Signal-to-noise ratio in neuro activation PET studies

It has become commonplace to compare scanner sensitivity characteristics by comparing noise equivalent count rate curves. However, because a 20-cm diameter uniform phantom is drastically different from a human brain, these curves give misleading information when planning a neuro activation PET experiment. Signal-to-noise ratio (SNR) calculations have been performed using measured data (Siemens 921 scanner) from the three-dimensional (3-D) Hoffman brain phantom for the purpose of determining the optimal injection and scanning protocol for [ (15)O] labeled activation experiments. Region of interest (ROI) values along with the variance due to prompt (trues plus randoms) and random events were determined for various regions and radioactivity concentrations. Calculated attenuation correction was used throughout. Scatter correction was not used when calculating the SNR in activation studies because the number of scattered events is almost identical in each data acquisition and hence cancels. The authors results indicate that randoms correction should not be performed and that rather than being limited by the scanner capabilities, neuro activation experiments are limited by the amount of radioactivity that can be injected and the length of time the patient can stay in the scanner.     

Noise characteristics of 3-D and 2-D PET images

The authors analyzed the noise characteristics of two-dimensional (2-D) and three-dimensional (3-D) images obtained from the GE Advance positron emission tomography (PET) scanner. Three phantoms were used: a uniform 20-cm phantom, a 3-D Hoffman brain phantom, and a chest phantom with heart and lung inserts. Using gated acquisition, the authors acquired 20 statistically equivalent scans of each phantom in 2-D and 3-D modes at several activity levels. From these data, they calculated pixel normalized standard deviations (NSD's), scaled to phantom mean, across the replicate scans, which allowed them to characterize the radial and axial distributions of pixel noise. The authors also performed sequential measurements of the phantoms in 2-D and 3-D modes to measure noise (from interpixel standard deviations) as a function of activity. To compensate for the difference in axial slice width between 2-D and 3-D images (due to the septa and reconstruction effects), they developed a smoothing kernel to apply to the 2-D data. After matching the resolution, the ratio of image-derived NSD values (NSD_2D/NSD_3D)² averaged throughout the uniform phantom was in good agreement with the noise equivalent count (NEC) ratio (NEC_3D/NEC_2D). By comparing different phantoms, the authors showed that the attenuation and emission distributions influence the spatial noise distribution. The estimates of pixel noise for 2-D and 3-D images produced here can be applied in the weighting of PET kinetic data and may be useful in the design of optimal dose and scanning requirements for PET studies. The accuracy of these phantom-based noise formulas should be validated for any given imaging situation, particularly in 3-D, if there is significant activity outside the scanner field of view     

Optimization of noise equivalent count rate performance for a partially collimated PET scanner by varying the number of septa

We present a simulation study of the global count-rate performance of a positron emission tomography (PET) scanner with different levels of partial collimation to maximize the noise equivalent count rate for whole-body PET imaging. We achieve partial collimation by removing different numbers of septal rings from the standard 2-D septa set for the GE Advance PET scanner. System behavior is studied with a photon tracking simulation package, which we modify to enable the production of random coincidences. The simulations are validated with measured data taken in 2-D and fully 3-D acquisition mode on a GE Advance system using the National Electrical Manufacturers Association NU-2 count-rate phantom with two sets of annular sleeves to expand the diameter to 27 and 35 cm. For all diameters and in 2-D and fully 3-D mode, there is good agreement between measurements and simulations. All studies use the three phantom diameters to evaluate the effect of patient thickness for each amount of collimation. Optimized system parameters, such as maximum ring difference for single slice rebinning, are determined for the five partially collimated systems considered. The resulting global count rates for true, scattered, and random coincidences, the noise equivalent count (NEC) rates, and the scatter fractions for different levels of collimation are compared along with the results from the conventional 2-D and fully 3-D modes. Improved statistical data quality relative to both 2-D and fully 3-D data is found with the partially collimated systems, particularly when one-half or two-thirds of the septal rings are removed. An increase in NEC rates of as much as 50% is found for clinically relevant activities between 5-10 mCi (184-370 MBq). Scatter fractions for the partially collimated systems are intermediate between the 2-D and fully 3-D numbers. Many factors that affect image quality have not been considered in this paper. However, the significant increase in statistical data quality warrants further investigation of the impact of partial collimation on clinical whole-body PET imaging.     

