Deformable Registration of the Inflated and Deflated Lung for Cone-Beam CT-Guided Thoracic Surgery

被引:1
|
作者
Uneri, Ali [1 ]
Nithiananthan, Sajendra [2 ]
Schafer, Sebastian [2 ]
Otake, Yoshito [1 ,2 ]
Stayman, J. Webster [2 ]
Kleinszig, Gerhard [3 ]
Sussman, Marc S. [4 ]
Taylor, Russell H. [1 ]
Prince, Jerry L. [5 ]
Siewerdsen, Jeffrey H. [1 ,2 ]
机构
[1] Johns Hopkins Univ, Dept Comp Sci, Baltimore, MD 21218 USA
[2] Johns Hopkins Univ, Dept Biomed Engn, Baltimore, MD 21218 USA
[3] Siemens Healthcare, Erlangen, Germany
[4] Johns Hopkins Bayview Med Ctr, Dept Surg, Baltimore, MD 21218 USA
[5] Johns Hopkins Univ, Dept Elect & Comp Engn, Baltimore, MD 21218 USA
来源
MEDICAL IMAGING 2012: IMAGE-GUIDED PROCEDURES, ROBOTIC INTERVENTIONS, AND MODELING | 2012年 / 8316卷
基金
美国国家卫生研究院;
关键词
CANCER; LOCALIZATION;
D O I
10.1117/12.911440
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Intraoperative cone-beam CT (CBCT) could offer an important advance to thoracic surgeons in directly localizing subpalpable nodules during surgery. An image-guidance system is under development using mobile C-arm CBCT to directly localize tumors in the OR, potentially reducing the cost and logistical burden of conventional preoperative localization and facilitating safer surgery by visualizing critical structures surrounding the surgical target (e. g., pulmonary artery, airways, etc.). To utilize the wealth of preoperative image/planning data and to guide targeting under conditions in which the tumor may not be directly visualized, a deformable registration approach has been developed that geometrically resolves images of the inflated (i.e., inhale or exhale) and deflated states of the lung. This novel technique employs a coarse model-driven approach using lung surface and bronchial airways for fast registration, followed by an image-driven registration using a variant of the Demons algorithm to improve target localization to within similar to 1 mm. Two approaches to model-driven registration are presented and compared - the first involving point correspondences on the surface of the deflated and inflated lung and the second a mesh evolution approach. Intensity variations (i.e., higher image intensity in the deflated lung) due to expulsion of air from the lungs are accounted for using an a priori lung density modification, and its improvement on the performance of the intensity-driven Demons algorithm is demonstrated. Preliminary results of the combined model-driven and intensity-driven registration process demonstrate accuracy consistent with requirements in minimally invasive thoracic surgery in both target localization and critical structure avoidance.
引用
收藏
页数:8
相关论文
共 50 条
  • [21] Assessment of contrast enhanced respiration managed cone-beam CT for image guided radiotherapy of intrahepatic tumors
    Jensen, Nikolaj K. G.
    Stewart, Errol
    Lock, Michael
    Fisher, Barbara
    Kozak, Roman
    Chen, Jeff
    Lee, Ting-Yim
    Wong, Eugene
    MEDICAL PHYSICS, 2014, 41 (05)
  • [22] DOSIMETRIC IMPACT OF ONLINE CORRECTION VIA CONE-BEAM CT-BASED IMAGE GUIDANCE FOR STEREOTACTIC LUNG RADIOTHERAPY
    Galerani, Ana Paula
    Grills, Inga
    Hugo, Geoffrey
    Kestin, Larry
    Mohammed, Nasiruddin
    Chao, K. Kenneth
    Suen, Andrew
    Martinez, Alvaro
    Yan, Di
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2010, 78 (05): : 1571 - 1578
  • [23] Progressively refined deep joint registration segmentation (ProRSeg) of gastrointestinal organs at risk: Application to MRI and cone-beam CT
    Jiang, Jue
    Hong, Jun
    Tringale, Kathryn
    Reyngold, Marsha
    Crane, Christopher
    Tyagi, Neelam
    Veeraraghavan, Harini
    MEDICAL PHYSICS, 2023, 50 (08) : 4758 - 4774
  • [24] Efficacy and Safety of Cone-Beam CT Augmented Electromagnetic Navigation Guided Bronchoscopic Biopsies of Indeterminate Pulmonary Nodules
    Podder, Shreya
    Chaudry, Sana
    Singh, Harpreet
    Jondall, Elise M.
    Kurman, Jonathan S.
    Benn, Bryan S.
    TOMOGRAPHY, 2022, 8 (04) : 2049 - 2058
  • [25] Self-calibration of cone-beam CT geometry using 3D-2D image registration
    Ouadah, S.
    Stayman, J. W.
    Gang, G. J.
    Ehtiati, T.
    Siewerdsen, J. H.
    PHYSICS IN MEDICINE AND BIOLOGY, 2016, 61 (07) : 2613 - 2632
  • [26] A study of respiration-correlated cone-beam CT scans to correct target positioning errors in radiotherapy of thoracic cancer
    Santoro, J. P.
    McNamara, J.
    Yorke, E.
    Pham, H.
    Rimner, A.
    Rosenzweig, K. E.
    Mageras, G. S.
    MEDICAL PHYSICS, 2012, 39 (10) : 5825 - 5834
  • [27] CT-guided microcoil localization for scapula-blocked pulmonary nodules using penetrating lung puncture before video-assisted thoracic surgery
    Tian, Ye
    An, Jianli
    Zou, Zibo
    Dong, Yanchao
    Wu, Jingpeng
    Chen, Zhuo
    Niu, Hongtao
    DIAGNOSTIC AND INTERVENTIONAL RADIOLOGY, 2023, 29 (01): : 155 - 160
  • [28] Dosimetric Evaluation of DIR Mapped Contours for Image Guided Adaptive Radiotherapy with 4D Cone-Beam CT
    Balik, S.
    Weiss, E.
    Jan, N.
    Zhang, L.
    Roman, N.
    Christensen, G.
    Williamson, J.
    Hugo, G.
    MEDICAL PHYSICS, 2014, 41 (06) : 191 - +
  • [29] Peripheral dose from megavoltage cone-beam CT imaging for nasopharyngeal carcinoma image-guided radiation therapy
    Jia, Ming X.
    Zhang, Xu
    Li, Na
    Wang, En Y.
    Liu, Da W.
    Cai, Wei S.
    JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS, 2012, 13 (05): : 3 - 11
  • [30] Ultrasound versus Cone-beam CT image-guided radiotherapy for prostate and post-prostatectomy pretreatment localization
    Fargier-Voiron, Marie
    Presles, Benoit
    Pommier, Pascal
    Munoz, Alexandre
    Rit, Simon
    Sarrut, David
    Biston, Marie-Claude
    PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS, 2015, 31 (08): : 997 - 1004