Proteogenomics of Non-smoking Lung Cancer in East Asia Delineates Molecular Signatures of Pathogenesis and Progression.

Lung cancer in East Asia is characterized by a high percentage of never-smokers, early onset and predominant EGFR mutations. To illuminate the molecular phenotype of this demographically distinct disease, we performed a deep comprehensive proteogenomic study on a prospectively collected cohort in Taiwan, representing early stage, predominantly female, non-smoking lung adenocarcinoma. Integrated genomic, proteomic, and phosphoproteomic analysis delineated the demographically distinct molecular attributes and hallmarks of tumor progression. Mutational signature analysis revealed age- and gender-related mutagenesis mechanisms, characterized by high prevalence of APOBEC mutational signature in younger females and over-representation of environmental carcinogen-like mutational signatures in older females. A proteomics-informed classification distinguished the clinical characteristics of early stage patients with EGFR mutations. Furthermore, integrated protein network analysis revealed the cellular remodeling underpinning clinical trajectories and nominated candidate biomarkers for patient stratification and therapeutic intervention. This multi-omic molecular architecture may help develop strategies for management of early stage never-smoker lung adenocarcinoma.

Comparative Analyses of the Outcomes Between Lobectomies and Trisegmentectomies/Lingulectomies in the Surgical Management of Clinical Stage I Left Upper Lobe Non-small Cell Lung Cancer.

BACKGROUND: Lobectomies are the standard surgical intervention for lung cancer; however, recently, surgeons have considered segmentectomies for smaller tumors, with their potential for favorable survival outcomes while preserving lung function. The surgical outcomes of trisegmentectomies/lingulectomies and lobectomies for clinical stage I left upper lobe (LUL) non-small cell lung cancers (NSCLCs) remain undetermined. Thus, our study aimed to assess the differences between the short-term surgical and long-term survival outcomes in patients with clinical stage I LUL NSCLC who underwent trisegmentectomies/lingulectomies and those who underwent lobectomies. METHODS: Between 2011 and 2021, we retrospectively reviewed the data of 377 patients with clinical stage I NSCLC who had undergone LUL lobectomies or trisegmentectomies/lingulectomies. Patients were categorized into two subcohorts according to tumor size, i.e. 0-2 and 2-4 cm. To ensure preoperative demographic comparability, 1:1 propensity-score matching (PSM) was performed. RESULTS: This study focused on the 2-4 cm subcohort. Post-PSM, patients who underwent trisegmentectomies/lingulectomies had quicker operations and shorter postoperative hospital and intensive care unit lengths of stay than those who underwent lobectomies. Post-PSM, no statistically significant differences in progression-free survival (PFS) or overall survival (OS) were observed between the segmentectomy and lobectomy groups in both the 0-2 and 2-4 cm subcohorts. The multivariate analysis revealed that different surgical methods were not statistically significant factors for either PFS or OS. CONCLUSIONS: Trisegmentectomies/lingulectomies are a feasible option for clinical stage I NSCLC, with better perioperative outcomes and similar survival rates when compared with LUL lobectomies.

CT-Based Deep-Learning Model for Spread-Through-Air-Spaces Prediction in Ground Glass-Predominant Lung Adenocarcinoma.

BACKGROUND: Sublobar resection is strongly associated with poor prognosis in early-stage lung adenocarcinoma, with the presence of tumor spread through air spaces (STAS). Thus, preoperative prediction of STAS is important for surgical planning. This study aimed to develop a STAS deep-learning (STAS-DL) prediction model in lung adenocarcinoma with tumor smaller than 3 cm and a consolidation-to-tumor (C/T) ratio less than 0.5. METHODS: The study retrospectively enrolled of 581 patients from two institutions between 2015 and 2019. The STAS-DL model was developed to extract the feature of solid components through solid components gated (SCG) for predicting STAS. The STAS-DL model was assessed with external validation in the testing sets and compared with the deep-learning model without SCG (STAS-DLwoSCG), the radiomics-based model, the C/T ratio, and five thoracic surgeons. The performance of the models was evaluated using area under the curve (AUC), accuracy and standardized net benefit of the decision curve analysis. RESULTS: The study evaluated 458 patients (institute 1) in the training set and 123 patients (institute 2) in the testing set. The proposed STAS-DL yielded the best performance compared with the other methods in the testing set, with an AUC of 0.82 and an accuracy of 74%, outperformed the STAS-DLwoSCG with an accuracy of 70%, and was superior to the physicians with an AUC of 0.68. Moreover, STAS-DL achieved the highest standardized net benefit compared with the other methods. CONCLUSION: The proposed STAS-DL model has great potential for the preoperative prediction of STAS and may support decision-making for surgical planning in early-stage, ground glass-predominant lung adenocarcinoma.

