Imaging and alignment for image-guided radiation therapy

Cardiac motion estimation from medical images: a regularisation framework applied on pairwise image registration displacement fields

Accurate cardiac motion estimation from medical images such as ultrasound is important for clinical evaluation. We present a novel regularisation layer for cardiac motion estimation that will be applied after image registration and demonstrate its effectiveness. The regularisation utilises a spatio-temporal model of motion, b-splines of Fourier, to fit to displacement fields from pairwise image registration. In the process, it enforces spatial and temporal smoothness and consistency, cyclic nature of cardiac motion, and better adherence to the stroke volume of the heart. Flexibility is further given for inclusion of any set of registration displacement fields. The approach gave high accuracy. When applied to human adult Ultrasound data from a Cardiac Motion Analysis Challenge (CMAC), the proposed method is found to have 10% lower tracking error over CMAC participants. Satisfactory cardiac motion estimation is also demonstrated on other data sets, including human fetal echocardiography, chick embryonic heart ultrasound images, and zebrafish embryonic microscope images, with the average Dice coefficient between estimation motion and manual segmentation at 0.82-0.87. The approach of performing regularisation as an add-on layer after the completion of image registration is thus a viable option for cardiac motion estimation that can still have good accuracy. Since motion estimation algorithms are complex, dividing up regularisation and registration can simplify the process and provide flexibility. Further, owing to a large variety of existing registration algorithms, such an approach that is usable on any algorithm may be useful.

Volume-of-interest imaging with dynamic fluence modulation using multiple aperture devices

Volume-of-interest (VOI) imaging is a strategy in computed tomography (CT) that restricts x-ray fluence to particular anatomical targets via dynamic beam modulation. This permits dose reduction while retaining image quality within the VOI. VOI-CT implementation has been challenged, in part, by a lack of hardware solutions for tailoring the incident fluence to the patient and anatomical site, as well as difficulties involving interior tomography reconstruction of truncated projection data. We propose a general VOI-CT imaging framework using multiple aperture devices (MADs), an emerging beam filtration scheme based on two binary x-ray filters. Location of the VOI is prescribed using two scout views at anterior-posterior (AP) and lateral perspectives. Based on a calibration of achievable fluence field patterns, MAD motion trajectories were designed using an optimization objective that seeks to maximize the relative fluence in the VOI subject to minimum fluence constraints. A modified penalized-likelihood method is developed for reconstruction of heavily truncated data using the full-field scout views to help solve the interior tomography problem. Physical experiments were conducted to show the feasibility of noncentered and elliptical VOI in two applications-spine and lung imaging. Improved dose utilization and retained image quality are validated with respect to standard full-field protocols. We observe that the contrast-to-noise ratio (CNR) is 40% higher compared with low-dose full-field scans at the same dose. The total dose reduction is 50% for equivalent image quality (CNR) within the VOI.

Current state and future applications of radiological image guidance for particle therapy

In this review paper, we first give a short overview of radiological image guidance in photon radiotherapy, placing emphasis on the fact that linac based radiotherapy has outpaced particle therapy in the adoption of volumetric image guidance. While cone beam computed tomography (CBCT) has been an established technique in linac treatment rooms for almost two decades, the widespread adoption of volumetric image guidance in particle therapy, whether by means of CBCT or in-room CT imaging, is recent. This lag may be attributable to the bespoke nature and lower number of particle therapy installations, as well as the differences in geometry between those installations and linac treatment rooms. In addition, for particle therapy the so called shift invariance of the dose distribution rarely applies. An overview of the different volumetric image guidance solutions found at modern particle therapy facilities is provided, covering gantry, nozzle, C-arm, and couch-mounted CBCT as well different in-room CT configurations. A summary of the use of in-room volumetric imaging data beyond anatomy-based positioning is also presented as well as the necessary corrections to CBCT images for accurate water equivalent thickness calculation. Finally, the use of non-ionizing imaging modalities is discussed.

