Search

Purpose: Recent applications of iterative image reconstruction algorithms to multislice helical CT have shown that iterative reconstruction can significantly improve image quality and reduce artifacts. In this paper, the authors introduce a combination of two different algorithms with different convergence properties: ordered subsets separable paraboloidal surrogates (OS-SPS) and iterative coordinate descent (ICD). The first one updates image voxels simultaneously, slightly changing attenuation values iteration by iteration. The second algorithm updates image voxel by voxel, each time performing full forward and backward projections of the voxel. It has been shown that ICD converges better at high-frequency areas and requires more iterations to reconstruct low-frequency components of the image. In contrast to ICD, SPS requires multiple iterations to reconstruct high-frequency areas. In this paper, the authors introduce an algorithm which leverages the benefits of both ICD and SPS. Methods: The idea is to update the entire image with SPS, determine high-frequency components, and focus ICD computations on it using nonhomogeneous ICD update. Results: The authors have successfully implemented OS-SPS, ICD, their hybrid approach, and few variations of ICD based on spatially nonuniform updates. Conclusions: The authors have examined the convergence of different algorithms and found that proposed algorithm converges better than OS-SPS, ICD, as well as various improved variants of ICD. [ABSTRACT FROM AUTHOR]

Purpose: The previously described 2D standardized vessel-wall-plus-plaque thickness (VWT) maps constructed from 3D ultrasound vessel wall measurements using an arc-length (AL) scaling approach adjusted the geometric variability of carotid arteries and has allowed for the comparisons of VWT distributions in longitudinal and cross-sectional studies. However, this mapping technique did not optimize point correspondence of the carotid arteries investigated. The potential misalignment may lead to errors in point-wise VWT comparisons. In this paper, we developed and validated an algorithm based on steepest description length (DL) descent to optimize the point correspondence implied by the 2D VWT maps. Methods: The previously described AL approach was applied to obtain initial 2D maps for a group of carotid arteries. The 2D maps were reparameterized based on an iterative steepest DL descent approach, which consists of the following two steps. First, landmarks established by resampling the 2D maps were aligned using the Procrustes algorithm. Then, the gradient of the DL with respect to horizontal and vertical reparameterizations of each landmark on the 2D maps was computed, and the 2D maps were subsequently deformed in the direction of the steepest descent of DL. These two steps were repeated until convergence. The quality of the correspondence was evaluated in a phantom study and an in vivo study involving ten carotid arteries enrolled in a 3D ultrasound interscan variability study. The correspondence quality was evaluated in terms of the compactness and generalization ability of the statistical shape model built based on the established point correspondence in both studies. In the in vivo study, the effect of the proposed algorithm on interscan variability of VWT measurements was evaluated by comparing the percentage of landmarks with statistically significant VWT-change before and after point correspondence optimization. Results: The statistical shape model constructed with optimized correspondence was more compact and had a better generalization ability than that constructed using the AL approach in both the phantom and in vivo studies. A statistical test on the group-average VWT-Change at each point of the 2D carotid template showed that the group-average VWT-change was significantly different from 0 in 18% of landmarks when the AL approach was used, and this percentage was reduced to 11% after correspondence optimization. Conclusions: The optimized correspondence resulted in a more compact and generalizable statistical shape model, and the algorithm was shown to reduce interscan variability of point-wise VWT measurements obtained using the previously described arc-length scaling parameterization approach. [ABSTRACT FROM AUTHOR]

