Localization Of Fiducial Markers Research Articles

Reattachable fiducial skin marker for automatic multimodality registration

PurposeFusing image information has become increasingly important for optimal diagnosis and treatment of the patient. Despite intensive research towards markerless registration approaches, fiducial marker-based methods remain the default choice for a wide range of applications in clinical practice. However, as especially non-invasive markers cannot be positioned reproducibly in the same pose on the patient, pre-interventional imaging has to be performed immediately before the intervention for fiducial marker-based registrations.MethodsWe propose a new non-invasive, reattachable fiducial skin marker concept for multi-modal registration approaches including the use of electromagnetic or optical tracking technologies. We furthermore describe a robust, automatic fiducial marker localization algorithm for computed tomography (CT) and magnetic resonance imaging (MRI) images. Localization of the new fiducial marker has been assessed for different marker configurations using both CT and MRI. Furthermore, we applied the marker in an abdominal phantom study. For this, we attached the marker at three poses to the phantom, registered ten segmented targets of the phantom’s CT image to live ultrasound images and determined the target registration error (TRE) for each target and each marker pose.ResultsReattachment of the marker was possible with a mean precision of 0.02 mm ± 0.01 mm. Our algorithm successfully localized the marker automatically in all (n=201) evaluated CT/MRI images. Depending on the marker pose, the mean (n=10) TRE of the abdominal phantom study ranged from 1.51 ± 0.75 mm to 4.65 ± 1.22 mm.ConclusionsThe non-invasive, reattachable skin marker concept allows reproducible positioning of the marker and automatic localization in different imaging modalities. The low TREs indicate the potential applicability of the marker concept for clinical interventions, such as the puncture of abdominal lesions, where current image-based registration approaches still lack robustness and existing marker-based methods are often impractical.

Feasibility study of fiducial marker localization using microwave radar.

We explore the potential use of radar technology for fiducial marker tracking for monitoring of respiratory tumor motion during radiotherapy. Historically microwave radar technology has been widely deployed in various military and civil aviation applications to provide detection, position, and tracking of single or multiples objects from far away and even through barriers. Recently, due to many advantages of the microwave technology, it has been successfully demonstrated to detect breast tumor, and to monitor vital signs in real time such as breathing signals or heart rates. We demonstrate a proof-of-concept for radar-based fiducial marker tracking through the synthetic human tissue phantom. We performed a series of experiments with the vector network analyzer (VNA) and wideband directional horn antenna. We considered the frequency range from 2.0 to 6.0GHz, with a maximum power of 3dBm. A horn antenna, transmitting and receiving radar pulses, was connected to the vector network analyzer to probe a gold fiducial marker through a customized synthetic human tissue phantom, consisting of 1-mm thickness of skin, 5-mm fat, and 25-mm muscle layers. A 1.2 × 10-mm gold fiducial marker was exploited as a motion surrogate, which was placed behind the phantom and statically positioned with an increment of 12.7mm to simulate different marker displacements. The returned signals from the marker were acquired and analyzed to evaluate the localization accuracy as a function of the marker position. The fiducial marker was successfully localized at various measurement positions through a simplified phantom study. The averaged localization accuracy across measurements was 3.5 ± 1.3mm, with a minimum error of 1.9mm at the closest measurement location and a maximum error of 4.9mm at the largest measurement location. We demonstrated that the 2-6GHz radar can penetrate through the attenuating tissues and localize a fiducial marker. This successful feasibility study establishes a foundation for further investigation of radar technology as a non-ionizing tumor localization device for radiotherapy.

