{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T20:32:07Z","timestamp":1786393927752,"version":"build-2736575974"},"reference-count":32,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T00:00:00Z","timestamp":1782345600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T00:00:00Z","timestamp":1782345600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Interfractional anatomical variations during breast cancer radiotherapy can significantly deviate the delivered dose from the treatment plan. Standard image guidance via Cone\u2010Beam CT (CBCT) is typically sparse due to radiation and workflow constraints, leaving daily geometric changes unmonitored.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>To bridge this gap, we propose a physics\u2010informed framework that utilizes monocular surface vision for continuous, non\u2010ionizing 3D dose reconstruction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>The system utilizes the weekly CBCT scans from the first 2\u00a0weeks of treatment (Week 1 and Week 2) for patient\u2010specific calibration. Surface features are extracted via a hybrid HOG\u2010CNN descriptor, while 3D deformation vector fields (DVFs) are compressed into a low\u2010dimensional latent space via Principal Component Analysis (PCA). A linear mapping from surface topography to PCA coefficients is optimized using physics\u2010informed Tikhonov regularization, incorporating an eigenvalue\u2010based penalty matrix to suppress high\u2010order non\u2010physical modes. Post\u2010calibration, the model reconstructs 3D dose distributions for subsequent fractions in real time using only monocular input.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Validated on 29 patients (87 fractions), the framework achieved a deformation coefficient correlation of\n                      <jats:italic>R<\/jats:italic>\n                      \u00a0=\u00a00.796. Reconstructed doses yielded a mean Gamma passing rate (3%\/3\u00a0mm) of 93.8%\u00a0\u00b1\u00a03.1% and a dose correlation of 0.940\u00a0\u00b1\u00a00.037. Ablation studies demonstrated that removing physics constraints or PCA reduction significantly degraded performance (\u0394GPR\u00a0=\u00a0\u22128.5% and \u221222.1%, respectively;\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0&lt;\u00a00.001). End\u2010to\u2010end latency was 42\u00a0\u00b1\u00a05\u00a0ms per fraction, representing a \u223c124\u2010fold acceleration over commercial deformable registration solutions.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This framework transforms routine weekly CBCTs into robust \u201ccalibration anchors\u201d for continuous visual dose monitoring. It provides clinical\u2010grade accuracy with negligible computational overhead and no additional ionizing dose, offering a practical solution for real\u2010time adaptive radiotherapy.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mp.70533","type":"journal-article","created":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T14:42:47Z","timestamp":1782398567000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Physics\u2010informed patient\u2010specific calibration for monocular visual\u2010based dose reconstruction in breast cancer radiotherapy"],"prefix":"10.1002","volume":"53","author":[{"given":"Yongjin","family":"Deng","sequence":"first","affiliation":[{"name":"Department of Radiation Oncology The First Affiliated Hospital, Sun Yat\u2010sen University  Guangzhou Guangdong 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