Evaluation of the ECAT EXACT HR+ 3-D PET scanner in H2(15)O brain activation studies: dose fractionation strategies for rCBF and signal enhancing protocols

We evaluated the performance of the ECAT EXACT HR+ 3-D whole-body positron emission tomography (PET) scanner when employed to measure brain function using H2(15)O bolus activation protocols that are completed in single same-day data acquisition sessions. Using vibrotactile and auditory stimuli as independent activation tasks, we studied the scanner performance under different imaging conditions in five healthy volunteers. Cerebral blood flow images were acquired from each volunteer using H2(15)O bolus injections of activity varying from 5-20 mCi. One-session dose-fractionation strategies were analyzed for rCBF, standard activity-concentration, switched, and cold-bolus/switched protocols. Performance characteristics. The scanner dead time grew linearly with injected dose from 10% to 25%. Random events varied from 30% to 50% of the detected events. Random and scattered events were corrected adequately at all doses. Estimated noise-effective-count curves plateau at about 10 mCi. One-session 12-injection bolus PET activation protocols. Using an acquisition protocol that accounts for the scanner performance and the practical aspects of imaging volunteers and neurological patients in a single same-day session, we assessed the correlation between the significance of activation foci and the dose/injection used. The one-session protocol employs 12 bolus injections/subject. We present evidence suggesting that when an rCBF protocol is used, image noise is reduced significantly when the activity injected increases from 5 to 10 mCi. Increasing the dose from 10 to 15 or 20 mCi yielded further but smaller reductions. Our observations also suggest that image noise will be strongly reduced if a 20-mCi dose/injection is used when data are collected using protocols that employ long acquisition times such as a switched or a cold-bolus/switched protocol.     

Characterization of dynamic 3-D PET imaging for functional brainmapping

Methods for optimizing the acquisition, reconstruction and analysis of positron emission tomography (PET) images for functional brain mapping have been investigated. The scatter fraction and noise-equivalent count rate characteristics were measured for the ECAT 951/31R PET scanner operating in septa-extended two-dimensional (2-D) and septa-retracted three-dimensional (3-D) modes. The 3-D mode is shown to provide higher signal-to-noise images than the 2-D mode at specific activities less than 30 kBq/ml. To enable increased temporal resolution in dynamic 3-D PET activation studies, a parallel version of the 3-D reconstruction algorithm was developed. Implementation of the reprojection algorithm on an 88 processor i860 supercomputer resulted in a more than tenfold increase in reconstruction speed compared to a single i860 processor system. An investigation of the optimal duration for imaging brain activations was undertaken in 12 normal subjects using repeated H₂¹⁵O slow infusions and a visually presented lexical decision task. The significance of change in regional cerebral blood flow (CBF) was determined using statistical parametric maps for images acquired during stimulation, immediately after stimulation, and commencing 1 min after cessation of the stimulus. Regions of CBF change were detected in all three images. Dynamic 3-D, or four-dimensional (4-D), PET activation scanning is shown to be practical and likely to further improve the sensitivity of PET for detection of subtle regional CBF changes in functional brain mapping research     

Investigation of time-of-flight benefit for fully 3-D PET

The purpose of this paper is to determine the benefit that can be achieved in image quality for a time-of-flight (TOF) fully three-dimensional (3-D) whole-body positron emission tomography (PET) scanner. We simulate a 3-D whole-body time-of-flight PET scanner with a complete modeling of spatial and energy resolutions. The scanner is based on LaBr3 Anger-logic detectors with which 300ps timing resolution has been achieved. Multiple simulations were performed for 70-cm long uniform cylinders with 27-cm and 35-cm diameters, containing hot spheres (22, 17, 13, and 10-mm diameter) in a central slice and 10-mm diameter hot spheres in a slice at 1/4 axial FOV. Image reconstruction was performed with a list-mode iterative TOF algorithm and data were analyzed after attenuation and scatter corrections for timing resolutions of 300, 600, 1000 ps and non-TOF for varying count levels. The results show that contrast recovery improves slightly with TOF (NEMA NU2-2001 analysis), and improved timing resolution leads to a faster convergence to the maximum contrast value. Detectability for 10-mm diameter hot spheres estimated using a nonprewhitening matched filter (NPW SNR) also improves nonlinearly with TOF. The gain in image quality using contrast and noise measures is proportional to the object diameter and inversely proportional to the timing resolution of the scanner. The gains in NPW SNR are smaller, but they also increase with increasing object diameter and improved timing resolution. The results show that scan times can be reduced in a TOF scanner to achieve images similar to those from a non-TOF scanner, or improved image quality achieved for same scan times.     

