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Updated: Nov 25, 2025
Whole-body PET/MRI of Pediatric Patients: The Details That Matter
Published on: December 19, 2017
Reducing scan time of paediatric 99mTc-DMSA SPECT via deep learning
1Department of Nuclear Medicine, Chang Gung Memorial Hospital, No. 5, Fuxing Street, Gueishan Dist., Taoyuan, 33305, Taiwan.
Aim:
To investigate the feasibility of reducing the scan time of paediatric technetium 99m (99mTc) dimercaptosuccinic acid (DMSA) single-photon-emission computed tomographic (SPECT) using a deep learning (DL) method.
Material And Methods:
A total of 112 paediatric 99mTc-DMSA renal SPECT scans were analysed retrospectively. Of the 112 examinations, 88 (84 for training and four for validation) were used to train a DL-based model that could generate full-acquisition-time reconstructed SPECT images from half-time acquisition. The remaining 24 examinations were used to evaluate the performance of the trained model.
Results:
DL-based SPECT images obtained from half-time acquisition have image quality similar to the standard clinical SPECT images obtained from full-acquisition-time acquisition. Moreover, the accuracy, sensitivity and specificity of the DL-based SPECT images for detection of affected kidneys were 91.7%, 83.3%, and 100%, respectively.
Conclusion:
These preliminary results suggest that DL has the potential to reduce the scan time of paediatric 99mTc-DMSA SPECT imaging while maintaining diagnostic accuracy.
