PSA doubling time 4.65 months as an optimal cut-off of Japanese nonmetastatic castration-resistant prostate cancer.

A multicenter study of nonmetastatic castration-resistant prostate cancer (nmCRPC) was conducted to identify the optimal cut-off value of prostate-specific antigen (PSA) doubling time (PSADT) that correlated with the prognosis in Japanese nmCRPC. Of the 515 patients diagnosed and treated for nmCRPC at 25 participating Japanese Urological Oncology Group centers, 450 patients with complete clinical information were included. The prognostic values of clinical factors were evaluated with respect to prostate specific antigen progression-free (PFS), cancer-specific survival (CSS), and overall survival (OS). The optimal cutoff value of PSADT was identified using survival tree analysis by Python. The Median PSA and PSADT at diagnosis of nmCRPC were 3.3 ng/ml, and 5.2 months, respectively. Patients treated with novel hormonal therapy (NHT) showed significantly longer PFS (HR: hazard ratio 0.38, p < 0.0001) and PFS2 (HR 0.45, p < 0.0001) than those treated with vintage nonsteroidal antiandrogen agent (Vintage). The survival tree identified 4.65 months as the most prognostic PSADT cutoff point. Among the clinical and pathological factors PSADT of < 4.65 months remained an independent prognostic factor for OS (HR 2.96, p = 0.0003) and CSS (HR 3.66, p < 0.0001). Current data represented optimal cut-off of PSADT 4.65 months for a Japanese nmCRPC.

Clinical Outcomes and Risk Stratification in Patients With Metastatic Hormone-Sensitive Prostate Cancer Treated With New-Generation Androgen Receptor Signaling Inhibitors.

BACKGROUND: Optimal drug selection for metastatic hormone-sensitive prostate cancer (mHSPC) remains unclear. We therefore assessed the clinical outcomes of mHSPC treated with new-generation androgen receptor pathway inhibitors (ARSIs) and identified risk factors associated with the prognosis of mHSPC. METHODS: We retrospectively reviewed 324 patients with mHSPC who were treated with ARSIs, including abiraterone acetate, enzalutamide, and apalutamide, between January 2018 and December 2022. In addition to assessing the prostate-specific antigen (PSA) response and overall survival (OS) during ARSI treatment, we investigated several potential risk factors for a poor OS in patients with mHSPC. RESULTS: Patients with a ≥ 90% PSA reduction (hazard ratio [HR]: 0.24, 95% confidence interval [CI], 0.10-0.58; P = .002) and those whose PSA declined to ≤ 0.2 ng/mL (HR: 0.22, 95% CI, 0.08-0.63; P = .005) showed significantly better OS than other patients. Gleason grade group 5 (GG5), presence of liver metastasis, and an LDH ≥ 250 U/L were identified as prognostic factors significantly associated with a poor OS, with HRs of 2.31 (95% CI, 1.02-5.20; P = .044), 7.87 (95% CI, 2.61-23.8; P < .001) and 3.21 (95% CI, 1.43-7.23; P = .005). CONCLUSION: We identified GG5, the presence of liver metastasis, and elevated LDH at the diagnosis as significant factors predicting the OS of mHSPC, but the choice of ARSIs did not affect the prognosis. The potential prognostic impact of these markers requires further investigation.

[A Case of Metastatic Renal Cancer Responding to Sunitinib as the Eighth Line Therapy].

A 62-year-old male presenting with gross hematuria and right renal mass was referred to our Urology Department. Computed tomography revealed a right renal mass, with multiple pulmonary lesions. He underwent right nephrectomy for highly suspected renal cell carcinoma with pulmonary metastases (cT3aN0M1). The pathological diagnosis was clear cell renal cell carcinoma, pT1b. Following surgery, he was treated with multiple regimens of chemotherapy, ranging from interferon alpha, multiple tyrosine kinase inhibitors such as sorafenib, axitinib, pazopanib and cabozantinib, everolimus, and nivolumab, all of which were discontinued after its induction, either due to adverse events or progressive disease. He was finally administered Sunitinib as the 8th line "last-ditch" treatment, which resulted in significant tumor shrinkage. No disease progression has been observed 25 months after initiating sunitinib administration.

