Purpose- The main aim of this study was to develop the pharmacokinetic model for the colorectal cancer’s complex 166Ho-DOTA-Bevacizumab in normal and tumoral rats to analyze of behavior as a new composition for diagnosing and treatment. The use of compartmental analysis allows a mathematical separation of tissues and organs to determine the concentration of activity in each fraction of interest. Biodistribution studies are expensive and difficult to carry out in humans, but such data can be obtained easily in rodents and rat.

Methods- We have developed a physiologically based pharmacokinetic model for scaling up activity concentration in each organ versus time. The mathematical model uses physiological parameters including organ volumes, blood flow rates, and vascular permeability. The compartments (organs) are connected anatomically. This allows the use of scale-up techniques to predict the new complex distribution in humans in each organ.

Results- The concentration of the new complex was measured in various organs at the different times. The behavior of the complex (166Ho-DOTA-Bevacizumab) was modeled as a function of time in various organs. These data was diagrammed as a time function in the separated graph for each organ between 2-96 hours after injection.

Conclusion- The variation of integrated uptake in organs is described with summationof 6-9 exponential terms and it approximated experimental data with 1-2 %precision. As shown in the diagram the mathematical model and biodistribution data in an experiment has a good joint and coincidence and it is a good sign to save time and cost in the next other researches.

Purpose- Acute lymphoblastic leukemia (ALL) is the most common form of
pediatric cancer of white blood cells which is categorized into three types of L1, L2, and L3. It is usually detected through screening of blood and bone marrow smears by pathologists. Since manual detection is time-consuming and boring, computer-based systems are preferred for convenient detection. The rigorous similarity between morphology of ALL types and that of normal, reactive and atypical lymphocytes, makes the automatic recognition a challenging problem. In this paper, we tried to improve the sensitivity of detection based on principle component analysis (PCA).
Methods- After segmenting cell nucleus using fuzzy c-means clustering algorithm, several geometric and statistical features are extracted. Then the feature space dimensionality is reduced based on (PCA). The first 8 components of the feature space are applied to support vector machine (SVM) classifier. Then the cancerous and lymphocyte cells are classified into their subtypes.
Results- For evaluating the proposed method, we used an expert pathologist’s
classification as a reference. Classification was evaluated by three parameters:
sensitivity, specificity and accuracy. A comparison with our previous work showed that using dimensionality reduced feature space based on PCA, instead of using individually selected features, improved the average sensitivity and precision of classification more than 10%.
Conclusion- The results show that proposed algorithm performs better than our
previous work. Its acceptable performance for the diagnosis of ALL and its subtypes as well as other lymphocyte types makes it an assistant diagnostic tool for pathologists.

Purpose- In this study, we investigated the impact of PSF reconstruction 
acquisition time would compromise the accuracy of quantitative measures using PSF algorithm.
Methods- Both phantom and patient images were evaluated. A complete set of experiments were performed using an image quality phantom containing 6 inserts with 4:1 lesion to background ratio. Whole-body FDG PET/CT scan of 17 patients with different primary cancers were used in this study. All hantom
images reconstructed with 3 iterations, 24 subsets for 180, 150, 120, 90, and 60 s acquisition time per bed position. Post-smoothing filters with FWHM of 5 and 4 mm applied to HD and HD+PSF images respectively. Clinical PET images reconstructed with 3 iterations and 18 subsets. Quantitative analysis performed by CV%, SNR, RC, and SUVmax.
Results- By incorporating PSF algorithm, CV decreased 11.1% and 17.01% 0.92% for both phantom and clinical images. In addition, better edge detection achieved specially for smaller focal points. It was shown by reconstructing images with PSF algorithm, acquisition time can be reduced 33.3% with no significant changes of image quality and quantitative accuracy (P-value<0.05).
Conclusion- It can be concluded that using PSF algorithm improves the image quality, lesion detection, and quantitative accuracy. Besides, by incorporating this algorithm, the acquisition time can be reduced with no loss of image quality and quantitative accuracy where it is possible to have higher patient throughout with the same image quality.

Purpose- The aim of this study was to determine optimal reconstruction parameters in relation to the image quality and quantitative accuracy for advanced reconstruction algorithms by phantom study.

Methods- A house-made image quality phantom, including 6 cylindrical inserts,
was filled with an 18F-FDG solution with a 4:1 radioactivity ratio compared to the background. All emission data was acquired in 3D list-mode. The PET data reconstructed with TOF only and TOF+PSF algorithms. The reconstructed images were post-filtered with Gaussian filters with varying FWHM (0 to 10 mm with 0.5 mm increment). All images were reconstructed with different product of iterations and subsets (It×SS) ranging from 3 to 144. Optimal image reconstruction parameters were determined by calculating quantitative parameters including noise, signal to noise ratio (SNR), and recovery coefficient (RC).
Results- Our results showed that Gaussian filtering with FWHM greater than 5
mm for TOF and greater than 3.5 mm for TOF+PSF algorithms led to an acceptable clinical noise level (<10%). By considering signal to noise ratio of the 10 mm insert (SNR10 mm) and quantitative accuracy of tracer concentration, optimum FWHM of Gaussian filter was 5-6.5 mm for TOF only reconstruction and 3.5-5 mm for TOF+PSF reconstruction. In terms of It×SS, SNR10 mm was maximized for 28 to 48 It×SS. In addition, there was no significant enhancement in RC for It×SS greater than 48.
Conclusion- Image quality and quantitative accuracy are strongly influenced by
reconstruction parameters. Our findings indicate that the optimization of the reconstruction parameters is necessary to obtain the best performance. Optimal FWHM range was 5-6.5 mm for TOF only reconstruction, and 3.5-5 mm for TOF+PSF reconstruction. Additionally, due to intensifying signal of the focal point by incorporating TOF information, faster SNR convergence can be achieved. Hence smaller It×SS can be applied while using TOF algorithm for image reconstruction.

