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X-Ray Hybrid Modalities for Image Guidance

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Intraoperative Imaging and Image-Guided Therapy

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Abstract

Minimally invasive procedures using image guidance have become a popular alternative to their surgical counterparts because they offer reduced patient risk and as a result reduced morbidity. X-ray fluoroscopy can be used to provide real-time image guidance for interventional procedures. Current state-of-the-art fluoroscopy systems consist of a high-power rotating anode x-ray tube and a digital flat-panel detector. However, the lack of three-dimensional visualization has motivated the development of advanced x-ray imaging modalities for image guidance purposes which include real-time tomosynthesis, C-arm computed tomography (CT), and hybrid x-ray/MRI (X-MR).

Tomosynthesis systems traditionally require mechanical motion of the source relative to the detector. Real-time tomosynthesis can be achieved via the scanning beam digital x-ray (SBDX) system, which can obtain a limited range of angular projections without requiring mechanical motion by using a distributed source array. This system has potential applications for three-dimensional tracking of catheters as well as for image guidance for lung nodule biopsy.

C-arm CT can provide three-dimensional imaging capabilities in the interventional suite. Improvements over the past decade to C-arm systems, such as the introduction of large-area flat-panel amorphous silicon detectors and more robust gantry designs, have enabled the development of new intra-procedural applications for this imaging modality. These applications include using the three-dimensional information provided by C-arm CT to obtain brain perfusion parameters in stroke patients and performing image guidance for radio-frequency ablations to treat cardiac arrhythmias.

Hybrid X-MR systems combine the three-dimensional imaging capabilities and excellent soft tissue contrast provided by MRI with the high spatial/temporal resolution and accurate device tracking provided by x-ray. These systems have been used for a variety of intraoperative procedures including shunt deployment in the liver, brain biopsy, chemoembolization of hepatic tumors, hysterosalpingograms, and loopograms. The various hybrid system geometries present different engineering challenges, with those geometries that attempt to place the modalities very close to each other requiring modification of hardware components. The safety and compatibility of interventional devices such as catheters in an MR environment is a concern in these hybrid systems as well, and work has been performed to offer solutions to these problems.

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References

  1. Garrison JB, et al. Three dimensional roentgenography. Am J Roentgenol Radium Ther Nucl Med. 1969;105:903–8.

    CAS  PubMed  Google Scholar 

  2. Grant DG. Tomosynthesis: a three-dimensional radiographic imaging technique. IEEE Trans Biomed Eng. 1972;19:20–8.

    CAS  PubMed  Google Scholar 

  3. Miller ER, et al. An infinite number of laminagrams from a finite number of radiographs. Radiology. 1971;98:249–55.

    CAS  PubMed  Google Scholar 

  4. Godfrey D, et al. Optimization of matrix inverse tomosynthesis. SPIE Med Imag. 2001;4320:696–704.

    Google Scholar 

  5. Niklason LT, et al. Digital tomosynthesis in breast imaging. Radiology. 1997;205:399–406.

    CAS  PubMed  Google Scholar 

  6. Suryanarayanan S, et al. Comparison of tomosynthesis methods used with digital mammography. Acad Radiol. 2000;7:1085–97.

    CAS  PubMed  Google Scholar 

  7. Badano A, et al. Anisotropic imaging performance in breast tomosynthesis. Med Phys. 2007;34:4076–91.

    CAS  PubMed  Google Scholar 

  8. Chen Y, et al. Importance of point-by-point back projection correction for isocentric motion in digital breast tomosynthesis: relevance to morphology of structures such as microcalcifications. Med Phys. 2007;34:3885–92.

    PubMed  Google Scholar 

  9. Diekmann F, Bick U. Tomosynthesis and contrast-enhanced digital mammography: recent advances in digital mammography. Eur Radiol. 2007;17:3086–92.

    PubMed  Google Scholar 

  10. Gur D. Tomosynthesis: potential clinical role in breast imaging. AJR Am J Roentgenol. 2007;189:614–5.

    PubMed  Google Scholar 

  11. Li B, et al. Optimization of slice sensitivity profile for radiographic tomosynthesis. Med Phys. 2007;34:2907–16.

    PubMed  Google Scholar 

  12. Park JM, et al. Breast tomosynthesis: present considerations and future applications. Radiographics. 2007;27 Suppl 1:S231–40.