Computed tomography mucus plugs and airway tree structure in patients with chronic obstructive pulmonary disease: Associations with airflow limitation, health-related independence and mortality.

BACKGROUND AND OBJECTIVE: Mucus plugs and underlying airway tree structure can affect airflow limitation and prognosis in patients with chronic obstructive pulmonary disease (COPD), but their relative roles are unclear. This study used two COPD cohorts to examine whether mucus plugs on computed tomography (CT) were associated with airflow limitation and clinical outcomes independent of other airway structural changes and emphysema. METHODS: Based on visual CT assessment, patients with mucus plugs in 0, 1-2 and ≥3 lung segments were assigned to no-, low- and high-mucus groups. Loss of health-related independence and mortality were prospectively recorded for 3 and 10 years in the Kyoto-Himeji and Hokkaido cohorts, respectively. The percentages of the wall area of the central airways (WA%), total airway count (TAC) and emphysema were quantified on CT. RESULTS: Of 199 and 96 patients in the Kyoto-Himeji and Hokkaido cohorts, 34% and 30%, respectively, had high mucus scores. In both cohorts, TAC was lower in the high-mucus group than in the no-mucus group, whereas their emphysema severity did not differ. High mucus score and low TAC were independently associated with airflow limitation after adjustment for WA% and emphysema. In multivariable models adjusted for WA% and emphysema, TAC, rather than mucus score, was associated with a greater rate of loss of independence, whereas high mucus score, rather than TAC, was associated with increased mortality. CONCLUSION: Mucus plugs and lower airway branch count on CT had distinct roles in airflow limitation, health-related independence and mortality in patients with COPD.

Comparison of Cabozantinib and Axitinib as Second-line Therapy After Nivolumab Plus Ipilimumab in Patients With Metastatic Clear Cell Renal Cell Carcinoma: A Comparative Analysis of Retrospective Real-world Data.

BACKGROUND: To date, no studies have compared the treatment outcomes of second-line therapies in patients with metastatic clear cell renal cell carcinoma (ccRCC). This study retrospectively evaluated the efficacy of cabozantinib and axitinib as second-line treatments in patients with metastatic ccRCC who previously received immune-oncology combination therapy. PATIENTS AND METHODS: Patients with metastatic ccRCC treated with cabozantinib and axitinib as second-line therapy after nivolumab-ipilimumab treatment were identified among 243 patients with RCC treated between August 1, 2018 and January 31, 2022 at 34 institutions belonging to the Japanese Urological Oncology Group. Patients were assessed for treatment outcomes, including progression-free survival (PFS), overall survival, objective response rate (ORR), and incidence rate of treatment-related adverse events (AEs). RESULTS: Forty-eight patients treated with cabozantinib and 60 treated with axitinib as second-line therapy after nivolumab-ipilimumab treatment for metastatic ccRCC were identified. The median PFS (95% confidence interval) was 11.0 months (9.0-16.0) with cabozantinib and 9.5 months (6.0-13.0) with axitinib. The ORRs were 37.5% (cabozantinib) and 38.3% (axitinib). The rates of any-grade AEs and grade ≥3 AEs were 79.2% (cabozantinib) versus 63.3% (axitinib; P = .091) and 35.4% (cabozantinib) versus 23.3% (axitinib; P = .202), respectively. In the poor-risk group, PFS was longer in the cabozantinib group than in the axitinib group (P = .033). CONCLUSION: The efficacy and safety of cabozantinib and axitinib were comparable. In the poor-risk group, cabozantinib was more effective than axitinib. These findings provide valuable insights into the selection of second-line treatment options after nivolumab-ipilimumab treatment in patients with metastatic ccRCC.

Longitudinal assessment of interstitial lung abnormalities on CT in patients with COPD using artificial intelligence-based segmentation: a prospective observational study.

