Mapping of the prostate in endorectal coil-based MRI/MRSI and CT: A deformable registration and validation study

Task Group 174 Report: Utilization of [18 F]Fluorodeoxyglucose Positron Emission Tomography ([18 F]FDG-PET) in Radiation Therapy

The use of positron emission tomography (PET) in radiation therapy (RT) is rapidly increasing in the areas of staging, segmentation, treatment planning, and response assessment. The most common radiotracer is ¹⁸ F-fluorodeoxyglucose ([¹⁸ F]FDG), a glucose analog with demonstrated efficacy in cancer diagnosis and staging. However, diagnosis and RT planning are different endeavors with unique requirements, and very little literature is available for guiding physicists and clinicians in the utilization of [¹⁸ F]FDG-PET in RT. The two goals of this report are to educate and provide recommendations. The report provides background and education on current PET imaging systems, PET tracers, intensity quantification, and current utilization in RT (staging, segmentation, image registration, treatment planning, and therapy response assessment). Recommendations are provided on acceptance testing, annual and monthly quality assurance, scanning protocols to ensure consistency between interpatient scans and intrapatient longitudinal scans, reporting of patient and scan parameters in literature, requirements for incorporation of [¹⁸ F]FDG-PET in treatment planning systems, and image registration. The recommendations provided here are minimum requirements and are not meant to cover all aspects of the use of [¹⁸ F]FDG-PET for RT.

Synthetic head and neck and phantom images for determining deformable image registration accuracy in magnetic resonance imaging

PURPOSE

Magnetic resonance imaging (MRI) provides noninvasive evaluation of patient's anatomy without using ionizing radiation. Due to this and the high soft-tissue contrast, MRI use has increased and has potential for use in longitudinal studies where changes in patients' anatomy or tumors at different time points are compared. Deformable image registration can be useful for these studies. Here, we describe two datasets that can be used to evaluate the registration accuracy of systems for MR images, as it cannot be assumed to be the same as that measured on CT images.

ACQUISITION AND VALIDATION METHODS

Two sets of images were created to test registration accuracy. (a) A porcine phantom was created by placing ten 0.35-mm gold markers into porcine meat. The porcine phantom was immobilized in a plastic container with movable dividers. T1-weighted, T2-weighted, and CT images were acquired with the porcine phantom compressed in four different ways. The markers were not visible on the MR images, due to the selected voxel size, so they did not interfere with the measured registration accuracy, while the markers were visible on the CT images and were used to identify the known deformation between positions. (b) Synthetic images were created using 28 head and neck squamous cell carcinoma patients who had MR scans pre-, mid-, and postradiotherapy treatment. An inter- and intrapatient variation model was created using these patient scans. Four synthetic pretreatment images were created using the interpatient model, and four synthetic post-treatment images were created for each of the pretreatment images using the intrapatient model.

DATA FORMAT AND USAGE NOTES

The T1-weighted, T2-weighted, and CT scans of the porcine phantom in the four positions are provided. Four T1-weighted synthetic pretreatment images each with four synthetic post-treatment images, and four T2-weighted synthetic pretreatment images each with four synthetic post-treatment images are provided. Additionally, the applied deformation vector fields to generate the synthetic post-treatment images are provided. The data are available on TCIA under the collection MRI-DIR.

POTENTIAL APPLICATIONS

The proposed database provides two sets of images (one acquired and one computer generated) for use in evaluating deformable image registration accuracy. T1- and T2-weighted images are available for each technique as the different image contrast in the two types of images may impact the registration accuracy.

Multimodal image registration for the identification of dominant intraprostatic lesion in high-precision radiotherapy treatments

PURPOSE

The integration of CT and multiparametric MRI (mpMRI) is a challenging task in high-precision radiotherapy for prostate cancer. A simple methodology for multimodal deformable image registration (DIR) of prostate cancer patients is presented.

METHODS

CT and mpMRI of 10 patients were considered. Organs at risk and prostate were contoured on both scans. The dominant intraprostatic lesion was additionally delineated on MRI. After a preliminary rigid image registration, the voxel intensity of all the segmented structures in both scans except the prostate was increased by a specific amount (a constant additional value, A), in order to enhance the contrast of the main organs influencing its position and shape. 70 couples of scans were obtained by varying A from 0 to 800 and they were subsequently non-rigidly registered. Quantities derived from image analysis and contour statistics were considered for the tuning of the best performing A.

RESULTS

A = 200 resulted the minimum enhancement value required to obtain statistically significant superior registration results. Mean centre of mass distance between corresponding structures decreases from 7.4 mm in rigid registration to 5.3 mm in DIR without enhancement (DIR-0) and to 2.7 mm in DIR with A = 200 (DIR-200). Mean contour distance was 2.5, 1.9 and 0.67 mm in rigid registration, DIR-0 and DIR-200, respectively. In DIR-200 mean contours overlap increases of +13 and +24% with respect to DIR-0 and rigid registration, respectively.

CONCLUSION

Contour propagation according to the vector field resulting from DIR-200 allows the delineation of dominant intraprostatic lesion on CT scan and its use for high-precision radiotherapy treatment planning. Advances in knowledge: We investigated the application of a B-spline, mutual information-based multimodal DIR coupled with a simple, patient-unspecific but efficient contrast enhancement procedure in the pelvic body area, thus obtaining a robust and accurate methodology to transfer the functional information deriving from mpMRI onto a planning CT reference volume.

Accuracy of deformable image registration on magnetic resonance images in digital and physical phantoms

PURPOSE

Accurate deformable image registration is necessary for longitudinal studies. The error associated with commercial systems has been evaluated using computed tomography (CT). Several in-house algorithms have been evaluated for use with magnetic resonance imaging (MRI), but there is still relatively little information about MRI deformable image registration. This work presents an evaluation of two deformable image registration systems, one commercial (Velocity) and one in-house (demons-based algorithm), with MRI using two different metrics to quantify the registration error.

METHODS

The registration error was analyzed with synthetic MR images. These images were generated from interpatient and intrapatient variation models trained on 28 patients. Four synthetic post-treatment images were generated for each of four synthetic pretreatment images, resulting in 16 image registrations for both the T1- and T2-weighted images. The synthetic post-treatment images were registered to their corresponding synthetic pretreatment image. The registration error was calculated between the known deformation vector field and the generated deformation vector field from the image registration system. The registration error was also analyzed using a porcine phantom with ten implanted 0.35-mm diameter gold markers. The markers were visible on CT but not MRI. CT, T1-weighted MR, and T2-weighted MR images were taken in four different positions. The markers were contoured on the CT images and rigidly registered to their corresponding MR images. The MR images were deformably registered and the distance between the projected marker location and true marker location was measured as the registration error.

RESULTS

The synthetic images were evaluated only on Velocity. Root mean square errors (RMSEs) of 0.76 mm in the left-right (LR) direction, 0.76 mm in the anteroposterior (AP) direction, and 0.69 mm in the superior-inferior (SI) direction were observed for the T1-weighted MR images. RMSEs of 1.1 mm in the LR direction, 0.75 mm in the AP direction, and 0.81 mm in the SI direction were observed for the T2-weighted MR images. The porcine phantom MR images, when evaluated with Velocity, had RMSEs of 1.8, 1.5, and 2.7 mm in the LR, AP, and SI directions for the T1-weighted images and 1.3, 1.2, and 1.6 mm in the LR, AP, and SI directions for the T2-weighted images. When the porcine phantom images were evaluated with the in-house demons-based algorithm, RMSEs were 1.2, 1.5, and 2.1 mm in the LR, AP, and SI directions for the T1-weighted images and 0.81, 1.1, and 1.1 mm in the LR, AP, and SI directions for the T2-weighted images.