Purpose- The setup verification is one of the important issues in radiation therapy. In this study, an experienced physicist evaluated the setup of the patients during treatments where many unexpected errors were observed.

Methods- The physicist spent few hours a week in the treatment room and recorded any error that happened in the treatment setup from the physicist’s point of view. In some errors, a follow up dosimetry was performed to evaluate the effect of a specific error.

Results- The errors were divided into a few categories. Out of 1000 patients in a 3 years period, various minor and major errors were observed for 115 patients. Most of the errors were in treatment field’s shape and size. There were also few mistakes made by technicians due to the lack of conceptual understanding particularly when the electron shield was placed too far from the skin. Results of film dosimetry revealed that this can cause a severe underdose of the tumor and an overdose of the shielded area.

Conclusion- Many of the recorded setup errors in this study were related to the
setup protocols for a particular center. However, there are many mistakes such
as mistakes of the technicians and physicists that can be prevented with proper
trainings.

Purpose- In order to develop new bone imaging agent based on bisphosphonate
moiety, an alendronate based complex was designed and prepared in this study.
Methods- A DTPA-conjugated bis-alendronate analog (DTPA-bis-ALN) 3, was
prepared for possible bone imaging after radiolabeling with 111In. Radiolabeled
DTPA-bis-ALN complex was prepared starting radionuclide in chloride form and
DTPA-bis-ALN in 30-90 min at 50-60°C in acetate buffer followed by solid phase
purification on C18 Sep-Pak cartridge. RTLC was used for radiochemical purity
determination followed by log P determination, stability studies, hydroxyl apatite tests and biodistribution studies in normal rats and imaging.
Results- Specific activity 1.1-1.3 TBq/mmmol was obtained for 111In-complex. The log Ps was calculated 0.48 for the complex consistent with water soluble complexes followed by stability test. The biodistribution of the labeled compound in normalrats demonstrated activity uptake in kidneys.
Conclusions- The anionic property of poly-dentate complex led to renal excretion instead of bone accumulation. These data showed that the developed complexes are not suitable agents for bone imaging as expected.

Purpose- Some practical and theoretical efforts have been made to investigate the effects of designing parameters on the performance of anger camera. In this study, the effects of light guide thickness on the accuracy of position estimation, linearity, and uniformity response of a typical gamma camera has assessed using Geant4 Monte Carlo (MC) simulation toolkit.

Methods- Three MC simulations are done using T/R values of 0, 0.5, and 1,
where T is the thickness of light guide and R is the effective radius of a hexagonal photomultiplier tube. For each T/R value, the accuracy of position estimation was investigated by the analysis of the relations between the true and estimated positions of scintillation events. Also, the differential non-uniformity and average non-linearity maps have been used to assess the effect of light guide thickness on the linearity and uniformity responses, respectively.

Results- The results showed that the accuracy of position estimation depends on the depth of scintillation causing erroneous estimated positions for T/R values of 0 and 0.5. For the case T=R, that dependency was eliminated due to the enough broadening of optical photon cones and the position estimation errors were in the range of intrinsic spatial resolution of camera.

Conclusions- Lack of a proper thickness of the light guide on the gamma camera can ruin the accuracy of position estimation on the gamma camera. In addition, both linearity and uniformity responses have a strong dependency on the thickness of light guide.

Purpose- In this report, technical operation of “RoboLens” as an assistant robot for laparoscopic surgery has been illustrated.

Methods- First, the RoboLens® mechanical mechanism and configuration of its
linkage, joints and actuators are illustrated. Then, the software and user interfaces of the robot are introduced. Next, its operation from start to end of a surgery has been evaluated. Also, a technical test for its trajectory tracking in a spherical coordinate has been performed using a standard optical tracking system. Finally, an overall report from more than 1000 human clinical trials in 2 hospitals is investigated.

Results- The robot was prepared for the operation in less than 30 Sec and started all the commanded movements including up, down, right, left, zoom-in or zoom-out of the screen in real time manner with less than 50 ms delay. Also, the trajectory tracking of the robot end effector on a spherical surface showed less than 1 mm error in the worst case.

Conclusion- Results of the evaluation of the RoboLens indicated that it has the
appropriate maneuvering capability as a robotic assistant for laparoscopic surgery in real human clinical trials