[Show abstract][Hide abstract] ABSTRACT: Optimization of Image-based Dosimetry in Y90 Radioembolization: a Monte Carlo approach using the GATE simulation toolkit.
K. Mountris1, A. Autret3, P. Papadimitroulas1, G. Loudos², D. Visvikis3, G. Nikiforidis1
1 Department of Medical Physics, School of Medicine, University of Patras, Rion, GR 265 04
² Department of Medical Instruments Technology, Technological Educational institute of Athens,
Ag. Spyridonos Street, Egaleo GR 122 10, Athens, Greece
3 LaTIM, UMR 1101 INSERM, CHRU Brest, Brest, France
Purpose: The ability of Monte Carlo simulation for PET acquisition of Y90 radioembolization and the correlation of image-based dosimetric results derived from the simulated data with respective results derived from the MC simulation of the treatment planning surrogates Tc99m-MAA (macroaggregated albumin) and Ga68-MAA were investigated.
Methods: We used the XCAT phantom, using GATE MC platform, since this combination can provide ground truth data. The tiny branch of Y90 internal pair production was modeled (32 ppm) for a 30 minutes PET acquisition. We assumed homogeneous distribution of a 2.5GBq activity in the liver tissue and the tumor with a TNR 3:1 to compare our results with the partition model. The Tc99m-MAA SPECT acquisition simulated assuming homogeneous distribution of 200MBq Tc99m-MAA for 10 min with 64 frames (20s/frame). For pretreatment dosimetry optimization we simulated a Ga68-MAA PET acquisition for the same activity and acquisition time as in the Tc99m-MAA protocol. Comparison was applied between the dosimetric results of Y90-surrogates and the Y90 protocol.
We generated 3D dose maps using a kernel-convolution method on the reconstructed images with an onsite generated Y90 kernel. Furthermore the total doses of tumor and normal liver parenchyma were calculated for all the scenarios creating 1D histograms.
Results: For the Y90 scenario the liver dose was 62.94Gy, 15.5% higher than the dose calculated with the partition model (54.50Gy) and the tumor dose was 147.28Gy, 9.9% lower than the partition model (163.50Gy).
For the Ga68 scenario the liver dose was 65.62Gy and the tumor dose 143.44Gy. For the Tc99m scenario the liver and tumor doses were 70.98Gy and 149.60Gy respectively. In all cases the tumor dose was underestimated relating to the partition model while the normal liver dose was overestimated. The difference between Ga68 derived doses over Y90 was +4.29% for the liver dose and -2.64% for the tumor dose while for the Tc99m acquisition the difference was +12.8% and +1.6% respectively.
Conclusion: The Ga68-MAA showed significantly lower dosimetric differences with Y90 than Tc99m-MAA in liver dose calculation. As liver dose estimation is a key limiting factor in the treatment planning, the better correlation of Ga68-MAA can improve the therapeutic results of the treatment. Further investigation in the usage of Ga68-MAA in radioembolization must be done.
keywords: yttrium-90, radioembolization, image-based dosimetry, Tc99m-MAA, Ga68-MAA
8th European Conference on Medical Physics, Athens; 09/2014
[Show abstract][Hide abstract] ABSTRACT: Cardiac imaging suffers from both respiratory and cardiac motion. One of the proposed solutions involves double gated acquisitions. Although such an approach may lead to both respiratory and cardiac motion compensation there are issues associated with (a) the combination of data from cardiac and respiratory motion bins, and (b) poor statistical quality images as a result of using only part of the acquired data. The main objective of this work was to evaluate different schemes of combining binned data in order to identify the best strategy to reconstruct motion free cardiac images from dual gated positron emission tomography (PET) acquisitions.
[Show abstract][Hide abstract] ABSTRACT: The goal of this study was to compare visual assessment of intratumor (18)F-FDG PET uptake distribution with a textural-features (TF) automated quantification and to establish their respective prognostic value in non-small cell lung cancer (NSCLC).
