Cargando…
Artificial intelligence for reduced dose 18F-FDG PET examinations: a real-world deployment through a standardized framework and business case assessment
BACKGROUND: To determine whether artificial intelligence (AI) processed PET/CT images of reduced by one-third of 18-F-FDG activity compared to the standard injected dose, were non-inferior to native scans and if so to assess the potential impact of commercialization. MATERIALS AND METHODS: SubtlePET...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7943690/ https://www.ncbi.nlm.nih.gov/pubmed/33687602 http://dx.doi.org/10.1186/s40658-021-00374-7 |
_version_ | 1783662543605071872 |
---|---|
author | Katsari, Katia Penna, Daniele Arena, Vincenzo Polverari, Giulia Ianniello, Annarita Italiano, Domenico Milani, Rolando Roncacci, Alessandro Illing, Rowland O. Pelosi, Ettore |
author_facet | Katsari, Katia Penna, Daniele Arena, Vincenzo Polverari, Giulia Ianniello, Annarita Italiano, Domenico Milani, Rolando Roncacci, Alessandro Illing, Rowland O. Pelosi, Ettore |
author_sort | Katsari, Katia |
collection | PubMed |
description | BACKGROUND: To determine whether artificial intelligence (AI) processed PET/CT images of reduced by one-third of 18-F-FDG activity compared to the standard injected dose, were non-inferior to native scans and if so to assess the potential impact of commercialization. MATERIALS AND METHODS: SubtlePET™ AI was introduced in a PET/CT center in Italy. Eligible patients referred for 18F-FDG PET/CT were prospectively enrolled. Administered 18F-FDG was reduced to two-thirds of standard dose. Patients underwent one low-dose CT and two sequential PET scans; “PET-processed” with reduced dose and standard acquisition time, and “PET-native” with an elapsed time to simulate standard acquisition time and dose. PET-processed images were reconstructed using SubtlePET™. PET-native images were defined as the standard of reference. The datasets were anonymized and independently evaluated in random order by four blinded readers. The evaluation included subjective image quality (IQ) assessment, lesion detectability, and assessment of business benefits. RESULTS: From February to April 2020, 61 patients were prospectively enrolled. Subjective IQ was not significantly different between datasets (4.62±0.23, p=0.237) for all scanner models, with “almost perfect” inter-reader agreement. There was no significant difference between datasets in lesions’ detectability, target lesion mean SUV(max) value, and liver mean SUV(mean) value (182.75/181.75 [SD:0.71], 9.8/11.4 [SD:1.13], 2.1/1.9 [SD:0.14] respectively). No false-positive lesions were reported in PET-processed examinations. Agreed SubtlePET™ price per examination was 15-20% of FDG savings. CONCLUSION: This is the first real-world study to demonstrate the non-inferiority of AI processed 18F-FDG PET/CT examinations obtained with 66% standard dose and a methodology to define the AI solution price. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40658-021-00374-7. |
format | Online Article Text |
id | pubmed-7943690 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-79436902021-03-28 Artificial intelligence for reduced dose 18F-FDG PET examinations: a real-world deployment through a standardized framework and business case assessment Katsari, Katia Penna, Daniele Arena, Vincenzo Polverari, Giulia Ianniello, Annarita Italiano, Domenico Milani, Rolando Roncacci, Alessandro Illing, Rowland O. Pelosi, Ettore EJNMMI Phys Original Research BACKGROUND: To determine whether artificial intelligence (AI) processed PET/CT images of reduced by one-third of 18-F-FDG activity compared to the standard injected dose, were non-inferior to native scans and if so to assess the potential impact of commercialization. MATERIALS AND METHODS: SubtlePET™ AI was introduced in a PET/CT center in Italy. Eligible patients referred for 18F-FDG PET/CT were prospectively enrolled. Administered 18F-FDG was reduced to two-thirds of standard dose. Patients underwent one low-dose CT and two sequential PET scans; “PET-processed” with reduced dose and standard acquisition time, and “PET-native” with an elapsed time to simulate standard acquisition time and dose. PET-processed images were reconstructed using SubtlePET™. PET-native images were defined as the standard of reference. The datasets were anonymized