Energy-based scatter correction for 3-D PET scanners using NaI(T1) detectors

Earlier investigations with BGO positron emission tomography (PET) scanners showed that the scatter correction technique based on multiple acquisitions with different energy windows are problematic to implement because of the poor energy resolution of BGO (22%), particularly for whole-body studies. We believe that these methods are likely to work better with NaI(TI) because of the better energy resolution achievable with NaI(TI) detectors (10%). Therefore, we investigate two different choices for the energy window, a low-energy window (LEW) on the Compton spectrum at 400-450 keV, and a high-energy window (HEW) within the photopeak (lower threshold above 511 keV). The results obtained for our three-dimensional (3-D) (septa-less) whole-body scanners [axial field of view (FOV) of 12.8 cm and 25.6 cm] as well as for our 3-D brain scanner (axial FOV of 25.6 cm) show an accurate prediction of the scatter distribution for the estimation of trues method (ETM) using a HEW, leading to a significant reduction of the scatter contamination. The dual-energy window (DEW) technique using a LEW is shown to be intrinsically wrong; in particular, it fails for line source and bar phantom measurements. However, the method is able to produce good results for homogeneous activity distributions. Both methods are easy to implement, are fast, have a low noise propagation, and will be applicable to other PET scanners with good energy resolution and stability, such as hybrid NaI(TI) PET/SPECT dual-head cameras and future PET cameras with GSO or LSO scintillators.     

Evaluating performance of reconstruction algorithms for 3-D [15O] water PET using subtraction analysis

Positron emission tomography (PET) [15O] activation studies have benefited significantly from three-dimensional (3-D) data acquisition. However, they have been slow to take advantage of new 3-D reconstruction techniques. Compared with the widely used 3-D reprojection reconstruction (3DRP), the advantage of signal and noise for iterative algorithms has been outweighed by concern about long and complicated reconstruction procedures and inconsistent performance. Most pseudo-3-D algorithms, such as rebinning methods, aim at increasing the speed of reconstruction but lack further resolution improvement or noise control. Although many evaluations have been conducted through simulations and phantom experiments, the spatially varying nature of signal and noise and the complexity of biological effects have complicated the interpretation of real data based on simulation or phantom results. We have taken a different approach and used the analysis of real data directly as a measure with which to compare three reconstruction algorithms: 3DRP, iterative filtered backprojection with median root prior (IFBP-MRP), and Fourier rebinning followed by two-dimensional (2-D) filtered backprojection (FORE-FBP) for [15O] PET. Two subjects, each with 32 scans acquired in four sessions during a finger opposition motor task, are analyzed using subtraction. A fixed volume-of-interest (VOI) measurement in regions related to the task demonstrates that at high resolution, IFBP-MRP has the best signal-to-noise performance followed by 3DRP and FORE-FBP; however, this advantage gradually diminishes as the resolution decreases. For a voxel measurement derived from the image of each reconstruction, all three algorithms are capable of detecting highly activated regions. Although there are some differences in the size, shape, and center location of the activated foci, our preliminary results suggest that IFBP-MRP does offer enhanced signal with some noise control compared with 3DRP for the analysis of high-resolution images. If images are to be analyzed at an intermediate to lower resolution, FORE-FBP provides a significant reduction of reconstruction time compared with 3DRP.     

Super-resolution in PET imaging

This paper demonstrates a super-resolution method for improving the resolution in clinical positron emission tomography (PET) scanners. Super-resolution images were obtained by combining four data sets with spatial shifts between consecutive acquisitions and applying an iterative algorithm. Super-resolution attenuation corrected PET scans of a phantom were obtained using the two-dimensional and three-dimensional (3-D) acquisition modes of a clinical PET/computed tomography (CT) scanner (Discovery LS, GEMS). In a patient study, following a standard 18F-FDG PET/CT scan, a super-resolution scan around one small lesion was performed using axial shifts without increasing the patient radiation exposure. In the phantom study, smaller features (3 mm) could be resolved axially with the super-resolution method than without (6 mm). The super-resolution images had better resolution than the original images and provided higher contrast ratios in coronal images and in 3-D acquisition transaxial images. The coronal super-resolution images had superior resolution and contrast ratios compared to images reconstructed by merely interleaving the data to the proper axial location. In the patient study, super-resolution reconstructions displayed a more localized 18F-FDG uptake. A new approach for improving the resolution of PET images using a super-resolution method has been developed and experimentally confirmed, employing a clinical scanner. The improvement in axial resolution requires no changes in hardware.     

