The purpose of this study was to examine the effects of off-season training on the anaerobic power output and muscle thickness of male varsity rowers. 23 rowers participated in this study. Four all-out cycle ergometer work tests lasting 7 and 40 seconds were used to estimate anaerobic alactic power (AAP) and anaerobic lactic power (ALP) with leg (pedaling) and arm (cranking) exercises. AAP was computed as the highest power output during 7 seconds and ALP was obtained as the mean power output during 40 seconds. Muscle thickness was measured by B-mode ultrasonography at 11 sites on the body. There were significant differences between before and after off-season training in AAP (cranking : 8.4±1.00 vs 9.2±1.10W /kg, p<0.001, pedaling: 14.4± 1.10 vs 15.0±1.00 W/kg, p<0.001) and ALP (cranking : 5.2±0.42 vs 5.5±1.20W/kg, p<0.001, pedaling: 10.1±0.62 vs 9.5±2.10 W/kg, n, s.) . Muscle thickness increased significantly as a result of off-season training at sites on the biceps, triceps, pectoralis major, subscaplar and hamstrings. Similarly, there were significant differences in estimated muscle cross-sectional area (MCSA) on sites on the elbow flexor (20.6±2.6 vs 22.1±1.8cm², p< 0.01), elbow extensor (25.3 ±4.8 vs 28.6±4.2cm², p<0.001) and knee flexor (71.1±5.8 vs 74.3±5.2cm², p<0.01) . The main training program in the off-season consisted of resistance training of the whole body. The high intensity training, used by male varsity rowers during off-season training, increased arm AAP, leg AAP, arm ALP and muscle thickness of the upper body ; but there was no difference in leg ALP and knee extensor muscle. It was suggested that improvements in leg ALP and knee extensor muscle are necessary to during the off-season training program of male varsity rowers.

We have previously reported that the thoracolumbar posterior nerve root shows a tortuous epidural course, based on studies of human fetuses near term. For comparison with the cervical nerve, examinations were conducted using frontal, sagittal and horizontal sections of cervical vertebrae from 22 fetuses at 30–38 weeks of gestation. The cervical nerve root showed a short, straight and lateral course near the zygapophysial joint. Multiple rather than single bundles of the cervical posterior root seemed to account for the majority of sensory nerve fibers innervating the upper extremity. Fasciculation of rootlets was evident near the thoracolumbar spinal cord, whereas it was seen in the dural pocket at the nerve exit from the dural sac although both sites were subdural. As in the thoracolumbar region, the nerve sheath was continuous with the dura mater and independently surrounded each of the anterior and posterior roots. Radicular arteries were few in the cervical region. In 2 of the 22 fetuses (31 weeks and 33 weeks), there was a segmental, unilateral abnormality of nerve rootlet fasciculation where the dorsal root ganglion was located lateral or peripheral to the intervertebral region. Long nerve roots running inferiorly are a necessary adaptation to the delayed and marked growth of the thoracolumbar vertebral column.In children, the cervical nerve roots are likely to be affected by movement or dislocation of the vertebrae. The segmental abnormality of the cervical nerve root may be linked to rare variations in the brachial plexus.

PURPOSE: Few studies have compared fractional exhaled nitric oxide (FeNO) measurement by NIOX VERO® (NOV) and other devices in children. Moreover, there is no agreement between differences in FeNO values obtained using different devices in adults. Here, we compared FeNO values obtained using NOV and NObreath® (NOB) systems to derive a correction equation for children. METHODS: Eighty-eight participants (age 7–15 years) who were diagnosed with atopic bronchial asthma and visited Sagamihara National Hospital as outpatients between January and April of 2017 were included. We measured FeNO values obtained using NOB and NOV, and analyzed them using Wilcoxon tests and Altman-Bland plots. RESULTS: The median age of the participants was 11.5 years, and the scored Asthma Control Test (ACT) or Childhood ACT (C-ACT) was 25 (interquartile range, 24–25) or 26 (24–27). NOB and NOV values were significantly different (31 [14–52] versus 36 [20–59] ppb; P = 0.020) and strongly correlated (r = 0.92). An equation to convert NOB values into NOV values was derived using linear regression as follows: log NOV = 0.7329 × log NOB + 0.4704; NOB for 20, 40, 58, 80 and 100 ppb corresponded to NOV for 27, 44, 59, 73 and 86 ppb. Thus, NOB < 58 ppb suggested NOB < NOV, whereas NOB > 58 ppb suggested NOB > NOV. CONCLUSIONS: NOB and NOV values were strongly correlated. Participants whose FeNO values were relatively low represented NOB < NOV, whereas those whose FeNO values were relatively high represented NOB > NOV.
Adult ; Asthma ; Child* ; Exhalation ; Humans ; Linear Models ; Nitric Oxide* ; Outpatients