Using synthetic CT for partial brain radiation therapy: Impact on image guidance

PURPOSE

Recent advancements in synthetic computed tomography (synCT) from magnetic resonance (MR) imaging data have made MRI-only treatment planning feasible in the brain, although synCT performance for image guided radiation therapy (IGRT) is not well understood. This work compares geometric equivalence of digitally reconstructed radiographs (DRRs) from CTs and synCTs for brain cancer patients and quantifies performance for partial brain IGRT.

METHODS AND MATERIALS

Ten brain cancer patients (12 lesions, 7 postsurgical) underwent MR-SIM and CT-SIM. SynCTs were generated by combining ultra-short echo time, T1, T2, and fluid attenuation inversion recovery datasets using voxel-based weighted summation. SynCT and CT DRRs were compared using patient-specific thresholding and assessed via overlap index, Dice similarity coefficient, and Jaccard index. Planar IGRT images for 22 fractions were evaluated to quantify differences between CT-generated DRRs and synCT-generated DRRs in 6 quadrants. Previously validated software was implemented to perform 2-dimensional (2D)-2D rigid registrations using normalized mutual information. Absolute (planar image/DRR registration) and relative (differences between synCT and CT DRR registrations) shifts were calculated for each axis and 3-dimensional vector difference. A total of 1490 rigid registrations were assessed.

RESULTS

DRR agreements in anteroposterior and lateral views for overlap index, Dice similarity coefficient, and Jaccard index were >0.95. Normalized mutual information results were equivalent in 75% of quadrants. Rotational registration results were negligible (<0.07°). Statistically significant differences between CT and synCT registrations were observed in 9/18 matched quadrants/axes (P < .05). The population average absolute shifts were 0.77 ± 0.58 and 0.76 ± 0.59 mm for CT and synCT, respectively, for all axes/quadrants. Three-dimensional vectors were <2 mm in 77.7 ± 10.8% and 76.5 ± 7.2% of CT and synCT registrations, respectively. SynCT DRRs were sensitive in postsurgical cases (vector displacements >2 mm in affected quadrants).

CONCLUSIONS

DRR synCT geometry was robust. Although statistically significant differences were observed between CT and synCT registrations, results were not clinically significant. Future work will address synCT generation in postsurgical settings.

Quantification of the accuracy limits of image registration using peak signal-to-noise ratio

A new method was developed for quantifying the accuracy limits of image registration devices and the distortion of anatomical structures in verification images without image registration. A correlation was found between peak signal-to-noise ratio (PSNR) and the amount of parallel movement (1-10 mm at 1-mm intervals) of a rectangular parallelepiped phantom [correlation coefficient (CC) -0.91, contribution ratio (CR) 0.83]. Rotating the phantom from 1° to 10° at 1° intervals produced a similar correlation with PSNR (CC -0.91, CR 0.83). To allow for manual registration, the grid pattern of the Mylar top plate was extracted from 455 pelvic portal images of 21 patients using a band-pass filtering technique. This revealed a different correlation between the original data (CC -0.62, CR 0.38) and averaged data (CC -0.96, CR 0.92), but this is considered to have been caused by structural distortion and manual matching errors. Thus, PSNR can be used to evaluate the accuracy limits of image registration and provide a judgment index that can be used in re-planning or re-setup in adaptive radiotherapy.

Subject-specific four-dimensional liver motion modeling based on registration of dynamic MRI

Magnetic resonance-guided high intensity focused ultrasound treatment of the liver is a promising noninvasive technique for ablation of liver lesions. For the technique to be used in clinical practice, however, the issue of liver motion needs to be addressed. A subject-specific four-dimensional liver motion model is presented that is created based on registration of dynamically acquired magnetic resonance data. This model can be used for predicting the tumor motion trajectory for treatment planning and to indicate the tumor position for treatment guidance. The performance of the model was evaluated on a dynamic scan series that was not used to build the model. The method achieved an average Dice coefficient of 0.93 between the predicted and actual liver profiles and an average vessel misalignment of 3.0 mm. The model performed robustly, with a small variation in the results per subject. The results demonstrate the potential of the model to be used for MRI-guided treatment of liver lesions. Furthermore, the model can possibly be applied in other image-guided therapies, for instance radiotherapy of the liver.

