Improved stent sharpness evaluation with Super-Resolution deep learning reconstruction in coronary computed tomography angiography.

OBJECTIVES: This study aimed to assess the impact of super-resolution deep learning reconstruction (SR-DLR) on coronary computed tomography angiography (CCTA) image quality and blooming artifacts from coronary artery stents in comparison to conventional methods, including hybrid iterative reconstruction (HIR) and deep learning-based reconstruction (DLR). METHODS: A retrospective analysis included sixty-six CCTA patients from July to November 2022. Major coronary arteries were evaluated for image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). Stent sharpness was quantified using 10-90% edge rise slope (ERS) and 10-90% edge rise distance (ERD). Qualitative analysis employed a 5-point scoring system to assess overall image quality, image noise, vessel wall, and stent structure. RESULTS: SR-DLR demonstrated significantly lower image noise compared to HIR and DLR. SNR and CNR were notably higher in SR-DLR. Stent ERS was significantly improved in SR-DLR, with mean ERD values of 0.70 ± 0.20 mm for SR-DLR, 1.13 ± 0.28 mm for HIR, and 0.85 ± 0.26 mm for DLR. Qualitatively, SR-DLR scored higher in all categories. CONCLUSIONS: SR-DLR produces images with lower image noise, leading to improved overall image quality, compared with HIR and DLR. SR-DLR is a valuable image reconstruction algorithm for enhancing the spatial resolution and sharpness of coronary artery stents without being constrained by hardware limitations. ADVANCED IN KNOWLEDGE: The overall image quality was significantly higher in SR-DLR, resulting in sharper coronary artery stents compared to HIR and DLR.

Use of a commercial artificial intelligence-based mammography analysis software for improving breast ultrasound interpretations.

OBJECTIVES: To evaluate the use of a commercial artificial intelligence (AI)-based mammography analysis software for improving the interpretations of breast ultrasound (US)-detected lesions. METHODS: A retrospective analysis was performed on 1109 breasts that underwent both mammography and US-guided breast biopsy. The AI software processed mammograms and provided an AI score ranging from 0 to 100 for each breast, indicating the likelihood of malignancy. The performance of the AI score in differentiating mammograms with benign outcomes from those revealing cancers following US-guided breast biopsy was evaluated. In addition, prediction models for benign outcomes were constructed based on clinical and imaging characteristics with and without AI scores, using logistic regression analysis. RESULTS: The AI software had an area under the receiver operating characteristics curve (AUROC) of 0.79 (95% CI, 0.79-0.82) in differentiating between benign and cancer cases. The prediction models that did not include AI scores (non-AI model), only used AI scores (AI-only model), and included AI scores (integrated model) had AUROCs of 0.79 (95% CI, 0.75-0.83), 0.78 (95% CI, 0.74-0.82), and 0.85 (95% CI, 0.81-0.88) in the development cohort, and 0.75 (95% CI, 0.68-0.81), 0.82 (95% CI, 0.76-0.88), and 0.84 (95% CI, 0.79-0.90) in the validation cohort, respectively. The integrated model outperformed the non-AI model in the development and validation cohorts (p < 0.001 for both). CONCLUSION: The commercial AI-based mammography analysis software could be a valuable adjunct to clinical decision-making for managing US-detected breast lesions. CLINICAL RELEVANCE STATEMENT: The commercial AI-based mammography analysis software could potentially reduce unnecessary biopsies and improve patient outcomes. KEY POINTS: • Breast US has high rates of false-positive interpretations. • A commercial AI-based mammography analysis software could distinguish mammograms having benign outcomes from those revealing cancers after US-guided breast biopsy. • A commercial AI-based mammography analysis software may improve interpretations for breast US-detected lesions.

Type 4 Dual Left Anterior Descending Artery: A Case Report of a Rare Congenital Coronary Anomaly.

