[Abstract] Generation of a benchmark dosimetry dataset – An IAEA study

Generation of a benchmark dosimetry dataset – An IAEA study 

G. Kayal1,2, N. Barbosa Parada3, C. Calderón Marín4, L. Ferrer5,6, J. A. F. Negrín7,8, D. Grosev9, S. Gupta10, N. R. Hidayati11, R. Hobbs12, T. C. G. Moalosi13, G. Poli14, P. Thakral15, V. Tsapaki16, S. Vauclin7, A. Vergara-Gil1, P. Knoll16, M. Bardiès8,17
 1 CRCT, INSERM, Toulouse, FRANCE,
2 SCK CEN, Belgian Nuclear Research Centre, Mol, BELGIUM,
3 Instituto Nacional de Cancerología ESE, Bogota, COLOMBIA,
4 Instituto de Oncología y Radiobiología (INOR), Havana, CUBA,
5 ICO René Gauducheau, Medical Physics Department, Saint Herblain, FRANCE,
7 DOSIsoft SA, Cachan, FRANCE,
8 IRCM, UMR 1194 INSERM, Université de Montpellier and Institut Régional du Cancer de Montpellier (ICM), Montpellier, FRANCE,
9 Department of Nuclear Medicine and Radiation Protection, University Hospital Centre Zagreb, Zagreb, CROATIA,
10 Department of Nuclear Medicine and PET, Mahamana Pandit Madanmohan Malviya Cancer Centre and Homi Bhabha Cancer Center (a TMC unit), Haryana, INDIA,
11 Research Center and Technology for Radiation Safety and Metrology – National Research and Innovation Agency (BRIN), Jakarta, INDONESIA,
12 Department of Radiation Oncology and Radiation Molecular Sciences, Johns Hopkins Medical Institute, Baltimore, MD, UNITED STATES OF AMERICA,
13 Department of Medical Imaging and Clinical Oncology, Medical Physics, Nuclear Medicine Division, Faculty of Medicine and Health Science, Stellenbosch University, Tygerberg Hospital, Cape Town, SOUTH AFRICA,
14 ASST Papa Giovanni XXIII, Bergamo, ITALY,
15 Department of Nuclear Medicine, Fortis Memorial Research Institute, Gurugram, Haryana, INDIA,
16 Dosimetry and Medical Radiation Physics, International Atomic Energy Agency, Vienna, AUSTRIA,
17 Département de Médecine Nucléaire, Institut Régional du Cancer de Montpellier (ICM), Montpellier, FRANCE.
Presented at EANM 2022


Aim/Introduction: With the development of clinical dosimetry solutions for molecular radiotherapy (including CE-marked or FDA-approved commercial software), it is critical to generate means for evaluating the precision and accuracy of the procedure. This work aimed at designing a benchmark dataset for use in clinical dosimetry, to help professionals assess their proficiency of the software. 

Materials and Methods: A dosimetric analysis was performed by eight participants using PLANET® Dose (DOSIsoft SA) on a patient administered with Lutathera®. A standard dosimetry protocol was defined – rigid registration; organ (liver, kidneys) and lesion segmentation on CT and SPECT with 40% thresholding respectively; convolution of activity distribution to obtain absorbed dose rates (ADR), followed by ADR time integration to obtain absorbed doses (AD).Initial results shown a high variability in dosimetric results. This led to the introduction of intermediary checkpoints to better identify the sources of variation. Several working sessions were organized between participants, including a one-week final “live” dosimetry session on the same site, to discriminate between processing errors and normal inter-operator fluctuations.The procedure ultimately contributed to increasing the operator proficiency in clinical dosimetry/ 

A standard dosimetric protocol was defined and PLANET® Dose (v3.1.1) from DOSIsoft SA was installed in nine participating centers to perform the dosimetric analysis of 3 (out of 4) treatment cycles on the reconstructed patient image dataset. The protocol included rigid image registration, segmentation (semi-manual for organs, activity threshold for tumors), dose point kernel convolution of activity followed by absorbed dose rates (ADR) integration to obtain the absorbed doses (AD). Iterations of the protocol were conducted with training and brainstorming sessions, to analyze dosimetric result variability. Intermediary checkpoints were developed to understand the sources of variation and to differentiate user error from legitimate user variability. Eventually, a ‘real-time’ clinical dosimetry session was conducted for one cycle at IAEA headquarters with 8 participants in order to reduce the sources of identifiable error.

Results: At the end of the optimization process, AD in organs varied within 5%. For lesions, this variation rose to 25%, primarily a consequence of the choice of the fitting model. Organ and lesion volumes differed amongst participants by 9.4% and by 5% respectively, with the exception of the right kidney varying by 14% because of a rather small volume segmented by one participant. The variability in organ activity was less than 10% except for the right kidney (11.5%), and the lesion activities varied by less than 5%. Yet, the fluctuations in activity concentration (AC) and ADR for the right kidney decreased to 4%, an expected but comforting result, and for other organs and lesions remained below 5%, except for normal liver (12%). Nevertheless, the ADR/AC ratio remained consistent among participants (variations less than 5.7%). 

Conclusion: This work resulted in the generation of a ‘benchmark dataset’ consisting of reconstructed patient SPECT/CT data at five time points, an associated calibration factor, a standard workflow to follow in PLANET® Dose, associated step-by-step intermediary dosimetry results, with a range of “expected values” that are considered normal. This will enable professionals to train themselves on the software (here PLANET® Dose, but an equivalent procedure can be implemented for different software) and to improve their own mastery of the software.