Feasibility of using a single MRI acquisition for fiducial marker localization and synthetic CT generation towards MRI-only prostate radiation therapy treatment planning

Purpose. To investigate the feasibility of using a single MRI acquisition for fiducial marker identification and synthetic CT (sCT) generation towards MRI-only treatment planning for prostate external beam radiation therapy (EBRT). Methods. Seven prostate cancer patients undergoing EBRT, each with three implanted gold fiducial markers, participated in this study. In addition to the planning CT scan, all patients were scanned on a 3 T MR scanner with a 3D double-echo gradient echo (GRE) sequence. Quantitative susceptibility mapping (QSM) was performed for marker localization. QSM-derived marker positions were compared to those from CT. The bulk density assignment technique for sCT generation was adopted. The magnitude GRE images were segmented into muscle, bone, fat, and air using a combination of unsupervised intensity-based classification of soft tissue and convolutional neural networks (CNN) for bone segmentation. Results. All implanted markers were visualized and accurately identified (average error: 0.7 ± 0.5 mm). QSM generated distinctive contrast for hemorrhage, calcifications, and gold fiducial markers. The estimated susceptibility/HU values on QSM/CT for gold and calcifications were 31.5 ± 2.9 ppm/1220 ± 100 HU and 14.6 ± 0.9 ppm/440 ± 100 HU, respectively. The intensity-based soft tissue classification resulted in an average Dice score of 0.97 ± 0.02; bone segmentation using CNN resulted in an average Dice score of 0.93 ± 0.03. Conclusion. This work indicates the feasibility of simultaneous fiducial marker identification and sCT generation using a single MRI acquisition. Future works includes evaluation of the proposed method in a large cohort of patients with optimized acquisition parameters as well as dosimetric evaluations.

Automated fiducial marker detection and localization in volumetric computed tomography images: a three-step hybrid approach with deep learning.

.Purpose: Automating fiducial detection and localization in the patient’s pre-operative images can lead to better registration accuracy, reduced human errors, and shorter intervention time. Most current approaches are optimized for a single marker type, mainly spherical adhesive markers. A fully automated algorithm is proposed and evaluated for screw and spherical titanium fiducials, typically used in high-accurate frameless surgical navigation.Approach: The algorithm builds on previous approaches with morphological functions and pose estimation algorithms. A 3D convolutional neural network (CNN) is proposed for the fiducial classification task and evaluated for both traditional closed-set and emerging open-set classifiers. A proposed digital ground-truth experiment, with cone-beam computed tomography (CBCT) imaging software, is performed to determine the localization accuracy of the algorithm. The localized fiducial positions in the CBCT images by the presented algorithm were compared to the actual known positions in the virtual phantom models. The difference represents the fiducial localization error (FLE).Results: A total of 241 screws, 151 spherical fiducials, and 1550 other structures are identified with the best true positive rate 95.9% for screw and 99.3% for spherical fiducials at 8.7% and 3.4% false positive rate, respectively. The best achieved FLE mean and its standard deviation for a screw and spherical marker are 58 (14) and , respectively.Conclusions: Accurate marker detection and localization were achieved, with spherical fiducials being superior to screws. Large marker volume and smaller voxel size yield significantly smaller FLEs. Attenuating noise by mesh smoothing has a minor effect on FLE. Future work will focus on expanding the CNN for image segmentation.

A generative adversarial network-based (GAN-based) architecture for automatic fiducial marker detection in prostate MRI-only radiotherapy simulation images.