Dual left anterior descending artery (LAD) is a rare congenital coronary artery anomaly with a prevalence of approximately 1% in the general population. To date, 10 types of dual LAD artery anomalies have been reported. Among these, type 4 is one of the rarest. Knowledge and recognition of the dual LAD artery are important for correct diagnosis and planning of coronary bypass surgery and percutaneous coronary intervention. We report a case of a 59-year-old male with type 4 dual LAD artery who presented with dyspepsia and sweating for several months and had approximately 50%-70% stenosis in a major diagonal branch off the short LAD artery.

Screening mammography performance according to breast density: a comparison between radiologists versus standalone intelligence detection.

BACKGROUND: Artificial intelligence (AI) algorithms for the independent assessment of screening mammograms have not been well established in a large screening cohort of Asian women. We compared the performance of screening digital mammography considering breast density, between radiologists and AI standalone detection among Korean women. METHODS: We retrospectively included 89,855 Korean women who underwent their initial screening digital mammography from 2009 to 2020. Breast cancer within 12 months of the screening mammography was the reference standard, according to the National Cancer Registry. Lunit software was used to determine the probability of malignancy scores, with a cutoff of 10% for breast cancer detection. The AI's performance was compared with that of the final Breast Imaging Reporting and Data System category, as recorded by breast radiologists. Breast density was classified into four categories (A-D) based on the radiologist and AI-based assessments. The performance metrics (cancer detection rate [CDR], sensitivity, specificity, positive predictive value [PPV], recall rate, and area under the receiver operating characteristic curve [AUC]) were compared across breast density categories. RESULTS: Mean participant age was 43.5 ± 8.7 years; 143 breast cancer cases were identified within 12 months. The CDRs (1.1/1000 examination) and sensitivity values showed no significant differences between radiologist and AI-based results (69.9% [95% confidence interval [CI], 61.7-77.3] vs. 67.1% [95% CI, 58.8-74.8]). However, the AI algorithm showed better specificity (93.0% [95% CI, 92.9-93.2] vs. 77.6% [95% CI, 61.7-77.9]), PPV (1.5% [95% CI, 1.2-1.9] vs. 0.5% [95% CI, 0.4-0.6]), recall rate (7.1% [95% CI, 6.9-7.2] vs. 22.5% [95% CI, 22.2-22.7]), and AUC values (0.8 [95% CI, 0.76-0.84] vs. 0.74 [95% CI, 0.7-0.78]) (all P < 0.05). Radiologist and AI-based results showed the best performance in the non-dense category; the CDR and sensitivity were higher for radiologists in the heterogeneously dense category (P = 0.059). However, the specificity, PPV, and recall rate consistently favored AI-based results across all categories, including the extremely dense category. CONCLUSIONS: AI-based software showed slightly lower sensitivity, although the difference was not statistically significant. However, it outperformed radiologists in recall rate, specificity, PPV, and AUC, with disparities most prominent in extremely dense breast tissue.

Regulatory Effect of Spray-Dried Lactiplantibacillus plantarum K79 on the Activation of Vasodilatory Factors and Inflammatory Responses.

The reduction of nitric oxide (NO) bioavailability in the endothelium induces endothelial dysfunction, contributing to the development of hypertension. Although Lactobacillus consumption decreases blood pressure, intracellular signaling pathways related to hypertension have not been well elucidated. Thus, this study examined the effect of spray-dried Lactiplantibacillus plantarum K79 (LpK79) on NO production, intracellular signaling pathways, and inflammatory responses related to vascular function and hypertension. NO production was assessed in human umbilical vein endothelial cells (HUVECs) treated with LpK79. Endothelial NO synthase (eNOS) and intracellular signaling molecules were determined using Western blot analysis. LpK79 dose-dependently increased NO production and activated eNOS via the phosphoinositide 3-kinase/Akt signaling pathway HUVECs. Moreover, LpK79 mitigated the activation of crucial factors pivotal for vascular contraction in smooth muscle cells, such as phospholipase Cγ, myosin phosphatase target subunit 1, and Rho-associated kinase 2. When HUVECs were treated with LpL79 in the presence of Escherichia coli lipopolysaccharide (LPS), LpK79 effectively suppressed mRNA and protein expression of pro-inflammatory mediators induced by E. coli LPS. These results suggest that LpK79 provided a beneficial effect on the regulation of vascular endothelial function.