CONCLUSIONS

The MRI registration error was low for both Velocity and the in-house demons-based algorithm according to both image evaluation methods, with all RMSEs below 3 mm. This implies that both image registration systems can be used for longitudinal studies using MRI.

Use of image registration and fusion algorithms and techniques in radiotherapy: Report of the AAPM Radiation Therapy Committee Task Group No. 132

Image registration and fusion algorithms exist in almost every software system that creates or uses images in radiotherapy. Most treatment planning systems support some form of image registration and fusion to allow the use of multimodality and time-series image data and even anatomical atlases to assist in target volume and normal tissue delineation. Treatment delivery systems perform registration and fusion between the planning images and the in-room images acquired during the treatment to assist patient positioning. Advanced applications are beginning to support daily dose assessment and enable adaptive radiotherapy using image registration and fusion to propagate contours and accumulate dose between image data taken over the course of therapy to provide up-to-date estimates of anatomical changes and delivered dose. This information aids in the detection of anatomical and functional changes that might elicit changes in the treatment plan or prescription. As the output of the image registration process is always used as the input of another process for planning or delivery, it is important to understand and communicate the uncertainty associated with the software in general and the result of a specific registration. Unfortunately, there is no standard mathematical formalism to perform this for real-world situations where noise, distortion, and complex anatomical variations can occur. Validation of the software systems performance is also complicated by the lack of documentation available from commercial systems leading to use of these systems in undesirable 'black-box' fashion. In view of this situation and the central role that image registration and fusion play in treatment planning and delivery, the Therapy Physics Committee of the American Association of Physicists in Medicine commissioned Task Group 132 to review current approaches and solutions for image registration (both rigid and deformable) in radiotherapy and to provide recommendations for quality assurance and quality control of these clinical processes.

An adaptive MR-CT registration method for MRI-guided prostate cancer radiotherapy

Magnetic Resonance images (MRI) have superior soft tissue contrast compared with CT images. Therefore, MRI might be a better imaging modality to differentiate the prostate from surrounding normal organs. Methods to accurately register MRI to simulation CT images are essential, as we transition the use of MRI into the routine clinic setting. In this study, we present a finite element method (FEM) to improve the performance of a commercially available, B-spline-based registration algorithm in the prostate region. Specifically, prostate contours were delineated independently on ten MRI and CT images using the Eclipse treatment planning system. Each pair of MRI and CT images was registered with the B-spline-based algorithm implemented in the VelocityAI system. A bounding box that contains the prostate volume in the CT image was selected and partitioned into a tetrahedral mesh. An adaptive finite element method was then developed to adjust the displacement vector fields (DVFs) of the B-spline-based registrations within the box. The B-spline and FEM-based registrations were evaluated based on the variations of prostate volume and tumor centroid, the unbalanced energy of the generated DVFs, and the clarity of the reconstructed anatomical structures. The results showed that the volumes of the prostate contours warped with the B-spline-based DVFs changed 10.2% on average, relative to the volumes of the prostate contours on the original MR images. This discrepancy was reduced to 1.5% for the FEM-based DVFs. The average unbalanced energy was 2.65 and 0.38 mJ cm(-3), and the prostate centroid deviation was 0.37 and 0.28 cm, for the B-spline and FEM-based registrations, respectively. Different from the B-spline-warped MR images, the FEM-warped MR images have clear boundaries between prostates and bladders, and their internal prostatic structures are consistent with those of the original MR images. In summary, the developed adaptive FEM method preserves the prostate volume during the transformation between the MR and CT images and improves the accuracy of the B-spline registrations in the prostate region. The approach will be valuable for the development of high-quality MRI-guided radiation therapy.

Volume and landmark analysis: comparison of MRI measurements obtained with an endorectal coil and with a phased-array coil

AIM

To compare prostate volumes and distances between anatomical landmarks on MRI images obtained with a phased-array coil (PAC) only and with a PAC and an endorectal coil (ERC).

MATERIALS AND METHODS

Informed consent was waived for this Health Insurance Portability and Accountability Act-compliant study. Fifty-nine men underwent PAC-MRI and ERC-MRI at 1.5 (n = 3) or 3 T (n = 56). On MRI images, two radiologists independently measured prostate volume and distances between the anterior rectal wall (ARW) and symphysis pubis at the level of the verumontanum; ARW and symphysis pubis at the level of the mid-symphysis pubis; and bladder neck and mid-symphysis pubis. Differences between measurements from PAC-MRI and ERC-MRI were assessed with the Wilcoxon RANK SUM test. Inter-reader agreement was assessed using the concordance correlation coefficient (CCC).

RESULTS

Differences in prostate volume between PAC-MRI and ERC-MRI [median: -0.75 mm(3) (p = 0.10) and median: -0.84 mm(3) (p = 0.06) for readers 1 and 2, respectively] were not significant. For readers 1 and 2, median differences between distances were as follows: -10.20 and -12.75 mm, respectively, ARW to symphysis pubis at the level of the verumontanum; -6.60 and -6.08 mm, respectively, ARW to symphysis pubis at the level of the mid-symphysis pubis; -3 and -3 mm respectively, bladder neck to mid-symphysis pubis. All differences in distance were significant for both readers (p ≤ 0.0005). Distances were larger on PAC-MRI (p ≤ 0.0005). Inter-reader agreement regarding prostate volume was almost perfect on PAC-MRI (CCC: 0.99; 95% CI: 0.98-1.00) and ERC-MRI (CCC: 0.99; 95% CI: 0.99-1.00); inter-reader agreement for distance measurements varied (CCCs: 0.54-0.86).

CONCLUSION

Measurements of distances between anatomical landmarks differed significantly between ERC-MRI and PAC-MRI, although prostate volume measurements did not.

A Domain Constrained Deformable (DoCD) Model for Co-registration of Pre- and Post-Radiated Prostate MRI

External beam radiation treatment (EBRT) is a popular method for treating prostate cancer (CaP) involving destroying tumor cells with ionizing radiation. Following EBRT, biochemical failure has been linked with disease recurrence. However, there is a need for methods for evaluating early treatment related changes to allow for an early intervention in case of incomplete disease response. One method for looking at treatment evaluation is to detect changes in MRI markers on a voxel-by-voxel basis following treatment. Changes in MRI markers may be correlated with disease recurrence and complete or partial response. In order to facilitate voxel-by-voxel imaging related treatment changes, and also to evaluate morphologic changes in the gland post treatment, the pre- and post-radiated MRI must first be brought into spatial alignment via image registration. However, EBRT induces changes in the prostate volume and distortion to the internal anatomy of the prostate following radiation treatment. The internal substructures of the prostate, the central gland (CG) and peripheral zone (PZ), may respond to radiation differently, and their resulting shapes may change drastically. Biomechanical models of the prostate that have been previously proposed tend to focus on how external forces affect the surface of the prostate (not the internals), and assume that the prostate is a volume-preserving entity. In this work we present DoCD, a biomechanical model for automatically registering pre-, post-EBRT MRI with the aim of expressly modeling the (1) changes in volume, and (2) changes to the CG and PZ. DoCD was applied to a cohort of 30 patients and achieved a root mean square error of 2.994 mm, which was statistically significantly better a traditional biomechanical model which did not consider changes to the internal anatomy of the prostate (mean of 5.071 mm).

