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PSMA PET for the Assessment of Metastatic Hormone-Sensitive Prostate Cancer Volume of Disease

  • Francesco Barbato
  • , Wolfgang P. Fendler
  • , Isabel Rauscher
  • , Ken Herrmann
  • , Axel Wetter
  • , Justin Ferdinandus
  • , Robert Seifert
  • , Michael Nader
  • , Kambiz Rahbar
  • , Boris Hadaschik
  • , Matthias Eiber
  • , Andrei Gafita
  • , Manuel Weber
  • University Hospital of Essen
  • Technical University of Munich
  • Universitätsklinikum Münster

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

Conventional imaging of low-volume disease (LVD) versus high-volume disease (HVD) is associated with survival in metastatic hormone-sensitive prostate cancer (mHSPC) according to the CHAARTED trial (Chemohormonal Therapy in Metastatic Hormone-Sensitive Prostate Cancer) and the STAMPEDE trial (Systemic Therapy for Advanced or Metastatic Prostate Cancer: Evaluation of Drug Efficacy). We propose a compatible quantitative PSMA PET framework for disease volume assessment in mHSPC. Methods: Three PET centers screened their PSMA PET database for mHSPC patients. CT versus PSMA PET stage, lesion number, and classification of LVD versus HVD were determined by 1 masked reader; PSMA-positive tumor volume was quantified semiautomatically. Results: In total, 85 CT-based CHAARTED LVD and 20 CT-based CHAARTED HVD patients were included. A PSMA tumor volume of about 40 cm3 was the optimal cutoff between CT-based CHAARTED LVD (nonunifocal) and HVD (non-M1c) (area under the curve, 0.86). Stratification into PET LVD (unifocal or oligometastatic/disseminated, ~40 cm3) and PET HVD (oligometastatic/disseminated $ ~40 cm3 or M1c) had 13% misalignment with the CHAARTED criteria. Conclusion: PSMA PET criteria with volume quantification deliver comparable LVD/HVD discrimination with additional subgroups for unifocal, oligometastatic, and disseminated disease, critical for guidance of targeted or multimodal therapy.

Original languageEnglish
Pages (from-to)1747-1750
Number of pages4
JournalJournal of Nuclear Medicine
Volume62
Issue number12
DOIs
StatePublished - 1 Dec 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • CHAARTED
  • PSMA
  • mHSPC
  • metastasis-directed treatment
  • prostate cancer

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