4D liver cone-beam CT imaging and tumor localization

Liver tumor imaging and localization remains a challenge task for modern image-guided radiation therapy. The liver tumor is usually of low-contrast in x-ray imaging, rendering it hardly discernable from surrounding normal liver tissues. Correspondingly, a large treatment margin needs to be added beyond the actual extent of the liver tumor, to account for the uncertainties of liver tumor localization for radiation therapy, to ensure sufficient tumor coverage by radiation beams. Such a practice unfortunately also adds unnecessary dose to normal liver tissues, increases liver toxicity, and potentially limits the efficacy of radiation therapy, especially those using large fractional doses like SBRT. We developed an advanced reconstruction technique combinining iterative reconstruction with deformable registration and biomechanical modeling to allow automatic, accurate 4D liver tumor imaging and localization using non-contrast CBCT projections (Bio-4DCBCT). Bio-4DCBCT allows substantial tumor localization accuracy improvement to within 2 mm, enabling accurate and safety radiation therapy to improve patient outcomes.  

  • Y. Zhang, M. Folkert, B. Li, X. Huang, J. Meyer, T. Chiu, P. Lee, J. Tehrani, J. Cai, D. Parsons, X. Jia and J. Wang, “4D Liver Tumor Localization using Cone-Beam Projections and a Biomechanical Model", Radiotherapy & Oncology 133, 183-192 (2019).
  • Y. Zhang, M. R. Folkert, X. Huang, J. Meyer, J. N. Tehrani, L. Ren, J. Wang, " Enhancing Liver Tumor Localization Accuracy by Prior-Knowledge-Guided Motion Modeling and A Biomechanical Model ", Quantitative Imaging in Medicine and Surgery 9(7), 1337-1349 (2019).
  • Y. Zhang, X. Huang, J. Wang, " Advanced 4D-CBCT reconstruction by combining motion estimation, motion-compensated reconstruction, biomechanical modeling and deep learning", Visual Computing for Industry, Biomedicine, and Art 2, 23 (2019).
  • Y. Zhang, J.N. Tehrani, J. Wang, " A biomechanical modeling guided CBCT estimation technique ", IEEE Transactions on Medical Imaging 36, 641-652 (2017).