Clinical sites utilizing magnetic resonance imaging (MRI)-only simulation for prostate radiotherapy planning typically use fiducial markers for pretreatment patient positioning and alignment. Fiducial markers appear as small signal voids in MRI images and are often difficult to discern. Existing clinical methods for fiducial marker localization require multiple MRI sequences and/or manual interaction and specialized expertise. In this study, we develop a robust method for automatic fiducial marker detection in prostate MRI simulation images and quantify the pretreatment alignment accuracy using automatically detected fiducial markers in MRI. In this study, a deep learning-based algorithm was used to convert MRI images into labeled fiducial marker volumes. Seventy-seven prostate cancer patients who received marker implantation prior to MRI and CT simulation imaging were selected for this study. Multiple-Echo T1 -VIBE MRI images were acquired, and images were stratified (at the patient level) based on the presence of intraprostatic calcifications. Ground truth (GT) contours were defined by an expert on MRI using CT images. Training was done using the pix2pix generative adversarial network (GAN) image-to-image translation package and model testing was done using fivefold cross validation. For performance comparison, an experienced medical dosimetrist and a medical physicist each manually contoured fiducial markers in MRI images. The percent of correct detections and F1 classification scores are reported for markers detected using the automatic detection algorithm and human observers. The patient positioning errors were quantified by calculating the target registration errors (TREs) from fiducial marker driven rigid registration between MRI and CBCT images. Target registration errors were quantified for fiducial marker contours defined on MRI by the automatic detection algorithm and the two expert human observers. Ninety-six percent of implanted fiducial markers were correctly identified using the automatic detection algorithm. Two expert raters correctly identified 97% and 96% of fiducial markers, respectively. The F1 classification score was 0.68, 0.75, and 0.72 for the automatic detection algorithm and two human raters, respectively. The main source of false discoveries was intraprostatic calcifications. The mean TRE differences between alignments from automatic detection algorithm and human detected markers and GT were <1mm. We have developed a deep learning-based approach to automatically detect fiducial markers in MRI-only simulation images in a clinically representative patient cohort. The automatic detection algorithm-predicted markers can allow for patient setup with similar accuracy to independent human observers.

Correcting for background fields and multipole field errors in the localization of the magnetic axis in quadrupole magnets

The fiducial marker localization with respect to the magnetic axis of the magnet elements is a crucial step in the qualification of the magnets for particle accelerators. Background fields, such as the Earth’s magnetic field and fringe fields from electrical sources may degrade the accuracy of this axis localization. In this paper, we discuss stretched-wire measurements, in static and vibrating operation modes, for the correction of stray fields in the quadrupole axis localization to an accuracy of 0.3 μm. Moreover, we present an analytical model to correct the magnetic axis position error due to higher-order multipole field errors in the magnet. This correction is particularly important for the static stretched-wire measurement because the wire movement must be large enough to obtain a sufficient signal-to-noise ratio.

Directional scatter imaging for the stereoscopic tracking of fiducial markers in a single kV exposure.

To demonstrate, via Monte Carlo simulation, that an image obtained from the patient-generated scattered radiation forced to impinge on the detector from a known direction by means of parallel-focused grids, can be used to complement the information conveyed by the primary image, such that accurate stereoscopic three-dimensional localization of fiducial markers can be achieved in a single kV x-ray exposure. A voxelized Zubal phantom was used to model the process of fiducial marker localization. The markers were represented as made of gold and cylindrical in shape with dimensions of 5mm in length and 1mm in diameter. Three such markers were placed in the Zubal phantom at the prostate level. Two gantry-mounted image acquisition geometries were modeled: a single kV imaging system and a dual kV-MV imaging system. The detector was modeled as a 30cm×40cm Gd2 O2 S screen with a thickness of 0.2cm and a resolution of 768×1024 pixels. The PENELOPE Monte Carlo code was used to calculate the absorbed dose in this detector imparted by the transmitted primary and directional scatter radiation. A grayscale conversion was then applied to obtain an image from which the positions of the markers were determined. Two parallel-focused grid geometries were modeled, one based on the standard lead-carbon fiber grids and a proposed modification using tungsten as the shielding material. Absorbed dose in the patient model was also calculated. It is shown that the combination of primary and directional scatter images provides the means for an accurate stereoscopic fiducial marker 3D localization in a single x-ray exposure, provided the antiscatter grids are made thick enough to allow radiation traveling only in a particular direction to reach the detector. For the proposed tungsten grid and the x-ray spectrum used in this work, grid ratios of 20 and thickness of 0.2cm, provide the necessary shielding while for the standard lead grids, a ratio of at least 166 and a thickness of 2cm are needed to obtain discernible directional scatter images. We have shown that it is in principle possible to determine the 3D position of fiducial markers in a single exposure by making use of the radiation scattered by the patient to form an image that complements the information obtained with the primary beam. The method here proposed requires minimal modification of existing clinical hardware.