BACKGROUND: Interstitial lung abnormalities (ILAs) on CT may affect the clinical outcomes in patients with chronic obstructive pulmonary disease (COPD), but their quantification remains unestablished. This study examined whether artificial intelligence (AI)-based segmentation could be applied to identify ILAs using two COPD cohorts. METHODS: ILAs were diagnosed visually based on the Fleischner Society definition. Using an AI-based method, ground-glass opacities, reticulations, and honeycombing were segmented, and their volumes were summed to obtain the percentage ratio of interstitial lung disease-associated volume to total lung volume (ILDvol%). The optimal ILDvol% threshold for ILA detection was determined in cross-sectional data of the discovery and validation cohorts. The 5-year longitudinal changes in ILDvol% were calculated in discovery cohort patients who underwent baseline and follow-up CT scans. RESULTS: ILAs were found in 32 (14%) and 15 (10%) patients with COPD in the discovery (n = 234) and validation (n = 153) cohorts, respectively. ILDvol% was higher in patients with ILAs than in those without ILA in both cohorts. The optimal ILDvol% threshold in the discovery cohort was 1.203%, and good sensitivity and specificity (93.3% and 76.3%) were confirmed in the validation cohort. 124 patients took follow-up CT scan during 5 ± 1 years. 8 out of 124 patients (7%) developed ILAs. In a multivariable model, an increase in ILDvol% was associated with ILA development after adjusting for age, sex, BMI, and smoking exposure. CONCLUSION: AI-based CT quantification of ILDvol% may be a reproducible method for identifying and monitoring ILAs in patients with COPD.

CT-derived vertebral bone mineral density is a useful biomarker to predict COVID-19 outcome.

The low vertebral bone computed tomography (CT) Hounsfield unit values measured on CT scans reflect low bone mineral density (BMD) and are known as diagnostic indicators for osteoporosis. The potential prognostic significance of low BMD defined by vertebral bone CT values for the coronavirus disease 2019 (COVID-19) remains unclear. This study aimed to assess the impact of BMD on the clinical outcome in Japanese patients with COVID-19 and evaluate the association between BMD and critical outcomes, such as high-flow nasal cannula, non-invasive and invasive positive pressure ventilation, extracorporeal membrane oxygenation, or death. We examined the effects of COVID-19 severity on the change of BMD over time. This multicenter retrospective cohort study enrolled 1132 inpatients with COVID-19 from the Japan COVID-19 Task Force database between February 2020 and September 2022. The bone CT values of the 4th, 7th, and 10th thoracic vertebrae were measured from chest CT images. The average of these values was defined as BMD. Furthermore, a comparative analysis was conducted between the BMD on admission and its value 3 months later. The low BMD group had a higher proportion of critical outcomes than did the high BMD group. In a subanalysis stratifying patients by epidemic wave according to onset time, critical outcomes were higher in the low BMD group in the 1st-4th waves. Multivariable logistic analysis of previously reported factors associated with COVID-19 severity revealed that low BMD, chronic kidney disease, and diabetes were independently associated with critical outcomes. At 3 months post-infection, patients with oxygen demand during hospitalization showed markedly decreased BMD than did those on admission. Low BMD in patients with COVID-19 may help predict severe disease after the disease onset. BMD may decrease over time in patients with severe COVID-19, and the impact on sequelae symptoms should be investigated in the future.

Lung volume measurement using chest CT in COVID-19 patients: a cohort study in Japan.

OBJECTIVE: This study aimed to investigate the utility of CT quantification of lung volume for predicting critical outcomes in COVID-19 patients. METHODS: This retrospective cohort study included 1200 hospitalised patients with COVID-19 from 4 hospitals. Lung fields were extracted using artificial intelligence-based segmentation, and the percentage of the predicted (%pred) total lung volume (TLC (%pred)) was calculated. The incidence of critical outcomes and posthospitalisation complications was compared between patients with low and high CT lung volumes classified based on the median percentage of predicted TLCct (n=600 for each). Prognostic factors for residual lung volume loss were investigated in 208 patients with COVID-19 via a follow-up CT after 3 months. RESULTS: The incidence of critical outcomes was higher in the low TLCct (%pred) group than in the high TLCct (%pred) group (14.2% vs 3.3%, p<0.0001). Multivariable analysis of previously reported factors (age, sex, body mass index and comorbidities) demonstrated that CT-derived lung volume was significantly associated with critical outcomes. The low TLCct (%pred) group exhibited a higher incidence of bacterial infection, heart failure, thromboembolism, liver dysfunction and renal dysfunction than the high TLCct (%pred) group. TLCct (%pred) at 3 months was similarly divided into two groups at the median (71.8%). Among patients with follow-up CT scans, lung volumes showed a recovery trend from the time of admission to 3 months but remained lower in critical cases at 3 months. CONCLUSION: Lower CT lung volume was associated with critical outcomes, posthospitalisation complications and slower improvement of clinical conditions in COVID-19 patients.

