Accurate patient alignment without unnecessary imaging using patient-specific 3D CT images synthesized from 2D kV images
Abstract Background In radiotherapy, 2D orthogonally projected kV images are used for patient alignment when 3D-on-board imaging (OBI) is unavailable. However, tumor visibility is constrained due to the projection of patient’s anatomy onto a 2D plane, potentially leading to substantial setup errors....
Saved in:
| Main Authors: | , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-11-01
|
| Series: | Communications Medicine |
| Online Access: | https://doi.org/10.1038/s43856-024-00672-y |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850128948565901312 |
|---|---|
| author | Yuzhen Ding Jason M. Holmes Hongying Feng Baoxin Li Lisa A. McGee Jean-Claude M. Rwigema Sujay A. Vora William W. Wong Daniel J. Ma Robert L. Foote Samir H. Patel Wei Liu |
| author_facet | Yuzhen Ding Jason M. Holmes Hongying Feng Baoxin Li Lisa A. McGee Jean-Claude M. Rwigema Sujay A. Vora William W. Wong Daniel J. Ma Robert L. Foote Samir H. Patel Wei Liu |
| author_sort | Yuzhen Ding |
| collection | DOAJ |
| description | Abstract Background In radiotherapy, 2D orthogonally projected kV images are used for patient alignment when 3D-on-board imaging (OBI) is unavailable. However, tumor visibility is constrained due to the projection of patient’s anatomy onto a 2D plane, potentially leading to substantial setup errors. In treatment room with 3D-OBI such as cone beam CT (CBCT), the field of view (FOV) of CBCT is limited with unnecessarily high imaging dose. A solution to this dilemma is to reconstruct 3D CT from kV images obtained at the treatment position. Methods We propose a dual-models framework built with hierarchical ViT blocks. Unlike a proof-of-concept approach, our framework considers kV images acquired by 2D imaging devices in the treatment room as the solo input and can synthesize accurate, full-size 3D CT within milliseconds. Results We demonstrate the feasibility of the proposed approach on 10 patients with head and neck (H&N) cancer using image quality (MAE: < 45HU), dosimetric accuracy (Gamma passing rate ((2%/2 mm/10%): > 97%) and patient position uncertainty (shift error: < 0.4 mm). Conclusions The proposed framework can generate accurate 3D CT faithfully mirroring patient position effectively, thus substantially improving patient setup accuracy, keeping imaging dose minimal, and maintaining treatment veracity. |
| format | Article |
| id | doaj-art-b76a854caba441a88fc17eb6c0163323 |
| institution | OA Journals |
| issn | 2730-664X |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Medicine |
| spelling | doaj-art-b76a854caba441a88fc17eb6c01633232025-08-20T02:33:08ZengNature PortfolioCommunications Medicine2730-664X2024-11-014111010.1038/s43856-024-00672-yAccurate patient alignment without unnecessary imaging using patient-specific 3D CT images synthesized from 2D kV imagesYuzhen Ding0Jason M. Holmes1Hongying Feng2Baoxin Li3Lisa A. McGee4Jean-Claude M. Rwigema5Sujay A. Vora6William W. Wong7Daniel J. Ma8Robert L. Foote9Samir H. Patel10Wei Liu11Department of Radiation Oncology, Mayo ClinicDepartment of Radiation Oncology, Mayo ClinicDepartment of Radiation Oncology, Mayo ClinicSchool of Computing and Augmented Intelligence, Arizona State UniversityDepartment of Radiation Oncology, Mayo ClinicDepartment of Radiation Oncology, Mayo ClinicDepartment of Radiation Oncology, Mayo ClinicDepartment of Radiation Oncology, Mayo ClinicDepartment of Radiation Oncology, Mayo ClinicDepartment of Radiation Oncology, Mayo ClinicDepartment of Radiation Oncology, Mayo ClinicDepartment of Radiation Oncology, Mayo ClinicAbstract Background In radiotherapy, 2D orthogonally projected kV images are used for patient alignment when 3D-on-board imaging (OBI) is unavailable. However, tumor visibility is constrained