Cone-beam imaging with tilted rotation axis: Method and performance evaluation.


Journal

Medical physics
ISSN: 2473-4209
Titre abrégé: Med Phys
Pays: United States
ID NLM: 0425746

Informations de publication

Date de publication:
Aug 2020
Historique:
received: 21 11 2019
revised: 26 02 2020
accepted: 13 04 2020
pubmed: 28 4 2020
medline: 15 5 2021
entrez: 28 4 2020
Statut: ppublish

Résumé

The recently introduced robotic x-ray systems provide the flexibility to acquire cone-beam computed tomography (CBCT) data using customized, application-specific source-detector trajectories. We exploit this capability to mitigate the effects of x-ray scatter and noise in CBCT imaging of weight-bearing foot and cervical spine (C-spine) using scan orbits with a tilted rotation axis. We used an advanced CBCT simulator implementing accurate models of x-ray scatter, primary attenuation, and noise to investigate the effects of the orbital tilt angle in upright foot and C-spine imaging. The system model was parameterized using a laboratory version of a three-dimensional (3D) robotic x-ray system (Multitom RAX, Siemens Healthineers). We considered a generalized tilted axis scan configuration, where the detector remained parallel to patient's long body axis during the acquisition, but the elevation of source and detector was changing. A modified Feldkamp-Davis-Kress (FDK) algorithm was developed for reconstruction in this configuration, which departs from the FDK assumption of a detector that is perpendicular to the scan plane. The simulated foot scans involved source-detector distance (SDD) of 1386 mm, orbital tilt angles ranging 10° to 40°, and 400 views at 1 mAs/view and 0.5° increment; the C-spine scans involved -25° to -45° tilt angles, SDD of 1090 mm, and 202 views at 1.3 mAs and 1° increment The imaging performance was assessed by projection-domain measurements of the scatter-to-primary ratio (SPR) and by reconstruction-domain measurements of contrast, noise and generalized contrast-to-noise ratio (gCNR, accounting for both image noise and background nonuniformity) of the metatarsals (foot imaging) and cervical vertebrae (spine imaging). The effects of scatter correction were also compared for horizontal and tilted scans using an ideal Monte Carlo (MC)-based scatter correction and a frame-by-frame mean scatter correction. The proposed modified FDK, involving projection resampling, mitigated streak artifacts caused by the misalignment between the filtering direction and the detector rows. For foot imaging (no grids), an optimized 20° tilted orbit reduced the maximum SPR from ~1.5 in a horizontal scan to <0.5. The gCNR of the second metatarsal was enhanced twofold compared to a horizontal orbit. For the C-spine (with vertical grids), imaging with a tilted orbit avoided highly attenuating x-ray paths through the lower cervical vertebrae and shoulders. A -35° tilted orbit yielded improved image quality and visualization of the lower cervical spine: the SPR of lower cervical vertebrae was reduced from ~10 (horizontal orbit) to <6 (tilted orbit), and the gCNR for C5-C7 increased by a factor of 2. Furthermore, tilted orbits showed potential benefits over horizontal orbits by enabling scatter correction with a simple frame-by-frame mean correction without substantial increase in noise-induced artifacts after the correction. Tilted scan trajectories, enabled by the emerging robotic x-ray system technology, were optimized for CBCT imaging of foot and cervical spine using an advanced simulation framework. The results demonstrated the potential advantages of tilted axis orbits in mitigation of scatter artifacts and improving contrast-to-noise ratio in CBCT reconstructions.

Identifiants

pubmed: 32340069
doi: 10.1002/mp.14209
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

3305-3320

Informations de copyright

© 2020 American Association of Physicists in Medicine.