Plasma Cytokines Pattern as a Prognostic Marker for Esophageal Squamous Cell Carcinoma via Unsupervised Clustering Analyses.

INTRODUCTION: Cytokines such as tumor necrosis factor-alpha (TNF-α), interleukin 6 (IL6), interferon-gamma (IFN-γ), interleukin 17-alpha (IL17-α), and interleukin 33 (IL33) play critical roles in immune responses and may impact cancer prognosis in future. However, few studies have simultaneously explored the prognostic impact of these cytokines for cancer. In this study, we aim to apply the unsupervised clustering analysis to approach the correlation between the expression of these cytokines and the subsequent prognosis of patients with esophageal squamous cell carcinoma (ESCC). METHODS: A robust clustering algorithm was used, the Gaussian mixture method (GMM), through the mclust R package to group patients based on the expression of their cytokines in plasma or tumors. The 324 NTU patients were grouped into 4 clusters, and the 179 GSE53625 patients were grouped into 3 clusters based on expression in plasma and tumors, respectively. Five- and 3-year overall survival (OS) and progression-free survival (PFS) curves of each cluster were compared. Univariate and multivariate Cox regression analyses were also performed. RESULTS: We successfully distinguished the multimodal distribution of cytokines through GMM clustering and discovered the relationship between cytokines and clinical outcomes. We observed that NTU-G3 and NTU-G4 subgroups showed most variation in 5-, 3-year OS and 5-, 3-year PFS with NTU-G3 being associated with poorer prognosis compared to NTU-G4 (p = 0.016, 0.0052, 0.0575, and 0.0168, respectively). NTU-G3 was characterized with higher TNF-α (median = 3.855, N = 78) and lower IL33 (median = 0.000, N = 78), while NTU-G4 showed lower TNF-α (median = 1.76, N = 51) and higher IL33 (median = 1.070, N = 51). The difference was statistically significant for TNF-α and IL33, with p = 0.0002 and p < 0.0001, respectively. A multivariate Cox-regression analysis revealed that GMM clustering and T/N stage were independent factors for prognosis, suggesting that the prognosis might be dependent on these cytokines. CONCLUSIONS: Our data suggest that expression patterns of IL33 and TNF-α in plasma might serve as a convenient marker to predict the prognosis of ESCC in the future.

Applying machine learning to construct an association model for lung cancer and environmental hormone high-risk factors and nursing assessment reconstruction.

INTRODUCTION: To utilize machine learning techniques to develop an association model linking lung cancer and environmental hormones to enhance the understanding of potential lung cancer risk factors and refine current nursing assessments for lung cancer. DESIGN: This study is exploratory in nature. In Stage 1, data were sourced from a biological database, and machine learning methods, including logistic regression and neural-like networks, were employed to construct an association model. Results indicate significant associations between lung cancer and blood cadmium, urine cadmium, urine cadmium/creatinine, and di(2-ethylhexyl) phthalate. In Stage 2, 128 lung adenocarcinoma patients were recruited through convenience sampling, and the model was validated using a questionnaire assessing daily living habits and exposure to environmental hormones. RESULTS: Analysis reveals correlations between the living habits of patients with lung adenocarcinoma and exposure to blood cadmium, urine cadmium, urine cadmium/creatinine, polyaromatic hydrocarbons, diethyl phthalate, and di(2-ethylhexyl) phthalate. CONCLUSIONS: According to the World Health Organization's global statistics, lung cancer claims approximately 1.8 million lives annually, with more than 50% of patients having no history of smoking or non-traditional risk factors. Environmental hormones have garnered significant attention in recent years in pathogen exploration. However, current nursing assessments for lung cancer risk have not incorporated environmental hormone-related factors. This study proposes reconstructing existing lung cancer nursing assessments with a comprehensive evaluation of lung cancer risks. CLINICAL RELEVANCE: The findings underscore the importance of future studies advocating for public screening of environmental hormone toxins to increase the sample size and validate the model externally. The developed association model lays the groundwork for advancing cancer risk nursing assessments.