Quantification of airway structures by persistent homology.

We propose two types of novel morphological metrics for quantifying the geometry of tubular structures on computed tomography (CT) images. We apply our metrics to identify irregularities in the airway of patients with chronic obstructive pulmonary disease (COPD) and demonstrate that they provide complementary information to the conventional metrics used to assess COPD, such as the tissue density distribution in lung parenchyma and the wall area ratio of the segmented airway. The three-dimensional shape of the airway and its abstraction as a rooted tree with the root at the trachea carina are automatically extracted from a lung CT volume, and the two metrics are computed based on a mathematical tool called persistent homology; treeH0 quantifies the distribution of branch lengths to assess the complexity of the tree-like structure and radialH0 quantifies the irregularities in the luminal radius along the airway. We show our metrics are associated with clinical outcomes.

Centrilobular emphysema and airway dysanapsis: factors associated with low respiratory function in younger smokers.

Background: Low respiratory function in young adulthood is one of the important factors in the trajectory leading to the future development of COPD, but its morphological characteristics are not well characterised. Methods: We retrospectively enrolled 172 subjects aged 40-49 years with ≥10 pack-years smoking history who underwent lung cancer screening by computed tomography (CT) and spirometry at two Japanese hospitals. Emphysema was visually assessed according to the Fleischner Society guidelines and classified into two types: centrilobular emphysema (CLE) and paraseptal emphysema (PSE). Airway dysanapsis was assessed with the airway/lung ratio (ALR), which was calculated by the geometric mean of the lumen diameters of the 14 branching segments divided by the cube root of total lung volume on a CT scan. Results: Among the subjects, CLE and PSE were observed in 20.9% and 30.8%, respectively. The mean ALR was 0.04 and did not differ between those with and without each type of emphysema. Multivariable regression analysis models adjusted for age, sex, body mass index and smoking status indicated that CLE and a low ALR were independently associated with lower forced expiratory volume in 1 s (FEV1)/forced vital capacity (estimate -1.64 (95% CI -2.68- -0.60) and 6.73 (95% CI 4.24-9.24), respectively) and FEV1 % pred (estimate -2.81 (95% CI -5.10- -0.52) and 10.9 (95% CI 5.36-16.4), respectively). Conclusions: CLE and airway dysanapsis on CT were independently associated with low respiratory function in younger smokers.

Therapeutic outcome of combination therapy using immune-checkpoint inhibitors and tyrosine kinase inhibitors for metastatic non-clear-cell renal cell carcinoma.

INTRODUCTION: We aimed to clarify the therapeutic outcome of combination therapy using immune-checkpoint inhibitors (ICIs) and/or tyrosine kinase inhibitors (TKIs) for meta-static non-clear-cell renal cell carcinoma (nccRCC). METHODS: We have been retrospectively investigating the therapeutic efficacy and prognosis in 36 patients with metastatic nccRCC undergoing combination therapy using two ICIs, ipilimumab plus nivolumab (ICI-ICI), and ICI plus TKI (ICI-TKI), at Kobe University and affiliated institutions since 2018. Progression-free survival (PFS), overall survival (OS), objective response rate (ORR), and adverse event (AE) were compared. RESULTS: The first-line regimen was ICI-ICI in 26 cases and ICI-TKI in 10 cases. The ORRs in the ICI-ICI and ICI-TKI groups were 34.6 and 30.0%, respectively (p=0.9433). The 50% PFS for the ICI-TKI group was 9.7 months, significantly longer than that for the ICI-ICI group (4.6 months, p=0.0499), and there was no significant difference in OS between groups (p=0.3984). There was no significant difference in the occurrence rate of AE for below grade 2 (p=0.8535), nor above grade 3 (p=0.3786) between the ICI-ICI and ICI-TKI groups. CONCLUSIONS: From our analysis of real-world data, a better outcome of PFS was expected in the ICI-TKI group compared with that in the ICI-ICI group, while there was no significant difference in OS or ORR.

