Idiopathic nonspecific interstitial pneumonia (iNSIP) is recognized as a distinct entity among various types of idiopathic interstitial pneumonias. It is identified histologically by the nonspecific interstitial pneumonia pattern. A diagnosis of iNSIP is feasible once secondary causes or underlying diseases are ruled out. Usually presenting with respiratory symptoms such as shortness of breath and cough, iNSIP has a subacute or chronic course. It predominantly affects females aged 50 to 60 years who are non-smokers. Key imaging findings on chest high-resolution computed tomography include bilateral reticular opacities in lower lungs, traction bronchiectasis, reduced lung volumes and, ground-glass opacities. Abnormalities are typically diffuse across both lungs with subpleural distributions. Treatment often involves systemic steroids, either alone or in combination with other immunosuppressants, although evidence supporting effectiveness of these treatments is limited. Prognosis is generally more favorable for iNSIP than for idiopathic pulmonary fibrosis, with many studies reporting a 5-year survival rate above 70%. Antifibrotic agents should be considered in a condition, termed progressive pulmonary fibrosis, where pulmonary fibrosis progressively worsens.

Background: Kelch-like ECH-associated protein 1 (KEAP1)–nuclear factor erythroid- 2-related factor 2 (NRF2) pathway is a major regulator protecting cells from oxidative and metabolic stress. Studies have revealed that this pathway is involved in mediating resistance to cytotoxic chemotherapy and immunotherapy; however, its implications in oncogene-addicted tumors are largely unknown. This study aimed to elucidate whether this pathway could be a potential therapeutic target for epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer. Methods: We measured the baseline expression of NRF2 using EGFR-mutant parental cells and acquired gefitinib resistant cells. We investigated whether NRF2 inhibition affected cell death in vitro and tumor growth in vivo using a xenograft mouse model, and compared the transcriptional changes before and after NRF2 inhibition. Results: Baseline NRF2 expression was enhanced in PC9 and PC9 with gefitinib resistance (PC9/GR) cells than in other cell lines, with a more prominent expression in PC9/ GR. The NRF2 inhibitor induced NRF2 downregulation and cell death in a dose-dependent manner. Cotreatment with an NRF2 inhibitor enhanced osimertinib-induced cell death in vitro, and potentiated tumor growth inhibition in a PC9/GR xenograft model. Finally, RNA sequencing revealed that NRF2 inhibition resulted in the altered expression of multiple genes involved in various signaling pathways. Conclusion We identified that NRF2 inhibition enhanced cell death and inhibited tumor growth in tyrosine kinase inhibitor (TKI)-resistant lung cancer with EGFR-mutation. Thus, NRF2 modulation may be a novel therapeutic strategy to overcome the resistance to EGFR-TKIs.

Purpose: This study evaluated the educational impact of an artificial intelligence (AI)–based decision support system for breast ultrasonography (US) on medical professionals not specialized in breast imaging. Methods: In this multi-case, multi-reader study, educational materials, including American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) descriptors, were provided alongside corresponding AI results during training. The AI system presented results in the form of AIheatmaps, AI scores, and AI-provided BI-RADS assessment categories. Forty-two readers evaluated the test set in three sessions: the first session (S1) occurred before the educational intervention, the second session (S2) followed education without AI assistance, and the third session (S3) took place after education with AI assistance. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and overall performance, were compared between the sessions. Results: The mean sensitivity increased from 66.5% (95% confidence interval [CI], 59.2% to 73.7%) to 88.7% (95% CI, 84.1% to 93.3%), with a statistically significant difference (P<0.001), and the AUC non-significantly increased from 0.664 (95% CI, 0.606 to 0.723) to 0.684 (95% CI, 0.620 to 0.748) (P=0.300). Both measures were higher in S2 than in S1. The AI-achieved AUC was comparable to that of the expert reader (0.747 [95% CI, 0.640 to 0.855] vs. 0.803 [95% CI, 0.706 to 0.900], P=0.217). Additionally, with AI assistance, the mean AUC for inexperienced readers was not significantly different from that of the expert reader (0.745 [95% CI, 0.660 to 0.830] vs. 0.803 [95% CI, 0.706 to 0.900], P=0.120). Conclusion The mean AUC and sensitivity improved after incorporating AI into breast US education and interpretation. AI systems with high-level performance for breast US can potentially be used as educational tools in the interpretation of breast US images.