Artificial Intelligence in Breast Cancer Diagnosis and Personalized Medicine.

Breast cancer is a significant cause of cancer-related mortality in women worldwide. Early and precise diagnosis is crucial, and clinical outcomes can be markedly enhanced. The rise of artificial intelligence (AI) has ushered in a new era, notably in image analysis, paving the way for major advancements in breast cancer diagnosis and individualized treatment regimens. In the diagnostic workflow for patients with breast cancer, the role of AI encompasses screening, diagnosis, staging, biomarker evaluation, prognostication, and therapeutic response prediction. Although its potential is immense, its complete integration into clinical practice is challenging. Particularly, these challenges include the imperatives for extensive clinical validation, model generalizability, navigating the "black-box" conundrum, and pragmatic considerations of embedding AI into everyday clinical environments. In this review, we comprehensively explored the diverse applications of AI in breast cancer care, underlining its transformative promise and existing impediments. In radiology, we specifically address AI in mammography, tomosynthesis, risk prediction models, and supplementary imaging methods, including magnetic resonance imaging and ultrasound. In pathology, our focus is on AI applications for pathologic diagnosis, evaluation of biomarkers, and predictions related to genetic alterations, treatment response, and prognosis in the context of breast cancer diagnosis and treatment. Our discussion underscores the transformative potential of AI in breast cancer management and emphasizes the importance of focused research to realize the full spectrum of benefits of AI in patient care.

Immunogenicity and Safety of a Newly Developed Live Attenuated Varicella Vaccine in Healthy Children: A Multi-National, Randomized, Double-Blinded, Active-Controlled, Phase 3 Study.

Korean manufacturers have developed a new varicella vaccine, NBP608. This phase 3, randomized, double-blind, multicenter study aimed to compare the immunogenicity and safety of NBP608 in healthy children to those of VarivaxTM (control). Children aged 12 months to 12 years were randomized in a ratio of 1:1 to receive either NBP608 or the control vaccine. Serum samples were obtained before vaccination and within six to eight weeks after vaccination. In total, 499 participants (NBP608, n = 251; control, n = 248) were enrolled. The seroconversion rate (SCR) measured using a FAMA assay was 99.53% in the NBP608 group, and the lower limit of the 95% confidence interval (95% LCL) for the SCR difference (NBP608 minus the control) was 0.52%. This 95% LCL for the difference was higher than the specified non-inferiority margin of -15%. In an assessment using gpELISA, the SCR was 99.53% in the NBP608 group, and the 95% LCL for the SCR difference was 6.5%, which was higher than the specified non-inferiority margin of -15%. There were no significant differences between the NBP608 and control group with respect to the proportions of participants who demonstrated local and systemic solicited AEs. This study indicated that NBP608 had a clinically acceptable safety profile and was not immunologically inferior to VarivaxTM.

Fermented Whey Protein Supplementation Improves Muscular Strength, Muscle Parameters, and Physical Performance in Middle-Aged Korean Adults: An 8-Week Double Blind Randomized Controlled Trial.

The present study evaluated the effects of fermented whey protein using kimchi lactic acid bacteria Lactobacillus casei DK211 on skeletal muscle mass, muscle strength, and physical performance in healthy middle-aged males performing regular resistance exercises. Effective protein supplementation and regular exercise are two important factors for improving muscle health. Therefore, in this study, the effects of consuming fermented whey protein twice a day were investigated and compared with that of non-fermented supplementation. Forty-eight males (average age 44.8) were randomly assigned to two groups: Fermented whey protein supplementation (FWPS) and non-fermented whey protein concentration supplementation (WPCS) groups. Each group ingested 37 g of FWPS or WPCS twice a day for eight weeks. Body composition, muscle strength, and physical performance were assessed pre- and post-intervention. Independent t-tests or chi-square tests for the categorical variables were performed for analyzing the observations. FWPS was effective in promoting the physical performance in dynamic balance measurement and muscle health, indicated through the increment in grip strength (left), upper arm circumference, and flat leg circumference from the baseline. However, similar improvements were not observed in the WPCS group. These results imply that whey protein fermented by L. casei DK211 is an effective protein supplement for enhancing muscle health in males performing regular resistance exercises.