Journal of nuclear medicine : official publication, Society of Nuclear Medicine. 06/2014;
[Show abstract][Hide abstract] ABSTRACT: In this paper, the authors' review the applicability of the open-source GATE Monte Carlo simulation platform based on the GEANT4 toolkit for radiation therapy and dosimetry applications. The many applications of GATE for state-of-the-art radiotherapy simulations are described including external beam radiotherapy, brachytherapy, intraoperative radiotherapy, hadrontherapy, molecular radiotherapy, and in vivo dose monitoring. Investigations that have been performed using GEANT4 only are also mentioned to illustrate the potential of GATE. The very practical feature of GATE making it easy to model both a treatment and an imaging acquisition within the same frameworkis emphasized. The computational times associated with several applications are provided to illustrate the practical feasibility of the simulations using current computing facilities.
[Show abstract][Hide abstract] ABSTRACT: Thirty patients with proven colorectal cancer prospectively underwent integrated 18F-FDG PET/DCE-CT to assess the metabolic-flow phenotype. Both CT blood flow parametric maps and PET images were analyzed. Correlations between PET heterogeneity and perfusion CT were assessed by Spearman's rank correlation analysis.
PLoS ONE 01/2014; 9(6):e99567. · 3.53 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Background and objective: For many cancer patients who develop vertebral metastases in the natural course of the disease, percutaneous kyphoplasty is a valuable treatment option. By using intraoperative radiotherapy (IORT) with the INTRABEAM™ system during kyphoplasty™, metastases may be sterilized and vertebra stabilized together. This solution results in the reduction of patient discomfort and also restores mobility, which improves the patient quality of life. The aim of our study is to perform a dosimetric evaluation of a Kypho-IORT treatment using the needle applicator to control and validate the doses actually received for such treatment.
Method: A simulation of a clinical treatment is performed on an anthropomorphic phantom (RANDO) and dose measurements are collected from thermoluminescent detectors placed on the skin and inside the phantom around the X-ray source. Finally dose calculations are made on the GATE Monte Carlo (MC) platform by integrating computed tomography (CT) images of the phantom with the applicator in place. The validation was performed by comparing simulations and experimental measurements on the phantom.
Result: The simulation results show a good fit with the experimental measurements. The average relative differences between experimental measurements and calculated dose rates was lower than 1.5% (Min: 0.2%, Max: 7.5%) and a maximum uncertainty of 0.3% in GATE.
Conclusions: This model which has been previously validated in breast cancer can be now considered to be validated for vertebral metastases. The next step will be the validation of the described approach for use in patient dosimetry which should facilitate accounting for the impact of local tissue heterogeneities.
Translational Cancer research. 01/2014; 3(1):83-87.
[Show abstract][Hide abstract] ABSTRACT: PET/CT imaging could improve delineation of rectal carcinoma gross tumor volume (GTV) and reduce interobserver variability. The objective of this work was to compare various functional volume delineation algorithms. We enrolled 31 consecutive patients with locally advanced rectal carcinoma. The FDG PET/CT and the high dose CT (CTRT) were performed in the radiation treatment position. For each patient, the anatomical GTVRT was delineated based on the CTRT and compared to six different functional/metabolic GTVPET derived from two automatic segmentation approaches (FLAB and a gradient-based method); a relative threshold (45% of the SUVmax) and an absolute threshold (SUV > 2.5), using two different commercially available software (Philips EBW4 and Segami OASIS). The spatial sizes and shapes of all volumes were compared using the conformity index (CI). All the delineated metabolic tumor volumes (MTVs) were significantly different. The MTVs were as follows (mean ± SD): GTVRT (40.6 ± 31.28ml); FLAB (21.36± 16.34 ml); the gradient-based method (18.97± 16.83ml); OASIS 45% (15.89 ± 12.68 ml); Philips 45% (14.52 ± 10.91 ml); OASIS 2.5 (41.6 2 ± 33.26 ml); Philips 2.5 (40 ± 31.27 ml). CI between these various volumes ranged from 0.40 to 0.90. The mean CI between the different MTVs and the GTVCT was < 0.4. Finally, the DICOM transfer of MTVs led to additional volume variations. In conclusion, we observed large and statistically significant variations in tumor volume delineation according to the segmentation algorithms and the software products. The manipulation of PET/CT images and MTVs, such as the DICOM transfer to the Radiation Oncology Department, induced additional volume variations.
Journal of applied clinical medical physics / American College of Medical Physics. 01/2014; 15(5):4696.
