2023 CiteScore: 0.8
pISSN: 2345-5829
eISSN: 2345-5837
Editor-in-Chief:
Mohammad Reza Ay
Chairman:
Saeid Sarkar
Executive Director:
Hossein Ghadiri
Vol 4 No 3-4 (2017)
Original Article(s)
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Purpose: The purpose of our work was to investigate delakis[1] quality control protocol for our MRI system on Tissue-equivalent diffusivity phantoms made of Nickel-doped agarose/sucrose gels.
Materials and Methods: we designed and manufactured a spherical phantom using these gels for T1, T2 and DW-MRI. Every compartments was filled with tissue equivalent relaxation and diffusivity gels. After that we assessed the quality control protocol for T1, T2 and DW-MRI on these gels and The magnetic resonance imaging of the phantom was performed on the 1.5 T clinical MRI system IMAM KHOMEINI hospital of TEHRAN (GE GENESIS SIGNA). Two parameters,Q and R, are used for the analysis of the quality control ADC values.
Results: T2 gel values, 84.804, 80.773, 86.57, 77.774, 77 (ms), were respectively obtained for BT(body tissue), P2(tumur), P2 in air, P2 in oil, P1(ischemi). Also, their corresponding T1 measurements were 1090.92, 1742.75, 1284.75, 1400, 1358.23 (ms) respectively. using this phantom DW- MRI experiments can be performed under very realistic conditions. The Q calculated for the p1 and p2 in different b-values (150, 400, 1000 mm s-2 ) is smaller than the Q for BT. This observation is likely to indicate that for b values 150, 400, 1000 mm s-2, the ADC measurement reproducibility is compromised by ADC deviations due to difference between effective and nominal b values over time. the R parameter used in our quality control protocol to quantitatively study the directional dependence is expected to be governed by the ADC fluctuation described by the equation of measurement of differences between nominal and effective b values.
Conclusion:. the quality control protocol presented in this study will be of value for monitoring the diffusion imaging performance of an MRI system in a clinically relevant way. -
Purpose:Photoacoustic spectral analysis is a novel tool for studying various parameters affecting signals in Photoacoustic microscopy. But only observing frequency components of photoacoustic signals doesn’t make enough data for a desirable analysis. Thus a hybrid time-domain and frequency-domain analysis scheme has been proposed to investigate effects of various parameters like depth of microscopy, laser focal spot size and contrast agent concentration on Photoacoustic signals.
Methods:Photoacoustic microscopy of mouse brain mathematical phantom has been simulated using k-space method and both time-domain and frequency-domain analysis of photoacoustic signals are presented for evaluation of three parameters affecting signals; depth of microscopy, concentration of Indocyanine Green as an exogenous contrast agent and size of laser focal spot illuminating hemoglobin as an optical absorber. A novel method for study of effects of different optical absorber sizes on PA signals has been proposed.
Results:This work demonstrates that going deeper through the brain will decrease contrast and resolution of photoacoustic microscopy of mouse brain vasculature and this can be solved by using an exogenous contrast agent like Indocyanine Green. Also, by proposed analysis of photoacoustic signals, we demonstrated that using Indocyanine Green will increase both depth resolution and contrast of photoacoustic signals.
Conclusion:Simulations and analysis done on different sizes of irradiated hemoglobin absorbers demonstrated that there is a need to ultra-broadband transducers for achieving more precise analysis of photoacoustic signals, and this means that Acoustic-Resolution Photoacoustic Microscopes are less efficient for utilization in photoacoustic spectral analysis. -
Purpose: The objective of this study is to align multi-parametric MR images of brain tumors using wavelet transformation and multi-similarity (RC and NMI) measures.
Materials and Methods: In this work, we implemented a multi-level non-rigid registration technique with multi-similarity measures for registration of perfusion- and diffusion–derived (rCBV and ADC) maps to morphological FLAIR images. To evaluate the performance of our proposed algorithm, we used synthetic data to test the robustness of the method to noise and intensity inhomogeneity. Finally, the algorithm was applied to multiparametric (FLAIR/rCBV-/ADC-maps) of 10 patients with glial tumors.
