Leventouri, Theodora

With the advent of newly and more reliably designed targeted therapy methods in the past several years, targeted radionuclide therapy has attracted more attentions around the world as a more reliable treatment modality in combination with other well established traditional cancer treatments i.e., external beam radiotherapy and chemotherapy. Alpha particles have a high relative biological effectiveness (RBE) due to their high linear energy transfer (LET). However, to utilize them for therapeutic purposes, precise human body dosimetry calculation is required. The measurement of their uptake and biodistribution can be quite challenging. Also, due to the complex biology of different types of cells, their shapes and functions, there is not a simple and clear understanding of the mechanism of action that fits all. This study aims to estimate and compare the human organ dosimetry of the alpha emitter, 212Pb, from animal data assuming that it is conjugated with three different types of commonly used targeting nanoparticles. For this purpose, the pre-published animal data of three different radionuclide labeled peptide, antibody, and small molecule carriers were selected and converted to human data. Then a compartmental model was designed for each of them to fit the model to the human data with 212Pb, half-life of 10.64 hours. Once each model reached the desired fit, the area under the curves were extracted then the estimated human organ dosimetry calculations took place via the MIRD scheme. The organ dosimetry results for 212Pb + three different carriers are presented in Tables 14, 17, and 20.

In radiotherapy, radiobiological indices tumor control probability (TCP), normal tissue complication probability (NTCP), and equivalent uniform dose (EUD) are computed by analytical models. These models are rarely employed to rank and optimize treatment plans even though radiobiological indices weights more compared to dosimetric indices to reflect treatment goal. The objective of this study is to predict TCP, NTCP and EUDs for lung cancer radiotherapy treatment plans using an artificial neural network (ANN). A total of 100 lung cancer patients’ treatment plans were selected for this study. Normal tissue complication probability (NTCP) of organs at risk (OARs) i.e., esophagus, spinal cord, heart and contralateral lung and tumor control probability (TCP) of treatment target volume (i.e., tumor) were calculated by the equivalent uniform dose (EUD) model. TCP/NTCP pairing with corresponding EUD are used individually as outputs for the neural network. The inputs for ANN are planning target volume (PTV), treatment modality, tumor location, prescribed dose, number of fractions, mean dose to PTV, gender, age, and mean doses to the OARs. The ANN is based on Levenberg-Marquardt algorithm with one hidden layer having 13 inputs and 2 outputs. 70% of the data was used for training, 15% for validation and 15% for testing the ANN. Our ANN model predicted TCP and EUD with correlation coefficient of 0.99 for training, 0.96 for validation, and 0.94 for testing. In NTCP and EUD prediction, averages of correlation coefficients are 0.94 for training, 0.89 for validation and 0.84 for testing. The maximum mean squared error (MSE) for the ANN is 0.025 in predicting the NTCP and EUD of heart. Our results show that an ANN model can be used with high discriminatory power to predict the radiobiological indices for lung cancer treatment plans.

Dosimetric uncertainty in very small (< 2 x 2 cm2) photon fields is notably higher that has created research questions when using small-field virtual cone with variable multileaf collimator (MLC) fields. We evaluate the efficacy of the virtual cone with a fixed MLC field for stereotactic radiosurgery (SRS) of small targets such as trigeminal neuralgia.
We employed a virtual cone technique with a fixed field geometry, called fixed virtual cone (fVC), for small target radiosurgery using the EDGE (Varian Medical Systems, Palo Alto, CA) linac. The fVC is characterized by 0.5 cm x 0.5 cm high-definition MLC field of 10 MV flattening filter-free (FFF) beam defined at 100 cm SAD, while jaws are positioned at 1.5 cm x 1.5 cm. A spherical dose distribution equivalent to 5 mm cone was generated by using 10–14 non-coplanar partial arcs. The dosimetric accuracy of this technique was validated using the SRS MapCHECK (Sun Nuclear Corporation, FL) and the EBT3 (Ashland Inc., NJ) film based on absolute dose measurements. For the quality assurance (QA), 10 treatment plans for trigeminal neuralgia consisting of various arc fields at different collimator angles were analyzed retrospectively using 6 MV and 10 MV FFF beams, including the field-by-field study (n = 130 fields). Dose outputs were compared between the SRS MapCHECK measurements and Eclipse treatment planning system (TPS) with Acuros XB algorithm (version 16.1). In addition, important clinical parameters of 15 cases treated for trigeminal neuralgia were evaluated for the clinical performance. Moreover, dosimetric (field output factors, dose/MU) uncertainties considering a minute (± 0.5–1.0 mm) leaf shift in the field defining fVC, were examined from the TPS, SRS diode (PTW 60018) measurements, and Monte Carlo (MC) simulations.

Matrix Metalloproteinase-13 (MMP-13) belongs to a large family of proteolytic enzymes which are characterized by their ability to degrade the extracellular matrix components. MMP-13 appears to have a critical role in tumor invasion and metastasis. In this study, several fluorogenic probes specific for MMP-13 were designed and characterized. These synthesized probes could be modified with chelators to be applied for imaging MMP-13 in breast cancer and/or multiple myeloma models. The activity and selectivity of MMP-13 and other MMPs against these probes were studied through two approaches. It was found that these probes were cleaved by all MMPs, but MMP-13 showed the highest activity and selectivity towards these peptides.

