Search results for: Shreyas S. Vasanawala

Items from 1 to 20 out of 81 results

article

Distortionless, free‐breathing, and respiratory resolved 3D diffusion weighted imaging of the abdomen

Philip K. Lee, Xuetong Zhou, Nan Wang, Ali B. Syed, more

Magnetic Resonance in Medicine > 92 > 2 > 586 - 604

Purpose Abdominal imaging is frequently performed with breath holds or respiratory triggering to reduce the effects of respiratory motion. Diffusion weighted sequences provide a useful clinical contrast but have prolonged scan times due to low signal‐to‐noise ratio (SNR), and cannot be completed in a single breath hold. Echo‐planar imaging (EPI) is the most commonly used trajectory for diffusion...

article

Motion‐compensated low‐rank reconstruction for simultaneous structural and functional UTE lung MRI

Fei Tan, Xucheng Zhu, Marilynn Chan, Matthew A. Zapala, more

Magnetic Resonance in Medicine > 90 > 3 > 1101 - 1113

Purpose Three‐dimensional UTE MRI has shown the ability to provide simultaneous structural and functional lung imaging, but it is limited by respiratory motion and relatively low lung parenchyma SNR. The purpose of this paper is to improve this imaging by using a respiratory phase‐resolved reconstruction approach, named motion‐compensated low‐rank reconstruction (MoCoLoR), which directly incorporates...

article

Editorial for “Gradual Self‐Training via Confidence and Volume Based Domain Adaptation for Multi Dataset Deep Learning‐Based Brain Metastases Detection Using Nonlocal Networks on MRI Images”

Feiyu Chen, Shreyas S. Vasanawala

Journal of Magnetic Resonance Imaging > 57 > 6 > 1741 - 1742

article

Accelerated two‐dimensional phase‐contrast for cardiovascular MRI using deep learning‐based reconstruction with complex difference estimation

Julio A. Oscanoa, Matthew J. Middione, Ali B. Syed, Christopher M. Sandino, more

Magnetic Resonance in Medicine > 89 > 1 > 356 - 369

Purpose To develop and validate a deep learning‐based reconstruction framework for highly accelerated two‐dimensional (2D) phase contrast (PC‐MRI) data with accurate and precise quantitative measurements. Methods We propose a modified DL‐ESPIRiT reconstruction framework for 2D PC‐MRI, comprised of an unrolled neural network architecture with a Complex Difference estimation (CD‐DL). CD‐DL was trained...

article

Improving high frequency image features of deep learning reconstructions via k‐space refinement with null‐space kernel

Kanghyun Ryu, Cagan Alkan, Shreyas S. Vasanawala

Magnetic Resonance in Medicine > 88 > 3 > 1263 - 1272

Purpose Deep learning (DL) based reconstruction using unrolled neural networks has shown great potential in accelerating MRI. However, one of the major drawbacks is the loss of high‐frequency details and textures in the output. The purpose of the study is to propose a novel refinement method that uses null‐space kernel to refine k‐space and improve blurred image details and textures. Methods The...

article

Volumetric and multispectral DWI near metallic implants using a non‐linear phase Carr‐Purcell‐Meiboom‐Gill diffusion preparation

Philip K. Lee, Daehyun Yoon, Jesse K. Sandberg, Shreyas S. Vasanawala, more

Magnetic Resonance in Medicine > 87 > 6 > 2650 - 2666

Purpose DWI near metal implants has not been widely explored due to substantial challenges associated with through‐slice and in‐plane distortions, the increased encoding requirement of different spectral bins, and limited SNR. There is no widely adopted clinical protocol for DWI near metal since the commonly used EPI trajectory fails completely due to distortion from extreme off‐resonance ranging...

article

Prospective Deployment of Deep Learning in MRI: A Framework for Important Considerations, Challenges, and Recommendations for Best Practices

Akshay S. Chaudhari, Christopher M. Sandino, Elizabeth K. Cole, David B. Larson, more