Results: Evaluation of the proposed method on synthetic and real data revealed that this approach has a large capture range and is more robust against noise and intensity inhomogeneity without increasing the load and complexity of registration algorithm. The results for synthetic data contaminated with noise and intensity inhomogeneity based on Hausdorff Distance (HD), Root Mean Square Error (RMSE) and Baddeley's delta image metric (Δ) improved by 8%, 8% and 21% respectively. For real data, the overall performances based on RMSE and HD metrics were 28% and 10% for ADC to FLAIR registration, and 40% and 14% for rCBV map to FLAIR registration.
Conclusion: In this work, through the proposed multi-similarity measure combined with each other in different wavelet decomposition levels, the capture range of multiparametric image registration algorithm and robustness against noise and intensity inhomogeneity artifacts could be improved. -
Purpose: With the increasing usage of radiography in dentistry, it is important to consider different aspects of radiation protection status in dental clinics including knowledge, practice and the attitude of staff. This study aimed to assess radiation protection KAP (Knowledge, Attitude and Practice) in dental radiography staff
Materials and Method: A questionnaire based survey was performed in different types of clinics (educational, public and private) in 5 geographical regions of Iran (capital, center, north, west and east) on 336 participants in 2015-16. The multiple choice questionnaire consisted of 68 questions with a coverage of the demographic, knowledge, attitude and practice of staff regarding radiation protection. The collected data were analyzed by the One-Way ANOVA test using SPSS statistical software.
Result: Our findings showed that there was no relation between KAP and sex (P=0.48) and KAP and work experience (P=0.61) of participants. A statistically significant difference was found between time duration after graduation and KAP (P=0.00). In addition, there was a significant difference between size of the clinic and KAP (P=0.04), but there was not any relation between type of clinic and KAP (P=0.80). There was a significant relation between region and KAP (P=0.00).
Conclusion: The result of present study showed that the level of radiation protection KAP is associated with time duration after graduation of participant, size of the clinic and geographical region. Besides, the fact of being no relation between type of clinic and KAP highlights the fact that in dental clinics, the absence of a radiation protection officer or a radiation training expert for training purposes causes a similar outcome regarding radiation protection status in educational and non-educational clinics. -
Purpose: In this work, we aimed to propose an automatic classification scheme based on the parameters derived from apparent diffusion coefficient (ADC)-maps for discriminating benign and malignant parotid tumors.
Methods: MRI was carried out prospectively on 41 patients presented with parotid tumors who underwent surgery and post-surgical histopathological assessment was provided for them (32 benign, 9 malignant). Based on anatomical images, regions of interest (ROIs) were selected on the most solid parts of tumors on ADC-maps. Three quantitative parameters, namely ADC-Mean, ADC-Max and ADC-Mean were calculated. Automatic classification of parotid tumors using ADC parameters was performed and assessed employing two different classifiers, namely, linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA).
Results: Following statistical analysis, it was indicated that the ADC values in benign tumors are significantly higher than malignant tumors. ADC-Mean, and -Max presented statistically significant differences among benign and malignant parotid tumors (p<0.05). Among the extracted parameters, ADC-Max is the most relevant quantitative parameter for tumor classification with 82.9% accuracy, 84.4% specificity, 77.8% sensitivity, and 83.3% area under the ROC curve (AUC) by exploiting each of the automatic classifiers. This implies that this parameter is inherently accurate and adding further classification complexity does not improve the results. A linear classifier using LDA classification based on ADC-max is proposed, which indicates that ADC-Max under 1.48×10-3mm2/s is highly suggestive of malignancy (with 83% accuracy).
Conclusion: ADC-Max is a potential biomarker for discriminating benign and malignant parotid tumors. Using ADC-Max and LDA, a simple and clinically-feasible classifier is proposed.
