Comparison of manual vs. automated multimodality (CT-MRI) image registration for brain tumors

Boundary-based registration improves sensitivity for detecting hypoperfusion in sporadic frontotemporal lobar degeneration

Introduction

Frontotemporal lobar degeneration (FTLD) is associated with FTLD due to tau (FTLD-tau) or TDP (FTLD-TDP) inclusions found at autopsy. Arterial Spin Labeling (ASL) MRI is often acquired in the same session as a structural T1-weighted image (T1w), enabling detection of regional changes in cerebral blood flow (CBF). We hypothesize that ASL-T1w registration with more degrees of freedom using boundary-based registration (BBR) will better align ASL and T1w images and show increased sensitivity to regional hypoperfusion differences compared to manual registration in patient participants. We hypothesize that hypoperfusion will be associated with a clinical measure of disease severity, the FTLD-modified clinical dementia rating scale sum-of-boxes (FTLD-CDR).

Materials and methods

Patients with sporadic likely FTLD-tau (sFTLD-tau; N = 21), with sporadic likely FTLD-TDP (sFTLD-TDP; N = 14), and controls (N = 50) were recruited from the Connectomic Imaging in Familial and Sporadic Frontotemporal Degeneration project (FTDHCP). Pearson's Correlation Coefficients (CC) were calculated on cortical vertex-wise CBF between each participant for each of 3 registration methods: (1) manual registration, (2) BBR initialized with manual registration (manual+BBR), (3) and BBR initialized using FLIRT (FLIRT+BBR). Mean CBF was calculated in the same regions of interest (ROIs) for each registration method after image alignment. Paired t-tests of CC values for each registration method were performed to compare alignment. Mean CBF in each ROI was compared between groups using t-tests. Differences were considered significant at p < 0.05 (Bonferroni-corrected). We performed linear regression to relate FTLD-CDR to mean CBF in patients with sFTLD-tau and sFTLD-TDP, separately (p < 0.05, uncorrected).

Results

All registration methods demonstrated significant hypoperfusion in frontal and temporal regions in each patient group relative to controls. All registration methods detected hypoperfusion in the left insular cortex, middle temporal gyrus, and temporal pole in sFTLD-TDP relative to sFTLD-tau. FTLD-CDR had an inverse association with CBF in right temporal and orbitofrontal ROIs in sFTLD-TDP. Manual+BBR performed similarly to FLIRT+BBR.

Discussion

ASL is sensitive to distinct regions of hypoperfusion in patient participants relative to controls, and in patients with sFTLD-TDP relative to sFTLD-tau, and decreasing perfusion is associated with increasing disease severity, at least in sFTLD-TDP. BBR can register ASL-T1w images adequately for controls and patients.

Content-Based Estimation of Brain MRI Tilt in Three Orthogonal Directions

In a general scenario, the brain images acquired from magnetic resonance imaging (MRI) may experience tilt, distorting brain MR images. The tilt experienced by the brain MR images may result in misalignment during image registration for medical applications. Manually correcting (or estimating) the tilt on a large scale is time-consuming, expensive, and needs brain anatomy expertise. Thus, there is a need for an automatic way of performing tilt correction in three orthogonal directions (X, Y, Z). The proposed work aims to correct the tilt automatically by measuring the pitch angle, yaw angle, and roll angle in X-axis, Z-axis, and Y-axis, respectively. For correction of the tilt around the Z-axis (pointing to the superior direction), image processing techniques, principal component analysis, and similarity measures are used. Also, for correction of the tilt around the X-axis (pointing to the right direction), morphological operations, and tilt correction around the Y-axis (pointing to the anterior direction), orthogonal regression is used. The proposed approach was applied to adjust the tilt observed in the T1- and T2-weighted MR images. The simulation study with the proposed algorithm yielded an error of 0.40 ± 0.09°, and it outperformed the other existing studies. The tilt angle (in degrees) obtained is ranged from 6.2 ± 3.94, 2.35 ± 2.61, and 5 ± 4.36 in X-, Z-, and Y-directions, respectively, by using the proposed algorithm. The proposed work corrects the tilt more accurately and robustly when compared with existing studies.

