Minimum Field Strength Simulator for Proton Density Weighted MRI
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{"title"=>"Minimum field strength simulator for proton density weighted MRI", "type"=>"journal", "authors"=>[{"first_name"=>"Ziyue", "last_name"=>"Wu", "scopus_author_id"=>"55758949800"}, {"first_name"=>"Weiyi", "last_name"=>"Chen", "scopus_author_id"=>"57040174200"}, {"first_name"=>"Krishna S.", "last_name"=>"Nayak", "scopus_author_id"=>"7006611436"}], "year"=>2016, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"610342453", "issn"=>"19326203", "doi"=>"10.1371/journal.pone.0154711", "scopus"=>"2-s2.0-84966699063", "pmid"=>"27136334", "sgr"=>"84966699063"}, "id"=>"470530c4-f613-3124-8594-b7da9ab31eda", "abstract"=>"OBJECTIVE To develop and evaluate a framework for simulating low-field proton-density weighted MRI acquisitions based on high-field acquisitions, which could be used to predict the minimum B0 field strength requirements for MRI techniques. This framework would be particularly useful in the evaluation of de-noising and constrained reconstruction techniques. MATERIALS AND METHODS Given MRI raw data, lower field MRI acquisitions can be simulated based on the signal and noise scaling with field strength. Certain assumptions are imposed for the simulation and their validity is discussed. A validation experiment was performed using a standard resolution phantom imaged at 0.35 T, 1.5 T, 3 T, and 7 T. This framework was then applied to two sample proton-density weighted MRI applications that demonstrated estimation of minimum field strength requirements: real-time upper airway imaging and liver proton-density fat fraction measurement. RESULTS The phantom experiment showed good agreement between simulated and measured images. The SNR difference between simulated and measured was ≤ 8% for the 1.5T, 3T, and 7T cases which utilized scanners with the same geometry and from the same vendor. The measured SNR at 0.35T was 1.8- to 2.5-fold less than predicted likely due to unaccounted differences in the RF receive chain. The predicted minimum field strength requirements for the two sample applications were 0.2 T and 0.3 T, respectively. CONCLUSIONS Under certain assumptions, low-field MRI acquisitions can be simulated from high-field MRI data. This enables prediction of the minimum field strength requirements for a broad range of MRI techniques.", "link"=>"http://www.mendeley.com/research/minimum-field-strength-simulator-proton-density-weighted-mri", "reader_count"=>11, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>1, "Librarian"=>1, "Student > Doctoral Student"=>2, "Researcher"=>1, "Student > Ph. D. Student"=>3, "Student > Bachelor"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>1, "Librarian"=>1, "Student > Doctoral Student"=>2, "Researcher"=>1, "Student > Ph. D. Student"=>3, "Student > Bachelor"=>1}, "reader_count_by_subject_area"=>{"Engineering"=>4, "Unspecified"=>2, "Materials Science"=>1, "Medicine and Dentistry"=>1, "Physics and Astronomy"=>1, "Social Sciences"=>1, "Computer Science"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>4}, "Materials Science"=>{"Materials Science"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Social Sciences"=>{"Social Sciences"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Computer Science"=>{"Computer Science"=>1}, "Unspecified"=>{"Unspecified"=>2}}, "reader_count_by_country"=>{"United States"=>1}, "group_count"=>1}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/5042341"], "description"=>"<p>Assumptions for Low Field Acquisition.</p>", "links"=>[], "tags"=>["MRI techniques", "RF", "SNR", "1.5 T", "7 T cases", "Minimum Field Strength Simulator", "B 0 field strength requirements", "field strength requirements", "3 T", "Proton Density Weighted MRI Objective", "0.35 T", "field MRI acquisitions"], "article_id"=>3211969, "categories"=>["Biophysics", "Physical Sciences not elsewhere classified", "Cell Biology", "Biotechnology", "Developmental Biology", "Plant Biology"], "users"=>["Ziyue Wu", "Weiyi Chen", "Krishna S. Nayak"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0154711.t001", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Assumptions_for_Low_Field_Acquisition_/3211969", "title"=>"Assumptions for Low Field Acquisition.", "pos_in_sequence"=>6, "defined_type"=>3, "published_date"=>"2016-05-02 08:19:09"}
