Validation of fully automatic brain SPET to MR co-registration

Fully automatic co-registration of functional to anatomical brain images using information intrinsic to the scans has been validated in a clinical setting for positron emission tomography (PET), but not for single-photon emission tomography (SPET). In this paper we evaluate technetium-99m hexamethylpropylene amine oxime to magnetic resonance (MR) co-registration for five fully automatic methods. We attached six small fiducial markers, visible in both SPET and MR, to the skin of 13 subjects. No increase in the radius of SPET acquisition was necessary. Distortion of the fiducial marker distribution observed in the SPET and MR studies was characterised by a measure independent of registration and three subjects were excluded on the basis of excessive distortion. The location of each fiducial marker was determined in each modality to sub-pixel precision and the inter-modality distance was averaged over all markers to give a fiducial registration error (FRE). The component of FRE excluding the variability inherent in the validation method was estimated by computing the error transformation between the arrays of MR marker locations and registered SPET marker locations. When applied to the fiducial marker locations this yielded the surface registration error (SRE), and when applied to a representative set of locations within the brain it yielded the intrinsic registration error (IRE). For the best method, mean IRE was 1.2 mm, SRE 1.5 mm and FRE 2.4 mm (with corresponding maxima of 3.3, 4.3 and 5.0 mm). All methods yielded a mean IRE <3 mm. The accuracy of the most accurate fully automatic SPET to MR co-registration was comparable with that published for PET to MR. With high standards of calibration and instrumentation, intra-subject cerebral SPET to MR registration accuracy of <2 mm is attainable.     

Validation of fully automatic brain SPET to MR co-registration

Fully automatic co-registration of functional to anatomical brain images using information intrinsic to the scans has been validated in a clinical setting for positron emission tomography (PET), but not for single-photon emission tomography (SPET). In this paper we evaluate technetium-99m hexamethylpropylene amine oxime to magnetic resonance (MR) co-registration for five fully automatic methods. We attached six small fiducial markers, visible in both SPET and MR, to the skin of 13 subjects. No increase in the radius of SPET acquisition was necessary. Distortion of the fiducial marker distribution observed in the SPET and MR studies was characterised by a measure independent of registration and three subjects were excluded on the basis of excessive distortion. The location of each fiducial marker was determined in each modality to sub-pixel precision and the inter-modality distance was averaged over all markers to give a fiducial registration error (FRE). The component of FRE excluding the variability inherent in the validation method was estimated by computing the error transformation between the arrays of MR marker locations and registered SPET marker locations. When applied to the fiducial marker locations this yielded the surface registration error (SRE), and when applied to a representative set of locations within the brain it yielded the intrinsic registration error (IRE). For the best method, mean IRE was 1.2 mm, SRE 1.5 mm and FRE 2.4 mm (with corresponding maxima of 3.3, 4.3 and 5.0 mm). All methods yielded a mean IRE <3 mm. The accuracy of the most accurate fully automatic SPET to MR co-registration was comparable with that published for PET to MR. With high standards of calibration and instrumentation, intra-subject cerebral SPET to MR registration accuracy of <2 mm is attainable. Received 29 May and in revised form 6 October 1999     

Registration of [18F]FDG microPET and small-animal MRI

This paper describes a voxel-based method for coregistering microPET [(18)F]FDG emission images and MRI data without the need for fiducial markers. [(18)F]FDG has a well-characterized biodistribution in normal mice and thus may be useful for image registration. Female BALB/c mice were implanted with EMT-6 mouse mammary carcinoma 1 week prior to imaging. Three imaging sessions were performed in which a [(18)F]FDG microPET-R4 emission scan was taken followed by small-animal MRI with and without Gd-based contrast agent. MicroPET and MR images were registered using a voxel-based algorithm that computes rigid-body image transformations based on the alignment of intensity gradients. Registration accuracy was assessed on the basis of dual-modality external fiducial line sources incorporated into the mouse bed. The root mean square (rms) registration errors were 0.74 mm translation and 1.44 degrees rotation without contrast and 0.72 mm translation and 0.89 degrees rotation with contrast. Generally, good registration was evident upon inspection of fused microPET/MR images. Accurate automated, voxel-based microPET-MR image coregistration, utilizing image intensity gradients, is feasible. Our technique requires no manual identification of image features and makes no use of surgically implanted or external fiducial markers or stereotactic apparatus.     