Variability in atlas registration of optical intrinsic signal imaging and its effect on functional connectivity analysis

To compare neuroimaging data between subjects, images from individual sessions need to be aligned to a common reference or "atlas." Atlas registration of optical intrinsic signal imaging of mice, for example, is commonly performed using affine transforms with parameters determined by manual selection of canonical skull landmarks. Errors introduced by such procedures have not previously been investigated. We quantify the variability that arises from this process and consequent errors from misalignment that affect interpretation of functional neuroimaging data. We propose an improved method, using separately acquired high-resolution images and demonstrate improvements in variability and alignment using this method.

Comparison of different registration methods and landmarks for image-guided radiation therapy of pulmonary tumors

BACKGROUND

To compare the accuracy, advantages and disadvantages of automatic registration methods at different anatomical-sites for thoracic image-guided radiation therapy (IGRT).

METHODS

The Varian-IX IGRT system was used to perform a manual registration of the images collected on the first fraction of 60 patients with lung cancer (42 cases central location and 18 cases of peripheral). The registered images were used as reference images. Offline registration was performed for computed tomography-CBCT images using four methods: whole image registration, ipsilateral registration, soft tissue tumor registration, and vertebral body registration. Time taken to complete and deviation value were analyzed between the different methods.

RESULTS

There were significant differences in absolute deviation value of all the three directions (P < 0.001) and the time consumption (P < 0.001) between 4 methods. The Z direction had significant differences in deviation value of 4 methods (0.023 ± 0.128 mm, - 0.030 ± 0.175 mm, - 0.010 ± 0.238 mm, - 0.075 ± 0.137 mm, P = 0.011). The difference was significant in the X direction of the ipsilateral registration method between central and peripheral lung cancer (0.033 ± 0.053 mm vs. 0.067 ± 0.067 mm, P = 0.045).

CONCLUSIONS

The whole lung or affected side registration methods could be recommended to be used in the automatic registration function of the Varian-IX's On-Board Imaging (OBI) system.

Optimized 3D co-registration of ultra-low-field and high-field magnetic resonance images

The prototypes of ultra-low-field (ULF) MRI scanners developed in recent years represent new, innovative, cost-effective and safer systems, which are suitable to be integrated in multi-modal (Magnetoencephalography and MRI) devices. Integrated ULF-MRI and MEG scanners could represent an ideal solution to obtain functional (MEG) and anatomical (ULF MRI) information in the same environment, without errors that may limit source reconstruction accuracy. However, the low resolution and signal-to-noise ratio (SNR) of ULF images, as well as their limited coverage, do not generally allow for the construction of an accurate individual volume conductor model suitable for MEG localization. Thus, for practical usage, a high-field (HF) MRI image is also acquired, and the HF-MRI images are co-registered to the ULF-MRI ones. We address here this issue through an optimized pipeline (SWIM—Sliding WIndow grouping supporting Mutual information). The co-registration is performed by an affine transformation, the parameters of which are estimated using Normalized Mutual Information as the cost function, and Adaptive Simulated Annealing as the minimization algorithm. The sub-voxel resolution of the ULF images is handled by a sliding-window approach applying multiple grouping strategies to down-sample HF MRI to the ULF-MRI resolution. The pipeline has been tested on phantom and real data from different ULF-MRI devices, and comparison with well-known toolboxes for fMRI analysis has been performed. Our pipeline always outperformed the fMRI toolboxes (FSL and SPM). The HF–ULF MRI co-registration obtained by means of our pipeline could lead to an effective integration of ULF MRI with MEG, with the aim of improving localization accuracy, but also to help exploit ULF MRI in tumor imaging.

Automated alignment of perioperative MRI scans: A technical note and application in pediatric epilepsy surgery

Conventional image registration utilizing brain voxel information may be erroneous in a neurosurgical setting due to pathology and surgery-related anatomical distortions. We report a novel application of an automated image registration procedure based on skull segmentation for magnetic resonance imaging (MRI) scans acquired before, during and after surgery (i.e., perioperative). The procedure was implemented to assist analysis of intraoperative brain shift in 11 pediatric epilepsy surgery cases, each of whom had up to five consecutive perioperative MRI scans. The procedure consisted of the following steps: (1) Skull segmentation using tissue classification tools. (2) Estimation of rigid body transformation between image pairs using registration driven by the skull segmentation. (3) Composition of transformations to provide transformations between each scan and a common space. The procedure was validated using locations of three types of reference structural landmarks: the skull pin sites, the eye positions, and the scalp skin surface, detected using the peak intensity gradient. The mean target registration error (TRE) scores by skull pin sites and scalp skin rendering were around 1 mm and <1 mm, respectively. Validation by eye position demonstrated >1 mm TRE scores, suggesting it is not a reliable reference landmark in surgical scenarios. Comparable registration accuracy was achieved between opened and closed skull scan pairs and closed and closed skull scan pairs. Our procedure offers a reliable registration framework for processing intrasubject time series perioperative MRI data, with potential of improving intraoperative MRI-based image guidance in neurosurgical practice. Hum Brain Mapp 37:3530-3543, 2016. © 2016 Wiley Periodicals, Inc.

