• Medientyp: E-Artikel
  • Titel: Quantitative imaging parameters to predict the local staging of prostate cancer in intermediate- to high-risk patients
  • Beteiligte: Laudicella, Riccardo; Skawran, Stephan; Ferraro, Daniela A.; Mühlematter, Urs J.; Maurer, Alexander; Grünig, Hannes; Rüschoff, Hendrik J.; Rupp, Niels; Donati, Olivio; Eberli, Daniel; Burger, Irene A.
  • Erschienen: Springer Science and Business Media LLC, 2022
  • Erschienen in: Insights into Imaging
  • Sprache: Englisch
  • DOI: 10.1186/s13244-022-01217-4
  • ISSN: 1869-4101
  • Schlagwörter: Radiology, Nuclear Medicine and imaging
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: <jats:title>Abstract</jats:title><jats:sec> <jats:title>Objectives</jats:title> <jats:p>PSMA PET/MRI showed the potential to increase the sensitivity for extraprostatic disease (EPD) assessment over mpMRI; however, the interreader variability for EPD is still high. Therefore, we aimed to assess whether quantitative PSMA and mpMRI imaging parameters could yield a more robust EPD prediction.</jats:p> </jats:sec><jats:sec> <jats:title>Methods</jats:title> <jats:p>We retrospectively evaluated PCa patients who underwent staging mpMRI and [<jats:sup>68</jats:sup>Ga]PSMA-PET, followed by radical prostatectomy at our institution between 01.02.2016 and 31.07.2019. Fifty-eight cases with PET/MRI and 15 cases with PET/CT were identified. EPD was determined on histopathology and correlated with quantitative PSMA and mpMRI parameters assessed by two readers: ADC (mm<jats:sup>2</jats:sup>/1000 s), longest capsular contact (LCC, mm), tumor volume (cm<jats:sup>3</jats:sup>), PSMA-SUV<jats:sub>max</jats:sub> and volume-based parameters using a fixed threshold at SUV &gt; 4 to delineate PSMA<jats:sub>total</jats:sub> (g/ml) and PSMA<jats:sub>vol</jats:sub> (cm<jats:sup>3</jats:sup>). The <jats:italic>t</jats:italic> test was used to compare means, Pearson’s test for categorical correlation, and ROC curve to determine the best cutoff. Interclass correlation (ICC) was performed for interreader agreement (95% CI).</jats:p> </jats:sec><jats:sec> <jats:title>Results</jats:title> <jats:p>Seventy-three patients were included (64.5 ± 6.0 years; PSA 14.4 ± 17.1 ng/ml), and 31 had EPD (42.5%). From mpMRI, only LCC reached significance (<jats:italic>p</jats:italic> = 0.005), while both volume-based PET parameters PSMA<jats:sub>total</jats:sub> and PSMA<jats:sub>vol</jats:sub> were significantly associated with EPD (<jats:italic>p</jats:italic> = 0.008 and <jats:italic>p</jats:italic> = 0.004, respectively). On ROC analysis, LCC, PSMA<jats:sub>total</jats:sub>, and PSMA<jats:sub>vol</jats:sub> reached an AUC of 0.712 (<jats:italic>p</jats:italic> = 0.002), 0.709 (<jats:italic>p</jats:italic> = 0.002), and 0.718 (<jats:italic>p</jats:italic> = 0.002), respectively. ICC was moderate–good for LCC 0.727 (0.565–0.828) and excellent for PSMA<jats:sub>total</jats:sub> and PSMA<jats:sub>vol</jats:sub> with 0.944 (0.990–0.996) and 0.985 (0.976–0.991), respectively.</jats:p> </jats:sec><jats:sec> <jats:title>Conclusions</jats:title> <jats:p>Quantitative PSMA parameters have a similar potential as mpMRI LCC to predict EPD of PCa, with a significantly higher interreader agreement.</jats:p> </jats:sec>
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