Evaluation of the prostate cancer and its metastases in the [68Ga]Ga-PSMA PET/CT images: deep learning method vs. conventional PET/CT processing
This study highlights significant improvements in image quality and lesion detection capabilities through the integration of DLAC in [ 68 Ga]Ga-PSMA PET imaging. This innovative approach not only addresses challenges such as bladder radioactivity but also represents a promising method to minimize patient radiation exposure by integrating low-dose computed tomography and DLAC, ultimately improving diagnostic accuracy and patient outcomes.
Authors
- Zahra Bakhshi Golestani
- Masoumeh Dorri Giv
- Emran Askari (ORCID: https://orcid.org/0000-0002-2973-2251)
- Vahid Reza Dabbagh Kakhki (ORCID: https://orcid.org/0000-0001-7222-786X)
- Nasrin Raeisi (ORCID: https://orcid.org/0009-0005-2087-2169)
- Leila Alipour Firouzabad
- Amin Saber Tanha (ORCID: https://orcid.org/0009-0008-0290-0412)
- Amir Hossein Dabbagh Kakhki
- Shahrokh Naseri
- Atena Aghaei
- Hossein Arabi (ORCID: https://orcid.org/0000-0001-6526-0960)
Institutions
- Iran University of Medical Sciences (IR)
- Mashhad University of Medical Sciences (IR)
- GTx (United States) (US)
- University Hospital of Geneva (CH)
- Ghaem Hospital (IR)
- Shahid Beheshti University (IR)
Publication Details
- Journal
- Nuclear Medicine Communications
- Published
- 2024-09-03
- DOI
- https://doi.org/10.1097/mnm.0000000000001891
- Citations
- 4
- Primary Topic
- Prostate Cancer Treatment and Research
- Type
- article
- Field-Weighted Citation Impact
- 1.68