4.0 Article

Dynamic 68Ga-DOTATOC PET/CT and static image in NET patients Correlation of parameters during PRRT

Journal

NUKLEARMEDIZIN-NUCLEAR MEDICINE
Volume 55, Issue 3, Pages 104-114

Publisher

SCHATTAUER GMBH-VERLAG MEDIZIN NATURWISSENSCHAFTEN
DOI: 10.3413/Nukmed-0742-15-05

Keywords

Ga-68-DOTATOC PET; K-i; somatostatin receptor expression; PRRT; neuroendocrine tumour

Funding

  1. Instituut voor de Aanmoediging van Innovatie door Wetenschap en Technologie in Vlaanderen (IWT) Protokol IWT-TBM Project [0707181]
  2. Innovatie door Wetenschap en Technologie-Toegepast Biomedisch onderzoek met een primair Maatschappelijke finaliteit project [0707181]
  3. Vlaamse Liga tegen Kanker

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Purpose: To investigate the relationship between the dynamic parameters (IQ and static image-derived parameters of Ga-68-DOTATOC-PET, to determine which static parameter best reflects underlying somatostatin-receptor-expression (SSR) levels on neuroendocrine tumours (NETs). Patients, methods: 20 patients with metastasized NETs underwent a dynamic and static Ga-68-DOTATOC-PET before PRRT and at 7 and 40 weeks after the first administration of Y-90-DOTATOC (in total 4 cycles were planned); 175 lesions were defined and analyzed on the dynamic as well as static scans. Quantitative analysis was performed using the software PMOD. One to five target lesions per patient were chosen and delineated manually on the baseline dynamic scan and further, on the corresponding static 68Ga-DOTATOC-PET and the dynamic and static Ga-68-DOTATOC-PET at the other time points; SUVmax and SUVmean of the lesions was assessed on the other six scans. The input function was retrieved from the abdominal aorta on the images. Further on, K-i was calculated using the Patlak-Plot. At last, 5 reference regions for normalization of SUVtumour were delineated on the static scans resulting in 5 ratios (SUVratio). Results: SUVmax and SUVmean of the tumoural lesions on the dynamic Ga-68-DOTATOC-PET had a very strong correlation with the corresponding parameters in the static scan (R-2: 0.94 and 0.95 respectively). SUVmax, SUVmean and Ki of the lesions showed a good linear correlation; the SUVranns correlated poorly with Ki. A significantly better correlation was noticed between Ki and SUVtumour(max (and) (mean)) (p < 0.0001). Conclusions: As the dynamic parameter K-i correlates best with the absolute SUVtumour SUVtumour best reflects underlying SSR-levels in NETs.

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