Optimization of fundamental parameters in routine production of 90Y-hydroxyapatite for radiosynovectomy

Davarpanah, Mohammad Reza; Khoshhosn, H. A.; Harati, Mohsen; Nosrati, S. Attar; Zoghi, M.; Mazidi, Mohammad; Maragheh, Mohammad Ghannadi

doi:10.1007/s10967-014-3326-4

Cited by 5 publications

(3 citation statements)

References 25 publications

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“…It has been found that during radiolabeling process, different reaction parameters directly affect the nal RCY [12,24]. The parameters which can notably affect the radiolabeling e ciency are the initial radioactivity of the radionuclide, pH, time and temperature of radiolabeling reaction [25].…”

Section: Resultsmentioning

confidence: 99%

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The Central Composite Design and Artificial Neural Network in Optimization and Modeling of Radiolabeling Process of 177Lu-hydroxyapatite as a Potential Radiosynovectomy Agent

Nosrati,

Salahinejad,

Aboudzadeh

et al. 2024

Preprint

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Background A promising material used in radiation synovectomy of small joints is hydroxyapatite which has been labeled with 177Lu. During the design and production of radiopharmaceuticals, the condition of the radiolabeling process, directly influences the radiochemical yield and consequently the quality of the final product so this process necessitates a precise optimization. In this investigation, central composite design based on response surface methodology and artificial neural networks are applied to build predictive models and explore the effect of key parameters in the radiolabeling process of hydroxyapatite with 177Lu radionuclide. The variables that directly affected the labeling reaction were the initial 177Lu radionuclide concentration, pH, radiolabeling reaction time and temperature. Results Based on the validation data set, the statistical values demonstrate that the artificial neural networks model performs better than the response surface methodology model. The artificial neural networks model has a small mean squared error (9.08 artificial neural networks < 12.36 response surface methodology) and a high coefficient of determination (R2: 0.99 artificial neural networks > 0.93 response surface methodology). In addition, the maximum radiochemical yield is found at the initial concentration of 177Lu radionuclide = 0.128 megabecquerel (MBq), pH = 6.1, and temperature = 38.9 (oC), by performing the response surface methodology. Conclusion The ability to generate more data with fewer experiments for optimization and improved production is a pertinent advantage of multivariate optimization methods over traditional methods in radiation-related activities. The central composite design optimization and artificial neural networks modeling are successfully utilized to create prediction models and investigate the impact of critical variables in the radiolabeling of hydroxyapatite with 177Lu radionuclide.

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Section: Resultsmentioning

confidence: 99%

“…The radiolabeling of hydroxyapatite with 177 Lu was carried out based on the similar work [12]. For this purpose, a reaction vial was prepared by transferring the weighted amount (40 mg) of hydroxyapatite precursor.…”

Section: Radiolabeling Of Hydroxyapatite With 177 Lumentioning

confidence: 99%

The Central Composite Design and Artificial Neural Network in Optimization and Modeling of Radiolabeling Process of 177Lu-hydroxyapatite as a Potential Radiosynovectomy Agent

Nosrati,

Salahinejad,

Aboudzadeh

et al. 2024

Preprint

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“…The obtained results showed that the 90 Y‐HA can be potentially used as an ideal agent for radiosynovectomy of the joints. Davarpanah et al optimized fundamental parameters in routine production of 90 Y‐HA for radiosynovectomy. First human study and initial Indian experience in the treatment of painful synovitis and recurrent joint effusion of knee joints in rheumatoid arthritis using 177 Lu‐labeled HA was reported by Shinto and co‐workers .…”

Section: Radiolabeled Nanocarriers For Nuclear Molecular Imaging and mentioning

confidence: 99%

An overview of nanoscale radionuclides and radiolabeled nanomaterials commonly used for nuclear molecular imaging and therapeutic functions

Farzin¹,

Sheibani²,

Moassesi³

et al. 2018

J Biomedical Materials Res

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Preparation of Pt-doped hydroxyapatite via wet co-precipitation method

Attar Nosrati,

Aboudzadeh,

Amiri

et al. 2024

J Aust Ceram Soc

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Optimization of fundamental parameters in routine production of 90Y-hydroxyapatite for radiosynovectomy

Cited by 5 publications

References 25 publications

The Central Composite Design and Artificial Neural Network in Optimization and Modeling of Radiolabeling Process of 177Lu-hydroxyapatite as a Potential Radiosynovectomy Agent

The Central Composite Design and Artificial Neural Network in Optimization and Modeling of Radiolabeling Process of 177Lu-hydroxyapatite as a Potential Radiosynovectomy Agent

An overview of nanoscale radionuclides and radiolabeled nanomaterials commonly used for nuclear molecular imaging and therapeutic functions

Preparation of Pt-doped hydroxyapatite via wet co-precipitation method

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