Photogrammetry-Based Head Digitization for Rapid and Accurate Localization of EEG Electrodes and MEG Fiducial Markers Using a Single Digital SLR Camera.

The performance of EEG source reconstruction has benefited from the increasing use of advanced head modeling techniques that take advantage of MRI together with the precise positions of the recording electrodes. The prevailing technique for registering EEG electrode coordinates involves electromagnetic digitization. However, the procedure adds several minutes to experiment preparation and typical digitizers may not be accurate enough for optimal source reconstruction performance (Dalal et al., 2014). Here, we present a rapid, accurate, and cost-effective alternative method to register EEG electrode positions, using a single digital SLR camera, photogrammetry software, and computer vision techniques implemented in our open-source toolbox, janus3D. Our approach uses photogrammetry to construct 3D models from multiple photographs of the participant's head wearing the EEG electrode cap. Electrodes are detected automatically or semi-automatically using a template. The rigid facial features from these photo-based models are then surface-matched to MRI-based head reconstructions to facilitate coregistration to MRI space. This method yields a final electrode coregistration error of 0.8 mm, while a standard technique using an electromagnetic digitizer yielded an error of 6.1 mm. The technique furthermore reduces preparation time, and could be extended to a multi-camera array, which would make the procedure virtually instantaneous. In addition to EEG, the technique could likewise capture the position of the fiducial markers used in magnetoencephalography systems to register head position.

Fiducial-based registration with a touchable region model.

Image-guided surgery requires registration between an image coordinate system and an intraoperative coordinate system that is typically referenced to a tracking device. In fiducial-based registration methods, this is achieved by localizing points (fiducials) in each coordinate system. Often, both localizations are performed manually, first by picking a fiducial point in the image and then by using a hand-held tracked pointer to physically touch the corresponding fiducial on the patient. These manual procedures introduce localization error that is user-dependent and can significantly decrease registration accuracy. Thus, there is a need for a registration method that is tolerant of imprecise fiducial localization in the preoperative and intraoperative phases. We propose the iterative closest touchable point (ICTP) registration framework, which uses model-based localization and a touchable region model. This method consists of three stages: (1) fiducial marker localization in image space, using a fiducial marker model, (2) initial registration with paired-point registration, and (3) fine registration based on the iterative closest point method. We perform phantom experiments with a fiducial marker design that is commonly used in neurosurgery. The results demonstrate that ICTP can provide accuracy improvements compared to the standard paired-point registration method that is widely used for surgical navigation and surgical robot systems, especially in cases where the surgeon introduces large localization errors. The results demonstrate that the proposed method can reduce the effect of the surgeon's localization performance on the accuracy of registration, thereby producing more consistent and less user-dependent registration outcomes.

Strategy for accurate liver intervention by an optical tracking system.

Image-guided navigation for radiofrequency ablation of liver tumors requires the accurate guidance of needle insertion into a tumor target. The main challenge of image-guided navigation for radiofrequency ablation of liver tumors is the occurrence of liver deformations caused by respiratory motion. This study reports a strategy of real-time automatic registration to track custom fiducial markers glued onto the surface of a patient's abdomen to find the respiratory phase, in which the static preoperative CT is performed. Custom fiducial markers are designed. Real-time automatic registration method consists of the automatic localization of custom fiducial markers in the patient and image spaces. The fiducial registration error is calculated in real time and indicates if the current respiratory phase corresponds to the phase of the static preoperative CT. To demonstrate the feasibility of the proposed strategy, a liver simulator is constructed and two volunteers are involved in the preliminary experiments. An ex-vivo porcine liver model is employed to further verify the strategy for liver intervention. Experimental results demonstrate that real-time automatic registration method is rapid, accurate, and feasible for capturing the respiratory phase from which the static preoperative CT anatomical model is generated by tracking the movement of the skin-adhered custom fiducial markers.

