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We used image-processing software to analyze the setup errors at the skin surface position of breast cancer patients (n=66) who underwent post-operative whole breast irradiation at our hospital in 2014-2015. The sixty-six digital reconstructed radiographs (DRR) were created at the treatment planning for each patient. The lineacgraphies (n=377) were taken after the patients' setup during radiotherapy. The lineacgraphies and DRR were superimposed at the skin surface position for each patient with the image-processing software. We measured the deviations of the isocenters for the nipple-lung (X) direction and craniocaudal (Y) direction and the deviation of the rotation angle of the XY axes between the lineacgraphy and DRR on the superimposed images. The systematic error (µ, Σ) and random error (σ) were calculated from the X and Y deviations and rotation angle deviation. The µ of X, Y, and rotation angle were 0.01 mm, -1.2 mm, and 0.05°, respectively. The Σ of X, Y, and rotation angle were 1.8 mm, 1.5 mm, and 0.9°, respectively. The σ of X, Y, and rotation angle were 2.0 mm, 1.5 mm, and 1.0°, respectively. Our analyses thus revealed that evaluations using image-processing software at the skin surface position in routine breast radiotherapy result in sufficiently small setup errors.

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The usefulness of dental approaches, such as oral management, has gained recognition among patients treated for head and neck cancer. In particular, oral management plays a very important role before, during, and after treatment in patients undergoing radiotherapy, chemotherapy, or a combination of both. However, specialized dentistry knowledge and techniques that are useful for patients undergoing radiotherapy for head and neck cancer have yet to be reported. Therefore, in this review article, our aim is to introduce dental approaches in radiotherapy for patients with head and neck cancer that have been developed and are currently being used at our institute.

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The aim of this study is to investigate the dosimetric uncertainty of stochastic noise and the post-irradiation density growth for reflective-type radiochromic film to obtain the appropriate dose from the exactly controlled film density. Film pieces were irradiated with 6-MV photon beams ranging from 0 to 400cGy. The pixel values (PVs) of these films were obtained using a flatbed scanner at elapsed times of 1min to 120h between the end of irradiation and the film scan. The means and standard deviations (SDs) of the PVs were calculated. The SDs of the converted dose scale, usd, and the dose increases resulting from the PV increases per ±29min at each elapsed time, utime, were computed. The combined dose uncertainties from these two factors, uc, were then calculated. A sharp increase in the PV occurred within the first 3h after irradiation, and a slight increase continued from 3h to 120h. usd was independent of post-irradiation elapsed time. Sharp decreases in utime were obtained within 1h after irradiation, and slight decreases in utime were observed from 1 to 24h after irradiation. uc first decreased 1h after irradiation and remained constant afterward. Assuming that the post-irradiation elapsed times of all of the related measurements are synchronized within ±29min, the elapsed time should be at least 1h in our system. It is important to optimize the scanning protocol for each institution with consideration of the required measurement uncertainty and acceptable latency time.

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The conveyor system plays a vital role in improving the performance of flexible manufacturing cells (FMCs). The conveyor selection problem involves the evaluation of a set of potential alternatives based on qualitative and quantitative criteria. This paper presents an integrated multi-criteria decision making (MCDM) model of a fuzzy AHP (analytic hierarchy process) and fuzzy ARAS (additive ratio assessment) for conveyor evaluation and selection. In this model, linguistic terms represented as triangular fuzzy numbers are used to quantify experts' uncertain assessments of alternatives with respect to the criteria. The fuzzy set is then integrated into the AHP to determine the weights of the criteria. Finally, a fuzzy ARAS is used to calculate the weights of the alternatives. To demonstrate the effectiveness of the proposed model, a case study is performed of a practical example, and the results obtained demonstrate practical potential for the implementation of FMCs.

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Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment.

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PURPOSE: The purpose of this study is to quantify the magnitudes of the position shifts of internal structures together with the correlation between the day-to-day positioning of the prostate and the bony anatomy using an integrated CT-linear accelerator system for external beam radiation therapy for prostate cancer. MATERIALS AND METHODS: A total of 1176 pretreatment in-room CT images and their digitally reconstructed radio-graph (DRR) pairs from 33 patients were acquired over the course of the study. The differences between the isocenter of the prostate on in-room CT and the isocenter of the bony anatomy on DRR were analyzed. The agreement between positions in each direction was compared using Bland-Altman limits of agreement. RESULTS: The 95% limits of agreement in lateral (LR), superoinferior (SI), and anteroposterior (AP) directions were -2.98 to 2.49 mm, -4.69 to 5.75 mm, and -8.23 to 7.30 mm, respectively. The isocenter was localized to within 3.0 mm on in-room CT images and DRR 99.0% in LR, 85.1% in SI, and 85.9% in AP. CONCLUSIONS: Considerable differences between in-room CT images and DRR exist. These data demonstrate that there is a significantly greater shift in the SI and AP directions than in the lateral direction for the entire patient group. Applications such as our image guide system will, with routine clinical use, continue to improve the precision of external beam radiation therapy for prostate cancer.

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Radiochromic film (RC-film) is of great interest as a film-type dosimeter for radiation oncology applications. We present a two-dimensional image-based evaluation of the measurement accuracy of a commercial RC-film product (Gafchromic MD-55-2 film, ISP TECHNOLOGIES, Inc.) by using a commercial Laser Densitometer (Model 1710, Computerized Medical Systems, Inc.) as an optical density imaging system. The coefficient of variation of the density (pixel-value) in one sample was approximately 3% to 11% at 3 Gy or less, and 3% or less at 4 to 60 Gy. Although the coefficient of variation between three samples at the same dose was about 14% at 1 Gy, it decreased as the dose increased, reaching several percent. In 1 to 6 Gy samples, geometric imaging artifacts [interference (moire) patterns] were observed, and it was found that scan-sampling pitch influenced the accuracy of measurement of the density of the sample. To improve the accuracy of density measurement, sufficient knowledge about characteristic features of the density measuring system is essential.

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