Co-registration of x-ray and MR fields of view in a hybrid XMR system

PURPOSE: To validate one possible function of a real-time x-ray/MR (XMR) interface in a hybrid XMR system using x-ray images as "scouts" to prescribe the MR slices. MATERIALS AND METHODS: The registration process consists of two steps: 1) calibration, in which the system's geometric parameters are found from fiducial-based registration; and 2) application, in which the x-ray image of a target structure and the estimated geometric parameters are used to prescribe an MR slice to observe the target structure. Errors from the noise in the location of the fiducial markers, and MR gradient nonlinearity were studied. Computer simulations were used to provide guidelines for fiducial marker placement and tolerable error estimation. A least-squares-based correction method was developed to reduce errors from gradient nonlinearity. RESULTS: In simulations with both sources of errors and the correction for gradient nonlinearity, the use of 16 fiducial markers yielded a mean error of about 0.4 mm over a 7200 cm(3) volume. Phantom scans showed that the prescribed target slice hit most of the target line, and that the length visualized was improved with the least-squares correction. CONCLUSION: The use of 16 fiducial markers to co-register XMR FOVs can offer satisfactory accuracy in both simulations and experiments.     

Intensity-based 2D-3D spine image registration incorporating a single fiducial marker

RATIONALE AND OBJECTIVES: The two-dimensional (2D)-three dimensional (3D) registration of a computed tomography image to one or more x-ray projection images has a number of image-guided therapy applications. In general, fiducial marker-based methods are fast, accurate, and robust, but marker implantation is not always possible, often is considered too invasive to be clinically acceptable, and entails risk. There also is the unresolved issue of whether it is acceptable to leave markers permanently implanted. Intensity-based registration methods do not require the use of markers and can be automated because such geometric features as points and surfaces do not need to be segmented from the images. However, for spine images, intensity-based methods are susceptible to local optima in the cost function and thus need initial transformations that are close to the correct transformation. MATERIALS AND METHODS: In this report, we propose a hybrid similarity measure for 2D-3D registration that is a weighted combination of an intensity-based similarity measure (mutual information) and a point-based measure using one fiducial marker. We evaluate its registration accuracy and robustness by using gold-standard clinical spine image data from four patients. RESULTS: Mean registration errors for successful registrations for the four patients were 1.3 and 1.1 mm for the intensity-based and hybrid similarity measures, respectively. Whereas the percentage of successful intensity-based registrations (registration error < 2.5 mm) decreased rapidly as the initial transformation got further from the correct transformation, the incorporation of a single marker produced successful registrations more than 99% of the time independent of the initial transformation. CONCLUSION: The use of one fiducial marker reduces 2D-3D spine image registration error slightly and improves robustness substantially. The findings are potentially relevant for image-guided therapy. If one marker is sufficient to obtain clinically acceptable registration accuracy and robustness, as the preliminary results using the proposed hybrid similarity measure suggest, the marker can be placed on a spinous process, which could be accomplished without penetrating muscle or using fluoroscopic guidance, and such a marker could be removed relatively easily.     

An imaging co-registration system using novel non-invasive and non-radioactive external markers

We present a system of image co-registration and its validation in phantom and volunteer studies. The system co-registered images via six novel non-invasive and non-radioactive external markers. The fiducial markers were attached with sponge bases on the skin surface of the phantom and the volunteers in a non-collinear and non-coplanar array. The subjects were scanned with a 1.5-T magnetic resonance (MR) imager using 2D spin-echo T1-weighted (SE) and 3D spoiled gradient recalled pulse sequences (SPGR) and with a positron emission tomography (PET) scanner for transmission imaging (TI) and emission imaging (EI). The sponge bases created radiolucent gaps with good contrast between the fiducial markers and skin surface. They made the markers visible with clear edge boundaries on both PET and MR images. The images to be registered were rescaled, interpolated, reformatted and followed by point-to-point registration for coordinate determination and the estimation of geometrical transformation and fiducial registration errors (FREs) via the fiducial markers. The images formed four matched pairs of inter-modality (SE-TI, SPGR-TI, SE-EI and SPGR-EI) and two pairs of intra-modality (SE-SPGR, TI-EI) imaging for direct co-registration. The parameters for direct co-registration of SE-TI and SPRG-TI were subsequently used as a bridge and applied for indirect co-registration of SE with EI (SE-EI(TI)) and SPGR with EI (SPGR-EI(TI)), respectively. The overall FREs of the phantom were, respectively, 1.50 mm for inter-modality and 1.10 mm for intra-modality direct co-registration. Those of volunteers were, respectively, 1.79 mm for inter-modality and 1.21 mm for intra-modality direct co-registration. For indirect co-registration, the overall FREs of the phantom were 2.53 mm (SE-EI(TI)) and 2.28 (SPGR-EI(TI)) mm; those of volunteers were 2.84 mm (SE-EI(TI)) and 2.81 mm (SPGR-EI(TI)). The errors of direct co-registration were smaller than those of indirect co-registration; the errors of phantom studies, MR-EI and SPGR-PET were smaller than those of the volunteer studies, MR-TI and SE-PET, respectively (all P<0.01, paired-difference test). In conclusion, motion artefacts, imaging blurring and spatial resolution of imaging remained the key factors affecting the accuracy of co-registration. High-accuracy indirect co-registration is provided by using non-invasive and non-radioactive external fiducial markers. The errors were less than 3 mm for both phantom and volunteer studies. The system is applicable for imaging co-registration of inter-modality non-dual imaging, inter-modality multi-tracer imaging and intra-modality multiple parameter images in clinical practice.     