Journal of Magnetic Resonance Imaging > 54 > 2 > 357 - 371

Artificial intelligence algorithms based on principles of deep learning (DL) have made a large impact on the acquisition, reconstruction, and interpretation of MRI data. Despite the large number of retrospective studies using DL, there are fewer applications of DL in the clinic on a routine basis. To address this large translational gap, we review the recent publications to determine three major...

article

Quantification of the Hemodynamic Changes of Cirrhosis with Free‐Breathing Self‐Navigated MRI

Ryan L. Brunsing, Dustin Brown, Hashem Almahoud, Yuko Kono, more

Journal of Magnetic Resonance Imaging > 53 > 5 > 1410 - 1421

Background Non‐invasive assessment of the hemodynamic changes of cirrhosis might help guide management of patients with liver disease but are currently limited. Purpose To determine whether free‐breathing 4D flow MRI can be used to quantify the hemodynamic effects of cirrhosis and introduce hydraulic circuit indexes of severity. Study Type Retrospective. Population Forty‐seven patients including...

article

Free‐breathing $R_{2}^{*}$ mapping of hepatic iron overload in children using 3D multi‐echo UTE cones MRI

Youngwook Kee, Christopher M. Sandino, Ali B. Syed, Joseph Y. Cheng, more

Magnetic Resonance in Medicine > 85 > 5 > 2608 - 2621

Purpose To enable motion‐robust, ungated, free‐breathing

R_{2}^{*}

mapping of hepatic iron overload in children with 3D multi‐echo UTE cones MRI. Methods A golden‐ratio re‐ordered 3D multi‐echo UTE cones acquisition was developed with chemical‐shift encoding (CSE). Multi‐echo complex‐valued source images were reconstructed via gridding and coil combination, followed by confounder‐corrected

R_{2}^{*}

(=1/

T_{2}

...

article

Rosette Trajectories Enable Ungated, Motion‐Robust, Simultaneous Cardiac and Liver T₂* Iron Assessment

Adam M. Bush, Christopher M. Sandino, Shreya Ramachandran, Frank Ong, more

Journal of Magnetic Resonance Imaging > 52 > 6 > 1688 - 1698

Background Quantitative T₂* MRI is the standard of care for the assessment of iron overload. However, patient motion corrupts T₂* estimates. Purpose To develop and evaluate a motion‐robust, simultaneous cardiac and liver T₂* imaging approach using non‐Cartesian, rosette sampling and a model‐based reconstruction as compared to clinical‐standard Cartesian MRI. Study Type Prospective. Phantom/Population...

article

Accelerating cardiac cine MRI using a deep learning‐based ESPIRiT reconstruction

Christopher M. Sandino, Peng Lai, Shreyas S. Vasanawala, Joseph Y. Cheng

Magnetic Resonance in Medicine > 85 > 1 > 152 - 167

Purpose To propose a novel combined parallel imaging and deep learning‐based reconstruction framework for robust reconstruction of highly accelerated 2D cardiac cine MRI data. Methods We propose DL‐ESPIRiT, an unrolled neural network architecture that utilizes an extended coil sensitivity model to address SENSE‐related field‐of‐view (FOV) limitations in previously proposed deep learning‐based reconstruction...

article

Extreme MRI: Large‐scale volumetric dynamic imaging from continuous non‐gated acquisitions

Frank Ong, Xucheng Zhu, Joseph Y. Cheng, Kevin M. Johnson, more

Magnetic Resonance in Medicine > 84 > 4 > 1763 - 1780

Purpose To develop a framework to reconstruct large‐scale volumetric dynamic MRI from rapid continuous and non‐gated acquisitions, with applications to pulmonary and dynamic contrast‐enhanced (DCE) imaging. Theory and Methods The problem considered here requires recovering 100 gigabytes of dynamic volumetric image data from a few gigabytes of k‐space data, acquired continuously over several minutes...