Purpose: Automatic measurement of the intima-media thickness (IMT) from ultrasound carotid images is an important task in clinical diagnosis. Many computer-based techniques for IMT measurement have been proposed to overcome the limits of manual segmentation. However, the robustness of the algorithms would be influenced by the inherent specklenoise of ultrasoundimage. This paper proposed a curvelet guided ant colony optimization (CGACO) strategy that could achieve satisfied accuracy for IMT measurement with improved robustness to noise. Methods: The curvelet-based orientation-selective (CBOS) filter was first introduced for speckle removal and edge enhancement. Different from conventional methods, CBOS filter processes the curvelet coefficients by orientations rather than by magnitude. Then, a specially designed two-leg ant colony optimization technique, combined with Otsu thresholding and Sobel edge detector, was proposed as a novel segmentation method to extract the media-adventitia (MA) and the lumen-intima (LI) boundaries. Finally, a coupled snake model was employed to further smooth the contours of MA and LI. Results: In addition to 224 carotid arteryimages acquired from 34 participants, simulated speckled images with nine levels of noise were also included in the database. The mean absolute distance errors of CGACO for LI interface tracings, MA interface tracings, and IMT measurements were 0.030 ± 0.027, 0.039 ± 0.036, and 0.041 ± 0.036 mm, respectively. Besides, CGACO had a correlation coefficient as high as 0.992 and a bias as low as -0.008. All these measures were comparable to or better than a previous technique and the manual segmentation. On the other hand, CGACO had the highest success rate of 98.7% in the segmentation of real data. It also maintained a much higher success rate in the segmentation of simulated images with different levels of specklenoise. Conclusions: The proposed technique showed accurate IMT measurement results. Furthermore, benefiting from the CBOS filter, the robustness to noise of the algorithm was substantially improved. Therefore, CGACO could provide a reliable way to segment the carotid artery from ultrasoundimages and could be used in clinical practice of IMT measurement, particularly in early atherosclerotic stages. [ABSTRACT FROM AUTHOR]

Purpose: This paper describes a method to achieve consistent clinical image quality in 18F-FDG scans accounting for patient habitus, dose regimen, image acquisition, and processing techniques. Methods: Oncological PET/CT scan data for 58 subjects were evaluated retrospectively to derive analytical curves that predict image quality. Patient noise equivalent count rate and coefficient of variation (CV) were used as metrics in their analysis. Optimized acquisition protocols were identified and prospectively applied to 179 subjects. Results: The adoption of different schemes for three body mass ranges (<60 kg, 60-90 kg, >90 kg) allows improved image quality with both point spread function and ordered-subsets expectation maximization-3D reconstruction methods. The application of this methodology showed that CV improved significantly (p < 0.0001) in clinical practice. Conclusions: Consistent oncological PET/CT image quality on a high-performance scanner was achieved from an analysis of the relations existing between dose regimen, patient habitus, acquisition, and processing techniques. The proposed methodology may be used by PET/CT centers to develop protocols to standardize PET/CT imaging procedures and achieve better patient management and cost-effective operations. [ABSTRACT FROM AUTHOR]

Purpose: For a given imaging task and patient size, the optimal selection of x-ray tube potential (kV) and tube current-rotation time product (mAs) is pivotal in achieving the maximal radiation dose reduction while maintaining the needed diagnostic performance. Although contrast-to-noise (CNR)-based strategies can be used to optimize kV/mAs for computed tomography (CT) imaging systems employing the linear filtered backprojection (FBP) reconstruction method, a more general framework needs to be developed for systems using the nonlinear statistical model-based iterative reconstruction (MBIR) method. The purpose of this paper is to present such a unified framework for the optimization of kV/mAs selection for both FBP- and MBIR-based CT systems. Methods: The optimal selection of kV and mAs was formulated as a constrained optimization problem to minimize the objective function, Dose(kV,mAs), under the constraint that the achievable detectability index d'(kV,mAs) is not lower than the prescribed value of d' for a given imaging task. Since it is difficult to analytically model the dependence of d' on kV and mAs for the highly nonlinear MBIR method, this constrained optimization problem is solved with comprehensive measurements of Dose(kV,mAs) and d'(kV,mAs) at a variety of kV-mAs combinations, after which the overlay of the dose contours and d' contours is used to graphically determine the optimal kV-mAs combination to achieve the lowest dose while maintaining the needed detectability for the given imaging task. As an example, R' for a 17 mm hypoattenuating liver lesion detection task was experimentally measured with an anthropomorphic abdominal phantom at four tube potentials (80, 100, 120, and 140 kV) and fifteen mA levels (25 and 50-700) with a sampling interval of 50 mA at a fixed rotation time of 0.5 s, which corresponded to a dose (CTDIvol) range of [0.6, 70] mGy. Using the proposed method, the optimal kV and mA that minimized dose for the prescribed detectability level of d'R = 16 were determined. As another example, the optimal kV and mA for an 8 mm hyperattenuating liver lesion detection task were also measured using the developed framework. Both an in vivo animal and human subject study were used as demonstrations of how the developed framework can be applied to the clinical work flow. Results: For the first task, the optimal kV and mAs were measured to be 100 and 500, respectively, for FBP, which corresponded to a dose level of 24 mGy. In comparison, the optimal kV and mAs for MBIR were 80 and 150, respectively, which corresponded to a dose level of 4 mGy. The topographies of the iso-d' map and the iso-CNR map were the same for FBP; thus, the use of d'- and CNR-based optimization methods generated the same results for FBP. However, the topographies of the iso-d' and iso-CNR map were significantly different in MBIR; the CNR-based method overestimated the performance of MBIR, predicting an overly aggressive dose reduction factor. For the second task, the developed framework generated the following optimization results: for FBP, kV = 140, mA= 350, dose = 37.5 mGy; for MBIR, kV = 120, mA= 250, dose = 18.8 mGy. Again, the CNR-based method overestimated the performance of MBIR. Results of the preliminary in vivo studies were consistent with those of the phantom experiments. Conclusions: A unified and task-driven kV/mAs optimization framework has been developed in this work. The framework is applicable to both linear and nonlinear CT systems such as those using the MBIR method. As expected, the developed framework can be reduced to the conventional CNR-based kV/mAs optimization frameworks if the system is linear. For MBIR-based nonlinear CT systems, however, the developed task-based kV/mAs optimization framework is needed to achieve the maximal dose reduction while maintaining the desired diagnostic performance. [ABSTRACT FROM AUTHOR]