Identifying group metacognition associated with medical students' teamwork satisfaction in an online small group tutorial context.

BACKGROUND: Collaborative learning is an essential pedagogy in medical education, within which small group learning constitutes an integral component. Online small group teaching has been widely applied and blended with in-person sessions in the aftermath of the Covid-19 pandemic. This study examined whether group metacognition was associated with teamwork satisfaction in an online small group teaching curriculum for medical students. METHODS: We enrolled medical students of the 2nd and 4th years during the 2021 fall semester after they participated in 3 consecutive sessions of online small group tutorials (SGTs), which have been implemented in our medical school for more than 20 years. The students completed a group metacognitive scale (GMS) and a teamwork satisfaction scale (TSS) after the sessions. We analyzed whether group metacognition in 4 dimensions (knowledge of cognition, planning, evaluating, and monitoring) could be connected with medical students' teamwork satisfaction using partial least squares-structural equation modeling (PLS-SEM). RESULTS: A total of 263 medical students participated in this study. Both GMS and TSS exhibited good reliability and validity. Three of the 4 dimensions of group metacognition (cognition, planning, and evaluating) positively correlated with teamwork satisfaction (path coefficients 0.311, 0.279, and 0.21; p = 0.002, 0.002, and 0.043, respectively) following the online SGT curriculum, whereas the monitoring dimension did not (path coefficient 0.087; p = 0.357). The model achieved an adjusted R square of 0.683. CONCLUSION: We discovered that group metacognition correlated positively with better teamwork satisfaction, supporting the importance of group metacognitive competency for online collaborative learning.

Sequential multimodal treatments with chemotherapy and surgery for advanced soft tissue sarcoma may be associated with better survival than chemotherapy.

BACKGROUND: In patients with advanced soft tissue sarcoma (STS), surgery had been reported to be associated with superior overall survival (OS). Chemotherapy details for such patients were less reported, and whether multimodal treatment with surgery and chemotherapy provides extra survival benefit remains unclear. METHODS: We retrospectively reviewed patients with newly diagnosed advanced STS treated at National Taiwan University Hospital from January 1, 2011, to December 31, 2017. OS was calculated from the day of diagnosis of advanced STS to the day of death or last follow-up. Baseline patient characteristics and details regarding surgery and chemotherapy were recorded. RESULTS: A total of 545 patients were diagnosed with STS from 2011 to 2017, of which 226 patients had advanced STS. The median age was 54.7 years, and 54% of patients were women. Approximately 38% of patients with advanced STS underwent surgery and exhibited a trend of longer OS compared with who did not (median = 18.6 vs. 11.9 months, p = 0.083). In the chemotherapy subgroup, the benefit of surgery was more prominent (median = 21.9 vs. 16.5 months, p = 0.037). Patients who received chemotherapy prior to surgery exhibited numerically longer OS than those who underwent surgery first (median = 33.9 vs. 18.3 months, p = 0.155). After adjusting other clinical factors, chemotherapy remained an independent factor associated with favourable OS. CONCLUSION: Surgery may be more beneficial for the patients who receive chemotherapy. Our results support evaluation of sequential multimodal treatments strategy including surgery and chemotherapy in patients with advanced STS.

Discrimination of invasive lung adenocarcinoma from Lung-RADS category 2 nonsolid nodules through visual assessment: a retrospective study.