  • {"files"=>["https://ndownloader.figshare.com/files/5042242"], "description"=>"<div><p>Objective</p><p>To develop and evaluate a framework for simulating low-field proton-density weighted MRI acquisitions based on high-field acquisitions, which could be used to predict the minimum B<sub>0</sub> field strength requirements for MRI techniques. This framework would be particularly useful in the evaluation of de-noising and constrained reconstruction techniques.</p><p>Materials and Methods</p><p>Given MRI raw data, lower field MRI acquisitions can be simulated based on the signal and noise scaling with field strength. Certain assumptions are imposed for the simulation and their validity is discussed. A validation experiment was performed using a standard resolution phantom imaged at 0.35 T, 1.5 T, 3 T, and 7 T. This framework was then applied to two sample proton-density weighted MRI applications that demonstrated estimation of minimum field strength requirements: real-time upper airway imaging and liver proton-density fat fraction measurement.</p><p>Results</p><p>The phantom experiment showed good agreement between simulated and measured images. The SNR difference between simulated and measured was ≤ 8% for the 1.5T, 3T, and 7T cases which utilized scanners with the same geometry and from the same vendor. The measured SNR at 0.35T was 1.8- to 2.5-fold less than predicted likely due to unaccounted differences in the RF receive chain. The predicted minimum field strength requirements for the two sample applications were 0.2 T and 0.3 T, respectively.</p><p>Conclusions</p><p>Under certain assumptions, low-field MRI acquisitions can be simulated from high-field MRI data. This enables prediction of the minimum field strength requirements for a broad range of MRI techniques.</p></div>", "links"=>[], "tags"=>["MRI techniques", "RF", "SNR", "1.5 T", "7 T cases", "Minimum Field Strength Simulator", "B 0 field strength requirements", "field strength requirements", "3 T", "Proton Density Weighted MRI Objective", "0.35 T", "field MRI acquisitions"], "article_id"=>3211891, "categories"=>["Biophysics", "Physical Sciences not elsewhere classified", "Cell Biology", "Biotechnology", "Developmental Biology", "Plant Biology"], "users"=>["Ziyue Wu", "Weiyi Chen", "Krishna S. Nayak"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0154711", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Minimum_Field_Strength_Simulator_for_Proton_Density_Weighted_MRI/3211891", "title"=>"Minimum Field Strength Simulator for Proton Density Weighted MRI", "pos_in_sequence"=>1, "defined_type"=>2, "published_date"=>"2016-05-02 08:19:09"}
  • {"files"=>["https://ndownloader.figshare.com/files/5042251"], "description"=>"<p>High-field k-space data <i>y</i><sub><i>h</i></sub> and pure noise <i>n</i><sub><i>h</i></sub> are first acquired and served as input. <i>y</i><sub><i>h</i></sub> is then scaled by <i>a</i><sup>2</sup> and <i>f</i> to account for signal magnitude change and different relaxation behaviors at different field strengths. <i>f</i> can be determined based on steady state signal equations for different types of sequences (see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0154711#sec023\" target=\"_blank\">Appendix</a> for details). To simulate low-field data additional noise , as calculated in the text, is added to compensate for the different noise levels.</p>", "links"=>[], "tags"=>["MRI techniques", "RF", "SNR", "1.5 T", "7 T cases", "Minimum Field Strength Simulator", "B 0 field strength requirements", "field strength requirements", "3 T", "Proton Density Weighted MRI Objective", "0.35 T", "field MRI acquisitions"], "article_id"=>3211900, "categories"=>["Biophysics", "Physical Sciences not elsewhere classified", "Cell Biology", "Biotechnology", "Developmental Biology", "Plant Biology"], "users"=>["Ziyue Wu", "Weiyi Chen", "Krishna S. Nayak"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0154711.g001", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Simulation_of_Low-field_k-Space_Data_/3211900", "title"=>"Simulation of Low-field k-Space Data.", "pos_in_sequence"=>2, "defined_type"=>1, "published_date"=>"2016-05-02 08:19:09"}