[Show abstract][Hide abstract] ABSTRACT: Radiotherapy of head and neck cancer induces changes in tumour cell proliferation during treatment, which can be depicted by the PET tracer (18)F-fluorothymidine (FLT). In this study, three advanced semiautomatic PET segmentation methods for delineation of the proliferative tumour volume (PV) before and during (chemo)radiotherapy were compared and related to clinical outcome.
The study group comprised 46 patients with 48 squamous cell carcinomas of the head and neck, treated with accelerated (chemo)radiotherapy, who underwent FLT PET/CT prior to treatment and in the 2nd and 4th week of therapy. Primary gross tumour volumes were visually delineated on CT images (GTVCT). PVs were visually determined on all PET scans (PVVIS). The following semiautomatic segmentation methods were applied to sequential PET scans: background-subtracted relative-threshold level (PVRTL), a gradient-based method using the watershed transform algorithm and hierarchical clustering analysis (PVW&C), and a fuzzy locally adaptive Bayesian algorithm (PVFLAB).
Pretreatment PVVIS correlated best with PVFLAB and GTVCT. Correlations with PVRTL and PVW&C were weaker although statistically significant. During treatment, the PVVIS, PVW&C and PVFLAB significant decreased over time with the steepest decline over time for PVFLAB. Among these advanced segmentation methods, PVFLAB was the most robust in segmenting volumes in the third scan (67 % of tumours as compared to 40 % for PVW&C and 27 % for PVRTL). A decrease in PVFLAB above the median between the pretreatment scan and the scan obtained in the 4th week was associated with better disease-free survival (4 years 90 % versus 53 %).
In patients with head and neck cancer, FLAB proved to be the best performing method for segmentation of the PV on repeat FLT PET/CT scans during (chemo)radiotherapy. This may potentially facilitate radiation dose adaptation to changing PV.
European Journal of Nuclear Medicine 12/2013; · 4.53 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Aim: PET/CT is widely used for the detection of lymph node involvement in head and neck squamous cell carcinoma (HNSCC). However, PET qualitative and quantitative capabilities are hindered by partial volume effects (PVE). Therefore, a retrospective study on 32 patients (57 lymph nodes) was carried out to evaluate the potential improvement of PVE correction (PVEC) in FDG PET/CT imaging for the diagnosis of HNSCC. Histopathological analysis of lymph nodes following neck dissection was used as the gold standard. Methods: A previously proposed deconvolution based PVEC approach was used to derive improved quantitative accuracy PET images, while the anatomical lymph node volumes were determined on the CT images. Different parameters including SUVmax and SUVmean were derived from both original and PVEC PET images for each patient. Results: Histopathology confirmed that SUVmax and SUVmean after PVEC allows a statistically significant differentiation of malignant and benign lymph nodes (p<0.05). The sensitivity of SUVmax and SUVmean was 64% and 57% respectively with or without PVEC. PVEC increased specificity from 71% to 76% for SUVmax and 57% to 66% for SUVmean. Corresponding accuracy increased from 66% to 71% for SUVmax and from 59% to 66% for SUVmean. However, the most accurate differentiation between benign and malignant nodes was obtained while using the magnitude of SUVmax increase after PVEC with a corresponding sensitivity, specificity and accuracy of 77%, 82% and 80% respectively. Conclusion: Our work shows that the use of partial volume effects correction allows a more accurate nodal staging using FDG PET imaging in HNSCC.
The quarterly journal of nuclear medicine and molecular imaging: official publication of the Italian Association of Nuclear Medicine (AIMN) [and] the International Association of Radiopharmacology (IAR), [and] Section of the Society of... 12/2013; · 1.92 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: 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/.