Using dynamic programming to improve fiducial marker localization

Fiducial markers are used in a wide range of medical imaging applications. In radiation therapy, they are often implanted near tumors and used as motion surrogates that are tracked with fluoroscopy. We propose a novel and robust method based on dynamic programming (DP) for retrospectively localizing radiopaque fiducial markers in fluoroscopic images. Our method was compared to template matching (TM) algorithms on 407 data sets from 24 patients. We found that the performance of TM varied dramatically depending on the template used (ranging from 47% to 92% of data sets with a mean error <1 mm). DP by itself requires no template and performed as well as the best TM method, localizing the markers in 91% of the data sets with a mean error <1 mm. Finally, by combining DP and TM, we were able to localize the markers in 99% of the data sets with a mean error <1 mm, regardless of the template used. Our results show that DP can be a powerful tool for analyzing tumor motion, capable of accurately locating fiducial markers in fluoroscopic images regardless of marker type, shape, and size.

Comparison of low‐dose, half‐rotation, cone‐beam CT with electronic portal imaging device for registration of fiducial markers during prostate radiotherapy

This study evaluated the agreement of fiducial marker localization between two modalities — an electronic portal imaging device (EPID) and cone‐beam computed tomography (CBCT) — using a low‐dose, half‐rotation scanning protocol. Twenty‐five prostate cancer patients with implanted fiducial markers were enrolled. Before each daily treatment, EPID and half‐rotation CBCT images were acquired. Translational shifts were computed for each modality and two marker‐matching algorithms, seed‐chamfer and grey‐value, were performed for each set of CBCT images. The localization offsets, and systematic and random errors from both modalities were computed. Localization performances for both modalities were compared using Bland‐Altman limits of agreement (LoA) analysis, Deming regression analysis, and Cohen's kappa inter‐rater analysis. The differences in the systematic and random errors between the modalities were within 0.2 mm in all directions. The LoA analysis revealed a 95% agreement limit of the modalities of 2 to 3.5 mm in any given translational direction. Deming regression analysis demonstrated that constant biases existed in the shifts computed by the modalities in the superior–inferior (SI) direction, but no significant proportional biases were identified in any direction. Cohen's kappa analysis showed good agreement between the modalities in prescribing translational corrections of the couch at 3 and 5 mm action levels. Images obtained from EPID and half‐rotation CBCT showed acceptable agreement for registration of fiducial markers. The seed‐chamfer algorithm for tracking of fiducial markers in CBCT datasets yielded better agreement than the grey‐value matching algorithm with EPID‐based registration.PACS numbers: 87.55.km, 87.55.Qr

MO‐D‐144‐02: Ultrasound Transducer Localization Using the CyberKnife's X‐Ray System

Purpose: 4D ultrasound has become an alternative for image guidance and motion compensation in radiosurgery. Nevertheless, a two‐step localization has to be performed when using ultrasound. In addition to target localization inside the ultrasound volume, the transducer itself has to be localized and the target position has to be transformed into treatment coordinates. Methods: The CyberKnife (Accuray Inc.) features a stereo X‐ray system which is used for patient and fiducial marker localization. Accessing only the raw X‐ray images, we designed a software package for additional marker detection. To measure the physical camera parameters, X‐ray phantoms were designed and a non‐orthogonal stereo camera calibration was performed on 50 calibration X‐ray pairs. Algorithms were developed for three‐dimensional single marker localization and six‐dimensional localization of marker geometries. Different X‐ray marker geometries were designed and attached to the ultrasound transducer. The final system was evaluated and compared to the on‐board localization system using a 6‐axis industrial robot to position different marker geometries at 150 randomly distributed positions over the acquisition volume. Results: Two marker geometries with 20 and 50mm base lengths were localized using the on‐board and newly developed software. The mean translational error for the on‐board localization is 0.202mm, for the new system 0.218mm. The rotational error of the on‐board system could be reduced from 0.212 to 0.053 degrees for the 50mm marker and from 0.272 to 0.076 degrees for the 20mm marker geometry. Conclusion: We have shown that ultrasound transducers can be localized using the CyberKnife x‐ray system. The rotational accuracy of the localization could be increased by a factor of four, which is important for high marker‐to‐ultrasound‐target distances. Furthermore, using the full area of the flat‐panel detectors without pre‐processing steps the tracking volume was increased by 70 percent, which helps detecting patient/fiducials and transducer at the same time.

