Monte Carlo simulation model of innovative SPECT systems
Recrutement: 
Recrutement en cours/passé: 
Recrutement en cours
Periode: 
2022-2023
Contact: 
Please send CV, a brief statement of interest and  the transcript of records to: ane.etxebeste@creatis.insa-lyon.fr david.sarrut@creatis.insa-lyon.fr

The main objective of this internship is to develop a Monte Carlo model of a new type of  multi-CZT detector SPECT system and validate the model against experimental data.

Context.

In nuclear medicine during the last ten years, cancer treatment by Molecular Radionuclide Therapy (MRT) has been growing rapidly. As an example, peptide receptor radionuclide therapy (PRRT) has been shown to be an alternative treatment for neuroendocrine tumors (NETs) when surgery is not indicated [1]. MRT consists in intravenous administration of a molecular vector labeled with a radionuclide. The vector’s goal is to accumulate the compound in target organs and β or α-emitting radionuclide provides cytotoxic effects. Lutetium-177 is one of the most used radionuclides. In addition to β particles, it also emits γ rays that allows to quantify the radionuclide concentration in the tumors and healthy organs with SPECT/CT images acquisitions repeated at different point-times after treatment injection.

Patient-personalized dosimetry [2], [3] is a key notion that allows to optimize tumor control by administering the highest possible activity in target volume while limiting complications due to irradiation to organs at risk. The principle is to estimate the biodistribution and the pharmacokinetic of the activity inside the patient from SPECT/CT images. This image-based estimation is however impaired by numerous effects (attenuation, scatter, breathing motion…) that must be corrected or accounted for [4]–[6]. Monte Carlo simulation of SPECT imaging systems, which consists in building a virtual model of the imaging process in the most accurate way possible [7], is an essential tool to optimize the acquisition parameters, calibrate the images, perform research in image reconstruction or estimate the dose distribution.

Recently, a new type of CZT-based digital camera (VERITON-CT, Spectrum Dynamics) was acquired by Leon Bérard cancer center. This system is characterized by its unique scanning geometry which allows independent radial and swivel motion of the detectors [8]. A Monte Carlo model of this innovative system will have to be developed and validated to be applied in this medical context.

Objectives of the master internship.

The main objective of this internship is to develop a Monte Carlo model of a new type of  multi-CZT detector SPECT system and validate the model against experimental data.

  1. Reproduce scanning geometry of acquisitions (including radial and swivel motion)
  2. Develop a Monte Carlo model of the system with GATE (python-based version)
  3. Compare Monte Carlo model predictions with experimental data
  4. Design new measurements, if needed, to further validate the model.
  5. Reconstruct the activity distribution from simulated projection data with RTK [9]

Environment.

The student will work in a multidisciplinary team composed of nuclear physicians, medical physicists, researchers, and computer scientists of CREATIS laboratory and Leon-Bérard Cancer Center.

Required skills

  • Medical physics, computer sciences, image processing
  • Technical skills:  Python is required, experience with GATE would be an asset

Location

Léon Bérard cancer center, Lyon, France

References

[1] M. Del Prete et al., “Personalized 177 Lu-octreotate peptide receptor radionuclide therapy of neuroendocrine tumours: initial results from the P-PRRT trial,” Eur. J. Nucl. Med. Mol. Imaging, vol. 46, no. 3, pp. 728–742, 2019, doi: 10.1007/s00259-018-4209-7.

[2] M. Del Prete, F.-A. Buteau, and J.-M. Beauregard, “Personalized 177-Lu-octreotate peptide receptor radionuclide therapy of neuroendocrine tumours: a simulation study.,” Eur. J. Nucl. Med. Mol. Imaging, vol. 44, no. 9, pp. 1490–1500, Aug. 2017, doi: 10.1007/s00259-017-3688-2.

[3] M. Ljungberg and K. Sjogreen Gleisner, “3-D Image-Based Dosimetry in Radionuclide Therapy,” IEEE Trans. Radiat. Plasma Med. Sci., vol. 2, no. 6, pp. 527–540, Nov. 2018, doi: 10/gf4465.

[4] M. Ljungberg, A. Celler, M. W. Konijnenberg, K. F. Eckerman, Y. K. Dewaraja, and K. Sjogreen-Gleisner, “MIRD Pamphlet No. 26: Joint EANM/MIRD Guidelines for Quantitative 177Lu SPECT Applied for Dosimetry of Radiopharmaceutical Therapy,” J. Nucl. Med., vol. 57, no. 1, pp. 151–162, Jan. 2016, doi: 10/f3mw4b

[5] E. Hippeläinen, M. Tenhunen, H. Mäenpää, and A. Sohlberg, “Quantitative accuracy of 177Lu SPECT reconstruction using different compensation methods: phantom and patient studies,” EJNMMI Res., vol. 6, no. 1, p. 16, Dec. 2016, doi: 10/gf6836.

[6] M. D’Arienzo et al., “Gamma camera calibration and validation for quantitative SPECT imaging with 177Lu,” Appl. Radiat. Isot., vol. 112, pp. 156–164, Jun. 2016, doi: 10/gf684q.

[7] D. Sarrut et al., “A review of the use and potential of the GATE Monte Carlo simulation code for radiation therapy and dosimetry applications,” Med. Phys., vol. 41, no. 6Part1, p. 064301, Jun. 2014, doi: 10.1118/1.4871617.

[8] Wacholz, C., Hruska, C. and OConnor, M., 2020. VERITON multi-CZT detector SPECT/CT system acceptance testing.

[9] S. Rit et al. The Reconstruction Toolkit (RTK), an open-source cone-beam CT reconstruction toolkit based on the Insight Toolkit (ITK)” J. Phys.: Conf. Ser. 489 012079, 2014, doi:10.1088/1742-6596/489/1/012079