the lesion CNR. Changes in Q total $$ {Q}_{\mathrm{total}} $$ were significant for all optimized algorithms except for the percentile algorithm. Liver ADC was significantly reduced (except for the exception set algorithm), particularly in the left lobe. CONCLUSION Postprocessing algorithms should be used for flow-compensated liver DWI. The proposed weighted averaging algorithm seems to be suited best to increase the image quality of artifact-corrupted flow-compensated diffusion-weighted liver data.
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Affiliation(s)
- Tobit Führes
- Institute of Radiology, University Hospital Erlangen Friedrich‐Alexander‐Universität Erlangen‐Nürnberg (FAU) Erlangen Germany
| | - Marc Saake
- Institute of Radiology, University Hospital Erlangen Friedrich‐Alexander‐Universität Erlangen‐Nürnberg (FAU) Erlangen Germany
| | - Jennifer Lorenz
- Institute of Radiology, University Hospital Erlangen Friedrich‐Alexander‐Universität Erlangen‐Nürnberg (FAU) Erlangen Germany
| | - Hannes Seuss
- Institute of Radiology, University Hospital Erlangen Friedrich‐Alexander‐Universität Erlangen‐Nürnberg (FAU) Erlangen Germany
- Abteilung für Radiologie Klinikum Forchheim – Fränkische Schweiz Forchheim Germany
| | - Alto Stemmer
- MR Application Predevelopment Siemens Healthcare GmbH Erlangen Germany
| | - Thomas Benkert
- MR Application Predevelopment Siemens Healthcare GmbH Erlangen Germany
| | - Michael Uder
- Institute of Radiology, University Hospital Erlangen Friedrich‐Alexander‐Universität Erlangen‐Nürnberg (FAU) Erlangen Germany
| | - Frederik Bernd Laun
- Institute of Radiology, University Hospital Erlangen Friedrich‐Alexander‐Universität Erlangen‐Nürnberg (FAU) Erlangen Germany
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12
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Gadjimuradov F, Benkert T, Nickel MD, Führes T, Saake M, Maier A. Deep Learning-Guided Weighted Averaging for Signal Dropout Compensation in DWI of the Liver. Magn Reson Med 2022; 88:2679-2693. [PMID: 35916385 DOI: 10.1002/mrm.29380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 06/03/2022] [Accepted: 06/15/2022] [Indexed: 11/11/2022]
Abstract
PURPOSE To develop an algorithm for the retrospective correction of signal dropout artifacts in abdominal DWI resulting from cardiac motion. METHODS Given a set of image repetitions for a slice, a locally adaptive weighted averaging is proposed that aims to suppress the contribution of image regions affected by signal dropouts. Corresponding weight maps were estimated by a sliding-window algorithm, which analyzed signal deviations from a patch-wise reference. In order to ensure the computation of a robust reference, repetitions were filtered by a classifier that was trained to detect images corrupted by signal dropouts. The proposed method, named Deep Learning-guided Adaptive Weighted Averaging (DLAWA), was evaluated in terms of dropout suppression capability, bias reduction in the ADC, and noise characteristics. RESULTS In the case of uniform averaging, motion-related dropouts caused signal attenuation and ADC overestimation in parts of the liver, with the left lobe being affected particularly. Both effects could be substantially mitigated by DLAWA while preventing global penalties with respect to SNR due to local signal suppression. Performing evaluations on patient data, the capability to recover lesions concealed by signal dropouts was demonstrated as well. Further, DLAWA allowed for transparent control of the trade-off between SNR and signal dropout suppression by means of a few hyperparameters. CONCLUSION This work presents an effective and flexible method for the local compensation of signal dropouts resulting from motion and pulsation. Because DLAWA follows a retrospective approach, no changes to the acquisition are required.