Integrated assessment of computed tomography density in pectoralis and erector spinae muscles as a prognostic biomarker for coronavirus disease 2019.

BACKGROUND ＆ AIMS: Muscle quantification using chest computed tomography (CT) is a useful prognostic biomarker for coronavirus disease 2019 (COVID-19). However, no studies have evaluated the clinical course through comprehensive assessment of the pectoralis and erector spinae muscles. Therefore, we compared the impact of the areas and densities of these muscles on COVID-19 infection outcome. METHODS: This multicenter retrospective cohort study was conducted by the COVID-19 Task Force. A total of 1410 patients with COVID-19 were included, and data on the area and density of the pectoralis and erector spinae muscles on chest CT were collected. The impact of each muscle parameter on the clinical outcome of COVID-19 was stratified according to sex. The primary outcome was the percentage of patients with severe disease, including those requiring oxygen supplementation and those who died. Additionally, 167 patients were followed up for changes in muscle parameters at three months and for the clinical characteristics in case of reduced CT density. RESULTS: For both muscles, low density rather than muscle area was associated with COVID-19 severity. Regardless of sex, lower erector spinae muscle density was associated with more severe disease than pectoralis muscle density. The muscles were divided into two groups using the receiver operating characteristic curve of CT density, and the population was classified into four (Group A: high CT density for both muscles, Group B: low CT density for pectoralis and high for erector spinae muscle. Group C: high CT density for pectoralis and low for erector spinae muscle, Group D: low CT density for both muscles). In univariate analysis, Group D patients exhibited worse outcomes than Group A (OR: 2.96, 95% CI: 2.03-4.34 in men; OR: 3.02, 95% CI: 2.66-10.4 in women). Multivariate analysis revealed that men in Group D had a significantly more severe prognosis than those in Group A (OR: 1.82, 95% CI: 1.16-2.87). Moreover, Group D patients tended to have the highest incidence of other complications due to secondary infections and acute kidney injury during the clinical course. Longitudinal analysis of both muscle densities over three months revealed that patients with decreased muscle density over time were more likely to have severe cases than those who did not. CONCLUSIONS: Muscle density, rather than muscle area, predicts the clinical outcomes of COVID-19. Integrated assessment of pectoralis and erector spinae muscle densities demonstrated higher accuracy in predicting the clinical course of COVID-19 than individual assessments.

Sterile versus non-sterile gloves during cystoscopy: A randomized prospective single-blind study.

Objective: The objective of this study is to evaluate the need for sterile gloves during cystoscopy by comparing the incidence of UTI symptoms between patients in whom the procedure is performed with non-sterile gloves with those performed with non-sterile gloves. Patients and Methods: This study had a randomized, prospective, single-blind design and included patients aged >20 years who underwent cystoscopy in either of two outpatient clinics between September 2015 and November 2021. The patients were allocated to a sterile group or a non-sterile group. Only the urologists were aware of whether or not the gloves were sterile. The patients were instructed to report any symptoms suggestive of UTI after cystoscopy. Results: A total of 1258 patients were enrolled in the sterile group and 1376 in the non-sterile group. Symptoms of UTI were reported by six patients (0.48%) in the sterile group and six (0.44%) in the non-sterile group. The between-group difference was not statistically significant (p = 0.88). Conclusion: It is not necessary to use sterile gloves during routine cystoscopy.

Aggregated eosinophils and neutrophils characterize the properties of mucus in chronic rhinosinusitis.