and independently evaluated in random order by four blinded readers. The evaluation included subjective image quality (IQ) assessment, lesion detectability, and assessment of business benefits. RESULTS: From February to April 2020, 61 patients were prospectively enrolled. Subjective IQ was not significantly different between datasets (4.62±0.23, p=0.237) for all scanner models, with “almost perfect” inter-reader agreement. There was no significant difference between datasets in lesions’ detectability, target lesion mean SUV(max) value, and liver mean SUV(mean) value (182.75/181.75 [SD:0.71], 9.8/11.4 [SD:1.13], 2.1/1.9 [SD:0.14] respectively). No false-positive lesions were reported in PET-processed examinations. Agreed SubtlePET™ price per examination was 15-20% of FDG savings. CONCLUSION: This is the first real-world study to demonstrate the non-inferiority of AI processed 18F-FDG PET/CT examinations obtained with 66% standard dose and a methodology to define the AI solution price. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40658-021-00374-7. Springer International Publishing 2021-03-09 /pmc/articles/PMC7943690/ /pubmed/33687602 http://dx.doi.org/10.1186/s40658-021-00374-7 Text en © The Author(s) 2021 Open AccessThis 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/. |
spellingShingle | Original Research Katsari, Katia Penna, Daniele Arena, Vincenzo Polverari, Giulia Ianniello, Annarita Italiano, Domenico Milani, Rolando Roncacci, Alessandro Illing, Rowland O. Pelosi, Ettore Artificial intelligence for reduced dose 18F-FDG PET examinations: a real-world deployment through a standardized framework and business case assessment |
title | Artificial intelligence for reduced dose 18F-FDG PET examinations: a real-world deployment through a standardized framework and business case assessment |
title_full | Artificial intelligence for reduced dose 18F-FDG PET examinations: a real-world deployment through a standardized framework and business case assessment |
title_fullStr | Artificial intelligence for reduced dose 18F-FDG PET examinations: a real-world deployment through a standardized framework and business case assessment |
title_full_unstemmed | Artificial intelligence for reduced dose 18F-FDG PET examinations: a real-world deployment through a standardized framework and business case assessment |
title_short | Artificial intelligence for reduced dose 18F-FDG PET examinations: a real-world deployment through a standardized framework and business case assessment |
title_sort | artificial intelligence for reduced dose 18f-fdg pet examinations: a real-world deployment through a standardized framework and business case assessment |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7943690/ https://www.ncbi.nlm.nih.gov/pubmed/33687602 http://dx.doi.org/10.1186/s40658-021-00374-7 |
work_keys_str_mv | AT katsarikatia artificialintelligenceforreduceddose18ffdgpetexaminationsarealworlddeploymentthroughastandardizedframeworkandbusinesscaseassessment AT pennadaniele artificialintelligenceforreduceddose18ffdgpetexaminationsarealworlddeploymentthroughastandardizedframeworkandbusinesscaseassessment AT arenavincenzo artificialintelligenceforreduceddose18ffdgpetexaminationsarealworlddeploymentthroughastandardizedframeworkandbusinesscaseassessment AT polverarigiulia artificialintelligenceforreduceddose18ffdgpetexaminationsarealworlddeploymentthroughastandardizedframeworkandbusinesscaseassessment AT iannielloannarita artificialintelligenceforreduceddose18ffdgpetexaminationsarealworlddeploymentthroughastandardizedframeworkandbusinesscaseassessment AT italianodomenico artificialintelligenceforreduceddose18ffdgpetexaminationsarealworlddeploymentthroughastandardizedframeworkandbusinesscaseassessment AT milanirolando artificialintelligenceforreduceddose18ffdgpetexaminationsarealworlddeploymentthroughastandardizedframeworkandbusinesscaseassessment AT roncaccialessandro artificialintelligenceforreduceddose18ffdgpetexaminationsarealworlddeploymentthroughastandardizedframeworkandbusinesscaseassessment AT illingrowlando artificialintelligenceforreduceddose18ffdgpetexaminationsarealworlddeploymentthroughastandardizedframeworkandbusinesscaseassessment AT pelosiettore artificialintelligenceforreduceddose18ffdgpetexaminationsarealworlddeploymentthroughastandardizedframeworkandbusinesscaseassessment |