A focus-of-attention preprocessing scheme for EM-ML PETreconstruction

The expectation-maximization maximum-likelihood (EM-ML) algorithm belongs to a family of algorithms that compute positron emission tomography (PET) reconstructions by iteratively solving a large linear system of equations. The authors describe a preprocessing scheme for automatically focusing the attention, and thus the computational resources, on a subset of the equations and unknowns. Experimental work with a CM-5 parallel computer implementation using a simulated phantom as well as real data obtained from an ECAT 921 PET scanner indicates that quite significant savings can be obtained with respect to both time and space requirements of the EM-ML algorithm without compromising the quality of the reconstructed images     

Restoration of gamma camera-based nuclear medicine images

Experiments were conducted using a Siemens Rota camera to study the applicability of two linear shift-invariant (LSI) filters, namely, the Wiener and power spectrum equalization filters, for restoration of planar projections and single-photon-emission computed tomography (SPECT) images. In the restoration scheme, the system transfer function, computed from a line source image, is modeled by a 2-D Gaussian function. The noise power spectrum is modeled as a constant for planar images and as a ramp for SPECT images. The filters have been applied to restore computer-simulated 1-D and 2-D projections and SPECT images of two simple phantoms, 2-D projections of two phantoms obtained from the Siemens Rota camera, and SPECT images of a cardiac phantom obtained from the Siemens Rota camera. The filters are shown to perform partial restoration. Considerable noise suppression and detail enhancement have been observed in the restored images. quantitative measurements such as root-mean-squared error and contrast ratio have been used for objective analysis of the results, which are encouraging.     

Noise equivalent count measurements in a neuro-PET scanner with retractable septa

The noise-equivalent count-rate (NEC) performance of a neuro-positron emission tomography (PET) scanner has been determined with and without interplane septa on uniform cylindrical phantoms of differing radii and in human studies to assess the optimum count rate conditions that realize the maximum gain. In the brain, the effective gain in NEC performance for three-dimensions (3-D) ranges from >5 at low count rates to approximately 3.3 at 200 kcps (equivalent to 37 kcps in 2-D). The gains of the 3-D method assessed by this analysis are significant, and are shown to be highly dependent on count rate and object dimensions.     

Novel scatter compensation of list-mode PET data using spatial and energy dependent corrections

With the widespread use of positron emission tomography (PET) crystals with greatly improved energy resolution (e.g., 11.5% with LYSO as compared to 20% with BGO) and of list-mode acquisitions, the use of the energy of individual events in scatter correction schemes becomes feasible. We propose a novel scatter approach that incorporates the energy of individual photons in the scatter correction and reconstruction of list-mode PET data in addition to the spatial information presently used in clinical scanners. First, we rewrite the Poisson likelihood function of list-mode PET data including the energy distributions of primary and scatter coincidences and show that this expression yields an MLEM reconstruction algorithm containing both energy and spatial dependent corrections. To estimate the spatial distribution of scatter coincidences we use the single scatter simulation (SSS). Next, we derive two new formulae which allow estimation of the 2-D (coincidences) energy probability density functions (E-PDF) of primary and scatter coincidences from the 1-D (photons) E-PDFs associated with each photon. We also describe an accurate and robust object-specific method for estimating these 1-D E-PDFs based on a decomposition of the total energy spectra detected across the scanner into primary and scattered components. Finally, we show that the energy information can be used to accurately normalize the scatter sinogram to the data. We compared the performance of this novel scatter correction incorporating both the position and energy of detected coincidences to that of the traditional approach modeling only the spatial distribution of scatter coincidences in 3-D Monte Carlo simulations of a medium cylindrical phantom and a large, nonuniform NCAT phantom. Incorporating the energy information in the scatter correction decreased bias in the activity distribution estimation by ~20% and ~40% in the cold regions of the large NCAT phantom at energy resolutions 11.5% and 20% at 511 keV, respectively, compared to when using the spatial information alone.     