Commissioning and Quality Assurance of an Integrated System for Patient Positioning and Setup Verification in Particle Therapy

In an increasing number of clinical indications, radiotherapy with accelerated particles shows relevant advantages when compared with high energy X-ray irradiation. However, due to the finite range of ions, particle therapy can be severely compromised by setup errors and geometric uncertainties. The purpose of this work is to describe the commissioning and the design of the quality assurance procedures for patient positioning and setup verification systems at the Italian National Center for Oncological Hadrontherapy (CNAO). The accuracy of systems installed in CNAO and devoted to patient positioning and setup verification have been assessed using a laser tracking device. The accuracy in calibration and image based setup verification relying on in room X-ray imaging system was also quantified. Quality assurance tests to check the integration among all patient setup systems were designed, and records of daily QA tests since the start of clinical operation (2011) are presented. The overall accuracy of the patient positioning system and the patient verification system motion was proved to be below 0.5 mm under all the examined conditions, with median values below the 0.3 mm threshold. Image based registration in phantom studies exhibited sub-millimetric accuracy in setup verification at both cranial and extra-cranial sites. The calibration residuals of the OTS were found consistent with the expectations, with peak values below 0.3 mm. Quality assurance tests, daily performed before clinical operation, confirm adequate integration and sub-millimetric setup accuracy. Robotic patient positioning was successfully integrated with optical tracking and stereoscopic X-ray verification for patient setup in particle therapy. Sub-millimetric setup accuracy was achieved and consistently verified in daily clinical operation.

The potential role of respiratory motion management and image guidance in the reduction of severe toxicities following stereotactic ablative radiation therapy for patients with centrally located early stage non-small cell lung cancer or lung metastases

Image guidance allows delivery of very high doses of radiation over a few fractions, known as stereotactic ablative radiotherapy (SABR). This treatment is associated with excellent outcome for early stage non-small cell lung cancer and metastases to the lungs. In the delivery of SABR, central location constantly poses a challenge due to the difficulty of adequately sparing critical thoracic structures that are immediately adjacent to the tumor if an ablative dose of radiation is to be delivered to the tumor target. As of current, various respiratory motion management and image guidance strategies can be used to ensure accurate tumor target localization prior and/or during daily treatment, which allows for maximal and safe reduction of set up margins. The incorporation of both may lead to the most optimal normal tissue sparing and the most accurate SABR delivery. Here, the clinical outcome, treatment related toxicities, and the pertinent respiratory motion management/image guidance strategies reported in the current literature on SABR for central lung tumors are reviewed.

Estimation of the uncertainty of elastic image registration with the demons algorithm

The accuracy of elastic image registration is limited. We propose an approach to detect voxels where registration based on the demons algorithm is likely to perform inaccurately, compared to other locations of the same image. The approach is based on the assumption that the local reproducibility of the registration can be regarded as a measure of uncertainty of the image registration. The reproducibility is determined as the standard deviation of the displacement vector components obtained from multiple registrations. These registrations differ in predefined initial deformations. The proposed approach was tested with artificially deformed lung images, where the ground truth on the deformation is known. In voxels where the result of the registration was less reproducible, the registration turned out to have larger average registration errors as compared to locations of the same image, where the registration was more reproducible. The proposed method can show a clinician in which area of the image the elastic registration with the demons algorithm cannot be expected to be accurate.

Fast reconstructed radiographs from octree-compressed volumetric data

PURPOSE

Simulated 2D X-ray images called digitally reconstructed radiographs (DRRs) have important applications within medical image registration frameworks where they are compared with reference X-rays or used in implementations of digital tomosynthesis (DTS). However, rendering DRRs from a CT volume is computationally demanding and relatively slow using the conventional ray-casting algorithm. Image-guided radiation therapy systems using DTS to verify target location require a large number DRRs to be precomputed since there is insufficient time within the automatic image registration procedure to generate DRRs and search for an optimal pose.

