{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T06:49:42Z","timestamp":1792046982975,"version":"4.4.0"},"reference-count":36,"publisher":"IOP Publishing","issue":"20","license":[{"start":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T00:00:00Z","timestamp":1792022400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/publishingsupport.iopscience.iop.org\/iop-standard\/v1"},{"start":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T00:00:00Z","timestamp":1792022400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"name":"Natural Science Foundation of Guangdong Province","award":["Grant No. 2024A1515010523"],"award-info":[{"award-number":["Grant No. 2024A1515010523"]}]},{"name":"Natural Science Foundation of Heilongjiang Province","award":["Grant No. PL2025T800"],"award-info":[{"award-number":["Grant No. PL2025T800"]}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Phys. Med. Biol."],"published-print":{"date-parts":[[2026,10,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    <jats:italic>Objective.<\/jats:italic>\n                    To develop a conditional vector-quantized (VQ) diffusion-based dynamic cone beam computed tomography imaging framework using dual-view x-ray projections for accurate reconstruction of respiratory-induced lung tumor motion, with the potential to enable four-dimensional (4D) target verification during lung radiotherapy.\n                    <jats:italic>Methods.<\/jats:italic>\n                    Patient-specific respiratory motion models were constructed from planning 4D- computed tomography(CT) images using deformable image registration and principal component analysis (PCA). Synthetic DVFs were generated by sampling PCA coefficients and applied to the reference-phase CT images to produce dynamic three-dimensional (3D) volumes, from which paired dual-view DRRs were generated. A conditional VQ diffusion framework was developed, consisting of separate two-dimensional and 3D vector quantized variational autoencoder s for encoding DRRs and DVFs into discrete latent representations, followed by a conditional diffusion model to learn the mapping from x-ray projection features to deformation vector field (DVF) latent representations. During inference, dual-view x-ray projections were encoded and processed by the conditional diffusion model to estimate DVFs, which were then used to deform the reference CT image and reconstruct temporally resolved 3D volumes.\n                    <jats:italic>Results.<\/jats:italic>\n                    The simulation study demonstrates that the estimated DVFs effectively captured the respiratory-induced deformation of lung tumors, and the reconstructed dynamic volume CT images demonstrated accurate anatomical motion characteristics across respiratory phases.\n                    <jats:italic>Conclusion.<\/jats:italic>\n                    The proposed patient-specific VQ diffusion framework enables accurate estimation of respiratory-induced lung tumor motion from dual-view x-ray projections and facilitates the high-temporal-resolution dynamic volume CT reconstruction. The results demonstrate its potential as an image-guided solution for tumor motion tracking in lung tumor radiotherapy.\n                  <\/jats:p>","DOI":"10.1088\/1361-6560\/aeb062","type":"journal-article","created":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T22:51:51Z","timestamp":1791240711000},"page":"205005","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["X-ray projection-guided deformation vector field estimation and dynamic CBCT imaging using patient-specific vector-quantized diffusion"],"prefix":"10.1088","volume":"71","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-0917-6473","authenticated-orcid":true,"given":"Zifeng","family":"Li","sequence":"first","affiliation":[{"name":"Southern Medical University"},{"name":"Southern Medical University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongqi","family":"Zhu","sequence":"additional","affiliation":[{"name":"Southern Medical University"},{"name":"Southern Medical University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daochi","family":"Qu","sequence":"additional","affiliation":[{"name":"Southern Medical University"},{"name":"Southern Medical University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhanghua","family":"Luo","sequence":"additional","affiliation":[{"name":"Southern Medical University"},{"name":"Southern Medical University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feng","family":"Chi","sequence":"additional","affiliation":[{"name":"Sun Yat-sen University Cancer Center"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5227-6429","authenticated-orcid":false,"given":"Hua","family":"Zhang","sequence":"additional","affiliation":[{"name":"Southern Medical University"},{"name":"Southern Medical University"},{"name":"Southern Medical University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2026,10,15]]},"reference":[{"key":"pmbaeb062bib1","first-page":"17981","type":"journal-article","article-title":"Structured denoising diffusion models in discrete state-spaces","volume":"vol 34","author":"Austin","year":"2021"},{"key":"pmbaeb062bib2","doi-asserted-by":"publisher","first-page":"1186","DOI":"10.1007\/s00270-010-9949-0","type":"journal-article","article-title":"Complications associated with the percutaneous insertion of fiducial markers in the thorax","volume":"33","author":"Bhagat","year":"2010","journal-title":"Cardiovasc. 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All rights, including for text and data mining, AI training, and similar technologies, are reserved.","name":"copyright_information","label":"Copyright Information"},{"value":"2026-06-28","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-10-05","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-10-15","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}