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1.
Magn Reson Med ; 88(5): 2208-2216, 2022 11.
Article in English | MEDLINE | ID: mdl-35877783

ABSTRACT

PURPOSE: Although many methods have been proposed to quantitatively map the main MRI parameters (e.g., T1 , T2 , C × M0 ), these methods often involve special sequences not readily available on clinical scanners and/or may require long scan times. In contrast, the proposed method can readily run on most scanners, offer flexible tradeoffs between scan time and image quality, and map MRI parameters jointly to ensure spatial alignment. METHODS: The approach is based on the multi-shot spin-echo (SE) EPI sequence. The corresponding signal equation was derived and strategies for solving it were developed. As usual with multi-shot EPI, scan time can readily be traded-off against image quality by adjusting the echo train length. Validation was performed against reference relaxometry methods, in gel phantoms with varying concentrations of gadobutrol and gadoterate meglumine contrast agents. In vivo examples are further presented, from 3 neuroradiology patients. RESULTS: Bland-Altman analysis was performed: for T2 , as compared to 2D SE, bias was 0.29 ms and the 95% limits of agreement ranged from -1.15 to +1.73 ms. For T1 , compared to inversion-recovery SE (and MOLLI), bias was -20.2 ms (and -14.5 ms) and the limits of agreement ranged from -62.4 to +22.0 ms (and -53.8 to +24.9 ms). The mean relative T1 error between the proposed method and each of the 2 reference methods was similar to that of the reference methods among themselves. CONCLUSION: In the constellation of existing relaxometry methods, the proposed method is meant to stand out in terms of its practicality and availability.


Subject(s)
Magnetic Resonance Imaging , Humans , Magnetic Resonance Imaging/methods , Phantoms, Imaging , Reproducibility of Results
2.
Invest Radiol ; 54(4): 238-246, 2019 04.
Article in English | MEDLINE | ID: mdl-30601292

ABSTRACT

PURPOSE: The aim of this study was to improve the geometric fidelity and spatial resolution of multi-b diffusion-weighted magnetic resonance imaging of the prostate. MATERIALS AND METHODS: An accelerated segmented diffusion imaging sequence was developed and evaluated in 25 patients undergoing multiparametric magnetic resonance imaging examinations of the prostate. A reduced field of view was acquired using an endorectal coil. The number of sampled diffusion weightings, or b-factors, was increased to allow estimation of tissue perfusion based on the intravoxel incoherent motion (IVIM) model. Apparent diffusion coefficients measured with the proposed segmented method were compared with those obtained with conventional single-shot echo-planar imaging (EPI). RESULTS: Compared with single-shot EPI, the segmented method resulted in faster acquisition with 2-fold improvement in spatial resolution and a greater than 3-fold improvement in geometric fidelity. Apparent diffusion coefficient values measured with the novel sequence demonstrated excellent agreement with those obtained from the conventional scan (R = 0.91 for bmax = 500 s/mm and R = 0.89 for bmax = 1400 s/mm). The IVIM perfusion fraction was 4.0% ± 2.7% for normal peripheral zone, 6.6% ± 3.6% for normal transition zone, and 4.4% ± 2.9% for suspected tumor lesions. CONCLUSIONS: The proposed accelerated segmented prostate diffusion imaging sequence achieved improvements in both spatial resolution and geometric fidelity, along with concurrent quantification of IVIM perfusion.


Subject(s)
Diffusion Magnetic Resonance Imaging/methods , Image Interpretation, Computer-Assisted/methods , Prostatic Neoplasms/diagnostic imaging , Aged , Humans , Male , Perfusion , Prostate/diagnostic imaging , Reproducibility of Results
3.
Magn Reson Med ; 77(2): 696-706, 2017 02.
Article in English | MEDLINE | ID: mdl-26899270

ABSTRACT

PURPOSE: High angular resolution diffusion imaging (HARDI) is a well-established method to help reveal the architecture of nerve bundles, but long scan times and geometric distortions inherent to echo planar imaging (EPI) have limited its integration into clinical protocols. METHODS: A fast imaging method is proposed here that combines accelerated multishot diffusion imaging (AMDI), multiplexed sensitivity encoding (MUSE), and crossing fiber angular resolution of intravoxel structure (CFARI) to reduce spatial distortions and reduce total scan time. A multishot EPI sequence was used to improve geometrical fidelity as compared to a single-shot EPI acquisition, and acceleration in both k-space and diffusion sampling enabled reductions in scan time. The method is regularized and self-navigated for motion correction. Seven volunteers were scanned in this study, including four with volumetric whole brain acquisitions. RESULTS: The average similarity of microstructural orientations between undersampled datasets and their fully sampled counterparts was above 85%, with scan times below 5 min for whole-brain acquisitions. Up to 2.7-fold scan time acceleration along with four-fold distortion reduction was achieved. CONCLUSION: The proposed imaging strategy can generate HARDI results with relatively good geometrical fidelity and low scan duration, which may help facilitate the transition of HARDI from a successful research tool to a practical clinical one. Magn Reson Med 77:696-706, 2017. © 2016 International Society for Magnetic Resonance in Medicine.