Prediction models for respiratory outcomes in patients with COVID-19: integration of quantitative computed tomography parameters, demographics, and laboratory features.

Background: We aimed to develop integrative machine-learning models using quantitative computed tomography (CT) parameters in addition to initial clinical features to predict the respiratory outcomes of coronavirus disease 2019 (COVID-19). Methods: This was a retrospective study involving 387 patients with COVID-19. Demographic, initial laboratory, and quantitative CT findings were used to develop predictive models of respiratory outcomes. High-attenuation area (HAA) (%) and consolidation (%) were defined as quantified percentages of the area with Hounsfield units between -600 and -250 and between -100 and 0, respectively. Respiratory outcomes were defined as the development of pneumonia, hypoxia, or respiratory failure. Multivariable logistic regression and random forest models were developed for each respiratory outcome. The performance of the logistic regression model was evaluated using the area under the receiver operating characteristic curve (AUC). The accuracy of the developed models was validated by 10-fold cross-validation. Results: A total of 195 (50.4%), 85 (22.0%), and 19 (4.9%) patients developed pneumonia, hypoxia, and respiratory failure, respectively. The mean patient age was 57.8 years, and 194 (50.1%) were female. In the multivariable analysis, vaccination status and levels of lactate dehydrogenase, C-reactive protein (CRP), and fibrinogen were independent predictors of pneumonia. The presence of hypertension, levels of lactate dehydrogenase and CRP, HAA (%), and consolidation (%) were selected as independent variables to predict hypoxia. For respiratory failure, the presence of diabetes, levels of aspartate aminotransferase, and CRP, and HAA (%) were selected. The AUCs of the prediction models for pneumonia, hypoxia, and respiratory failure were 0.904, 0.890, and 0.969, respectively. Using the feature selection in the random forest model, HAA (%) was ranked as one of the top 10 features predicting pneumonia and hypoxia and was first place for respiratory failure. The accuracies of the cross-validation of the random forest models using the top 10 features for pneumonia, hypoxia, and respiratory failure were 0.872, 0.878, and 0.945, respectively. Conclusions: Our prediction models that incorporated quantitative CT parameters into clinical and laboratory variables showed good performance with high accuracy.

Clinical outcomes after incomplete cycles of R-CHOP for diffuse large B-cell lymphoma: 10 years' real-world experience in a single institute.

Although the current standard of care for diffuse large B-cell lymphoma (DLBCL) is six cycles of rituximab/cyclophosphamide/doxorubicin/vincristine/prednisolone combination chemotherapy (R-CHOP), a larger than expected number of patients cannot complete planned six cycles for various reasons in the real world. We aimed to evaluate the prognosis of patients with DLBCL after incomplete treatment by analyzing the chemotherapy response and survival according to the cause of discontinuation and the number of cycles. We analyzed a retrospective cohort of patients diagnosed with DLBCL who underwent incomplete cycles of R-CHOP at Seoul National University Hospital and Boramae Medical Center from January 2010 to April 2019. A total of 1183 patients were diagnosed with DLBCL, of which 260 (22%) did not complete six cycles of R-CHOP. The most common cause of discontinuation of chemotherapy was life-threatening infection, and the most common pathogen was Pneumocystis jirovecii. Overall survival (OS) and progression-free survival (PFS) were significantly better in patients who achieved complete response (CR) or partial response (PR) at the first response evaluation. Patients underwent three or more cycles of chemotherapy had a longer OS than those who did not. In patients with limited-stage disease, consolidative radiotherapy showed a significant improvement in OS and PFS. Advanced stage, high comorbidity score, and poor primary response to chemotherapy were poor prognostic factors in patients with unplanned treatment shortening. This study provides real-world outcomes for patients who could not complete the planned six cycles of R-CHOP.

Efficacy of Perilla frutescens (L.) Britton var. frutescens extract on mild knee joint pain: A randomized controlled trial.