Enhancing the multivariate signal of [15O] water PETstudies with a new nonlinear neuroanatomical registration algorithm [MRIapplication]

This paper addresses the problem of neuro-anatomical registration across individuals for functional [15O] water PET activation studies. A new algorithm for three-dimensional (3-D) nonlinear structural registration (warping) of MR scans is presented. The method performs a hierarchically scaled search for a displacement field, maximizing one of several voxel similarity measures derived from the two-dimensional (2-D) histogram of matched image intensities, subject to a regularizer that ensures smoothness of the displacement field. The effect of the nonlinear structural registration is studied when it is computed on anatomical MR scans and applied to coregistered [15O] water PET scans from the same subjects: in this experiment, a study of visually guided saccadic eye movements. The performance of the nonlinear warp is evaluated using multivariate functional signal and noise measures. These measures prove to be useful for comparing different intersubject registration approaches, e.g., affine versus nonlinear. A comparison of 12-parameter affine registration versus non-linear registration demonstrates that the proposed nonlinear method increases the number of voxels retained in the cross-subject mask. We demonstrate that improved structural registration may result in an improved multivariate functional signal-to-noise ratio (SNR). Furthermore, registration of PET scans using the 12-parameter affine transformations that align the coregistered MR images does not improve registration, compared to 12-parameter affine alignment of the PET images directly.     

Analytical calculation of volumes-of-intersection for iterative, fully 3-D PET reconstruction

Use of iterative algorithms to reconstruct three-dimensional (3-D) positron emission tomography (PET) data requires the computation of the system probability matrix. The pure geometrical contribution can easily be approximated by the length-of-intersection (LOI) between lines-of-response (LOR) and individual voxels. However, more accurate geometrical projectors are desirable. Therefore, we have developed a fast method for the analytical calculation of the 3-D shape and volume of volumes-of-intersection (VOI). This method provides an alternative robust projector with a uniformly continuous sampling of the image space. The enhanced calculation effort is facilitated by using several speedup techniques. Exploiting intrinsic symmetry relations and the sparseness of the system matrix allows to create an efficiently compressed matrix which can be precomputed and completely stored in memory. In addition, a new voxel addressing scheme has been implemented. This scheme avoids time-consuming symmetry transformations of voxel addresses by using an octant-wise symmetrically ordered field of voxels. The above methods have been applied for a fully 3-D, iterative reconstruction of 3-D sinograms recorded with a Siemens/CTI ECAT HR+ PET scanner. A comparison of the performance of the reconstruction using LOI weighting and VOI weighting is presented.     

Motion tracking for medical imaging: a nonvisible structured light tracking approach

We present a system for head motion tracking in 3D brain imaging. The system is based on facial surface reconstruction and tracking using a structured light (SL) scanning principle. The system is designed to fit into narrow 3D medical scanner geometries limiting the field of view. It is tested in a clinical setting on the high resolution research tomograph (HRRT), Siemens PET scanner with a head phantom and volunteers. The SL system is compared to a commercial optical tracking system, the Polaris Vicra system, from NDI based on translatory and rotary ground truth motions of the head phantom. The accuracy of the systems was similar, with root mean square (rms) errors of 0.09 degrees for ±20 degrees axial rotations, and rms errors of 0.24 mm for ± 25 mm translations. Tests were made using (1) a light emitting diode (LED) based miniaturized video projector, the Pico projector from Texas Instruments, and (2) a customized version of this projector replacing a visible light LED with a 850 nm near infrared LED. The latter system does not provide additional discomfort by visible light projection into the patient's eyes. The main advantage over existing head motion tracking devices, including the Polaris Vicra system, is that it is not necessary to place markers on the patient. This provides a simpler workflow and eliminates uncertainties related to marker attachment and stability. We show proof of concept of a marker less tracking system especially designed for clinical use with promising results.     

