Clinical and Dosimetric Implications of Air Gaps between Bolus and Skin Surface during Radiation Therapy

Purpose: The main objective of the study was to evaluate the effect of air gaps of 0 - 5.0 cm between bolus and skin for 1.0 cm Superflab bolus on surface dose (DSurf) and depth of maximum dose (dmax) in solid water and Rando? phantoms. Methods: In this work, the effects of bolus to surface distance on DSurf and variation in dmax were analyzed in a solid water phantom and in an anthropomorphic Rando? phantom for different field sizes, using Gafchromic? EBT films and farmer chamber. Results: For field sizes of 5 × 5 cm2 the DSurf is significantly affected by increasing air gaps greater than 5 mm. For field sizes larger than 10 × 10 cm2, DSurf is nearly the same for air gaps of 0 - 5.0 cm. For small fields and 6 MV photon beam, dmax increases with increasing air gap, while for 10 MV beam and smaller field sizes (i.e. 5 × 5 and 10 × 10 cm2) the dmax first decreases and then increases with the air gaps. For both 3DCRT and IMRT plans on Rando?, DSurf reduction is more prominent with increasing air gaps. Conclusion: For field sizes larger than 10 × 10 cm2 DSurf is largely unaffected by air gaps. However, smaller air gap results in shallower dmax for both 6 MV and 10 MV photon beams at all fields sizes. Special consideration should be taken to reduce air gaps between bolus and skin for field sizes smaller than 10 × 10 cm2 or when surface contour variations are greater or when the bolus covers small area and at the border of the field.

IRMIRS:Inception-ResNet-Based Network for MRI Image Super-Resolution

Medical image super-resolution is a fundamental challenge due to absorption and scattering in tissues.These challenges are increasing the interest in the quality of medical images.Recent research has proven that the rapid progress in convolutional neural networks(CNNs)has achieved superior performance in the area of medical image super-resolution.However,the traditional CNN approaches use interpolation techniques as a preprocessing stage to enlarge low-resolution magnetic resonance(MR)images,adding extra noise in the models and more memory consumption.Furthermore,conventional deep CNN approaches used layers in series-wise connection to create the deeper mode,because this later end layer cannot receive complete information and work as a dead layer.In this paper,we propose Inception-ResNet-based Network for MRI Image Super-Resolution known as IRMRIS.In our proposed approach,a bicubic interpolation is replaced with a deconvolution layer to learn the upsampling filters.Furthermore,a residual skip connection with the Inception block is used to reconstruct a high-resolution output image from a low-quality input image.Quantitative and qualitative evaluations of the proposed method are supported through extensive experiments in reconstructing sharper and clean texture details as compared to the state-of-the-art methods.

Variation in patient dose due to differences in calibration and dosimetry protocols

For precise and accurate patient dose delivery,the dosimetry system must be calibrated properly according to the recommendations of standard dosimetry protocols such as TG-51 and TRS-398. However, the dosimetry protocol followed by a calibration laboratory is usually different from the protocols that are followed by different clinics, which may result in variations in the patient dose.Our prime objective in this study was to investigate the effect of the two protocols on dosimetry measurements.Dose measurements were performed for a Co-60 teletherapy unit and a high-energy Varian linear accelerator with 6 and 15 MV photon and 6, 9, 12, and 15 MeV electron beams, following the recommendations and procedures of the AAPM TG-51 and IAEA TRS-398 dosimetry protocols. The dosimetry systems used for this study were calibrated in a Co-60 radiation beam at the Secondary Standard Dosimetry Laboratory(SSDL) PINSTECH,Pakistan, following the IAEA TRS-398 protocol. The ratio of the measured absorbed doses to water in clinical setting,D_w(TG-51/TRS-398), was 0.999 and 0.997 for 6 and15 MV photon beams,whereas these ratios were 1.013,1.009, 1.003, and 1.000 for 6, 9, 12, and 15 MeV electron beams, respectively. This difference in the absorbed dosesto-water D_w ratio may be attributed mainly due to beam quality(K_Q) and ion recombination correction factor.