Whole prostate volume and shape changes with the use of an inflatable and flexible endorectal coil

Purpose. To determine to what extent an inflatable endorectal coil (ERC) affects whole prostate (WP) volume and shape during prostate MRI. Materials and Methods. 79 consecutive patients underwent T2W MRI at 3T first with a 6-channel surface coil and then with the combination of a 16-channel surface coil and ERC in the same imaging session. WP volume was assessed by manually contouring the prostate in each T2W axial slice. PSA density was also calculated. The maximum anterior-posterior (AP), left-right (LR), and craniocaudal (CC) prostate dimensions were measured. Changes in WP prostate volume, PSA density, and prostate dimensions were then evaluated. Results. In 79 patients, use of an ERC yielded no significant change in whole prostate volume (0.6 ± 5.7%, P = 0.270) and PSA density (−0.2 ± 5.6%, P = 0.768). However, use of an ERC significantly decreased the AP dimension of the prostate by −8.6 ± 7.8% (P < 0.001), increased LR dimension by 4.5 ± 5.8% (P < 0.001), and increased the CC dimension by 8.8 ± 6.9% (P < 0.001). Conclusion. Use of an ERC in prostate MRI results in the shape deformation of the prostate gland with no significant change in the volume of the prostate measured on T2W MRI. Therefore, WP volumes calculated on ERC MRI can be reliably used in clinical workflow.

Registration of in vivo prostate MRI and pseudo-whole mount histology using Local Affine Transformations guided by Internal Structures (LATIS)

PURPOSE

To present a novel registration approach called LATIS (Local Affine Transformation guided by Internal Structures) for coregistering post prostatectomy pseudo-whole mount (PWM) pathological sections with in vivo MRI (magnetic resonance imaging) images.

MATERIALS AND METHODS

Thirty-five patients with biopsy-proven prostate cancer were imaged at 3T with an endorectal coil. Excised prostate specimens underwent quarter mount step-section pathologic processing, digitization, annotation, and assembly into a PWM. Manually annotated macro-structures on both pathology and MRI were used to assist registration using a relaxed local affine transformation approximation. Registration accuracy was assessed by calculation of the Dice similarity coefficient (DSC) between transformed and target capsule masks and least-square distance between transformed and target landmark positions.

RESULTS

LATIS registration resulted in a DSC value of 0.991 ± 0.004 and registration accuracy of 1.54 ± 0.64 mm based on identified landmarks common to both datasets. Image registration performed without the use of internal structures led to an 87% increase in landmark-based registration error. Derived transformation matrices were used to map regions of pathologically defined disease to MRI.

CONCLUSION

LATIS was used to successfully coregister digital pathology with in vivo MRI to facilitate improved correlative studies between pathologically identified features of prostate cancer and multiparametric MRI.

MR-CT registration using a Ni-Ti prostate stent in image-guided radiotherapy of prostate cancer

PURPOSE

In image-guided radiotherapy of prostate cancer defining the clinical target volume often relies on magnetic resonance (MR). The task of transferring the clinical target volume from MR to standard planning computed tomography (CT) is not trivial due to prostate mobility. In this paper, an automatic local registration approach is proposed based on a newly developed removable Ni-Ti prostate stent.

METHODS

The registration uses the voxel similarity measure mutual information in a two-step approach where the pelvic bones are used to establish an initial registration for the local registration.

RESULTS

In a phantom study, the accuracy was measured to 0.97 mm and visual inspection showed accurate registration of all 30 data sets. The consistency of the registration was examined where translation and rotation displacements yield a rotation error of 0.41° ± 0.45° and a translation error of 1.67 ± 2.24 mm.

CONCLUSIONS

This study demonstrated the feasibility for an automatic local MR-CT registration using the prostate stent.

Contour propagation using feature-based deformable registration for lung cancer

Accurate target delineation of CT image is a critical step in radiotherapy treatment planning. This paper describes a novel strategy for automatic contour propagation, based on deformable registration, for CT images of lung cancer. The proposed strategy starts with a manual-delineated contour in one slice of a 3D CT image. By means of feature-based deformable registration, the initial contour in other slices of the image can be propagated automatically, and then refined by active contour approach. Three algorithms are employed in the strategy: the Speeded-Up Robust Features (SURF), Thin-Plate Spline (TPS), and an adapted active contour (Snake), used to refine and modify the initial contours. Five pulmonary cancer cases with about 400 slices and 1000 contours have been used to verify the proposed strategy. Experiments demonstrate that the proposed strategy can improve the segmentation performance in the pulmonary CT images. Jaccard similarity (JS) mean is about 0.88 and the maximum of Hausdorff distance (HD) is about 90%. In addition, delineation time has been considerably reduced. The proposed feature-based deformable registration method in the automatic contour propagation improves the delineation efficiency significantly.

Effect of endorectal balloon positioning errors on target deformation and dosimetric quality during prostate SBRT

An inflatable endorectal balloon (ERB) is often used during stereotactic body radiation therapy (SBRT) for treatment of prostate cancer in order to reduce both intrafraction motion of the target and risk of rectal toxicity. However, the ERB can exert significant force on the prostate, and this work assessed the impact of ERB position errors on deformation of the prostate and treatment dose metrics. Seventy-one cone-beam computed tomography (CBCT) image datasets of nine patients with clinical stage T1cN0M0 prostate cancer were studied. An ERB (Flexi-Cuff, EZ-EM, Westbury, NY) inflated with 60 cm(3) of air was used during simulation and treatment, and daily kilovoltage (kV) CBCT imaging was performed to localize the prostate. The shape of the ERB in each CBCT was analyzed to determine errors in position, size, and shape. A deformable registration algorithm was used to track the dose received by (and deformation of) the prostate, and dosimetric values such as D95, PTV coverage, and Dice coefficient for the prostate were calculated. The average balloon position error was 0.5 cm in the inferior direction, with errors ranging from 2 cm inferiorly to 1 cm superiorly. The prostate was deformed primarily in the AP direction, and tilted primarily in the anterior-posterior/superior-inferior plane. A significant correlation was seen between errors in depth of ERB insertion (DOI) and mean voxel-wise deformation, prostate tilt, Dice coefficient, and planning-to-treatment prostate inter-surface distance (p < 0.001). Dosimetrically, DOI is negatively correlated with prostate D95 and PTV coverage (p < 0.001). For the model of ERB studied, error in ERB position can cause deformations in the prostate that negatively affect treatment, and this additional aspect of setup error should be considered when ERBs are used for prostate SBRT. Before treatment, the ERB position should be verified, and the ERB should be adjusted if the error is observed to exceed tolerable values.

Deformable image registration of CT and truncated cone-beam CT for adaptive radiation therapy

Truncation of a cone-beam computed tomography (CBCT) image, mainly caused by the limited field of view (FOV) of CBCT imaging, poses challenges to the problem of deformable image registration (DIR) between computed tomography (CT) and CBCT images in adaptive radiation therapy (ART). The missing information outside the CBCT FOV usually causes incorrect deformations when a conventional DIR algorithm is utilized, which may introduce significant errors in subsequent operations such as dose calculation. In this paper, based on the observation that the missing information in the CBCT image domain does exist in the projection image domain, we propose to solve this problem by developing a hybrid deformation/reconstruction algorithm. As opposed to deforming the CT image to match the truncated CBCT image, the CT image is deformed such that its projections match all the corresponding projection images for the CBCT image. An iterative forward-backward projection algorithm is developed. Six head-and-neck cancer patient cases are used to evaluate our algorithm, five with simulated truncation and one with real truncation. It is found that our method can accurately register the CT image to the truncated CBCT image and is robust against image truncation when the portion of the truncated image is less than 40% of the total image.