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Affiliation(s)
- Fasil Gadjimuradov
- Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.,MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Thomas Benkert
- MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | | | - Tobit Führes
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Marc Saake
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Andreas Maier
- Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
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13
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Laun FB, Führes T, Seuss H, Müller A, Bickelhaupt S, Stemmer A, Benkert T, Uder M, Saake M. Flow-compensated diffusion encoding in MRI for improved liver metastasis detection. PLoS One 2022; 17:e0268843. [PMID: 35617260 PMCID: PMC9135229 DOI: 10.1371/journal.pone.0268843] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 05/09/2022] [Indexed: 12/27/2022] Open
Abstract
Magnetic resonance (MR) diffusion-weighted imaging (DWI) is often used to detect focal liver lesions (FLLs), though DWI image quality can be limited in the left liver lobe owing to the pulsatile motion of the nearby heart. Flow-compensated (FloCo) diffusion encoding has been shown to reduce this pulsation artifact. The purpose of this prospective study was to intra-individually compare DWI of the liver acquired with conventional monopolar and FloCo diffusion encoding for assessing metastatic FLLs in non-cirrhotic patients. Forty patients with known or suspected multiple metastatic FLLs were included and measured at 1.5 T field strength with a conventional (monopolar) and a FloCo diffusion encoding EPI sequence (single refocused; b-values, 50 and 800 s/mm2). Two board-certified radiologists analyzed the DWI images independently. They issued Likert-scale ratings (1 = worst, 5 = best) for pulsation artifact severity and counted the difference of lesions visible at b = 800 s/mm² separately for small and large FLLs (i.e., < 1 cm or > 1 cm) and separately for left and right liver lobe. Differences between the two diffusion encodings were assessed with the Wilcoxon signed-rank test. Both readers found a reduction in pulsation artifact in the liver with FloCo encoding (p < 0.001 for both liver lobes). More small lesions were detected with FloCo diffusion encoding in both liver lobes (left lobe: six and seven additional lesions by readers 1 and 2, respectively; right lobe: five and seven additional lesions for readers 1 and 2, respectively). Both readers found one additional large lesion in the left liver lobe. Thus, flow-compensated diffusion encoding appears more effective than monopolar diffusion encoding for the detection of liver metastases.
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Affiliation(s)
- Frederik B. Laun
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Tobit Führes
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Hannes Seuss
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- Department of Radiology, Klinikum Forchheim—Fränkische Schweiz gGmbH, Forchheim, Germany
| | - Astrid Müller
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Sebastian Bickelhaupt
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | | | | | - Michael Uder
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Marc Saake
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- * E-mail:
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14
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Yin J, Gao X, Wu M, Liang Y. A Method for the Reconstruction of Myocardial Fiber Structure in Diffusivity Adaptive Imaging Based on Particle Filter. INTERNATIONAL JOURNAL OF E-COLLABORATION 2022. [DOI: 10.4018/ijec.304033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
In order to explore the cause of characteristic change and pathological variation of myocardial fiber structure, the posterior probability distribution of fiber direction was described. To solve the problems of low computational efficiency and slow convergence of traditional particle filter, an adaptive particle filter myocardial fiber reconstruction algorithm based on diffusion anisotropy is proposed. This algorithm dynamically adjusts the number of particles and the disturbance intensity at the prediction stage according to the diffusion anisotropy values at different body elements. While ensuring the quality of state estimation, the computational complexity of the algorithm is reduced and the operating efficiency of the system is significantly improved. The experimental results show that the proposed method has strong anti-noise ability. While improving the accuracy of fiber reconstruction, the computational cost of the system decreases by 50%, which significantly improves the efficiency of the system. The proposed algorithm is good over traditional PF and STL approaches.