due to the projection of patient’s anatomy onto a 2D plane, potentially leading to substantial setup errors. In treatment room with 3D-OBI such as cone beam CT (CBCT), the field of view (FOV) of CBCT is limited with unnecessarily high imaging dose. A solution to this dilemma is to reconstruct 3D CT from kV images obtained at the treatment position. Methods We propose a dual-models framework built with hierarchical ViT blocks. Unlike a proof-of-concept approach, our framework considers kV images acquired by 2D imaging devices in the treatment room as the solo input and can synthesize accurate, full-size 3D CT within milliseconds. Results We demonstrate the feasibility of the proposed approach on 10 patients with head and neck (H&N) cancer using image quality (MAE: < 45HU), dosimetric accuracy (Gamma passing rate ((2%/2 mm/10%): > 97%) and patient position uncertainty (shift error: < 0.4 mm). Conclusions The proposed framework can generate accurate 3D CT faithfully mirroring patient position effectively, thus substantially improving patient setup accuracy, keeping imaging dose minimal, and maintaining treatment veracity.https://doi.org/10.1038/s43856-024-00672-y |
| spellingShingle | Yuzhen Ding Jason M. Holmes Hongying Feng Baoxin Li Lisa A. McGee Jean-Claude M. Rwigema Sujay A. Vora William W. Wong Daniel J. Ma Robert L. Foote Samir H. Patel Wei Liu Accurate patient alignment without unnecessary imaging using patient-specific 3D CT images synthesized from 2D kV images Communications Medicine |
| title | Accurate patient alignment without unnecessary imaging using patient-specific 3D CT images synthesized from 2D kV images |
| title_full | Accurate patient alignment without unnecessary imaging using patient-specific 3D CT images synthesized from 2D kV images |
| title_fullStr | Accurate patient alignment without unnecessary imaging using patient-specific 3D CT images synthesized from 2D kV images |
| title_full_unstemmed | Accurate patient alignment without unnecessary imaging using patient-specific 3D CT images synthesized from 2D kV images |
| title_short | Accurate patient alignment without unnecessary imaging using patient-specific 3D CT images synthesized from 2D kV images |
| title_sort | accurate patient alignment without unnecessary imaging using patient specific 3d ct images synthesized from 2d kv images |
| url | https://doi.org/10.1038/s43856-024-00672-y |
| work_keys_str_mv | AT yuzhending accuratepatientalignmentwithoutunnecessaryimagingusingpatientspecific3dctimagessynthesizedfrom2dkvimages AT jasonmholmes accuratepatientalignmentwithoutunnecessaryimagingusingpatientspecific3dctimagessynthesizedfrom2dkvimages AT hongyingfeng accuratepatientalignmentwithoutunnecessaryimagingusingpatientspecific3dctimagessynthesizedfrom2dkvimages AT baoxinli accuratepatientalignmentwithoutunnecessaryimagingusingpatientspecific3dctimagessynthesizedfrom2dkvimages AT lisaamcgee accuratepatientalignmentwithoutunnecessaryimagingusingpatientspecific3dctimagessynthesizedfrom2dkvimages AT jeanclaudemrwigema accuratepatientalignmentwithoutunnecessaryimagingusingpatientspecific3dctimagessynthesizedfrom2dkvimages AT sujayavora accuratepatientalignmentwithoutunnecessaryimagingusingpatientspecific3dctimagessynthesizedfrom2dkvimages AT williamwwong accuratepatientalignmentwithoutunnecessaryimagingusingpatientspecific3dctimagessynthesizedfrom2dkvimages AT danieljma accuratepatientalignmentwithoutunnecessaryimagingusingpatientspecific3dctimagessynthesizedfrom2dkvimages AT robertlfoote accuratepatientalignmentwithoutunnecessaryimagingusingpatientspecific3dctimagessynthesizedfrom2dkvimages AT samirhpatel accuratepatientalignmentwithoutunnecessaryimagingusingpatientspecific3dctimagessynthesizedfrom2dkvimages AT weiliu accuratepatientalignmentwithoutunnecessaryimagingusingpatientspecific3dctimagessynthesizedfrom2dkvimages |