Medical Imaging Biomarker Discovery and Integration Towards AI-Based Personalized Radiotherapy
Intensity-modulated radiation therapy (IMRT) has been used for high-accurate physical dose distribution sculpture and employed to modulate different dose levels into Gross Tumor Volume (GTV), Clinical Target Volume (CTV) and Planning Target Volume (PTV). GTV, CTV and PTV can be prescribed at differe...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-01-01
|
| Series: | Frontiers in Oncology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2021.764665/full |
| _version_ | 1798025430806036480 |
|---|---|
| author | Yaru Pang Hui Wang He Li |
| author_facet | Yaru Pang Hui Wang He Li |
| author_sort | Yaru Pang |
| collection | DOAJ |
| description | Intensity-modulated radiation therapy (IMRT) has been used for high-accurate physical dose distribution sculpture and employed to modulate different dose levels into Gross Tumor Volume (GTV), Clinical Target Volume (CTV) and Planning Target Volume (PTV). GTV, CTV and PTV can be prescribed at different dose levels, however, there is an emphasis that their dose distributions need to be uniform, despite the fact that most types of tumour are heterogeneous. With traditional radiomics and artificial intelligence (AI) techniques, we can identify biological target volume from functional images against conventional GTV derived from anatomical imaging. Functional imaging, such as multi parameter MRI and PET can be used to implement dose painting, which allows us to achieve dose escalation by increasing doses in certain areas that are therapy-resistant in the GTV and reducing doses in less aggressive areas. In this review, we firstly discuss several quantitative functional imaging techniques including PET-CT and multi-parameter MRI. Furthermore, theoretical and experimental comparisons for dose painting by contours (DPBC) and dose painting by numbers (DPBN), along with outcome analysis after dose painting are provided. The state-of-the-art AI-based biomarker diagnosis techniques is reviewed. Finally, we conclude major challenges and future directions in AI-based biomarkers to improve cancer diagnosis and radiotherapy treatment. |
| first_indexed | 2024-04-11T18:18:57Z |
| format | Article |
| id | doaj.art-77ab4eae7282453eb031e6cf34bbce8d |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-04-11T18:18:57Z |
| publishDate | 2022-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-77ab4eae7282453eb031e6cf34bbce8d2022-12-22T04:09:49ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2022-01-011110.3389/fonc.2021.764665764665Medical Imaging Biomarker Discovery and Integration Towards AI-Based Personalized RadiotherapyYaru Pang0Hui Wang1He Li2Department of Medical Physics and Biomedical Engineering, University College London, London, United KingdomDepartment of Chemical Engineering, University College London, London, United KingdomDepartment of Engineering, University of Cambridge, Cambridge, United KingdomIntensity-modulated radiation therapy (IMRT) has been used for high-accurate physical dose distribution sculpture and employed to modulate different dose levels into Gross Tumor Volume (GTV), Clinical Target Volume (CTV) and Planning Target Volume (PTV). GTV, CTV and PTV can be prescribed at different dose levels, however, there is an emphasis that their dose distributions need to be uniform, despite the fact that most types of tumour are heterogeneous. With traditional radiomics and artificial intelligence (AI) techniques, we can identify biological target volume from functional images against conventional GTV derived from anatomical imaging. Functional imaging, such as multi parameter MRI and PET can be used to implement dose painting, which allows us to achieve dose escalation by increasing doses in certain areas that are therapy-resistant in the GTV and reducing doses in less aggressive areas. In this review, we firstly discuss several quantitative functional imaging techniques including PET-CT and multi-parameter MRI. Furthermore, theoretical and experimental comparisons for dose painting by contours (DPBC) and dose painting by numbers (DPBN), along with outcome analysis after dose painting are provided. The state-of-the-art AI-based biomarker diagnosis techniques is reviewed. Finally, we conclude major challenges and future directions in AI-based biomarkers to improve cancer diagnosis and radiotherapy treatment.https://www.frontiersin.org/articles/10.3389/fonc.2021.764665/fullfunctional imagingradiotherapypersonalized radiation dosedose painting by contoursdose painting by numbers |
| spellingShingle | Yaru Pang Hui Wang He Li Medical Imaging Biomarker Discovery and Integration Towards AI-Based Personalized Radiotherapy Frontiers in Oncology functional imaging radiotherapy personalized radiation dose dose painting by contours dose painting by numbers |
| title | Medical Imaging Biomarker Discovery and Integration Towards AI-Based Personalized Radiotherapy |
| title_full | Medical Imaging Biomarker Discovery and Integration Towards AI-Based Personalized Radiotherapy |
| title_fullStr | Medical Imaging Biomarker Discovery and Integration Towards AI-Based Personalized Radiotherapy |
| title_full_unstemmed | Medical Imaging Biomarker Discovery and Integration Towards AI-Based Personalized Radiotherapy |
| title_short | Medical Imaging Biomarker Discovery and Integration Towards AI-Based Personalized Radiotherapy |
| title_sort | medical imaging biomarker discovery and integration towards ai based personalized radiotherapy |
| topic | functional imaging radiotherapy personalized radiation dose dose painting by contours dose painting by numbers |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2021.764665/full |
| work_keys_str_mv | AT yarupang medicalimagingbiomarkerdiscoveryandintegrationtowardsaibasedpersonalizedradiotherapy AT huiwang medicalimagingbiomarkerdiscoveryandintegrationtowardsaibasedpersonalizedradiotherapy AT heli medicalimagingbiomarkerdiscoveryandintegrationtowardsaibasedpersonalizedradiotherapy |