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Pham TP, Presles B, Popoff R, Alberini JL, Vrigneaud JM. Pre-treatment dosimetry in 90Y-SIRT: Is it possible to optimise SPECT reconstruction parameters and calculation methods for accurate dosimetry? Phys Med 2023; 115:103145. [PMID: 37852020 DOI: 10.1016/j.ejmp.2023.103145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Revised: 06/03/2023] [Accepted: 09/21/2023] [Indexed: 10/20/2023] Open
Abstract
PURPOSE The aim of this study was (a) to optimise the99mTc-SPECT reconstruction parameters for the pre-treatment dosimetry of90Y-selective internal radiation therapy (SIRT) and (b) to compare the accuracy of clinical dosimetry methods with full Monte-Carlo dosimetry (fMCD) performed with Gate. METHODS To optimise the reconstruction parameters, two hundred reconstructions with different parameters were performed on a NEMA phantom, varying the number of iterations, subsets, and post-filtering. The accuracy of the dosimetric methods was then investigated using an anthropomorphic phantom. Absorbed dose maps were generated using (1) the Partition Model (PM), (2) the Dose Voxel Kernel (DVK) convolution, and (3) the Local Deposition Method (LDM) with known activity restricted to the whole phantom (WP) or to the liver and lungs (LL). The dose to the lungs was calculated using the "multiple DVK" and "multiple LDM" methods. RESULTS Optimal OSEM reconstruction parameters were found to depend on object size and dosimetric criterion chosen (Dmean or DVH-derived metric). The Dmean of all three dosimetric methods was close (≤ 10%) to the Dmean of fMCD simulations when considering large segmented volumes (whole liver, normal liver). In contrast, the Dmean to the small volume (∅=31) was systemically underestimated (12%-25%). For lungs, the "multiple DVK" and "multiple LDM" methods yielded a Dmean within 20% for the WP method and within 10% for the LL method. CONCLUSIONS All three methods showed a substantial degradation of the dose-volume histograms (DVHs) compared to fMCD simulations. The DVK and LDM methods performed almost equally well, with the "multiple DVK" method being more accurate in the lungs.
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Affiliation(s)
- Tien-Phong Pham
- Institut de Chimie Moléculaire de l'Université de Bourgogne (ICMUB) - UMR CNRS 6302, University of Burgundy, Dijon, France; Department of Nuclear Medicine, Georges-François Leclerc Cancer Centre, Dijon, France.
| | - Benoit Presles
- Institut de Chimie Moléculaire de l'Université de Bourgogne (ICMUB) - UMR CNRS 6302, University of Burgundy, Dijon, France
| | - Romain Popoff
- Institut de Chimie Moléculaire de l'Université de Bourgogne (ICMUB) - UMR CNRS 6302, University of Burgundy, Dijon, France; Department of Nuclear Medicine, Georges-François Leclerc Cancer Centre, Dijon, France
| | - Jean-Louis Alberini
- Institut de Chimie Moléculaire de l'Université de Bourgogne (ICMUB) - UMR CNRS 6302, University of Burgundy, Dijon, France; Department of Nuclear Medicine, Georges-François Leclerc Cancer Centre, Dijon, France
| | - Jean-Marc Vrigneaud
- Institut de Chimie Moléculaire de l'Université de Bourgogne (ICMUB) - UMR CNRS 6302, University of Burgundy, Dijon, France; Department of Nuclear Medicine, Georges-François Leclerc Cancer Centre, Dijon, France.