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Affiliation(s)
- Jun Yin
- Institute of Physical Education and Training, Capital University of Physical Education and Sports, China
| | - Xuan Gao
- School of Kinesiology and Health, Capital University of Physical Education and Sports, China
| | - Min Wu
- School of Sport and Health, Guangzhou Sport University, China
| | - Yan Liang
- School of Kinesiology and Health, Capital University of Physical Education and Sports, China
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15
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Simchick G, Geng R, Zhang Y, Hernando D. b value and first-order motion moment optimized data acquisition for repeatable quantitative intravoxel incoherent motion DWI. Magn Reson Med 2022; 87:2724-2740. [PMID: 35092092 DOI: 10.1002/mrm.29165] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 01/03/2022] [Accepted: 01/04/2022] [Indexed: 12/12/2022]
Abstract
PURPOSE To design a b value and first-order motion moment (M1 ) optimized data acquisition for repeatable intravoxel incoherent motion (IVIM) quantification in the liver. METHODS Cramer-Rao lower bound optimization was performed to determine optimal monopolar and optimal 2D samplings of the b-M1 space based on noise performance. Monte Carlo simulations were used to evaluate the bias and variability in estimates obtained using the proposed optimal samplings and conventional monopolar sampling. Diffusion MRI of the liver was performed in 10 volunteers using 3 IVIM acquisitions: conventional monopolar, optimized monopolar, and b-M1 -optimized gradient waveforms (designed based on the optimal 2D sampling). IVIM parameter maps of diffusion coefficient, perfusion fraction, and blood velocity SD were obtained using nonlinear least squares fitting. Noise performance (SDs), stability (outlier percentage), and test-retest or scan-rescan repeatability (intraclass correlation coefficients) were evaluated and compared across acquisitions. RESULTS Cramer-Rao lower bound and Monte Carlo simulations demonstrated improved noise performance of the optimal 2D sampling in comparison to monopolar samplings. Evaluating the designed b-M1 -optimized waveforms in healthy volunteers, significant decreases (p < 0.05) in the SDs and outlier percentages were observed for measurements of diffusion coefficient, perfusion fraction, and blood velocity SD in comparison to measurements obtained using monopolar samplings. Good-to-excellent repeatability (intraclass correlation coefficients ≥ 0.77) was observed for all 3 parameters in both the right and left liver lobes using the b-M1 -optimized waveforms. CONCLUSIONS 2D b-M1 -optimized data acquisition enables repeatable IVIM quantification with improved noise performance. 2D acquisitions may advance the establishment of IVIM quantitative biomarkers for liver diseases.
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Affiliation(s)
- Gregory Simchick
- Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Ruiqi Geng
- Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Yuxin Zhang
- Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Diego Hernando
- Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
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16
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McTavish S, Van AT, Peeters JM, Weiss K, Makowski MR, Braren RF, Karampinos DC. Gradient nonlinearity correction in liver DWI using motion-compensated diffusion encoding waveforms. MAGMA (NEW YORK, N.Y.) 2022; 35:827-841. [PMID: 34894335 PMCID: PMC9463296 DOI: 10.1007/s10334-021-00981-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 11/25/2021] [Accepted: 11/26/2021] [Indexed: 12/29/2022]
Abstract
OBJECTIVE : To experimentally characterize the effectiveness of a gradient nonlinearity correction method in removing ADC bias for different motion-compensated diffusion encoding waveforms. METHODS The diffusion encoding waveforms used were the standard monopolar Stejskal-Tanner pulsed gradient spin echo (pgse) waveform, the symmetric bipolar velocity-compensated waveform (sym-vc), the asymmetric bipolar velocity-compensated waveform (asym-vc) and the asymmetric bipolar partial velocity-compensated waveform (asym-pvc). The effectiveness of the gradient nonlinearity correction method using the spherical harmonic expansion of the gradient coil field was tested with the aforementioned waveforms in a phantom and in four healthy subjects. RESULTS The gradient nonlinearity correction method reduced the ADC bias in the phantom experiments for all used waveforms. The range of the ADC values over a distance of ± 67.2 mm from isocenter reduced from 1.29 × 10-4 to 0.32 × 10-4 mm2/s for pgse, 1.04 × 10-4 to 0.22 × 10-4 mm2/s for sym-vc, 1.22 × 10-4 to 0.24 × 10-4 mm2/s for asym-vc and 1.07 × 10-4 to 0.11 × 10-4 mm2/s for asym-pvc. The in vivo results showed that ADC overestimation due to motion or bright vessels can be increased even further by the gradient nonlinearity correction. CONCLUSION The investigated gradient nonlinearity correction method can be used effectively with various motion-compensated diffusion encoding waveforms. In coronal liver DWI, ADC errors caused by motion and residual vessel signal can be increased even further by the gradient nonlinearity correction.