A strategy for multimodal deformable image registration to integrate PET/MR into radiotherapy treatment planning

BACKGROUND

Combined positron emission tomography (PET)/magnetic resonance imaging (MRI) is highly promising for biologically individualized radiotherapy (RT). Hence, the purpose of this work was to develop an accurate and robust registration strategy to integrate combined PET/MR data into RT treatment planning. Material and methods. Eight patient datasets consisting of an FDG PET/computed tomography (CT) and a subsequently acquired PET/MR of the head and neck (HN) region were available. Registration strategies were developed based on CT and MR data only, whereas the PET components were fused with the resulting deformation field. Following a rigid registration, deformable registration was performed with a transform parametrized by B-splines. Three different optimization metrics were investigated: global mutual information (GMI), GMI combined with a bending energy penalty (BEP) for regularization (GMI+ BEP) and localized mutual information with BEP (LMI+ BEP). Different quantitative registration quality measures were developed, including volumetric overlap and mean distance measures for structures segmented on CT and MR as well as anatomical landmark distances. Moreover, the local registration quality in the tumor region was assessed by the normalized cross correlation (NCC) of the two PET datasets.

RESULTS

LMI+ BEP yielded the most robust and accurate registration results. For GMI, GMI+ BEP and LMI+ BEP, mean landmark distances (standard deviations) were 23.9 mm (15.5 mm), 4.8 mm (4.0 mm) and 3.0 mm (1.0 mm), and mean NCC values (standard deviations) were 0.29 (0.29), 0.84 (0.14) and 0.88 (0.06), respectively.

CONCLUSION

Accurate and robust multimodal deformable image registration of CT and MR in the HN region can be performed using a B-spline parametrized transform and LMI+ BEP as optimization metric. With this strategy, biologically individualized RT based on combined PET/MRI in terms of dose painting is possible.

Magnetic resonance spectroscopy imaging-directed transrectal ultrasound biopsy increases prostate cancer detection in men with prostate-specific antigen between 4-10 ng/mL and normal digital rectal examination

OBJECTIVES

To evaluate the ability of magnetic resonance spectroscopic imaging to improve prostate cancer detection rate.

METHODS

A retrospective analysis was carried out of 278 men with prostate-specific antigen in the range of 4-10 ng/mL and normal digital rectal examination who underwent transrectal ultrasound-guided prostate biopsy. Outcomes were compared between men who had a standard biopsy versus those who also underwent a prebiopsy magnetic resonance spectroscopic imaging. Men with an abnormal voxel on magnetic resonance spectroscopic imaging had standard transrectal ultrasound biopsies plus biopsies directed to the abnormal voxels.

RESULTS

The study group (n = 140) and control group (n = 138) were similar in baseline parameters, such as mean age, prostate size and mean prostate-specific antigen. The overall cancer detection in the magnetic resonance spectroscopic imaging positive group (24.4%) was more than double that of the control group (10.1%). On comparing the magnetic resonance spectroscopic imaging results with the transrectal ultrasound biopsy findings, magnetic resonance spectroscopic imaging had 95.6% sensitivity, 41.9% specificity, a positive predictive value of 24.4%, a negative predictive value of 98% and an accuracy of 51.4%.

CONCLUSIONS

Magnetic resonance spectroscopic imaging-directed transrectal ultrasound biopsy increases the cancer detection rate compared with standard transrectal ultrasound biopsy in patients with normal digital rectal examination and elevated prostate-specific antigen in the range of 4-10 ng/mL.

A statistical model-based technique for accounting for prostate gland deformation in endorectal coil-based MR imaging

In prostate brachytherapy procedures, combining high-resolution endorectal coil (ERC)-MRI with Computed Tomography (CT) images has shown to improve the diagnostic specificity for malignant tumors. Despite such advantage, there exists a major complication in fusion of the two imaging modalities due to the deformation of the prostate shape in ERC-MRI. Conventionally, nonlinear deformable registration techniques have been utilized to account for such deformation. In this work, we present a model-based technique for accounting for the deformation of the prostate gland in ERC-MR imaging, in which a unique deformation vector is estimated for every point within the prostate gland. Modes of deformation for every point in the prostate are statistically identified using a set of MR-based training set (with and without ERC-MRI). Deformation of the prostate from a deformed (ERC-MRI) to a non-deformed state in a different modality (CT) is then realized by first calculating partial deformation information for a limited number of points (such as surface points or anatomical landmarks) and then utilizing the calculated deformation from a subset of the points to determine the coefficient values for the modes of deformations provided by the statistical deformation model. Using a leave-one-out cross-validation, our results demonstrated a mean estimation error of 1mm for a MR-to-MR registration.

A framework for deformable image registration validation in radiotherapy clinical applications

Quantitative validation of deformable image registration (DIR) algorithms is extremely difficult because of the complexity involved in constructing a deformable phantom that can duplicate various clinical scenarios. The purpose of this study is to describe a framework to test the accuracy of DIR based on computational modeling and evaluating using inverse consistency and other methods. Three clinically relevant organ deformations were created in prostate (distended rectum and rectal gas), head and neck (large neck flexion), and lung (inhale and exhale lung volumes with variable contrast enhancement) study sets. DIR was performed using both B-spline and diffeomorphic demons algorithms in the forward and inverse direction. A compositive accumulation of forward and inverse deformation vector fields was done to quantify the inverse consistency error (ICE). The anatomical correspondence of tumor and organs at risk was quantified by comparing the original RT structures with those obtained after DIR. Further, the physical characteristics of the deformation field, namely the Jacobian and harmonic energy, were computed to quantify the preservation of image topology and regularity of spatial transformation obtained in DIR. The ICE was comparable in prostate case but the B-spline algorithm had significantly better anatomical correspondence for rectum and prostate than diffeomorphic demons algorithm. The ICE was 6.5 mm for demons algorithm for head and neck case when compared to 0.7 mm for B-spline. Since the induced neck flexion was large, the average Dice similarity coefficient between both algorithms was only 0.87, 0.52, 0.81, and 0.67 for tumor, cord, parotids, and mandible, respectively. The B-spline algorithm accurately estimated deformations between images with variable contrast in our lung study, while diffeomorphic demons algorithm led to gross errors on structures affected by contrast variation. The proposed framework offers the application of known deformations on any image datasets, to evaluate the overall accuracy and limitations of a DIR algorithm used in radiation oncology. The evaluation based on anatomical correspondence, physical characteristics of deformation field, and image characteristics can facilitate DIR verification with the ultimate goal of implementing adaptive radiotherapy. The suitability of application of a particular evaluation metric in validating DIR is dependent on the clinical deformation observed.

Deformable image registration with inclusion of autodetected homologous tissue features

A novel deformable registration algorithm is proposed in the application of radiation therapy. The algorithm starts with autodetection of a number of points with distinct tissue features. The feature points are then matched by using the scale invariance features transform (SIFT) method. The associated feature point pairs are served as landmarks for the subsequent thin plate spline (TPS) interpolation. Several registration experiments using both digital phantom and clinical data demonstrate the accuracy and efficiency of the method. For the 3D phantom case, markers with error less than 2 mm are over 85% of total test markers, and it takes only 2-3 minutes for 3D feature points association. The proposed method provides a clinically practical solution and should be valuable for various image-guided radiation therapy (IGRT) applications.