METHOD

DRRs were rendered from octree-compressed CT data. Previous work showed that octree-compressed volumes rendered by conventional ray casting deliver a registration with acceptable clinical accuracy, but efficiently rendering the irregular grid of an octree data structure is a challenge for conventional ray casting. We address this by using vertex and fragment shaders of modern graphics processing units (GPUs) to directly project internal spaces of the octree, represented by textured particle sprites, onto the view plane. The texture is procedurally generated and depends on the CT pose.

RESULTS

The performance of this new algorithm was found to be 4 times faster than that of a ray-casting algorithm implemented using NVIDIA™Compute Unified Device Architecture (CUDA™) on an equivalent GPU (~95 % octree compression). Rendering artifacts are apparent (consistent with other splatting algorithm), but image quality tends to improve with compression and fewer particles are needed. A peak signal-to-noise ratio analysis confirmed that the images rendered from compressed volumes were of marginally better quality to those rendered using Gaussian footprints.

CONCLUSIONS

Using octree-encoded DRRs within a 2D/3D registration framework indicated the approach may be useful in accelerating automatic image registration.

Quantitative metrics for assessing plan quality

Despite many studies over the last 3 decades that have attempted to explicitly quantify the decision-making process for radiotherapy treatment plan evaluation, judgments of an individual plan's degree of quality are still largely subjective and can show inter- and intra-practitioner variability even if the clinical treatment goals are the same. Several factors conspire to confound the full quantification of treatment plan quality, including uncertainties in dose response of cancerous and normal tissue, the rapid pace of new technology adoption, and the human component of treatment planning. However, new developments in clinical informatics and automation are lowering the bar for developing and implementing quantitative metrics into the treatment planning process. This review discusses general strategies for using quantitative metrics in the treatment planning process and presents a case study in intensity-modulated radiation therapy planning whereby control was established on a variable system via such techniques.

Integration of FDG-PET/CT into external beam radiation therapy planning: technical aspects and recommendations on methodological approaches

This work addresses the clinical adoption of FDG-PET/CT for image-guided radiation therapy planning (RTP). As such, important technical and methodological aspects of PET/CT-based RTP are reviewed and practical recommendations are given for routine patient management and clinical studies. First, recent developments in PET/CT hardware that are relevant to RTP are reviewed in the context of quality control and system calibration procedures that are mandatory for a reproducible adoption of PET/CT in RTP. Second, recommendations are provided on image acquisition and reconstruction to support the standardization of imaging protocols. A major prerequisite for routine RTP is a complete and secure data transfer to the actual planning system. Third, state-of-the-art tools for image fusion and co-registration are discussed briefly in the context of PET/CT imaging pre- and post-RTP. This includes a brief review of state-of-the-art image contouring algorithms relevant to PET/CT-guided RTP. Finally, practical aspects of clinical workflow and patient management, such as patient setup and requirements for staff training are emphasized. PET/CT-guided RTP mandates attention to logistical aspects, patient set-up and acquisition parameters as well as an in-depth appreciation of quality control and protocol standardization.

CONCLUSION

Upon fulfilling the requirements to perform PET/CT for RTP, a new dimension of molecular imaging can be added to traditional morphological imaging. As a consequence, PET/CT imaging will support improved RTP and better patient care. This document serves as a guidance on practical and clinically validated instructions that are deemed useful to the staff involved in PET/CT-guided RTP.

