Publications by Type: Journal Article

In Press
Madore B, Jerosch-Herold M, Chiou J-Y, Cheng C-C, Guenette JP, and Mihai GA. In Press. “A relaxometry method that emphasizes practicality and availability.” Magn Reson Med.
2022
Madore B, Belsley G, Cheng C-C, Preiswerk P, Foley Kijewski M, Wu P-H, Martell LB, Pluim JPW, Di Carli M, and Moore SC. 12/2022. “Ultrasound-based sensors for respiratory motion assessment in multimodality PET imaging.” Phys Med Biol, 19;67(2).
2021
Schiebler ML, Parraga G, Gefter WB, Madore B, Lee KS, Ohno Y, Kauczor HU, and Hatabu H. 12/2021. “Synopsis from expanding applications of pulmonary MRI in the clinical evaluation of lung disorders: Fleishner Society position paper.” Chest, 159, Pp. 492-5.
Madore B, Preiswerk F, Bredfeldt J, Zong S, and Cheng C-C. 12/2021. “Ultrasound-based sensors to monitor physiological motion.” Med Phys, 48, Pp. 3614-22.
2020
Cheng C-C, Preiswerk F, and Madore B. 12/31/2020. “Multi-pathway multi-echo acquisition and neural contrast translation to generate a variety of quantitative and qualitative image contrasts. Finalist in the 2020 ISMRM Young Investigators Rabi Award Competition.” Magn Reson Med, 83, Pp. 2310-21.
Hatabu H, Ohno Y, Gefter WB, Parraga G, Madore B, Lee KS, Altes TA, Lynch DA, Mayo JR, Seo JB, Wild JM, Beek van EJR, Schiebler ML, and Kauczor HU. 12/2020. “Expanding applications of pulmonary MRI in the clinical evaluation of lung disorders: Fleischner Society position paper.” Radiology, 297, Pp. 286-301.
Zong S, Mei C-S, and Madore B. 12/2020. “Improved PRF-based MR thermometry using k-space energy spectrum analysis.” Magn Reson Med, 84, Pp. 3325-32.
LP Panych, V Kimbrell, S Mukundan, and B Madore. 12/2020. “Magnetic Force Mapping and MRI Safety.” J Magn Reson Imag, 51, Pp. 1260-71.
2019
P Aksit Ciris, Jr-y Chiou, D Glazer, SH Zhang, TC Chao, CM Tempany-Afdhal, B Madore, and SE Maier. 12/2019. “Accelerated Segmented Diffusion-Weighted Prostate Imaging for Higher Resolution, Higher Geometric Fidelity, and Multi-b Perfusion Quantification.” Investigative Radiology, 54, Pp. 238-46.
SS Yengul, PE Barbone, and B Madore. 12/2019. “Dispersion in tissue-mimicking gels measured with shear wave elastography and torsional vibration rheometry.” Ultrasound in Medicine and Biology, 45, 2, Pp. 586-604.
Cheng-Chieh Cheng, W. Scott Hoge, Terry H Kuo, Frank Preiswerk, and Bruno Madore. 12/2019. “Multi-Pathway Multi-Echo (MPME) imaging: all main MR parameters mapped based on a single 3D scan.” Magn Reson Med, 81, 3, Pp. 1699-1713.
2018
Sanjay S Yengul, Paul E Barbone, and Bruno Madore. 12/2018. “Application of a forward model of axisymmetric shear wave propagation in viscoelastic media to shear wave elastography.” J Acoust Soc Am, 143, Pp. 3266-3277.Abstract
A simple but general solution of Navier's equation for axisymmetric shear wave propagation in a homogeneous isotropic viscoelastic medium is presented. It is well-suited for use as a forward model for some acoustic radiation force impulse based shear wave elastography applications because it does not require precise knowledge of the strength of the source, nor its spatial or temporal distribution. Instead, it depends on two assumptions: (1) the source distribution is axisymmetric and confined to a small region near the axis of symmetry, and (2) the propagation medium is isotropic and homogeneous. The model accounts for the vector polarization of shear waves and exactly represents geometric spreading of the shear wavefield, whether spherical, cylindrical, or neither. It makes no assumption about the frequency dependence of material parameters, i.e., it is material-model independent. Validation using measured shear wavefields excited by acoustic radiation force in a homogeneous gelatin sample show that the model accounts for well over 90% of the measured wavefield "energy." An optimal fit of the model to simulated shear wavefields with noise in a homogeneous viscoelastic medium enables estimation of both the shear storage modulus and shear wave attenuation to within 1%.