  • {"files"=>["https://ndownloader.figshare.com/files/5042296"], "description"=>"<p>a) Gridding reconstruction for data acquired at 3 T & simulated at low field strengths. Two temporal frames are shown: one with the airway partially collapsed (top row) and one with it open (second row). Notice the strong noise that makes the airways gradually unidentifiable as field strength goes down. b) The same frames using CG-SENSE with temporal finite difference sparsity constraint. c) Airways segmented from images using reconstructions in b) are used to calculate the average DICE coefficients over 100 temporal frames (3 breaths) at different field strengths. 3T images are served as references. Fifty independent simulations were performed at each field strength. Error bars correspond to 95% confidence intervals.</p>", "links"=>[], "tags"=>["MRI techniques", "RF", "SNR", "1.5 T", "7 T cases", "Minimum Field Strength Simulator", "B 0 field strength requirements", "field strength requirements", "3 T", "Proton Density Weighted MRI Objective", "0.35 T", "field MRI acquisitions"], "article_id"=>3211933, "categories"=>["Biophysics", "Physical Sciences not elsewhere classified", "Cell Biology", "Biotechnology", "Developmental Biology", "Plant Biology"], "users"=>["Ziyue Wu", "Weiyi Chen", "Krishna S. Nayak"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0154711.g003", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Application_to_Upper_Airway_Compliance_Measurement_/3211933", "title"=>"Application to Upper Airway Compliance Measurement.", "pos_in_sequence"=>4, "defined_type"=>1, "published_date"=>"2016-05-02 08:19:09"}
  • {"files"=>["https://ndownloader.figshare.com/files/5042278"], "description"=>"<p>The acquired 0.35T/1.5T/3T/7T images and simulated images from data acquired at 3T and 7T respectively are listed for comparison. Measured SNR values are shown below each image. For simulated images, the mean and standard deviation of SNR of twenty different simulations were used. Contrast was adjusted for better noise visualization.</p>", "links"=>[], "tags"=>["MRI techniques", "RF", "SNR", "1.5 T", "7 T cases", "Minimum Field Strength Simulator", "B 0 field strength requirements", "field strength requirements", "3 T", "Proton Density Weighted MRI Objective", "0.35 T", "field MRI acquisitions"], "article_id"=>3211918, "categories"=>["Biophysics", "Physical Sciences not elsewhere classified", "Cell Biology", "Biotechnology", "Developmental Biology", "Plant Biology"], "users"=>["Ziyue Wu", "Weiyi Chen", "Krishna S. Nayak"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0154711.g002", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Phantom_Validations_of_Simulated_SNR_Change_/3211918", "title"=>"Phantom Validations of Simulated SNR Change.", "pos_in_sequence"=>3, "defined_type"=>1, "published_date"=>"2016-05-02 08:19:09"}
  • {"files"=>["https://ndownloader.figshare.com/files/5042320"], "description"=>"<p>a) Fat-water separated images reconstructed from data acquired at 3 T and simulated at low fields. Top row: water only; middle: fat only; bottom: proton-density fat fractions. b) The mean and standard deviation of fat fraction in the ROI at different field strengths. Fifty independent simulations were performed at each field strength.</p>", "links"=>[], "tags"=>["MRI techniques", "RF", "SNR", "1.5 T", "7 T cases", "Minimum Field Strength Simulator", "B 0 field strength requirements", "field strength requirements", "3 T", "Proton Density Weighted MRI Objective", "0.35 T", "field MRI acquisitions"], "article_id"=>3211951, "categories"=>["Biophysics", "Physical Sciences not elsewhere classified", "Cell Biology", "Biotechnology", "Developmental Biology", "Plant Biology"], "users"=>["Ziyue Wu", "Weiyi Chen", "Krishna S. Nayak"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0154711.g004", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Application_to_Abdominal_Fat-Water_Separated_Imaging_/3211951", "title"=>"Application to Abdominal Fat-Water Separated Imaging.", "pos_in_sequence"=>5, "defined_type"=>1, "published_date"=>"2016-05-02 08:19:09"}

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Relative Metric

{"start_date"=>"2016-01-01T00:00:00Z", "end_date"=>"2016-12-31T00:00:00Z", "subject_areas"=>[]}
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