Three-dimensional elastic image registration based on strain energy minimization: application to prostate magnetic resonance imaging

The use of magnetic resonance (MR) imaging in conjunction with an endorectal coil is currently the clinical standard for the diagnosis of prostate cancer because of the increased sensitivity and specificity of this approach. However, imaging in this manner provides images and spectra of the prostate in the deformed state because of the insertion of the endorectal coil. Such deformation may lead to uncertainties in the localization of prostate cancer during therapy. We propose a novel 3-D elastic registration procedure that is based on the minimization of a physically motivated strain energy function that requires the identification of similar features (points, curves, or surfaces) in the source and target images. The Gauss-Seidel method was used in the numerical implementation of the registration algorithm. The registration procedure was validated on synthetic digital images, MR images from prostate phantom, and MR images obtained on patients. The registration error, assessed by averaging the displacement of a fiducial landmark in the target to its corresponding point in the registered image, was 0.2 ± 0.1 pixels on synthetic images. On the prostate phantom and patient data, the registration errors were 1.0 ± 0.6 pixels (0.6 ± 0.4 mm) and 1.8 ± 0.7 pixels (1.1 ± 0.4 mm), respectively. Registration also improved image similarity (normalized cross-correlation) from 0.72 ± 0.10 to 0.96 ± 0.03 on patient data. Registration results on digital images, phantom, and prostate data in vivo demonstrate that the registration procedure can be used to significantly improve both the accuracy of localized therapies such as brachytherapy or external beam therapy and can be valuable in the longitudinal follow-up of patients after therapy.

Interactive, multi-modality image registrations for combined MRI/MRSI-planned HDR prostate brachytherapy

Purpose

This study presents the steps and criteria involved in the series of image registrations used clinically during the planning and dose delivery of focal high dose-rate (HDR) brachytherapy of the prostate.

Material and methods

Three imaging modalities – Magnetic Resonance Imaging (MRI), Magnetic Resonance Spectroscopic Imaging (MRSI), and Computed Tomography (CT) – were used at different steps during the process. MRSI is used for identification of dominant intraprosatic lesions (DIL). A series of rigid and nonrigid transformations were applied to the data to correct for endorectal-coil-induced deformations and for alignment with the planning CT. Mutual information was calculated as a morphing metric. An inverse planning optimization algorithm was applied to boost dose to the DIL while providing protection to the urethra, penile bulb, rectum, and bladder. Six prostate cancer patients were treated using this protocol.

Results

The morphing algorithm successfully modeled the probe-induced prostatic distortion. Mutual information calculated between the morphed images and images acquired without the endorectal probe showed a significant (p = 0.0071) increase to that calculated between the unmorphed images and images acquired without the endorectal probe. Both mutual information and visual inspection serve as effective diagnostics of image morphing. The entire procedure adds less than thirty minutes to the treatment planning.

Conclusion

This work demonstrates the utility of image transformations and registrations to HDR brachytherapy of prostate cancer.

Image-based modeling of tumor shrinkage in head and neck radiation therapy

PURPOSE

Understanding the kinetics of tumor growth/shrinkage represents a critical step in quantitative assessment of therapeutics and realization of adaptive radiation therapy. This article presents a novel framework for image-based modeling of tumor change and demonstrates its performance with synthetic images and clinical cases.

METHODS

Due to significant tumor tissue content changes, similarity-based models are not suitable for describing the process of tumor volume changes. Under the hypothesis that tissue features in a tumor volume or at the boundary region are partially preserved, the kinetic change was modeled in two steps: (1) Autodetection of homologous tissue features shared by two input images using the scale invariance feature transformation (SIFT) method; and (2) establishment of a voxel-to-voxel correspondence between the images for the remaining spatial points by interpolation. The correctness of the tissue feature correspondence was assured by a bidirectional association procedure, where SIFT features were mapped from template to target images and reversely. A series of digital phantom experiments and five head and neck clinical cases were used to assess the performance of the proposed technique.

RESULTS

The proposed technique can faithfully identify the known changes introduced when constructing the digital phantoms. The subsequent feature-guided thin plate spline calculation reproduced the "ground truth" with accuracy better than 1.5 mm. For the clinical cases, the new algorithm worked reliably for a volume change as large as 30%.

CONCLUSIONS

An image-based tumor kinetic algorithm was developed to model the tumor response to radiation therapy. The technique provides a practical framework for future application in adaptive radiation therapy.

Assessment of a commercially available automatic deformable registration system

In recent years, a number of approaches have been applied to the problem of deformable registration validation. However, the challenge of assessing a commercial deformable registration system - in particular, an automatic registration system in which the deformable transformation is not readily accessible - has not been addressed. Using a collection of novel and established methods, we have developed a comprehensive, four-component protocol for the validation of automatic deformable image registration systems over a range of IGRT applications. The protocol, which was applied to the Reveal-MVS system, initially consists of a phantom study for determination of the system's general tendencies, while relative comparison of different registration settings is achieved through postregistration similarity measure evaluation. Synthetic transformations and contour-based metrics are used for absolute verification of the system's intra-modality and inter-modality capabilities, respectively. Results suggest that the commercial system is more apt to account for global deformations than local variations when performing deform-able image registration. Although the protocol was used to assess the capabilities of the Reveal-MVS system, it can readily be applied to other commercial systems. The protocol is by no means static or definitive, and can be further expanded to investigate other potential deformable registration applications.

Tissue feature-based and segmented deformable image registration for improved modeling of shear movement of lungs

PURPOSE

To report a tissue feature-based image registration strategy with explicit inclusion of the differential motions of thoracic structures.

METHODS AND MATERIALS

The proposed technique started with auto-identification of a number of corresponding points with distinct tissue features. The tissue feature points were found by using the scale-invariant feature transform method. The control point pairs were then sorted into different "colors" according to the organs in which they resided and used to model the involved organs individually. A thin-plate spline method was used to register a structure characterized by the control points with a given "color." The proposed technique was applied to study a digital phantom case and 3 lung and 3 liver cancer patients.

RESULTS

For the phantom case, a comparison with the conventional thin-plate spline method showed that the registration accuracy was markedly improved when the differential motions of the lung and chest wall were taken into account. On average, the registration error and standard deviation of the 15 points against the known ground truth were reduced from 3.0 to 0.5 mm and from 1.5 to 0.2 mm, respectively, when the new method was used. A similar level of improvement was achieved for the clinical cases.

CONCLUSION

The results of our study have shown that the segmented deformable approach provides a natural and logical solution to model the discontinuous organ motions and greatly improves the accuracy and robustness of deformable registration.

Interactive deformation registration of endorectal prostate MRI using ITK thin plate splines

RATIONALE AND OBJECTIVES

Magnetic resonance imaging with an endorectal coil allows high-resolution imaging of prostate cancer and the surrounding normal organs. These anatomic details can be used to direct radiotherapy. However, organ deformation introduced by the endorectal coil makes it difficult to register magnetic resonance images for treatment planning. In this study, plug-ins for the volume visualization software VolView were implemented on the basis of algorithms from the National Library of Medicine's Insight Segmentation and Registration Toolkit (ITK).

MATERIALS AND METHODS

Magnetic resonance images of a phantom simulating human pelvic structures were obtained with and without the endorectal coil balloon inflated. The prostate not deformed by the endorectal balloon was registered to the deformed prostate using an ITK thin plate spline (TPS). This plug-in allows the use of crop planes to limit the deformable registration in the region of interest around the prostate. These crop planes restricted the support of the TPS to the area around the prostate, where most of the deformation occurred. The region outside the crop planes was anchored by grid points.

RESULTS

The TPS was more accurate in registering the local deformation of the prostate compared with a TPS variant, the elastic body spline. The TPS was also applied to register an in vivo T(2)-weighted endorectal magnetic resonance image. The intraprostatic tumor was accurately registered. This could potentially guide the boosting of intraprostatic targets. The source and target landmarks were placed graphically. This TPS plug-in allows the registration to be undone. The landmarks could be added, removed, and adjusted in real time and in three dimensions between repeated registrations.