    PubMed  Google Scholar 

  13. Poplack SP, et al. Digital breast tomosynthesis: initial experience in 98 women with abnormal digital screening mammography. AJR Am J Roentgenol. 2007;189:616–23.

    PubMed  Google Scholar 

  14. Zeng K, et al. Digital tomosynthesis aided by low-resolution exact computed tomography. J Comput Assist Tomogr. 2007;31:976–83.

    PubMed  Google Scholar 

  15. Zhou J, et al. A computer simulation platform for the optimization of a breast tomosynthesis system. Med Phys. 2007;34:1098–109.

    PubMed  Google Scholar 

  16. Gennaro G, et al. Digital breast tomosynthesis versus digital mammography: a clinical performance study. Eur Radiol. 2010;20:1545–53.

    PubMed  Google Scholar 

  17. Tagliafico A, et al. One-to-one comparison between digital spot compression view and digital breast tomosynthesis. Eur Radiol. 2012;22:539–44.

    PubMed  Google Scholar 

  18. Solomon EG, et al. Low-exposure scanning-beam x-ray fluoroscopy system. Proceedings of SPIE – the international society for optical engineering medical imaging 1996: physics of medical imaging, vol. 2708; 11–13 Feb 1996. Newport Beach; 1996. p. 140–9.

    Google Scholar 

  19. Solomon EG, et al. Scanning-beam digital x-ray (SBDX) system for cardiac angiography. Proceedings of SPIE – the international society for optical engineering proceedings of the 1999 medical imaging – physics of medical imaging, vol. 3659; 21–23 Feb 1999. San Diego; 1999. p. 246–57.

    Google Scholar 

  20. Sprenger F, et al. Stationary digital breast tomosynthesis with distributed field emission x-ray tube. Proc SPIE. 2011; 79615I-1–79615I-6.

    Google Scholar 

  21. Maltz JS, et al. Fixed gantry tomosynthesis system for radiation therapy image guidance based on a multiple source x-ray tube with carbon nanotube cathodes. Med Phys. 2009;36:1624–36.

    PubMed  Google Scholar 

  22. Barrett HH. Limited-angle tomography for the nineties. J Nucl Med. 1990;31:1688–92.

    CAS  PubMed  Google Scholar 

  23. Dobbins 3rd JT, Godfrey DJ. Digital x-ray tomosynthesis: current state of the art and clinical potential. Phys Med Biol. 2003;48:R65–106.

    PubMed  Google Scholar 

  24. Speidel MA, et al. Scanning-beam digital x-ray (SBDX) technology for interventional and diagnostic cardiac angiography. Med Phys. 2006;33:2714–27.

    PubMed  Google Scholar 

  25. Speidel MA, et al. Comparison of entrance exposure and signal-to-noise ratio between an SBDX prototype and a wide-beam cardiac angiographic system. Med Phys. 2006;33:2728–43.

    PubMed  Google Scholar 

  26. Wolff MR, et al. Pilot study with a scanning-beam digital x-ray system. Am J Cardiol. 2004;94.

    Google Scholar 

  27. Speidel MA, et al. Three-dimensional tracking of cardiac catheters using an inverse geometry x-ray fluoroscopy system. Med Phys. 2010;37:6377–89.

    PubMed  Google Scholar 

  28. National Lung Screening Trial. 2002. http://www.cancer.gov/nlst.

  29. Henschke CI, et al. Early lung cancer action project: overall design and findings from baseline screening. Lancet. 1999;354:99–105.

    CAS  PubMed  Google Scholar 

  30. Lechtzin N, et al. Patient satisfaction with bronchoscopy. Am J Respir Crit Care Med. 2002;166:1326–31.

    PubMed  Google Scholar 

  31. Suratt PM, et al. Deaths and complications associated with fiberoptic bronchoscopy. Chest. 1976;69:747–51.

    CAS  PubMed  Google Scholar 

  32. Geraghty PR, et al. CT-guided transthoracic needle aspiration biopsy of pulmonary nodules: needle size and pneumothorax rate. Radiology. 2003;229:475–81.

    PubMed  Google Scholar 

  33. Gupta S, et al. Small (</=2-cm) subpleural pulmonary lesions: short- versus long-needle-path CT-guided biopsy–comparison of diagnostic yields and complications. Radiology. 2005;234:631–7.

