Marcus Kaar

Automatic patient alignment system using 3D ultrasound

PURPOSE Recent developments in radiation therapy such as intensity modulated radiotherapy (IMRT) or dose painting promise to provide better dose distribution on the tumor. For effective application of these methods the exact positioning of the patient and the localization of the irradiated organ and surrounding structures is crucial. Especially with respect to the treatment of the prostate, ultrasound (US) allows for differentiation between soft tissue and was therefore applied by various repositioning systems, such as BAT or Clarity. The authors built a new system which uses 3D US at both sites, the CT room and the intervention room and applied a 3D/3D US/US registration for automatic repositioning. METHODS In a first step the authors applied image preprocessing methods to prepare the US images for an optimal registration process. For the 3D/3D registration procedure five different metrics were evaluated. To find the image metric which fits best for a particular patient three 3D US images were taken at the CT site and registered to each other. From these results an US registration error was calculated. The most successful image metric was then applied for the US/US registration process. The success of the whole repositioning method was assessed by taking the results of an ExacTrac system as golden standard. RESULTS The US/US registration error was found to be 2.99 ± 1.54 mm with respect to the mutual information metric by Mattes (eleven patients) which revealed to be the most suitable of the assessed metrics. For complete repositioning chain the error amounted to 4.15 ± 1.20 mm (ten patients). CONCLUSIONS The authors developed a system for patient repositioning which works automatically without the necessity of user interaction with an accuracy which seems to be suitable for clinical application.

Factors for conversion between human and automatic read-outs of CDMAM images.

PURPOSE According to the European protocol for the quality control of the physical and technical aspects of mammography screening (EPQCM) image quality of digital mammography devices has to be assessed using human evaluation of the CDMAM contrast-detail phantom. This is accomplished by the determination of threshold thicknesses of gold disks with different diameters (0.08-2 mm) and revealed to be very time consuming. Therefore a software solution based on a nonprewhitening matched filter (NPW) model was developed at the University of Nijmegen. Factors for the conversion from automatic to human readouts have been determined by Young et al. [Proc. SPIE 614206, 1-13 (2006) and Proc. SPIE 6913, 69131C1 (2008)] using a huge amount of data of both human and automatic readouts. These factors depend on the observer groups and are purely phenomenological. The authors present an alternative approach to determine the factors by using the Rose observer model. METHODS Their method uses the Rose theory which gives a relationship between threshold contrast, diameter of the object and number of incident photons. To estimate the conversion factors for the five diameters from 0.2 to 0.5 mm they exposed with five different current-time products which resulted in 25 equations with five unknowns. RESULTS The theoretical conversion factors (in dependence of the diameters) amounted to be 1.61 ± 0.02 (0.2 mm diameter), 1.67 ± 0.02 (0.25 mm), 1.85 ± 0.02 (0.31 mm), 2.09 ± 0.02 (0.4 mm), and 2.28 ± 0.02 (0.5 mm). The corresponding phenomenological factors found in literature are 1.74 (0.2 mm), 1.78 (0.25 mm), 1.83 (0.31 mm), 1.88 (0.4 mm), and 1.93 (0.5 mm). CONCLUSIONS They transferred the problem of determining the factors to a well known observer model which has been examined for many years and is also well established. This method reveals to be reproduceable and produces factors comparable to the phenomenological ones.

Evaluation of three 3D US calibration methods

With the introduction of 3D US image devices the demand for accurate and fast 3D calibration methods arose. We implemented three different calibration methods and compared the calibration results in terms of fiducial registration error (FRE) and target registration error (TRE). The three calibration methods included a multi-points phantom (MP), a feature based model (FM) and a membrane model (MM). With respect to the sphere method a simple point-to-point registration was applied. For the feature based model we employed a phantom consisting of spheres, pyramids and cones. These objects were imaged from different angles and a 3D3D registration was applied for all possible image combinations. The last method was accomplished by imaging a simple membrane which allows for calculation of the calibration matrix. For a first evaluation we computed the FRE for each method. To assess the calibration success on real patient data we used ten 3D3D registrations between images from the prostate. The FRE for the sphere method amounted to 1.40 mm, for the figure method to 1.05 mm and with respect to the membrane method to 1.12 mm. The deviation arising from ten 3D3D patient registration were 3.44 mm (MP), 2.93 mm (FM)and 2.84 mm (MM). The MM revealed to be the most accurate of the evaluated procedure while the MP has shown significant higher errors. The results from FM were close to the one from MM and also significant better than the one with the SM. Between FM and MM no significant difference was to detect.