Purpose: Association between tissue stiffness alteration and pathology is well known. This has formed the basis for prostate elastography imaging techniques where images of prostate tissue mechanical properties are reconstructed. In this paper, the authors present a novel prostate elastography technique which, unlike other techniques, relies on magnitude image data only. Methods: This proposed technique works in conjunction with ultrasound or magnetic resonance imaging (MRI) imaging modalities and it requires the prostate's pre- and postdeformation images as input. It uses a constrained reconstruction method where the elastic moduli of the prostate's normal and pathological tissues are determined based on an essential subset of the tissue deformation provided by the images data. The elasticity reconstruction technique uses optimization where similarity between calculated and observed shape features of the postcompression prostate image is maximized. The method was validated with an in silico phantom study followed by studies using ultrasound and MR with tissue-mimicking phantoms. Results: Using the proposed methods, it was observed that the maximum uncertainties of the reconstructed Young's modulus ratios of tumor to normal tissue were 15.6% and 9.7%, which were obtained from the transrectal ultrasound (TRUS) and MR tissue-mimicking phantom studies, respectively. Conclusions: This novel prostate elastography technique relies on prostate TRUS or MRI images that can be routinely acquired without additional imaging hardware. The phantom studies provided evidence that the proposed technique has a good potential to reconstruct prostate stiffness maps noninvasively particularly when applied in conjunction with MRI. Further studies are necessary to evaluate the technique's merits for clinical use. [ABSTRACT FROM AUTHOR]

Purpose: Functional image guided intensity-modulated radiation therapy has the potential to improve cancer treatment quality by basing treatment parameters such as heterogeneous dose distributions information derived from imaging. However, such heterogeneous dose distributions are subject to imaging uncertainty. In this paper, the authors develop a robust optimization model to design plans that are desensitized to imaging uncertainty. Methods: Starting from the pretreatment fluorodeoxyglucose-positron emission tomography scans, the authors use the raw voxel standard uptake values (SUVs) as input into a series of intermediate functions to transform the SUV into a desired dose. The calculated desired doses were used as an input into a robust optimization model to generate beamlet intensities. For each voxel, the authors assume that the true SUV cannot be observed but instead resides in an interval centered on the nominal (i.e., observed) SUV. Then the authors evaluated the nominal and robust solutions through a simulation study. The simulation considered the effect of the true SUV being different from the nominal SUV on the quality of the treatment plan. Treatment plans were compared on the metrics of objective function value and tumor control probability (TCP). Results: Computational results demonstrate the potential for improvements in tumor control probability and deviation from the desired dose distribution compared to a nonrobust model while maintaining acceptable tissue dose. Conclusions: Robust optimization can help design treatment plans that are more stable in the presence of image value uncertainties. [ABSTRACT FROM AUTHOR]