Gangliogliomas: characterization by registered positron emission tomography-MR images

OBJECTIVE: The purpose of this study was to correlate 18F-fluorodeoxyglucose positron emission tomography (PET) and MR imaging features of cerebral gangliogliomas before and after PET-MR image registration. CONCLUSION: After registration of PET and MR images, all six gangliogliomas in our series were shown to have heterogeneous metabolic activity. Areas of hypermetabolic activity were seen in all lesions. In five of the six cases, PET-MR image registration provided information regarding tumor metabolism that was not available on nonregistered hard-copy examinations.     

Transmission imaging for registration of ictal and interictal single-photon emission tomography, magnetic resonance imaging and electroencephalography

A method developed for registration of ictal and interictal single-photon emission tomography (SPET), magnetic resonance imaging (MRI) and electroencephalography (EEG) is described. For SPET studies, technetium-99m ethyl cysteinate dimer (ECD) was injected intravenously while the patient was monitored on video-EEG to document the ictal or interictal state. Imaging was performed using a triple-head gamma camera equipped with a transmission imaging device using a gadolinium-153 source. The images (128x128 pixels, voxel size 3.7x3.7x3.6 mm3) were reconstructed using an iterative algorithm and postfiltered with a Wiener filter. The gold-plated silver electrodes on the patient's scalp were utilized as markers for registration of the ictal and interictal SPET images, as these metallic markers were clearly seen on the transmission images. Fitting of the marker sets was based on a non-iterative least squares method. The interictal SPET image was subtracted from the ictal image after scaling. The T1-weighted MPRAGE MR images with voxel size of 1.0x1.0x1.0 mm3 were obtained with a 1.5-T scanner. For registration of MR and subtraction SPET images, the external marker set of the ictal SPET study was fitted to the surface of the head segmented from MR images. The SPET registration was tested with a phantom experiment. Registration of ictal and interictal SPET in five patient studies resulted in a 2-mm RMS residual of the marker sets. The estimated RMS error of registration in the final result combining locations of the electrodes, subtraction SPET and MR images was 3-5 mm. In conclusion, transmission imaging can be utilized for an accurate and easily implemented registration procedure for ictal and interictal SPET, MRI and EEG.     

Registration of prostate histology images to ex vivo MR images via strand‐shaped fiducials

Purpose:

To present and evaluate a method for registration of whole‐mount prostate digital histology images to ex vivo magnetic resonance (MR) images.

Materials and Methods:

Nine radical prostatectomy specimens were marked with 10 strand‐shaped fiducial markers per specimen, imaged with T1‐ and T2‐weighted 3T MRI protocols, sliced at 4.4‐mm intervals, processed for whole‐mount histology, and the resulting histological sections (3–5 per specimen, 34 in total) were digitized. The correspondence between fiducial markers on histology and MR images yielded an initial registration, which was refined by a local optimization technique, yielding the least‐squares best‐fit affine transformation between corresponding fiducial points on histology and MR images. Accuracy was quantified as the postregistration 3D distance between landmarks (3–7 per section, 184 in total) on histology and MR images, and compared to a previous state‐of‐the‐art registration method.

Results:

The proposed method and previous method had mean (SD) target registration errors of 0.71 (0.38) mm and 1.21 (0.74) mm, respectively, requiring 3 and 11 hours of processing time, respectively.

