Gross tumor volume delineation in primary prostate cancer on 18F-PSMA-1007 PET/MRI and 68Ga-PSMA-11 PET/MRI

Background We aimed to assess the clinical value of 18F-PSMA-1007 and 68Ga-PSMA-11 PET/MRI in the gross tumor volume (GTV) delineation of radiotherapy for prostate cancer (PCa). Methods Sixty-nine patients were retrospectively enrolled (57 in the 18F subgroup and 12 in the 68Ga subgroup). Three physicians delineated the GTV and tumor length by the visual method and threshold method with thresholds of 30%, 40%, 50%, and 60% SUVmax. The volume correlation and differences in GTVs were assessed. The dice similarity coefficient (DSC) was applied to estimate the spatial overlap between GTVs. For 51 patients undergoing radical prostatectomy, the tumor length (Lpath) of the maximum area was measured, and compared with the longest tumor length obtained based on the images ($ L_{MRI} $, $ L_{PET/MRI} $, $ L_{PET} $, $ L_{PET30%} $, $ L_{PET40%} $, $ L_{PET50%} $, $ L_{PET60%} $) to determine the best delineation method. Results In the 18F subgroup, (1) GTV-PET/MRI (p < 0.001) was significantly different from the reference GTV-MRI. DSC between them was > 0.7. (2) GTV-MRI (R2 = 0.462, p < 0.05) was the influencing factor of DSC. In the 68Ga subgroup, (1) GTV-PET/MRI (p < 0.05) was significantly different from the reference GTV-MRI. DSC between them was > 0.7. (2) There was a significant correlation between GTV-MRI (r = 0.580, p < 0.05) and DSC. The longest tumor length measured by PET/MRI was in good agreement with that measured by histopathological analysis in both subgroups. Conclusion It is feasible to visually delineate GTV on PSMA PET/MRI in PCa radiotherapy, and we emphasize the utility of PET/MRI fusion images in GTV delineation. In addition, the overlap degree was the highest between GTV-MRI and GTV-PET/MRI, and it increased with increasing volume..

Medienart:

E-Artikel

Erscheinungsjahr:

2022

Erschienen:

2022

Enthalten in:

Zur Gesamtaufnahme - volume:22

Enthalten in:

Cancer imaging - 22(2022), 1 vom: 22. Juli

Sprache:

Englisch

Beteiligte Personen:

Zhang, Yan-Nan [VerfasserIn]
Lu, Zhen-Guo [VerfasserIn]
Wang, Shuai-Dong [VerfasserIn]
Lu, Xin [VerfasserIn]
Zhu, Lei-Lei [VerfasserIn]
Yang, Xu [VerfasserIn]
Fu, Li-Ping [VerfasserIn]
Zhao, Jun [VerfasserIn]
Wang, Hai-Feng [VerfasserIn]
Xiang, Zuo-Lin [VerfasserIn]

Links:

Volltext [kostenfrei]

Themen:

Gross tumor volume
PSMA PET/MRI
Prostate cancer
Radiotherapy

Anmerkungen:

© The Author(s) 2022

doi:

10.1186/s40644-022-00475-1

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

OLC2131419279