TY - JOUR
T1 - Optimal 68Ga-PSMA and 18F-PSMA PET window levelling for gross tumour volume delineation in primary prostate cancer
AU - Draulans, Cédric
AU - De Roover, Robin
AU - van der Heide, Uulke A
AU - Kerkmeijer, Linda
AU - Smeenk, Robert J
AU - Pos, Floris
AU - Vogel, Wouter V
AU - Nagarajah, James
AU - Janssen, Marcel
AU - Isebaert, Sofie
AU - Maes, Frederik
AU - Mai, Cindy
AU - Oyen, Raymond
AU - Joniau, Steven
AU - Kunze-Busch, Martina
AU - Goffin, Karolien
AU - Haustermans, Karin
N1 - Funding Information:
Robin De Roover is funded by a Kom op tegen Kanker (Stand up to Cancer) grant from the Flemish Cancer Society. Acknowledgments
Funding Information:
We thank the team of Kim Serdons for the production of 68 Ga-PSMA-11 and 18 F-PSMA-1007. We thank Kwinten Porters and Jef Van Loock for performing PSMA PET/MRI acquisitions. We thank Lotte Lutkenhaus, Laurence Delombaerde and Kenneth Poels for their efforts in the data transfer and IT support.
Publisher Copyright:
© 2020, Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2021/4
Y1 - 2021/4
N2 - Purpose: This study proposes optimal tracer-specific threshold-based window levels for PSMA PET–based intraprostatic gross tumour volume (GTV) contouring to reduce interobserver delineation variability. Methods: Nine
68Ga-PSMA-11 and nine
18F-PSMA-1007 PET scans including GTV delineations of four expert teams (GTV
manual) and a majority-voted GTV (GTV
majority) were assessed with respect to a registered histopathological GTV (GTV
histo) as the gold standard reference. The standard uptake values (SUVs) per voxel were converted to a percentage (SUV%) relative to the SUV
max. The statistically optimised SUV% threshold (SOST) was defined as those that maximises accuracy for threshold-based contouring. A leave-one-out cross-validation receiver operating characteristic (ROC) curve analysis was performed to determine the SOST for each tracer. The SOST analysis was performed twice, first using the GTV
histo contour as training structure (GTV
SOST-H) and second using the GTV
majority contour as training structure (GTV
SOST-MA) to correct for any limited misregistration. The accuracy of both GTV
SOST-H and GTV
SOST-MA was calculated relative to GTV
histo in the ‘leave-one-out’ patient of each fold and compared with the accuracy of GTV
manual. Results: ROC curve analysis for
68Ga-PSMA-11 PET revealed a median threshold of 25 SUV% (range, 22–27 SUV%) and 41 SUV% (40–43 SUV%) for GTV
SOST-H and GTV
SOST-MA, respectively. For
18F-PSMA-1007 PET, a median threshold of 42 SUV% (39–45 SUV%) for GTV
SOST-H and 44 SUV% (42–45 SUV%) for GTV
SOST-MA was found. A significant pairwise difference was observed when comparing the accuracy of the GTV
SOST-H contours with the median accuracy of the GTV
manual contours (median, − 2.5%; IQR, − 26.5–0.2%; p = 0.020), whereas no significant pairwise difference was found for the GTV
SOST-MA contours (median, − 0.3%; IQR, − 4.4–0.6%; p = 0.199). Conclusions: Threshold-based contouring using GTV
majority-trained SOSTs achieves an accuracy comparable with manual contours in delineating GTV
histo. The median SOSTs of 41 SUV% for
68Ga-PSMA-11 PET and 44 SUV% for
18F-PSMA-1007 PET form a base for tracer-specific window levelling. Trial registration: Clinicaltrials.gov;
AB - Purpose: This study proposes optimal tracer-specific threshold-based window levels for PSMA PET–based intraprostatic gross tumour volume (GTV) contouring to reduce interobserver delineation variability. Methods: Nine
68Ga-PSMA-11 and nine
18F-PSMA-1007 PET scans including GTV delineations of four expert teams (GTV
manual) and a majority-voted GTV (GTV
majority) were assessed with respect to a registered histopathological GTV (GTV
histo) as the gold standard reference. The standard uptake values (SUVs) per voxel were converted to a percentage (SUV%) relative to the SUV
max. The statistically optimised SUV% threshold (SOST) was defined as those that maximises accuracy for threshold-based contouring. A leave-one-out cross-validation receiver operating characteristic (ROC) curve analysis was performed to determine the SOST for each tracer. The SOST analysis was performed twice, first using the GTV
histo contour as training structure (GTV
SOST-H) and second using the GTV
majority contour as training structure (GTV
SOST-MA) to correct for any limited misregistration. The accuracy of both GTV
SOST-H and GTV
SOST-MA was calculated relative to GTV
histo in the ‘leave-one-out’ patient of each fold and compared with the accuracy of GTV
manual. Results: ROC curve analysis for
68Ga-PSMA-11 PET revealed a median threshold of 25 SUV% (range, 22–27 SUV%) and 41 SUV% (40–43 SUV%) for GTV
SOST-H and GTV
SOST-MA, respectively. For
18F-PSMA-1007 PET, a median threshold of 42 SUV% (39–45 SUV%) for GTV
SOST-H and 44 SUV% (42–45 SUV%) for GTV
SOST-MA was found. A significant pairwise difference was observed when comparing the accuracy of the GTV
SOST-H contours with the median accuracy of the GTV
manual contours (median, − 2.5%; IQR, − 26.5–0.2%; p = 0.020), whereas no significant pairwise difference was found for the GTV
SOST-MA contours (median, − 0.3%; IQR, − 4.4–0.6%; p = 0.199). Conclusions: Threshold-based contouring using GTV
majority-trained SOSTs achieves an accuracy comparable with manual contours in delineating GTV
histo. The median SOSTs of 41 SUV% for
68Ga-PSMA-11 PET and 44 SUV% for
18F-PSMA-1007 PET form a base for tracer-specific window levelling. Trial registration: Clinicaltrials.gov;
KW - Delineation
KW - Focal boost
KW - PSMA PET
KW - Prostatic neoplasms
KW - Radiotherapy
UR - https://www.scopus.com/pages/publications/85092101596
U2 - 10.1007/s00259-020-05059-4
DO - 10.1007/s00259-020-05059-4
M3 - Article
C2 - 33025093
SN - 1619-7070
VL - 48
SP - 1211
EP - 1218
JO - European Journal of Nuclear Medicine and Molecular Imaging
JF - European Journal of Nuclear Medicine and Molecular Imaging
IS - 4
ER -