BACKGROUND: Airway obstruction caused by viscous mucus is an important pathophysiologic characteristic of persistent inflammation, which can result in organ damage. OBJECTIVE: We investigated the hypothesis that the biophysical characteristics of accumulating granulocytes affect the clinical properties of mucus. METHODS: Surgically acquired nasal mucus samples from patients with eosinophilic chronic rhinosinusitis and neutrophil-dominant, noneosinophilic chronic rhinosinusitis were evaluated in terms of computed tomography density, viscosity, water content, wettability, and protein composition. Isolated human eosinophils and neutrophils were stimulated to induce the formation of extracellular traps, followed by the formation of aggregates. The biophysical properties of the aggregated cells were also examined. RESULTS: Mucus from patients with eosinophilic chronic rhinosinusitis had significantly higher computed tomography density, viscosity, dry weight, and hydrophobicity compared to mucus from patients with noneosinophilic chronic rhinosinusitis. The levels of eosinophil-specific proteins in mucus correlated with its physical properties. Eosinophil and neutrophil aggregates showed physical and pathologic characteristics resembling those of mucus. Cotreatment with deoxyribonuclease and heparin, which slenderizes the structure of eosinophil extracellular traps, efficiently induced reductions in the viscosity and hydrophobicity of both eosinophil aggregates and eosinophilic mucus. CONCLUSIONS: The present study elucidated the pathogenesis of mucus stasis in infiltrated granulocyte aggregates from a novel perspective. These findings may contribute to the development of treatment strategies for eosinophilic airway diseases.

Artificial intelligence-based analysis of the spatial distribution of abnormal computed tomography patterns in SARS-CoV-2 pneumonia: association with disease severity.

BACKGROUND: The substantial heterogeneity of clinical presentations in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia still requires robust chest computed tomography analysis to identify high-risk patients. While extension of ground-glass opacity and consolidation from peripheral to central lung fields on chest computed tomography (CT) might be associated with severely ill conditions, quantification of the central-peripheral distribution of ground glass opacity and consolidation in assessments of SARS-CoV-2 pneumonia remains unestablished. This study aimed to examine whether the central-peripheral distributions of ground glass opacity and consolidation were associated with severe outcomes in patients with SARS-CoV-2 pneumonia independent of the whole-lung extents of these abnormal shadows. METHODS: This multicenter retrospective cohort included hospitalized patients with SARS-CoV-2 pneumonia between January 2020 and August 2021. An artificial intelligence-based image analysis technology was used to segment abnormal shadows, including ground glass opacity and consolidation. The area ratio of ground glass opacity and consolidation to the whole lung (GGO%, CON%) and the ratio of ground glass opacity and consolidation areas in the central lungs to those in the peripheral lungs (GGO(C/P)) and (CON(C/P)) were automatically calculated. Severe outcome was defined as in-hospital death or requirement for endotracheal intubation. RESULTS: Of 512 enrolled patients, the severe outcome was observed in 77 patients. GGO% and CON% were higher in patients with severe outcomes than in those without. Multivariable logistic models showed that GGO(C/P), but not CON(C/P), was associated with the severe outcome independent of age, sex, comorbidities, GGO%, and CON%. CONCLUSION: In addition to GGO% and CON% in the whole lung, the higher the ratio of ground glass opacity in the central regions to that in the peripheral regions was, the more severe the outcomes in patients with SARS-CoV-2 pneumonia were. The proposed method might be useful to reproducibly quantify the extension of ground glass opacity from peripheral to central lungs and to estimate prognosis.

Longitudinal changes in respiratory reactance in patients with COPD: associations with longitudinal change in air-trapping, exacerbations, and mortality.

INTRODUCTION: Air-trapping affects clinical outcomes in patients with chronic obstructive pulmonary disease (COPD) and may be detected by reactance at 5 Hz (X5) on respiratory oscillometry because X5 sensitively reflects the elasticity of the chest wall, airway and lung. However, the longitudinal association between X5 and air-trapping remains to be explored. This study aimed to test whether longitudinal changes in X5 could be associated with air-trapping progression, exacerbations, and mortality in patients with COPD. METHODS: In this prospective COPD observational study, the follow-up period consisted of the first 4 years to obtain longitudinal changes in X5 and residual volume (RV) and number of exacerbations and the remaining years (year 4 to 10) to test mortality. Patients were divided into large, middle, and small X5 decline groups based on the tertiles of longitudinal change in X5, and mortality after 4 years was compared between the groups. RESULTS: Patients with COPD (n = 114) were enrolled. The large X5 decline group (n = 38) showed a greater longitudinal change in RV and more exacerbations compared with the small X5 decline group (n = 39) in multivariable models adjusted for age, sex, body mass index, and smoking history. Long-term mortality after the 4-year follow-up was higher in the large X5 decline group than in the small X5 decline group (hazard ratio [95 % confidence interval] = 8.37[1.01, 69.0]) in the multivariable Cox proportional hazard model. CONCLUSION: Longitudinal changes in respiratory reactance could be associated with progressive air-trapping, exacerbation frequency, and increased mortality in patients with COPD.

