Rigid Co-registration Research Articles

EP-1333: Impact of 18 F-Choline PET scan acquisition time on delineation of GTV in Prostate cancer

Background: Dose painting radiotherapy requires accurate outlining of primary tumour volumes in the prostate. T2-Weighted (T2W) Magnetic Resonance Imaging (MRI) is the best imaging method for defining the gross tumour volume (GTV). Choline positron emission tomography (PET) is currently a controversial tracer. The image acquisition differs significantly in published studies. Many used early static imaging. One study found that 18F-choline PET/CT with late image acquisition has superior accuracy to T2W MR and functional MR alone1. We investigate whether increasing 18F-Choline PET scan acquisition time from 60 (PET-60) to 90 (PET-90) minutes improves GTV TVD. Methods. Analysis was performed on 9 18F-Choline PET scans. Patients were injected with 370MBq of activity. Three clinicians (C1, C2 and C3) independently and without reference to each other contoured GTVs on each of the T2W-MRI, PET-60 and PET-90 scans at differing times. Scans were registered by a clinician using rigid co-registration. The treating clinicians MRI contour was used as a reference contour. The resulting PET and MRI GTVs were transferred to the PET-60 and PET-90 scans after image registration. The Dice Similarity Coefficient (DSC), Specificity (Sp) and Sensitivity (S) were calculated from contour mask voxel analysis. Results. Table 1 shows the mean and range DSC, S and Sp scores on MRI, PET-60 and PET-90 for C1, C2 and C3 in comparison to the treating clinicians contour on MRI (C1). A 2 sampled T-test (P < 0.01) showed, no significant difference in the Sp, S and DSC between GTVs on PET-60 and PET-90 scans. Further to this, as shown in Figure 1, variability in GTV delineation is significant between observers in a singular case as well as across imaging modalities. Conclusion. Compared to MRI delineated GTVs, 18F-Choline PET GTVs are significantly different. This study found however that increasing the PET scan acquisition time from 60 to 90 minutes did not improve the performance of GTV TVD in comparison to MRI delineated GTV.

Do perfusion and diffusion MRI predict glioblastoma relapse sites following chemoradiation?

To assess the value of T2* dynamic-susceptibility contrast MRI (DSC-MRI) and diffusion-weighted imaging (DWI) to predict the glioblastoma relapse sites after chemoradiation. From a cohort of 44 patients, primarily treated with radiotherapy (60Gy) and concomitant temozolomide for glioblastoma, who were included in the reference arm of a prospective clinical trial (NCT01507506), 15 patients relapsed and their imaging data were analyzed. All patients underwent anatomical MRI, DSC-MRI and DWI before radiotherapy and every 2 months thereafter until relapse. Voxels within the sites of relapse were correlated with their perfusion and/or diffusion abnormality (PDA) pretreatment status after rigid co-registration. The relative cerebral blood volume (rCBV) and apparent diffusion coefficient (ADC) were used as biomarkers. Several PDA areas were thresholded: hyperperfused voxels using a 1.75 fixed rCBV threshold (HPt); hypoperfused (hPg) and hyperperfused (HPg) voxels using a histogram-based Gaussian method; diffusion-restricted voxels (DRg); and HPg voxels with diffusion restriction (HPg&DRg). Two sets of voxels (2,459,483 and 2,073,880) were analyzed according to these thresholding methods. Positive predictive values (PPV) of PDA voxels were low (between 9.5 and 31.9 %). The best PPV was obtained with HPg&DRg voxels within the FLAIR hyperintensity, as 18.3 % of voxels without initial PDA were within relapse sites, versus 31.9 % with initial PDA (p < 0.0001). This prospective study suggests that DSC and/or DWI-MRI do not predict the glioblastoma relapse sites. However, further investigations with new methodological approaches are needed to better understand the role of these modalities in the prediction of glioblastoma relapse sites.