Objectives: This study aimed to evaluate the clinical efficacy and safety of PE extracts developed for the purpose of relieving pain and improving knee joint function on semi-healthy people with mild knee joint pain. Methods: A randomized, double-blind, two-arm, single-center, placebo-controlled clinical trial was conducted. Individuals with knee joint pain and a visual analogue scale (VAS) score < 50 mm were included in the study, and participants with radiological arthritis were excluded. Participants were administered either PFE or a placebo capsule (700 mg, twice a day) orally for eight weeks. The comparisons of the changed VAS score and Western Ontario and McMaster Universities Osteoarthritis (WOMAC) scores between the PFE and placebo groups were primary outcomes, while the five inflammation-related laboratory tests including cartilage oligomeric matrix protein, cyclooxygenase-2, neutrophil and lymphocyte ratio, high sensitive C-reactive protein, and erythrocyte sedimentation rate were secondary outcomes. Also, a safety assessment was done. Results: Eighty participants (mean age, 38.4 ± 14.0, male: female, 28:52) were enrolled; 75 completed the trial (PFE 36 and placebo 39). After eight weeks, both VAS and WOMAC scores were reduced in the PFE and placebo groups. The changed scores were significantly higher in the PFE group compared to the placebo group: 19.6 ± 10.9 vs. 6.8 ± 10.5; VAS scores (p < 0.001), and 20.5 ± 14.7 vs. 9.3 ± 16.5; total WOMAC scores (p < 0.01) including the sub-scores for pain, stiffness, and functions. No significant changes were reported in the five inflammation-related laboratory parameters. All adverse events were considered minor and unlikely to result from the intervention. Conclusion: Eight weeks of PFE intake was more effective than placebo in reducing knee joint pain and improving knee joint function in sub-healthy people with mild knee joint pain, and there were no major safety concerns. Clinical Trial Registration: https://cris.nih.go.kr/cris/search/detailSearch.do?search_lang=E&focus=reset_12&search_page=M&pageSize=10&page=undefined&seq=23101&status=5&seq_group=19745, identifier CRIS: KCT0007219.

Efficacy of Prophylactic Cranial Irradiation According to the Risk of Extracranial Recurrence in Limited-Stage Small Cell Lung Cancer.

PURPOSE: We aimed to evaluate the effectiveness of prophylactic cranial irradiation (PCI) for "early brain metastasis", which occurs before extracranial recurrence (ECR), and "late brain metastasis", which occurs after ECR, in limited-stage small cell lung cancer (LS-SCLC). Materials and Methods: We retrospectively analyzed 271 LS-SCLC patients who underwent definitive chemoradiation. All patients were initially staged with brain magnetic resonance imaging and positron emission tomography. Intracranial recurrence (ICR), ECR, progression-free rate (PFR), and overall survival (OS) were analyzed as clinical endpoints. The competing risk of the first recurrence with ICR (ICRfirst) was evaluated. Significantly associated variables in multivariate analysis of ECR were considered as ECR risk factors. Patients were stratified according to the number of ECR risk factors. RESULTS: The application of PCI was associated with higher PFR (p=0.008) and OS (p=0.045). However, PCI was not associated with any of the clinical endpoints in multivariate analysis. The competing risk of ICRfirst was significantly decreased with the application of PCI (hazard ratio, 0.476; 95% confidence interval, 0.243 to 0.931; p=0.030). Stage III disease, sequential, and stable disease after thoracic radiation were selected as ECR risk factors. For patients without these risk factors, the application of PCI was significantly associated with increased OS (p=0.048) and a decreased risk of ICRfirst (p=0.026). CONCLUSION: PCI may play a role in preventing early brain metastasis rather than late brain metastasis after ECR, suggesting that only patients with a low risk of ECR may currently benefit from PCI.

Prognostic roles of leptin-signaling proteins, PD-L1, and tumor-infiltrating lymphocytes in surgically-resected biliary tract cancers.

