Literature DB >> 33687285

Tomoelastography Based on Multifrequency MR Elastography for Prostate Cancer Detection: Comparison with Multiparametric MRI.

Mengsi Li1, Jing Guo1, Ping Hu1, Huichuan Jiang1, Juan Chen1, Jiaxi Hu1, Patrick Asbach1, Ingolf Sack1, Wenzheng Li1.   

Abstract

Background Multiparametric MRI is used for depiction of prostate cancer (PCa) but without consideration of the mechanical alteration of prostatic tissue by cancer. Purpose To investigate the diagnostic performance of stiffness and fluidity quantified with tomoelastography, a multifrequency MR elastography technique, for depiction of PCa compared with multiparametric MRI with Prostate Imaging Reporting and Data System (PI-RADS) version 2.1. Materials and Methods Prospective participants suspected to have PCa and healthy controls (HCs) underwent multiparametric MRI and tomoelastography between March 2019 and July 2020. Tomoelastography maps of shear-wave speed (c) and loss angle (φ) quantified stiffness and fluidity, respectively, for PCa and benign prostatic disease and for the peripheral and transition zones in HCs. Differences between entities and regions were analyzed by using analysis of variance or Kruskal-Wallis test. Diagnostic performance was assessed with area under the receiver operating characteristic curve (AUC) analysis. Results There were 73 participants with PCa (mean age, 72 years ± 7 [standard deviation]), 82 with benign prostatic disease (66 years ± 7), and 53 HCs (41 years ± 14). Mean ± standard deviation of c and φ were higher in PCa (3.4 m/sec ± 0.6 and 1.3 radian ± 0.2, respectively) than in benign prostatic disease (2.6 m/sec ± 0.3 and 1.0 radian ± 0.2, respectively; P < .001) and age-matched HCs (2.2 m/sec ± 0.1 and 0.8 radian ± 0.1, respectively; P < .001). Incorporating c and φ (AUC, 0.95; 95% CI: 0.92, 0.98) improved the diagnostic performance of PI-RADS version 2.1 (AUC, 0.85; 95% CI: 0.80, 0.91; P < .001). Multiparametric MRI combined with c and φ enabled detection of PCa with 95% (78 of 82 non-PCa) specificity, which was significantly higher than with use of multiparametric MRI alone (77% [63 of 82 non-PCa]; P < .001). In regional analysis, c combined with φ enabled differentiation of transition zone PCa from benign prostatic hyperplasia (AUC, 0.91; 95% CI: 0.83, 0.98) and peripheral zone PCa from chronic prostatitis (AUC, 0.94; 95% CI: 0.88, 1.00). Conclusion Use of tomoelastography-quantified stiffness and fluidity improved the diagnostic performance of multiparametric MRI with Prostate Imaging Reporting and Data System version 2.1 in detecting cancer in both the peripheral and transition zones. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Hectors and Lewis in this issue. An earlier incorrect version of this article appeared online. This article was corrected on March 24, 2021.

Entities:  

Year:  2021        PMID: 33687285     DOI: 10.1148/radiol.2021201852

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  5 in total

Review 1.  Emerging MR methods for improved diagnosis of prostate cancer by multiparametric MRI.

Authors:  Durgesh Kumar Dwivedi; Naranamangalam R Jagannathan
Journal:  MAGMA       Date:  2022-07-22       Impact factor: 2.533

2.  Tomoelastography based on multifrequency MR elastography predicts liver function reserve in patients with hepatocellular carcinoma: a prospective study.

Authors:  Huimin Lin; Yihuan Wang; Jiahao Zhou; Yuchen Yang; Xinxin Xu; Di Ma; Yongjun Chen; Chunxue Yang; Ingolf Sack; Jing Guo; Ruokun Li; Fuhua Yan
Journal:  Insights Imaging       Date:  2022-06-03

3.  Rectal Tumor Stiffness Quantified by In Vivo Tomoelastography and Collagen Content Estimated by Histopathology Predict Tumor Aggressiveness.

Authors:  Jiaxi Hu; Jing Guo; Yigang Pei; Ping Hu; Mengsi Li; Ingolf Sack; Wenzheng Li
Journal:  Front Oncol       Date:  2021-08-13       Impact factor: 6.244

4.  Fully automated quantification of in vivo viscoelasticity of prostate zones using magnetic resonance elastography with Dense U-net segmentation.

Authors:  Nader Aldoj; Federico Biavati; Marc Dewey; Anja Hennemuth; Patrick Asbach; Ingolf Sack
Journal:  Sci Rep       Date:  2022-02-07       Impact factor: 4.996

5.  Whole tissue and single cell mechanics are correlated in human brain tumors.

Authors:  Frank Sauer; Anatol Fritsch; Steffen Grosser; Steve Pawlizak; Tobias Kießling; Martin Reiss-Zimmermann; Mehrgan Shahryari; Wolf C Müller; Karl-Titus Hoffmann; Josef A Käs; Ingolf Sack
Journal:  Soft Matter       Date:  2021-12-08       Impact factor: 4.046

  5 in total

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