Design and development of C-arm based cone-beam CT for image-guided interventions: initial results

Chen, Guang-Hong; Zambelli, Joseph; Nett, Brian E.; Supanich, Mark; Riddell, Cyril; Belanger, Barry; Mistretta, Charles A.

doi:10.1117/12.653197

Cited by 29 publications

(19 citation statements)

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“…Cone-beam CT (CBCT) is an increasingly prevalent modality for image-guided procedures, including surgery, interventional radiology, and radiotherapy (Jaffray et al 2002, Siewerdsen et al 2005, Chen et al 2006, Fahrig et al 2006). In such procedures, images from pre-operative planning CT and/or previous intraoperative CBCT scans are often available and provide valuable information on patient-specific anatomy that can be used to specify locations of interest and the nature of the imaging task.…”

Section: A Introductionmentioning

confidence: 99%

Task-driven image acquisition and reconstruction in cone-beam CT

et al. 2015

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This work introduces a task-driven imaging framework that incorporates a mathematical definition of the imaging task, a model of the imaging system, and a patient-specific anatomical model to prospectively design image acquisition and reconstruction techniques to optimize task performance. The framework is applied to joint optimization of tube current modulation, view-dependent reconstruction kernel, and orbital tilt in cone-beam CT. The system model considers a cone-beam CT system incorporating a flat-panel detector and 3D filtered backprojection and accurately describes the spatially varying noise and resolution over a wide range of imaging parameters and in the presence of a realistic anatomical model. Task-based detectability index (d') is incorporated as the objective function in a task-driven optimization of image acquisition and reconstruction techniques. The orbital tilt was optimized through an exhaustive search across tilt angles ranging ±30°. For each tilt angle, the view-dependent tube current and reconstruction kernel (i.e., the modulation profiles) that maximized detectability were identified via an alternating optimization. The task-driven approach was compared with conventional unmodulated and automatic exposure control (AEC) strategies for a variety of imaging tasks and anthropomorphic phantoms. The task-driven strategy outperformed the unmodulated and AEC cases for all tasks. For example, d' for a sphere detection task in a head phantom was improved by 30% compared to the unmodulated case by using smoother kernels for noisy views and distributing mAs across less noisy views (at fixed total mAs) in a manner that was beneficial to task performance. Similarly for detection of a line-pair pattern, the task-driven approach increased d' by 80% compared to no modulation by means of view-dependent mA and kernel selection that yields modulation transfer function and noise-power spectrum optimal to the task. Optimization of orbital tilt identified the tilt angle that reduced quantum noise in the region of the stimulus by avoiding highly attenuating anatomical structures. The task-driven imaging framework offers a potentially valuable paradigm for prospective definition of acquisition and reconstruction protocols that improve task performance without increase in dose.

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Section: A Introductionmentioning

confidence: 99%

Task-driven image acquisition and reconstruction in cone-beam CT

et al. 2015

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“…C-arm cone-beam CT (CBCT) is increasingly being used for a growing scope of intraoperative applications, providing surgeons with up-to-date images that reflect anatomic changes within the patient (Siewerdsen et al 2005, Chen et al 2006, Wallace et al 2008, Orth et al 2008, Miracle and Mukherji 2009). While the high spatial resolution typically offered by CBCT is well-suited for imaging applications of high-contrast structures such as the sinuses, skull base, and head-and-neck (Daly et al 2006, Rafferty et al 2006) as well as spine (Schafer et al 2011, Oertel et al 2011) and contrast-enhanced vessels (Fahrig et al 1997, Kamran et al 2010, Patel et al 2011), soft-tissue imaging remains challenging due to inherently low contrast and fairly high levels of noise and artifact in conventional 3D filtered backprojection (FBP) image reconstruction (Struffert et al 2010, King et al 2012).…”