A reference equation for lung volume on computed tomography in Japanese middle-aged and elderly adults.

BACKGROUND: Effective use of lung volume data measured on computed tomography (CT) requires reference values for specific populations. This study examined whether an equation previously generated for multiple ethnic groups in the United States, including Asians predominantly composed of Chinese people, in the Multi-Ethnic Study of Atherosclerosis (MESA) could be used for Japanese people and, if necessary, to optimize this equation. Moreover, the equation was used to characterize patients with chronic obstructive pulmonary disease (COPD) and lung hyperexpansion. METHODS: This study included a lung cancer screening CT cohort of asymptomatic never smokers aged ≥40 years from two institutions (n = 364 and 419) to validate and optimize the MESA equation and a COPD cohort (n = 199) to test its applicability. RESULTS: In all asymptomatic never smokers, the variance explained by the predicted values (R2) based on the original MESA equation was 0.60. The original equation was optimized to minimize the root mean squared error (RMSE) by adjusting the scaling factor but not the age, sex, height, or body mass index terms of the equation. The RMSE changed from 714 ml in the original equation to 637 ml in the optimized equation. In the COPD cohort, lung hyperexpansion, defined based on the 95th percentile of the ratio of measured lung volume to predicted lung volume in never smokers (122 %), was observed in 60 (30 %) patients and was associated with centrilobular emphysema and air trapping on inspiratory/expiratory CT. CONCLUSIONS: The MESA equation was optimized for Japanese middle-aged and elderly adults.

Epicardial adipose tissue measured from analysis of adipose tissue area using chest CT imaging is the best potential predictor of COVID-19 severity.

BACKGROUND: Computed tomography (CT) imaging is widely used for diagnosing and determining the severity of coronavirus disease 2019 (COVID-19). Chest CT imaging can be used to calculate the epicardial adipose tissue (EAT) and upper abdominal visceral adipose tissue (Abd-VAT) areas. The EAT is the main source of inflammatory cytokines involved in chest inflammatory diseases; thus, the EAT area might be a more useful severity predictor than the Abd-VAT area for COVID-19. However, to the best of our knowledge, there are no large-scale reports that sufficiently consider this issue. In addition, there are no reports on the characteristics of patients with normal body mass index (BMI) and high adipose tissue. AIM: The purpose of this study was to analyze whether the EAT area, among various adipose tissues, was the most associated factor with COVID-19 severity. Using a multicenter COVID-19 patient database, we analyzed the associations of chest subcutaneous, chest visceral, abdominal subcutaneous, and Abd-VAT areas with COVID-19 outcomes. In addition, the clinical significance of central obesity, commonly disregarded by BMI, was examined. METHODS: This retrospective cohort study evaluated patients with COVID-19 aged ≥18 years In Japan. Data including from chest CT images collected between February 2020 and October 2022 in four hospitals of the Japan COVID-19 Task Force were analyzed. Patient characteristics and COVID-19 severity were compared according to the adipose tissue areas (chest and abdominal subcutaneous adipose tissue [Chest-SAT and Abd-SAT], EAT, and Abd-VAT) calculated from chest CT images. RESULTS: We included 1077 patients in the analysis. Patients with risk factors of severe COVID-19 such as old age, male sex, and comorbidities had significantly higher areas of EAT and Abd-VAT. High EAT area but not high Abd-VAT area was significantly associated with COVID-19 severity (adjusted odds ratio (aOR): 2.66, 95 % confidence interval [CI]: 1.19-5.93). There was no strong correlation between BMI and VAT. Patients with high VAT area accounted for 40.7 % of the non-obesity population (BMI < 25 kg/m2). High EAT area was also significantly associated with COVID-19 severity in the non-obesity population (aOR: 2.50, 95 % CI: 1.17-5.34). CONCLUSIONS: Our study indicated that VAT is significantly associated with COVID-19 severity and that EAT is the best potential predictor for risk stratification in COVID-19 among adipose tissue areas. Body composition assessment using EAT is an appropriate marker for identifying obesity patients overlooked by BMI. Considering the next pandemic of the global health crisis, our findings open new avenues for implementing appropriate body composition assessments based on CT imaging.