In single photon emission computed tomography, the choice of the collimator has a major impact on the sensitivity and resolution of the system. Traditional parallel-hole and fan-beam collimators used in clinical practice, for example, have a relatively poor sensitivity and subcentimeter spatial resolution, while in small-animal imaging, pinhole collimators are used to obtain submillimeter resolution and multiple pinholes are often combined to increase sensitivity. This paper reviews methods for production, sensitivity maximization, and task-based optimization of collimation for both clinical and preclinical imaging applications. New opportunities for improved collimation are now arising primarily because of (i) new collimator-production techniques and (ii) detectors with improved intrinsic spatial resolution that have recently become available. These new technologies are expected to impact the design of collimators in the future. The authors also discuss concepts like septal penetration, high-resolution applications, multiplexing, sampling completeness, and adaptive systems, and the authors conclude with an example of an optimization study for a parallel-hole, fan-beam, cone-beam, and multiple-pinhole collimator for different applications. [ABSTRACT FROM AUTHOR]

Purpose: Electromagnetically guided endoscopic procedure, which aims at accurately and robustly localizing the endoscope, involves multimodal sensory information during interventions. However, it still remains challenging in how to integrate these information for precise and stable endoscopic guidance. To tackle such a challenge, this paper proposes a new framework on the basis of an enhanced particle swarm optimization method to effectively fuse these information for accurate and continuous endoscope localization. Methods: The authors use the particle swarm optimization method, which is one of stochastic evolutionary computation algorithms, to effectively fuse the multimodal information including preoperative information (i.e., computed tomography images) as a frame of reference, endoscopic camera videos, and positional sensor measurements (i.e., electromagnetic sensor outputs). Since the evolutionary computation method usually limits its possible premature convergence and evolutionary factors, the authors introduce the current (endoscopic camera and electromagnetic sensor's) observation to boost the particle swarm optimization and also adaptively update evolutionary parameters in accordance with spatial constraints and the current observation, resulting in advantageous performance in the enhanced algorithm. Results: The experimental results demonstrate that the authors' proposed method provides a more accurate and robust endoscopic guidance framework than state-of-the-art methods. The average guidance accuracy of the authors' framework was about 3.0 mm and 5.6° while the previous methods show at least 3.9 mm and 7.0°. The average position and orientation smoothness of their method was 1.0 mm and 1.6°, which is significantly better than the other methods at least with (2.0 mm and 2.6°). Additionally, the average visual quality of the endoscopic guidance was improved to 0.29. Conclusions: A robust electromagnetically guided endoscopy framework was proposed on the basis of an enhanced particle swarm optimization method with using the current observation information and adaptive evolutionary factors. The authors proposed framework greatly reduced the guidance errors from (4.3, 7.8) to (3.0 mm, 5.6°), compared to state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Purpose: Efficient and accurate segmentations of 3D end-firing transrectal ultrasound (TRUS) images play an important role in planning of 3D TRUS guided prostate biopsy. However, poor image quality of the input 3D TRUS images, such as strong imaging artifacts and speckles, often makes it a challenging task to extract the prostate boundaries accurately and efficiently. Methods: In this paper, the authors propose a novel convex optimization-based approach to delineate the prostate surface from a given 3D TRUS image, which reduces the original 3D segmentation problem to a sequence of simple 2D segmentation subproblems over the rotational reslices of the 3D TRUS volume. Essentially, the authors introduce a novel convex relaxation-based contour evolution approach to each 2D slicewise image segmentation with the joint optimization of shape information, where the learned 2D nonlinear statistical shape prior is incorporated to segment the initial slice, its result is propagated as a shape constraint to the segmentation of the following slices. In practice, the proposed segmentation algorithm is implemented on a GPU to achieve the high computational performance. Results: Experimental results using 30 patient 3D TRUS images show that the proposed method can achieve a mean Dice similarity coefficient of 93.4% ± 2.2% in 20 s for one 3D image, outperforming the existing local-optimization-based methods, e.g., level-set and active-contour, in terms of accuracy and efficiency. In addition, inter- and intraobserver variability experiments show its good reproducibility. Conclusions: A semiautomatic segmentation approach is proposed and evaluated to extract the prostate boundary from 3D TRUS images acquired by a 3D end-firing TRUS guided prostate biopsy system. Experimental results suggest that it may be suitable for the clinical use involving the image guided prostate biopsy procedures. [ABSTRACT FROM AUTHOR]