BACKGROUND: Biliary tract cancers are rare, with a poor patient prognosis. Leptin and programmed death-ligand 1 (PD-L1) influence CD8+ and forkhead box P3 (FOXP3)+ lymphocytes, and thus, cancer cell growth. We aimed to define the prognostic implications of these variables and the clinicopathological features of biliary tract cancers. METHODS: Immunohistochemistry for leptin signaling-related proteins (leptin, leptin receptor, pSTAT3, extracellular-regulated kinase, mammalian target of rapamycin), PD-L1, CD8, and FOXP3 and in situ hybridization for Epstein-Barr virus-encoded small RNAs were performed in 147 cases of surgically-resected biliary tract cancers. RESULTS: Immune cell PD-L1-positivity, tumor size < 3 cm, adjuvant chemotherapy, no recurrence, and early-stage tumors were correlated with better 5-year survival in the tumoral PD-L1(-) and leptin(-) subgroups, and extrahepatic cholangiocarcinoma through multivariate analysis (all p < 0.05). Immune cell PD-L1 and adjuvant chemotherapy lost its prognostic significance in the tumoral PD-L1+ and leptin+ subgroups. CONCLUSIONS: The prognostic implication of the variables may depend upon tumoral protein expression and the anatomical site. Immune cell PD-L1-positivity and the administration of adjuvant chemotherapy may indicate the favorable survival of patients with surgically-resected biliary tract cancers, specifically, in the tumoral PD-L1(-) or tumor leptin(-) subgroups and extrahepatic cholangiocarcinoma. PD-L1- or leptin-targeted therapy combined with conventional chemotherapy may benefit the tumoral PD-L1+ or leptin+ subgroups.

In vitro anti-inflammatory and antibiofilm activities of bacterial lysates from lactobacilli against oral pathogenic bacteria.

Postbiotics are functional biological compounds, such as bacterial lysates (BLs) released from probiotic bacteria. Although postbiotics exert various bioactivities, the anti-inflammatory and antibiofilm activities of BLs against oral pathogenic bacteria have not been investigated. In the present study, pretreatment with BLs extracted from Lactobacillus plantarum and L. rhamnosus GG suppressed the mRNA and protein expression levels of inflammatory mediators induced by the lipopolysaccharide (LPS) of Porphyromonas gingivalis in RAW 264.7 cells. Both BLs attenuated P. gingivalis LPS-induced phosphorylation of mitogen-activated protein kinases (MAPKs) and activation of nuclear factor-κB (NF-κB), suggesting that BLs inhibit periodontal inflammatory responses by regulating the MAPK and NF-κB signaling pathways. Moreover, both BLs interfered with biofilm formation by Streptococcus mutans; however, they did not eradicate the established S. mutans biofilm. Furthermore, both BLs downregulated gtfB, gtfC, and gtfD responsible for biofilm formation by S. mutans, suggesting that BLs reduce the synthesis of extracellular polysaccharide and thereby reduce S. mutans biofilm. Taken together, these results suggest that BLs of L. plantarum and L. rhamnosus GG can attenuate periodontal inflammation and dental caries and thus contribute to the improvement of oral health.

Antibiofilm, AntiAdhesive and Anti-Invasive Activities of Bacterial Lysates Extracted from Pediococcus acidilactici against Listeria monocytogenes.

This study aimed to investigate whether bacterial lysates (BLs) extracted from Pediococcus acidilactici reduce Listeria monocytogenes biofilm formation, as well as adhesion to and invasion of human intestinal epithelial cells. Pretreatment with P. acidilactici BLs (20, 40, and 80 µg/mL) significantly inhibited L. monocytogenes biofilm formation on the surface of polystyrene (p < 0.05). Fluorescence and scanning-electron-microscopic analyses indicated that L. monocytogenes biofilm comprised a much less dense layer of more-dispersed cells in the presence of P. acidilactici BLs. Moreover, biofilm-associated genes, such as flaA, fliG, flgE, motB, degU, agrA, and prfA, were significantly downregulated in the presence of P. acidilactici BLs (p < 0.05), suggesting that P. acidilactici BLs prevent L. monocytogenes biofilm development by suppressing biofilm-associated genes. Although P. acidilactici BLs did not dose-dependently inhibit L. monocytogenes adhesion to and invasion of intestinal epithelial cells, the BLs effectively inhibited adhesion and invasion at 40 and 80 µg/mL (p < 0.05). Supporting these findings, P. acidilactici BLs significantly downregulated L. monocytogenes transcription of genes related to adhesion and invasion, specifically fbpA, ctaP, actA, lapB, ami, and inlA. Collectively, these results suggest that P. acidilactici BLs have the potential to reduce health risks from L. monocytogenes.

