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.

Purpose: The study aimed to compare the diagnostic performance of washout-parametric imaging (WOPI) with that of conventional contrast-enhanced ultrasound (cCEUS) in differentiating focal liver lesions (FLLs). Methods: A total of 181 FLLs were imaged with contrast-enhanced ultrasound using Sonazoid, and the recordings were captured for 10 minutes in a prospective setting. WOPI was constructed from three images, depicting the arterial phase (peak enhancement), the early portal venous phase (1-minute post-injection), and the vasculo-Kupffer phase (5 or 10 minutes post-injection). The intensity variations in these images were color-coded and superimposed to produce a single image representing the washout timing across the lesions. From the 181 FLLs, 30 hepatocellular carcinomas (HCCs), 30 non-HCC malignancies, and 30 benign lesions were randomly selected for an observer study. Both techniques (cCEUS and WOPI) were evaluated by four off-site readers. They classified each lesion as benign or malignant using a continuous rating scale, with the endpoints representing "definitely benign" and "definitely malignant." The diagnostic performance of cCEUS and WOPI was compared using the area under the receiver operating characteristic curve (AUC) with the DeLong test. Interobserver agreement was assessed using the intraclass correlation coefficient (ICC). Results: The difference in average AUC values between WOPI and cCEUS was 0.0062 (95% confidence interval, -0.0161 to 0.0285), indicating no significant difference between techniques. The interobserver agreement was higher for WOPI (ICC, 0.77) than cCEUS (ICC, 0.67). Conclusion The diagnostic performance of WOPI is comparable to that of cCEUS in differentiating FLLs, with superior interobserver agreement.

Purpose: The study aimed to compare the diagnostic performance of washout-parametric imaging (WOPI) with that of conventional contrast-enhanced ultrasound (cCEUS) in differentiating focal liver lesions (FLLs). Methods: A total of 181 FLLs were imaged with contrast-enhanced ultrasound using Sonazoid, and the recordings were captured for 10 minutes in a prospective setting. WOPI was constructed from three images, depicting the arterial phase (peak enhancement), the early portal venous phase (1-minute post-injection), and the vasculo-Kupffer phase (5 or 10 minutes post-injection). The intensity variations in these images were color-coded and superimposed to produce a single image representing the washout timing across the lesions. From the 181 FLLs, 30 hepatocellular carcinomas (HCCs), 30 non-HCC malignancies, and 30 benign lesions were randomly selected for an observer study. Both techniques (cCEUS and WOPI) were evaluated by four off-site readers. They classified each lesion as benign or malignant using a continuous rating scale, with the endpoints representing "definitely benign" and "definitely malignant." The diagnostic performance of cCEUS and WOPI was compared using the area under the receiver operating characteristic curve (AUC) with the DeLong test. Interobserver agreement was assessed using the intraclass correlation coefficient (ICC). Results: The difference in average AUC values between WOPI and cCEUS was 0.0062 (95% confidence interval, -0.0161 to 0.0285), indicating no significant difference between techniques. The interobserver agreement was higher for WOPI (ICC, 0.77) than cCEUS (ICC, 0.67). Conclusion The diagnostic performance of WOPI is comparable to that of cCEUS in differentiating FLLs, with superior interobserver agreement.