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Ultra-fast Whole-body Bone Tomoscintigraphies Achieved with a High-sensitivity 360° CZT Camera and a Dedicated Deep-learning Noise Reduction Algorithm

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Date 2023 Dec 11
PMID 38082197
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Abstract

Methods: DLNR was applied on whole-body images recorded after the injection of 545 ± 33 MBq of [Tc]Tc-HDP in 19 patients (14 with bone metastasis) and reconstructed with 100%, 90%, 80%, 70%, 60%, 50%, 40%, and 30% of the original SPECT recording times.

Results: Irrespective of recording time, DLNR enhanced the contrast-to-noise ratios and slightly decreased the standardized uptake values of bone lesions. Except in one markedly obese patient, the quality of DLNR processed images remained good-to-excellent down to 60% of the recording time, corresponding to around 6 min SPECT-recording.

Conclusion: Ultra-fast SPECT recordings of 6 min can be achieved when DLNR is applied on whole-body bone 360° CZT-SPECT.

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References
1.
Desmonts C, Bouthiba M, Enilorac B, Nganoa C, Agostini D, Aide N . Evaluation of a new multipurpose whole-body CzT-based camera: comparison with a dual-head Anger camera and first clinical images. EJNMMI Phys. 2020; 7(1):18. PMC: 7078403. DOI: 10.1186/s40658-020-0284-5. View

2.
Melki S, Chawki M, Marie P, Imbert L, Verger A . Augmented planar bone scintigraphy obtained from a whole-body SPECT recording of less than 20 min with a high-sensitivity 360° CZT camera. Eur J Nucl Med Mol Imaging. 2019; 47(5):1329-1331. DOI: 10.1007/s00259-019-04525-y. View

3.
Weyts K, Lasnon C, Ciappuccini R, Lequesne J, Corroyer-Dulmont A, Quak E . Artificial intelligence-based PET denoising could allow a two-fold reduction in [F]FDG PET acquisition time in digital PET/CT. Eur J Nucl Med Mol Imaging. 2022; 49(11):3750-3760. PMC: 9399218. DOI: 10.1007/s00259-022-05800-1. View

4.
Sohlberg A, Kangasmaa T, Constable C, Tikkakoski A . Comparison of deep learning-based denoising methods in cardiac SPECT. EJNMMI Phys. 2023; 10(1):9. PMC: 9908801. DOI: 10.1186/s40658-023-00531-0. View

5.
Imbert L, Poussier S, Franken P, Songy B, Verger A, Morel O . Compared performance of high-sensitivity cameras dedicated to myocardial perfusion SPECT: a comprehensive analysis of phantom and human images. J Nucl Med. 2012; 53(12):1897-903. DOI: 10.2967/jnumed.112.107417. View