A Comparison of Accuracy of Image- versus Hardware-based Tracking Technologies in 3D Fusion in Aortic Endografting

Fusion of three-dimensional (3D) computed tomography and intraoperative two-dimensional imaging in endovascular surgery relies on manual rigid co-registration of bony landmarks and tracking of hardware to provide a 3D overlay (hardware-based tracking, HWT). An alternative technique (image-based tracking, IMT) uses image recognition to register and place the fusion mask. We present preliminary experience with an agnostic fusion technology that uses IMT, with the aim of comparing the accuracy of overlay for this technology with HWT. Data were collected prospectively for 12 patients. All devices were deployed using both IMT and HWT fusion assistance concurrently. Postoperative analysis of both systems was performed by three blinded expert observers, from selected time-points during the procedures, using the displacement of fusion rings, the overlay of vascular markings and the true ostia of renal arteries. The Mean overlay error and the deviation from mean error was derived using image analysis software. Comparison of the mean overlay error was made between IMT and HWT. The validity of the point-picking technique was assessed. IMT was successful in all of the first 12 cases, whereas technical learning curve challenges thwarted HWT in four cases. When independent operators assessed the degree of accuracy of the overlay, the median error for IMT was 3.9mm (IQR 2.89-6.24, max 9.5) versus 8.64mm (IQR 6.1-16.8, max 24.5) for HWT (p=.001). Variance per observer was 0.69mm(2) and 95% limit of agreement ±1.63. In this preliminary study, the error of magnitude of displacement from the "true anatomy" during image overlay in IMT was less than for HWT. This confirms that ongoing manual re-registration, as recommended by the manufacturer, should be performed for HWT systems to maintain accuracy. The error in position of the fusion markers for IMT was consistent, thus may be considered predictable.

Coregistration of datasets from a micro-SPECT/CT and a preclinical 1.5 T MRI

An universal tool was designed for small animal SPECT/CT/MR coregistration. It was tested on a preclinical MRI (OPTImouse, RS2D, Bischwiller, France) and a micro-SPECT/CT (eXplore speCZT Vision 120, GE, Waukesha, USA), closed to each other, thanks to the short extension of the MRI magnet fringe field. The tool consists of a curved catheter describing many rigid loops, and fixed on a plastic sheet. During acquisitions, it is placed around the animal, in an isolated imaging cell, and filled with a solution containing iodine, copper sulfate and radioisotope. Multimodality imaging is achieved sequentially by moving the cell from one system to the other, in about 20s. Acquisitions on phantom demonstrate the resolution accuracy of the coregistration process. Whole body trimodal SPECT/CT/MR acquisitions on live mice were coregistrated as well. A simple, cheap tool, easy to fill, could efficiently help for rigid coregistration of preclinical images, acquired on separate imaging apparatus.

Respiratory gated [18F]FDG PET/CT for target volume delineation in stereotactic radiation treatment of liver metastases

The use of 4D-[(18)F]fluorodeoxyglucose (FDG) PET/CT in combination with respiratory gated magnet resonance imaging (MRI) in target volume definition for stereotactic radiation of liver metastases was investigated. A total of 18patients received respiration gated FDG-PET/CT and MRI. Data were fused using a rigid co-registration algorithm. The quality of the co-registration was rated on a scale from 1 (excellent) to 5 (poor) for co-registration of MRI with gated PET and ungated PET. Gross tumor volume (GTV) was delineated in CT (GTV (CT)), MRI (GTV(MRI)), and PET (GTV(PET)). MRI- and PET-based GTVs were defined by three observers each. Interobserver variability was calculated for all patients as well as for subgroups with and without previous treatment of liver metastases. All GTVs were compared for all patients and separately for patients with previous local therapy. In addition, a semiautomatic segmentation algorithm was applied on the PET images. Co-registration between MR and PET images was rated with 3.3 in average when non-gated PET was used and improved significantly (p < 0.01) to 2.1 using gated PET. The average GTV(CT) was 51.5ml, GTV(MRI) 51.8ml, and the average GTV(PET) 48.1ml. Volumes delineated in MRI were 9.9% larger compared to those delineated in CT. Volumes delineated in PET were 13.8% larger than in MRI. The differences between the GTVs were more pronounced in patients with previous treatment. The GTVs defined in MRI showed an interobserver variability of 47.9% (84.1% with previous treatment and 26.2% without previous treatment). The PET-defined GTVs showed an interobserver variability of 21% regardless of previous treatment. Semiautomatic segmentation did not provide satisfying results. FDG-PET can distinguish vital tumor tissue and scar tissue, and therefore alters the GTV especially in patients with previous local treatment. In addition, it reduces the interobserver variability significantly compared to MRI. However, respiratory gated PET is necessary for good co-registration of PET and MRI.