Subject(s)
Brain/diagnostic imaging , Diffusion Magnetic Resonance Imaging/methods , Image Processing, Computer-Assisted/methods , Algorithms , Data Compression/methods , Female , Humans , Male
4.
Magn Reson Med ; 78(3): 897-908, 2017 09.
Article in English | MEDLINE | ID: mdl-27739101

ABSTRACT

PURPOSE: To combine MRI, ultrasound, and computer science methodologies toward generating MRI contrast at the high frame rates of ultrasound, inside and even outside the MRI bore. METHODS: A small transducer, held onto the abdomen with an adhesive bandage, collected ultrasound signals during MRI. Based on these ultrasound signals and their correlations with MRI, a machine-learning algorithm created synthetic MR images at frame rates up to 100 per second. In one particular implementation, volunteers were taken out of the MRI bore with the ultrasound sensor still in place, and MR images were generated on the basis of ultrasound signal and learned correlations alone in a "scannerless" manner. RESULTS: Hybrid ultrasound-MRI data were acquired in eight separate imaging sessions. Locations of liver features, in synthetic images, were compared with those from acquired images: The mean error was 1.0 pixel (2.1 mm), with best case 0.4 and worst case 4.1 pixels (in the presence of heavy coughing). For results from outside the bore, qualitative validation involved optically tracked ultrasound imaging with/without coughing. CONCLUSION: The proposed setup can generate an accurate stream of high-speed MR images, up to 100 frames per second, inside or even outside the MR bore. Magn Reson Med 78:897-908, 2017. © 2016 International Society for Magnetic Resonance in Medicine.


Subject(s)
Image Processing, Computer-Assisted/methods , Magnetic Resonance Imaging/methods , Ultrasonography/methods , Algorithms , Equipment Design , Humans , Image Processing, Computer-Assisted/instrumentation , Liver/diagnostic imaging , Machine Learning , Movement/physiology , Transducers
5.
J Magn Reson Imaging ; 43(4): 843-52, 2016 Apr.
Article in English | MEDLINE | ID: mdl-26395366

ABSTRACT

PURPOSE: To assess whether measurements on American College of Radiology (ACR) phantom images performed by magnetic resonance imaging (MRI) technologists as part of a weekly quality control (QC) program could be performed exclusively using an automated system without compromising the integrity of the QC program. MATERIALS AND METHODS: ACR phantom images are acquired on 15 MRI scanners at a number of ACR-accredited sites to fulfill requirements of a weekly QC program. MRI technologists routinely perform several measurements on these images. Software routines are also used to perform the measurements. A set of geometry measurements made by technologists over a five week period and those made using software routines were compared to reference-standard measurements made by two MRI physicists. RESULTS: The geometry measurements performed by software routines had a very high positive correlation (0.92) with the reference-standard measurements. Technologist measurements also had a high positive correlation (0.63), although the correlation was less than for the automated measurements. Bland-Altman analysis revealed overall good agreement between the automated and reference-standard measurements, with the 95% limits of agreement being within ±0.62 mm. Agreement between the technologist and the reference-standard measurements was demonstratively poorer, with 95% limits of agreement being ±1.46 mm. Some of the technologist measurements differed from the reference standard by as much as 2 mm. CONCLUSION: The technologists' geometry measurements may be able to be replaced by automated measurement without compromising the weekly QC program required by the ACR.


Subject(s)
Image Processing, Computer-Assisted/methods , Magnetic Resonance Imaging/methods , Pattern Recognition, Automated , Phantoms, Imaging , Radiology/methods , Radiology/standards , Humans , Observer Variation , Quality Control , Reference Values , Signal-To-Noise Ratio , Software
6.
Med Image Comput Comput Assist Interv ; 9349: 315-322, 2015 Oct.
Article in English | MEDLINE | ID: mdl-27135063

ABSTRACT

Magnetic Resonance (MR) imaging provides excellent image quality at a high cost and low frame rate. Ultrasound (US) provides poor image quality at a low cost and high frame rate. We propose an instance-based learning system to obtain the best of both worlds: high quality MR images at high frame rates from a low cost single-element US sensor. Concurrent US and MRI pairs are acquired during a relatively brief offine learning phase involving the US transducer and MR scanner. High frame rate, high quality MR imaging of respiratory organ motion is then predicted from US measurements, even after stopping MRI acquisition, using a probabilistic kernel regression framework. Experimental results show predicted MR images to be highly representative of actual MR images.

7.
Magn Reson Med ; 72(2): 324-36, 2014 Aug.
Article in English | MEDLINE | ID: mdl-24006236

ABSTRACT

PURPOSE: To reduce image distortion in MR diffusion imaging using an accelerated multi-shot method. METHODS: The proposed method exploits the fact that diffusion-encoded data tend to be sparse when represented in the kb-kd space, where kb and kd are the Fourier transform duals of b and d, the b-factor and the diffusion direction, respectively. Aliasing artifacts are displaced toward under-used regions of the kb-kd plane, allowing nonaliased signals to be recovered. A main characteristic of the proposed approach is how thoroughly the navigator information gets used during reconstruction: The phase of navigator images is used for motion correction, while the magnitude of the navigator signal in kb-kd space is used for regularization purposes. As opposed to most acceleration methods based on compressed sensing, the proposed method reduces the number of ky lines needed for each diffusion-encoded image, but not the total number of images required. Consequently, it tends to be most effective at reducing image distortion rather than reducing total scan time. RESULTS: Results are presented for three volunteers with acceleration factors ranging from 4 to 8, with and without the inclusion of parallel imaging. CONCLUSION: An accelerated motion-corrected diffusion imaging method was introduced that achieves good image quality at relatively high acceleration factors.


Subject(s)
Algorithms , Artifacts , Brain/anatomy & histology , Diffusion Magnetic Resonance Imaging/methods , Image Enhancement/methods , Image Interpretation, Computer-Assisted/methods , Signal Processing, Computer-Assisted , Humans , Reproducibility of Results , Sensitivity and Specificity
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