OBJECTIVES: Invasive adenocarcinomas (IADs) have been identified among nonsolid nodules (NSNs) assigned as Lung Imaging Reporting and Data System (Lung-RADS) category 2. This study used visual assessment for differentiating IADs from noninvasive lesions (NILs) in this category. METHODS: This retrospective study included 222 patients with 242 NSNs, which were resected after preoperative computed tomography (CT)-guided dye localization. Visual assessment was performed by using the lung and bone window (BW) settings to classify NSNs into BW-visible (BWV) and BW-invisible (BWI) NSNs. In addition, nodule size, shape, border, CT attenuation, and location were evaluated and correlated with histopathological results. Logistic regression was performed for multivariate analysis. A p value of < 0.05 was considered statistically significant. RESULTS: A total of 242 NSNs (mean diameter, 7.6 ± 2.8 mm), including 166 (68.6%) BWV and 76 (31.4%) BWI NSNs, were included. IADs accounted for 31% (75) of the nodules. Only 4 (5.3%) IADs were identified in the BWI group and belonged to the lepidic-predominant (n = 3) and acinar-predominant (n = 1) subtypes. In univariate analysis for differentiating IADs from NILs, the nodule size, shape, CT attenuation, and visual classification exhibited statistical significance. Nodule size and visual classification were the significant predictors for IAD in multivariate analysis with logistic regression (p < 0.05). The sensitivity, specificity, positive predictive value, and negative predictive value of visual classification in IAD prediction were 94.7%, 43.1%, 42.8%, and 94.7%, respectively. CONCLUSIONS: The window-based visual classification of NSNs is a simple and objective method to discriminate IADs from NILs. CLINICAL RELEVANCE STATEMENT: The present study shows that using the bone window to classify nonsolid nodules helps discriminate invasive adenocarcinoma from noninvasive lesions. KEY POINTS: • Evidence has shown the presence of lung adenocarcinoma in Lung-RADS category 2 nonsolid nodules. • Nonsolid nodules are classified into the bone window-visible and the bone window-invisible nonsolid nodules, and this classification differentiates invasive adenocarcinoma from noninvasive lesions. • The Lung-RADS category 2 nonsolid nodules are unlikely invasive adenocarcinoma if they show nonvisualization in the bone window.

Wedge Resection Versus Segmentectomy for Older Patients With Stage IA Non-Small-Cell Lung Cancer.

INTRODUCTION: Anatomic lung resection remains the standard of care for early-stage non-small-cell lung cancer (NSCLC), but wedge resection may offer similar survival in older adult patients. The objective of this study was to evaluate the survival of patients aged 80 y and older undergoing wedge resection versus segmentectomy for stage IA NSCLC using a large clinical registry. METHODS: Patients aged 80 y and older in the National Cancer Database who underwent wedge resection or segmentectomy for cT1a-b N0 M0 NSCLC between 2004 and 2018 were identified for an analysis. Survival was assessed using multivariable Cox proportional hazards analysis, propensity-score matching, and inverse probability weighting. A subgroup analysis of patients who underwent lymph node evaluation with their wedge resection or segmentectomy was also performed. RESULTS: Of the 2690 patients identified, 2272 (84%) underwent wedge resection and 418 (16%) underwent segmentectomy. Wedge resection was associated with worse 5-year overall survival relative to segmentectomy in multivariable-adjusted (adjusted Hazard Ratio: 1.26, [1.06-1.51], P = 0.01) and propensity score-matched analysis (49% [95% confidence interval {CI}: 42%-55%] versus 59% [95% CI: 52%-65%], P = 0.02). Among a subgroup of 1221 wedge resection and 347 segmentectomy patients who also received intraoperative lymph node evaluation, however, there were no significant differences in 5-year survival in multivariable-adjusted (adjusted Hazard Ratio: 1.12, [0.90-1.39], P = 0.31) or propensity score-matched analysis (55% [95% CI: 48%-62%] versus 61% [95% CI: 54%-68%], P = 0.10). CONCLUSIONS: In this national analysis, there were no significant differences in survival between older adult patients with stage IA NSCLC who underwent wedge resection versus segmentectomy when a lymph node evaluation was performed.

Uniportal versus multiportal nonintubated thoracoscopic anatomical resection for lung cancer: A propensity-matched analysis.