Comparison of the Accuracy of Cone Beam Computed Tomography and Medical Computed Tomography: Implications for Clinical Diagnostics with Guided Surgery

This study compared the accuracy of cone beam computed tomography (CBCT) and medical-grade CT in the context of evaluating the diagnostic value and accuracy of fiducial marker localization for reference marker-based guided surgery systems. Cadaver mandibles with attached radiopaque gutta-percha markers, as well as glass balls and composite cylinders of known dimensions, were measured manually with a highly accurate digital caliper. The objects were then scanned using a medical-grade CT scanner (Philips Brilliance 64) and five different CBCT scanners (Sirona Galileos, Morita 3D Accuitomo 80, Vatech PaX-Reve3D, 3M Imtech Iluma, and Planmeca ProMax 3D). The data were then imported into commercially available software, and measurements were made of the scanned markers and objects. CT and CBCT measurements were compared to each other and to the caliper measurements. The difference between the CBCT measurements and the caliper measurements was larger than the difference between the CT measurements and the caliper measurements. Measurements of the cadaver mandible and the geometric reference markers were highly accurate with CT. The average absolute errors of the human mandible measurements were 0.03 mm for CT and 0.23 mm for CBCT. The measurement errors of the geometric objects based on CT ranged between 0.00 and 0.12 mm, compared to an error range between 0.00 and 2.17 mm with the CBCT scanners. CT provided the most accurate images in this study, closely followed by one CBCT of the five tested. Although there were differences in the distance measurements of the hard tissue of the human mandible between CT and CBCT, these differences may not be of clinical significance for most diagnostic purposes. The fiducial marker localization error caused by some CBCT scanners may be a problem for guided surgery systems.

SU-E-J-02: Accuracy of Fiducial Marker Localization Using Axial and Helical CT, Cone-Beam CT and KV Imaging.

To determine localization errors of fiducial markers using axial (ACT) and helical CT (HCT), cone beam CT (CBCT) and kV imaging. A thorax phantom containing markers of various sizes (2.5, 5, 10, 20mm) was imaged using ACT, HCT, CBCT and kV imaging. The phantom was imaged with and without motion (15mm amplitude, 15 cycles/min). CT images were reconstructed at 0.625, 1.25, 2.5 and 5mm thickness. Marker location and length were measured using axial and coronal imaging. The measured marker size increased almost linearly with increased slice thickness used in CT reconstruction with ACT for the stationary phantom. In HCT, the marker size varied non-linearly with increase in slice thickness. Motion of the phantom induced further blurring and shifts of the center of the marker with different sizes. The 10 mm marker was elongated up to 13.5 mm and 16.2 mm in the ACT and HCT, respectively. The markers were elongated up to nearly 26 mm using axial and helical scanning modes by phantom motion. The displacement of maker center was more prominent in the HCT with a shift up to 2 mm due to slice thickness for stationary phantom. The marker center was displaced by up to 18 and 22 mm using ACT and HCT, respectively, which was even higher than 15 mm motion amplitude. KV imaging produced the sharpest marker image with the least difference between actual and measured marker sizes. Increase in slice thickness enlarged the apparent marker size and displaced the maker center in ACT and HCT. Motion led to further enlargement in the maker size and displacement of maker center that depended on the motion amplitude. These effects should be considered in CT-based image-guided radiation therapy to ensure accurate tumor localization and patient positioning with implanted markers.