Intraoperative image-based multiview 2D/3D registration for image-guided orthopaedic surgery: incorporation of fiducial-based C-arm tracking and GPU-acceleration

Intraoperative patient registration may significantly affect the outcome of image-guided surgery (IGS). Image-based registration approaches have several advantages over the currently dominant point-based direct contact methods and are used in some industry solutions in image-guided radiation therapy with fixed X-ray gantries. However, technical challenges including geometric calibration and computational cost have precluded their use with mobile C-arms for IGS. We propose a 2D/3D registration framework for intraoperative patient registration using a conventional mobile X-ray imager combining fiducial-based C-arm tracking and graphics processing unit (GPU)-acceleration. The two-stage framework 1) acquires X-ray images and estimates relative pose between the images using a custom-made in-image fiducial, and 2) estimates the patient pose using intensity-based 2D/3D registration. Experimental validations using a publicly available gold standard dataset, a plastic bone phantom and cadaveric specimens have been conducted. The mean target registration error (mTRE) was 0.34 ± 0.04 mm (success rate: 100%, registration time: 14.2 s) for the phantom with two images 90° apart, and 0.99 ± 0.41 mm (81%, 16.3 s) for the cadaveric specimen with images 58.5° apart. The experimental results showed the feasibility of the proposed registration framework as a practical alternative for IGS routines.

A review of methods of analysis in contouring studies for radiation oncology

Inter-observer variability in anatomical contouring is the biggest contributor to uncertainty in radiation treatment planning. Contouring studies are frequently performed to investigate the differences between multiple contours on common datasets. There is, however, no widely accepted method for contour comparisons. The purpose of this study is to review the literature on contouring studies in the context of radiation oncology, with particular consideration of the contouring comparison methods they employ. A literature search, not limited by date, was conducted using Medline and Google Scholar with key words: contour, variation, delineation, inter/intra observer, uncertainty and trial dummy-run. This review includes a description of the contouring processes and contour comparison metrics used. The use of different processes and metrics according to tumour site and other factors were also investigated with limitations described. A total of 69 relevant studies were identified. The most common tumour sites were prostate (26), lung (10), head and neck cancers (8) and breast (7).The most common metric of comparison was volume used 59 times, followed by dimension and shape used 36 times, and centre of volume used 19 times. Of all 69 publications, 67 used a combination of metrics and two used only one metric for comparison. No clear relationships between tumour site or any other factors that may influence the contouring process and the metrics used to compare contours were observed from the literature. Further studies are needed to assess the advantages and disadvantages of each metric in various situations.

Multi-system verification of registrations for image-guided radiotherapy in clinical trials

PURPOSE

To provide quantitative information on the image registration differences from multiple systems for image-guided radiotherapy (IGRT) credentialing and margin reduction in clinical trials.

METHODS AND MATERIALS

Images and IGRT shift results from three different treatment systems (Tomotherapy Hi-Art, Elekta Synergy, Varian Trilogy) have been sent from various institutions to the Image-Guided Therapy QA Center (ITC) for evaluation for the Radiation Therapy Oncology Group (RTOG) trials. Nine patient datasets (five head-and-neck and four prostate) were included in the comparison, with each patient having 1-4 daily individual IGRT studies. In all cases, daily shifts were re-calculated by re-registration of the planning CT with the daily IGRT data using three independent software systems (MIMvista, FocalSim, VelocityAI). Automatic fusion was used in all calculations. The results were compared with those submitted from institutions. Similar regions of interest (ROIs) and same initial positions were used in registrations for inter-system comparison. Different slice spacings for CBCT sampling and different ROIs for registration were used in some cases to observe the variation of registration due to these factors.

RESULTS

For the 54 comparisons with head-and-neck datasets, the absolute values of differences of the registration results between different systems were 2.6±2.1 mm (mean±SD; range 0.1-8.6 mm, left-right [LR]), 1.7±1.3 mm (0.0-4.9 mm, superior-inferior [SI]), and 1.8±1.1 mm (0.1-4.0 mm, anterior-posterior [AP]). For the 66 comparisons in prostate cases, the differences were 1.1±1.0 mm (0.0-4.6 mm, LR), 2.1±1.7 mm (0.0-6.6 mm, SI), and 2.0±1.8 mm (0.1-6.9 mm, AP). The differences caused by the slice spacing variation were relatively small, and the different ROI selections in FocalSim and MIMvista also had limited impact.