Automatic patient alignment for prostate radiation applying 3D ultrasound

Latest developments in radiation therapy such as IGRT (image guided radiation therapy) and IMRT (intensity modulated radiation therapy) promise to spare organs at risk by applying better dose distribution on the tumor. For any effective application of these methods the exact positioning of the patient and the localization of the exposured organ is crucially. With respect to the filling of rectum and bladder the prostate can move several millimeters up to centimeters. That implies the need of daily determination and correction of the position of the prostate before irradiation. We build a system which uses 3D US at both sites, the CT room and the intervention room and applied a 3D/3D USUS registration for fully automatic repositioning. In a first step an appropriate preprocessing of the US images is necessary. We implemented an importance image filter process to improve the following registration success. For the 3D3D registration five different object functions were implemented. To find the object function which fits best for the particular patient three 3D US images were taken at the CT site and an US registration error was calculated. The most successful object function was then applied at the treatment site.The US registration error was found to be 3.48 ± 2.32 mm (eight patients) with resect to the Mutual Information metric by Mattes. For complete repositioning the distance error amounted to be 5.0 ± 3.1 mm (four patients).

On the dose sensitivity of a new CDMAM phantom

For the technical quality assurance of breast cancer screening protocols several phantoms have been developed. Their dose sensitivity is a common topic often discussed in literature. The European protocol for the quality control of the physical and technical aspects of mammography screening suggests a contrast-detail phantom like the CDMAM phantom (Artinis Medical Systems, Elst, NL). The CDMAM 3.4 was tested with respect to its dose sensitivity and compared to other phantoms in a recent paper. The CDMAM 4.0 phantom provides other disc diameters and thicknesses adapted more closely to the image quality found in modern mammography systems. This motivates a comparison of the two generations using the same exposure parameters. We varied the time-current (mAs) within a range of clinically used values (40-140 mAs). All evaluations were done using automatic evaluation software provided by Artinis (for CDMAM 4.0) and the National Coordinating Centre for the Physics of Mammography, Guildford UK (CDMAM 3.4). We compared the relative dose sensitivity with respect to the different diameters and also computed the IQFinv parameter, which averages over the diameters as suggested in the manual for the phantom. The IQFinv parameter linearly depends on dose for both phantoms. The CDMAM 4.0 shows a more monotonous dependence on dose, the total variation of the threshold thicknesses as functions of the dose are significantly smaller than with the CDMAM 3.4. As the automatic evaluation shows rather different threshold thicknesses for the two phantoms, conversion factors for human to automatic readout have to be adapted.

An error analysis perspective for patient alignment systems

Purpose This paper analyses the effects of error sources which can be found in patient alignment systems. As an example, an ultrasound (US) repositioning system and its transformation chain are assessed. The findings of this concept can also be applied to any navigation system.Methods and materials In a first step, all error sources were identified and where applicable, corresponding target registration errors were computed. By applying error propagation calculations on these commonly used registration/calibration and tracking errors, we were able to analyse the components of the overall error. Furthermore, we defined a special situation where the whole registration chain reduces to the error caused by the tracking system. Additionally, we used a phantom to evaluate the errors arising from the image-to-image registration procedure, depending on the image metric used. We have also discussed how this analysis can be applied to other positioning systems such as Cone Beam CT–based systems or Brainlab’s ExacTrac.Results The estimates found by our error propagation analysis are in good agreement with the numbers found in the phantom study but significantly smaller than results from patient evaluations. We probably underestimated human influences such as the US scan head positioning by the operator and tissue deformation. Rotational errors of the tracking system can multiply these errors, depending on the relative position of tracker and probe.Conclusions We were able to analyse the components of the overall error of a typical patient positioning system. We consider this to be a contribution to the optimization of the positioning accuracy for computer guidance systems.

Comparison of two navigation system designs for flexible endoscopes using abdominal 3D ultrasound

This paper describes a navigation system for flexible endoscopes equipped with ultrasound scan heads. For navigation and needle biopsy procedures it provides additional oblique slices from preoperative computed tomography (CT) volumes which are displayed with the corresponding endoscopic ultrasound (US) image. In contrast to similar systems an additional abdominal 3D ultrasound image is used to achieve the required registration. Two different approaches are compared: one method is based on direct inter-modal registration between abdominal 3D ultrasound and CT volume. The second method uses another 3D US scan taken preoperatively before the CT scan. Here, the CT is calibrated by means of an optical tracking system and the transformation between CT and the calibrated 3D US can be calculated without image registration. Before intervention, a pre-interventional 3D US is registered intra-modal to the preoperative US. This second method invoked to be the more robust and accurate procedure. For experimental studies a phantom has been developed which consists of a plastic tube inside a water tank. For error evaluation small plastic spheres have been fixed around the tube at different distances. First results give an overall error of 3.9 mm for the first method while the overall error for the intramodal method amounted to 3.1 mm.