This paper aims to review the statistical methods that are widely used in medical and clinical research. Statistical analysis is crucial for ensuring the reliability of research results; therefore, methods should be carefully tailored to research interests and objectives, depending on the type and characteristics of the data. This paper explains various types of data, discusses how to confirm whether the data satisfy these methods’ specific assumptions, and elucidates the meaning and interpretation of univariable and multivariable analysis. Finally, it presents corresponding examples to help other researchers understand how these methods are applied in real-world studies and select appropriate methods that ensure both research quality and reliability.

Idiopathic nonspecific interstitial pneumonia (iNSIP) is recognized as a distinct entity among various types of idiopathic interstitial pneumonias. It is identified histologically by the nonspecific interstitial pneumonia pattern. A diagnosis of iNSIP is feasible once secondary causes or underlying diseases are ruled out. Usually presenting with respiratory symptoms such as shortness of breath and cough, iNSIP has a subacute or chronic course. It predominantly affects females aged 50 to 60 years who are non-smokers. Key imaging findings on chest high-resolution computed tomography include bilateral reticular opacities in lower lungs, traction bronchiectasis, reduced lung volumes and, ground-glass opacities. Abnormalities are typically diffuse across both lungs with subpleural distributions. Treatment often involves systemic steroids, either alone or in combination with other immunosuppressants, although evidence supporting effectiveness of these treatments is limited. Prognosis is generally more favorable for iNSIP than for idiopathic pulmonary fibrosis, with many studies reporting a 5-year survival rate above 70%. Antifibrotic agents should be considered in a condition, termed progressive pulmonary fibrosis, where pulmonary fibrosis progressively worsens.

Background: Kelch-like ECH-associated protein 1 (KEAP1)–nuclear factor erythroid- 2-related factor 2 (NRF2) pathway is a major regulator protecting cells from oxidative and metabolic stress. Studies have revealed that this pathway is involved in mediating resistance to cytotoxic chemotherapy and immunotherapy; however, its implications in oncogene-addicted tumors are largely unknown. This study aimed to elucidate whether this pathway could be a potential therapeutic target for epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer. Methods: We measured the baseline expression of NRF2 using EGFR-mutant parental cells and acquired gefitinib resistant cells. We investigated whether NRF2 inhibition affected cell death in vitro and tumor growth in vivo using a xenograft mouse model, and compared the transcriptional changes before and after NRF2 inhibition. Results: Baseline NRF2 expression was enhanced in PC9 and PC9 with gefitinib resistance (PC9/GR) cells than in other cell lines, with a more prominent expression in PC9/ GR. The NRF2 inhibitor induced NRF2 downregulation and cell death in a dose-dependent manner. Cotreatment with an NRF2 inhibitor enhanced osimertinib-induced cell death in vitro, and potentiated tumor growth inhibition in a PC9/GR xenograft model. Finally, RNA sequencing revealed that NRF2 inhibition resulted in the altered expression of multiple genes involved in various signaling pathways. Conclusion We identified that NRF2 inhibition enhanced cell death and inhibited tumor growth in tyrosine kinase inhibitor (TKI)-resistant lung cancer with EGFR-mutation. Thus, NRF2 modulation may be a novel therapeutic strategy to overcome the resistance to EGFR-TKIs.

Purpose: This study evaluated the educational impact of an artificial intelligence (AI)–based decision support system for breast ultrasonography (US) on medical professionals not specialized in breast imaging. Methods: In this multi-case, multi-reader study, educational materials, including American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) descriptors, were provided alongside corresponding AI results during training. The AI system presented results in the form of AIheatmaps, AI scores, and AI-provided BI-RADS assessment categories. Forty-two readers evaluated the test set in three sessions: the first session (S1) occurred before the educational intervention, the second session (S2) followed education without AI assistance, and the third session (S3) took place after education with AI assistance. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and overall performance, were compared between the sessions. Results: The mean sensitivity increased from 66.5% (95% confidence interval [CI], 59.2% to 73.7%) to 88.7% (95% CI, 84.1% to 93.3%), with a statistically significant difference (P<0.001), and the AUC non-significantly increased from 0.664 (95% CI, 0.606 to 0.723) to 0.684 (95% CI, 0.620 to 0.748) (P=0.300). Both measures were higher in S2 than in S1. The AI-achieved AUC was comparable to that of the expert reader (0.747 [95% CI, 0.640 to 0.855] vs. 0.803 [95% CI, 0.706 to 0.900], P=0.217). Additionally, with AI assistance, the mean AUC for inexperienced readers was not significantly different from that of the expert reader (0.745 [95% CI, 0.660 to 0.830] vs. 0.803 [95% CI, 0.706 to 0.900], P=0.120). Conclusion The mean AUC and sensitivity improved after incorporating AI into breast US education and interpretation. AI systems with high-level performance for breast US can potentially be used as educational tools in the interpretation of breast US images.