CONCLUSION

This interactive TPS plug-in allows a user to obtain a high level of accuracy satisfactory to a specific application efficiently. Because it is open-source software, the imaging community will be able to validate and improve the algorithm.

Objective assessment of deformable image registration in radiotherapy: a multi-institution study

The looming potential of deformable alignment tools to play an integral role in adaptive radiotherapy suggests a need for objective assessment of these complex algorithms. Previous studies in this area are based on the ability of alignment to reproduce analytically generated deformations applied to sample image data, or use of contours or bifurcations as ground truth for evaluation of alignment accuracy. In this study, a deformable phantom was embedded with 48 small plastic markers, placed in regions varying from high contrast to roughly uniform regional intensity, and small to large regional discontinuities in movement. CT volumes of this phantom were acquired at different deformation states. After manual localization of marker coordinates, images were edited to remove the markers. The resulting image volumes were sent to five collaborating institutions, each of which has developed previously published deformable alignment tools routinely in use. Alignments were done, and applied to the list of reference coordinates at the inhale state. The transformed coordinates were compared to the actual marker locations at exhale. A total of eight alignment techniques were tested from the six institutions. All algorithms performed generally well, as compared to previous publications. Average errors in predicted location ranged from 1.5 to 3.9 mm, depending on technique. No algorithm was uniformly accurate across all regions of the phantom, with maximum errors ranging from 5.1 to 15.4 mm. Larger errors were seen in regions near significant shape changes, as well as areas with uniform contrast but large local motion discontinuity. Although reasonable accuracy was achieved overall, the variation of error in different regions suggests caution in globally accepting the results from deformable alignment.

Feature-based rectal contour propagation from planning CT to cone beam CT

The purpose of this work is to develop a novel feature-based registration strategy to automatically map the rectal contours from planning computed tomography (CT) (pCT) to cone beam CT (CBCT). The rectal contours were manually outlined on the pCT. A narrow band with the outlined contour as its interior surface was then constructed, so that we can exclude the volume inside the rectum in the registration process. The corresponding contour in the CBCT was found by using a feature-based registration algorithm, which consists of two steps: (1) automatically searching for control points in the pCT and CBCT based on the features of the surrounding tissue and matching the homologous control points using the scale invariance feature transformation; and (2) using the control points for a thin plate spline transformation to warp the narrow band and mapping the corresponding contours from pCT to CBCT. The proposed contour propagation technique is applied to digital phantoms and clinical cases and, in all cases, the contour mapping results are found to be clinically acceptable. For clinical cases, the method yielded satisfactory results even when there were significant rectal content changes between the pCT and CBCT scans. As a consequence, the accordance between the rectal volumes after deformable registration and the manually segmented rectum was found to be more than 90%. The proposed technique provides a powerful tool for adaptive radiotherapy of prostate, rectal, and gynecological cancers in the future.

Changes in prostate shape and volume and their implications for radiotherapy after introduction of endorectal balloon as determined by MRI at 3T

PURPOSE

To determine the changes in prostate shape and volume after the introduction of an endorectal coil (ERC) by means of magnetic resonance imaging (MRI) at 3T.

METHODS AND MATERIALS

A total of 44 consecutive patients with biopsy-proven prostate cancer underwent separate MRI examinations at 3T with a body array coil and subsequently with an ERC inflated with 50 mL of fluid. Prospectively, two experienced readers independently evaluated all data sets in random order. The maximal anteroposterior, right-to-left, and craniocaudal prostate diameters, as well as the total prostate and peripheral zone and central gland volumes were measured before and after ERC introduction. The changes in prostate shape and volume were analyzed using Wilcoxon's test for paired samples.

RESULTS

The introduction of the ERC significantly changed the prostate shape in all three directions, with mean changes in the anteroposterior, right-to-left, and craniocaudal diameters of 15.7% (5.5 mm), 7.7% (3.5 mm), and 6.3% (2.2 mm), respectively. The mean total prostate, peripheral zone, and central gland volume decreased significantly after ERC introduction by 17.9% (8.3 cm(3)), 21.6% (4.8 cm(3)), and 14.2% (3.4 cm(3)), respectively.

CONCLUSION

ERC introduction as observed by 3T MRI changed the prostate shape and volume significantly. The mean anteroposterior diameter was reduced by nearly one-sixth of its original diameter, and the mean total prostate volume was decreased by approximately 18%. This could cause difficulties and should be considered when using ERC-based MRI for MRI-computed tomography fusion and radiotherapy planning.

A registration based approach for 4D cardiac micro-CT using combined prospective and retrospective gating

Recent advances in murine cardiac studies with three-dimensional cone beam micro-computed tomography (CT) have used either prospective or retrospective gating technique. While prospective gating ensures the best image quality and the highest resolution, it involves longer sampling times and higher radiation dose. Sampling is faster and the radiation dose can be reduced with retrospective gating but the image quality is affected by the limited number of projections with an irregular angular distribution which complicate the reconstruction process, causing significant streaking artifacts. This work involves both prospective and retrospective gating in sampling. Deformable registration is used between a high quality image set acquired with prospective gating with the multiple data sets during the cardiac cycle obtained using retrospective gating. Tests were conducted on a four-dimensional (4D) cardiac mouse phantom and after optimization, the method was applied to in vivo cardiac micro-CT data. Results indicate that, by using our method, the sampling time can be reduced by a factor of 2.5 and the radiation dose can be reduced 35% compared to the prospective sampling while the image quality can be maintained. In conclusion, we proposed a novel solution to 4D cine cardiac micro-CT based on a combined prospective with retrospective gating in sampling and deformable registration post reconstruction that mixed the advantages of both strategies.

A comparison framework for breathing motion estimation methods from 4-D imaging

Motion estimation is an important issue in radiation therapy of moving organs. In particular, motion estimates from 4-D imaging can be used to compute the distribution of an absorbed dose during the therapeutic irradiation. We propose a strategy and criteria incorporating spatiotemporal information to evaluate the accuracy of model-based methods capturing breathing motion from 4-D CT images. This evaluation relies on the identification and tracking of landmarks on the 4-D CT images by medical experts. Three different experts selected more than 500 landmarks within 4-D CT images of lungs for three patients. Landmark tracking was performed at four instants of the expiration phase. Two metrics are proposed to evaluate the tracking performance of motion-estimation models. The first metric cumulates over the four instants the errors on landmark location. The second metric integrates the error over a time interval according to an a priori breathing model for the landmark spatiotemporal trajectory. This latter metric better takes into account the dynamics of the motion. A second aim of this paper is to estimate the impact of considering several phases of the respiratory cycle as compared to using only the extreme phases (end-inspiration and end-expiration). The accuracy of three motion estimation models (two image registration-based methods and a biomechanical method) is compared through the proposed metrics and statistical tools. This paper points out the interest of taking into account more frames for reliably tracking the respiratory motion.

Computational Challenges for Image-Guided Radiation Therapy: Framework and Current Research

It is arguable that the imaging and delivery hardware necessary for delivering real-time adaptive image-guided radiotherapy is available on high-end linear accelerators. Robust and computationally efficient software is the limiting factor in achieving highly accurate and precise radiotherapy to the constantly changing anatomy of a cancer patient. The limitations are not caused by the availability of algorithms but rather issues of reliability, integration, and calculation time. However, each of the software components is an active area of research and development at academic and commercial centers. This article describes the software solutions in 4 broad areas: deformable image registration, adaptive replanning, real-time image guidance, and dose calculation and accumulation. Given the pace of technological advancement, the integration of these software solutions to develop real-time adaptive image-guided radiotherapy and the associated challenges they bring will be implemented to varying degrees by all major manufacturers over the coming years.