    PubMed  Google Scholar 

  34. Sawabata N, et al. Fine-needle aspiration cytologic technique for lung cancer has a high potential of malignant cell spread through the tract. Chest. 2000;118:936–9.

    CAS  PubMed  Google Scholar 

  35. Yeow KM, et al. Risk factors of pneumothorax and bleeding: multivariate analysis of 660 CT-guided coaxial cutting needle lung biopsies. Chest. 2004;126:748–54.

    PubMed  Google Scholar 

  36. Allen MS, et al. Video-assisted thoracic surgical procedures: the Mayo experience. Mayo Clin Proc. 1996;71:351–9.

    CAS  PubMed  Google Scholar 

  37. DeCamp Jr MM, et al. The safety and versatility of video-thoracoscopy: a prospective analysis of 895 consecutive cases. J Am Coll Surg. 1995;181:113–20.

    PubMed  Google Scholar 

  38. Wang KP. Transbronchial needle aspiration and percutaneous needle aspiration for staging and diagnosis of lung cancer. Clin Chest Med. 1995;16:535–52.

    CAS  PubMed  Google Scholar 

  39. Gay PC, Brutinel WM. Transbronchial needle aspiration in the practice of bronchoscopy. Mayo Clin Proc. 1989;64:158–62.

    CAS  PubMed  Google Scholar 

  40. Harrow EM, et al. The utility of transbronchial needle aspiration in the staging of bronchogenic carcinoma. Am J Respir Crit Care Med. 2000;161:601–7.

    CAS  PubMed  Google Scholar 

  41. Rong F, Cui B. CT scan directed transbronchial needle aspiration biopsy for mediastinal nodes. Chest. 1998;114:36–9.

    CAS  PubMed  Google Scholar 

  42. Schenk DA, et al. Transbronchial needle aspiration in the diagnosis of bronchogenic carcinoma. Chest. 1987;92:83–5.

    CAS  PubMed  Google Scholar 

  43. Schenk DA, et al. Utility of the Wang 18-gauge transbronchial histology needle in the staging of bronchogenic carcinoma. Chest. 1989;96:272–4.

    CAS  PubMed  Google Scholar 

  44. Wang KP, et al. Flexible transbronchial needle aspiration for staging of bronchogenic carcinoma. Chest. 1983;84:571–6.

    CAS  PubMed  Google Scholar 

  45. Schreiber G, McCrory DC. Performance characteristics of different modalities for diagnosis of suspected lung cancer: summary of published evidence. Chest. 2003;123:115S–28.

    PubMed  Google Scholar 

  46. Anantham D, et al. Electromagnetic navigation bronchoscopy-guided fiducial placement for robotic stereotactic radiosurgery of lung tumors: a feasibility study. Chest. 2007;132:930–5.

    PubMed  Google Scholar 

  47. Eberhardt R, et al. Electromagnetic navigation diagnostic bronchoscopy in peripheral lung lesions. Chest. 2007;131:1800–5.

    PubMed  Google Scholar 

  48. Makris D, et al. Electromagnetic navigation diagnostic bronchoscopy for small peripheral lung lesions. Eur Respir J. 2007;29:1187–92.

    CAS  PubMed  Google Scholar 

  49. Schwarz Y, et al. Real-time electromagnetic navigation bronchoscopy to peripheral lung lesions using overlaid CT images: the first human study. Chest. 2006;129:988–94.

    PubMed  Google Scholar 

  50. Hautmann H, et al. Electromagnetic catheter navigation during bronchoscopy: validation of a novel method by conventional fluoroscopy. Chest. 2005;128:382–7.

    PubMed  Google Scholar 

  51. Gildea TR, et al. Electromagnetic navigation diagnostic bronchoscopy: a prospective study. Am J Respir Crit Care Med. 2006;174:982–9.

    PubMed  Google Scholar 

  52. Samei E, et al. Detection of subtle lung nodules: relative influence of quantum and anatomic noise on chest radiographs. Radiology. 1999;213:727–34.

    CAS  PubMed  Google Scholar 

  53. Samei E, et al. Subtle lung nodules: influence of local anatomic variations on detection. Radiology. 2003;228:76–84.

    PubMed  Google Scholar 

  54. Pineda AR, et al. Optimization of a tomosynthesis system for the detection of lung nodules. Med Phys. 2006;33:1372–9.