A Frameless Stereotaxic MRI Technique for Macaque Neuroscience Studies

MRI has achieved widespread use for preplanning neuroscience procedures for non-human primate studies. However, orienting imaging studies in stereotaxic space has relied primarily on using a stereotaxic frame or co-registering fiducial markers with the neuroimaging. In this study, we present a simple approach in which the MRI dataset is aligned to the bony landmarks that define the Frankfurt stereotaxic baseline plane, without the need for a stereotaxic frame or additional external fiducials. To facilitate localizing the bony landmarks (infraorbital margin, external bony auditory meatus) on the MRI scans additional imaging landmarks (mid ocular plane, temporomandibular joint) are discussed that provide supplementary and readily visible points of reference. The frameless MRI stereotaxic technique was evaluated in 8 rhesus macaque monkeys using 3D fast gradient echo MRI images with 0.7mm isotropic resolution. 1) Difference in stereotaxic coordinates of fiducial markers was compared between a traditional stereotaxic frame and the frameless MRI technique (n=2). 2) Differences in stereotaxic coordinates for cerebral regions were compared between the frameless MRI technique and MRI obtained with the animal positioned in a MRI-compatible stereotaxic frame (n=4). 3) The frameless MRI technique was further refined to prescribe electrode penetrations within a dural recording chamber in stereotaxic coordinates relative to the electrode microdrive. Differences in MRI coordinates were compared with the electrode microdrive (n=3). Mean localization of fiducial markers differed by 1.6 +/- 0.6 mm between the frameless MRI technique and a traditional stereotaxic frame. Between the frameless technique and an MRI-compatible stereotaxic frame, localization of cerebral anatomy differed by 2.8 +/- 2.2 mm with the primary source of error being a pitch-up rotation in the sagittal plane. This localization difference was reduced to 0.5 +/- 0.6 mm when this rotation was removed. Frameless MRI coordinates for electrode tracts within the dural recording chamber were within 0.5mm +/- 0.2 mm of the electrode microdrive readings. This simple technique provides the ability to accurately plan surgery and neurophysiological recordings in an individual animal, and to define the location of cerebral anatomy and electrode or injection tracts using publically available software, and without the need for dedicated MRI-compatible localization hardware. The reduced need for deep anesthesia (a necessity with traditional stereotaxic frames) makes the technique more amenable for functional MRI studies. Since each animal provides the bony landmarks to define their own stereotaxic space, this technique is readily applicable to other species.

Fiducial registration error as a statistical process control metric in image-guidance radiotherapy with fiducial markers

Portal imaging of implanted fiducial markers has been in use for image-guided radiotherapy (IGRT) of prostate cancer, with ample attention to localization accuracy and organ motion. The geometric uncertainties in point-based rigid-body matching algorithms during localization of prostate fiducial markers can be quantified in terms of a fiducial registration error (FRE). In this study, the aim is to demonstrate how statistical process control (SPC) can be used to intercept potential problems with rigid-body matching algorithms in a retrospective study of FRE for a pilot cohort of 34 patients with fiducial markers. A procedure for estimating control parameters of a SPC control chart (x-chart) from a small number of initial observations (N) of FRE was implemented. The sensitivity analysis of N on the number of ‘in-control’ and ‘out-of-control’ x-charts was also performed. Uncorrected rotational offsets of an individual patient were examined to elucidate possible correlations with the behaviours of an x-chart. Four specific types of qualitative x-chart behaviour have been observed. The number of out-of-control processes was insensitive to the choice of N, provided N ⩾ 5. Residual errors of rigid-body registration were contributed from uncorrected rotational offsets in 5 out of 15 ‘out-of-control’ x-charts. Out-of-control x-charts were also shown to be correlated with potential changes in the IGRT processes, which may compromise the quality of the radiation treatment delivery. The SPC methodology, implemented in the form of individually customized x-charts, has been shown to be a useful tool for monitoring process reliability during fiducial-based IGRT for prostate cancer.

