This study aimed to determine whether the whole-body bone Single Photon Emission Computed Tomography (SPECT) recording times of around 10 min, routinely provided by a high-sensitivity 360° cadmium and zinc telluride (CZT) camera, can be further reduced by a deep-learning noise reduction (DLNR) algorithm.
Methods: DLNR was applied on whole-body images recorded after the injection of 545 ± 33 MBq of [99mTc]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.
Keywords: Bone scintigraphy; Deep learning; Recording time; Whole-body CZT-camera.
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.