Comparison of manual and automatic MR-CT registration for radiotherapy of prostate cancer

In image‐guided radiotherapy (IGRT) of prostate cancer, delineation of the clinical target volume (CTV) often relies on magnetic resonance (MR) because of its good soft‐tissue visualization. Registration of MR and computed tomography (CT) is required in order to add this accurate delineation to the dose planning CT. An automatic approach for local MR‐CT registration of the prostate has previously been developed using a voxel property‐based registration as an alternative to a manual landmark‐based registration. The aim of this study is to compare the two registration approaches and to investigate the clinical potential for replacing the manual registration with the automatic registration. Registrations and analysis were performed for 30 prostate cancer patients treated with IGRT using a Ni‐Ti prostate stent as a fiducial marker. The comparison included computing translational and rotational differences between the approaches, visual inspection, and computing the overlap of the CTV. The computed mean translational difference was 1.65, 1.60, and 1.80 mm and the computed mean rotational difference was 1.51°, 3.93°, and 2.09° in the superior/inferior, anterior/posterior, and medial/lateral direction, respectively. The sensitivity of overlap was 87%. The results demonstrate that the automatic registration approach performs registrations comparable to the manual registration.

PACS number(s): 87.57.nj, 87.61.‐c, 87.57.Q‐, 87.56.J‐

A new strategy to improve coregistration of SPECT and MR images in patients with high grade glioma

This paper proposes a new strategy to optimize the coregistration of Technetium-99m Sestamibi SPECT and MRI data in case of patients with high grade glioma. It consists in a personalized approach which selects, for each data set, the best registration method among several ones. To achieve this selection, a quantitative dedicated evaluation criterion based on the average intensities within specific anatomical structures corresponding to physiological areas of uptake of Sestamibi was defined. The strategy was applied to sixty-two data sets using nine registration methods based on mutual information and chamfer distance registration approaches, with different settings. It was implemented within the Anatomist/Brainvisa environment, using its basic registration functions. The visual evaluation by experts indicated that this strategy provides 60% good quality registrations, and 26% intermediate quality ones. Compared to the single use of the best global registration method, the number of registrations of good quality was multiplied by 1.4 when using the data specific strategy.

An evaluation of four CT-MRI co-registration techniques for radiotherapy treatment planning of prone rectal cancer patients

OBJECTIVES

MRI is the preferred staging modality for rectal carcinoma patients. This work assesses the CT-MRI co-registration accuracy of four commercial rigid-body techniques for external beam radiotherapy treatment planning for patients treated in the prone position without fiducial markers.

METHODS

17 patients with biopsy-proven rectal carcinoma were scanned with CT and MRI in the prone position without the use of fiducial markers. A reference co-registration was performed by consensus of a radiologist and two physicists. This was compared with two automated and two manual techniques on two separate treatment planning systems. Accuracy and reproducibility were analysed using a measure of target registration error (TRE) that was based on the average distance of the mis-registration between vertices of the clinically relevant gross tumour volume as delineated on the CT image.

RESULTS

An automated technique achieved the greatest accuracy, with a TRE of 2.3 mm. Both automated techniques demonstrated perfect reproducibility and were significantly faster than their manual counterparts. There was a significant difference in TRE between registrations performed on the two planning systems, but there were no significant differences between the manual and automated techniques.

CONCLUSION

For patients with rectal cancer, MRI acquired in the prone treatment position without fiducial markers can be accurately registered with planning CT. An automated registration technique offered a fast and accurate solution with associated uncertainties within acceptable treatment planning limits.