article

Data‐driven self‐calibration and reconstruction for non‐cartesian wave‐encoded single‐shot fast spin echo using deep learning

Feiyu Chen, Joseph Y. Cheng, Valentina Taviani, Vipul R. Sheth, more

Journal of Magnetic Resonance Imaging > 51 > 3 > 841 - 853

Background Current self‐calibration and reconstruction methods for wave‐encoded single‐shot fast spin echo imaging (SSFSE) requires long computational time, especially when high accuracy is needed. Purpose To develop and investigate the clinical feasibility of data‐driven self‐calibration and reconstruction of wave‐encoded SSFSE imaging for computation time reduction and quality improvement. ...

article

Deep residual network for off‐resonance artifact correction with application to pediatric body MRA with 3D cones

David Y. Zeng, Jamil Shaikh, Signy Holmes, Ryan L. Brunsing, more

Magnetic Resonance in Medicine > 82 > 4 > 1398 - 1411

Purpose To enable rapid imaging with a scan time–efficient 3D cones trajectory with a deep‐learning off‐resonance artifact correction technique. Methods A residual convolutional neural network to correct off‐resonance artifacts (Off‐ResNet) was trained with a prospective study of pediatric MRA exams. Each exam acquired a short readout scan (1.18 ms ± 0.38) and a long readout scan (3.35 ms ± 0.74)...

article

Targeted rapid knee MRI exam using T₂ shuffling

Jonathan I. Tamir, Valentina Taviani, Marcus T. Alley, Becki C. Perkins, more

Journal of Magnetic Resonance Imaging > 49 > 7 > e195 - e204

Background MRI is commonly used to evaluate pediatric musculoskeletal pathologies, but same‐day/near‐term scheduling and short exams remain challenges. Purpose To investigate the feasibility of a targeted rapid pediatric knee MRI exam, with the goal of reducing cost and enabling same‐day MRI access. Study Type A cost effectiveness study done prospectively. Subjects Forty‐seven pediatric patients...

article

Evaluation of the routine use of pelvic MRI in women presenting with symptomatic uterine fibroids: When is pelvic MRI useful?

Kim‐Nhien Vu, Angela M. Fast, Robyn K. Shaffer, Jarrett Rosenberg, more

Journal of Magnetic Resonance Imaging > 49 > 7 > e271 - e281

Background Pelvic ultrasound (US) diagnosis of uterine fibroids may overlook coexisting gynecological conditions that contribute to women's symptoms. Purpose To determine the added value of pelvic MRI for women diagnosed with symptomatic fibroids by US, and to identify clinical factors associated with additional MRI findings. Study Type Retrospective observational study. Population In all,...

article

View‐Sharing Artifact Reduction With Retrospective Compressed Sensing Reconstruction in the Context of Contrast‐Enhanced Liver MRI for Hepatocellular Carcinoma (HCC) Screening

Jamil Shaikh, Paul B. Stoddard, Evan G. Levine, Albert T. Roh, more

Journal of Magnetic Resonance Imaging > 49 > 4 > 984 - 993

Background View‐sharing (VS) increases spatiotemporal resolution in dynamic contrast‐enhanced (DCE) MRI by sharing high‐frequency k‐space data across temporal phases. This temporal sharing results in respiratory motion within any phase to propagate artifacts across all shared phases. Compressed sensing (CS) eliminates the need for VS by recovering missing k‐space data from pseudorandom undersampling,...

article

Motion‐robust reconstruction of multishot diffusion‐weighted images without phase estimation through locally low‐rank regularization

Yuxin Hu, Evan G. Levine, Qiyuan Tian, Catherine J. Moran, more

Magnetic Resonance in Medicine > 81 > 2 > 1181 - 1190

Purpose The goal of this work is to propose a motion robust reconstruction method for diffusion‐weighted MRI that resolves shot‐to‐shot phase mismatches without using phase estimation. Methods Assuming that shot‐to‐shot phase variations are slowly varying, spatial‐shot matrices can be formed using a local group of pixels to form columns, in which each column is from a different shot (excitation)...