    PubMed  Google Scholar 

  55. Fahrig R, et al. Characterization of a C-arm-mounted XRII for 3D image reconstruction during interventional neuroradiology. In: Medical imaging 1996: physics of medical imaging 1996. p. 351–60.

    Google Scholar 

  56. Fahrig R, et al. Use of a C-arm system to generate true three-dimensional computed rotational angiograms: preliminary in vitro and in vivo results. AJNR Am J Neuroradiol. 1997;18:1507–14.

    CAS  PubMed  Google Scholar 

  57. Rougee A, et al. Geometrical calibration of X-ray imaging chains for three-dimensional reconstruction. Comput Med Imaging Graph. 1993;17:295–300.

    CAS  PubMed  Google Scholar 

  58. Navab N, et al. Dynamic geometrical calibration for 3D cerebral angiography. In: Medical imaging 1996: physics of medical imaging. Newport Beach, California; 1996. p. 361–70.

    Google Scholar 

  59. Bani-Hashemi A, et al. Applications of Computer Vision, 1998. WACV ‘98. Proceedings, Fourth IEEE Workshop; 19–21 Oct 1998. p. 246–247. ISBN:0-8186-8606-5: Princton; NJ, doi: 10.1109/ACV.1998.732891.

  60. Navab N, et al. Medical Image Computing and Computer–Assisted Interventation – MICCAI’98. Lecture Notes in Computer Science. Vol. 1496, 1998, pp. 119–129.

    Google Scholar 

  61. Fahrig R, et al. Three-dimensional computed tomographic reconstruction using a C-arm mounted XRII: correction of image intensifier distortion. Med Phys. 1997;24:1097–106.

    CAS  PubMed  Google Scholar 

  62. Cerveri P, et al. Distortion correction for x-ray image intensifiers: local unwarping polynomials and RBF neural networks. Med Phys. 2002;29:1759–71.

    CAS  PubMed  Google Scholar 

  63. Liu RR, et al. Super-global distortion correction for a rotational C-arm x-ray image intensifier. Med Phys. 1999;26:1802–10.

    CAS  PubMed  Google Scholar 

  64. Mitschke MM, Navab N. Mathematical Methords in Biomedical Image Analysis, 2000. Proceedings, IEEE Workshop; 2000. pp. 204–209. ISBN:0-7695-0737-9: INSPEC, Accession Number: 6657281.

    Google Scholar 

  65. Schueler BA, et al. Three-dimensional vascular reconstruction with a clinical x-ray angiography system. Acad Radiol. 1997;4:693–9.

    CAS  PubMed  Google Scholar 

  66. Wiesent K, et al. Enhanced 3-Dreconstruction algorithm for C-arm systems suitable for interventional procedures. IEEE Trans Med Imaging. 2000;19:391–403.

    CAS  PubMed  Google Scholar 

  67. Fahrig R, Holdsworth DW. Three-dimensional computed tomographic reconstruction using a C-arm mounted XRII: image-based correction of gantry motion nonidealities. Med Phys. 2000;27:30–8.

    CAS  PubMed  Google Scholar 

  68. Starman J, et al. Estimating 0/sup th/ and 1/sup st/ moments in C-arm CT data for extrapolating truncated projections. Proc SPIE. 2005;5747:378–87.

    Google Scholar 

  69. Sourbelle K, et al. Reconstruction from truncated projections in CT using adaptive detruncation. Eur Radiol. 2005;15:1008–14.

    CAS  PubMed  Google Scholar 

  70. Ohnesorge B, et al. Efficient correction for CT image artifacts caused by objects extending outside the scan field of view. Med Phys. 2000;27:39–46.

    CAS  PubMed  Google Scholar 

  71. Hsieh J, et al. A novel reconstruction algorithm to extend the CT scan field-of-view. Med Phys. 2004;31:2385–91.

    CAS  PubMed  Google Scholar 

  72. Bani-Hashemi A, et al. Cone beam X-ray scatter removal via image frequency modulation and filtering. Medical Physics. 2005;32:2093.