Functional MRI for Radiotherapy of Gliomas

In this paper, we review the applications of functional magnetic resonance imaging (MRI) for target delineation and critical organ avoidance for brain radiotherapy. In this article we distinguish functional MRI from brain functional MRI (fMRI). Functional MRI includes magnetic resonance spectroscopic imaging (MRSI), perfusion MRI, diffusion tensor imaging (DTI) and brain fMRI. These functional MRI modalities can provide unique metabolic, pathological and physiological information that are not available in anatomic MRI and can potentially improve the treatment outcomes of brain tumors. For example, both choline (Cho) to N-acetylaspartate (NAA) and Cho to creatine (Cr) ratios from MRSI increase with increasing tumor malignancy and can be used to grade gliomas. Relative cerebral blood volume (rCBV) measurements from dynamic susceptibility contrast perfusion magnetic resonance imaging (DSC MRI) are superior to conventional contrast-enhanced MRI in predicting tumor biology and may be even superior to pathologic assessment in predicting patient clinical outcomes. Brain fMRI can help identify and avoid functionally critical areas when constructing treatment plans for brain radiotherapy. In the past, functional MRI measurements have not been routinely used in a clinical arena due to the experimental nature of these imaging modalities. As these methods become more commonly used and effective image co-registration algorithms become available, integration of functional MRI into the treatment process of brain radiotherapy now appears to be clinically feasible, at least in major medical centers.

Results of a multi-institutional benchmark test for cranial CT/MR image registration

PURPOSE

Variability in computed tomography/magnetic resonance imaging (CT/MR) cranial image registration was assessed using a benchmark case developed by the Quality Assurance Review Center to credential institutions for participation in Children's Oncology Group Protocol ACNS0221 for treatment of pediatric low-grade glioma.

METHODS AND MATERIALS

Two DICOM image sets, an MR and a CT of the same patient, were provided to each institution. A small target in the posterior occipital lobe was readily visible on two slices of the MR scan and not visible on the CT scan. Each institution registered the two scans using whatever software system and method it ordinarily uses for such a case. The target volume was then contoured on the two MR slices, and the coordinates of the center of the corresponding target in the CT coordinate system were reported. The average of all submissions was used to determine the true center of the target.

RESULTS

Results are reported from 51 submissions representing 45 institutions and 11 software systems. The average error in the position of the center of the target was 1.8 mm (1 standard deviation = 2.2 mm). The least variation in position was in the lateral direction. Manual registration gave significantly better results than did automatic registration (p = 0.02).

CONCLUSION

When MR and CT scans of the head are registered with currently available software, there is inherent uncertainty of approximately 2 mm (1 standard deviation), which should be considered when defining planning target volumes and PRVs for organs at risk on registered image sets.

A comparative study of three CT and MRI registration algorithms in nasopharyngeal carcinoma

Objective: To evaluate the image registration accuracy and efficiency of CT and MRI fusion using three algorithms in nasopharyngeal carcinoma (NPC). Methods and materials: Twelve sets of CT and MRI scans of 12 NPC patients were fused using three image registration algorithms, respectively: Mark‐and‐link, Interactive, and Normalized Mutual Information (NMI). Registration accuracy was evaluated by performing statistical analysis of the coordinate differences between CT and MR anatomical landmarks along the x‐, y‐ and z‐axes. The time required to complete the registration process using three algorithms was also recorded. One‐way ANOVA was used to analyze the difference of the three registration methods. Results: The mean time required for CT/MRI registration using the three different registration algorithms, mark‐and‐link, interactive, and NMI, was 6.25 min, 5.25 min, and 5.15 min, respectively. The mark‐and‐link method was more time consuming (F=8.74,p=0.001); however no statistical difference was found between the time required using interactive and NMI methods (p=0.77). Mean registration errors of the three methods along the x‐axis were 0.66 mm, 0.70 mm, and 0.68 mm, respectively (F=0.09,p=0.91). Along the y‐axis, the mean registration errors were 1.03 mm, 1.04 mm, and 1.03 mm, respectively (F=0.02,p=0.98). Along the z‐axis, they were 0.58 mm, 0.64 mm, and 0.56 mm, respectively (F=0.21,p=0.81).

Conclusions: All three registration algorithms, mark‐and‐link, interactive, and NMI, can provide accurate CT/MRI registration. However the mark‐and‐link method was most time consuming.

