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3D absorbed dose distribution estimated by Monte Carlo simulation in radionuclide therapy with a monoclonal antibody targeting synovial sarcoma

Overview of attention for article published in EJNMMI Physics, January 2017
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Title
3D absorbed dose distribution estimated by Monte Carlo simulation in radionuclide therapy with a monoclonal antibody targeting synovial sarcoma
Published in
EJNMMI Physics, January 2017
DOI 10.1186/s40658-016-0172-1
Pubmed ID
Authors

David Sarrut, Jean-Noël Badel, Adrien Halty, Gwenaelle Garin, David Perol, Philippe Cassier, Jean-Yves Blay, David Kryza, Anne-Laure Giraudet

Abstract

Radiolabeled OTSA101, a monoclonal antibody targeting synovial sarcoma (SS) developed by OncoTherapy Science, was used to treat relapsing SS metastases following a theranostic procedure: in case of significant (111)In-OTSA101 tumor uptake and favorable biodistribution, patient was randomly treated with 370/1110 MBq (90)Y-OTSA101. Monte Carlo-based 3D dosimetry integrating time-activity curves in VOI was performed on (111)In-OTSA101 repeated SPECT/CT. Estimated absorbed doses (AD) in normal tissues were compared to biological side effects and to the admitted maximal tolerated absorbed dose (MTD) in normal organs. Results in the tumors were also compared to disease evolution. Biodistribution and tracer quantification were analyzed on repeated SPECT/CT acquisitions performed after injection of (111)In-OTSA101 in 19/20 included patients. SPECT images were warped to a common coordinates system with deformable registration. Volumes of interest (VOI) for various lesions and normal tissues were drawn on the first CT acquisition and reported to all the SPECT images. Tracer quantification and residence time of (111)In-OTSA101 in VOI were used to evaluate the estimated absorbed doses per MBq of (90)Y-OTSA101 by means of Monte Carlo simulations (GATE). A visual scale analysis was applied to assess tumor uptake (grades 0 to 4) and results were compared to the automated quantification. Results were then compared to biological side effects reported in the selected patients treated with (90)Y-OTSA101 but also to disease response to treatment. After screening, 8/20 patients were treated with 370 or 1110 MBq (90)Y-OTSA101. All demonstrated medullary toxicity, only one presented with transient grade 3 liver toxicity due to disease progression, and two patients presented with transient grade 1 renal toxicity. Median absorbed doses were the highest in the liver (median, 0.64 cGy/MBq; [0.27 -1.07]) being far lower than the 20 Gy liver MTD, and the lowest in bone marrow (median, 0.09 cGy/MBq; [0.02 -0.18]) being closer to the 2 Gy bone marrow MTD. Most of the patients demonstrated progressive disease on RECIST criteria during patient follow-up. (111)In-OTSA101 tumors tracer uptake visually appeared highly heterogeneous in inter- and intra-patient analyses, independently of tumor sizes, with variable kinetics. The majority of visual grades corresponded to the automated computed ones. Estimated absorbed doses in the 95 supra-centimetric selected lesions ranged from 0.01 to 0.71 cGy per injected MBq (median, 0.22 cGy/MBq). The maximal tumor AD obtained was 11.5 Gy. 3D dosimetry results can explain the observed toxicity and tumors response. Despite an intense visual (111)In-OTSA101 liver uptake, liver toxicity was not the dose limiting factor conversely to bone marrow toxicity. Even though tumors (111)In-OTSA101 avidity was visually obvious for treated patients, the low estimated tumors AD obtained by 3D dosimetry explain the lack of tumor response.

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The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 39 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 28%
Student > Ph. D. Student 7 18%
Unspecified 5 13%
Student > Master 3 8%
Other 2 5%
Other 4 10%
Unknown 7 18%
Readers by discipline Count As %
Physics and Astronomy 10 26%
Unspecified 5 13%
Medicine and Dentistry 5 13%
Computer Science 3 8%
Immunology and Microbiology 2 5%
Other 6 15%
Unknown 8 21%