Purpose: Beam-quality optimization in digital mammography traditionally considers detection of a target obscured by quantum noise in a homogeneous background. This does not correspond well to the clinical imaging task because real mammographic images contain a complex superposition of anatomical structures, resulting in anatomical noise that may dominate over quantum noise. The purpose of this paper is to assess the influence on optimal beam quality in mammography when anatomical noise is taken into account. Methods: The detectability of microcalcifications and masses was quantified using a theoretical ideal-observer model that included quantum noise as well as anatomical noise and a simplified model of a photon-counting mammography system. The outcome was experimentally verified using two types of simulated tissue phantoms. Results: The theoretical model showed that the detectability of tumors and microcalcifications behaves differently with respect to beam quality and dose. The results for small microcalcifications were similar to what traditional optimization methods yield, which is to be expected because quantum noise dominates over anatomical noise at high spatial frequencies. For larger tumors, however, low-frequency anatomical noise was the limiting factor. Because anatomical structure noise has similar energy dependence as tumor contrast, the optimal x-ray energy was found to be higher and the useful energy region was wider than traditional methods suggest. A simplified scalar model was able to capture this behavior using a fitted noise mixing parameter. The phantom measurements confirmed these theoretical results. Conclusions: It was shown that since quantum noise constitutes only a small fraction of the noise, the dose could be reduced substantially without sacrificing tumor detectability. Furthermore, when anatomical noise is included, the tube voltage can be increased well beyond what is conventionally considered optimal and used clinically, without loss of image quality. However, no such conclusions can be drawn for the more complex mammographic imaging task as a whole [ABSTRACT FROM AUTHOR]

Purpose: Active matrix flat-panel imagers (AMFPIs) incorporating thick, segmented scintillators have demonstrated order-of-magnitude improvements in detective quantum efficiency (DQE) at radiotherapy energies compared to systems based on conventional phosphor screens. Such improved DQE values facilitate megavoltage cone-beam CT (MV CBCT) imaging at clinically practical doses. However, the MV CBCT performance of such AMFPIs is highly dependent on the design parameters of the scintillators. In this paper, optimization of the design of segmented scintillators was explored using a hybrid modeling technique which encompasses both radiation and optical effects. Methods: Imaging performance in terms of the contrast-to-noise ratio (CNR) and spatial resolution of various hypothetical scintillator designs was examined through a hybrid technique involvingMonte Carlo simulation of radiation transport in combination with simulation of optical gain distributions and optical point spread functions. The optical simulations employed optical parameters extracted from a best fit to measurement results reported in a previous investigation of a 1.13 cm thick, 1016 µm pitch prototype BGO segmented scintillator. All hypothetical designs employed BGO material with a thickness and element-to-element pitch ranging from 0.5 to 6 cm and from 0.508 to 1.524 mm, respectively. In the CNR study, for each design, full tomographic scans of a contrast phantom incorporating various soft-tissue inserts were simulated at a total dose of 4 cGy. Results: Theoretical values for contrast, noise, and CNR were found to be in close agreement with empirical results from the BGO prototype, strongly supporting the validity of the modeling technique. CNR and spatial resolution for the various scintillator designs demonstrate complex behavior as scintillator thickness and element pitch are varied--with a clear trade-off between these two imaging metrics up to a thickness of ~3 cm. Based on these results, an optimization map indicating the regions of design that provide a balance between these metrics was obtained. The map shows that, for a given set of optical parameters, scintillator thickness and pixel pitch can be judiciously chosen to maximize performance without resorting to thicker, more costly scintillators. Conclusions: Modeling radiation and optical effects in thick, segmented scintillators through use of a hybrid technique can provide a practical way to gain insight as to how to optimize the performance of such devices in radiotherapy imaging. Assisted by such modeling, the development of practical designs should greatly facilitate low-dose, soft tissue visualization employing MV CBCT imaging in external beam radiotherapy [ABSTRACT FROM AUTHOR]

Purpose: Transcranial magnetic resonance-guided focused ultrasound surgery is a noninvasive technique for causing selective tissue necrosis. Variations in density, thickness, and shape of the skull cause aberrations in the location and shape of the focal zone. In this paper, the authors propose a hybrid simulation-MR-ARFI technique to achieve aberration correction for transcranial MR-guided focused ultrasound surgery. The technique uses ultrasound beam propagation simulations with MR Acoustic Radiation Force Imaging (MR-ARFI) to correct skull-caused phase aberrations. Methods: Skull-based numerical aberrations were obtained from a MR-guided focused ultrasound patient treatment and were added to all elements of the InSightec conformal bone focused ultrasound surgery transducer during transmission. In the first experiment, the 1024 aberrations derived from a human skull were condensed into 16 aberrations by averaging over the transducer area of 64 elements. In the second experiment, all 1024 aberrations were applied to the transducer. The aberrated MR-ARFI images were used in the hybrid simulation-MR-ARFI technique to find 16 estimated aberrations. These estimated aberrations were subtracted from the original aberrations to result in the corrected images. Each aberration experiment (16-aberration and 1024-aberration) was repeated three times Results: The corrected MR-ARFI image was compared to the aberrated image and the ideal image (image with zero aberrations) for each experiment. The hybrid simulation-MR-ARFI technique resulted in an average increase in focal MR-ARFI phase of 44% for the 16-aberration case and 52% for the 1024-aberration case, and recovered 83% and 39% of the ideal MR-ARFI phase for the 16- aberrations and 1024-aberration case, respectively. Conclusions: Using one MR-ARFI image and no a priori information about the applied phase aberrations, the hybrid simulation-MR-ARFI technique improved the maximum MRARFI phase of the beam's focus. [ABSTRACT FROM AUTHOR]

