Evaluation of Multiparametric Magnetic Resonance Imaging in Detection and Prediction of Prostate Cancer
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{"title"=>"Evaluation of multiparametric magnetic resonance imaging in detection and prediction of prostate cancer", "type"=>"journal", "authors"=>[{"first_name"=>"Rui", "last_name"=>"Wang", "scopus_author_id"=>"56710708600"}, {"first_name"=>"He", "last_name"=>"Wang", "scopus_author_id"=>"56048913500"}, {"first_name"=>"Chenglin", "last_name"=>"Zhao", "scopus_author_id"=>"56710772700"}, {"first_name"=>"Juan", "last_name"=>"Hu", "scopus_author_id"=>"56663431700"}, {"first_name"=>"Yuanyuan", "last_name"=>"Jiang", "scopus_author_id"=>"55784216800"}, {"first_name"=>"Yanjun", "last_name"=>"Tong", "scopus_author_id"=>"14120488800"}, {"first_name"=>"Ting", "last_name"=>"Liu", "scopus_author_id"=>"56710742200"}, {"first_name"=>"Rong", "last_name"=>"Huang", "scopus_author_id"=>"55216155100"}, {"first_name"=>"Xiaoying", "last_name"=>"Wang", "scopus_author_id"=>"36063233400"}], "year"=>2015, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "sgr"=>"84935429823", "doi"=>"10.1371/journal.pone.0130207", "pmid"=>"26067423", "scopus"=>"2-s2.0-84935429823", "pui"=>"605092375"}, "id"=>"fac22c59-0ae6-357c-b77d-1e4913348814", "abstract"=>"BACKGROUND: Although European Society of Urogenital Radiology proposed the potential of multiparametric magnetic resonance imaging (MP-MRI) as a tool in the diagnostic pathway for prostate cancer (PCa) and published a unified scoring system named Prostate Imaging Reporting and Data System (PI-RADS version 1), these still need to be validated by real-life studies. OBJECTIVE: To evaluate the role of MP-MRI in detection and prediction of PCa. METHODS: Patients with clinical suspicion of PCa who underwent prebiopsy MP-MRI from 2002 to 2009 were recruited. MP-MRI results were retrospectively assigned as overall scores using PI-RADS by two radiologists. Patients were followed and the end point was the diagnosis of PCa. Receiver operating characteristics (ROC) curve was performed to test diagnostic efficacy of MP-MRI, under results of biopsy within three months. The cox proportional hazards model was used to identify independent variables for the detection of PCa. RESULTS: Finally, 1113 of the 1806 enrolled patients were included for analysis. The median follow-up was 56.0 months (1-137 mo). For 582 patients biopsied within three months, area under the curve for the detection of PCa with MP-MRI was 0.88 (95% confidence interval [CI], 0.75-1.00) in group of baseline prostate specific antigen (PSA) 0.01-4.00 ng/ml (n = 31), 0.90 (95% CI, 0.84-0.95) in PSA 4.01-10.00 ng/ml (n = 142), and 0.91 (95% CI, 0.87-0.94) in PSA >10.00 ng/ml (n = 409), respectively. In the cox model adjusted for age and baseline PSA level, for the detection rate of PCa, compared with PI-RADS 1-2 (reference), the hazard ratio was 6.43 (95% CI, 4.29-9.65) for PI-RADS 3, 18.58 (95% CI, 13.36-25.84) for PI-RADS 4-5 (p < 0.001). CONCLUSIONS: Prebiopsy MP-MRI with PI-RADS is demonstrated as a valuable diagnostic and predictive tool for PCa.", "link"=>"http://www.mendeley.com/research/evaluation-multiparametric-magnetic-resonance-imaging-detection-prediction-prostate-cancer", "reader_count"=>15, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>1, "Student > Doctoral Student"=>1, "Researcher"=>1, "Student > Ph. D. Student"=>1, "Student > Postgraduate"=>1, "Other"=>2, "Student > Master"=>2, "Student > Bachelor"=>2, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>1, "Student > Doctoral Student"=>1, "Researcher"=>1, "Student > Ph. D. Student"=>1, "Student > Postgraduate"=>1, "Other"=>2, "Student > Master"=>2, "Student > Bachelor"=>2, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>2}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Unspecified"=>3, "Medicine and Dentistry"=>10, "Computer Science"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>10}, "Computer Science"=>{"Computer Science"=>1}, "Unspecified"=>{"Unspecified"=>3}}, "group_count"=>1}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/2108669"], "description"=>"<p>PCa: prostate cancer; MP-MRI: multiparametric magnetic resonance imaging.