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Nodari G, Popoff R, Riedinger JM, Lopez O, Pellegrinelli J, Dygai-Cochet I, Tabouret-Viaud C, Presles B, Chevallier O, Gehin S, Gallet M, Latournerie M, Manfredi S, Loffroy R, Vrigneaud JM, Cochet A. Impact of contouring methods on pre-treatment and post-treatment dosimetry for the prediction of tumor control and survival in HCC patients treated with selective internal radiation therapy. EJNMMI Res 2021; 11:24. [PMID: 33687596 PMCID: PMC7943673 DOI: 10.1186/s13550-021-00766-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Accepted: 02/23/2021] [Indexed: 12/16/2022] Open
Abstract
INTRODUCTION The aim of this study was to evaluate the impact of the contouring methods on dose metrics and their predictive value on tumor control and survival, in both situations of pre-treatment and post-treatment dosimetry, for patients with advanced HCC treated with SIRT. METHODS Forty-eight patients who underwent SIRT between 2012 and 2020 were retrospectively included in this study. Target volumes were delineated using two methods: MRI-based contours manually drawn by a radiologist and then registered on SPECT/CT and PET/CT via deformable registration (Pre-CMRI and Post-CMRI), 99mTc-MAA-SPECT and 90Y-microspheres-PET 10% threshold contouring (Pre-CSPECT and Post-CPET). The mean absorbed dose (Dm) and the minimal absorbed dose delivered to 70% of the tumor volume (D70) were evaluated with both contouring methods; the tumor-to-normal liver uptake ratio (TNR) was evaluated with MRI-based contours only. Tumor response was assessed using the mRECIST criteria on the follow-up MRIs. RESULTS No significant differences were found for Dm and TNR between pre- and post-treatment. TNR evaluated with radiologic contours (Pre-CMRI and Post-CMRI) were predictive of tumor control at 6 months on pre- and post-treatment dosimetry (OR 5.9 and 7.1, respectively; p = 0.02 and 0.01). All dose metrics determined with both methods were predictive of overall survival (OS) on pre-treatment dosimetry, but only Dm with MRI-based contours was predictive of OS on post-treatment images with a median of 23 months for patients with a supramedian Dm versus 14 months for the others (p = 0.04). CONCLUSION In advanced HCC treated with SIRT, Dm and TNR determined with radiologic contours were predictive of tumor control and OS. This study shows that a rigorous clinical workflow (radiologic contours + registration on scintigraphic images) is feasible and should be prospectively considered for improving therapeutic strategy.
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Affiliation(s)
- Guillaume Nodari
- Department of Nuclear Medicine, Centre Georges-François Leclerc, Dijon, France.
| | - Romain Popoff
- Department of Nuclear Medicine, Centre Georges-François Leclerc, Dijon, France.,ImViA Laboratory, IFTIM Team, EA 7535, University of Burgundy, Dijon, France
| | - Jean Marc Riedinger
- Department of Nuclear Medicine, Centre Georges-François Leclerc, Dijon, France
| | - Olivier Lopez
- Department of Vascular and Interventional Radiology, University Hospital Dijon, Dijon, France
| | - Julie Pellegrinelli
- Department of Vascular and Interventional Radiology, University Hospital Dijon, Dijon, France
| | - Inna Dygai-Cochet
- Department of Nuclear Medicine, Centre Georges-François Leclerc, Dijon, France
| | | | - Benoit Presles
- ImViA Laboratory, IFTIM Team, EA 7535, University of Burgundy, Dijon, France
| | - Olivier Chevallier
- ImViA Laboratory, IFTIM Team, EA 7535, University of Burgundy, Dijon, France.,Department of Vascular and Interventional Radiology, University Hospital Dijon, Dijon, France
| | - Sophie Gehin
- Department of Vascular and Interventional Radiology, University Hospital Dijon, Dijon, France
| | - Matthieu Gallet
- Department of Nuclear Medicine, Centre Georges-François Leclerc, Dijon, France
| | | | - Sylvain Manfredi
- Department of Gastroenterology, University Hospital Dijon, Dijon, France
| | - Romaric Loffroy
- ImViA Laboratory, IFTIM Team, EA 7535, University of Burgundy, Dijon, France.,Department of Vascular and Interventional Radiology, University Hospital Dijon, Dijon, France
| | - Jean Marc Vrigneaud
- Department of Nuclear Medicine, Centre Georges-François Leclerc, Dijon, France.,ImViA Laboratory, IFTIM Team, EA 7535, University of Burgundy, Dijon, France
| | - Alexandre Cochet
- Department of Nuclear Medicine, Centre Georges-François Leclerc, Dijon, France.,ImViA Laboratory, IFTIM Team, EA 7535, University of Burgundy, Dijon, France
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