Acoustic Thermometry is one of non-invasive methods to measure the temperature inside tissue area. Especially, when using the thermal therapy techniques such as High Intensity Focused Ultrasound (HIFU) and other thermal based methods, thermal assessment of heated area seems to be necessary. Some of acoustic properties of medium are temperature dependent; therefore, evaluation of temperature dependent parameters will be an indirect and non-invasive approach in Thermometry. In this paper some of Thermometry methods based on changes in acoustic properties of medium have been reviewed. The published methods are classified in two main categories: passive and active Thermometry. In the passive Thermometry, the thermal measurement probes, induced no acoustic signals to the medium, but they receive the radiated signals from the heated medium. In active method, the Thermometry probe transmits a signal into the heated region and receives the echoes, then the received RF signals are processed in order to measure the temperature.

Purpose: Passive Acoustic Thermometer (PAT) is a safe method for internal temperature estimation that works based on acoustic radiation of materials with a specific temperature. Several experimental studies have been carried out so far in the field of PAT. While, to the best of our knowledge, there is no simulation-based research reported yet. Materials and Methods: In this article (for the first time) we proposed a simulation framework for evaluating the PAT methodologies. This framework supports the generation of acoustic radiation, signal processing, parameter estimation, and temperature reconstruction processes. At the moment, the proposed framework estimates the temperature in the frequency domain and uses the frequency spectrum of the acquired ultrasound signals captured by a single transducer. Results: Using the proposed framework, we tried to implement previously practical experiments and the results of the simulation are consistent with those of the practical experiment. The mean error of temperature estimation was below 0. 45 ° C. The results show that it is possible to use this framework to evaluate the PAT in different scenarios. Conclusion: Therefore, this method enhances the possibility of examination of different conditions and algorithms. It also reduces the cost of practical experiment.

Purpose: Internal temperature is a significant factor for medical diagnosis. There are several thermometric methods, including IR, MRI, and active ultrasonic Thermometry, which have limitations for clinical applications. The new method in this field called Passive Acoustic Thermometry (PAT), which enhanced some of this limitation. PAT is a safe method for internal temperature estimation that works based on acoustic radiation of materials with a specific temperature. Several experimental studies have been carried out so far in the field of PAT. While, to the best of our knowledge, there is no simulation-based research for nonhomogeneous materials reported yet. In this article (for the first time) we proposed a simulation framework for evaluating the PAT methodologies in nonhomogeneous materials; also we proposed a new formulation for temperature estimation in PAT algorithm. Materials and Methods: This framework supports the generation of acoustic radiation, signal processing, parameter estimation, and temperature reconstruction processes. At the moment the proposed framework estimates the temperature in the frequency domain and uses the frequency spectrum of the acquired ultrasound signals captured by a single transducer. Using the proposed framework, we tried to implement the previously practical experiments and the results of the simulation are consistent with those of the practical experiments. Also, we proposed the formulation that improves the error of temperature estimation. Results: We study 6 scenarios, including 2 environments with a target at 3 different temperatures. The average error of the proposed formulation in two different nonhomogeneous materials for three different temperatures is less than 0. 25° C. Conclusion: The results show that the proposed formulation is the best estimation in the formula that has been introduced until now and compare with the previous study the accuracy is enhanced 54% (from 0. 79 to 0. 36 deg. ). Therefore, the proposed formula enhanced PAT accuracy for temperature estimation. Also, the results show that it is possible to use this framework to evaluate the PAT in different scenarios. Therefore, this method enhances the possibility of examination of different conditions and algorithms. It also reduces the cost of practical experiment.

Purpose: For over three decades, various researchers have aimed to construct a model of breast cancer. Most of them have used an infrared thermal model to stimulate breast cancer, but in this study, a novel estimation methodology is presented to detect the breast cancer tumor using the surface measurement obtained by Passive Acoustic Thermometer (PAT). PAT is a safe method for internal temperature estimation that works based on acoustic radiation of materials with a specific temperature. Materials and Methods: This article uses a simulation framework for breast tissue simulation and tumor detection using the PAT methodologies in different scenarios. This framework supports the generation of acoustic radiation, tissue modelling, signal processing, parameter estimation, and temperature reconstruction processes. The proposed framework estimates the temperature in the frequency domain and uses the frequency spectrum of the acquired ultrasound signals captured by a single transducer. Using the proposed framework, PAT has been evaluated in breast cancer detection. Results: According to the results, obtained from the temperature estimation in scenario 3, the sub-band estimation method, which is utilized in practical experiments in this field, shows different errors in each sub-band, making it difficult to select the true estimation. Therefore, a novel formulation is proposed that provides only one estimated temperature for breast tissue with a reasonable error (1. 28 degrees) for tumor detection. Conclusion: The results show that it is possible to use this framework to evaluate the PAT in different scenarios for tumor detection. In fact, this method enhances the possibility of examination of different conditions and algorithms. It also reduces the cost of practical experiments.

