Mathias Walke

The influence of different signal-to-background ratios on spatial resolution and F18-FDG-PET quantification using point spread function and time-of-flight reconstruction

BackgroundF18-fluorodeoxyglucose positron-emission tomography (FDG-PET) reconstruction algorithms can have substantial influence on quantitative image data used, e.g., for therapy planning or monitoring in oncology. We analyzed radial activity concentration profiles of differently reconstructed FDG-PET images to determine the influence of varying signal-to-background ratios (SBRs) on the respective spatial resolution, activity concentration distribution, and quantification (standardized uptake value [SUV], metabolic tumor volume [MTV]).MethodsMeasurements were performed on a Siemens Biograph mCT 64 using a cylindrical phantom containing four spheres (diameter, 30 to 70 mm) filled with F18-FDG applying three SBRs (SBR1, 16:1; SBR2, 6:1; SBR3, 2:1). Images were reconstructed employing six algorithms (filtered backprojection [FBP], FBP + time-of-flight analysis [FBP + TOF], 3D-ordered subset expectation maximization [3D-OSEM], 3D-OSEM + TOF, point spread function [PSF], PSF + TOF). Spatial resolution was determined by fitting the convolution of the object geometry with a Gaussian point spread function to radial activity concentration profiles. MTV delineation was performed using fixed thresholds and semiautomatic background-adapted thresholding (ROVER, ABX, Radeberg, Germany).ResultsThe pairwise Wilcoxon test revealed significantly higher spatial resolutions for PSF + TOF (up to 4.0 mm) compared to PSF, FBP, FBP + TOF, 3D-OSEM, and 3D-OSEM + TOF at all SBRs (each P < 0.05) with the highest differences for SBR1 decreasing to the lowest for SBR3. Edge elevations in radial activity profiles (Gibbs artifacts) were highest for PSF and PSF + TOF declining with decreasing SBR (PSF + TOF largest sphere; SBR1, 6.3%; SBR3, 2.7%). These artifacts induce substantial SUVmax overestimation compared to the reference SUV for PSF algorithms at SBR1 and SBR2 leading to substantial MTV underestimation in threshold-based segmentation. In contrast, both PSF algorithms provided the lowest deviation of SUVmean from reference SUV at SBR1 and SBR2.ConclusionsAt high contrast, the PSF algorithms provided the highest spatial resolution and lowest SUVmean deviation from the reference SUV. In contrast, both algorithms showed the highest deviations in SUVmax and threshold-based MTV definition. At low contrast, all investigated reconstruction algorithms performed approximately equally. The use of PSF algorithms for quantitative PET data, e.g., for target volume definition or in serial PET studies, should be performed with caution - especially if comparing SUV of lesions with high and low contrasts.

Photogrammetric measurement of patients in radiotherapy

Abstract The correct positioning of the patient is an important demand in radiotherapy. Optical measurements seem appropriate, but special requirements of speed and accuracy must be met. A new photogrammetric system that captures patient surface data in real-time is introduced. It allows reproducible patient set-up, and monitors the patients position during irradiation even when the patient is moving. It consists of two cameras and one projector and is based on the photogrammetric evaluation of stereo image pairs by projecting white light fringes onto the patients body. The raw data of the 3D measurement is a sequence of point clouds. It can be evaluated together with other data modes common in radiotherapy for diagnosis and treatment planning. The system can be used as an additional verification tool for the correct positioning of the patient, and completely new applications emerge.

A multimodal image fusion framework applied in radiotherapy

The monitoring of patients position during treatment in radiotherapy requires suitable real-time vizualization tools which provide a maximum of information. Often, only Electronic Portal Images (EPIs), which are of poor quality, exist for the dynamical verification of position deviations, whereas static image material of higher quality is available from diagnostics and treatment planning. A framework for the fusion of static and dynamic multimodal image data is proposed, which is based on the several image sources existing in radiotherapy.

Accuracy of applicator tip reconstruction in MRI-guided interstitial 192Ir-high-dose-rate brachytherapy of liver tumors.