Validation of co-registration of clinical lung ventilation and perfusion SPECT

Ventilation (V) and perfusion (Q) image data from 20 patients undergoing a routine clinical SPECT V/Q study were aligned via rigid coregistration using intrinsic image intensity values with the software package 'Qonsub'. Accuracy of the coregistration was quantified by an independent technique that used Tc-99m filled fiducial markers which had been adhered to the patient's skin prior to imaging. These were visible on both the V and Q scans, but were removed from the images for the coregistration step. The level of inter-marker displacement between scans was monitored to ensure it did not invalidate the assessment of coregistration accuracy. Once coregistered, results showed that for 65% of patients in the survey co-registration accuracy was better than 1 pixel (3.8 mm), 30% were co-registered with an accuracy of between 1 and 2 pixels and 5% were co-registered with an accuracy of between 2 and 3 pixels.

Analysis of Prostate Bed Motion Using Daily Cone-Beam Computed Tomography During Postprostatectomy Radiotherapy

To report on the interfraction total positioning error of the postoperative prostate bed and to quantify its components (bony misalignment [BM] and prostate bed motion [PBM]) using daily kilovoltage cone-beam computed tomography (CBCT). The role of an adaptive radiotherapy schedule (ART) was investigated. A total of 547 daily CBCT images from 15 consecutive patients who had been treated with prostate bed radiotherapy were retrospectively analyzed. The positioning error was measured by rigid co-registration of the daily CBCT with pretreatment CT planning scan. The total positioning error was quantified by co-registration of the CBCT with the CT planning scan to match the anterior rectal wall. Automatic bony pelvis co-registration was performed to separate BM and PBM. The ART was determined by the average total positioning error from the first 5 CBCT images. The systematic error for the total positioning error in the left-right, superoinferior, and anteroposterior direction was 2.69, 2.00, and 2.65 mm with a random error of 1.99, 1.49, and 2.25 mm, resulting in a planning target volume margin of 8, 6, and 8 mm, respectively. ART reduced the margin by 54%, 44%, and 40%, respectively. Systematic errors in the left-right, superoinferior, and anteroposterior direction for BM was 2.66, 1.83, and 2.60 mm and for PBM was 0.44, 0.92, and 2.50 mm with a random error of 1.88, 1.24, and 1.77 mm for BM and 0.99, 1.38, and 2.32 mm for PBM, respectively. Without treatment verifications, 6-8-mm planning target volume margins are required because of PBM and BM. The anteroposterior PBM was significant. An ART protocol can reduce these planning target volume margins.

A Hybrid Breath Hold and Continued Respiration-Triggered Technique for Time-Resolved 3D MRI Perfusion Studies in Lung Cancer

Assessment of lung cancer perfusion is impaired by respiratory motion. Imaging times for contrast agent wash-out studies often exceed breath hold capabilities, and respiration triggering reduces temporal resolution. Temporally resolved volume acquisition of entire tumors is required to assess heterogeneity. Therefore, we developed and evaluated an MR measurement technique that exceeds a single breath hold, and provides a variable temporal resolution during acquisition while suspending breath-dependent motion. 20 patients with suspected lung cancer were subjected to perfusion studies using a spoiled 3D gradient echo sequence after bolus injection of 0.07 mmol/kg body weight of Gd-DTPA. 10 acquisitions in expiratory breath hold were followed by 50 navigator-triggered acquisitions under free breathing. Post-processing allowed for co-registration of the 3D data sets. An ROI-based visualization of the signal-time curves was performed. In all cases motion-suspended, time-resolved volume data sets (40 x 33 x 10 cm(3), voxel size: 2.1 x 2.1 x 5.0 mm(3)) were generated with a variable, initially high temporal resolution (2.25 sec) that was synchronized with the breath pattern and covered up to 8 1/2 min. In 7 / 20 cases a remaining offset could be reduced by rigid co-registration. The tumors showed fast wash-in, followed by rapid signal decay (8 / 20) or a plateau. The feasibility of a perfusion study with hybrid breath hold and navigator-triggered time-resolved 3D MRI which combines high initial temporal resolution during breath hold with a long wash-out period under free breathing was demonstrated.