Purpose: This study aimed to investigate changes in target coverage using magnetic resonance–guided online adaptive radiotherapy (MRgoART) for kidney tumors and to evaluate the suitable timing of treatment. Materials and Methods: Among patients treated with 3-fraction MRgoART for kidney cancer, 18 tumors located within 1 cm of the gastrointestinal tract were selected. Stereotactic radiosurgery planning with a prescription dose of 26 Gy was performed using pretreatment simulation and three MRgoART timings with an adapt-to-shape method. The best MRgoART plan was defined as the plan achieving the highest percentage of planning target volume (PTV) coverage of 26 Gy. In clinical scenario simulation, MRgoART plans were evaluated in the order of actual treatment. Waiting for the next timing was done when the PTV coverage of 26 Gy did not achieve 95%–99% or did not increase by 5% or more compared to the pretreatment plan. Results: The median percentages of PTV receiving 26 Gy in pretreatment and the first, second, and third MRgoART were 82% (range, 19%), 63% (range, 7% to 99%), 88% (range, 31% to 99%), and 95% (range, 3% to 99%), respectively. Comparing pretreatment simulation plans with the best MRgoART plans showed a significant difference (p = 0.025). In the clinical scenario simulation, 16 of the 18 planning series, including nine plans with 95%–99% PTV coverage of 26 Gy and seven plans with increased PTV coverage by 5% or more, would be irradiated at a good timing. Conclusion MRgoART revealed dose coverage differences at each MRgoART timing. Waiting for optimal irradiation timing could be an option in case of suboptimal timing.

Purpose: This study aimed to investigate changes in target coverage using magnetic resonance–guided online adaptive radiotherapy (MRgoART) for kidney tumors and to evaluate the suitable timing of treatment. Materials and Methods: Among patients treated with 3-fraction MRgoART for kidney cancer, 18 tumors located within 1 cm of the gastrointestinal tract were selected. Stereotactic radiosurgery planning with a prescription dose of 26 Gy was performed using pretreatment simulation and three MRgoART timings with an adapt-to-shape method. The best MRgoART plan was defined as the plan achieving the highest percentage of planning target volume (PTV) coverage of 26 Gy. In clinical scenario simulation, MRgoART plans were evaluated in the order of actual treatment. Waiting for the next timing was done when the PTV coverage of 26 Gy did not achieve 95%–99% or did not increase by 5% or more compared to the pretreatment plan. Results: The median percentages of PTV receiving 26 Gy in pretreatment and the first, second, and third MRgoART were 82% (range, 19%), 63% (range, 7% to 99%), 88% (range, 31% to 99%), and 95% (range, 3% to 99%), respectively. Comparing pretreatment simulation plans with the best MRgoART plans showed a significant difference (p = 0.025). In the clinical scenario simulation, 16 of the 18 planning series, including nine plans with 95%–99% PTV coverage of 26 Gy and seven plans with increased PTV coverage by 5% or more, would be irradiated at a good timing. Conclusion MRgoART revealed dose coverage differences at each MRgoART timing. Waiting for optimal irradiation timing could be an option in case of suboptimal timing.