Pan-cancer molecular tumor board experience with biomarker-driven precision immunotherapy.

Despite remarkable responses to immune checkpoint blockade (ICB) in some advanced cancers, most patients do not benefit, perhaps due to the complexity of tumor/immune/genome interactions. We implemented a multidisciplinary Molecular Tumor Board (MTB) that reviewed multi-omic cancer characteristics to develop N-of-One therapies for patients in the pan-cancer, advanced, refractory setting. This study evaluates the experience of 80 patients who were presented to the MTB and received a treatment regimen that included ICB. Overall, 60/80 patients (75%) who received ICB following MTB discussion had a high degree of matching between tumor molecular characteristics, including ICB biomarkers (reflected by a high Matching Score (≥50%)) and therapy administered. Patients with high versus low Matching Score experienced significantly longer median progression-free survival (6.4 vs. 3.0 months; p = 0.011) and median overall survival (15.3 vs. 4.7 months; p = 0.014) and higher clinical benefit rates (stable disease ≥6 months/partial response/complete response) (53% vs. 21%, p = 0.019). Although most patients (52/80 (65%)) received a personalized combination therapy (e.g., targeted, hormonal, chemotherapy, or a second immunotherapy agent), administering >1 drug was not associated with outcome. Only degree of matching and age, but no other variables, including individual biomarkers (e.g., microsatellite status, tumor mutational burden, or PD-L1 status), were independently correlated with outcome. In the pan-cancer setting, the MTB facilitated a precision medicine strategy to match therapeutic regimens that included ICB alone or combined with matched targeted drugs to patients with advanced malignancy, which was associated with improved clinical outcomes.

Quantitative Computed Tomography Parameters in Coronavirus Disease 2019 Patients and Prediction of Respiratory Outcomes Using a Decision Tree.

Background: Chest computed tomography (CT) scans play an important role in the diagnosis of coronavirus disease 2019 (COVID-19). This study aimed to describe the quantitative CT parameters in COVID-19 patients according to disease severity and build decision trees for predicting respiratory outcomes using the quantitative CT parameters. Methods: Patients hospitalized for COVID-19 were classified based on the level of disease severity: (1) no pneumonia or hypoxia, (2) pneumonia without hypoxia, (3) hypoxia without respiratory failure, and (4) respiratory failure. High attenuation area (HAA) was defined as the quantified percentage of imaged lung volume with attenuation values between -600 and -250 Hounsfield units (HU). Decision tree models were built with clinical variables and initial laboratory values (model 1) and including quantitative CT parameters in addition to them (model 2). Results: A total of 387 patients were analyzed. The mean age was 57.8 years, and 50.3% were women. HAA increased as the severity of respiratory outcome increased. HAA showed a moderate correlation with lactate dehydrogenases (LDH) and C-reactive protein (CRP). In the decision tree of model 1, the CRP, fibrinogen, LDH, and gene Ct value were chosen as classifiers whereas LDH, HAA, fibrinogen, vaccination status, and neutrophil (%) were chosen in model 2. For predicting respiratory failure, the decision tree built with quantitative CT parameters showed a greater accuracy than the model without CT parameters. Conclusions: The decision tree could provide higher accuracy for predicting respiratory failure when quantitative CT parameters were considered in addition to clinical characteristics, PCR Ct value, and blood biomarkers.

Corrigendum: Artificial Intelligence for Breast Cancer Screening in Mammography (AI-STREAM): A Prospective Multicenter Study Design in Korea Using AI-Based CADe/x.

This corrects the article on p. 57 in vol. 25, PMID: 35133093.