article

4D flow MRI quantification of mitral and tricuspid regurgitation: Reproducibility and consistency relative to conventional MRI

Jennifer F. Feneis, Espoir Kyubwa, Kimberly Atianzar, Joseph Y. Cheng, more

Journal of Magnetic Resonance Imaging > 48 > 4 > 1147 - 1158

Background In patients with mitral or tricuspid valve regurgitation, evaluation of regurgitant severity is essential for determining the need for surgery. While transthoracic echocardiography is widely accessible, it has limited reproducibility for grading inlet valve regurgitation. Multiplanar cardiac MRI is the quantitative standard but requires specialized local expertise, and is thus not widely...

article

Conical ultrashort echo time (UTE) MRI in the evaluation of pediatric acute appendicitis

Albert T. Roh, Zhibo Xiao, Joseph Y. Cheng, Shreyas S. Vasanawala, more

Abdominal Radiology > 2019 > 44 > 1 > 22-30

Purpose Magnetic resonance imaging (MRI) sequences with conical k-space trajectories are able to decrease motion artifacts while achieving ultrashort echo times (UTE). We assessed the performance of free-breathing conical UTE MRI in the evaluation of the pediatric pelvis for suspected appendicitis. Methods Our retrospective review of 84 pediatric patients who underwent MRI for suspected appendicitis...

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INFONA - science communication portal

Search results for: Shreyas S. Vasanawala

Distortionless, free‐breathing, and respiratory resolved 3D diffusion weighted imaging of the abdomen

Motion‐compensated low‐rank reconstruction for simultaneous structural and functional UTE lung MRI

Editorial for “Gradual Self‐Training via Confidence and Volume Based Domain Adaptation for Multi Dataset Deep Learning‐Based Brain Metastases Detection Using Nonlocal Networks on MRI Images”

Accelerated two‐dimensional phase‐contrast for cardiovascular MRI using deep learning‐based reconstruction with complex difference estimation

Improving high frequency image features of deep learning reconstructions via k‐space refinement with null‐space kernel

Volumetric and multispectral DWI near metallic implants using a non‐linear phase Carr‐Purcell‐Meiboom‐Gill diffusion preparation

Prospective Deployment of Deep Learning in MRI: A Framework for Important Considerations, Challenges, and Recommendations for Best Practices

Quantification of the Hemodynamic Changes of Cirrhosis with Free‐Breathing Self‐Navigated MRI

Free‐breathing $R_{2}^{*}$ mapping of hepatic iron overload in children using 3D multi‐echo UTE cones MRI

Rosette Trajectories Enable Ungated, Motion‐Robust, Simultaneous Cardiac and Liver T₂* Iron Assessment

Accelerating cardiac cine MRI using a deep learning‐based ESPIRiT reconstruction

Extreme MRI: Large‐scale volumetric dynamic imaging from continuous non‐gated acquisitions

Data‐driven self‐calibration and reconstruction for non‐cartesian wave‐encoded single‐shot fast spin echo using deep learning

Deep residual network for off‐resonance artifact correction with application to pediatric body MRA with 3D cones

Targeted rapid knee MRI exam using T₂ shuffling

Evaluation of the routine use of pelvic MRI in women presenting with symptomatic uterine fibroids: When is pelvic MRI useful?

View‐Sharing Artifact Reduction With Retrospective Compressed Sensing Reconstruction in the Context of Contrast‐Enhanced Liver MRI for Hepatocellular Carcinoma (HCC) Screening

Motion‐robust reconstruction of multishot diffusion‐weighted images without phase estimation through locally low‐rank regularization

4D flow MRI quantification of mitral and tricuspid regurgitation: Reproducibility and consistency relative to conventional MRI

Conical ultrashort echo time (UTE) MRI in the evaluation of pediatric acute appendicitis

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