Conclusion:

The proposed method registers digital histology to prostate MR images, yielding 70% reduced processing time and mean accuracy sufficient to achieve 85% overlap on histology and ex vivo MR images for a 0.2 cc spherical tumor. J. Magn. Reson. Imaging 2012; 36:1402–1412. © 2012 Wiley Periodicals, Inc.     

A method for fast 3D tracking using tuned fiducial markers and a limited projection reconstruction FISP (LPR-FISP) sequence.

This work demonstrates the feasibility of using wireless, tuned fiducial markers with a limited projection reconstruction-fast imaging with steady-state free precession sequence (LPR-FISP) to accurately obtain tracking information necessary for interactive scan plane selection in magnetic resonance imaging (MRI). The position and orientation of a rigid interventional device can be uniquely determined from the 3D coordinates of three fiducial markers mounted in a known configuration on the device. Three fiducial markers were tuned to the proton resonant frequency in a 0.2T open MR scanner and mounted to the surface of a cylindrical water phantom. An LPR-FISP sequence was developed to suppress the water phantom signal while preserving that of the fiducial markers through a nonselective low-tip-angle excitation and a dephaser gradient applied prior to data acquisition. A localization algorithm was developed to accurately calculate the 3D coordinates of the fiducial markers using four LPR-FISP projections in two orthogonal scan planes. The sequence repetition time (TR = 21 msec) and the limited projection set resulted in fast LPR-FISP coordinate acquisition times of approximately 170 msec with an accuracy (max error) of 3 mm on a 0.2T MR system. This fast, accurate tracking method provides the fundamental technology for interactive MRI scan plane definition for rigid interventional devices without the need for stereotactic cameras or reference frames.     

Registration of three-dimensional MR and CT studies of the cervical spine

A three-dimensional image registration technique for CT and MR studies of the cervical spine was evaluated for feasibility and efficacy. Registration by means of external fiducial markers was slightly more accurate than registration by anatomic landmarks. The interrelationships between bony (eg, neural foramina) and soft tissue structures (eg, nerve roots) in the cervical spine were more conspicuous on registered images than on conventional displays. Registration of CT and MR images may be used to examine more precisely the relationships between bony and soft tissue structures of the cervical spine.     

Image-guidance technique comparison on respiratory reproducibility and dose indexes for stereotactic body radiotherapy in lung tumor

We investigated respiratory reproducibility from position errors of gold internal fiducial markers for breath-hold (BH) and real-time tumor tracking (RTT) techniques for stereotactic body radiotherapy in lung tumors. The relationship between position errors and dose indexes was checked for both techniques. The stereotactic body radiotherapy plan in lung tumors was planned for 29 patients. The tumor positioning was arranged using 1.5 mm diameter gold internal fiducial markers. First, CT images were acquired to analyze position errors of gold markers for BH and RTT techniques. The offset plans for both techniques were calculated by displacing the mean position errors. The dose indexes (D98, D95, D2, mean dose) in a planning target volume were evaluated from dose volume histograms for the original plan, BH, and RTT offset plans. The relationship between position errors and dose indexes was analyzed using the root mean square (RMS) for both techniques. For the BH, the RMS was 3.29 mm at the lower lobe. Similarly, it was 1.34 mm for the RTT. The difference for D98 by position error for BH was ?7.0 ± 10.8% at the lower lobe and the difference of all dose indexes for the RTT was less than 1%. The D2 and mean dose for both techniques were nearly the same as those of the original plan. In conclusion, the adaptation of the BH technique should be ≤2 mm RMS. If the position error is >2 mm RMS, the RTT technique should be used instead of the BH technique.     

Transmission imaging for registration of ictal and interictal single-photon emission tomography, magnetic resonance imaging and electroencephalography

A method developed for registration of ictal and interictal single-photon emission tomography (SPET), magnetic resonance imaging (MRI) and electroencephalography (EEG) is described. For SPET studies, technetium-99m ethyl cysteinate dimer (ECD) was injected intravenously while the patient was monitored on video-EEG to document the ictal or interictal state. Imaging was performed using a triple-head gamma camera equipped with a transmission imaging device using a gadolinium-153 source. The images (128×128 pixels, voxel size 3.7×3.7×3.6 mm³) were reconstructed using an iterative algorithm and postfiltered with a Wiener filter. The gold-plated silver electrodes on the patient’s scalp were utilized as markers for registration of the ictal and interictal SPET images, as these metallic markers were clearly seen on the transmission images. Fitting of the marker sets was based on a non-iterative least squares method. The interictal SPET image was subtracted from the ictal image after scaling. The T1-weighted MPRAGE MR images with voxel size of 1.0×1.0×1.0 mm³ were obtained with a 1.5-T scanner. For registration of MR and subtraction SPET images, the external marker set of the ictal SPET study was fitted to the surface of the head segmented from MR images. The SPET registration was tested with a phantom experiment. Registration of ictal and interictal SPET in five patient studies resulted in a 2-mm RMS residual of the marker sets. The estimated RMS error of registration in the final result combining locations of the electrodes, subtraction SPET and MR images was 3–5 mm. In conclusion, transmission imaging can be utilized for an accurate and easily implemented registration procedure for ictal and interictal SPET, MRI and EEG. Received 20 September and in revised form 16 October 1999     