    Google Scholar 

  73. Bertram M, et al. Potential of software-based scatter corrections in cone-beam volume CT. Proc SPIE. 2005;5745:259–70.

    Google Scholar 

  74. Kyriakou Y, Kalender W. Efficiency of antiscatter grids for flat-detector CT. Phys Med Biol. 2007;52:6275–93.

    PubMed  Google Scholar 

  75. Maltz J, et al. Unified algorithm for KV and MV scatter and beam-hardening correction using the convolution-superposition method. Medical Physics. 2006;33:2280.

    Google Scholar 

  76. Ning R, Tang X, Conover DL. X-ray scatter suppression algorithm for cone-beam volume CT. Proc SPIE. 2002;4682:774–81.

    Google Scholar 

  77. Ning R, et al. X-ray scatter correction algorithm for cone beam CT imaging. Medical Physics. 2004;31:1195–202.

    PubMed  Google Scholar 

  78. Ruhrnschopf EP, et al. A general framework and review of scatter correction methods in cone beam CT. Part 2: scatter estimation approaches. Med Phys. 2011;38:5186–99.

    Google Scholar 

  79. Ruhrnschopf EP, Klingenbeck K. Erratum: a general framework and review of scatter correction methods in x-ray cone beam CT. Part 1: scatter compensation approaches [Med. Phys. 38(7), 4296-4311 (2011)]. Med Phys. 2011;38:5830.

    Google Scholar 

  80. Ruhrnschopf EP, Klingenbeck K. A general framework and review of scatter correction methods in x-ray cone-beam computerized tomography. Part 1: scatter compensation approaches. Med Phys. 2011;38:4296–311.

    PubMed  Google Scholar 

  81. Siewerdsen JH, et al. A simple, direct method for x-ray scatter estimation and correction in digital radiography and cone-beam CT. Medi Phys. 2006;33:187–97.

    CAS  Google Scholar 

  82. Zhu L, et al. Scatter correction method for X-ray CT using primary modulation: theory and preliminary results. IEEE Trans Med Imaging. 2006;25:1573–87.

    PubMed  Google Scholar 

  83. Zhu L, et al. X-ray scatter correction for cone-beam CT using moving blocker array. In: Medical imaging 2005: physics of medical imaging. San Diego, California; 2005. p. 251–8.

    Google Scholar 

  84. Rinkel J, et al. A new method for x-ray scatter correction: first assessment on a cone-beam CT experimental setup. Phys Med Biol. 2007;52:4633–52.

    CAS  PubMed  Google Scholar 

  85. Kyriakou Y, et al. Combining deterministic and Monte Carlo calculations for fast estimation of scatter intensities in CT. Phys Med Biol. 2006;51:4567–86.

    PubMed  Google Scholar 

  86. Mail N, et al. An empirical method for lag correction in cone-beam CT. Med Phys. 2008;35:5187–96.

    CAS  PubMed  Google Scholar 

  87. Starman J, et al. Investigation into the optimal linear time-invariant lag correction for radar artifact removal. Med Phys. 2011;38:2398–411.

    PubMed  Google Scholar 

  88. Parker DL. Optimization of short scan convolution reconstruction in fan beam CT. 1982.

    Google Scholar 

  89. Feldkamp LA, et al. Practical cone-beam algorithm. J Opt Soc Am A (Opt Imag Sci). 1984;1:612–9.

    Google Scholar 

  90. Zellerhoff M, et al. Low contrast 3D reconstruction from C-arm data. Proc SPIE. 2005;5745:646–55.

    Google Scholar 

  91. Tuy HK. An inversion formula for cone-beam reconstruction. SIAM J Appl Math. 1983;43:546–52.

    Google Scholar 

  92. Hamelin B, et al. Design of iterative ROI transmission tomography reconstruction procedures and image quality analysis. Med Phys. 2010;37:4577–89.

    PubMed  Google Scholar 

  93. Zou Y, et al. Image reconstruction in regions-of-interest from truncated projections in a reduced fan-beam scan. Phys Med Biol. 2005;50:13–27.

    PubMed  Google Scholar 

  94. Ziegler A, et al. Iterative reconstruction of a region of interest for transmission tomography. Med Phys. 2008;35:1317–27.

    PubMed  Google Scholar 

  95. Yu L, et al. Region of interest reconstruction from truncated data in circular cone-beam CT. IEEE Trans Med Imaging. 2006;25:869–81.