Background: Rectal route is a gold standard method of measuring fever, but it is invasive and stressful for parents and children. A recently used method is tympanic that has the advantages of safety, speed and compatibility but its accuracy is under question. Methods: In order to assess the accuracy of tympanic Thermometry, 220 children within 3 months to 6 years old were selected and temperature was checked by rectal, axillary and tympanic methods. Results: The mean rectal temperature, compared with tympanic and axillary, was higher (0.3oc and 0.1oc, respectively). There was a good correlation between right and left tympanic measurements (r=0.87, P<0.001), rectal and right tympanic (r=0.76, P<0.005), axillary and right tympanic (r=0.80, P<0.001), and axillary and rectal methods (r=0.74, P<0.001). The sensitivity, specificity and accuracy of tympanic method (with 38°Cascut off point) were 46.4%, 97.2 % and 90.9%. ROC curve analysis showed that the best cut off point for fever was 37°c; the sensitivity, specificity and accuracy were increased 92.9%, 90.1% and 90.4%, respectively, using this cut off point. Kappa coefficient showed a good correlation between rectal and tympanic methods. Conclusion: Tympanic Thermometry, in comparison to axillary and rectal Thermometry is an accurate, rapid, safe and comfortable method and the best cut off point for defining fever is 37°c.

Background: Patients with cancer under chemotherapy who encounter oral mucositis are about 40% to 100%. Accurate diagnosis of fever among such patients is important as detecting fever among such patients particularly patients with fever and neutropenia can necessitate the start of antibiotics. It is more important when the oral method is the most common way for measuring the body temperature and oral mucositis may play a confounding role. According to importance of correct Thermometry and high prevalence of oral mucositis in patients with cancer, the aim of this study was to compare the body temperature detected by oral, axillary and tympanic routes among the groups of patients with and without oral mucositis in self-referred or hospitalized patients of Hazrat Sayyed Al-Shohada (as) during 2010-2011.Methods: This is a cross-sectional study conducted among patients with cancer treated with chemotherapy with or without oral mucositis, hospitalized at Hazrat Sayyed Al-Shohada (as) during 2010-2011. We used simple non-random sampling method. Standard deviation was determined according to normal body temperature of 36.8±0.4oC to use for calculating the sample population number. One hundred and sixty four patients were divided in two groups based on presence of oral mucositis (group A: with oral mucositis and group B: without oral mucositis) and then the temperature of the three areas of the mouth, axilla and tympanic in each group were measured, simultaneously.Results: In the group of patients with oral mucositis in all three methods of temperature measurement by oral, axillary and tympanic compared to patients without oral mucositis, body temperature significantly was higher. Also in group A, the average temperature measured by mouth (37.10oC) compared to the average temperature measured by axillary method (36.85oC) was higher and was significantly different [d=0.25oC, p=0.000], while compared to the average tympanic temperature from right ear (37.10oC), [d=0oC, p=0.48] and left ear (37.11oC), [d=0.01oC, p=0.46] did not differ significantly. In Group B, the difference between average oral temperature (36.68oC) than Axillary (36.32oC), [d=0.35oC, p=0.000] were significant, but compared to the tympanic average temperature of the right ear (36.74oC), [d=0.05oC, p=0.16] and left ear (36.70oC), [d=0.01oC, p=0.385] were not significantly different.Conclusions: Based upon the study it seems in patients with cancer, oral mucositis as an important confounder, cannot cause error in the temperature measurement taken by mouth. Therefore start of proper treatment in this group of patients based on the temperature measured by mouth seems reasonable.

Background/Objective: To evaluate T1 and PRF Thermometry methods utilizing fast MR sequences and fluoroptic thermometer.Materials and Methods: The MR-guided LITT (Laser-Induced Interstitial Thermotherapy) with a laser wavelength/power of 1064nm/30W was applied to pig liver and a gel phantom. During the ablation process, the temperature was measured using a fluoroptic thermometer and MR imaging was performed applying a 1.5-Tesla tomograph with an EPI (Echo Planar Imaging) sequence for PRF (Proton Resonance Frequency) method and FLASH, IRTF, SRTF and TRUFI sequences for T1 method. Plotting MR signal intensity against measured temperature determined the temperature constant for each of the T1 sequences. To determine the PRF temperature constant, phase values were recorded from phase images and then plotted against temperature. The PRF temperature constant was verified comparing the MR temperature with the measured one obtained from a second LITT experiment on gel phantom.Results: The experiments determining the temperature constant for T1 method showed that the IRTF and FLASH sequences have the highest temperature sensitivity and the most linear relationship between MR signal intensity and measured temperature. SRTF sequence presented relatively good linearity but inferior temperature sensitivity compared to IRTF and FLASH sequences. Conversely, TRUFI sequence exhibited the lowest temperature sensitivity and linearity of data points. Concerning the PRF method, the measured and the MR-based temperatures agreed up to approximately 7°C.Conclusion: To demonstrate and control temperature in target tissue during the LITT process, the PRF method with an EPI sequence is preferred for temperatures below 70 C due to its acceptable accuracy. Among the T1 sequences, FLASH is preferable as the most robust, though not the most accurate T1 sequence.