BACKGROUND AND PURPOSE To evaluate the reconstruction accuracy of brachytherapy (BT) applicators tips in vitro and in vivo in MRI-guided (192)Ir-high-dose-rate (HDR)-BT of inoperable liver tumors. MATERIALS AND METHODS Reconstruction accuracy of plastic BT applicators, visualized by nitinol inserts, was assessed in MRI phantom measurements and in MRI (192)Ir-HDR-BT treatment planning datasets of 45 patients employing CT co-registration and vector decomposition. Conspicuity, short-term dislocation, and reconstruction errors were assessed in the clinical data. The clinical effect of applicator reconstruction accuracy was determined in follow-up MRI data. RESULTS Applicator reconstruction accuracy was 1.6±0.5 mm in the phantom measurements. In the clinical MRI datasets applicator conspicuity was rated good/optimal in ⩾72% of cases. 16/129 applicators showed not time dependent deviation in between MRI/CT acquisition (p>0.1). Reconstruction accuracy was 5.5±2.8 mm, and the average image co-registration error was 3.1±0.9 mm. Vector decomposition revealed no preferred direction of reconstruction errors. In the follow-up data deviation of planned dose distribution and irradiation effect was 6.9±3.3 mm matching the mean co-registration error (6.5±2.5 mm; p>0.1). CONCLUSION Applicator reconstruction accuracy in vitro conforms to AAPM TG 56 standard. Nitinol-inserts are feasible for applicator visualization and yield good conspicuity in MRI treatment planning data. No preferred direction of reconstruction errors were found in vivo.

Assessment of Iterative Closest Point Registration Accuracy for Different Phantom Surfaces Captured by an Optical 3D Sensor in Radiotherapy

An optical 3D sensor provides an additional tool for verification of correct patient settlement on a Tomotherapy treatment machine. The patients position in the actual treatment is compared with the intended position defined in treatment planning. A commercially available optical 3D sensor measures parts of the body surface and estimates the deviation from the desired position without markers. The registration precision of the in-built algorithm and of selected ICP (iterative closest point) algorithms is investigated on surface data of specially designed phantoms captured by the optical 3D sensor for predefined shifts of the treatment table. A rigid body transform is compared with the actual displacement to check registration reliability for predefined limits. The curvature type of investigated phantom bodies has a strong influence on registration result which is more critical for surfaces of low curvature. We investigated the registration accuracy of the optical 3D sensor for the chosen phantoms and compared the results with selected unconstrained ICP algorithms. Safe registration within the clinical limits is only possible for uniquely shaped surface regions, but error metrics based on surface normals improve translational registration. Large registration errors clearly hint at setup deviations, whereas small values do not guarantee correct positioning.

Optical Surface Sensing and Multimodal Image Fusion for Position Verification in Radiotherapy

A method for the analysis and visualization of patient motion in radiotherapy is proposed. Motion parameters are derived from two image modes: data from an optical sensor and of an electronic portal imaging device which are synchronized. Fusion of both image modes increases robustness of estimation of the real patient motion because both image modes provide different motion parameters with sufficient accuracy. Spatial transformation parameters yield by registration of portal images with digitally reconstructed radiographs (DRR) and of surface data obtained from optical sensor with those obtained from CT.

Multimodale Bilddatenfusion zur verbesserten Patientenlagerung und -überwachung in der Strahlentherapie

Es wird ein Verfahren zur 3D-Bewegungsanalyse von Patienten in der Strahlentherapie vorgestellt. Die Erfassung der Bewegung erfolgt mittels zeitlich synchron aufgenommener Daten eines optischen 3D-Sensors und elektronischen Portalbildern. Da jeweils nur bestimmte Bewegungsparameter in einer Modalitat mit hinreichend hoher Genauigkeit bestimmt werden konnen, ermoglicht eine Fusion der Daten beider Sensoren eine Erhohung der Robustheit der Schatzung der tatsachlichen Patientenbewegungen. Die raumlichen Transformationsparameter ergeben sich dabei aus der Registrierung von Portalbildern mit Digital-Rekonstruierten Rontgenbildern (DRR) und gemessenen 3D-Korperoberflachen mit CT-Daten.

Bilder aus Diagnostik und Behandlungsplanung in der Strahlentherapie zur Auswertung von Online-daten mit Neuronalen Netzen

Die Technik der elektronischen Portalbilder konnte sich zu einem wichtigen Werkzeug bei der Verifizierung der korrekten Patientenlagerung in der Strahlentherapie entwickeln. Im Gegensatz zu klassischen Verfahren der Bildverbesserung wird bei der vorgestellten Methode a-priori-Wissen aus vorab gewonnenen Bildern benutzt, um die Aussagekraft der Bildinformation wesentlich zu erhohen. Zusatzlich werden Daten eines optischen Oberflachensensors fur die Vermessung der tatsachlichen Patientenlagerung einbezogen und um eine eindeutige Registrierung zwischen den Bildmodi sowie die Verfolgung von Patientenbewegungen zu ermoglichen.