    PubMed  Google Scholar 

  96. Courdurier M, et al. Solving the interior problem of computed tomography using a priori knowledge. Inverse Probl. 2008;24:065001.

    Google Scholar 

  97. Defrise M, et al. Truncated Hilbert transform and image reconstruction from limited tomographic data. Inverse Probl. 2006;22:1037–53.

    Google Scholar 

  98. Endo M, et al. Effect of scattered radiation on image noise in cone beam CT. Med Phys. 2001;28:469–74.

    CAS  PubMed  Google Scholar 

  99. Siewerdsen JH, Jaffray DA. Cone-beam computed tomography with a flat-panel imager: magnitude and effects of x-ray scatter. Med Phys. 2001;28:220–31.

    CAS  PubMed  Google Scholar 

  100. Siewerdsen JH, Moseley DJ, Bakhtiar B, Richard S, Jaffray D. The influence of antiscatter grids on soft-tissue detectability in cone-beam computed tomography with flat-panel detectors. Med Phys. 2004;31:3506–20.

    CAS  PubMed  Google Scholar 

  101. Wiegert J, et al. Performance of standard fluoroscopy antiscatter grids in flat-detector-based cone-beam CT. Proc SPIE. 2004;5368:67–78.

    Google Scholar 

  102. Ganguly A, et al. Cerebral CT perfusion using an interventional C-arm imaging system: cerebral blood flow measurements. AJNR Am J Neuroradiol. 2011;32:1525–31.

    CAS  PubMed Central  PubMed  Google Scholar 

  103. Orlov MV, et al. Three-dimensional rotational angiography of the left atrium and esophagus-A virtual computed tomography scan in the electrophysiology lab? Heart Rhythm. 2007;4:37–43.

    PubMed  Google Scholar 

  104. Nölker G, et al. Three-dimensional left atrial and esophagus reconstruction using cardiac C-arm computed tomography with image integration into fluoroscopic views for ablation of atrial fibrillation: accuracy of a novel modality in comparison with multislice computed tomography. Heart Rhythm. 2008;5:1651–7.

    PubMed  Google Scholar 

  105. Tognolini A, et al. Intraprocedure visualization of the esophagus using interventional C-arm CT as guidance for left atrial radiofrequency ablation. Acad Radiol. 2011;18:850–7.

    PubMed Central  PubMed  Google Scholar 

  106. Thiagalingam A, et al. Intraprocedural volume imaging of the left atrium and pulmonary veins with rotational x-ray angiography: implications for catheter ablation of atrial fibrillation. J Cardiovasc Electrophysiol. 2008;19:293–300.

    PubMed  Google Scholar 

  107. Dick AJ, et al. Invasive human magnetic resonance imaging: feasibility during revascularization in a combined XMR suite. Catheter Cardiovasc Interv. 2005;64:265–74.

    PubMed Central  PubMed  Google Scholar 

  108. Ladd ME, Debatin JF. Interventional and intravascular MR angiography. Herz. 2000;25:440–51.

    CAS  PubMed  Google Scholar 

  109. Ladd ME, et al. Interventional MRA and intravascular imaging. J Magn Reson Imaging. 2000;12:534–46.

    CAS  PubMed  Google Scholar 

  110. Vogl TJ, et al. Hybrid MR interventional imaging system: combined MR and angiography suites with single interactive table. Feasibility study in vascular liver tumor procedures. Eur Radiol. 2002;12:1394–400.

    PubMed  Google Scholar 

  111. Wilson MW, et al. Experimental renal artery embolization in a combined MR imaging/angiographic unit. J Vasc Interv Radiol. 2003;14:1169–75.

    PubMed  Google Scholar 

  112. Rhode KS, et al. Registration and tracking to integrate x-ray and MR images in an XMR facility. IEEE Trans Med Imaging. 2003;22:1369–78.

    PubMed  Google Scholar 

  113. Kucharczyk J, et al. Cost-efficacy of MR-guided neurointerventions. Neuroimaging Clin N Am. 2001;11:767–72, xii.

    CAS  PubMed  Google Scholar 

  114. Chu RM, et al. Minimally invasive procedures. Interventional MR image-guided functional neurosurgery. Neuroimaging Clin N Am. 2001;11:715–25.