Simulating Annealing Algorithm (SAA) has been proposed for optimization of the Intensity-Modulated Radiation Therapy (IMRT). Despite the advantage of the SAA to be a global optimizer, the SAA optimization of IMRT is an extensive computational task due to the large scale of the optimization variables, and therefore it requires significant computational resources. In this research we introduce a parallel graphics processing unit (GPU)-based SAA developed in MATLAB platform and compliant with the computational environment for radiotherapy research (CERR) for IMRT treatment planning in order elucidate the performance improvement of the SAA in IMRT optimization. First, we identify the “bottlenecks” of our code, and then we parallelize those on the GPU accordingly. Performance tests were conducted on four different GPU cards in comparison to a serial version of the algorithm executed on a CPU. A gradual increase of the speedup factor as a function of the number of beamlets was found for all four GPUs. A maximum speedup factor of 33.48 was achieved for a prostate case, and 30.51 for a lung cancer case when the K40m card and the maximum number of beams was utilized for each case. At the same time, the two optimized IMRT plans that were created (prostate and lung cancer plans) were met the IMRT optimization goals.

The accuracy of proton dose computation in the treatment planning system relies on the conversion from the Hounsfield units (HU) of each voxel in the patient CT scan to the proton stopping power ratio (SPR). The aim of this study is to investigate the potential improvement in determining proton SPR using single energy computed tomography (SECT) to reduce the uncertainty in predicting the proton range in patients. Factors which may cause CT number variations in the calibration curve have been examined. The HU-SPR calibration curve was determined based on HU of human body tissues using the stoichiometric method. The uncertainties in SPR were divided into two major categories: The inherent uncertainty, and the CT number uncertainty. The root mean square errors of the inherent uncertainties were estimated 0.02%, 0.61% and 0.26% for lung tissues, soft tissues (excluding Thyroid), and bone tissues, respectively. The total uncertainties due to the inherent uncertainty and CT imaging errors were estimated 1.50%. The average calibration curve of two sized phantoms (head and body) were used in the treatment planning system to mitigate beam hardening effect through the attenuating media. A higher accuracy of the SPR prediction using the stoichiometric method is suggested through comparison with the predicted SPRs that derived from the direct calibration approach.

The Computer Tomography (CT) scanned images are very important for the Treatment Planning System (TPS) to provide the electron density of the different types of tissues that the radiation penetrates in the path to the tumor to be treated. This electron density is converted to an attenuation coefficient, which varies with tissue for each structure and even varies by the tissue volume. The purpose of this research is to evaluate the CT numbers, and convert them into relative electron densities. Twenty-five patients’ data and CT numbers were evaluated in the CT scanner and in Eclipse and were converted into relative electron density and compared with each other. The differences between the relative electron density in the Eclipse was found to be from 0 up to 6% between tissue equivalent materials, the final result for all equivalent tissue materials was about 2%. For the patients’ data, the percentage difference of CT number versus electron density was found to be high for high relative electron density organs, namely the final average result for the spine was 8%, less for pelvis, and less for rib while for the other organs it was even less. The very lowest was 0.3% compared with 1% which is acceptable for clinical standards.

The lateral penumbra of a proton pencil beam scanning system (PBS) is of great importance in sparing of organs at risk and normal tissue when treating patients. The purpose of this current work is to measure the lateral penumbra of the Ion Beam Applications (Ion Beam Applications, Louvain‐la‐Neuve, Belgium) ProteusPLUS PBS Proton Therapy System and compare the measurements with the computed results from the RayStation proton treatment planning system. The lateral penumbra (80%-20%) was measured using EBT-3 Gafchromic film in the water tank. The lateral penumbra was studied for various parameters such as range, depth, and air gap. The computed lateral penumbra was found to be higher than the measured lateral penumbra by up to 2.3 mm in the case of depth dependency at 30 cm, and lower by up to 1.18 mm in the case of an air gap of 15 cm.

Reducing the amount of radiation in X-ray computed tomography has been an
active area of research in the recent years. The reduction of radiation has the downside of
degrading the quality of the CT scans by increasing the ratio of the noise. Therefore, some
techniques must be utilized to enhance the quality of images. In this research, we approach
the denoising problem using two class of algorithms and we reduce the noise in CT scans
that have been acquired with 75% less dose to the patient compared to the normal dose
scans.
Initially, we implemented wavelet denoising to successfully reduce the noise in
low-dose X-ray computed tomography (CT) images. The denoising was improved by
finding the optimal threshold value instead of a non-optimal selected value. The mean
structural similarity (MSSIM) index was used as the objective function for the
optimization. The denoising performance of combinations of wavelet families, wavelet
orders, decomposition levels, and thresholding methods were investigated. Results of this study have revealed the best combinations of wavelet orders and decomposition levels for
low dose CT denoising. In addition, a new shrinkage function is proposed that provides
better denoising results compared to the traditional ones without requiring a selected
parameter.
Alternatively, convolutional neural networks were employed using different
architectures to resolve the same denoising problem. This new approach improved
denoising even more in comparison to the wavelet denoising.

MapCheck measurements for 50 retrospective patient’s treatment plans suggested that MapCheck could be effectively employed in routine patient specific quality assurance in M6 Cyberknife with beams delivered at different treatment angles. However, these measurements also suggested that for highly intensity modulated MLC plans, field segments of width < 8 mm should further be analyzed with a modified (-4%) correction factor. Results of MC simulations of the M6 Cyberknife using the EGSnrc program for 2-5 millions of incident particles in BEAMnrc and 10-20 millions in DOSXYZnrc have shown dose uncertainties within 2% for open fields from 7.6 x 7.7 mm2 to 100 x 100 mm2. Energy and corresponding FWHM were optimized by comparing with water phantom measurements at 800 mm SAD resulting to E = 7 MeV and FWHM = 2.2 mm. Good agreement of dose profiles (within 2%) and outputs (within 3%) were found between the MC simulations and water phantom measurements for the open fields.