Références

Zbijewski W, De Jean P, Prakash P, et al. A dedicated cone-beam CT system for musculoskeletal extremities imaging: design, optimization, and initial performance characterization. Med Phys. 2011;38:4700-4713.
Cao Q, Sisniega A, Brehler M, et al. Modeling and evaluation of a high-resolution CMOS detector for cone-beam CT of the extremities. Med Phys. 2018;45:114-130.
Sisniega A, Stayman JW, Yorkston J, Siewerdsen JH, Zbijewski W. Motion compensation in extremity cone-beam CT using a penalized image sharpness criterion. Phys Med Biol. 2017;62:3712-3734.
Boone JM, Kwan ALC, Yang K, Burkett GW, Lindfors KK, Nelson TR. Computed tomography for imaging the breast. J Mamm Gland Biol Neoplasia. 2006;11:103-111.
Lindfors KK, Boone JM, Nelson TR, Yang K, Kwan ALC, Miller DF. Dedicated breast CT: initial clinical experience. Radiology. 2008;246:725-733.
Sisniega A, Zbijewski W, Xu J, et al. High-fidelity artifact correction for cone-beam CT imaging of the brain. Phys Med Biol. 2015;60:1415-1439.
Xu J, Sisniega A, Zbijewski W, et al. Modeling and design of a cone-beam CT head scanner using task-based imaging performance optimization. Phys Med Biol. 2016;61:3180-3207.
Xu J, Reh DD, Carey JP, Mahesh M, Siewerdsen JH. Technical assessment of a cone-beam CT scanner for otolaryngology imaging: image quality, dose, and technique protocols. Med Phys. 2012;39:4932-4942.
Pireau N, Cordemans V, Banse X, Irda N, Lichtherte S, Kaminski L. Radiation dose reduction in thoracic and lumbar spine instrumentation using navigation based on an intraoperative cone beam CT imaging system: a prospective randomized clinical trial. Eur Spine J. 2017;26:2818-2827.
Schafer S, Nithiananthan S, Mirota DJ, et al. Mobile C-arm cone-beam CT for guidance of spine surgery: image quality, radiation dose, and integration with interventional guidance. Med Phys. 2011;38:4563-4574.
Siewerdsen JH. Cone-beam CT with a flat-panel detector: from image science to image-guided surgery. Nucl Instrum Methods Phys Res Sect A Accel Spectrometers Detect Assoc Equip. 2011;648:S241-S250.
Jaffray DA, Siewerdsen JH, Wong JW, Martinez AA. Flat-panel cone-beam computed tomography for image-guided radiation therapy. Int J Radiat Oncol. 2002;53:1337-1349.
Bapst B, Lagadec M, Breguet R, Vilgrain V, Ronot M. Cone beam computed tomography (CBCT) in the field of interventional oncology of the liver. Cardiovasc Intervent Radiol. 2016;39:8-20.
Hirota S, Nakao N, Yamamoto S, et al. Cone-beam CT with flat-panel-detector digital angiography system: early experience in abdominal interventional procedures. Cardiovasc Intervent Radiol. 2006;29:1034-1038.
Ouadah S, Jacobson M, Stayman JW, et al. Task-driven orbit design and implementation on a robotic C-arm system for cone-beam CT. In: Proc. SPIE 10132, Med. Imaging Phys. Med. Imaging, 2017:101320H.
Ouadah S, Stayman JW, Gang GJ, Ehtiati T, Siewerdsen JH. Self-calibration of cone-beam CT geometry using 3D-2D image registration. Phys Med Biol. 2016;61:2613-2632.
Hua C, Yao W, Kidani T, et al. A robotic C-arm cone beam CT system for image-guided proton therapy: design and performance. Br J Radiol. 2017;90:20170266.
Liu WP, Otake Y, Azizian M, et al. 2D-3D radiograph to cone-beam computed tomography (CBCT) registration for C-arm image-guided robotic surgery. Int J Comput Assist Radiol Surg. 2015;10:1239-1252.
Cordemans V, Kaminski L, Banse X, Francq BG, Cartiaux O. Accuracy of a new intraoperative cone beam CT imaging technique (Artis zeego II) compared to postoperative CT scan for assessment of pedicle screws placement and breaches detection. Eur Spine J. 2017;26:2906-2916.
Noo F, Oktay MB, Ritschl L, et al.X-ray cone-beam imaging of the entire spine in the weight-bearing position. In: Med. Imaging Phys. Med. Imaging, 2018:27.
Capostagno S, Stayman JW, Jacobson M, Ehtiati T, Weiss CR, Siewerdsen JH. Task-driven source-detector trajectories in cone-beam computed tomography: II. Application to neuroradiology. J Med Imaging. 2019;6:1.
Fieselmann A, Steinbrener J, Jerebko AK, et al. Twin robotic x-ray system for 2D radiographic and 3D cone-beam CT imaging. In: Proc. SPIE 9783, Med. Imaging Phys. Med. Imaging; 2016:97830G.
Luckner C, Ritschl L, Sesselmann S, Mertelmeier T, Maier A, Parallel-shift tomosynthesis for orthopedic applications. In: Proc. SPIE 10573, Med. Imaging Phys. Med. Imaging; 2018:105730G.
Benz RM, Harder D, Amsler F, et al. Initial assessment of a prototype 3D cone-beam computed tomography system for imaging of the lumbar spine, evaluating human cadaveric specimens in the upright position. Invest Radiol. 2018;53:714-719.
Zhao C, Herbst M, Vogt S, et al. A robotic x-ray cone-beam CT system: trajectory optimization for 3D imaging of the weight-bearing spine. In: Proc. SPIE 10948, Med. Imaging Phys. Med. Imaging; 2019:109481L.
Zhao C, Herbst M, Vogt S, et al. Optimization of cone-beam CT scan orbits for cervical spine imaging. In: Proc. 15th Int. Meet. Fully Three-Dimensional Image Reconstr. Radiol. Nucl. Med.; 110720U.
