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@ARTICLE{Tavakoli:163204,
      author       = {A. A. Tavakoli$^*$ and T. A. Kuder$^*$ and D. Tichy$^*$ and
                      J. P. Radtke$^*$ and M. Görtz and V. Schütz and A.
                      Stenzinger and M. Hohenfellner and H.-P. Schlemmer$^*$ and
                      D. Bonekamp$^*$},
      title        = {{M}easured {M}ultipoint {U}ltra-{H}igh b-{V}alue
                      {D}iffusion {MRI} in the {A}ssessment of {MRI}-{D}etected
                      {P}rostate {L}esions.},
      journal      = {Investigative radiology},
      volume       = {56},
      number       = {2},
      issn         = {0020-9996},
      address      = {[s.l.]},
      publisher    = {Ovid},
      reportid     = {DKFZ-2020-01901},
      pages        = {94-102},
      year         = {2021},
      note         = {#EA:E010#LA:E010#2021 Feb 1;56(2):94-102},
      abstract     = {The aim of this study was to assess quantitative ultra-high
                      b-value (UHB) diffusion magnetic resonance imaging
                      (MRI)-derived parameters in comparison to standard clinical
                      apparent diffusion coefficient (SD-ADC-2b-1000,
                      SD-ADC-2b-1500) for the prediction of clinically significant
                      prostate cancer, defined as Gleason Grade Group greater than
                      or equal to 2.Seventy-three patients who underwent 3-T
                      prostate MRI with diffusion-weighted imaging acquired at b =
                      50/500/1000/1500s/mm and b =
                      100/500/1000/1500/2250/3000/4000 s/mm were included.
                      Magnetic resonance lesions were segmented manually on
                      individual sequences, then matched to targeted transrectal
                      ultrasonography/MRI fusion biopsies. Monoexponential 2-point
                      and multipoint fits of standard diffusion and of UHB
                      diffusion were calculated with incremental b-values.
                      Furthermore, a kurtosis fit with parameters Dapp and Kapp
                      with incremental b-values was obtained. Each parameter was
                      examined for prediction of clinically significant prostate
                      cancer using bootstrapped receiver operating characteristics
                      and decision curve analysis. Parameter models were compared
                      using Vuong test.Fifty of 73 men (age, 66 years
                      [interquartile range, 61-72]; prostate-specific antigen, 6.6
                      ng/mL [interquartile range, 5-9.7]) had 64 MRI-detected
                      lesions. The performance of SD-ADC-2b-1000 (area under the
                      curve, 0.82) and SD-ADC-2b-1500 (area under the curve, 0.82)
                      was not statistically different (P = 0.99), with
                      SD-ADC-2b-1500 selected as reference. Compared with the
                      reference model, none of the 19 tested logistic regression
                      parameter models including multipoint and 2-point UHB-ADC,
                      Dapp, and Kapp with incremental b-values of up to 4000 s/mm
                      outperformed SD-ADC-2b-1500 (all P's > 0.05). Decision curve
                      analysis confirmed these results indicating no higher net
                      benefit for UHB parameters in comparison to SD-ADC-2b-1500
                      in the clinically important range from $3\%$ to $20\%$ of
                      cancer threshold probability. Net reduction analysis showed
                      no reduction of MR lesions requiring biopsy.Despite
                      evaluation of a large b-value range and inclusion of
                      2-point, multipoint, and kurtosis models, none of the
                      parameters provided better predictive performance than
                      standard 2-point ADC measurements using b-values 50/1000 or
                      50/1500. Our results suggest that most of the diagnostic
                      benefits available in diffusion MRI are already represented
                      in an ADC composed of one low and one 1000 to 1500 s/mm
                      b-value.},
      cin          = {E010 / E020 / C060},
      ddc          = {610},
      cid          = {I:(DE-He78)E010-20160331 / I:(DE-He78)E020-20160331 /
                      I:(DE-He78)C060-20160331},
      pnm          = {315 - Bildgebung und Radioonkologie (POF4-315)},
      pid          = {G:(DE-HGF)POF4-315},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:32930560},
      doi          = {10.1097/RLI.0000000000000712},
      url          = {https://inrepo02.dkfz.de/record/163204},
}