Current role and future perspectives of magnetic resonance spectroscopy in radiation oncology for prostate cancer

Prostatic neoplasms are not uniformly distributed within the prostate volume. With recent developments in three-dimensional intensity-modulated and image-guided radiation therapy, it is possible to treat different volumes within the prostate to different thresholds of doses. This approach has the potential to adapt the dose to the biologic aggressiveness of various clusters of tumor cells within the gland. The definition of tumor burden volume in prostate cancer can be facilitated by the use of magnetic resonance spectroscopy (MRS). The increasing sensitivity and specificity of MRS to the prostate is causing new interest in its potential role in the definition of target subvolumes at higher risk of failure following radical radiotherapy. Prostate MRS might also play a role as a noninvasive predictive factor for tumor response and treatment outcome. We review the use of MRS in radiation therapy for prostate cancer by evaluating its accuracy in the classification of aggressive cancer regions and target definition; its current role in the radiotherapy planning process, with special interest in technical issues behind the successful inclusion of MRS in clinical use; and available early experiences as a prognostic tool.

Development of Multiorgan Finite Element-Based Prostate Deformation Model Enabling Registration of Endorectal Coil Magnetic Resonance Imaging for Radiotherapy Planning

PURPOSE

Endorectal coil (ERC) magnetic resonance imaging (MRI) provides superior visualization of the prostate compared with computed tomography at the expense of deformation. This study aimed to develop a multiorgan finite element deformable method, Morfeus, to accurately co-register these images for radiotherapy planning.

METHODS

Patients with prostate cancer underwent fiducial marker implantation and computed tomography simulation for radiotherapy planning. A series of axial MRI scans were acquired with and without an ERC. The prostate, bladder, rectum, and pubic bones were manually segmented and assigned linear elastic material properties. Morfeus mapped the surface of the bladder and rectum between two imaged states, calculating the deformation of the prostate through biomechanical properties. The accuracy of deformation was measured as fiducial marker error and residual surface deformation between the inferred and actual prostate. The deformation map was inverted to deform from 100 cm(3) to no coil.

RESULTS

The data from 19 patients were analyzed. Significant prostate deformation occurred with the ERC (mean intrapatient range, 0.88 +/- 0.25 cm). The mean vector error in fiducial marker position (n = 57) was 0.22 +/- 0.09 cm, and the mean vector residual surface deformation (n = 19) was 0.15 +/- 0.06 cm for deformation from no coil to 100-cm(3) ERC, with an image vector resolution of 0.22 cm. Accurately deformed MRI scans improved soft-tissue resolution of the anatomy for radiotherapy planning.

CONCLUSIONS

This method of multiorgan deformable registration enabled accurate co-registration of ERC-MRI scans with computed tomography treatment planning images. Superior structural detail was visible on ERC-MRI, which has potential for improving target delineation.

Transrectal ultrasound-guided biopsy of prostate voxels identified as suspicious of malignancy on three-dimensional (1)H MR spectroscopic imaging in patients with abnormal digital rectal examination or raised prostate specific antigen level of 4-10 ng/ml

Results of the evaluation of transrectal ultrasound (TRUS) guided needle biopsy of voxels identified as suspicious of malignancy on magnetic resonance spectroscopic imaging (MRSI) in a large cohort of men (n = 83) with abnormal digital rectal examination (DRE) [prostate specific antigen (PSA) 0-4 ng/ml] or PSA less than 10 ng/ml, are reported. Three-dimensional (1)H MRSI was carried out at 1.5 T using a pelvic-phased array coil in combination with an endorectal surface coil. Voxels were classified as suspicious of malignancy based on Cit/(Cho + Cr) metabolite ratio. TRUS-guided biopsy of suspicious voxels was performed using the z- and x-coordinates obtained from MR images and two to three cores were taken from the suspected site. A systematic sextant biopsy was also carried out. MRSI showed voxels suspicious of malignancy in 44 patients while biopsy revealed cancer in 11 patients (25%). Patients who were negative for malignancy on MRSI were also negative on biopsy. An overall sensitivity of 100%, specificity of 54%, negative predictive value of 100% and accuracy of 60% were obtained. The site of biopsy was confirmed (n = 20) as a hypo-intense area on repeat MRI while repeat MRSI revealed high choline and low citrate. The overall success rate of MRI-directed TRUS-guided biopsy of 25% was higher compared with a 9% success rate achieved without MR guidance in another group of 120 patients. Our results indicate that TRUS-guided biopsy of suspicious area identified as malignant from MRSI can be performed using the coordinates of the voxel derived from MR images. This increases the detection rate of prostate cancer in men with PSA level <10 ng/ml or abnormal DRE and also demonstrates the potential of MR in routine clinical practice.

Overview of image-guided radiation therapy

Radiation therapy has gone through a series of revolutions in the last few decades and it is now possible to produce highly conformal radiation dose distribution by using techniques such as intensity-modulated radiation therapy (IMRT). The improved dose conformity and steep dose gradients have necessitated enhanced patient localization and beam targeting techniques for radiotherapy treatments. Components affecting the reproducibility of target position during and between subsequent fractions of radiation therapy include the displacement of internal organs between fractions and internal organ motion within a fraction. Image-guided radiation therapy (IGRT) uses advanced imaging technology to better define the tumor target and is the key to reducing and ultimately eliminating the uncertainties. The purpose of this article is to summarize recent advancements in IGRT and discussed various practical issues related to the implementation of the new imaging techniques available to radiation oncology community. We introduce various new IGRT concepts and approaches, and hope to provide the reader with a comprehensive understanding of the emerging clinical IGRT technologies. Some important research topics will also be addressed.

Deformable and rigid registration of MRI and microPET images for photodynamic therapy of cancer in mice

We are investigating imaging techniques to study the tumor response to photodynamic therapy (PDT). Positron emission tomography (PET) can provide physiological and functional information. High-resolution magnetic resonance imaging (MRI) can provide anatomical and morphological changes. Image registration can combine MRI and PET images for improved tumor monitoring. In this study, we acquired high-resolution MRI and microPET 18F-fluorodeoxyglucose (FDG) images from C3H mice with RIF-1 tumors that were treated with Pc 4-based PDT. We developed two registration methods for this application. For registration of the whole mouse body, we used an automatic three-dimensional, normalized mutual information algorithm. For tumor registration, we developed a finite element model (FEM)-based deformable registration scheme. To assess the quality of whole body registration, we performed slice-by-slice review of both image volumes; manually segmented feature organs, such as the left and right kidneys and the bladder, in each slice; and computed the distance between corresponding centroids. Over 40 volume registration experiments were performed with MRI and microPET images. The distance between corresponding centroids of organs was 1.5 +/- 0.4 mm which is about 2 pixels of microPET images. The mean volume overlap ratios for tumors were 94.7% and 86.3% for the deformable and rigid registration methods, respectively. Registration of high-resolution MRI and microPET images combines anatomical and functional information of the tumors and provides a useful tool for evaluating photodynamic therapy.