</p>", "links"=>[], "tags"=>["Cox model", "roc", "end point", "Urogenital Radiology", "pca", "582 patients biopsied", "Prostate Cancer BackgroundAlthough", "ci", "baseline PSA level", "Prostate cancer", "baseline prostate", "resonance imaging", "Prostate Imaging Reporting", "hazards model", "data system", "Hazard ratio", "detection rate"], "article_id"=>1447588, "categories"=>["Biological Sciences"], "users"=>["Rui Wang", "He Wang", "Chenglin Zhao", "Juan Hu", "Yuanyuan Jiang", "Yanjun Tong", "Ting Liu", "Rong Huang", "Xiaoying Wang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0130207.g001", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Inclusion_and_Exclusion_Criteria_for_Patients_Included_in_Data_Analysis_/1447588", "title"=>"Inclusion and Exclusion Criteria for Patients Included in Data Analysis.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-12 03:04:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/2108670"], "description"=>"<p>PCa: prostate cancer; TURP: transurethral resection of the prostate; PSA: prostate specific antigen.</p>", "links"=>[], "tags"=>["Cox model", "roc", "end point", "Urogenital Radiology", "pca", "582 patients biopsied", "Prostate Cancer BackgroundAlthough", "ci", "baseline PSA level", "Prostate cancer", "baseline prostate", "resonance imaging", "Prostate Imaging Reporting", "hazards model", "data system", "Hazard ratio", "detection rate"], "article_id"=>1447589, "categories"=>["Biological Sciences"], "users"=>["Rui Wang", "He Wang", "Chenglin Zhao", "Juan Hu", "Yuanyuan Jiang", "Yanjun Tong", "Ting Liu", "Rong Huang", "Xiaoying Wang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0130207.g002", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Final_Diagnosis_and_the_Diagnosis_Evidence_of_the_Cohort_/1447589", "title"=>"Final Diagnosis and the Diagnosis Evidence of the Cohort.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-12 03:04:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/2108678"], "description"=>"<p>PCa: prostate cancer; MR-MRI: multiparametric magnetic resonance imaging; PI-RADS: prostate imaging reporting and data system. PSA: prostate specific antigen.</p>", "links"=>[], "tags"=>["Cox model", "roc", "end point", "Urogenital Radiology", "pca", "582 patients biopsied", "Prostate Cancer BackgroundAlthough", "ci", "baseline PSA level", "Prostate cancer", "baseline prostate", "resonance imaging", "Prostate Imaging Reporting", "hazards model", "data system", "Hazard ratio", "detection rate"], "article_id"=>1447591, "categories"=>["Biological Sciences"], "users"=>["Rui Wang", "He Wang", "Chenglin Zhao", "Juan Hu", "Yuanyuan Jiang", "Yanjun Tong", "Ting Liu", "Rong Huang", "Xiaoying Wang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0130207.g003", "stats"=>{"downloads"=>0, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Kaplan_Meier_Curves_of_Cumulative_Detection_Rate_of_PCa_with_MP_MRI_in_Groups_Stratified_by_PI_RADS_for_the_Entire_Cohort_Panel_3A_and_the_Cohort_Categorized_in_Different_Baseline_PSA_levels_Panel_3B_3D_/1447591", "title"=>"Kaplan-Meier Curves of Cumulative Detection Rate of PCa with MP-MRI in Groups Stratified by PI-RADS for the Entire Cohort (Panel 3A) and the Cohort Categorized in Different Baseline PSA levels (Panel 3B-3D).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-12 03:04:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/2108680"], "description"=>"<p>PI-RADS: Prostate Imaging Reporting and Data System; MR-MRI: multiparametric magnetic resonance imaging; PCa: prostate cancer.</p>", "links"=>[], "tags"=>["Cox model", "roc", "end point", "Urogenital Radiology", "pca", "582 patients biopsied", "Prostate Cancer BackgroundAlthough", "ci", "baseline PSA level", "Prostate cancer", "baseline prostate", "resonance imaging", "Prostate Imaging Reporting", "hazards model", "data system", "Hazard ratio", "detection rate"], "article_id"=>1447593, "categories"=>["Biological Sciences"], "users"=>["Rui Wang", "He Wang", "Chenglin Zhao", "Juan Hu", "Yuanyuan Jiang", "Yanjun Tong", "Ting Liu", "Rong Huang", "Xiaoying Wang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0130207.g004", "stats"=>{"downloads"=>5, "page_views"=>183, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Findings_of_patients_with_score_5_of_PI_RADS_during_follow_up_period_/1447593", "title"=>"Findings of patients with score 5 of PI-RADS during follow-up period.