Anatomical-based FDG-PET reconstruction for the detection of hypo-metabolic regions in epilepsy

Positron emission tomography (PET) of the cerebral glucose metabolism has shown to be useful in the presurgical evaluation of patients with epilepsy. Between seizures, PET images using fluorodeoxyglucose (FDG) show a decreased glucose metabolism in areas of the gray matter (GM) tissue that are associated with the epileptogenic region. However, detection of subtle hypo-metabolic regions is limited by noise in the projection data and the relatively small thickness of the GM tissue compared to the spatial resolution of the PET system. Therefore, we present an iterative maximum-a-posteriori based reconstruction algorithm, dedicated to the detection of hypo-metabolic regions in FDG-PET images of the brain of epilepsy patients. Anatomical information, derived from magnetic resonance imaging data, and pathophysiological knowledge was included in the reconstruction algorithm. Two Monte Carlo based brain software phantom experiments were used to examine the performance of the algorithm. In the first experiment, we used perfect, and in the second, imperfect anatomical knowledge during the reconstruction process. In both experiments, we measured signal-to-noise ratio (SNR), root mean squared (rms) bias and rms standard deviation. For both experiments, bias was reduced at matched noise levels, when compared to post-smoothed maximum-likelihood expectation-maximization (ML-EM) and maximum a posteriori reconstruction without anatomical priors. The SNR was similar to that of ML-EM with optimal post-smoothing, although the parameters of the prior distributions were not optimized. We can conclude that the use of anatomical information combined with prior information about the underlying pathology is very promising for the detection of subtle hypo-metabolic regions in the brain of patients with epilepsy.     

Fully three-dimensional reconstruction for a PET camera with retractable septa

A fully 3-D reconstruction algorithm has been developed to reconstruct data from a 16 ring PET camera (a Siemens/CTI 953B) with automatically retractable septa. The tomograph is able to acquire coincidences between any pair of detector rings and septa retraction increases the total system count rate by a factor of 7.8 (including scatter) and 4.7 (scatter subtracted) for a uniform, 20 cm diameter cylinder. The reconstruction algorithm is based on 3-D filtered backprojection, expressed in a form suitable for the multi-angle sinogram data. Sinograms which are not measured due to the truncated cylindrical geometry of the tomograph, but which are required for a spatially invariant response function, are obtained by forward projection. After filtering, the complete set of sinograms is backprojected into a 3-D volume of 128x128x31 voxels using a voxel-driven procedure. The algorithm has been validated with simulation, and tested with both phantom and clinical data from the 953B.     

Resolution and noise properties of MAP reconstruction for fully 3-D PET

We derive approximate analytical expressions for the local impulse response and covariance of images reconstructed from fully three-dimensional (3-D) positron emission tomography (PET) data using maximum a posteriori (MAP) estimation. These expressions explicitly account for the spatially variant detector response and sensitivity of a 3-D tomograph. The resulting spatially variant impulse response and covariance are computed using 3-D Fourier transforms. A truncated Gaussian distribution is used to account for the effect on the variance of the nonnegativity constraint used in MAP reconstruction. Using Monte Carlo simulations and phantom data from the microPET small animal scanner, we show that the approximations provide reasonably accurate estimates of contrast recovery and covariance of MAP reconstruction for priors with quadratic energy functions. We also describe how these analytical results can be used to achieve near-uniform contrast recovery throughout the reconstructed volume.     

Continuous and discrete data rebinning in time-of-flight PET

This paper investigates data compression methods for time-of-flight (TOF) positron emission tomography (PET), which rebin the 3-D TOF measurements into a set of 2-D TOF data for a stack of transaxial slices. The goal of this work is to develop rebinning algorithms that are more accurate than the TOF single-slice-rebinning (TOF-SSRB) method proposed by Mullani in 1982. Two approaches are explored. The first one is based on a partial differential equation, which expresses a consistency condition for TOF-PET data with a Gaussian TOF profile. From this equation we derive an analytical rebinning algorithm, which is unbiased in the limit of continuous sampling. The second approach is discrete: each 2-D rebinned data sample is calculated as a linear combination of the 3-D TOF samples in the same axial plane parallel to the axis of the scanner. The coefficients of the linear combination are precomputed by optimizing a cost function which enforces both accuracy and good variance reduction, models the TOF profile, the axial PSF of the LORs, and the specific sampling scheme of the scanner. Measurements of a thorax phantom on a prototype TOF-PET scanner with a resolution of 550 ps show that the proposed discrete method improves the bias-variance trade-off and is a promising alternative to TOF-SSRB when data compression is required to achieve clinically acceptable reconstruction time.