PACS number: 87.57.nj

Accuracy of 3D volumetric image registration based on CT, MR and PET/CT phantom experiments

Registration is critical for image‐based treatment planning and image‐guided treatment delivery. Although automatic registration is available, manual, visual‐based image fusion using three orthogonal planar views (3P) is always employed clinically to verify and adjust an automatic registration result. However, the 3P fusion can be time consuming, observer dependent, as well as prone to errors, owing to the incomplete 3‐dimensional (3D) volumetric image representations. It is also limited to single‐pixel precision (the screen resolution). The 3D volumetric image registration (3DVIR) technique was developed to overcome these shortcomings. This technique introduces a 4th dimension in the registration criteria beyond the image volume, offering both visual and quantitative correlation of corresponding anatomic landmarks within the two registration images, facilitating a volumetric image alignment, and minimizing potential registration errors. The 3DVIR combines image classification in real‐time to select and visualize a reliable anatomic landmark, rather than using all voxels for alignment. To determine the detection limit of the visual and quantitative 3DVIR criteria, slightly misaligned images were simulated and presented to eight clinical personnel for interpretation. Both of the criteria produce a detection limit of 0.1 mm and 0.1°. To determine the accuracy of the 3DVIR method, three imaging modalities (CT, MR and PET/CT) were used to acquire multiple phantom images with known spatial shifts. Lateral shifts were applied to these phantoms with displacement intervals of 5.0±0.1mm. The accuracy of the 3DVIR technique was determined by comparing the image shifts determined through registration to the physical shifts made experimentally. The registration accuracy, together with precision, was found to be: 0.02±0.09mm for CT/CT images, 0.03±0.07mm for MR/MR images, and 0.03±0.35mm for PET/CT images. This accuracy is consistent with the detection limit, suggesting an absence of detectable systematic error. This 3DVIR technique provides a superior alternative to the 3P fusion method for clinical applications.

PACS numbers: 87.57.nj, 87.57.nm, 87.57.‐N, 87.57.‐s

Intracranial stereotactic positioning systems: Report of the American Association of Physicists in Medicine Radiation Therapy Committee Task Group No. 68

Intracranial stereotactic positioning systems (ISPSs) are used to position patients prior to precise radiation treatment of localized lesions of the brain. Often, the lesion is located in close proximity to critical anatomic features whose functions should be maintained. Many types of ISPSs have been described in the literature and are commercially available. These are briefly reviewed. ISPS systems provide two critical functions. The first is to establish a coordinate system upon which a guided therapy can be applied. The second is to provide a method to reapply the coordinate system to the patient such that the coordinates assigned to the patient's anatomy are identical from application to application. Without limiting this study to any particular approach to ISPSs, this report introduces nomenclature and suggests performance tests to quantify both the stability of the ISPS to map diagnostic data to a coordinate system, as well as the ISPS's ability to be realigned to the patient's anatomy. For users who desire to develop a new ISPS system, it may be necessary for the clinical team to establish the accuracy and precision of each of these functions. For commercially available systems that have demonstrated an acceptable level of accuracy and precision, the clinical team may need to demonstrate local ability to apply the system in a manner consistent with that employed during the published testing. The level of accuracy and precision required of an individual ISPS system is dependent upon the clinical protocol (e.g., fractionation, margin, pathology, etc.). Each clinical team should provide routine quality assurance procedures that are sufficient to support the assumptions of accuracy and precision used during the planning process. The testing of ISPS systems can be grouped into two broad categories, type testing, which occurs prior to general commercialization, and site testing, performed when a commercial system is installed at a clinic. Guidelines to help select the appropriate tests as well as recommendations to help establish the required frequency of testing are provided. Because of the broad scope of different systems, it is important that both the manufacturer and user rigorously critique the system and set QA tests appropriate to the particular device and its possible weaknesses. Major recommendations of the Task Group include: introduction of a new nomenclature for reporting repositioning accuracy; comprehensive analysis of patient characteristics that might adversely affect positioning accuracy; performance of testing immediately before each treatment to establish that there are no gross positioning errors; a general request to the Medical Physics community for improved QA tools; implementation of weekly portal imaging (perhaps cone beam CT in the future) as a method of tracking fractionated patients (as per TG 40); and periodic routine reviews of positioning accuracy.