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-06-12 03:04:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/2108681"], "description"=>"<p>MP-MRI: multiparametric magnetic resonance imaging; MR: magnetic resonance; T2WI: T2-weighted imaging; DWI: diffusion-weighted imaging; DCEI: dynamic contrast enhanced imaging; MRS: magnetic resonance spectroscopy.</p><p>* Signa Twinspeed; GE Medical System, Milwaukee, Wis. Used with a 8-channel pelvic phased array coil and an endorectal coil.</p><p>** An intravenous injection of 0.1 mmol/kg of gadopentetic acid dimeglumine salt injection (Bayer Schering Pharma, Germany) was performed at 2.0 ml/sec, with saline flush of 15ml.</p><p>*** Three-dimensional MRS was performed using the Point Resolved Selective Spectroscopy sequence.</p><p>MP-MRI Parameters at 1.5 T.</p>", "links"=>[], "tags"=>["Cox model", "roc", "end point", "Urogenital Radiology", "pca", "582 patients biopsied", "Prostate Cancer BackgroundAlthough", "ci", "baseline PSA level", "Prostate cancer", "baseline prostate", "resonance imaging", "Prostate Imaging Reporting", "hazards model", "data system", "Hazard ratio", "detection rate"], "article_id"=>1447594, "categories"=>["Biological Sciences"], "users"=>["Rui Wang", "He Wang", "Chenglin Zhao", "Juan Hu", "Yuanyuan Jiang", "Yanjun Tong", "Ting Liu", "Rong Huang", "Xiaoying Wang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0130207.t001", "stats"=>{"downloads"=>0, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_MP_MRI_Parameters_at_1_5_T_/1447594", "title"=>"MP-MRI Parameters at 1.5 T.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-06-12 03:04:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/2108682"], "description"=>"<p>PSA: prostate specific antigen.</p><p>Baseline Characteristics and Biopsy Results Categorized in Different Baseline PSA Levels.</p>", "links"=>[], "tags"=>["Cox model", "roc", "end point", "Urogenital Radiology", "pca", "582 patients biopsied", "Prostate Cancer BackgroundAlthough", "ci", "baseline PSA level", "Prostate cancer", "baseline prostate", "resonance imaging", "Prostate Imaging Reporting", "hazards model", "data system", "Hazard ratio", "detection rate"], "article_id"=>1447595, "categories"=>["Biological Sciences"], "users"=>["Rui Wang", "He Wang", "Chenglin Zhao", "Juan Hu", "Yuanyuan Jiang", "Yanjun Tong", "Ting Liu", "Rong Huang", "Xiaoying Wang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0130207.t002", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Baseline_Characteristics_and_Biopsy_Results_Categorized_in_Different_Baseline_PSA_Levels_/1447595", "title"=>"Baseline Characteristics and Biopsy Results Categorized in Different Baseline PSA Levels.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-06-12 03:04:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/2108683"], "description"=>"<p>MP-MRI: multiparametric magnetic resonance imaging; PI-RADS: Prostate Imaging Reporting and Data System; PSA: prostate specific antigen; AUC: areas under the curve; ROC: receiver operating characteristic; CI: confidence interval; PPV: positive predictive value; NPV: negative predictive value.</p><p>Diagnostic Performance of MP-MRI with PI-RADS.</p>", "links"=>[], "tags"=>["Cox model", "roc", "end point", "Urogenital Radiology", "pca", "582 patients biopsied", "Prostate Cancer BackgroundAlthough", "ci", "baseline PSA level", "Prostate cancer", "baseline prostate", "resonance imaging", "Prostate Imaging Reporting", "hazards model", "data system", "Hazard ratio", "detection rate"], "article_id"=>1447596, "categories"=>["Biological Sciences"], "users"=>["Rui Wang", "He Wang", "Chenglin Zhao", "Juan Hu", "Yuanyuan Jiang", "Yanjun Tong", "Ting Liu", "Rong Huang", "Xiaoying Wang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0130207.t004", "stats"=>{"downloads"=>3, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Diagnostic_Performance_of_MP_MRI_with_PI_RADS_/1447596", "title"=>"Diagnostic Performance of MP-MRI with PI-RADS.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-06-12 03:04:24"}

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Relative Metric

{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}
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