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  Prostate Cancer

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Articles published in Invest Radiol

Retrieve available abstracts of 15 articles:
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Single Articles

    December 2023
  1. TENBERGEN CJA, Fortuin AS, van Asten JJA, Veltien A, et al
    The Potential of Iron Oxide Nanoparticle-Enhanced MRI at 7 T Compared With 3 T for Detecting Small Suspicious Lymph Nodes in Patients With Prostate Cancer.
    Invest Radiol. 2023 Dec 29. doi: 10.1097/RLI.0000000000001056.
    PubMed     Abstract available

    November 2023
  2. SCHILHAM MGM, Somford DM, Veltien A, Zamecnik P, et al
    Subnodal Correspondence of PSMA Expression and USPIO-MRI in Metastatic Pelvic Lymph Nodes in Prostate Cancer.
    Invest Radiol. 2023 Nov 17. doi: 10.1097/RLI.0000000000001046.
    PubMed     Abstract available

    October 2023
  3. LEMBERSKIY G, Chandarana H, Bruno M, Ginocchio LA, et al
    Feasibility of Accelerated Prostate Diffusion-Weighted Imaging on 0.55 T MRI Enabled With Random Matrix Theory Denoising.
    Invest Radiol. 2023;58:720-729.
    PubMed     Abstract available

    March 2023
  4. BISCHOFF LM, Katemann C, Isaak A, Mesropyan N, et al
    T2 Turbo Spin Echo With Compressed Sensing and Propeller Acquisition (Sampling k-Space by Utilizing Rotating Blades) for Fast and Motion Robust Prostate MRI: Comparison With Conventional Acquisition.
    Invest Radiol. 2023;58:209-215.
    PubMed     Abstract available

    December 2022
  5. AL-BOURINI O, Seif Amir Hosseini A, Giganti F, Balz J, et al
    T1 Mapping of the Prostate Using Single-Shot T1FLASH: A Clinical Feasibility Study to Optimize Prostate Cancer Assessment.
    Invest Radiol. 2022 Dec 8. doi: 10.1097/RLI.0000000000000945.
    PubMed     Abstract available

    October 2022
  6. LI Y, Gao S, Jiang H, Ayat N, et al
    Evaluation of Physicochemical Properties, Pharmacokinetics, Biodistribution, Toxicity, and Contrast-Enhanced Cancer MRI of a Cancer-Targeting Contrast Agent, MT218.
    Invest Radiol. 2022;57:639-654.
    PubMed     Abstract available

    April 2022
  7. ZHANG KS, Schelb P, Netzer N, Tavakoli AA, et al
    Pseudoprospective Paraclinical Interaction of Radiology Residents With a Deep Learning System for Prostate Cancer Detection: Experience, Performance, and Identification of the Need for Intermittent Recalibration.
    Invest Radiol. 2022 Apr 22. pii: 00004424-990000000-00010.
    PubMed     Abstract available

    December 2021
  8. NETZER N, Weisser C, Schelb P, Wang X, et al
    Fully Automatic Deep Learning in Bi-institutional Prostate Magnetic Resonance Imaging: Effects of Cohort Size and Heterogeneity.
    Invest Radiol. 2021;56:799-808.
    PubMed     Abstract available

    November 2021
  9. RACZECK P, Frenzel F, Woerner T, Graeber S, et al
    Noninferiority of Monoparametric MRI Versus Multiparametric MRI for the Detection of Prostate Cancer: Diagnostic Accuracy of ADC Ratios Based on Advanced "Zoomed" Diffusion-Weighted Imaging.
    Invest Radiol. 2021 Nov 4. pii: 00004424-900000000-98655.
    PubMed     Abstract available

    October 2021
  10. WINKEL DJ, Tong A, Lou B, Kamen A, et al
    A Novel Deep Learning Based Computer-Aided Diagnosis System Improves the Accuracy and Efficiency of Radiologists in Reading Biparametric Magnetic Resonance Images of the Prostate: Results of a Multireader, Multicase Study.
    Invest Radiol. 2021;56:605-613.
    PubMed     Abstract available

    September 2021
  11. BREIT HC, Block TK, Winkel DJ, Gehweiler JE, et al
    Revisiting DCE-MRI: Classification of Prostate Tissue Using Descriptive Signal Enhancement Features Derived From DCE-MRI Acquisition With High Spatiotemporal Resolution.
    Invest Radiol. 2021;56:553-562.
    PubMed     Abstract available

    July 2021
  12. KHALIGHINEJAD P, Parrott D, Jordan VC, Chirayil S, et al
    Magnetic Resonance Imaging Detection of Glucose-Stimulated Zinc Secretion in the Enlarged Dog Prostate as a Potential Method for Differentiating Prostate Cancer From Benign Prostatic Hyperplasia.
    Invest Radiol. 2021;56:450-457.
    PubMed     Abstract available

    May 2021
  13. LANGBEIN BJ, Szczepankiewicz F, Westin CF, Bay C, et al
    A Pilot Study of Multidimensional Diffusion MRI for Assessment of Tissue Heterogeneity in Prostate Cancer.
    Invest Radiol. 2021 May 27. pii: 00004424-900000000-98695.
    PubMed     Abstract available

    April 2021
  14. MAKOWSKI MR, Bressem KK, Franz L, Kader A, et al
    De Novo Radiomics Approach Using Image Augmentation and Features From T1 Mapping to Predict Gleason Scores in Prostate Cancer.
    Invest Radiol. 2021 Apr 22. doi: 10.1097/RLI.0000000000000788.
    PubMed     Abstract available

    February 2021
  15. TAVAKOLI AA, Kuder TA, Tichy D, Radtke JP, et al
    Measured Multipoint Ultra-High b-Value Diffusion MRI in the Assessment of MRI-Detected Prostate Lesions.
    Invest Radiol. 2021;56:94-102.
    PubMed     Abstract available

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