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Register a new userPreliminary study of metabolic radiotherapy with 188Re via small animal imaging
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Added by
Francesco-Luigi Navarria
Publication date
2005
fields
Physics
and research's language is
English
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188Re is a beta- (Emax = 2.12 MeV) and gamma (155 keV) emitter. Since its chemistry is similar to that of the largely employed tracer, 99mTc, molecules of hyaluronic acid (HA) have been labelled with 188Re to produce a target specific radiopharmaceutical. The radiolabeled compound, i.v. injected in healthy mice, is able to accumulate into the liver after a few minutes. To study the effect of metabolic radiotherapy in mice, we have built a small gamma camera based on a matrix of YAP:Ce crystals, with 0.6x0.6x10 mm**3 pixels, read out by a R2486 Hamamatsu PSPMT. A high-sensitivity 20 mm thick lead parallel-hole collimator, with hole diameter 1.5 mm and septa of 0.18 mm, is placed in front of the YAP matrix. Preliminary results obtained with various phantoms containing a solution of 188Re and with C57 black mice injected with the 188Re-HA solution are presented. To increase the space resolution and to obtain two orthogonal projections simultaneously we are building in parallel two new cameras to be positioned at 90 degrees. They use a CsI(Tl) matrix with 1x1x5 mm**3 pixels read out by H8500 Hamamatsu Flat panel PMT.
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A detector using liquid Xenon (LXe) in the scintillation mode is studied for Positron Emission Tomography (PET) of small animals. Its specific design aims at taking full advantage of the Liquid Xenon scintillation properties. This paper reports on energy, time and spatial resolution capabilities of the first LXe prototype module equipped with a Position Sensitive Photo- Multiplier tube (PSPMT) operating in the VUV range (178 nm) and at 165 K. The experimental results show that such a LXe PET configuration might be a promising solution insensitive to any parallax effect.
Currently, dual-energy X-ray phase contrast imaging is usually conducted with an X-ray Talbot-Lau interferometer. However, in this system, the two adopted energy spectra have to be chosen carefully in order to match well with the phase grating. For example, the accelerating voltages of the X-ray tube are supposed to be respectively set as 40 kV and 70 kV, with other energy spectra being practically unusable for dual energy imaging. This system thus has low flexibility and maneuverability in practical applications. In this work, dual energy X-ray phase-contrast imaging is performed in a grating-based non-interferometric imaging system rather than in a Talbot-Lau interferometer. The advantage of this system is that, theoretically speaking, any two separated energy spectra can be utilized to perform dual energy X-ray phase-contrast imaging. The preliminary experimental results show that dual-energy X-ray phase contrast imaging is successfully performed when the accelerating voltages of the X-ray tube are successively set as 40 kV and 50 kV. Our work increases the flexibility and maneuverability when employing dual-energy X-ray phase-contrast imaging in medical diagnoses and nondestructive tests.
Purpose: Retinoblastoma (RB) is the most common eye tumor in childhood and can be treated external radiotherapy. The purpose of this work is to evaluate the adequacy of Monte Carlo simulations and the accuracy of a commercial treatment planning system by means of experimental measurements. Dose measurements in water were performed using a dedicated collimator. Methods: A 6MV Varian Clinac 2100 C/D and a dedicated collimator are used for RB treatment. The collimator conforms a D-shaped off-axis field whose irradiated area can be either 5.2 or 3.1cm$^2$. Depth dose distributions and lateral profiles were measured and compared with Monte Carlo simulations run with PENELOPE and with calculations performed with the analytical anisotropic algorithm (AAA) using the gamma test. Results: PENELOPE simulations agree well with the experimental data with discrepancies in the dose profiles less than 3mm of distance-to-agreement and 3% of dose. Discrepancies between the results of AAA and the experimental data reach 3mm and 6%. The agreement in the penumbra region between AAA and the experiment is noticeably worse than that between the latter and PENELOPE. The percentage of voxels passing the gamma test when comparing PENELOPE (AAA) and the experiment is on average 99% (93%) assuming a 3mm distance-to-agreement and a discrepancy of 3% of dose. Conclusions: Although the discrepancies between AAA and experimental results are noticeable, it is possible to consider this algorithm for routine treatment planning of RB patients, provided the limitations of the algorithm are known and taken into account by the medical physicist. Monte Carlo simulation is essential for knowing these limitations. Monte Carlo simulation is required for optimizing the treatment technique and the dedicated collimator.
In this paper, we present a new method to generate an instantaneous volumetric image using a single x-ray projection. To fully extract motion information hidden in projection images, we partitioned a projection image into small patches. We utilized a sparse learning method to automatically select patches that have a high correlation with principal component analysis (PCA) coefficients of a lung motion model. A model that maps the patch intensity to the PCA coefficients is built along with the patch selection process. Based on this model, a measured projection can be used to predict the PCA coefficients, which are further used to generate a motion vector field and hence a volumetric image. We have also proposed an intensity baseline correction method based on the partitioned projection, where the first and the second moments of pixel intensities at a patch in a simulated image are matched with those in a measured image via a linear transformation. The proposed method has been valid in simulated data and real phantom data. The algorithm is able to identify patches that contain relevant motion information, e.g. diaphragm region. It is found that intensity correction step is important to remove the systematic error in the motion prediction. For the simulation case, the sparse learning model reduced prediction error for the first PCA coefficient to 5%, compared to the 10% error when sparse learning is not used. 95th percentile error for the predicted motion vector is reduced from 2.40 mm to 0.92mm. In the phantom case, the predicted tumor motion trajectory is successfully reconstructed with 0.82 mm mean vector field error compared to 1.66 mm error without using the sparse learning method. The algorithm robustness with respect to sparse level, patch size, and existence of diaphragm, as well as computation time, has also been studied.
Osteopenia is indicated as a common phenomenon in patients who have scoliosis. Quantitative ultrasound (QUS) has been used to assess skeletal status for decades, and recently ultrasound imaging using reflection signals from vertebra were as well applied to measure spinal curvatures on children with scoliosis. The objectives of this study are to develop a new method which can robustly extract a parameter from ultrasound spinal data for estimating bone quality of scoliotic patients and to investigate the potential for the parameter on predicting curve progression. The frequency amplitude index (FAI) was calculated based on the spectrum of the original radio frequency (RF) signals reflected from the tissue-vertebra interface. The correlation between FAI and reflection coefficient was validated using decalcified bovine bone samples in vitro, and the FAIs of scoliotic subjects were investigated in vivo referring to BMI, Cobb angles and curve progression status. The results showed that the intra-rater measures were highly reliable between different trials (ICC=0.997). The FAI value was strongly correlated to the reflection coefficient of bone tissue ($R^{2}=0.824$), and the lower FAI indicated the higher risk of curve progression for the non-mild cases. This preliminary study reported that the FAI method can provide a feasible and promising approach to assess bone quality and monitor curve progression of the patients who have AIS.
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