Lawrence P. Panych and Bruno Madore. 12/2018. “The physics of MRI safety.” J Mag Reson Imaging, 47, 1, Pp. 28-43.Abstract
The main risks associated with magnetic resonance imaging (MRI) have been extensively reported and studied; for example, everyday objects may turn into projectiles, energy deposition can cause burns, varying fields can induce nerve stimulation, and loud noises can lead to auditory loss. The present review article is geared toward providing intuition about the physical mechanisms that give rise to these risks. On the one hand, excellent literature already exists on the practical aspect of risk management, with clinical workflow and recommendations. On the other hand, excellent technical articles also exist that explain these risks from basic principles of electromagnetism. We felt that an underserved niche might be found between the two, ie, somewhere between basic science and practical advice, to help develop intuition about electromagnetism that might prove of practical value when working around MR scanners. Following a wide-ranging introduction, risks originating from the main magnetic field, the excitation RF electromagnetic field, and switching of the imaging gradients will be presented in turn.
2017
F Preiswerk, M Toews, C-C Cheng, Jr-y Chiou, C-S Mei, LF Schaefer, W. S. Hoge, B Schwartz, LP Panych, and B Madore. 12/31/2017. “Hybrid MRI ultrasound acquisitions, and scannerless real-time imaging. Finalist of the YIA Rabi Award, and recipient of a YIA Cum Laude Award.” Magn Reson Med, 78, Pp. 897-908.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, 2016. (c) 2016 International Society for Magnetic Resonance in Medicine.
P Aksit Ciris, C-C Cheng, C-S Mei, LP Panych, and B Madore. 12/2017. “Dual-Pathway sequences for MR thermometry: When and where to use them.” Magn Reson Med, 77, 3, Pp. 1193–1200.Abstract
PURPOSE: Dual-pathway sequences have been proposed to help improve the temperature-to-noise ratio (TNR) in MR thermometry. The present work establishes how much of an improvement these so-called "PSIF-FISP" sequences may bring in various organs and tissues. METHODS: Simulations and TNR calculations were validated against analytical equations, phantom, abdomen, and brain scans. Relative TNRs for PSIF-FISP, as compared to a dual-FISP reference standard, were calculated for flip angle (FA) = 1 to 85 º and repetition time (TR) = 6 to 60 ms, for gray matter, white matter, cervix, endometrium, myometrium, prostate, kidney medulla and cortex, bone marrow, pancreas, spleen, muscle, and liver tissues. RESULTS: PSIF-FISP was TNR superior in the kidney, pelvis, spleen, or gray matter at most tested TR and FA settings, and benefits increased at shorter TRs. PSIF-FISP was TNR superior in other tissues, e.g., liver, muscle, pancreas, for only short TR settings (20 ms or less). The TNR benefits of PSIF-FISP increased slightly with FA, and strongly with decreasing TR. Up to two- to three-fold reductions in TR with 20% TNR gains were achievable. In any given tissue, TNR performance is expected to further improve with heating, due to changes in relaxation rates. CONCLUSION: Dual-pathway PSIF-FISP can improve TNR and acquisition speed over standard gradient-recalled echo sequences, but optimal acquisition parameters are tissue dependent. Magn Reson Med 77:1193-1200, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
T-C Chao, Jr-y Chiou, SE Maier, and B Madore. 12/2017. “Fast diffusion imaging with high angular resolution.” Magn Reson Med, 77, 2, Pp. 696–706.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.
2016
C-C Cheng, C-S Mei, J Duryea, H-W Chung, T-C Chao, LP Panych, and B Madore. 12/2016. “Dual-pathway multi-echo sequence for simultaneous frequency and T2 mapping.” J Magn Reson, 265, Pp. 177-87.Abstract
PURPOSE: To present a dual-pathway multi-echo steady state sequence and reconstruction algorithm to capture T2, T2( *) and field map information. METHODS: Typically, pulse sequences based on spin echoes are needed for T2 mapping while gradient echoes are needed for field mapping, making it difficult to jointly acquire both types of information. A dual-pathway multi-echo pulse sequence is employed here to generate T2 and field maps from the same acquired data. The approach might be used, for example, to obtain both thermometry and tissue damage information during thermal therapies, or susceptibility and T2 information from a same head scan, or to generate bonus T2 maps during a knee scan. RESULTS: Quantitative T2, T2( *) and field maps were generated in gel phantoms, ex vivo bovine muscle, and twelve volunteers. T2 results were validated against a spin-echo reference standard: A linear regression based on ROI analysis in phantoms provided close agreement (slope/R(2)=0.99/0.998). A pixel-wise in vivo Bland-Altman analysis of R2=1/T2 showed a bias of 0.034 Hz (about 0.3%), as averaged over four volunteers. Ex vivo results, with and without motion, suggested that tissue damage detection based on T2 rather than temperature-dose measurements might prove more robust to motion. CONCLUSION: T2, T2( *) and field maps were obtained simultaneously, from the same datasets, in thermometry, susceptibility-weighted imaging and knee-imaging contexts.