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Affiliation(s)
- Sean McTavish
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Anh T. Van
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | | | | | - Marcus R. Makowski
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Rickmer F. Braren
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Dimitrios C. Karampinos
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
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17
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Gadjimuradov F, Benkert T, Nickel MD, Maier A. Robust partial Fourier reconstruction for diffusion-weighted imaging using a recurrent convolutional neural network. Magn Reson Med 2021; 87:2018-2033. [PMID: 34841550 DOI: 10.1002/mrm.29100] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 10/21/2021] [Accepted: 11/07/2021] [Indexed: 12/12/2022]
Abstract
PURPOSE To develop an algorithm for robust partial Fourier (PF) reconstruction applicable to diffusion-weighted (DW) images with non-smooth phase variations. METHODS Based on an unrolled proximal splitting algorithm, a neural network architecture is derived, which alternates between data consistency operations and regularization implemented by recurrent convolutions. In order to exploit correlations, multiple repetitions of the same slice are jointly reconstructed under consideration of permutation-equivariance. The algorithm is trained on DW liver data of 60 volunteers and evaluated on retrospectively and prospectively subsampled data of different anatomies and resolutions. RESULTS The proposed method is able to significantly outperform conventional PF techniques on retrospectively subsampled data in terms of quantitative measures as well as perceptual image quality. In this context, joint reconstruction of repetitions as well as the particular type of recurrent network unrolling are found to be beneficial with respect to reconstruction quality. On prospectively PF-sampled data, the proposed method enables DW imaging with higher signal without sacrificing image resolution or introducing additional artifacts. Alternatively, it can be used to counter the TE increase in acquisitions with higher resolution. Furthermore, generalizability can be shown to prospective brain data exhibiting anatomies and contrasts not present in the training set. CONCLUSION This work demonstrates that robust PF reconstruction of DW data is feasible even at strong PF factors in anatomies prone to phase variations. Since the proposed method does not rely on smoothness priors of the phase but uses learned recurrent convolutions instead, artifacts of conventional PF methods can be avoided.
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Affiliation(s)
- Fasil Gadjimuradov
- Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany.,Magnetic Resonance Applications Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Thomas Benkert
- Magnetic Resonance Applications Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Marcel Dominik Nickel
- Magnetic Resonance Applications Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Andreas Maier
- Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
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18
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Hernando D, Zhang Y, Pirasteh A. Quantitative diffusion MRI of the abdomen and pelvis. Med Phys 2021; 49:2774-2793. [PMID: 34554579 DOI: 10.1002/mp.15246] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2021] [Revised: 08/05/2021] [Accepted: 09/15/2021] [Indexed: 12/14/2022] Open
Abstract
Diffusion MRI has enormous potential and utility in the evaluation of various abdominal and pelvic disease processes including cancer and noncancer imaging of the liver, prostate, and other organs. Quantitative diffusion MRI is based on acquisitions with multiple diffusion encodings followed by quantitative mapping of diffusion parameters that are sensitive to tissue microstructure. Compared to qualitative diffusion-weighted MRI, quantitative diffusion MRI can improve standardization of tissue characterization as needed for disease detection, staging, and treatment monitoring. However, similar to many other quantitative MRI methods, diffusion MRI faces multiple challenges including acquisition artifacts, signal modeling limitations, and biological variability. In abdominal and pelvic diffusion MRI, technical acquisition challenges include physiologic motion (respiratory, peristaltic, and pulsatile), image distortions, and low signal-to-noise ratio. If unaddressed, these challenges lead to poor technical performance (bias and precision) and clinical outcomes of quantitative diffusion MRI. Emerging and novel technical developments seek to address these challenges and may enable reliable quantitative diffusion MRI of the abdomen and pelvis. Through systematic validation in phantoms, volunteers, and patients, including multicenter studies to assess reproducibility, these emerging techniques may finally demonstrate the potential of quantitative diffusion MRI for abdominal and pelvic imaging applications.
