Whole-body parametric mapping of tumour perfusion in metastatic prostate cancer using long axial field-of-view 15OH2O PET
Tumour perfusion is a nutrient-agnostic biomarker for cancer metabolic rate. Use of tumour perfusion for cancer growth assessment has been limited by complicated image acquisition, image analysis and limited field-of-view scanners. Long axial field-of-view (LAFOV) PET scan using [15O]H2O, allows qua...
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Published in | European journal of nuclear medicine and molecular imaging Vol. 51; no. 13; p. 4134 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
01.11.2024
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Online Access | Get full text |
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Summary: | Tumour perfusion is a nutrient-agnostic biomarker for cancer metabolic rate. Use of tumour perfusion for cancer growth assessment has been limited by complicated image acquisition, image analysis and limited field-of-view scanners. Long axial field-of-view (LAFOV) PET scan using [15O]H2O, allows quantitative assessment of whole-body tumour perfusion. We created a tool for automated creation of quantitative parametric whole-body tumour perfusion images in metastatic cancer.PURPOSETumour perfusion is a nutrient-agnostic biomarker for cancer metabolic rate. Use of tumour perfusion for cancer growth assessment has been limited by complicated image acquisition, image analysis and limited field-of-view scanners. Long axial field-of-view (LAFOV) PET scan using [15O]H2O, allows quantitative assessment of whole-body tumour perfusion. We created a tool for automated creation of quantitative parametric whole-body tumour perfusion images in metastatic cancer.Ten metastatic prostate cancer patients underwent dynamic LAFOV [15O]H2O PET (Siemens, Quadra) followed by [18F]PSMA-1007 PET. Perfusion was measured as [15O]H2O K1 (mL/min/mL) with a single-tissue compartment model and an automatically captured cardiac image-derived input function. Parametric perfusion images were automatically calculated using the basis-function method with initial voxel-wise delay estimation and a leading-edge approach. Subsequently, perfusion of volumes-of-interest (VOI) can be directly extracted from the parametric images. We used a [18F]PSMA-1007 SUV 4 fixed threshold for tumour delineation and transferred these VOIs to the perfusion map.METHODSTen metastatic prostate cancer patients underwent dynamic LAFOV [15O]H2O PET (Siemens, Quadra) followed by [18F]PSMA-1007 PET. Perfusion was measured as [15O]H2O K1 (mL/min/mL) with a single-tissue compartment model and an automatically captured cardiac image-derived input function. Parametric perfusion images were automatically calculated using the basis-function method with initial voxel-wise delay estimation and a leading-edge approach. Subsequently, perfusion of volumes-of-interest (VOI) can be directly extracted from the parametric images. We used a [18F]PSMA-1007 SUV 4 fixed threshold for tumour delineation and transferred these VOIs to the perfusion map.For 8 primary tumours, 64 lymph node metastases, and 85 bone metastases, median tumour perfusion were 0.19 (0.15-0.27) mL/min/mL, 0.16 (0.13-0.27) mL/min/mL, and 0.26 (0.21-0.39), respectively. The correlation between calculated perfusion from time-activity-curves and parametric images was excellent (r = 0.99, p < 0.0001).RESULTSFor 8 primary tumours, 64 lymph node metastases, and 85 bone metastases, median tumour perfusion were 0.19 (0.15-0.27) mL/min/mL, 0.16 (0.13-0.27) mL/min/mL, and 0.26 (0.21-0.39), respectively. The correlation between calculated perfusion from time-activity-curves and parametric images was excellent (r = 0.99, p < 0.0001).LAFOV PET imaging using [15O]H2O enables truly quantitative parametric images of whole-body tumour perfusion, a potential biomarker for guiding personalized treatment and monitoring treatment response.CONCLUSIONLAFOV PET imaging using [15O]H2O enables truly quantitative parametric images of whole-body tumour perfusion, a potential biomarker for guiding personalized treatment and monitoring treatment response. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 content type line 23 ObjectType-Feature-2 |
ISSN: | 1619-7089 1619-7089 |
DOI: | 10.1007/s00259-024-06799-3 |