RT Journal Article
SR Electronic
T1 How many time points for personalized dosimetry? Use of automated batch processing software for analysis of large patient population.
JF Journal of Nuclear Medicine
JO J Nucl Med
FD Society of Nuclear Medicine
SP 1743
OP 1743
VO 59
IS supplement 1
A1 Alexandre Chicheportiche
A1 Adam Kesner
A1 Nanette Freedman
YR 2018
UL http://jnm.snmjournals.org/content/59/supplement_1/1743.abstract
AB 1743Objectives: Personalized dosimetry offers the potential of reducing risk of high dose to vulnerable normal organs while maximizing tumor dose in radionuclide therapy, but involves additional efforts in scan acquisition and data analysis. In this retrospective study of post-treatment scans of patients with neuroendocrine tumors receiving Lu-177 DOTATATE Peptide Receptor RadioTherapy (PRRT), we compared the impact of removing one of the three recommended biodistribution SPECT scans required for modelling source organ biodistribution. Dosimetry estimations were compared between full 3 scan and abbreviated 2 scan methods in a population of clinical scans/administration cycles using in-house developed automated batch processing software, Dosimetry Data Processor (DDP), for rapid efficient data analysis. Methods: Patients receiving PRRT underwent 3 post-treatment scans during the week following treatment to verify tumor uptake and provide data for personalized dosimetry. Vendor software, Dosimetry ToolKit (DTK) from GE, was used to define VOI’s on the post-treatment scans, calculate corresponding time activity curves for patient organs, and save this data in a file. DDP software was run to read in these files and perform curve fitting, numerical integration, error checking, and absorbed dose calculation (using OLINDA/EXM Dose Conversion Factors). Standard processing of files from 634 treatments (197 patients) used mono-exponential curve fitting of the three original data points and integration to estimate organ and body remainder time integrated activity - (residence time), which were then processed to derive absorbed dose estimations. We then modified our DDP software to omit the first time point of scan data, and to recalculate dosimetry for the population using only the two other measurement time points. The population dose estimates based on two vs three time points were compared. Results: The time required for reprocessing data with 2 time points for the 634 treatments was about 6 minutes and 30 sec, i.e., about 0.6 sec per treatment using a PC on Windows 10 with an Intel Core i5 CPU @ 2.30 Ghz. Kidney dose per treatment cycle estimated from 3 and from 2 time points respectively were 0.709 ± 0.306 mGy/MBq (mean ± SD) and 0.710 ± 0.307 mGy/MBq with a mean absolute % difference <2%. However, it is noteworthy that in few cases (about 10 cycles) the magnitude of the relative difference exceeds 10%. The reasons for such differences and the influence on the number of projected permissible treatment cycles for the 197 patients were varied and case specific. For liver, spleen and tumors mean absolute % differences between the two calculations of 2.56%, 3.00% and 10.25%, respectively, were obtained. Conclusions: Interest in and acceptance of radionuclide therapy continues to grow. New mandates in regulations are compelling new levels of responsibility from treatment providers. Provision of quality dosimetry must be balanced with practical considerations imposed by the assessment. Whether a reduction of acquisition time points is built into protocols, or imposed by uncontrollable circumstances, we must understand our capacity to utilize the remaining available information. Our results show similar dose estimates whether using the 2 time points or 3 time points calculation with low mean absolute % differences (≤3% for organs). However, caution is required since in few cases the relative difference in kidney dose can reach few tens of percent. In the future we will use our data and tools to perform more analysis on the impact of measurement timing on dose estimation. RESEARCH SUPPORT: We would like to acknowledge GE Healthcare for their partial support of this project.