Electrocardiogram (ECG) has been widely used for assessment of right ventricular (RV) hypertrophy (RVH) in patients with pulmonary hypertension (PH). However, it still remains unclear which ECG criteria of RVH are useful to predict for the severity of PH. The aim of our study was to examine the utility of ECG findings of RVH in assessment of PH. A total of 53 patients (42 women, mean age; 57.6 ± 16.4 years) with pre-capillary PH, who were diagnosed by right heart catheterization, underwent blood sampling, ECG, and cardiac magnetic resonance within a week before the right heart catheterization. We assessed the traditional ECG criteria of RVH in PH patients, and compared to age- and gender-matched control subjects without PH confirmed by 2-dimensional echocardiography (n = 42, mean age 55.3 ± 15.9 years). We also analyzed the clinical variables associated with ECG findings in patients with PH. Mean pulmonary arterial pressure (mPAP), cardiac index, and pulmonary vascular resistance (PVR) in PH patients were 35.3 ± 11.9 mmHg, 2.82 (2.09–3.45) L/min/m2, and 576 ± 376 dyne·sec·cm-5, respectively. The prevalence of right axis deviation (43.4%), R:S ratio V1 > 1 (32.1%), and RV1+SV5/6 > 10.5 mm (69.8%) in PH patients was greater than those in control subjects (p < 0.001). In univariate analysis, mPAP, PVR, RV wall thickness, RV mass index, RV volume, and RV ejection fraction (EF) (inversely) were significantly correlated with the amplitude of RV1+SV5/6. Multiple regression analysis revealed that mPAP and RVEF (inversely) were independently associated with the amplitude of RV1+SV5/6 (R2 = 0.282). Also, we performed the survival analysis among pre-capillary PH patients. During a mean follow-up of 3.7 years, patients with ≥ 16.4 mm of RV1+SV5/6 had worse prognosis than those with < 16.4 mm (Log rank p = 0.015). In conclusion, the amplitude of SV1+RV5/6 could be the most useful factor reflected for RV remodeling, hemodynamics and survival in patients with pre-capillary PH.
Stereotactic radiosurgery (SRS) and radiotherapy (SRT) are intricate techniques that deliver a highly precise radiation dose to a localized target, usually a tumor. At our hospital, we perform SRS and SRT on brain tumors using a linear accelerator (linac) mounted with an external micro multi-leaf system. The Task Group TG-142 Report by the American Association of Physicists in Medicine recommends the coincidence of the radiation and mechanical isocenter to be within ±1 mm. The Winston-Lutz test is commonly used to verify the linac isocenter position: it has the advantages of being a simple method that uses a film or electronic portal imaging device (EPID). However, the film method requires a higher radiation dose, which makes it more time-consuming than the EPID method, and the results are highly dependent on the skills of the observer. The EPID method has certain advantages over the film method, but it has low resolution and can only be used for a few combinations of gantry and couch angles. This prompted us to develop an in-house-designed radiation receptor system based on digital radiography, using a photostimulable storage phosphor and automated analysis algorithm for Winston-Lutz test images using a template-matching technique based on cross-correlation coefficients. Our proposed method shows a maximum average absolute error of 0.222 mm (less than 2 pixels) for 0.5 mm and 1.0 mm displacement from the isocenter toward the inline and crossline directions. Our proposed method is thus potentially useful for verifying the Linac isocenter position with a small error and good reproducibility, as demonstrated by improved accuracy of evaluation.
Digital pelvic radiographs are used to identify the locations of implanted iodine-125 seeds and their numbers after insertion. However, it is difficult and laborious to visually identify and count all implanted seeds on the pelvic radiographs within a short time. Therefore, our purpose in this research was to develop an automated method for estimation of the number of implanted seeds based on two-view analysis of pelvic radiographs. First, the images of the seed candidates on the pelvic image were enhanced using a difference of Gaussian filter, and were identified by binarizing the enhanced image with a threshold value determined by multiple-gray level thresholding. Second, a simple rule-base method using ten image features was applied for false positive removal. Third, the candidates for the likely number of a multiply overlapping seed region, which may include one or more seeds, were estimated by a seed area histogram analysis and calculation of the probability of the likely number of overlapping seeds. As a result, the proposed method detected 99.9% of implanted seeds with 0.71 false positives per image on average in a test for training cases, and 99.2% with 0.32 false positives in a validation test. Moreover, the number of implanted seeds was estimated correctly at an overall recognition rate of 100% in the validation test using the proposed method. Therefore, the verification time for the number of implanted seeds could be reduced by the provision of several candidates for the likely number of seeds.
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