    CAS  PubMed  Google Scholar 

  115. Medical Imaging 2004: Physiology, Function, and Structure from Medical Images, 10 (April 30, 2004). doi: 10.1117/12.535103

  116. Rhode K, et al. Real-time XMR guidance for cardiac electrophysiology procedures. In: Proceedings of 5th interventional MRI symposium. Boston; 2004.

    Google Scholar 

  117. Hegde S, et al. Towards safer cardiac intervention: a novel approach that combines x-ray and magnetic resonance imaging for guidance of stent implantation. In: Proceedings of 5th interventional MRI symposium. Boston; 2004. p. 82–3.

    Google Scholar 

  118. Ginks MR, et al. A simultaneous X-Ray/MRI and noncontact mapping study of the acute hemodynamic effect of left ventricular endocardial and epicardial cardiac resynchronization therapy in humans. Circ Heart Fail. 2011;4:170–9.

    PubMed  Google Scholar 

  119. Acher P, et al. An analysis of intraoperative versus post-operative dosimetry with CT, CT-MRI fusion and XMR for the evaluation of permanent prostate brachytherapy implants. Radiother Oncol. 2010;96:166–71.

    PubMed  Google Scholar 

  120. Carlsson M, et al. Magnetic resonance imaging quantification of left ventricular dysfunction following coronary microembolization. Magn Reson Med. 2009;61:595–602.

    PubMed  Google Scholar 

  121. Acher P, et al. Comparison of combined x-ray radiography and magnetic resonance (XMR) imaging-versus computed tomography-based dosimetry for the evaluation of permanent prostate brachytherapy implants. Int J Radiat Oncol Biol Phys. 2008;71:1518–25.

    PubMed  Google Scholar 

  122. Chinchapatnam PP, et al. Anisotropic wave propagation and apparent conductivity estimation in a fast electrophysiological model: application to XMR interventional imaging. Med Image Comput Comput Assist Interv. 2007;10:575–83.

    CAS  PubMed  Google Scholar 

  123. Matsumae M, et al. World’s first magnetic resonance imaging/x-ray/operating room suite: a significant milestone in the improvement of neurosurgical diagnosis and treatment. J Neurosurg. 2007;107:266–73.

    PubMed  Google Scholar 

  124. Sermesant M, et al. A fast-marching approach to cardiac electrophysiology simulation for XMR interventional imaging. Med Image Comput Comput Assist Interv. 2005;8:607–15.

    CAS  PubMed  Google Scholar 

  125. Fahrig R, et al. A truly hybrid interventional MR/X-ray system: feasibility demonstration. J Magn Reson Imaging. 2001;13:294–300.

    CAS  PubMed  Google Scholar 

  126. Wen Z, et al. Shimming with permanent magnets for the x-ray detector in a hybrid x-ray/ MR system. Med Phys. 2008;35:3895–902.

    PubMed  Google Scholar 

  127. Fahrig R, et al. Performance of a static-anode/flat-panel x-ray fluoroscopy system in a diagnostic strength magnetic field: a truly hybrid x-ray/MR imaging system. Med Phys. 2005;32:1775–84.

    CAS  PubMed  Google Scholar 

  128. Wen Z, et al. Investigation of electron trajectories of an x-ray tube in magnetic fields of MR scanners. Med Phys. 2007;34:2048–58.

    PubMed  Google Scholar 

  129. Kee ST, et al. MR-guided transjugular intrahepatic portosystemic shunt creation with use of a hybrid radiography/MR system. J Vasc Interv Radiol. 2005;16:227–34.

    PubMed  Google Scholar 

  130. Fahrig R, et al. Truly hybrid interventional MR/X-ray system: investigation of in vivo applications. Acad Radiol. 2001;8:1200–7.

    CAS  PubMed  Google Scholar 

  131. Fahrig R, et al. First use of a truly-hybrid X-ray/MR imaging system for guidance of brain biopsy. Acta Neurochir (Wien). 2003;145:995–7; discussion 997.

    CAS  Google Scholar 

  132. Ganguly A, et al. Truly hybrid X-ray/MR imaging: toward a streamlined clinical system. Acad Radiol. 2005;12:1167–77.

