Population-based input function (PBIF) applied to dynamic whole-body 68Ga-DOTATOC-PET/CT acquisition

Area of Science:

• Nuclear Medicine
• Radiochemistry
• Medical Imaging

Background:

• Dynamic whole-body (WBdyn) PET imaging requires scanning from injection time, increasing acquisition duration.
• A population-based input function (PBIF) model can potentially alleviate the need for prolonged scanning.
• Validating such models is crucial for clinical implementation in oncology.

Purpose of the Study:

• To validate a PBIF model for dynamic whole-body (WBdyn) PET/CT imaging.
• To assess the model's ability to reduce scan times in patients with neuroendocrine tumors.
• To compare quantitative parameters derived from PBIF and image-derived input functions (IDIFs).

Main Methods:

• Developed a PBIF model using 20 WBdyn 68Ga-DOTATOC-PET/CT exams from the GAPETNET trial.
• Applied the PBIF model to 17 independent patient studies, scaling it to match IDIFs from WB-passes 3-7.
• Compared AUCs and Patlak-estimated Ki values (liver, spleen, tumor) between PBIF and IDIF using Bland-Altman analysis.

Main Results:

• The mean AUC ratio (PBIF/IDIF) was 0.98 ± 0.06.
• Mean Ki bias between PBIF and IDIF was -2.6 ± 6.2%.
• Low relative bias and SD were observed for Ki-spleen (4.65 ± 7.59%) and Ki-tumor (3.70 ± 8.29%), with slightly higher values for Ki-liver (7.43 ± 13.13%).

Conclusions:

• The validated PBIF model enables a reduction in WBdyn DOTATOC-PET/CT acquisition times.
• A minimum gain of 20 minutes in scan time can be achieved using this PBIF approach.
• This method enhances efficiency for dynamic whole-body PET imaging in neuroendocrine tumor assessment.