Recent advances and current landscape of software tools for image analysis and dosimetry in nuclear medicine.
Authors
Affiliations (7)
Affiliations (7)
- Nuclear Medicine Research Infrastructure (NuMeRI), Pretoria, South Africa.
- University of Pretoria, Pretoria, South Africa.
- Steve Biko Academic Hospital, Pretoria, South Africa.
- University of the Free State, Bloemfontein, South Africa.
- Nuclear Medicine Research Infrastructure (NuMeRI), Pretoria, South Africa. [email protected].
- University of Pretoria, Pretoria, South Africa. [email protected].
- Steve Biko Academic Hospital, Pretoria, South Africa. [email protected].
Abstract
Recent advancements in nuclear medicine, particularly in personalised radiopharmaceutical therapy, have emphasised the growing need for precise assessments of therapeutic safety and efficacy. These evaluations depend heavily on individual patient pharmacokinetics and dosimetry studies. Pharmacokinetics are typically assessed using whole-body SPECT/CT or PET/CT time-point imaging, preceded by rigorous calibration procedures to ensure the accuracy of absorbed dose calculations. The growing need for reliable imaging data has driven the development and adoption of various software tools aimed at optimising the processing, analysis, and dosimetry of nuclear medicine images. Open-source solutions are increasingly bridging the gap in accessibility, especially in resource-constrained environments, while AI-driven segmentation and time-activity curve modelling are emerging as critical innovations for improving workflow efficiency. Future efforts should prioritise validation, standardisation, and the development of robust tools tailored to complex dosimetry scenarios, including alpha and Auger therapies. This review evaluates several available software tools, both open-source and commercial, for processing calibration phantoms and patient images with an emphasis on quantitative analyses. It also examines tools used for post-imaging dosimetry. Key advancements in computational techniques are highlighted, including algorithms for dose calculation, computational models, and applications in deep learning. Furthermore, the review addresses existing limitations and ongoing efforts to enhance the accuracy, reproducibility, and clinical integration of these technologies. Future directions include integration of ultra-high-sensitivity detectors (e.g., long-axial-FOV PET and full-ring SPECT), wider adoption of standardised reconstruction and quantification workflows, incorporation of targeted alpha therapy and Auger models, improved uncertainty propagation, and routine implementation of accelerated clinical dosimetry pipelines. This manuscript aims to help support researchers, medical physicists, and clinicians in effectively adopting and applying these tools to improve outcomes in nuclear medicine practices.