BACKGROUND/PURPOSE: No studies have compared between uniportal and multiportal nonintubated thoracoscopic anatomical resection for non-small cell lung cancer (NSCLC). We aimed to compare short- and long-term postoperative outcomes concerning these two methods. METHODS: Our retrospective dataset comprised patients with NSCLC who underwent uniportal or multiportal nonintubated thoracoscopic anatomical resection between January 2011 and December 2019. The primary outcome was recurrence-free survival. Propensity scores were matched according to age, sex, body mass index, pulmonary function, tumor size, cancer stage, and surgical method. RESULTS: In total, 1130 such patients underwent nonintubated video-assisted thoracoscopic surgery (VATS), and 490 consecutive patients with stage I-III NSCLC underwent nonintubated anatomical resection, including lobectomy and segmentectomy (uniportal, n = 158 [32.3%]; multiportal, n = 331 [67.7%]). The uniportal group had fewer dissected lymph nodes and lymph node stations. In paired group analysis, the uniportal group had shorter operation durations (99.8 vs. 138.2 min; P < 0.001), lower intensive care unit (ICU) admission rates and ICU admission intervals (7.0% vs. 27.8%; P < 0.001), and shorter postoperative hospital stays (4.1 days vs. 5.2 days; P < 0.001). The most common postoperative complication was prolonged air leaks. No surgical mortality was observed. The multiportal group had higher complication rates for grades ≥ II NSCLC; however, this difference was not significant (4.4% vs. 1.3%, respectively; P = 0.09). CONCLUSION: Nonintubated uniportal VATS for anatomical resection had better results for some perioperative outcomes than multiportal VATS. Oncological outcomes such as recurrence-free and overall survival remained uncompromised, despite fewer dissected lymph nodes.

Primary Tumor Resection for Stage IV Non-small-cell Lung Cancer Without Progression After First-Line Epidermal Growth Factor Receptor-Tyrosine Kinase Inhibitor Treatment: A Retrospective Case-Control Study.

BACKGROUND: In studies of stage IV epidermal growth factor receptor (EGFR)-mutant nonsmall-cell lung cancer (NSCLC), <10% of patients underwent surgery; thus, the effect of surgery in these patients remains unclear. We investigated whether primary lung tumor resection could improve the survival of patients with stage IV EGFR-mutant NSCLC without progression after first-line EGFR-tyrosine kinase inhibitor (EGFR-TKI) treatment. METHODS: This retrospective case-control study included patients treated with first-line EGFR-TKIs without progression on follow-up imaging. Patients in the surgery group (n = 56) underwent primary tumor resection, followed by TKI maintenance therapy. Patients in the control group (n = 224; matched for age, metastatic status, and Eastern Cooperative Oncology Group performance status) received only TKI maintenance therapy. Local ablative therapy for distant metastasis was allowed in both groups. The primary endpoint was progression-free survival. The secondary endpoints were overall survival, failure patterns, and complications/adverse events. RESULTS: The median time from TKI treatment to surgery was 5.1 months. For the surgery and control groups, the median follow-up periods were 34.0 and 38.5 months, respectively, with a median (95% confidence interval) progression-free survival of 29.6 (18.9-40.3) and 13.0 (11.8-14.2) months, respectively (P < 0.001). Progression occurred in 29/56 (51.8%) and 207/224 (92.4%) patients, respectively. The median overall survival in the surgery group was not reached. The rate of surgical complications of grade ≥2 was 12.5%; complications were treated conservatively. CONCLUSIONS: Primary tumor resection is feasible for patients with EGFR-mutant nonprogressed NSCLC during first-line EGFR-TKI treatment and may improve survival better than maintenance EGFR-TKI therapy alone.

Solid Attenuation Components Attention Deep Learning Model to Predict Micropapillary and Solid Patterns in Lung Adenocarcinomas on Computed Tomography.

BACKGROUND: High-grade adenocarcinoma subtypes (micropapillary and solid) treated with sublobar resection have an unfavorable prognosis compared with those treated with lobectomy. We investigated the potential of incorporating solid attenuation component masks with deep learning in the prediction of high-grade components to optimize surgical strategy preoperatively. METHODS: A total of 502 patients with pathologically confirmed high-grade adenocarcinomas were retrospectively enrolled between 2016 and 2020. The SACs attention DL model was developed to apply solid-attenuation-component-like subregion masks (tumor area ≥ - 190 HU) to guide the DL model for predicting high-grade subtypes. The SACA-DL was assessed using 5-fold cross-validation and external validation in the training and testing sets, respectively. The performance, which was evaluated using the area under the curve (AUC), was compared between SACA-DL and the DL model without SACs attention (DLwoSACs), the prior radiomics model, or the model based on the consolidation/tumor (C/T) diameter ratio. RESULTS: We classified 313 and 189 patients into training and testing cohorts, respectively. The SACA-DL achieved an AUC of 0.91 for the cross-validation, which was significantly superior to those of the DLwoSACs (AUC = 0.88; P = 0.02), prior radiomics model (AUC = 0.85; P = 0.004), and C/T ratio (AUC = 0.84; P = 0.002). An AUC of 0.93 was achieved for external validation in the SACA-DL and was significantly better than those of the DLwoSACs (AUC = 0.89; P = 0.04), prior radiomics model (AUC = 0.85; P < 0.001), and C/T ratio (AUC = 0.85; P < 0.001). CONCLUSIONS: The combination of solid-attenuation-component-like subregion masks with the DL model is a promising approach for the preoperative prediction of high-grade adenocarcinoma subtypes.