Model-based image reconstruction for four-dimensional PET

Positron emission tonography (PET) is useful in diagnosis and radiation treatment planning for a variety of cancers. For patients with cancers in thoracic or upper abdominal region, the respiratory motion produces large distortions in the tumor shape and size, affecting the accuracy in both diagnosis and treatment. Four-dimensional (4D) (gated) PET aims to reduce the motion artifacts and to provide accurate measurement of the tumor volume and the tracer concentration. A major issue in 4D PET is the lack of statistics. Since the collected photons are divided into several frames in the 4D PET scan, the quality of each reconstructed frame degrades as the number of frames increases. The increased noise in each frame heavily degrades the quantitative accuracy of the PET imaging. In this work, we propose a method to enhance the performance of 4D PET by developing a new technique of 4D PET reconstruction with incorporation of an organ motion model derived from 4D-CT images. The method is based on the well-known maximum-likelihood expectation-maximization (ML-EM) algorithm. During the processes of forward- and backward-projection in the ML-EM iterations, all projection data acquired at different phases are combined together to update the emission map with the aid of deformable model, the statistics is therefore greatly improved. The proposed algorithm was first evaluated with computer simulations using a mathematical dynamic phantom. Experiment with a moving physical phantom was then carried out to demonstrate the accuracy of the proposed method and the increase of signal-to-noise ratio over three-dimensional PET. Finally, the 4D PET reconstruction was applied to a patient case.

Reducing respiratory motion artifacts in positron emission tomography through retrospective stacking

Respiratory motion artifacts in positron emission tomography (PET) imaging can alter lesion intensity profiles, and result in substantially reduced activity and contrast-to-noise ratios (CNRs). We propose a corrective algorithm, coined "retrospective stacking" (RS), to restore image quality without requiring additional scan time. Retrospective stacking uses b-spline deformable image registration to combine amplitude-binned PET data along the entire respiratory cycle into a single respiratory end point. We applied the method to a phantom model consisting of a small, hot vial oscillating within a warm background, as well as to 18FDG-PET images of a pancreatic and a liver patient. Comparisons were made using cross-section visualizations, activity profiles, and CNRs within the region of interest. Retrospective stacking was found to properly restore the lesion location and intensity profile in all cases. In addition, RS provided CNR improvements up to three-fold over gated images, and up to five-fold over ungated data. These phantom and patient studies demonstrate that RS can correct for lesion motion and deformation, while substantially improving tumor visibility and background noise.

Image registration with auto-mapped control volumes

Many image registration algorithms rely on the use of homologous control points on the two input image sets to be registered. In reality, the interactive identification of the control points on both images is tedious, difficult, and often a source of error. We propose a two-step algorithm to automatically identify homologous regions that are used as a priori information during the image registration procedure. First, a number of small control volumes having distinct anatomical features are identified on the model image in a somewhat arbitrary fashion. Instead of attempting to find their correspondences in the reference image through user interaction, in the proposed method, each of the control regions is mapped to the corresponding part of the reference image by using an automated image registration algorithm. A normalized cross-correlation (NCC) function or mutual information was used as the auto-mapping metric and a limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm (L-BFGS) was employed to optimize the function to find the optimal mapping. For rigid registration, the transformation parameters of the system are obtained by averaging that derived from the individual control volumes. In our deformable calculation, the mapped control volumes are treated as the nodes or control points with known positions on the two images. If the number of control volumes is not enough to cover the whole image to be registered, additional nodes are placed on the model image and then located on the reference image in a manner similar to the conventional BSpline deformable calculation. For deformable registration, the established correspondence by the auto-mapped control volumes provides valuable guidance for the registration calculation and greatly reduces the dimensionality of the problem. The performance of the two-step registrations was applied to three rigid registration cases (two PET-CT registrations and a brain MRI-CT registration) and one deformable registration of inhale and exhale phases of a lung 4D CT. Algorithm convergence was confirmed by starting the registration calculations from a large number of initial transformation parameters. An accuracy of approximately 2 mm was achieved for both deformable and rigid registration. The proposed image registration method greatly reduces the complexity involved in the determination of homologous control points and allows us to minimize the subjectivity and uncertainty associated with the current manual interactive approach. Patient studies have indicated that the two-step registration technique is fast, reliable, and provides a valuable tool to facilitate both rigid and nonrigid image registrations.

Deformable structure registration of bladder through surface mapping

Cumulative dose distributions in fractionated radiation therapy depict the dose to normal tissues and therefore may permit an estimation of the risk of normal tissue complications. However, calculation of these distributions is highly challenging because of interfractional changes in the geometry of patient anatomy. This work presents an algorithm for deformable structure registration of the bladder and the verification of the accuracy of the algorithm using phantom and patient data. In this algorithm, the registration process involves conformal mapping of genus zero surfaces using finite element analysis, and guided by three control landmarks. The registration produces a correspondence between fractions of the triangular meshes used to describe the bladder surface. For validation of the algorithm, two types of balloons were inflated gradually to three times their original size, and several computerized tomography (CT) scans were taken during the process. The registration algorithm yielded a local accuracy of 4 mm along the balloon surface. The algorithm was then applied to CT data of patients receiving fractionated high-dose-rate brachytherapy to the vaginal cuff, with the vaginal cylinder in situ. The patients' bladder filling status was intentionally different for each fraction. The three required control landmark points were identified for the bladder based on anatomy. Out of an Institutional Review Board (IRB) approved study of 20 patients, 3 had radiographically identifiable points near the bladder surface that were used for verification of the accuracy of the registration. The verification point as seen in each fraction was compared with its predicted location based on affine as well as deformable registration. Despite the variation in bladder shape and volume, the deformable registration was accurate to 5 mm, consistently outperforming the affine registration. We conclude that the structure registration algorithm presented works with reasonable accuracy and provides a means of calculating cumulative dose distributions.

Image interpolation in 4D CT using a BSpline deformable registration model

PURPOSE

To develop a method for deriving the phase-binned four-dimensional computed tomography (4D CT) image sets through interpolation of the images acquired at some known phases.

METHODS AND MATERIALS

Four-dimensional computed tomography data sets for 3 patients were acquired. For each patient, the correlation between inhale and exhale phases was studied and quantified using a BSpline deformable model. Images at an arbitrary phase were deduced by an interpolation of the deformation coefficients. The accuracy of the proposed scheme was assessed by comparing marker trajectories and by checkerboard/difference display of the interpolated and acquired images.

RESULTS

The images at intermediate phases could be derived by an interpolation of the deformation field. An analysis of marker movements indicated that 3 mm accuracy is achievable by the interpolation. The subtraction of image analysis indicated a similar level of success. The proposed technique was useful also for automatically mapping the organ contours in a known phase to other phases, and for designing patient-specific margins in the presence of respiratory motion. Finally, the technique led to a 90% reduction in the acquired data, because in the BSpline model, a lattice of only a few thousand values is sufficient to describe a CT data set of 25 million pixels.

CONCLUSIONS

Organ deformation can be well modeled by using a BSpline model. The proposed technique may offer useful means for radiation dose reduction, binning artifacts removal, and disk storage improvement in 4D imaging.

Deformable registration for image-guided radiation therapy

Ths paper examines several applications of deformable registration algorithms in the field of image-guided radiotherapy. The first part focuses on the description of input and output of deformable registration algorithms, with a brief review of conventional and most current methods. The typical applications of deformable registration are then reviewed on the basis of four practical examples. The first two sets of examples deal with the fusion of images obtained from the same patient (inter-fraction registration), with time intervals of several days between each image. The other two examples deal with the fusion of images obtained in immediate sequence (intra-fraction registration); in this case, the focus is the displacement during image acquisition or patient treatment (mainly due to respiratory movement), with time intervals in the order of magnitude of tenths of seconds. Finally, the registration of images of different patients (inter-patient registration) is also discussed. In conclusion, deformable registration has become a fundamental tool for image analysis in radiotherapy. Although extensive validation of the numerous existing methods is required before extending its clinical use, deformable registration is expected to become a standard methodology in the treatment planning systems in the near future.