Is Dose Deformation-Invariance Hypothesis Verified in Prostate IGRT?

PURPOSE: To assess dose uncertainties resulting from the dose deformation-invariance hypothesis in prostate cone beam computed tomography (CT)-based image guided radiation therapy (IGRT), namely to evaluate whether rigidly propagated planned dose distribution enables good estimation of fraction dose distributions. METHODS AND MATERIALS: Twenty patients underwent a CT scan for planning intensity modulated radiation therapy-IGRT delivering 80 Gy to the prostate, followed by weekly CT scans. Two methods were used to obtain the dose distributions on the weekly CT scans: (1) recalculating the dose using the original treatment plan; and (2) rigidly propagating the planned dose distribution. The cumulative doses were then estimated in the organs at risk for each dose distribution by deformable image registration. The differences between recalculated and propagated doses were finally calculated for the fraction and the cumulative dose distributions, by use of per-voxel and dose-volume histogram (DVH) metrics. RESULTS: For the fraction dose, the mean per-voxel absolute dose difference was <1 Gy for 98% and 95% of the fractions for the rectum and bladder, respectively. The maximum dose difference within 1 voxel reached, however, 7.4 Gy in the bladder and 8.0 Gy in the rectum. The mean dose differences were correlated with gas volume for the rectum and patient external contour variations for the bladder. The mean absolute differences for the considered volume receiving greater than or equal to dose x (Vx) of the DVH were between 0.37% and 0.70% for the rectum and between 0.53% and 1.22% for the bladder. For the cumulative dose, the mean differences in the DVH were between 0.23% and 1.11% for the rectum and between 0.55% and 1.66% for the bladder. The largest dose difference was 6.86%, for bladder V80Gy. The mean dose differences were <1.1 Gy for the rectum and <1 Gy for the bladder. CONCLUSIONS: The deformation-invariance hypothesis was corroborated for the organs at risk in prostate IGRT except in cases of a large disappearance or appearance of rectal gas for the rectum and large external contour variations for the bladder.

Comparative performance investigation of DICOM C-STORE and DICOM HTTP-based requests.

Increasingly, physicians have to access clinical images distributed over multiple healthcare organizations. To this end, two DICOM protocols may be used: a regular DICOM C-STORE transaction or an HTTP-based DICOM request such as WADO or STOW. A major problem of the DICOM C-STORE transaction is that it is inefficient to transfer DICOM data sets that consist of thousands of DICOM objects (such as functional MRI data set) because of the large number of negotiations involved in the transfer. We compare the performances of C-STORE transactions with the STOW HTTP-based protocol, and show that the STOW protocol can divide the transfer time by about 50 when compared to a DICOM C-STORE transaction for studies that consists of thousands of DICOM objects.

Investigation of realistic PET simulations incorporating tumor patient's specificity using anthropomorphic models: creation of an oncology database.

PURPOSE: The GATE Monte Carlo simulation toolkit is used for the implementation of realistic PET simulations incorporating tumor heterogeneous activity distributions. The reconstructed patient images include noise from the acquisition process, imaging system's performance restrictions and have limited spatial resolution. For those reasons, the measured intensity cannot be simply introduced in GATE simulations, to reproduce clinical data. Investigation of the heterogeneity distribution within tumors applying partial volume correction (PVC) algorithms was assessed. The purpose of the present study was to create a simulated oncology database based on clinical data with realistic intratumor uptake heterogeneity properties. METHODS: PET/CT data of seven oncology patients were used in order to create a realistic tumor database investigating the heterogeneity activity distribution of the simulated tumors. The anthropomorphic models (NURBS based cardiac torso and Zubal phantoms) were adapted to the CT data of each patient, and the activity distribution was extracted from the respective PET data. The patient-specific models were simulated with the Monte Carlo Geant4 application for tomography emission (GATE) in three different levels for each case: (a) using homogeneous activity within the tumor, (b) using heterogeneous activity distribution in every voxel within the tumor as it was extracted from the PET image, and (c) using heterogeneous activity distribution corresponding to the clinical image following PVC. The three different types of simulated data in each case were reconstructed with two iterations and filtered with a 3D Gaussian postfilter, in order to simulate the intratumor heterogeneous uptake. Heterogeneity in all generated images was quantified using textural feature derived parameters in 3D according to the ground truth of the simulation, and compared to clinical measurements. Finally, profiles were plotted in central slices of the tumors, across lines with heterogeneous activity distribution for visual assessment. RESULTS: The accuracy of the simulated database was assessed against the original clinical images. The PVC simulated images matched the clinical ones best. Local, regional, and global features extracted from the PVC simulated images were closest to the clinical measurements, with the exception of the size zone variability and the mean intensity values, where heterogeneous tumors showed better reproducibility. The profiles on PVC simulated tumors after postfiltering seemed to represent the more realistic heterogeneous regions with respect to the clinical reference. CONCLUSIONS: In this study, the authors investigated the input activity map heterogeneity in the GATE simulations of tumors with heterogeneous activity distribution. The most realistic heterogeneous tumors were obtained by inserting PVC activity distributions from the clinical image into the activity map of the simulation. Partial volume effect (PVE) can play a crucial role in the quantification of heterogeneity within tumors and have an important impact on applications such as patient follow-up during treatment and assessment of tumor response to therapy. The development of such a database incorporating patient anatomical and functional variability can be used to evaluate new image processing or analysis algorithms, while providing control of the ground truth, which is not available when dealing with clinical datasets. The database includes all images used and generated in this study, as well as the sinograms and the attenuation phantoms for further investigation. It is freely available to the interested reader of the journal at http://www.med.upatras.gr/oncobase/.

Impact of the accuracy of automatic tumour functional volume delineation on radiotherapy treatment planning.

Over the past few years several automatic and semi-automatic PET segmentation methods for target volume definition in radiotherapy have been proposed. The objective of this study is to compare different methods in terms of dosimetry. For such a comparison, a gold standard is needed. For this purpose, realistic GATE-simulated PET images were used. Three lung cases and three H&N cases were designed with various shapes, contrasts and heterogeneities. Four different segmentation approaches were compared: fixed and adaptive thresholds, a fuzzy C-mean and the fuzzy locally adaptive Bayesian method. For each of these target volumes, an IMRT treatment plan was defined. The different algorithms and resulting plans were compared in terms of segmentation errors and ground-truth volume coverage using different metrics (V(95), D(95), homogeneity index and conformity index). The major differences between the threshold-based methods and automatic methods occurred in the most heterogeneous cases. Within the two groups, the major differences occurred for low contrast cases. For homogeneous cases, equivalent ground-truth volume coverage was observed for all methods but for more heterogeneous cases, significantly lower coverage was observed for threshold-based methods. Our study demonstrates that significant dosimetry errors can be avoided by using more advanced image-segmentation methods.