Herbst M, Luckner C, Wicklein J, et al. Misalignment compensation for ultra-high-resolution and fast CBCT acquisitions. In: Med. Imaging Phys. Med. Imaging; 2019:57.
Luckner C, Ritschl L, Herbst M, Maier A, Kappler S. Assessment of measurement deviations: length-extended x-ray imaging for orthopedic applications. In: Proc. SPIE 10948, Med. Imaging. Phys. Med: Imaging; 2019:1094839.
Siewerdsen JH, Daly MJ, Bakhtiar B, et al. A simple, direct method for x-ray scatter estimation and correction in digital radiography and cone-beam CT. Med Phys. 2006;33:187-197.
Sisniega A, Zbijewski W, Badal A, et al. Monte Carlo study of the effects of system geometry and antiscatter grids on cone-beam CT scatter distributions. Med Phys. 2013;40:051915.
Boas FE, Fleischmann D. CT artifacts: causes and reduction techniques. Imaging Med. 2012;4:229-240.
Siewerdsen JH, Jaffray DA. Cone-beam computed tomography with a flat-panel imager: magnitude and effects of x-ray scatter. Med Phys. 2001;28:220-231.
Yeoman LJ, Howarth L, Britten A, Cotterill A, Adam EJ. Gantry angulation in brain CT: dosage implications, effect on posterior fossa artifacts, and current international practice. Radiology. 1992;184:113-116.
Frank E, Long B, Smith B. Merrill’s Atlas of Radiographic Positioning and Procedures-E-Book;2013.
Feldkamp LA, Davis LC, Kress JW. Practical cone-beam algorithm. J Opt Soc Am A. 1984;1:612-619.
Stayman JW, Capostagno S, Gang GJ, Siewerdsen JH. Task-driven source-detector trajectories in cone-beam computed tomography: I theory and methods. J Med Imaging. 2019;6:1.
Benz RM, Garcia MA, Amsler F, et al. Initial evaluation of image performance of a 3-D x-ray system: phantom-based comparison of 3-D tomography with conventional computed tomography. J Med Imaging. 2018;5:015502.
Boswell SA, Jeraj R, Ruchala KJ, et al. A novel method to correct for pitch and yaw patient setup errors in helical tomotherapy. Med Phys. 2005;32:1630-1639.
Cho Y, Moseley DJ, Siewerdsen JH, Jaffray DA. Accurate technique for complete geometric calibration of cone-beam computed tomography systems. Med Phys. 2005;32:968-983.
Siewerdsen JH, Waese AM, Moseley DJ, Richard S, Jaffray DA. Spektr: a computational tool for x-ray spectral analysis and imaging system optimization. Med Phys. 2004;31:3057-3067.
Siewerdsen JH, Antonuk LE, El-Mohri Y, et al. Empirical and theoretical investigation of the noise performance of indirect detection, active matrix flat-panel imagers (AMFPIs) for diagnostic radiology. Med Phys. 1997;24:71-89.
Day GJ, Dance DR. X-ray transmission formula for antiscatter grids. Phys Med Biol. 1983;28:1429-1433.
Wang AS, Stayman JW, Otake Y, et al. Low-dose preview for patient-specific, task-specific technique selection in cone-beam CT. Med Phys. 2014;41:071915.
Wang G, Lin T-H, Cheng P, Shinozaki DM. A general cone-beam reconstruction algorithm. IEEE Trans Med Imaging. 1993;12:486-496.
Yang H, Li M, Koizumi K, Kudo H. Exact cone beam reconstruction for a saddle trajectory. Phys Med Biol. 2006;51:1157-1172.
Noo F, Defrise M, Kudo H. General reconstruction theory for multislice x-ray computed tomography with a gantry tilt. IEEE Trans Med Imaging. 2004;23:1109-1116.
Ohnesorge B, Flohr T, Klingenbeck-Regn K. Efficient object scatter correction algorithm for third and fourth generation CT scanners. Eur Radiol. 1999;9:563-569.
Star-Lack J, Sun M, Kaestner A, et al. Efficient scatter correction using asymmetric kernels. In: Proc. SPIE 7258, Med. Imaging Phys. Med. Imaging (2009); 2009:72581Z.
Kachelrieß M, Watzke O, Kalender WA. Generalized multi-dimensional adaptive filtering for conventional and spiral single-slice, multi-slice, and cone-beam CT. Med Phys. 2001;28:475-490.
Xu J, Sisniega A, Zbijewski W, et al. Evaluation of detector readout gain mode and bowtie filters for cone-beam CT imaging of the head. Phys Med Biol. 2016;61:5973-5992.
Mail N, Moseley DJ, Siewerdsen JH, Jaffray DA. The influence of bowtie filtration on cone-beam CT image quality. Med Phys. 2009;36:22-32.
Sisniega A, Zbijewski W, Wu P, et al. Image quality, scatter, and dose in compact CBCT systems with flat and curved detectors. In: Proc. SPIE 10573, Med. Imaging Phys. Med. Imaging (2018); 2018:105734E.

Auteurs

Chumin Zhao (C)

Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21205, USA.

Magdalena Herbst (M)

Siemens Healthineers, Forchheim, 91301, Germany.

Sebastian Vogt (S)

Siemens Healthineers, Forchheim, 91301, Germany.

Ludwig Ritschl (L)

Siemens Healthineers, Forchheim, 91301, Germany.

Steffen Kappler (S)

Siemens Healthineers, Forchheim, 91301, Germany.

Jeffrey H Siewerdsen (JH)

Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21205, USA.
Russell H. Morgan Department of Radiology, Johns Hopkins University, Baltimore, MD, 21287, USA.

Wojciech Zbijewski (W)

Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21205, USA.

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