Evaluation occupationally radiation exposure during diagnostic imaging examinations.

Occupational radiation exposure can occur due to various human activities, including the use of radiation in medicine. Occupationally exposed personnel surpassing 7.4 millions, and respresent the biggest single group of employees who are exposed to artificial radiation sources at work. This study compares the occupational radiation dose levels for 145 workers in four different hospitals located in the Aseer region in Saudi Arabia. The occupational exposure was quantified using thermoluminescence dosimeters (TLD-100). The levels of annual occupational exposures in targeted hospitals were calculated and compared with the levels of the international atomic energy agency (IAEA) Safety Standards. An average yearly cumulative dose for the two consecutive years. The average, highest and lowest resulted occupational doses under examination in this work is 1.42, 3.9 mSv and 0.72 for workers in various diagnostic radiology procedures. The resulted annual effective dose were within the IAEA approved yearly dose limit for occupational exposure of workers over 18, which is 20 mSv. Staff should be monitored on a regular basis, according to current practice, because their annual exposure may surpass 15% of the annual effective doses.

Sensing mammographic density using single-sided portable Nuclear Magnetic Resonance.

This research paper presents a quantitative approach to sensing mammographic density (MD) using single-sided portable Nuclear Magnetic Resonance (NMR). It focuses on three main techniques: spin-lattice relaxation (recovery) time (T1), spin-spin relaxation (decay) time (T2), and Diffusion (D) techniques by testing whether or not the aforementioned techniques are in agreement with the gold standard and with each other when used for scanning breast tissue specimens with a variety of mammographic densities (MDs). The high mammographic density (HMD), intermediate MD, and low mammographic density (LMD) regions of each slice were identified according to the mammogram images. Subsequently, the grayscale values for these regions were quantified. One region was measured from the first sample while the remaining ones were measured from the second sample. The same areas were then exposed to portable NMR, and the sequences used as following: the stimulated echo sequence for diffusion (D), the Carr-Purcell-Meiboom-Gill (CPMG) sequence for T2, and saturation recovery sequence for T1. The correlations between the grayscale values and NMR techniques were strongly correlated. The Pearson correlation coefficient, R, of T1 (%) versus grayscale value, D (%) versus grayscale value, and T2 (%) versus grayscale value, was 0.91, 0.91, and 0.93, respectively. Furthermore, the relative water content of the breast slices based on T1, T2, and diffusion (D) measurements were strongly in agreement with each other. The Pearson correlation coefficient, R, of D (%) versus T1 (%), D (%) versus T2 (%), and T1 (%) versus T2 (%), was 0.984, 0.966, and 0.9868, respectively. The three pulse sequences can be employed in a portable NMR device to deliver continuous quantitative measurements of MD in breast tissue samples. As a result, the method demonstrated to be acceptable for determining the distribution of MDs among breast tissue samples without the need for additional qualitative analysis.

The suitability of smartphone camera sensors for detecting radiation.

The advanced image sensors installed on now-ubiquitous smartphones can be used to detect ionising radiation in addition to visible light. Radiation incidents on a smartphone camera's Complementary Metal Oxide Semiconductor (CMOS) sensor creates a signal which can be isolated from a visible light signal to turn the smartphone into a radiation detector. This work aims to report a detailed investigation of a well-reviewed smartphone application for radiation dosimetry that is available for popular smartphone devices under a calibration protocol that is typically used for the commercial calibration of radiation detectors. The iPhone 6s smartphone, which has a CMOS camera sensor, was used in this study. Black tape was utilized to block visible light. The Radioactivity counter app developed by Rolf-Dieter Klein and available on Apple's App Store was installed on the device and tested using a calibrated radioactive source, calibration concrete pads with a range of known concentrations of radioactive elements, and in direct sunlight. The smartphone CMOS sensor is sensitive to radiation doses as low as 10 µGy/h, with a linear dose response and an angular dependence. The RadioactivityCounter app is limited in that it requires 4-10 min to offer a stable measurement. The precision of the measurement is also affected by heat and a smartphone's battery level. Although the smartphone is not as accurate as a conventional detector, it is useful enough to detect radiation before the radiation reaches hazardous levels. It can also be used for personal dose assessments and as an alarm for the presence of high radiation levels.