Dataset Information

Computational modeling of PET tracer distribution in solid tumors integrating microvasculature.

ABSTRACT:

Background

We present computational modeling of positron emission tomography radiotracer uptake with consideration of blood flow and interstitial fluid flow, performing spatiotemporally-coupled modeling of uptake and integrating the microvasculature. In our mathematical modeling, the uptake of fluorodeoxyglucose F-18 (FDG) was simulated based on the Convection-Diffusion-Reaction equation given its high accuracy and reliability in modeling of transport phenomena. In the proposed model, blood flow and interstitial flow are solved simultaneously to calculate interstitial pressure and velocity distribution inside cancer and normal tissues. As a result, the spatiotemporal distribution of the FDG tracer is calculated based on velocity and pressure distributions in both kinds of tissues.

Results

Interstitial pressure has maximum value in the tumor region compared to surrounding tissue. In addition, interstitial fluid velocity is extremely low in the entire computational domain indicating that convection can be neglected without effecting results noticeably. Furthermore, our results illustrate that the total concentration of FDG in the tumor region is an order of magnitude larger than in surrounding normal tissue, due to lack of functional lymphatic drainage system and also highly-permeable microvessels in tumors. The magnitude of the free tracer and metabolized (phosphorylated) radiotracer concentrations followed very different trends over the entire time period, regardless of tissue type (tumor vs. normal).

Conclusion

Our spatiotemporally-coupled modeling provides helpful tools towards improved understanding and quantification of in vivo preclinical and clinical studies.

SUBMITTER: Fasaeiyan N

PROVIDER: S-EPMC8620574 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:Predicting the aggressive behavior of non-functional pancreatic neuroendocrine tumors (NF-PNET) remains controversial. We wanted to explore, in a prospective setting, whether the diagnostic accuracy can be improved by dual-tracer functional imaging 68Ga-DOTANOC and 18F-FDG-PET/CT in patients with NF-PNETs. METHODS:Thirty-one patients with NF-PNET (90% asymptomatic) underwent PET-imaging with 18F-FDG and 68Ga-DOTANOC, followed by surgery (n = 20), an endoscopic ultrasonography and fine-needle biopsy (n = 2) or follow-up (n = 9). A focal activity on PET/CT greater than the background that could not be identified as physiological activity was considered to indicate tumor tissue. The imaging results were compared to histopathology. The mean follow-up time was 31.3 months. RESULTS:Thirty-one patients presented a total of 53 lesions (40 histologically confirmed) on PET/CT. Thirty patients had a 68Ga-DOTANOC-positive tumor (sensitivity 97%) and 10 patients had an 18F-FDG-positive tumor. In addition, one 68Ga-DOTANOC-negative patient was 18F-FDG-positive. 18F-FDG-PET/CT was positive in 19% (3/16) of the G1 tumors, 63% (5/8) of the G2 tumors and 1/1 of the well-differentiated G3 tumor. 68Ga-DOTANOC-PET/CT was positive in 94% of the G1 tumors, 100% of the G2 tumors and 1/1 of the well-differentiated G3 tumor. Two out of six (33%) of the patients with lymph node metastases (LN+) were 18F-FDG-positive. The 18F-FDG-PET/CT correlated with tumor Ki-67 (P = 0.021). Further, the Krenning score correlated with tumor Ki-67 (P = 0.013). 18F-FDG-positive tumors were significantly larger than the 18F-FDG-negative tumors (P = 0.012). 18F-FDG-PET/CT showed a positive predictive value of 78% in the detection of potentially aggressive tumors (G2, G3, or LN + PNETs); the negative predictive value was 69%. CONCLUSIONS:18F-FDG-PET/CT is useful to predict tumor grade but not the LN+ of NF-PNETs. Patients with 18F-FDG-avid NF-PNETs should be referred for surgery. The 68Ga-DOTANOC-PET/CT also has prognostic value since the Krenning score predicts the histopathological tumor grade. TRIAL REGISTRATION:The study has been registered at ClinicalTrials.gov; Non-functional Pancreatic NET and PET imaging, NCT02621541.