Jiao, Jieqing;
Heeman, Fiona;
Dixon, Rachael;
Wimberley, Catriona;
Alves, Isadora Lopes;
Gispert, Juan Domingo;
Lammertsma, Adriaan A;
... Barkhof, Frederik; + view all
(2023)
NiftyPAD-Novel Python Package for Quantitative Analysis of Dynamic PET Data.
Neuroinformatics
10.1007/s12021-022-09616-0.
(In press).
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Abstract
Current PET datasets are becoming larger, thereby increasing the demand for fast and reproducible processing pipelines. This paper presents a freely available, open source, Python-based software package called NiftyPAD, for versatile analyses of static, full or dual-time window dynamic brain PET data. The key novelties of NiftyPAD are the analyses of dual-time window scans with reference input processing, pharmacokinetic modelling with shortened PET acquisitions through the incorporation of arterial spin labelling (ASL)-derived relative perfusion measures, as well as optional PET data-based motion correction. Results obtained with NiftyPAD were compared with the well-established software packages PPET and QModeling for a range of kinetic models. Clinical data from eight subjects scanned with four different amyloid tracers were used to validate the computational performance. NiftyPAD achieved R2> 0.999 correlation with PPET, with absolute difference ∼ 10 - 2 for linearised Logan and MRTM2 methods, and R2> 0.999999 correlation with QModeling, with absolute difference ∼ 10 - 4 for basis function based SRTM and SRTM2 models. For the recently published SRTM ASL method, which is unavailable in existing software packages, high correlations with negligible bias were observed with the full scan SRTM in terms of non-displaceable binding potential (R2= 0.96), indicating reliable model implementation in NiftyPAD. Together, these findings illustrate that NiftyPAD is versatile, flexible, and produces comparable results with established software packages for quantification of dynamic PET data. It is freely available (https://github.com/AMYPAD/NiftyPAD), and allows for multi-platform usage. The modular setup makes adding new functionalities easy, and the package is lightweight with minimal dependencies, making it easy to use and integrate into existing processing pipelines.
| Type: | Article |
|---|---|
| Title: | NiftyPAD-Novel Python Package for Quantitative Analysis of Dynamic PET Data |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/s12021-022-09616-0 |
| Publisher version: | https://doi.org/10.1007/s12021-022-09616-0 |
| Language: | English |
| Additional information: | This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
| Keywords: | Science & Technology, Technology, Life Sciences & Biomedicine, Computer Science, Interdisciplinary Applications, Neurosciences, Computer Science, Neurosciences & Neurology, NiftyPAD, PET, Pharmacokinetic analysis, Reference input-based modelling, Python package, POSITRON-EMISSION-TOMOGRAPHY, REFERENCE TISSUE MODEL, KINETIC-ANALYSIS, BINDING |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Brain Repair and Rehabilitation UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Neurodegenerative Diseases |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10166743 |
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