[Verification of the accuracy of the delivered dose in pelvic and breast cancer radiotherapy by in-vivo semi-conductor dosimetry]

Delivering maximum dose to tumor and minimum dose to normal tissues is the most important goal in radiotherapy. According to ICRU, the maximum acceptable uncertainty in the delivered dose compared to the prescribed dose should be lower than 5% and this is because of the relationship between absorbed dose, tumor control and normal tissue damage. Absorbed dose accuracy is investigated by an in vivo dosimetry method. In this paper, we compared absorbed dose in the tumors of the breast and pelvic region against the calculated dose. The amount of deviations and the factors that cause this deviation in dose delivery to patients and some methods for decreasing them were evaluated. The entrance and exit doses of 36 pelvi-region cancer patients and 38 breast cancer patients who were treated by cobalt-60 teletherapy were measured using p-type diodes. It should be noted that the transmission method was used to assess the dose at isocenter. Two ionization chambers [0.6cc and 0.3cc] were used for calibration and determination of the correction coefficients in water and slab phantoms. Deviations between calculated and measured doses of entrance, exit and midline point were calculated and the results were shown using histograms. The average and standard deviation for entrance, exit and midline points for pelvis cancer were assessed to be about 0.10%, -1.86% and -1.35% for mean deviation an d5.03%, 7.32% and 5.86% for standard deviation, respectively. The corresponding data for breast cancer were 0.78%, 5.29% and 3.59% for mean deviation and 5.97%, 10.23% and 9.86%, respectively. There was not significant difference between the calculated and measured doses [p>0.1], except exit dose in breast cancer [p<0.05]. The temperature and angle of incidence correction factors were neglected due to their less than 1% deviations. Some error sources are patient setup error, patient motion and dose calculation algorithm error [due to ignoring in homogeneity and patient curvature]. As no significant deviations were found in midline dose, the method used has an acceptable accuracy. In vivo dosminetry can perform a basic role in the quality control of radiotherapy departments

value of myocardial perfusion imaging with Tc-99m MIBI for the prediction of perfusion improvement after percutaneous transluminal coronary angioplasty

Percutaneous transluminal coronary angioplasty [PTCA] is an effective method for revascularizing of stenotic coronary vessels. Lack of response to this treatment, either in symptomatic or asymptomatic patients, is usually due to incomplete revascularization, restenosis, and/or irreversibility of myocardial perfusion. Introduction of a noninvasive method with high predictive value for diagnosis of reversibility in ischemic myocardium is of high importance to determine the patients who will benefit from PTCA. Sixty patients with one or two vessel disease, who were candidates for PTCA and had a successful PTCA [proved by post-revascularization angiography], enrolled the study. For all patients myocardial perfusion within 6 months after PTCA. The predictive values of pre-PTCA scan for the diagnosis of reversibility and prediction of perfusion improvement after PTCA were evaluated. Perfusion improvement after PTCA was noted in 52 of 60 patients [86.7%]. The positive predictive value of pre-intervention MPI for diagnosis of reversibility was 94.3% and the corresponding negative predictive value was 71.4%. Myocardial perfusion imaging may play an important role for accurate prediction of perfusion improvement after percutaneous transluminal coronary angioplasty

Platelet-based MPLE algorithm for denoising of SPECT Images: phantom and patient study

In this study the evaluation of a Platelet-based Maximum Penalized Likelihood Estimation [MPLE] for denoising SPECT images was performed and compared with other denoising methods such as Wavelets or Butterworth filtration. Platelet-based MPLE factorization as a multiscale decomposition approach has been already proposed for better edges and surfaces representation due to Poisson noise and inherent smoothness of this kind of images. We applied this approach on both simulated and real SPECT images. Monte Carlo simulations were generated with the SIMSET package to model the physical processes and instrumentation used in emission imaging. Cardiac, brain and NEMA phantom SPECT images were obtained using a single-head, Argus model SPECT system. The performance of this method has been evaluated both qualitatively and quantitatively with power spectrum, SNR and noise level measurements on simulated and real SPECT images. For NEMA phantom images, the measured noise levels before [M[b]] and after [M[a]] denoising with Platelet-based MPLE approach were M[b]=2.1732, M[a]=0.1399. In patient study for 32 cardiac SPECT images, the difference between noise level and SNR before and after the approach were [M[b]=3.7607, SNR[b]=9.7762, M[a]=0.7374, SNR[a]41.0848] respectively. Thus the Coefficient of variance [C.V] of SNR values for denoised images with this algorithm as compared with Butterworth filter, [145/33%] was found. For 32 brain SPECT images the Coefficient Variance of SNR values, [196/17%] was obtained. Our results shows that, Platelet-based MPLE is a useful method for denoising SPECT images considering better homogenous image, improvements in SNR, better radioactive uptake in target organ and reduction of interfering activity from background radiation in comparison to that of other conventional denoising methods