Assessment of a technique for 2D-3D registration of cerebral intra-arterial angiography

This study assesses the ability of a computer algorithm to perform automated 2D-3D registrations of digitally subtracted cerebral angiograms. The technique was tested on clinical studies of five patients with intracranial aneurysms. The automated procedure was compared against a gold standard manual registration, and achieved a mean registration accuracy of 1.3 mm (SD 0.6 mm). Two registration strategies were tested using coarse (128 x 128 pixel) or fine (256 x 256 pixel) images. The mean registration errors proved similar but registration of the lower resolution images was 3 times quicker (mean registration times 33 s, SD 13 s for low and 150 s SD 48 s for high resolution images). The automated techniques were considerably faster than manual registrations but achieved similar accuracy. The technique has several potential uses but is particularly applicable to endovascular treatment techniques.     

A comparative study on manual and automatic slice-to-volume registration of CT images

In order to assess the clinical relevance of a slice-to-volume registration algorithm, this technique was compared to manual registration. Reformatted images obtained from a diagnostic CT examination of the lower abdomen were reviewed and manually registered by 41 individuals. The results were refined by the algorithm. Furthermore, a fully automatic registration of the single slices to the whole CT examination, without manual initialization, was also performed. The manual registration error for rotation and translation was found to be 2.7±2.8 ° and 4.0±2.5 mm. The automated registration algorithm significantly reduced the registration error to 1.6±2.6 ° and 1.3±1.6 mm (p = 0.01). In 3 of 41 (7.3%) registration cases, the automated registration algorithm failed completely. On average, the time required for manual registration was 213±197 s; automatic registration took 82±15 s. Registration was also performed without any human interaction. The resulting registration error of the algorithm without manual pre-registration was found to be 2.9±2.9 ° and 1.1±0.2 mm. Here, a registration took 91±6 s, on average. Overall, the automated registration algorithm improved the accuracy of manual registration by 59% in rotation and 325% in translation. The absolute values are well within a clinically relevant range.     

Alginate moulding: an empirical method for magnetic resonance imaging/positron emission tomography co-registration in a tumor rat model

BACKGROUND AND PURPOSE: In the experimental field of animal models, co-registration between positron emission tomography (PET) and magnetic resonance imaging (MRI) data still relies on non-automated post-processing using sophisticated algorithms and software developments. We assessed the value of an empirical method using alginate moulding for PET-MR co-registration in a tumor rat model. METHODS: Male WAG/RijHsd rats bearing grafted syngenic rhabdomyosarcoma were examined under general anesthesia by MRI using a clinical whole-body 3-T system equipped with a sensitivity-encoding four-channel wrist coil and by a small animal PET system using labelled [(18)F]-fluorocholine as tracer. An alginate mould including a system of external fiducials was manufactured for each animal, allowing strict immobilization and similar positioning for both modalities. Fourteen rats (27 tumors) had only one MR/PET imaging session. Five rats (9 tumors) had a similar MR/PET session before and 3 days after external radiation therapy (13 Gy in one fraction) using the same mould. Co-registration was performed using the Pmod release 2.75 software (PMOD Technologies, Ltd., Adliswil, Switzerland) with mutual information algorithm. RESULTS: The manufacture of the alginate moulds was easy and innocuous. Imaging sessions were well tolerated. PET-MR co-registration based on mutual information was perfect at visual examination, which was confirmed by the superimposition of external fiducials on fused images. Reuse of the same mould for the post-therapeutic session was feasible 3 days after the pre-therapeutic one in spite of tumor growth. CONCLUSION: The empirical method using alginate moulding with external fiducials for PET-MR co-registration in a rodent tumor model was feasible and accurate.     