Moving from tangibility toward digitalization: investigating team dynamics and facilitator support among medical students in conventional and digital small-group tutorials.

BACKGROUND: Small group tutorials (SGT) promotes self-directed learning and is widely used in medical education. The coronavirus pandemic (COVID-19) has accelerated the trend toward SGT digitalization, with unclear effect. We hypothesize that team dynamics and facilitator support influence SGT satisfaction in digital versus conventional SGT. METHODS: During the spring semester of year 2021, medical students (the second, third, and fourth year; n = 433) participating in conventional face-to-face and digital SGT curricula were enrolled. Participating students completed the collaborative learning attitude scale (including team dynamics, team acquaintance, and facilitator support dimensions) and teamwork satisfaction scale, previously validated for small-group collaborative learning, and chose preference between conventional or digital SGT in future curricula. Exploratory factor analysis (EFA) was performed to extract the essential structural factors of these scales. Paired t-tests were conducted to compare differences in different dimensions and satisfaction between the conventional and digital SGT settings. Two sets of multiple regression analyses were done; one with team satisfaction scale results and the other with preference for digital SGT as the dependent variable were used to evaluate determinants of these two variables. RESULTS: The EFA results revealed that the original collaborative learning attitude scale was concentrated on two dimensions: team dynamics and facilitator support. No significant differences were noted between the SGT settings for the two dimensions and teamwork satisfaction. Regression analyses showed that teamwork dynamics was independently correlated with teamwork satisfaction in both conventional and digital SGT. Facilitator support was positively correlated with teamwork satisfaction in conventional, but not digital SGT. Higher teamwork satisfaction was an important determinant of preference for digital SGT among medical students. CONCLUSIONS: Team dynamics were closely linked to teamwork satisfaction among medical students in both conventional and digital SGT, while the role of facilitator support became less obvious during digital SGT.

Effectiveness of tutor shadowing on faculty development in problem-based learning.

BACKGROUND: To enhance tutors' teaching skills, tutor shadowing for novice tutors of problem-based learning (PBL) in addition to conventional faculty development (FD) was applied. This study aimed to develop a tutoring-skill scale (TS-scale) and evaluate the effect of shadowing on PBL tutors. METHODS: This study employed a before-and-after study design with three phases. In phase 1, a TS-scale was elaborated. A validity examination was performed in phase 2. Phase 3 was a study of the effectiveness using a TS-scale survey of novice PBL tutors before and after the FD course. The FD course for novice PBL tutors included an FD workshop and PBL shadowing activities. RESULTS: A TS-scale with a 32-item questionnaire of self-rated confidence for PBL tutors was identified in phase 1. In phase 2, 7 experienced specialists in medical education were invited to evaluate the content validity of the scale. The item content validity index (I-CVI) ranged from 0.86 to 1, and the scale-CVI (S-CVI) was 0.95. A total of 85 novice PBL tutors completed the TS-scale before the FD course, yielding a Cronbach's alpha of 0.98. An exploratory factor analysis with varimax rotation was performed. The twenty-four items with significant loadings greater than 0.5 were incorporated into a new TS-scale and were grouped into three factors: student contact, medical expertise, and teaching expertise. In phase 3, 76 novice PBL tutors completed the 24-item TS-scale before (pretest) and after (posttest) the FD course. Their self-rated confidence improved significantly across the three factors after the FD course. The pretest and posttest scores did not differ according to the tutors' gender, the grades they taught, or their specialty background. CONCLUSIONS: Novice PBL tutors benefit from FD that incorporates tutor shadowing in the 3 key domains of tutoring competencies. The TS-scale developed in this study can be applied in future research on FD design.

Fully digital problem-based learning for undergraduate medical students during the COVID-19 period: Practical considerations.