CONCLUSION

The extent of differences was reported when different systems were used for image registration. Careful examination and quality assurance of the image registration process are crucial before considering margin reduction using IGRT in clinical trials.

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 BPF-FBP tandem algorithm for image reconstruction in reverse helical cone-beam CT

PURPOSE

Reverse helical cone-beam computed tomography (CBCT) is a scanning configuration for potential applications in image-guided radiation therapy in which an accurate anatomic image of the patient is needed for image-guidance procedures. The authors previously developed an algorithm for image reconstruction from nontruncated data of an object that is completely within the reverse helix. The purpose of this work is to develop an image reconstruction approach for reverse helical CBCT of a long object that extends out of the reverse helix and therefore constitutes data truncation.

METHODS

The proposed approach comprises of two reconstruction steps. In the first step, a chord-based backprojection-filtration (BPF) algorithm reconstructs a volumetric image of an object from the original cone-beam data. Because there exists a chordless region in the middle of the reverse helix, the image obtained in the first step contains an unreconstructed central-gap region. In the second step, the gap region is reconstructed by use of a Pack-Noo-formula-based filteredback-projection (FBP) algorithm from the modified cone-beam data obtained by subtracting from the original cone-beam data the reprojection of the image reconstructed in the first step.

RESULTS

The authors have performed numerical studies to validate the proposed approach in image reconstruction from reverse helical cone-beam data. The results confirm that the proposed approach can reconstruct accurate images of a long object without suffering from data-truncation artifacts or cone-angle artifacts.

CONCLUSIONS

They developed and validated a BPF-FBP tandem algorithm to reconstruct images of a long object from reverse helical cone-beam data. The chord-based BPF algorithm was utilized for converting the long-object problem into a short-object problem. The proposed approach is applicable to other scanning configurations such as reduced circular sinusoidal trajectories.

Method comparison of automated matching software-assisted cone-beam CT and stereoscopic kilovoltage x-ray positional verification image-guided radiation therapy for head and neck cancer: a prospective analysis

We sought to characterize interchangeability and agreement between cone-beam computed tomography (CBCT) and digital stereoscopic kV x-ray (KVX) acquisition, two methods of isocenter positional verification currently used for IGRT of head and neck cancers (HNC). A cohort of 33 patients were near-simultaneously imaged by in-room KVX and CBCT. KVX and CBCT shifts were suggested using manufacturer software for the lateral (X), vertical (Y) and longitudinal (Z) dimensions. Intra-method repeatability, systematic and random error components were calculated for each imaging modality, as were recipe-based PTV expansion margins. Inter-method agreement in each axis was compared using limits of agreement (LOA) methodology, concordance analysis and orthogonal regression. 100 daily positional assessments were performed before daily therapy in 33 patients with head and neck cancer. Systematic error was greater for CBCT in all axes, with larger random error components in the Y- and Z-axis. Repeatability ranged from 9 to 14 mm for all axes, with CBCT showing greater repeatability in 2/3 axes. LOA showed paired shifts to agree 95% of the time within +/-11.3 mm in the X-axis, +/-9.4 mm in the Y-axis and +/-5.5 mm in the Z-axis. Concordance ranged from 'mediocre' to 'satisfactory'. Proportional bias was noted between paired X- and Z-axis measures, with a constant bias component in the Z-axis. Our data suggest non-negligible differences in software-derived CBCT and KVX image-guided directional shifts using formal method comparison statistics.