PET与MRI三维脑图像高精度配准

目的 在PC机上实现高精度的PET与MRI三维脑图像配准。方法 采用最大互信息法对6例患者PET和MRI三维脑图像进行刚体配准。使用归一化互信息作为相似性量度。在互信息计算过程中，使用Powell多参数优化法和Brent一维搜索算法。为加快配准速度，使用了多分辨金字塔方法。采用基于坐标的阈值选取方法对PET图像进行分割预处理，消除星状背景伪影。结果 配准误差平均值为2．6mm，误差中位数平均为2．7mm。结论 配准视觉效果良好，评估证明该算法可达亚体元级配准精度。     

Unsupervised estimation of myocardial displacement from tagged MR sequences using nonrigid registration.

We propose a fully automatic cardiac motion estimation technique that uses nonrigid registration between temporally adjacent images to compute the myocardial displacement field from tagged MR sequences using as inputs (sources) both horizontally and vertically tagged images. We present a new multisource nonrigid registration algorithm employing a semilocal deformation model that provides controlled smoothness. The method requires no segmentation. We apply a multiresolution optimization strategy for better speed and robustness. The accuracy of the algorithm is assessed on experimental data (animal model) and healthy volunteer data by calculating the root mean square (RMS) difference in position between the estimated tag trajectories and manual tracings outlined by an expert. For the approximately 20000 tag lines analyzed (45 slices over 20-40 time frames), the RMS difference between the automatic tag trajectories and the manually segmented tag trajectories was 0.51 pixels (0.25 mm) for the animal data and 0.49 pixels (0.49 mm) for the human volunteer data. The RMS difference in the separation between adjacent tag lines (RMS_TS) was also assessed, resulting in an RMS_TS of 0.40 pixels (0.19 mm) in the experimental data and 0.52 pixels (0.56 mm) in the volunteer data. These results confirm the subpixel accuracy achieved using the proposed methodology.     

Prostate cancer: precision of integrating functional MR imaging with radiation therapy treatment by using fiducial gold markers

The use of intensity-modulated radiation therapy for treatment of dominant intraprostatic lesions may require integration of functional magnetic resonance (MR) imaging with treatment-planning computed tomography (CT). The purpose of this study was to compare prospectively the landmark and iterative closest point methods for registration of CT and MR images of the prostate gland after placement of fiducial markers. The study was approved by the institutional ethics review board, and informed consent was obtained. CT and MR images were registered by using fiducial gold markers that were inserted into the prostate. Two image registration methods--a commonly available landmark method and dedicated iterative closest point method--were compared. Precision was assessed for a data set of 21 patients by using five operators. Precision of the iterative closest point method (1.1 mm) was significantly better (P < .01) than that of the landmark method (2.0 mm). Furthermore, a method is described by which multimodal MR imaging data are reduced into a single interpreted volume that, after registration, can be incorporated into treatment planning.     

Automated analysis of small animal PET studies through deformable registration to an atlas

Purpose

This work aims to develop a methodology for automated atlas-guided analysis of small animal positron emission tomography (PET) data through deformable registration to an anatomical mouse model.

Methods

A non-rigid registration technique is used to put into correspondence relevant anatomical regions of rodent CT images from combined PET/CT studies to corresponding CT images of the Digimouse anatomical mouse model. The latter provides a pre-segmented atlas consisting of 21 anatomical regions suitable for automated quantitative analysis. Image registration is performed using a package based on the Insight Toolkit allowing the implementation of various image registration algorithms. The optimal parameters obtained for deformable registration were applied to simulated and experimental mouse PET/CT studies. The accuracy of the image registration procedure was assessed by segmenting mouse CT images into seven regions: brain, lungs, heart, kidneys, bladder, skeleton and the rest of the body. This was accomplished prior to image registration using a semi-automated algorithm. Each mouse segmentation was transformed using the parameters obtained during CT to CT image registration. The resulting segmentation was compared with the original Digimouse atlas to quantify image registration accuracy using established metrics such as the Dice coefficient and Hausdorff distance. PET images were then transformed using the same technique and automated quantitative analysis of tracer uptake performed.

Results

The Dice coefficient and Hausdorff distance show fair to excellent agreement and a mean registration mismatch distance of about 6?mm. The results demonstrate good quantification accuracy in most of the regions, especially the brain, but not in the bladder, as expected. Normalized mean activity estimates were preserved between the reference and automated quantification techniques with relative errors below 10?% in most of the organs considered.

Conclusion

The proposed automated quantification technique is reliable, robust and suitable for fast quantification of preclinical PET data in large serial studies.