Digital problem-based learning (PBL) was originally introduced as a means to improve student engagement and increase flexibility. However, its use becomes mandatory during the coronavirus disease 2019 (COVID-19) period, accelerating changes in medical education. Few elaborated on the implementation details of digital PBL curricula. Technical guidance can be important but under-recognized prerequisite of a successful digital PBL session. In National Taiwan University College of Medicine, we established a digital PBL curriculum and previously validated a confidence questionnaire for surveying undergraduate students receiving digital PBL sessions. In this opinion piece, we gleaned multiple procedural details from our experiences based on students'/tutors' feedback, which we summarized in a 5″W″ recommendations (Who), timing/duration (When), location (Where), software/hardware/topics (What), and evaluation aspects (Why). Suggestions on how to optimally prepare for digital PBL session are also provided. We believe that these tips can further facilitate the wide adoption of digital PBL.

Undiagnosed solitary caseating granulomas: Is lung resection surgery a feasible method for diagnosis and treatment?

BACKGROUND: In many patients, low-dose computed tomography (CT) screening for lung cancer reveals asymptomatic pulmonary nodules. Lung resection surgery may be indicated in these patients; however, distinguishing malignancies from benign lesions preoperatively can be challenging. METHODS: From 2013 to 2018, 4181 patients undergoing surgery for pulmonary nodules were reviewed at National Taiwan University Hospital, and 837 were diagnosed with benign pathologies. Only patients with pathological diagnosis as caseating granulomatous inflammation were included, sixty-nine patients were then analyzed for preoperative clinical and imaging characteristics, surgical methods and complications, pathogens, medical treatment and outcomes. Mycobacterial evidence was obtained from the culture of respiratory or surgical specimen. RESULTS: Overall, 68% of the patients were asymptomatic before surgery. More than half of the nodules were in the upper lobes, and all patients underwent video-assisted thoracoscopic surgery (VATS). Some patients (14.5%) developed grade I complications, and the mean postoperative hospital stay was 4 days. The final pathology reports of 20% benign entities postoperatively, and caseating granulomatous inflammation accounted for a significant part. MTB and NTM were cultured from one-fourth of the patients respectively. All patients with confirmed MTB infection received antimycobacterial treatment, while the medical treatment in NTM-infected patients was decided by the infectious disease specialists. The mean follow-up period was 736 days, and no recurrence was found. CONCLUSION: Lung resection surgery is an aggressive but safe and feasible method for diagnosing MTB- or NTM-associated pulmonary nodules, and, potentially, an effective therapeutic tool for patients with undiagnosed MTB- or NTM-associated pulmonary nodules.

Indocyanine green imaging to identify intralobar pulmonary sequestration for uniportal thoracoscopic resection.

Surgical excision of pulmonary sequestration is a definite treatment, but dissection of the arterial supply from systemic circulation and determination of the boundary are always challenging. We reported a case utilising pre-operative three-dimensional reconstruction and indocyanine green injection to make the procedure minimally invasive, precise and safe.

The Long-Term Clinical Impact of Thoracic Endovascular Aortic Repair (TEVAR) for Advanced Esophageal Cancer Invading Aorta.

BACKGROUND: Advanced esophageal cancer invading the aorta is considered unsuitable for surgery with definitive chemotherapy or chemoradiation as the treatments of choice. In the current study, we evaluated the long-term clinical impact of combining thoracic endovascular aortic repair (TEVAR) with multimodality treatment in caring for such patients. METHODS: We evaluated 48 patients who had advanced esophageal cancer with aortic invasion. The oncological outcome, including overall survival (OS) and progression-free survival (PFS), after multimodality treatment with or without TEVAR is evaluated for these patients. RESULTS: Overall, 25/48 patients (52.1%) received a TEVAR procedure. There was no significant difference in OS (p = 0.223) between patients who did or did not receive TEVAR; however, patients who received TEVAR had significantly less local tumor recurrence (p = 0.020) and longer PFS (p = 0.019). This impact was most evident in patients who received both TEVAR and esophagectomy, with an incremental increase in hazard ratio (HR) for disease progression of 2.89 (95% confidence interval [CI] 0.86-9.96) and 4.37 (95% CI 1.33-14.33) observed under multivariable analysis, respectively, in comparison with patients who underwent only one or neither of these procedures (p = 0.005 for trend test). CONCLUSION: TEVAR is a feasible procedure for esophageal cancers invading the aorta and can be used for curative-intent resection to improve local tumor control and PFS.

