Standardised quantitative radioiodine SPECT/CT Imaging for multicentre dosimetry trials in molecular radiotherapy

The SEL-I-METRY trial (EudraCT No 2015-002269-47) is the first multicentre trial to investigate the role of123I and131I SPECT/CT-based tumour dosimetry to predict response to radioiodine therapy. Standardised dosimetry methodology is essential to provide a robust evidence-base for absorbed dose-response thresholds for molecular radiotherapy (MRT). In this paper a practical standardised protocol is used to establish the first network of centres with consistent methods of radioiodine activity quantification. Nine SPECT/CT systems at 8 centres were set-up for quantitative radioiodine imaging. The dead-time of the systems was characterised for up to 2.8 GBq131I. Volume dependent calibration factors were measured on centrally reconstructed images of123I and131I in six (0.8-196 ml) cylinders. Validation of image quantification using these calibration factors was performed on 3 systems, by imaging a 3D-printed phantom mimicking a patient's activity distribution. The percentage differences between the activities measured in the SPECT/CT image and those measured by the radionuclide calibrator were calculated. Additionally uncertainties on the SPECT/CT-based activities were calculated to indicate the limit on the quantitative accuracy of this method. For systems set-up to image high131I count rates, the count rate versus activity did not peak below 2.8 GBq and fit a non-paralysable model. The dead-times and volume-dependent calibration factors were comparable between systems of the same model and crystal thickness. Therefore a global calibration curve could be fitted to each. The errors on the validation phantom activities' were comparable to the measurement uncertainties derived from uncertainty analysis, at 10% and 16% on average for123I and131I respectively in a 5 cm sphere. In conclusion, the dead-time and calibration factors varied between centres, with different models of system. However, global calibration factors may be applied to the same system model with the same crystal thickness, to simplify set-up of future multi-centre MRT studies.

[1]  M. Kaminski,et al.  Prediction of therapy tumor-absorbed dose estimates in I-131 radioimmunotherapy using tracer data via a mixed-model fit to time activity. , 2012, Cancer biotherapy & radiopharmaceuticals.

[2]  Irène Buvat,et al.  Multi-centre evaluation of accuracy and reproducibility of planar and SPECT image quantification: An IAEA phantom study. , 2017, Zeitschrift fur medizinische Physik.

[3]  W. Waddington,et al.  Objective comparison of lesion detectability in low and medium-energy collimator iodine-123 mIBG images using a channelized Hotelling observer , 2016, Physics in medicine and biology.

[4]  Iain Murray,et al.  EANM practical guidance on uncertainty analysis for molecular radiotherapy absorbed dose calculations , 2018, European Journal of Nuclear Medicine and Molecular Imaging.

[5]  A revised monitor source method for practical deadtime count loss compensation in clinical planar and SPECT studies. , 2015, Physics in medicine and biology.

[6]  A. Chiti,et al.  EANM procedure guidelines for 131I-meta-iodobenzylguanidine (131I-mIBG) therapy , 2008, European Journal of Nuclear Medicine and Molecular Imaging.

[7]  P. Green Bayesian reconstructions from emission tomography data using a modified EM algorithm. , 1990, IEEE transactions on medical imaging.

[8]  V S Hertzberg,et al.  Relation between effective radiation dose and outcome of radioiodine therapy for thyroid cancer. , 1983, The New England journal of medicine.

[9]  E. Hoffman,et al.  Quantitation in Positron Emission Computed Tomography: 1. Effect of Object Size , 1979, Journal of computer assisted tomography.

[10]  J. I. Gear,et al.  Development of patient-specific molecular imaging phantoms using a 3D printer. , 2014, Medical Physics (Lancaster).

[11]  Glenn D. Flux,et al.  A dose-effect correlation for radioiodine ablation in differentiated thyroid cancer , 2010, European Journal of Nuclear Medicine and Molecular Imaging.

[12]  Kris Thielemans,et al.  Object dependency of resolution and convergence rate in OSEM with filtering , 2001, 2001 IEEE Nuclear Science Symposium Conference Record (Cat. No.01CH37310).

[13]  W. Oyen,et al.  Guidelines for radioiodine therapy of differentiated thyroid cancer , 2008, European Journal of Nuclear Medicine and Molecular Imaging.

[14]  V S Hertzberg,et al.  Radioiodine-131 therapy for well-differentiated thyroid cancer--a quantitative radiation dosimetric approach: outcome and validation in 85 patients. , 1992, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[15]  O. Schober,et al.  Procedure guidelines for radioiodine therapy of differentiated thyroid cancer , 2016 .

[16]  F. Mottaghy,et al.  Dose–Response Relationship in Differentiated Thyroid Cancer Patients Undergoing Radioiodine Treatment Assessed by Means of 124I PET/CT , 2016, The Journal of Nuclear Medicine.

[17]  M S Rosenthal,et al.  Quantitative SPECT imaging: a review and recommendations by the Focus Committee of the Society of Nuclear Medicine Computer and Instrumentation Council. , 1995, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[18]  J. Anthony Parker,et al.  The SNMMI Practice Guideline for Therapy of Thyroid Disease with 131I 3.0* , 2012, The Journal of Nuclear Medicine.

[19]  L. Moss,et al.  Investigating the potential clinical benefit of Selumetinib in resensitising advanced iodine refractory differentiated thyroid cancer to radioiodine therapy (SEL-I-METRY): protocol for a multicentre UK single arm phase II trial , 2019, BMC Cancer.

[20]  S. Larson,et al.  Selumetinib-enhanced radioiodine uptake in advanced thyroid cancer. , 2013, The New England journal of medicine.

[21]  L. Moss,et al.  SELIMETRY—a multicentre I-131 dosimetry trial: a clinical perspective , 2017, The British journal of radiology.

[22]  S. Kappadath,et al.  Characterization of the count rate performance of modern gamma cameras. , 2013, Medical physics.

[23]  A. Sohlberg,et al.  Fast Monte Carlo-simulator with full collimator and detector response modelling for SPECT , 2011, Annals of Nuclear Medicine.

[24]  C A J van Gils,et al.  Impact of reconstruction parameters on quantitative I-131 SPECT , 2016, Physics in medicine and biology.

[25]  Michael Ljungberg,et al.  MIRD Pamphlet No. 24: Guidelines for Quantitative 131I SPECT in Dosimetry Applications , 2013, The Journal of Nuclear Medicine.

[26]  Antti Sohlberg,et al.  Reduction of Collimator Correction Artefacts with Bayesian Reconstruction in Spect , 2010, International journal of molecular imaging.

[27]  J A Sorenson Deadtime characteristics of Anger cameras. , 1975, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[28]  D. McGowan,et al.  Time to demand dosimetry for molecular radiotherapy? , 2015, The British journal of radiology.

[29]  M. Dietlein,et al.  Radioiodtherapie beim differenzierten Schilddrüsenkarzinom , 2016, Nuklearmedizin.

[30]  Dale L. Bailey,et al.  Quantitative SPECT/CT: SPECT joins PET as a quantitative imaging modality , 2014, European Journal of Nuclear Medicine and Molecular Imaging.

[31]  T. Ohtake,et al.  Estimation of deadtime in imaging human subjects , 1998, European Journal of Nuclear Medicine.