SU-E-T-531: Comparison of Film and CBCT Based Fiducial Marker Localization for Prostate Patients

Purpose: This study is to compare film and cone-beam computed tomography (CBCT) based fiducial marker localization results for intensity modulated radiation therapy (IMRT) of prostate cancer patients. Methods: From 2005 to 2011, 290 prostate cancer patients with 3 intra-prostatic fiducial markers implanted were treated with IMRT boost following 4-field pelvis radiation. Orthogonal films for 241 patients and CBCT images for 49 patients were taken daily before treatment to localize the prostate glands. The estimated couch shifts were recorded and applied. Total of 4072 fractions were analyzed in this study. Results: The overall standard deviations in the left—right (LR), anterior—posterior (AP), and superior- inferior (SI) directions for film and CBCT based localization are 3.90, 4.65, 3.64 mm and 3.94, 4.27, 3.82 mm, respectively. After removing average shifts of each patient, the standard deviations in LR, AP, SI are 3.06, 3.64, 2.63 mm and 3.08, 3.29, 2.48 mm, respectively. The Pearson coefficients of correlation for the frequency distribution of the couch shifts based on films vs. CBCT are 0.99, 0.98, and 0.98 in the LR, AP and SI directions. Conclusions: The CBCT based fiducial marker localization achieves the equivalent accuracy with the orthogonal film based method. The 3–4 mm standard deviations for both film and CBCT groups represent the natural inter-treatment movements of prostates of this patient population. Any new localization methods should be tested against these standard deviations if the same planned target volume (PTV) margins are used.

Optimizing monoscopic kV fluoro acquisition for prostate intrafraction motion evaluation

Monoscopic kV imaging during radiotherapy has been recently implemented for prostate intrafraction motion evaluation. However, the accuracy of 3D localization techniques from monoscopic imaging of prostate and the effect of acquisition parameters on the 3D accuracy have not been studied in detail, with imaging dose remaining a concern. In this paper, we investigate methods to optimize the kV acquisition parameters and imaging protocol to achieve improved 3D localization and 2D image registration accuracy for minimal imaging dose. Prostate motion during radiotherapy was simulated using existing cine-MRI measurements, and was used to investigate the accuracy of various 3D localization techniques and the effect of the kV acquisition protocol. We also investigated the relationship between mAs and the accuracy of the 2D image registration for localization of fiducial markers and we measured imaging dose for a 30 cm diameter phantom to evaluate the necessary dose to achieve acceptable image registration accuracy. Simulations showed that the error in assuming the shortest path to localize the prostate in 3D using monoscopic imaging during a typical IMRT fraction will be less than ∼1.5 mm for 95% of localizations, and will also depend on prostate motion distribution, treatment duration and image acquisition and treatment protocol. Most uncertainty cannot be reduced from higher imaging frequency or acquiring during gantry rotation between beams. Measured maximum surface dose to the cylindrical phantom from monoscopic kV intrafraction acquisitions varied between 0.4 and 5.5 mGy, depending on the acquisition protocol, and was lower than the required dose for CBCT (21.1 mGy). Imaging dose can be lowered by ∼15–40% when mAs is optimized with acquisition angle. Images acquired during MV beam delivery require increased mAs to obtain the same level of registration accuracy, with mAs/registration increasing roughly linearly with field size and dose rate.

Size‐selective colloidal‐gold localization in transmission X‐ray microscopy

Colloidal gold is a useful marker for functional-imaging experiments in transmission X-ray microscopy. Due to the low contrast of gold particles with small diameters it is necessary to develop a powerful algorithm to localize the single gold particles. The presented image-analysis algorithm for identifying colloidal gold particles is based on the combination of a threshold with respect to the local absorption and shape discrimination, realized by fitting a Gaussian profile to the identified regions of interest. The shape discrimination provides the possibility of size-selective identification and localization of single colloidal gold particles down to a diameter of 50 nm. The image-analysis algorithm, therefore, has potential for localization studies of several proteins simultaneously and for localization of fiducial markers in X-ray tomography.