    PubMed  Google Scholar 

  133. Jackson JD. Classical electrodynamics. 3rd ed. New York: Wiley; 1999.

    Google Scholar 

  134. Bracken JA, et al. Closed-bore XMR (CBXMR) systems for aortic valve replacement: x-ray tube imaging performance. Med Phys. 2009;36:1086–97.

    PubMed  Google Scholar 

  135. Bracken JA, et al. Closed bore XMR (CBXMR) systems for aortic valve replacement: active magnetic shielding of x-ray tubes. Med Phys. 2009;36:1717–26.

    PubMed  Google Scholar 

  136. Lillaney PV, et al. Electrostatic focal spot correction for x-ray tubes operating in strong magnetic fields. In: American Association of Physicists in Medicine. Vancouver; 2011.

    Google Scholar 

  137. Brzozowski L, et al. Compatibility of interventional x-ray and magnetic resonance imaging: feasibility of a closed bore XMR (CBXMR) system. Med Phys. 2006;33:3033–45.

    PubMed  Google Scholar 

  138. Lillaney P, et al. U.S. Patent No. 7,701,215. Washington, DC: U.S. Patent and Trademark Office. 2010.

    Google Scholar 

  139. Dumoulin CL, et al. Real-time position monitoring of invasive devices using magnetic resonance. Magn Reson Med. 1993;29:411–5.

    CAS  PubMed  Google Scholar 

  140. McKinnon GC, et al. Towards active guidewire visualization in interventional magnetic resonance imaging. MAGMA. 1996;4:13–8.

    CAS  PubMed  Google Scholar 

  141. Ladd ME, et al. Active MR visualization of a vascular guidewire in vivo. J Magn Reson Imaging. 1998;8:220–5.

    CAS  PubMed  Google Scholar 

  142. Quick HH, et al. Interventional magnetic resonance angiography with no strings attached: wireless active catheter visualization. Magn Reson Med. 2005;53:446–55.

    PubMed  Google Scholar 

  143. Henderson JM, et al. Permanent neurological deficit related to magnetic resonance imaging in a patient with implanted deep brain stimulation electrodes for Parkinson’s disease: case report. Neurosurgery. 2005;57:E1063; discussion E1063.

    PubMed  Google Scholar 

  144. Venook R, et al. Reducing and monitoring resonant heating in MR guidewires. In: The international society for magnetic resonance in medicine. Seattle; 2006.

    Google Scholar 

  145. Zanchi MG, et al. An optically coupled system for quantitative monitoring of MRI-induced RF currents into long conductors. IEEE Trans Med Imaging. 2010;29:169–78.

    PubMed Central  PubMed  Google Scholar 

  146. Scott GC, et al. A vector modulation transmit array system. In: The international society for magnetic resonance in medicine. Seattle; 2006.

    Google Scholar 

  147. Overall WR, et al. Ensuring safety of implanted devices under MRI using reversed RF polarization. Magn Reson Med. 2010;64:823–33.

    PubMed Central  PubMed  Google Scholar 

  148. Schmidt TG, Fahrig R, Pelc NJ. A three-dimensional reconstruction algorithm for an inverse-geometry volumetric CT system. Med Phys. 2005;32:3234–45.

    PubMed  Google Scholar 

  149. Zhifei W. Investigation of election trajections of an X-ray tube in Magnetic fields of MR scanners. Med Phys. 34(2007):2048.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Departments of Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry Street, Suite 350 Lobby 6, San Francisco, CA, 94107, USA

    Prasheel V. Lillaney PhD

  2. Departments of Bioengineering and Radiology, Stanford University, Stanford, CA, USA

    Norbert J. Pelc & Rebecca Fahrig PhD

Authors
  1. Prasheel V. Lillaney PhD
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  2. Norbert J. Pelc
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  3. Rebecca Fahrig PhD
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Corresponding author

Correspondence to Norbert J. Pelc .

Editor information

Editors and Affiliations

  1. National Center for Image Guided Therapy, Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA

    Ferenc A. Jolesz

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Lillaney, P.V., Pelc, N.J., Fahrig, R. (2014). X-Ray Hybrid Modalities for Image Guidance. In: Jolesz, F. (eds) Intraoperative Imaging and Image-Guided Therapy. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7657-3_9

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  • DOI: https://doi.org/10.1007/978-1-4614-7657-3_9

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