B Vanbilloen

Comparison of diagnostic accuracy of (111)In-pentetreotide SPECT and (68)Ga-DOTATOC PET/CT: A lesion-by-lesion analysis in patients with metastatic neuroendocrine tumours.

AbstractObjectivesTo compare the diagnostic accuracy of 111In-pentetreotide-scintigraphy with 68Ga-DOTATOC-positron emission tomography (PET)/computed tomography (CT) in patients with metastatic-neuroendocrine tumour (NET) scheduled for peptide receptor radionuclide therapy (PRRT). Incremental lesions (ILs) were defined as lesions observed on only one modality.MethodsFifty-three metastatic-NET-patients underwent 111In-pentetreotide-scintigraphy (24 h post-injection; planar+single-photon emission CT (SPECT) abdomen) and whole-body 68Ga-DOTATOC-PET/CT. SPECT and PET were compared in a lesion-by-lesion and organ-by-organ analysis, determining the total lesions and ILs for both modalities.ResultsSignificantly more lesions were detected on 68Ga-DOTATOC-PET/CT versus 111In-pentetreotide-scintigraphy. More specifically, we observed 1,098 lesions on PET/CT (range: 1–105; median: 15) versus 660 on SPECT (range: 0–73, median: 9) (p<0.0001), with 439 PET-ILs (42/53 patients) and one SPECT-IL (1/53 patients). The sensitivity for PET/CT was 99.9 % (95 % CI, 99.3–100.0), for SPECT 60.0 % (95 % CI, 48.5–70.2). The organ-by-organ analysis showed that the PET-ILs were most frequently visualized in liver and skeleton.ConclusionGa-DOTATOC-PET/CT is superior for the detection of NET-metastases compared to 111In-pentetreotide SPECT.Key Points• Somatostatin receptor PET is superior to SPECT in detecting NET metastases • PET is the scintigraphic method for accurate depiction of NET tumour burden • The sensitivity of PET is twofold higher than the sensitivity of SPECT

Optimized multipinhole design for mouse imaging

To enhance high-sensitivity focused mouse imaging using multipinhole SPECT on a dual head camera, a fast analytical method was used to predict the contrast-to-noise ratio (CNR) in many points of a homogeneous cylinder for a large number of pinhole collimator designs with modest overlap. The design providing the best overall CNR, a configuration with 7 pinholes, was selected. Next, the pinhole pattern was made slightly irregular to reduce multiplexing artifacts. Two identical, but mirrored 7-pinhole plates were manufactured. In addition, the calibration procedure was refined to cope with small deviations of the camera from circular motion. First, the new plates were tested by reconstructing a simulated homogeneous cylinder measurement. Second, a Jaszczak phantom filled with 37 MBq 99mTc was imaged on a dual head gamma camera, equipped with the new pinhole collimators. The image quality before and after refined calibration was compared for both heads, reconstructed separately and together. Next, 20 short scans of the same phantom were performed with single and multipinhole collimation to investigate the noise improvement of the new design. Finally, two normal mice were scanned using the new multipinhole designs to illustrate the reachable image quality of abdomen and thyroid imaging. The simulation study indicated that the irregular patterns suppress most multiplexing artifacts. Using body support information strongly reduces the remaining multiplexing artifacts. Refined calibration improved the spatial resolution. Depending on the location in the phantom, the CNR increased with a factor of 1 to 2.5 using the new instead of a single pinhole design. The first proof of principle scans and reconstructions were successful, allowing the release of the new plates and software for preclinical studies in mice.

Influence of chronic bromocriptine and levodopa administration on cerebral type 1 cannabinoid receptor binding

The endocannabinoid system is an important modulatory system in the brain. Complex interactions with brain dopaminergic circuits have been demonstrated. The aim of this study was to investigate the in vivo effect of the commonly used antiparkinsonian drugs, levodopa (L‐DOPA) and bromocriptine, on type 1 cannabinoid (CB1) receptors, using the PET radioligand [18F]MK‐9470.

Altered Biodistribution of Somatostatin Analogues After First Cycle of Peptide Receptor Radionuclide Therapy

Introduction Peptide receptor radionuclide therapy (PRRT) targeting the somatostatin receptor has emerged as a powerful palliative therapy in metastasized neuroendocrine tumors. A treatment schedule consisting of several administrations of Y-[DOTA]-Tyroctreotide (Y-DOTATOC) is the standard approach. Because long-term renal toxicity is the dose-limiting factor, dosimetry with In-octreotide is performed in all patients. Sequential images are acquired at five different time points, allowing calculation of the biologic effective dose (BED) on the dose-limiting organs, the kidneys, after several cycles of Y-DOTATOC treatment (1 GBq/m per cycle). On the basis of published data, the maximum-tolerated BED after four cycles is fixed at 37 Gy. In our protocol, Ga-DOTATOC positron emission tomography (PET)/computed tomography (CT) and functional magnetic resonance imaging (perfusion and diffusion weighted) performed before and at weeks 7 and 40 are included.