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Affiliation(s)
- Diego Hernando
- Departments of Radiology and Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Yuxin Zhang
- Departments of Radiology and Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Ali Pirasteh
- Departments of Radiology and Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
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19
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Geng R, Zhang Y, Starekova J, Rutkowski DR, Estkowski L, Roldán-Alzate A, Hernando D. Characterization and correction of cardiovascular motion artifacts in diffusion-weighted imaging of the pancreas. Magn Reson Med 2021; 86:1956-1969. [PMID: 34142375 DOI: 10.1002/mrm.28846] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Revised: 04/23/2021] [Accepted: 04/26/2021] [Indexed: 02/01/2023]
Abstract
PURPOSE To assess the effects of cardiovascular-induced motion on conventional DWI of the pancreas and to evaluate motion-robust DWI methods in a motion phantom and healthy volunteers. METHODS 3T DWI was acquired using standard monopolar and motion-compensated gradient waveforms, including in an anatomically accurate pancreas phantom with controllable compressive motion and healthy volunteers (n = 8, 10). In volunteers, highly controlled single-slice DWI using breath-holding and cardiac gating and whole-pancreas respiratory-triggered DWI were acquired. For each acquisition, the ADC variability across volunteers, as well as ADC differences across parts of the pancreas were evaluated. RESULTS In motion phantom scans, conventional DWI led to biased ADC, whereas motion-compensated waveforms produced consistent ADC. In the breath-held, cardiac-triggered study, conventional DWI led to heterogeneous DW signals and highly variable ADC across the pancreas, whereas motion-compensated DWI avoided these artifacts. In the respiratory-triggered study, conventional DWI produced heterogeneous ADC across the pancreas (head: 1756 ± 173 × 10-6 mm2 /s; body: 1530 ± 338 × 10-6 mm2 /s; tail: 1388 ± 267 × 10-6 mm2 /s), with ADCs in the head significantly higher than in the tail (P < .05). Motion-compensated ADC had lower variability across volunteers (head: 1277 ± 102 × 10-6 mm2 /s; body: 1204 ± 169 × 10-6 mm2 /s; tail: 1235 ± 178 × 10-6 mm2 /s), with no significant difference (P ≥ .19) across the pancreas. CONCLUSION Cardiovascular motion introduces artifacts and ADC bias in pancreas DWI, which are addressed by motion-robust DWI.
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Affiliation(s)
- Ruiqi Geng
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Yuxin Zhang
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Jitka Starekova
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - David R Rutkowski
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Mechanical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | | | - Alejandro Roldán-Alzate
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Mechanical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Diego Hernando
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
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20
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Middione MJ, Loecher M, Moulin K, Ennis DB. Optimization methods for magnetic resonance imaging gradient waveform design. NMR IN BIOMEDICINE 2020; 33:e4308. [PMID: 32342560 PMCID: PMC7606655 DOI: 10.1002/nbm.4308] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Revised: 02/07/2020] [Accepted: 03/13/2020] [Indexed: 06/11/2023]
Abstract
The development and implementation of novel MRI pulse sequences remains challenging and laborious. Gradient waveforms are typically designed using a combination of analytical and ad hoc methods to construct each gradient waveform axis independently. This strategy makes coding the pulse sequence complicated, in addition to being time inefficient. As a consequence, nearly all commercial MRI pulse sequences fail to maximize use of the available gradient hardware or efficiently mitigate physiological effects. This results in expensive MRI systems that underperform relative to their inherent hardware capabilities. To address this problem, a software solution is proposed that incorporates numerical optimization methods into MRI pulse sequence programming. Examples are shown for rotational variant vs. invariant waveform designs, acceleration nulled velocity encoding gradients, and mitigation of peripheral nerve stimulation for diffusion encoding. The application of optimization methods to MRI pulse sequence design incorporates gradient hardware limits and the prescribed MRI protocol parameters (e.g. field-of-view, resolution, gradient moments, and/or b-value) to simultaneously construct time-optimal gradient waveforms. In many cases, the resulting constrained gradient waveform design problem is convex and can be solved on-the-fly on the MRI scanner. The result is a set of multi-axis time-optimal gradient waveforms that satisfy the design constraints, thereby increasing SNR-efficiency. These optimization methods can also be used to mitigate imaging artifacts (e.g. eddy currents) or account for peripheral nerve stimulation. The result of the optimization method is to enable easier pulse sequence gradient waveform design and permit on-the-fly implementation for a range of MRI pulse sequences.