Ultrasound guidance system for prostate biopsy

We designed a guidance system for prostate biopsy based on PET/MR images and 3D ultrasound (US). With our proposed method common inter-modal MR-US (or CT-US in case of PET/CTs) registration can be replaced by an intra-modal 3D/3D-US/US registration and an optical tracking system (OTS). On the pre-operative site, a PET/MR calibration allows to link both hybrid modalities with an abdominal 3D-US. On the interventional site, another abdominal 3D US is taken to merge the pre-operative images with the real-time 3D-US via 3D/3D-US/US registration. Finally, the images of a tracked trans-rectal US probe can be displayed with the pre-operative images by overlay. For PET/MR image fusion we applied a point-to-point registration between PET and OTS and MR and OTS, respectively. 3D/3D-US/US registration was evaluated for images taken in supine and lateral patient position. To enable table shifts between PET/MR and US image acquisition a table calibration procedure is presented. We found fiducial registration errors of 0.9 mm and 2.8 mm, respectively, with respect to the MR and PET calibration. A target registration error between MR and 3D US amounted to 1.4 mm. The registration error for the 3D/3D-US/US registration was found to be 3.7 mm. Furthermore, we have shown that ultrasound is applicable in an MR environment.

New conversion factors between human and automatic readouts of the CDMAM phantom for CR systems

Mammography screenings demand for profound image quality (IQ) assessment to guarantee their screening success. The European protocol for the quality control of the physical and technical aspects of mammography screening (EPQCM) suggests a contrast detail phantom such as the CDMAM phantom to evaluate IQ. For automatic evaluation a software is provided by the EUREF. As human and automatic readouts differ systematically conversion factors were published by the official reference organisation (EUREF). As we experienced a significant difference for these factors for Computed Radiography (CR) systems we developed an objectifying analysis software which presents the cells including the gold disks randomly in thickness and rotation. This allows to overcome the problem of an inevitable learning effect where observers know the position of the disks in advance. Applying this software, 45 computed radiography (CR) systems were evaluated and the conversion factors between human and automatic readout determined. The resulting conversion factors were compared with the ones resulting from the two methods published by EUREF. We found our conversion factors to be substantially lower than those suggested by EUREF, in particular 1.21 compared to 1.42 (EUREF EU method) and 1.62 (EUREF UK method) for 0.1 mm, and 1.40 compared to 1.73 (EUREF EU) and 1.83 (EUREF UK) for 0.25 mm disc diameter, respectively. This can result in a dose increase of up to 90% using either of these factors to adjust patient dose in order to fulfill image quality requirements. This suggests the need of an agreement on their proper application and limits the validity of the assessment methods. Therefore, we want to stress the need for clear criteria for CR systems based on appropriate studies.

Conversion factors between human and automatic readouts of CDMAM phantom images of CR mammography systems

In mammography screening, profound assessment of technical image quality is imperative. The European protocol for the quality control of the physical and technical aspects of mammography screening (EPQCM) suggests using an alternate fixed choice contrast-detail phantom-like CDMAM. For the evaluation of technical image quality, human or automated readouts can be used. For automatic evaluation, a software (cdcom) is provided by EUREF. If the automated readout indicates unacceptable image quality, additional human readout may be performed overriding the automated readout. As the latter systematically results in higher image quality ratings, conversion factors between both methods are regularly applied. Since most image quality issues with mammography systems arise within CR systems, an assessment restricted to CR systems with data from the Austrian Reference Center in the mammography screening program has been conducted. Forty-five CR systems were evaluated. Human readouts were performed with a randomisation software to avoid bias due to learning effects. Additional automatic evaluation allowed for the computation of conversion factors between human and automatic readouts. These factors were substantially lower compared to those suggested by EUREF, namely 1.21 compared to 1.62 (EUREF UK method) and 1.42 (EUREF EU method) for 0.1 mm, and 1.40 compared to 1.83 (EUREF UK) and 1.73 (EUREF EU) for 0.25 mm structure size, respectively. Using either of these factors to adjust patient dose in order to comply with image quality requirements results in differences in the dose increase of up to 90%. This necessitates a consensus on their proper application and limits the validity of the assessment methods. Clear criteria for CR systems based on appropriate studies should be promoted.