Systematic analysis of biological and physical limitations of proton beam range verification with offline PET/CT scans

The clinical use of offline positron emission tomography/computed tomography (PET/CT) scans for proton range verification is currently under investigation at the Massachusetts General Hospital (MGH). Validation is achieved by comparing measured activity distributions, acquired in patients after receiving one fraction of proton irradiation, with corresponding Monte Carlo (MC) simulated distributions. Deviations between measured and simulated activity distributions can either reflect errors during the treatment chain from planning to delivery or they can be caused by various inherent challenges of the offline PET/CT verification method. We performed a systematic analysis to assess the impact of the following aspects on the feasibility and accuracy of the offline PET/CT method: (1) biological washout processes, (2) patient motion, (3) Hounsfield unit (HU) based tissue classification for the simulation of the activity distributions and (4) tumor site specific aspects. It was found that the spatial reproducibility of the measured activity distributions is within 1 mm. However, the feasibility of range verification is restricted to a limited amount of positions and tumor sites. Washout effects introduce discrepancies between the measured and simulated ranges of about 4 mm at positions where the proton beam stops in soft tissue. Motion causes spatial deviations of up to 3 cm between measured and simulated activity distributions in abdominopelvic tumor cases. In these later cases, the MC simulated activity distributions were found to be limited to about 35% accuracy in absolute values and about 2 mm in spatial accuracy depending on the correlativity of HU into the physical and biological parameters of the irradiated tissue. Besides, for further specific tumor locations, the beam arrangement, the limited accuracy of rigid co-registration and organ movements can prevent the success of PET/CT range verification. All the addressed factors explain why the proton beam range can only be verified within an accuracy of 1–2 mm in low-perfused bony structures of head and neck patients for which an accurate co-registration of predominant bony anatomy is possible, as shown previously. However, most of the limitations of the current approach are conquerable. By implementing technological and methodological improvements like the use of in-room PET scanners, PET measurements could soon be used to provide proton range verification in clinical routine.

Evaluation of a multimodality image (CT, MRI and PET) coregistration procedure on phantom and head and neck cancer patients: accuracy, reproducibility and consistency

Background and purpose In radiotherapy planning of head and neck tumors, coregistration of various anatomical (e.g. CT and MRI) and functional (e.g. PET) images is a promising way to improve the delineation of the target volumes. In this paper, we report data on accuracy, reproducibility and consistency of an interactive coregistration procedure in a specifically designed phantom and in a group of patients with primary head and neck tumors. Patients and methods A phantom and a group of four patients with pharyngo-laryngeal tumors were imaged by CT scan (taken as the reference image), MRI (T1- and T2-weighed sequences) and PET (transmission and FDG emission). Sets of images were coregistered using an interactive rigid coregistration method based on interactive surface segmentation. Translational and rotational displacements relative to the reference CT scan were measured and expressed in terms of accuracy, reproducibility (inter- and intra-observer variation) and consistency (between T1- and T2-weighed MRI). Results Coregistration accuracy was in the range of 0.8–6.2 mm and 1.2–4.6 mm for the phantom and the patients, respectively. Accuracy was slightly worse in the z direction, and was significantly correlated with the spatial resolution of the imaging modalities, at least for the phantom. Inter- and intra-observer variations were very small and always far below the residual variance. Consistency was perfect except in the y direction. Conclusion Providing adequate set-up is chosen, accurate coregistration of CT, MR and FDG-PET images can be obtained in the head and neck area. Coregistration was consistent and highly reproducible among observers.

Automatic measurement of changes in brain volume on consecutive 3D MR images by segmentation propagation

This article presents a technique to automatically measure changes in the volume of a structure of interest in successive 3D magnetic resonance (MR) images and its application in the study of the brain and lateral cerebral ventricles. The only manual step is a segmentation of the structure of interest in the first image. The analysis comprises, first, precise rigid co-registration of the time series of images; second, computation of residual deformations between pairs of images; third, automatic quantification of the volume change, obtained by propagation of the segmentation of the structure of interest through the series of MR images. This approach has been applied to monitor changes in the volume of the brain and lateral cerebral ventricles in a healthy subject and a patient with primary progressive aphasia (PPA). Results are consistent with those obtained by application of the boundary shift integral (BSI) and by stereology in the same subjects.