Increasing source to image distance for AP pelvis imaging – impact on radiation dose and image quality

Aim: A quantative primary study to determine whether increasing source to image distance (SID), with and without the use of automatic exposure control (AEC) for antero-posterior (AP) pelvis imaging, reduces dose whilst still producing an image of diagnostic quality. Methods: Using a computed radiography (CR) system, an anthropomorphic pelvic phantom was positioned for an AP examination using the table bucky. SID was initially set at 110 cm, with tube potential set at a constant 75 kVp, with two outer chambers selected and a fine focal spot of 0.6 mm. SID was then varied from 90 cm to 140 cm with two exposures made at each 5 cm interval, one using the AEC and another with a constant 16 mAs derived from the initial exposure. Effective dose (E) and entrance surface dose (ESD) were calculated for each acquisition. Seven experienced observers blindly graded image quality using a 5-point Likert scale and 2 Alternative Forced Choice software. Signal-to-Noise Ratio (SNR) was calculated for comparison. For each acquisition, femoral head diameter was also measured for magnification indication. Results: Results demonstrated that when increasing SID from 110 cm to 140 cm, both E and ESD reduced by 3.7% and 17.3% respectively when using AEC and 50.13% and 41.79% respectively, when the constant mAs was used. No significant statistical (T-test) difference (p ¼ 0.967) between image quality was detected when increasing SID, with an intra-observer correlation of 0.77 (95% confidence level). SNR reduced slightly for both AEC (38%) and no AEC (36%) with increasing SID. Conclusion: For CR, increasing SID significantly reduces both E and ESD for AP pelvis imaging without adversely affecting image quality

Defining the targets of antiparasitic compounds

The treatment of major human parasitic infections is dependent on drugs that are plagued by issues of drug resistance. New chemotherapeutics with novel mechanisms of action (MOA) are desperately needed to combat multi-drug-resistant parasites. Although widespread screening strategies are identifying potential new hits for development against most major human parasitic diseases, in many cases such efforts are hindered by limited MOA data. Although MOA data are not essential for drug development, they can facilitate compound triage and provide a mechanism to combat drug resistance. Here we describe and discuss methods currently used to identify the targets of antiparasitic compounds, which could circumvent this bottleneck and facilitate the development of new antiparasitic drugs