Section: Introductionmentioning

confidence: 99%

Soft-tissue imaging with C-arm cone-beam CT using statistical reconstruction

et al. 2014

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The potential for statistical image reconstruction methods such as penalized-likelihood (PL) to improve C-arm cone-beam CT (CBCT) soft-tissue visualization for intraoperative imaging over conventional filtered backprojection (FBP) is assessed in this work by making a fair comparison in relation to soft-tissue performance. A prototype mobile C-arm was used to scan anthropomorphic head and abdomen phantoms as well as a cadaveric torso at doses substantially lower than typical values in diagnostic CT, and the effects of dose reduction via tube current reduction and sparse sampling were also compared. Matched spatial resolution between PL and FBP was determined by the edge spread function of low-contrast (~40–80 HU) spheres in the phantoms, which were representative of soft-tissue imaging tasks. PL using the non-quadratic Huber penalty was found to substantially reduce noise relative to FBP, especially at lower spatial resolution where PL provides a contrast-to-noise ratio increase up to 1.4–2.2 × over FBP at 50% dose reduction across all objects. Comparison of sampling strategies indicates that soft-tissue imaging benefits from fully sampled acquisitions at dose above ~1.7 mGy and benefits from 50% sparsity at dose below ~1.0 mGy. Therefore, an appropriate sampling strategy along with the improved low-contrast visualization offered by statistical reconstruction demonstrates the potential for extending intraoperative C-arm CBCT to applications in soft-tissue interventions in neurosurgery as well as thoracic and abdominal surgeries by overcoming conventional tradeoffs in noise, spatial resolution, and dose.

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“…Cone-beam computed tomography (CBCT) is a powerful imaging tool in image-guided interventions (IGI)1-3 and image-guided radiation therapy (IGRT) 4-6. It provides volumetric information for accurate target localization in IGRT and a three-dimensional vasculature roadmap in IGI.…”

Section: Introductionmentioning

confidence: 99%

Streaking artifacts reduction in four‐dimensional cone‐beam computed tomography

et al. 2008

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Cone-beam computed tomography (CBCT) using an “on-board” x-ray imaging device integrated into a radiation therapy system has recently been made available for patient positioning, target localization, and adaptive treatment planning. One of the challenges for gantry mounted image-guided radiation therapy (IGRT) systems is the slow acquisition of projections for cone-beam CT (CBCT), which makes them sensitive to any patient motion during the scans. Aiming at motion artifact reduction, four-dimensional CBCT (4D CBCT) techniques have been introduced, where a surrogate for the target's motion profile is utilized to sort the cone-beam data by respiratory phase. However, due to the limited gantry rotation speed and limited readout speed of the on-board imager, fewer than 100 projections are available for the image reconstruction at each respiratory phase. Thus, severe undersampling streaking artifacts plague 4D CBCT images. In this paper, the authors propose a simple scheme to significantly reduce the streaking artifacts. In this method, a prior image is first reconstructed using all available projections without gating, in which static structures are well reconstructed while moving objects are blurred. The undersampling streaking artifacts from static structures are estimated from this prior image volume and then can be removed from the phase images using gated reconstruction. The proposed method was validated using numerical simulations, experimental phantom data, and patient data. The fidelity of stationary and moving objects is maintained, while large gains in streak artifact reduction are observed. Using this technique one can reconstruct 4D CBCT datasets using no more projections than are acquired in a 60 s scan. At the same time, a temporal gating window as narrow as 100 ms was utilized. Compared to the conventional 4D CBCT reconstruction, streaking artifacts were reduced by 60% to 70%.

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Design and development of C-arm based cone-beam CT for image-guided interventions: initial results

Cited by 29 publications

References 0 publications

Task-driven image acquisition and reconstruction in cone-beam CT

Task-driven image acquisition and reconstruction in cone-beam CT

Soft-tissue imaging with C-arm cone-beam CT using statistical reconstruction

Streaking artifacts reduction in four‐dimensional cone‐beam computed tomography

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