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@ARTICLE{Tavakoli:181233,
      author       = {A. A. Tavakoli$^*$ and T. Hielscher and P. Badura$^*$ and
                      M. Görtz and T. A. Kuder$^*$ and R. Gnirs$^*$ and C. Schwab
                      and M. Hohenfellner and H.-P. Schlemmer$^*$ and D. Bonekamp},
      title        = {{C}ontribution of {D}ynamic {C}ontrast-enhanced and
                      {D}iffusion {MRI} to {PI}-{RADS} for {D}etecting
                      {C}linically {S}ignificant {P}rostate {C}ancer.},
      journal      = {Radiology},
      volume       = {306},
      number       = {1},
      issn         = {0033-8419},
      address      = {Oak Brook, Ill.},
      publisher    = {Soc.},
      reportid     = {DKFZ-2022-01879},
      pages        = {186-199},
      year         = {2023},
      note         = {#EA:E010#LA:E010# / 2023 Jan;306(1):186-199},
      abstract     = {Background Prostate Imaging Reporting and Data System
                      (PI-RADS) version 2.0 requires multiparametric MRI of the
                      prostate, including diffusion-weighted imaging (DWI) and
                      dynamic contrast-enhanced (DCE) imaging sequences; however,
                      the contribution of DCE imaging remains unclear. Purpose To
                      assess whether DCE imaging in addition to apparent diffusion
                      coefficient (ADC) and normalized T2 values improves PI-RADS
                      version 2.0 for prediction of clinically significant
                      prostate cancer (csPCa). Materials and Methods In this
                      retrospective study, clinically reported PI-RADS lesions in
                      consecutive men who underwent 3-T multiparametric MRI
                      (T2-weighted, DWI, and DCE MRI) from May 2015 to September
                      2016 were analyzed quantitatively and compared with
                      systematic and targeted MRI-transrectal US fusion biopsy.
                      The normalized T2 signal (nT2), ADC measurement, mean
                      early-phase DCE signal (mDCE), and heuristic DCE parameters
                      were calculated. Logistic regression analysis indicated the
                      most predictive DCE parameters for csPCa (Gleason grade
                      group ≥2). Receiver operating characteristic parameter
                      models were compared using the Obuchowski test. Recursive
                      partitioning analysis determined ADC and mDCE value ranges
                      for combined use with PI-RADS. Results Overall, 260 men
                      (median age, 64 years [IQR, 58-69 years]) with 432 lesions
                      (csPCa [n = 152] and no csPCa [n = 280]) were included. The
                      mDCE parameter was predictive of csPCa when accounting for
                      the ADC and nT2 parameter in the peripheral zone (odds ratio
                      [OR], 1.76; $95\%$ CI: 1.30, 2.44; P = .001) but not the
                      transition zone (OR, 1.17; $95\%$ CI: 0.81, 1.69; P = .41).
                      Recursive partitioning analysis selected an ADC cutoff of
                      0.897 × 10-3 mm2/sec (P = .04) as a classifier for
                      peripheral zone lesions with a PI-RADS score assessed on the
                      ADC map (hereafter, ADC PI-RADS) of 3. The mDCE parameter
                      did not differentiate ADC PI-RADS 3 lesions (P = .11), but
                      classified lesions with ADC PI-RADS scores greater than 3
                      with low ADC values (less than 0.903 × 10-3 mm2/sec, P <
                      .001) into groups with csPCa rates of $70\%$ and $97\%$ (P =
                      .008). A lesion size cutoff of 1.5 cm and qualitative DCE
                      parameters were not defined as classifiers according to
                      recursive partitioning (P > .05). Conclusion Quantitative or
                      qualitative dynamic contrast-enhanced MRI was not relevant
                      for Prostate Imaging Reporting and Data System (PI-RADS) 3
                      lesion risk stratification, while quantitative apparent
                      diffusion coefficient (ADC) values were helpful in upgrading
                      PI-RADS 3 and PI-RADS 4 lesions. Quantitative ADC
                      measurement may be more important for risk stratification
                      than current methods in future versions of PI-RADS. © RSNA,
                      2022 Online supplemental material is available for this
                      article See also the editorial by Goh in this issue.},
      cin          = {E010 / C060 / E020},
      ddc          = {610},
      cid          = {I:(DE-He78)E010-20160331 / I:(DE-He78)C060-20160331 /
                      I:(DE-He78)E020-20160331},
      pnm          = {315 - Bildgebung und Radioonkologie (POF4-315)},
      pid          = {G:(DE-HGF)POF4-315},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:35972360},
      doi          = {10.1148/radiol.212692},
      url          = {https://inrepo02.dkfz.de/record/181233},
}