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Affiliation(s)
| | - Michael Loecher
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Kévin Moulin
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Daniel B. Ennis
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Radiology, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
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Riexinger A, Laun FB, Bickelhaupt S, Seuß H, Uder M, Hensel B, Saake M. On the dependence of the cardiac motion artifact on the breathing cycle in liver diffusion-weighted imaging. PLoS One 2020; 15:e0239743. [PMID: 33002028 PMCID: PMC7529231 DOI: 10.1371/journal.pone.0239743] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 09/11/2020] [Indexed: 12/17/2022] Open
Abstract
Purpose The purpose of this study was to investigate whether the cardiac motion artifact that regularly appears in diffusion-weighted imaging of the left liver lobe might be reduced by acquiring images in inspiration, when the coupling between heart and liver might be minimal. Materials and methods 43 patients with known or suspected focal liver lesions were examined at 1.5 T with breath hold acquisition, once in inspiration and once in expiration. Data were acquired with a diffusion-weighted echo planar imaging sequence and two b-values (b50 = 50 s/mm² and b800 = 800 s/mm²). The severity of the cardiac motion artifact in the left liver lobe was rated by two experienced radiologists for both b-values with a 5 point Likert scale. Additionally, the normalized signal S(b800)/S(b50) in the left liver lobe was computed. The Wilcoxon signed-rank test was used comparing the scores of the two readers obtained in inspiration and expiration, and to compare the normalized signal in inspiration and expiration. Results The normalized signal in inspiration was slightly higher than in expiration (0.349±0.077 vs 0.336±0.058), which would indicate a slight reduction of the cardiac motion artifact, but this difference was not significant (p = 0.24). In the qualitative evaluation, the readers did not observe a significant difference for b50 (reader 1: p = 0.61; reader 2: p = 0.18). For b800, reader 1 observed a significant difference of small effect size favouring expiration (p = 0.03 with a difference of mean Likert scores of 0.27), while reader 2 observed no significant difference (p = 0.62). Conclusion Acquiring the data in inspiration does not lead to a markedly reduced cardiac motion artifact in diffusion-weighted imaging of the left liver lobe and is in this regard not to be preferred over acquiring the data in expiration.
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Affiliation(s)
- Andreas Riexinger
- Institute of Radiology, University Hospital Erlangen, Erlangen, Germany
- * E-mail:
| | | | | | - Hannes Seuß
- Institute of Radiology, University Hospital Erlangen, Erlangen, Germany
| | - Michael Uder
- Institute of Radiology, University Hospital Erlangen, Erlangen, Germany
| | - Bernhard Hensel
- Center for Medical Physics and Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Marc Saake
- Institute of Radiology, University Hospital Erlangen, Erlangen, Germany
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Brunsing RL, Fowler KJ, Yokoo T, Cunha GM, Sirlin CB, Marks RM. Alternative approach of hepatocellular carcinoma surveillance: abbreviated MRI. HEPATOMA RESEARCH 2020; 6:59. [PMID: 33381651 PMCID: PMC7771881 DOI: 10.20517/2394-5079.2020.50] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
This review focuses on emerging abbreviated magnetic resonance imaging (AMRI) surveillance of patients with chronic liver disease for hepatocellular carcinoma (HCC). This surveillance strategy has been proposed as a high-sensitivity alternative to ultrasound for identification of patients with early-stage HCC, particularly in patients with cirrhosis or obesity, in whom sonographic visualization of small tumors may be compromised. Three general AMRI approaches have been developed and studied in the literature - non-contrast AMRI, dynamic contrast-enhanced AMRI, and hepatobiliary phase contrast-enhanced AMRI - each comprising a small number of selected sequences specifically tailored for HCC detection. The rationale, general technique, advantages and disadvantages, and diagnostic performance of each AMRI approach is explained. Additionally, current gaps in knowledge and future directions are discussed. Based on emerging evidence, we cautiously recommend the use of AMRI for HCC surveillance in situations where ultrasound is compromised.