Purpose: Cognitive behavioral therapy (CBT) has long been recognized as an effective treatment for depression and suicidality.Virtual reality (VR) technology is widely used for cognitive training for conditions such as anxiety disorder and post-traumatic stress disorder, but little research has considered VR-based CBT for depressive symptoms and suicidality. We tested the effectiveness and safety of a VR-based CBT program for depressive disorders. Materials and Methods: We recruited 57 participants from May 2022 through February 2023 using online advertisements. This multi-center, assessor-blinded, randomized, controlled exploratory trial used two groups: VR treatment group and treat as usual (TAU) group. VR treatment group received a VR mental health training/education program. TAU group received standard pharmacotherapy. Assessments were conducted at baseline, immediately after the 6-week treatment period, and 4 weeks after the end of the treatment period in each group. Results: Depression scores decreased significantly over time in both VR treatment and TAU groups, with no differences between the two groups. The suicidality score decreased significantly only in VR group. No group differences were found in the remission or response rate for depression, perceived stress, or clinical severity. No adverse events or motion sickness occurred during the VR treatment program. Conclusion VR CBT treatment for major depressive disorder has the potential to be equivalent to the gold-standard pharmacotherapy in reducing depressive symptoms, suicidality, and related clinical symptoms, with no difference in improvement found in this study. Thus, VR-based CBT might be an effective alternative to pharmacotherapy for depressive disorders.

Purpose: Telemedicine is advantageous in providing medical care to patients with mobility difficulties. This single-center study aimed to report on the provision of video televisits to people living with amyotrophic lateral sclerosis (pALS, ALS) who were registered with a home-based medical care (HBMC) team in a tertiary hospital in South Korea. Materials and Methods: A retrospective cross-sectional study was conducted for pALS provided with video televisits by the HBMC team between July 2020 and February 2023. The patients’ demographics, disease status, mobility level, and supportive care equipment were investigated. The main issues discussed at televisits were investigated. Results: During the 32-month study period, video televisits were provided to 69 (81.2%) of the 85 pALS registered with the HBMC team. Their median (interquartile range) age was 66 (57–71) years, and 66.7% were aged 60 years or older. At the time of the televisits, 71.0% were non-ambulatory and 27.5% were at an assisted ambulatory level. Furthermore, 82.6% were receiving nutritional support with a nasogastric or gastrostomy tube, and 78.3% had received either non-invasive positive pressure ventilation (43.5%) or tracheostomy invasive ventilation (34.8%). Common issues addressed on televisits were disease-related symptoms (100%), management of supportive care equipment (92.8%), acute health issues (52.2%), and advance care planning (ACP) including goal of care discussion (14.5%). Conclusion Video telemedicine is feasible for pALS, including older adults with limited mobility due to muscle weakness or reliance on various supportive care equipment. Video televisits allow for a variety of discussions, ranging from acute health issues to ACP.

Background: Studies on predictive markers of insulin resistance (IR) and elevated liver transaminases in children and adolescents are limited. We evaluated the predictive capabilities of the single-point insulin sensitivity estimator (SPISE) index, metabolic score for insulin resistance (METS-IR), homeostasis model assessment of insulin resistance (HOMA-IR), the triglyceride (TG)/ high-density lipoprotein cholesterol (HDL-C) ratio, and the triglyceride-glucose index (TyG) for IR and alanine aminotransferase (ALT) elevation in this population. Methods: Data from 1,593 participants aged 10 to 18 years were analyzed using a nationwide survey. Logistic regression analysis was performed with IR and ALT elevation as dependent variables. Receiver operating characteristic (ROC) curves were generated to assess predictive capability. Proportions of IR and ALT elevation were compared after dividing participants based on parameter cutoff points. Results: All parameters were significantly associated with IR and ALT elevation, even after adjusting for age and sex, and predicted IR and ALT elevation in ROC curves (all P<0.001). The areas under the ROC curve of SPISE and METS-IR were higher than those of TyG and TG/HDL-C for predicting IR and were higher than those of HOMA-IR, TyG, and TG/HDL-C for predicting ALT elevation. The proportions of individuals with IR and ALT elevation were higher among those with METS-IR, TyG, and TG/ HDL-C values higher than the cutoff points, whereas they were lower among those with SPISE higher than the cutoff point. Conclusion SPISE and METS-IR are superior to TG/HDL-C and TyG in predicting IR and ALT elevation. Thus, this study identified valuable predictive markers for young individuals.