Association between blood eosinophil count and small airway eosinophils in smokers with and without COPD.

Introduction: Airway eosinophilic inflammation is a pathological feature in a subgroup of patients with COPD and in some smokers with a high COPD risk. Although blood eosinophil count is used to define eosinophilic COPD, the association between blood eosinophil count and airway eosinophilic inflammation remains controversial. This cross-sectional study tested this association in smokers with and without COPD while considering potential confounders, such as smoking status and comorbidities. Methods: Lung specimens were obtained from smokers with and without COPD and non-COPD never-smokers undergoing lung lobectomy. Those with any asthma history were excluded. The infiltration of eosinophils into the small airway wall was quantified on histological sections stained with major basic protein (MBP). Results: The number of airway MBP-positive cells was greater in smokers (n=60) than in never-smokers (n=14). Smokers with and without COPD (n=30 each) exhibited significant associations between blood eosinophil count and airway MBP-positive cells (ρ=0.45 and 0.71). When smokers were divided into the high and low airway MBP groups based on their median value, blood eosinophil count was higher in the high-MBP group, with no difference in age, smoking status, comorbidities, emphysema or coronary artery calcification on computed tomography, and inhaled corticosteroid (ICS) use. The association between greater blood eosinophil count and the high-MBP group was confirmed in multivariable models adjusted for smoking status, airflow limitation and ICS use. Conclusion: The blood eosinophil count may reflect eosinophilic inflammation in the small airways in smokers with and without COPD.

Clinical utilization of artificial intelligence-based COVID-19 pneumonia quantification using chest computed tomography - a multicenter retrospective cohort study in Japan.

BACKGROUND: Computed tomography (CT) imaging and artificial intelligence (AI)-based analyses have aided in the diagnosis and prediction of the severity of COVID-19. However, the potential of AI-based CT quantification of pneumonia in assessing patients with COVID-19 has not yet been fully explored. This study aimed to investigate the potential of AI-based CT quantification of COVID-19 pneumonia to predict the critical outcomes and clinical characteristics of patients with residual lung lesions. METHODS: This retrospective cohort study included 1,200 hospitalized patients with COVID-19 from four hospitals. The incidence of critical outcomes (requiring the support of high-flow oxygen or invasive mechanical ventilation or death) and complications during hospitalization (bacterial infection, renal failure, heart failure, thromboembolism, and liver dysfunction) was compared between the groups of pneumonia with high/low-percentage lung lesions, based on AI-based CT quantification. Additionally, 198 patients underwent CT scans 3 months after admission to analyze prognostic factors for residual lung lesions. RESULTS: The pneumonia group with a high percentage of lung lesions (N = 400) had a higher incidence of critical outcomes and complications during hospitalization than the low percentage group (N = 800). Multivariable analysis demonstrated that AI-based CT quantification of pneumonia was independently associated with critical outcomes (adjusted odds ratio [aOR] 10.5, 95% confidence interval [CI] 5.59-19.7), as well as with oxygen requirement (aOR 6.35, 95% CI 4.60-8.76), IMV requirement (aOR 7.73, 95% CI 2.52-23.7), and mortality rate (aOR 6.46, 95% CI 1.87-22.3). Among patients with follow-up CT scans (N = 198), the multivariable analysis revealed that the pneumonia group with a high percentage of lung lesions on admission (aOR 4.74, 95% CI 2.36-9.52), older age (aOR 2.53, 95% CI 1.16-5.51), female sex (aOR 2.41, 95% CI 1.13-5.11), and medical history of hypertension (aOR 2.22, 95% CI 1.09-4.50) independently predicted persistent residual lung lesions. CONCLUSIONS: AI-based CT quantification of pneumonia provides valuable information beyond qualitative evaluation by physicians, enabling the prediction of critical outcomes and residual lung lesions in patients with COVID-19.