The impact that number of analyzed metastatic breast cancer lesions has on response assessment by (18)F-FDG PET/CT using PERCIST Journal Article


Authors: Pinker, K.; Riedl, C. C.; Ong, L.; Jochelson, M.; Ulaner, G. A.; McArthur, H.; Dickler, M.; Gönen, M.; Weber, W. A.
Article Title: The impact that number of analyzed metastatic breast cancer lesions has on response assessment by (18)F-FDG PET/CT using PERCIST
Abstract: The PET Response Criteria in Solid Tumors (PERCIST) are not specific regarding the number of lesions that should be analyzed per patient. This study evaluated how the number of analyzed lesions affects response assessment in metastatic breast cancer. Methods: In 60 patients, response was assessed by the change in SUVpeak, normalized to lean body mass, of the most 18F-FDG-avid lesion (PERCIST 1) and by the change in the sum of normalized SUVpeak for up to 5 lesions (PERCIST 5). The correlation between response by PERCIST and progression-free and disease-specific survival was evaluated. Results: In responders and nonresponders, the respective progression-free survival at 2 y was 37.26% and 6.43% for PERCIST 1 (P < 0.0001) and 33.65% and 7.14% for PERCIST 5 (P < 0.0001) and the respective disease-specific survival at 4 y was 58.96% and 25.44% for PERCIST 1 (P < 0.012) and 59.12% vs 20.01% for PERCIST 5 (P < 0.002). Conclusion: The number of analyzed lesions does not appear to have a major impact on the prognostic value of response assessment with 18F-FDG PET/CT in metastatic breast cancer. © Copyright 2016 SNMMI; all rights reserved.
Keywords: treatment response; breast cancer; prediction; pet; 18f-fdg; percist
Journal Title: Journal of Nuclear Medicine
Volume: 57
Issue: 7
ISSN: 0161-5505
Publisher: Society of Nuclear Medicine  
Date Published: 2016-07-01
Start Page: 1102
End Page: 1104
Language: English
DOI: 10.2967/jnumed.115.166629
PROVIDER: scopus
PUBMED: 26985059
PMCID: PMC5493391
DOI/URL:
Notes: Article -- Export Date: 2 August 2016 -- Source: Scopus
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MSK Authors
  1. Christopher Riedl
    60 Riedl
  2. Gary Ulaner
    146 Ulaner
  3. Mithat Gonen
    1028 Gonen
  4. Maura N Dickler
    262 Dickler
  5. Maxine Jochelson
    134 Jochelson
  6. Leonard Tsung-Wei Ong
    23 Ong
  7. Wolfgang Andreas Weber
    173 Weber