Purpose: This study aimed to investigate changes in target coverage using magnetic resonance–guided online adaptive radiotherapy (MRgoART) for kidney tumors and to evaluate the suitable timing of treatment. Materials and Methods: Among patients treated with 3-fraction MRgoART for kidney cancer, 18 tumors located within 1 cm of the gastrointestinal tract were selected. Stereotactic radiosurgery planning with a prescription dose of 26 Gy was performed using pretreatment simulation and three MRgoART timings with an adapt-to-shape method. The best MRgoART plan was defined as the plan achieving the highest percentage of planning target volume (PTV) coverage of 26 Gy. In clinical scenario simulation, MRgoART plans were evaluated in the order of actual treatment. Waiting for the next timing was done when the PTV coverage of 26 Gy did not achieve 95%–99% or did not increase by 5% or more compared to the pretreatment plan. Results: The median percentages of PTV receiving 26 Gy in pretreatment and the first, second, and third MRgoART were 82% (range, 19%), 63% (range, 7% to 99%), 88% (range, 31% to 99%), and 95% (range, 3% to 99%), respectively. Comparing pretreatment simulation plans with the best MRgoART plans showed a significant difference (p = 0.025). In the clinical scenario simulation, 16 of the 18 planning series, including nine plans with 95%–99% PTV coverage of 26 Gy and seven plans with increased PTV coverage by 5% or more, would be irradiated at a good timing. Conclusion MRgoART revealed dose coverage differences at each MRgoART timing. Waiting for optimal irradiation timing could be an option in case of suboptimal timing.

Purpose: This study aimed to investigate changes in target coverage using magnetic resonance–guided online adaptive radiotherapy (MRgoART) for kidney tumors and to evaluate the suitable timing of treatment. Materials and Methods: Among patients treated with 3-fraction MRgoART for kidney cancer, 18 tumors located within 1 cm of the gastrointestinal tract were selected. Stereotactic radiosurgery planning with a prescription dose of 26 Gy was performed using pretreatment simulation and three MRgoART timings with an adapt-to-shape method. The best MRgoART plan was defined as the plan achieving the highest percentage of planning target volume (PTV) coverage of 26 Gy. In clinical scenario simulation, MRgoART plans were evaluated in the order of actual treatment. Waiting for the next timing was done when the PTV coverage of 26 Gy did not achieve 95%–99% or did not increase by 5% or more compared to the pretreatment plan. Results: The median percentages of PTV receiving 26 Gy in pretreatment and the first, second, and third MRgoART were 82% (range, 19%), 63% (range, 7% to 99%), 88% (range, 31% to 99%), and 95% (range, 3% to 99%), respectively. Comparing pretreatment simulation plans with the best MRgoART plans showed a significant difference (p = 0.025). In the clinical scenario simulation, 16 of the 18 planning series, including nine plans with 95%–99% PTV coverage of 26 Gy and seven plans with increased PTV coverage by 5% or more, would be irradiated at a good timing. Conclusion MRgoART revealed dose coverage differences at each MRgoART timing. Waiting for optimal irradiation timing could be an option in case of suboptimal timing.

Purpose: This study aimed to investigate changes in target coverage using magnetic resonance–guided online adaptive radiotherapy (MRgoART) for kidney tumors and to evaluate the suitable timing of treatment. Materials and Methods: Among patients treated with 3-fraction MRgoART for kidney cancer, 18 tumors located within 1 cm of the gastrointestinal tract were selected. Stereotactic radiosurgery planning with a prescription dose of 26 Gy was performed using pretreatment simulation and three MRgoART timings with an adapt-to-shape method. The best MRgoART plan was defined as the plan achieving the highest percentage of planning target volume (PTV) coverage of 26 Gy. In clinical scenario simulation, MRgoART plans were evaluated in the order of actual treatment. Waiting for the next timing was done when the PTV coverage of 26 Gy did not achieve 95%–99% or did not increase by 5% or more compared to the pretreatment plan. Results: The median percentages of PTV receiving 26 Gy in pretreatment and the first, second, and third MRgoART were 82% (range, 19%), 63% (range, 7% to 99%), 88% (range, 31% to 99%), and 95% (range, 3% to 99%), respectively. Comparing pretreatment simulation plans with the best MRgoART plans showed a significant difference (p = 0.025). In the clinical scenario simulation, 16 of the 18 planning series, including nine plans with 95%–99% PTV coverage of 26 Gy and seven plans with increased PTV coverage by 5% or more, would be irradiated at a good timing. Conclusion MRgoART revealed dose coverage differences at each MRgoART timing. Waiting for optimal irradiation timing could be an option in case of suboptimal timing.