Thoracoscopic Wedge Resection Versus Segmentectomy for cT1N0 Lung Adenocarcinoma.

BACKGROUND: The choice between wedge resection and segmentectomy as a sublobar resection method for patients with cT1N0 lung cancer remains debatable. This study aimed to evaluate the clinical outcomes after wedge resection and segmentectomy for patients with cT1N0 lung adenocarcinoma. METHODS: The study enrolled 1002 consecutive patients with cT1N0 lung adenocarcinoma who underwent sublobar resection at the authors' institution between 2011 and 2017. A propensity score-matching analysis was used to compared the clinical outcomes between the wedge resection and segmentectomy groups. RESULTS: Wedge resection was performed for 810 patients (80.8%), and segmentectomy was performed for 192 patients (19.2%). Wedge resection resulted in better perioperative outcomes than segmentectomy. The multivariate analysis showed that the significant risk factors for poor disease-free survival (DFS) were elevated preoperative serum carcinoembryonic antigen levels, total tumor diameter greater than 2 cm, and a consolidation-to-tumor (C/T) ratio higher than 50%. After propensity-matching, no differences in overall survival or DFS were noted between the two matched groups. However, subgroup analysis showed that segmentectomy was associated with better DFS than wedge resection (p = 0.039) for the patients with a tumor diameter greater than 2 cm and a C/T ratio higher than 50%. CONCLUSION: Segmentectomy is the appropriate surgical method for sublobar resection in cT1N0 lung adenocarcinoma patients with a tumor diameter greater than 2 cm and a C/T ratio higher than 50%. Wedge resection may be a safe and feasible sublobar resection method for patients with a tumor diameter of 2 cm or smaller or a C/T ratio of 50% or lower.

Prediction of micropapillary and solid pattern in lung adenocarcinoma using radiomic values extracted from near-pure histopathological subtypes.

OBJECTIVES: Near-pure lung adenocarcinoma (ADC) subtypes demonstrate strong stratification of radiomic values, providing basic information for pathological subtyping. We sought to predict the presence of high-grade (micropapillary and solid) components in lung ADCs using quantitative image analysis with near-pure radiomic values. METHODS: Overall, 103 patients with lung ADCs of various histological subtypes were enrolled for 10-repetition, 3-fold cross-validation (cohort 1); 55 were enrolled for testing (cohort 2). Histogram and textural features on computed tomography (CT) images were assessed based on the "near-pure" pathological subtype data. Patch-wise high-grade likelihood prediction was performed for each voxel within the tumour region. The presence of high-grade components was then determined based on a volume percentage threshold of the high-grade likelihood area. To compare with quantitative approaches, consolidation/tumour (C/T) ratio was evaluated on CT images; we applied radiological invasiveness (C/T ratio > 0.5) for the prediction. RESULTS: In cohort 1, patch-wise prediction, combined model (C/T ratio and patch-wise prediction), whole-lesion-based prediction (using only the "near-pure"-based prediction model), and radiological invasiveness achieved a sensitivity and specificity of 88.00 ± 2.33% and 75.75 ± 2.82%, 90.00 ± 0.00%, and 77.12 ± 2.67%, 66.67% and 90.41%, and 90.00% and 45.21%, respectively. The sensitivity and specificity, respectively, for cohort 2 were 100.0% and 95.35% using patch-wise prediction, 100.0% and 95.35% using combined model, 75.00% and 95.35% using whole-lesion-based prediction, and 100.0% and 69.77% using radiological invasiveness. CONCLUSION: Using near-pure radiomic features and patch-wise image analysis demonstrated high levels of sensitivity and moderate levels of specificity for high-grade ADC subtype-detecting. KEY POINTS: • The radiomic values extracted from lung adenocarcinoma with "near-pure" histological subtypes provide useful information for high-grade (micropapillary and solid) components detection. • Using near-pure radiomic features and patch-wise image analysis, high-grade components of lung adenocarcinoma can be predicted with high sensitivity and moderate specificity. • Using near-pure radiomic features and patch-wise image analysis has potential role in facilitating the prediction of the presence of high-grade components in lung adenocarcinoma prior to surgical resection.