In recent years, non-cognitive abilities have garnered attention, and their significance is attributed to overall well-being. Social Emotional Learning (SEL) is an educational program specifically focused on the social and emotional aspects of non-cognitive abilities. The domains of SEL are divided into self-awareness, self-management, social awareness, relationship skills, and responsible decision-making. These can be incorporated into various educational settings, including classroom instruction and extracurricular activities. While SEL is primarily introduced in elementary education, non-cognitive abilities remain crucial for higher education and professional training as they both learners and educators.

To educate medical professionals to meet the needs of future medical care, which will be highly complex and require a broader perspective, it is not enough to provide education that emphasizes positivism based on natural scientific thinking, such as clinical reasoning. It is also important to provide education based on a phenomenological perspective that seeks to understand patients’ experiences in the living world and their meaning, as seen in biopsychosocial models. We have developed an online class on clinical reasoning for fourth-year medical students prior to clinical practice, in which students can simultaneously learn clinical reasoning and biopsychosocial models through structured case studies. We expect that this teaching model will be widely adopted, as it allows students to learn both positivist and phenomenological perspectives, and to view patients as individuals in their daily lives, through a multifaceted learning experience using the same case study.

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.

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.

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.

Methods: The study participants were 249 patients who underwent intradiscal condoliase injection for LDH at nine participating institutions, including 241 patients with initial LDH (group C) and eight with recurrent LDH (group R). Patient characteristics including age, sex, body mass index, disease duration, intervertebral LDH level, smoking history, and diabetes history were evaluated. Low back pain/leg pain Numerical Rating Scale (NRS) scores and the Oswestry Disability Index (ODI) were used to evaluate clinical symptoms before treatment and at 6 months and 1 year after treatment. Results: Low back pain NRS scores (before treatment and at 6 months and 1 year after treatment, respectively) in group C (4.9 → 2.6 → 1.8) showed significant improvement until 1 year after treatment. Although a tendency for improvement was observed in group R (3.5 → 2.8 → 2.2), no significant difference was noted. Groups C (6.6 → 2.4 → 1.4) and R (7.0 → 3.1 → 3.2) showed significant improvement in the leg pain NRS scores after treatment. Group C (41.4 → 19.5 → 13.7) demonstrated significant improvement in the ODI up to 1 year after treatment; however, no significant difference was found in group R (35.7 → 31.7 → 26.4). Conclusions Although intradiscal condoliase injection is less effective for LDH recurrence than for initial cases, it is useful for improving leg pain and can be considered a minimally invasive and safe treatment method.

Objective: To assess the relationships between phase angle and muscle mass, strength, and physical function in patients with heart failure. Methods: This study used a cross-sectional design. The analysis included 51 patients with heart failure. The Short Physical Performance Battery, one-leg standing time, handgrip strength, phase angle, and skeletal muscle index were measured. To identify explanatory variables of phase angle, hierarchical multiple regression analysis was performed. Results: Handgrip strength was found to be an explanatory variable of phase angle independent of age, sex, and body mass index. This model was able to explain 30.4% of the model variance for phase angle. Conclusion In patients with heart failure, improving muscle strength rather than muscle mass or physical function might be more important for improving phase angle. Handgrip strength is an important outcome for improving prognosis in patients with heart failure.

Due to the importance of developing physicians' competencies to utilize information, science, and technology, the 2022 revision of the Model Core Curriculum for Medical Education newly established guidelines for qualities and competencies, which it refers to as "Competencies to utilize information, science, and technology." The Model Core Curriculum outlines these qualities as "understanding the ever-developing information society and practicing medical research and treatment while utilizing information, science and technology such as artificial intelligence." The guidelines are organized by the three perspectives of "ethical viewpoints and rules for dealing with information, science and technology," "principles of information, science and technology necessary for medicine and its surrounding society," and "utilization of information, science and technology in the medical field." The objectives of the course were set from the three perspectives of "ethics and rules for dealing with information, science and technology," "principles of information, science and technology necessary for medicine and the society surrounding it," and "utilization of information, science and technology in medical practice." We looked back on the process of formulating these qualities and competencies, which will become increasingly important, and discussed their future prospects.