A stochastic approach to estimate the uncertainty involved in B-spline image registration

Uncertainties in image registration may be a significant source of errors in anatomy mapping as well as dose accumulation in radiotherapy. It is, therefore, essential to validate the accuracy of image registration. Here, we propose a method to detect areas where mono modal B-spline registration performs well and to distinguish those from areas of the same image, where the registration is likely to be less accurate. It is a stochastic approach to automatically estimate the uncertainty of the resulting displacement vector field. The coefficients resulting from the B-spline registration are subject to moderate and randomly performed variations. A quantity is proposed to characterize the local sensitivity of the similarity measure to these variations. We demonstrate the statistical dependence between the local image registration error and this quantity by calculating their mutual information. We show the significance of the statistical dependence with an approach based on random redistributions. The proposed method has the potential to divide an image into subregions which differ in the magnitude of their average registration error.

Stochastic rank correlation: a robust merit function for 2D/3D registration of image data obtained at different energies

In this article, the authors evaluate a merit function for 2D/3D registration called stochastic rank correlation (SRC). SRC is characterized by the fact that differences in image intensity do not influence the registration result; it therefore combines the numerical advantages of cross correlation (CC)-type merit functions with the flexibility of mutual-information-type merit functions. The basic idea is that registration is achieved on a random subset of the image, which allows for an efficient computation of Spearman's rank correlation coefficient. This measure is, by nature, invariant to monotonic intensity transforms in the images under comparison, which renders it an ideal solution for intramodal images acquired at different energy levels as encountered in intrafractional kV imaging in image-guided radiotherapy. Initial evaluation was undertaken using a 2D/3D registration reference image dataset of a cadaver spine. Even with no radiometric calibration, SRC shows a significant improvement in robustness and stability compared to CC. Pattern intensity, another merit function that was evaluated for comparison, gave rather poor results due to its limited convergence range. The time required for SRC with 5% image content compares well to the other merit functions; increasing the image content does not significantly influence the algorithm accuracy. The authors conclude that SRC is a promising measure for 2D/3D registration in IGRT and image-guided therapy in general.

Region-of-interest image reconstruction with intensity weighting in circular cone-beam CT for image-guided radiation therapy

Imaging plays a vital role in radiation therapy and with recent advances in technology considerable emphasis has been placed on cone-beam CT (CBCT). Attaching a kV x-ray source and a flat panel detector directly to the linear accelerator gantry has enabled progress in target localization techniques, which can include daily CBCT setup scans for some treatments. However, with an increasing number of CT scans there is also an increasing concern for patient exposure. An intensity-weighted region-of-interest (IWROI) technique, which has the potential to greatly reduce CBCT dose, in conjunction with the chord-based backprojection-filtration (BPF) reconstruction algorithm, has been developed and its feasibility in clinical use is demonstrated in this article. A nonuniform filter is placed in the x-ray beam to create regions of two different beam intensities. In this manner, regions outside the target area can be given a reduced dose but still visualized with a lower contrast to noise ratio. Image artifacts due to transverse data truncation, which would have occurred in conventional reconstruction algorithms, are avoided and image noise levels of the low- and high-intensity regions are well controlled by use of the chord-based BPF reconstruction algorithm. The proposed IWROI technique can play an important role in image-guided radiation therapy.

Technological approaches to in-room CBCT imaging

The use of Cone-Beam Computed Tomography (CBCT) in Image-Guided Radiation Therapy (IGRT) has become increasingly feasible and popular in recent years. Advances and developments in Flat-Panel Imager (FPI) technology and image reconstruction software allow for linac-mounted 3D CBCT imaging. Taking CBCT images on a daily/weekly basis, offers the possibility to guide the treatment beam according to tumour motion and to apply changes to the treatment plan if necessary. This however raises the issue of additional imaging dose and thus increases in secondary cancer risk. The performance characteristics of kV-CBCT and MV-CBCT solutions currently offered by Elekta, Siemens and Varian are compared in this paper in terms of additional imaging dose and image quality. The review also outlines applications of CBCT for IGRT and Adaptive Radiotherapy (ART). As CBCT is not the only in-room IGRT platform, helical MV-CT (Tomotherapy) and in-room CT designs are also presented.

Biological image-guided radiotherapy in rectal cancer: is there a role for FMISO or FLT, next to FDG?