Purpose: This paper describes the development of a forward planning process for modulated electron radiotherapy (MERT). The approach is based on a previously developed electron beam model used to calculate dose distributions of electron beams shaped by a photon multi leaf collimator (pMLC). Methods: As the electron beam model has already been implemented into the Swiss Monte Carlo Plan environment, the Eclipse treatment planning system (Varian Medical Systems, Palo Alto, CA) can be included in the planning process for MERT. In a first step, CT data are imported into Eclipse and a pMLC shaped electron beam is set up. This initial electron beam is then divided into segments, with the electron energy in each segment chosen according to the distal depth of the planning target volume (PTV) in beam direction. In order to improve the homogeneity of the dose distribution in the PTV, a feathering process (Gaussian edge feathering) is launched, which results in a number of feathered segments. For each of these segments a dose calculation is performed employing the inhouse developed electron beam model along with the macro Monte Carlo dose calculation algorithm. Finally, an automated weight optimization of all segments is carried out and the total dose distribution is read back into Eclipse for display and evaluation. One academic and two clinical situations are investigated for possible benefits of MERT treatment compared to standard treatments performed in our clinics and treatment with a bolus electron conformal (BolusECT) method. Results: The MERT treatment plan of the academic case was superior to the standard single segment electron treatment plan in terms of organs at risk (OAR) sparing. Further, a comparison between an unfeathered and a feathered MERT plan showed better PTV coverage and homogeneity for the feathered plan, with V95% increased from 90% to 96% and V107% decreased from 8% to nearly 0%. For a clinical breast boost irradiation, the MERT plan led to a similar homogeneity in the PTV compared to the standard treatment plan while the mean body dose was lower for the MERT plan. Regarding the second clinical case, a whole breast treatment, MERT resulted in a reduction of the lung volume receiving more than 45% of the prescribed dose when compared to the standard plan. On the other hand, the MERT plan leads to a larger low-dose lung volume and a degraded dose homogeneity in the PTV. For the clinical cases evaluated in this work, treatment plans using the BolusECT technique resulted in a more homogenous PTV and CTV coverage but higher doses to the OARs than theMERT plans. Conclusions: MERT treatments were successfully planned for phantom and clinical cases, applying a newly developed intuitive and efficient forward planning strategy that employs a MC based electron beam model for pMLC shaped electron beams. It is shown that MERT can lead to a dose reduction in OARs compared to other methods. The process of feathering MERT segments results in an improvement of the dose homogeneity in the PTV. [ABSTRACT FROM AUTHOR]

The 2012 Summer School of the American Association of Physicists in Medicine (AAPM) focused on optimization of the use of ionizing radiation in medical imaging. Day 2 of the Summer School was devoted to fluoroscopy and interventional radiology and featured seven lectures. These lectures have been distilled into a single review paper covering equipment specification and siting, equipment acceptance testing and quality control, fluoroscope configuration, radiation effects, dose estimation and measurement, and principles of flat panel computed tomography. This review focuses on modern fluoroscopic equipment and is comprised in large part of information not found in textbooks on the subject. While this review does discuss technical aspects of modern fluoroscopic equipment, it focuses mainly on the clinical use and support of such equipment, from initial installation through estimation of patient dose and management of radiation effects. This review will be of interest to those learning about fluoroscopy, to those wishing to update their knowledge of modern fluoroscopic equipment, to those wishing to deepen their knowledge of particular topics, such as flat panel computed tomography, and to those who support fluoroscopic equipment in the clinic. [ABSTRACT FROM AUTHOR]