Medical Physics 11/2013; 40(11):112506. · 2.91 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Monte Carlo simulation (MCS) plays a key role in medical applications, especially for emission tomography and radiotherapy. However MCS is also associated with long calculation times that prevent its use in routine clinical practice. Recently, graphics processing units (GPU) became in many domains a low cost alternative for the acquisition of high computational power. The objective of this work was to develop an efficient framework for the implementation of MCS on GPU architectures. Geant4 was chosen as the MCS engine given the large variety of physics processes available for targeting different medical imaging and radiotherapy applications. In addition, Geant4 is the MCS engine behind GATE which is actually the most popular medical applications' simulation platform. We propose the definition of a global strategy and associated structures for such a GPU based simulation implementation. Different photon and electron physics effects are resolved on the fly directly on GPU without any approximations with respect to Geant4. Validations have shown equivalence in the underlying photon and electron physics processes between the Geant4 and the GPU codes with a speedup factor of 80-90. More clinically realistic simulations in emission and transmission imaging led to acceleration factors of 400-800 respectively compared to corresponding GATE simulations.
Physics in Medicine and Biology 07/2013; 58(16):5593-5611. · 2.70 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Intratumour uptake heterogeneity in PET quantified in terms of textural features for response to therapy has been investigated in several studies, including assessment of their robustness for reconstruction and physiological reproducibility. However, there has been no thorough assessment of the potential impact of preprocessing steps on the resulting quantification and its predictive value. The goal of this work was to assess the robustness of PET heterogeneity in textural features for delineation of functional volumes and partial volume correction (PVC).
This retrospective analysis included 50 patients with oesophageal cancer. PVC of each PET image was performed. Tumour volumes were determined using fixed and adaptive thresholding, and the fuzzy locally adaptive Bayesian algorithm, and heterogeneity was quantified using local and regional textural features. Differences in the absolute values of the image-derived parameters considered were assessed using Bland-Altman analysis. The impact on their predictive value for the identification of patient nonresponders was assessed by comparing areas under the receiver operating characteristic curves.
Heterogeneity parameters were more dependent on delineation than on PVC. The parameters most sensitive to delineation and PVC were regional ones (intensity variability and size zone variability), whereas local parameters such as entropy and homogeneity were the most robust. Despite the large differences in absolute values obtained from different delineation methods or after PVC, these differences did not necessarily translate into a significant impact on their predictive value.
Parameters such as entropy, homogeneity, dissimilarity (for local heterogeneity characterization) and zone percentage (for regional characterization) should be preferred. This selection is based on a demonstrated high differentiation power in terms of predicting response, as well as a significant robustness with respect to the delineation method used and the partial volume effects.
European Journal of Nuclear Medicine 07/2013; · 4.53 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Over the past century technology has played a decisive role in defining, driving, and reinventing procedures, devices, and pharmaceuticals in healthcare. Cloud computing has been introduced only recently but is already one of the major topics of discussion in research and clinical settings. The provision of extensive, easily accessible, and reconfigurable resources such as virtual systems, platforms, and applications with low service cost has caught the attention of many researchers and clinicians. Healthcare researchers are moving their efforts to the cloud, because they need adequate resources to process, store, exchange, and use large quantities of medical data. This Vision 20∕20 paper addresses major questions related to the applicability of advanced cloud computing in medical imaging. The paper also considers security and ethical issues that accompany cloud computing.
Medical Physics 07/2013; 40(7):070901. · 2.91 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Denoising of Positron Emission Tomography (PET) images is a challenging task due to the inherent low signal-to-noise ratio (SNR) of the acquired data. A pre-processing denoising step may facilitate and improve the results of further steps such as segmentation, quantification or textural features characterization. Different recent denoising techniques have been introduced and most state-of-the-art methods are based on filtering in the wavelet domain. However, the wavelet transform suffers from some limitations due to its non-optimal processing of edge discontinuities. More recently, a new multi scale geometric approach has been proposed, namely the curvelet transform. It extends the wavelet transform to account for directional properties in the image. In order to address the issue of resolution loss associated with standard denoising, we considered a strategy combining the complementary wavelet and curvelet transforms. We compared different figures of merit (e.g. SNR increase, noise decrease in homogeneous regions, resolution loss, and intensity bias) on simulated and clinical datasets with the proposed combined approach and the wavelet-only and curvelet-only filtering techniques. The three methods led to an increase of the SNR. Regarding the quantitative accuracy however, the wavelet and curvelet only denoising approaches led to larger biases in the intensity and the contrast than the proposed combined algorithm. This approach could become an alternative solution to filters currently used after image reconstruction in clinical systems such as the Gaussian filter.
Medical image analysis 06/2013; 17(8):877-891. · 3.09 Impact Factor