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Affiliation(s)
- Ryan L. Brunsing
- Department of Radiology, Stanford University, Stanford, CA 94305, USA
| | - Kathryn J. Fowler
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA 92093, USA
| | - Takeshi Yokoo
- Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Guilherme Moura Cunha
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA 92093, USA
| | - Claude B. Sirlin
- Liver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA 92093, USA
| | - Robert M. Marks
- Department of Radiology, Naval Medical Center San Diego, San Diego, CA 92134, USA
- Department of Radiology, Uniformed Services University of the Health Sciences, Bethesda, MD 20892, USA
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Chen X, Zhu A, Du YP. Center‐out EPI (COEPI): A fast single‐shot imaging technique with a short TE. Magn Reson Med 2020; 84:787-799. [DOI: 10.1002/mrm.28175] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Revised: 12/03/2019] [Accepted: 12/27/2019] [Indexed: 12/20/2022]
Affiliation(s)
- Xudong Chen
- School of Biomedical Engineering Shanghai Jiao Tong University Shanghai People's Republic of China
| | - Ante Zhu
- College of Biomedical Engineering and Instrument Science Zhejiang University Hangzhou Zhejiang People's Republic of China
- Departments of Biomedical Engineering University of Wisconsin Madison Wisconsin
- Departments of Radiology University of Wisconsin Madison Wisconsin
| | - Yiping P. Du
- School of Biomedical Engineering Shanghai Jiao Tong University Shanghai People's Republic of China
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Rauh SS, Riexinger AJ, Ohlmeyer S, Hammon M, Saake M, Stemmer A, Uder M, Hensel B, Laun FB. A mixed waveform protocol for reduction of the cardiac motion artifact in black-blood diffusion-weighted imaging of the liver. Magn Reson Imaging 2020; 67:59-68. [PMID: 31923466 DOI: 10.1016/j.mri.2019.12.011] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 12/11/2019] [Accepted: 12/31/2019] [Indexed: 02/06/2023]
Abstract
OBJECTIVE Diffusion-weighted imaging (DWI) in the liver suffers from signal loss due to the cardiac motion artifact, especially in the left liver lobe. The purpose of this work was to improve the image quality of liver DWI in terms of cardiac motion artifact reduction and achievement of black-blood images in low b-value images. MATERIAL AND METHODS Ten healthy volunteers (age 20-31 years) underwent MRI examinations at 1.5 T with a prototype DWI sequence provided by the vendor. Two diffusion encodings (i.e. waveforms), monopolar and flow-compensated, and the b-values 0, 20, 50, 100, 150, 600 and 800 s/mm2 were used. Two Likert scales describing the severity of the pulsation artifact and the quality of the black-blood state were defined and evaluated by two experienced radiologists. Regions of interest (ROIs) were manually drawn in the right and left liver lobe in each slice and combined to a volume of interest (VOI). The mean and coefficient of variation were calculated for each normalized VOI-averaged signal to assess the severity of the cardiac motion artifact. The ADC was calculated using two b-values once for the monopolar data and once with mixed data, using the monopolar data for the small and the flow-compensated data for the high b-value. A Wilcoxon rank sum test was used to compare the Likert scores obtained for monopolar and flow-compensated data. RESULTS At b-values from 20 to 150 s/mm2, unlike the flow-compensated diffusion encoding, the monopolar encoding yielded black blood in all images with a negligible signal loss due to the cardiac motion artifact. At the b-values 600 and 800 s/mm2, the flow-compensated encoding resulted in a significantly reduced cardiac motion artifact, especially in the left liver lobe, and in a black-blood state. The ADC calculated with monopolar data was significantly higher in the left than in the right liver lobe. CONCLUSION It is recommendable to use the following mixed waveform protocol: Monopolar diffusion encodings at small b-values and flow-compensated diffusion encodings at high b-values.
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Affiliation(s)
- Susanne S Rauh
- Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands; Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
| | - Andreas J Riexinger
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Sabine Ohlmeyer
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Matthias Hammon
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Marc Saake
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | | | - Michael Uder
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Bernhard Hensel
- Center for Medical Physics and Engineering, Friedrich-Alexander-Universität Erlangen-, Nürnberg, (FAU), Erlangen, Germany
| | - Frederik B Laun
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
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