J Duryea, C Cheng, LF Schaefer, S. Smith, and B Madore. 12/2016. “Integration of accelerated MRI and post-processing software: a promising method for studies of knee osteoarthritis.” Osteoarthritis CartilageOsteoarthritis Cartilage, 24, Pp. 1905-1909.Abstract
OBJECTIVE: Magnetic resonance imaging (MRI) is a widely used imaging modality for studies of knee osteoarthritis (OA). Compared to radiography, MRI offers exceptional soft tissue imaging and true three-dimensional (3D) visualization. However, MRI is expensive both due to the cost of acquisition and evaluation of the images. The goal of our study is to develop a new method to address the cost of MRI by combining innovative acquisition methods and automated post-processing software. METHODS: Ten healthy volunteers were scanned with three different MRI protocols: A standard 3D dual-echo steady state (DESS) pulse sequence, an accelerated DESS (DESSAcc), acquired at approximately half the time compared to DESS, and a multi-echo time DESS (DESSMTE), which is capable of producing measurements of T2 relaxation time. A software tool was used to measure cartilage volume. Accuracy was quantified by comparing DESS to DESSAcc and DESSMTE and precision was measured using repeat readings and acquisitions. T2 precision was determined using duplicate DESSMTE acquisitions. Intra-class correlation coefficients (ICCs), root-mean square standard deviation (RMSSD), and the coefficient of variation (CoV) were used to quantify accuracy and precision. RESULTS: The accuracies of DESSAcc and DESSMTE were CoV = 3.7% and CoV = 6.6% respectively, while precision was 3.8%, 3.0%, and 3.1% for DESS, DESSAcc and DESSMTE. T2 repositioning precision was 5.8%. CONCLUSION: The results demonstrate that accurate and precise quantification of cartilage volume is possible using a combination of substantially faster MRI acquisition and post-processing software. Precise measurements of cartilage T2 and volume can be made using the same acquisition.
2015
C-S Mei, R Chu, W. S. Hoge, LP Panych, and B Madore. 12/2015. “Accurate field mapping in the presence of B0 inhomogeneities, applied to MR thermometry.” Magn Reson Med, 73, 6, Pp. 2142–2151.Abstract
PURPOSE: To describe how B0 inhomogeneities can cause errors in proton resonance frequency (PRF) shift thermometry, and to correct for these errors. METHODS: With PRF thermometry, measured phase shifts are converted into temperature measurements through the use of a scaling factor proportional to the echo time, TE. However, B0 inhomogeneities can deform, spread, and translate MR echoes, potentially making the "true" echo time vary spatially within the imaged object and take on values that differ from the prescribed TE value. Acquisition and reconstruction methods able to avoid or correct for such errors are presented. RESULTS: Tests were performed in a gel phantom during sonication, and temperature measurements were made with proper shimming as well as with intentionally introduced B0 inhomogeneities. Errors caused by B0 inhomogeneities were observed, described, and corrected by the proposed methods. No statistical difference was found between the corrected results and the reference results obtained with proper shimming, while errors by more than 10% in temperature elevation were corrected for. The approach was also applied to an abdominal in vivo dataset. CONCLUSION: Field variations induce errors in measured field values, which can be detected and corrected. The approach was validated for a PRF thermometry application.
F Preiswerk, M Toews, W. S. Hoge, JG Chiou, LP Panych, WM Wells, and B Madore. 11/2015. “Hybrid Utrasound and MRI Acquisitions for High-Speed Imaging of Respiratory Organ Motion.” In: Navab N, Hornegger J, Wells W, Frangi A, editors. Medical Image Computing and Computer-Assisted Intervention – MICCAI: Springer International Publishing, Pp. 315-322.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.

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