PURPOSE

The purpose of this study is to investigate the use of PET/CT with fluorodeoxyglucose (FDG), fluorothymidine (FLT) and fluoromisonidazole (FMISO) for radiotherapy (RT) target definition and evolution in rectal cancer.

MATERIALS AND METHODS

PET/CT was performed before and during preoperative chemoradiotherapy (CRT) in 15 patients with resectable rectal cancer. PET signals were delineated and CT images on the different time points were non-rigidly registered. Mismatch analyses were carried out to quantify the overlap between FDG and FLT or FMISO tumour volumes (TV) and between PET TVs over time.

RESULTS

Ninety sequential PET/CT images were analyzed. The mean FDG, FLT and FMISO-PET TVs showed a tendency to shrink during preoperative CRT. On each time point, the mean FDG-PET TV was significantly larger than the FMISO-PET TV but not significantly larger than the mean FLT-PET TV. There was a mean 65% mismatch between the FMISO and FDG TVs obtained before and during CRT. FLT TVs corresponded better with the FDG TVs (25% mismatch before and 56% during CRT). During CRT, on average 61% of the mean FDG TV (7 cc) overlapped with the baseline mean TV (15.5 cc) (n=15). For FLT, the TV overlap was 49% (n=5) and for FMISO only 20% of the TV during CRT remained inside the contour at baseline (n=10).

CONCLUSION

FDG, FLT and FMISO-PET reflect different functional characteristics that change during CRT in rectal cancer. FLT and FDG show good spatial correspondence, while FMISO seems less reliable due to the non-specific FMISO uptake in normoxic tissue and tracer diffusion through the bowel wall. FDG and FLT-PET/CT imaging seem most appropriate to integrate in preoperative RT for rectal cancer.

IGRT in rectal cancer

To date, no great interest has been shown in the clinical implementation of recent Image-guided radiation therapy (IGRT) modalities in rectal cancer since only a few studies have been published on this issue. This may be explained by the fact that with current treatment modalities locoregional recurrences are already very low (around 10%). However, there is still room for improvement in treatment of high risk patients (cT3 CRM+, cT4, N+). In these patients better results may be obtained improving radiation technique from 2D to 3D, which showed to be more reliable in terms of target coverage. Also, when higher doses are delivered, Intensity Modulated Radiation Therapy (IMRT) may be used to spare small bowel. But before employing 3D irradiation or IMRT, a proper definition of our clinical target volume (CTV) and planning target volume (PTV) is needed. The CTV should encompass the tumour site, the mesorectum and the lateral nodes, recognized as the most likely sites of local recurrence, with different incidence according to tumour stage. Recent studies discussed the correct delineation of these target volumes in respect of tumour site and stage. From the preliminary results of a study conducted in Rome University 2D planning seemed insufficient to cover the different target volumes especially in T4 patients compared to 3D planning. Also an appropriate PTV margin is necessary in order to manage set-up errors and organ motion. Particularly in these patients, the knowledge of mesorectal movement is required to avoid target missing. Large mesorectal displacements were observed in a study carried out in Leuven University in collaboration with Rome University. A systematic review of the literature together with the data from these first experiences led to the awareness that IGRT could help us to follow the target volume and organs at risk during the treatment, allowing adjustments to improve accuracy in dose delivery, especially when dose escalation studies are planned in the treatment of rectal cancer.

Innovations in image-guided radiotherapy

The limited ability to control for the location of a tumour compromises the accuracy with which radiation can be delivered to tumour-bearing tissue. The resultant requirement for larger treatment volumes to accommodate target uncertainty restricts the radiation dose because more surrounding normal tissue is exposed. With image-guided radiotherapy (IGRT) these volumes can be optimized and tumoricidal doses can be delivered, achieving maximal tumour control with minimal complications. Moreover, with the ability of high-precision dose delivery and real-time knowledge of the target volume location, IGRT has initiated the exploration of new indications for radiotherapy, some of which were previously considered infeasible.