Molecular Imaging of Human Embryonic Stem Cells Stably Expressing Human PET Reporter Genes After Zinc Finger Nuclease-Mediated Genome Editing

Molecular imaging is indispensable for determining the fate and persistence of engrafted stem cells. Standard strategies for transgene induction involve the use of viral vectors prone to silencing and insertional mutagenesis or the use of nonhuman genes. Methods: We used zinc finger nucleases to induce stable expression of human imaging reporter genes into the safe-harbor locus adeno-associated virus integration site 1 in human embryonic stem cells. Plasmids were generated carrying reporter genes for fluorescence, bioluminescence imaging, and human PET reporter genes. Results: In vitro assays confirmed their functionality, and embryonic stem cells retained differentiation capacity. Teratoma formation assays were performed, and tumors were imaged over time with PET and bioluminescence imaging. Conclusion: This study demonstrates the application of genome editing for targeted integration of human imaging reporter genes in human embryonic stem cells for long-term molecular imaging.

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

Purpose: To investigate the relationship between the dynamic parameters (Ki) and static image-derived parameters of 68Ga-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 68Ga-DOTATOC-PET before PRRT and at 7 and 40 weeks after the first administration of 90Y-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 68Ga-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, Ki 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 68Ga-DOTATOC-PET had a very strong correlation with the corresponding parameters in the static scan (R²: 0.94 and 0.95 respectively). SUVmax, SUVmean and Ki of the lesions showed a good linear correlation; the SUVratios 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 Ki correlates best with the absolute SUVtumour, SUVtumour best reflects underlying SSR-levels in NETs.PURPOSE To investigate the relationship between the dynamic parameters (Ki) and static image-derived parameters of 68Ga-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 68Ga-DOTATOC-PET before PRRT and at 7 and 40 weeks after the first administration of 90Y-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 68Ga-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, Ki 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 68Ga-DOTATOC-PET had a very strong correlation with the corresponding parameters in the static scan (R²: 0.94 and 0.95 respectively). SUVmax, SUVmean and Ki of the lesions showed a good linear correlation; the SUVratios 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 Ki correlates best with the absolute SUVtumour, SUVtumour best reflects underlying SSR-levels in NETs.

Dynamic 68Ga-DOTATOC PET/CT and static image in NET patients

Purpose: To investigate the relationship between the dynamic parameters (Ki) and static image-derived parameters of 68Ga-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 68Ga-DOTATOC-PET before PRRT and at 7 and 40 weeks after the first administration of 90Y-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 68Ga-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, Ki 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 68Ga-DOTATOC-PET had a very strong correlation with the corresponding parameters in the static scan (R²: 0.94 and 0.95 respectively). SUVmax, SUVmean and Ki of the lesions showed a good linear correlation; the SUVratios 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 Ki correlates best with the absolute SUVtumour, SUVtumour best reflects underlying SSR-levels in NETs.PURPOSE To investigate the relationship between the dynamic parameters (Ki) and static image-derived parameters of 68Ga-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 68Ga-DOTATOC-PET before PRRT and at 7 and 40 weeks after the first administration of 90Y-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 68Ga-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, Ki 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 68Ga-DOTATOC-PET had a very strong correlation with the corresponding parameters in the static scan (R²: 0.94 and 0.95 respectively). SUVmax, SUVmean and Ki of the lesions showed a good linear correlation; the SUVratios 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 Ki correlates best with the absolute SUVtumour, SUVtumour best reflects underlying SSR-levels in NETs.

Dynamische und statische 68Ga-DOTATOC-PET/CT bei Patienten mit NET

Purpose: To investigate the relationship between the dynamic parameters (Ki) and static image-derived parameters of 68Ga-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 68Ga-DOTATOC-PET before PRRT and at 7 and 40 weeks after the first administration of 90Y-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 68Ga-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, Ki 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 68Ga-DOTATOC-PET had a very strong correlation with the corresponding parameters in the static scan (R²: 0.94 and 0.95 respectively). SUVmax, SUVmean and Ki of the lesions showed a good linear correlation; the SUVratios 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 Ki correlates best with the absolute SUVtumour, SUVtumour best reflects underlying SSR-levels in NETs.PURPOSE To investigate the relationship between the dynamic parameters (Ki) and static image-derived parameters of 68Ga-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 68Ga-DOTATOC-PET before PRRT and at 7 and 40 weeks after the first administration of 90Y-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 68Ga-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, Ki 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 68Ga-DOTATOC-PET had a very strong correlation with the corresponding parameters in the static scan (R²: 0.94 and 0.95 respectively). SUVmax, SUVmean and Ki of the lesions showed a good linear correlation; the SUVratios 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 Ki correlates best with the absolute SUVtumour, SUVtumour best reflects underlying SSR-levels in NETs.