Headaches caused by metastatic brain tumors result from dural tension and traction of the sites of nociceptive nerves that originates from displacement of cerebral vessels and intracranial hypertension caused by the tumor. Causes of such headaches also include meningeal irritation resulting from intrathecal dissemination of tumor and carcinomatous meningitis.Treatment of headaches resulting from intracranial hypertension involves alleviation of cerebral edema and reduction of intracranial pressure using hyperosmolar therapy and steroid administration, but treatment is often complicated by a lack of pressure reduction. We encountered 2 cases of headaches with intracranial hypertension that did not improve following hyperosmolar therapy and steroid administration, but resolved with increased opioid dose.In cases where intracranial pressure does not decrease, or for headaches attributed to direct stimulus of intracranial nociceptive nerves rather than intracranial hypertension, attempts to treat the patient with initiation or increased dosage of opioids may prove effective from a clinical standpoint.

Along with clinical practice and education, research is among the most important activities for medical doctors. The same is true in cardiovascular surgery: Young cardiovascular surgeons are expected to improve their surgical techniques and prioritize their clinical practice. However, their perspective on the role of research in their field of expertise is unknown. Therefore, we conducted a survey of and discussion with young cardiovascular surgeons to clarify their thoughts and concerns about performing research. Here we review and report the survey and discussion results.

BACKGROUND/AIMS: Both fecal immunochemical test (FIT) and fecal calprotectin (Fcal) results are useful biomarkers for ulcerative colitis (UC). However, the situations in which each marker should be used are largely unknown. METHODS: A total of 110 colonoscopy intervals of UC patients were assessed, and correlations between changes in colonoscopic findings and changes in the two aforementioned fecal markers were examined. RESULTS: Among patients with mucosal healing (MH) and negative FIT or Fcal results at the initial colonoscopy, FIT and Fcal findings exhibited accuracies of 93% (38/41) and 79% (26/33), respectively, for predicting the results of the subsequent examination. Among the 24 patients who showed endoscopic activity at the precedent colonoscopy and MH at the subsequent examination, positive-to-negative conversion of FIT and Fcal findings at the subsequent examination was observed in 92% (12/13) and 62% (8/13) of patients, respectively. Among the 43 patients who showed endoscopic activity at both the precedent and subsequent examinations, Fcal findings reflected the change in endoscopic activity better than FIT results (r=0.59, p<0.0001 vs r=0.30, p=0.054). CONCLUSIONS: The FIT is useful for confirming MH and the occurrence of relapse. In contrast, Fcal is useful for monitoring the mucosal status of patients with active inflammation.
Biomarkers ; Colitis ; Colitis, Ulcerative* ; Colonoscopy ; Humans ; Inflammation ; Leukocyte L1 Antigen Complex* ; Recurrence ; Ulcer*

BACKGROUND/AIMS: Fecal calprotectin (Fcal) as well as the fecal immunochemical test (FIT) are useful biomarkers for detecting activity and mucosal healing in inflammatory bowel diseases. Here, we report the performance of simultaneous measurements of Fcal and FIT for ulcerative colitis (UC) patients using the newly-developed latex agglutination turbidimetric immunoassay (LATIA) system. METHODS: Fcal and hemoglobin were measured by the LATIA system in 152 UC patients who underwent colonoscopy. Fcal was also quantified with a conventional enzyme-linked immunosorbent assay (ELISA). Fecal markers were evaluated in conjunction with the mucosal status of UC, which was assessed via the Mayo endoscopic subscore (MES) classification. RESULTS: The LATIA system could quantify calprotectin and hemoglobin simultaneously with the same fecal samples within 10 minutes. The values of the Fcal-LATIA closely correlated with those of the Fcal-ELISA (Spearman rank correlation coefficient, r=0.84; P<0.0001). The values of Fcal for each assay and the FIT all significantly correlated with the MESs (Spearman rank correlation coefficient, Fcal-LATIA: r=0.58, Fcal-ELISA: r=0.55, and FIT: r=0.72). The mucosal healing predictability (determined by an MES of 0 alone) of the Fcal-LATIA, Fcal-ELISA, and FIT-LATIA with the cutoffs determined by receiver operating characteristic curve analysis was 0.79, 0.78, and 0.92 for sensitivity, respectively, and 0.78, 0.69, and 0.73 for specificity, respectively. CONCLUSIONS: The performance of the novel Fcal-LATIA was equivalent to that of the conventional Fcal assay. Simultaneous measurements with FITs would promote the clinical relevance of fecal biomarkers in UC.
Agglutination ; Biomarkers ; Classification ; Colitis, Ulcerative ; Colonoscopy ; Enzyme-Linked Immunosorbent Assay ; Feces ; Humans ; Immunoassay ; Inflammatory Bowel Diseases ; Latex ; Leukocyte L1 Antigen Complex ; ROC Curve ; Sensitivity and Specificity

BACKGROUND/AIMS: Although mucosal healing (MH) has been considered a treatment goal for patients with ulcerative colitis (UC), the risk factors predictive of relapse in patients who achieve MH are unknown. Because the platelet count has been shown to be a marker of inflammation in inflammatory bowel diseases, this study aimed to assess whether the platelet count could predict relapse in UC patients with MH. METHODS: A prospective observational study was performed. UC patients with MH were consecutively enrolled in the study and monitored for at least 2 years or until relapse. The correlation between the incidence of relapse and the platelet count at the time of study enrollment was examined. RESULTS: In total, 43 patients were enrolled, and 14 patients (33%) relapsed. The median platelet count at the time of enrollment in the patients who relapsed significantly differed from that in the patients who did not relapse (27.2×104/μL vs 23.8×104/μL, respectively; p=0.016). A platelet count >25.0×104/μL was a significant risk factor for relapse based on a multivariate analysis (hazard ratio, 4.85; 95% confidence interval, 1.07 to 25.28), and according to the Kaplan-Meier analysis, this cutoff could identify patients susceptible to relapse (p=0.041, log-rank test). CONCLUSIONS: The platelet count could be used as a predictor of relapse in UC patients with MH.
Blood Platelets* ; Colitis ; Colitis, Ulcerative* ; Humans ; Incidence ; Inflammation ; Inflammatory Bowel Diseases ; Kaplan-Meier Estimate ; Multivariate Analysis ; Observational Study ; Platelet Count* ; Prospective Studies ; Recurrence* ; Risk Factors ; Ulcer*

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.