Multicenter Study on Physician-Modified Endografts for Thoracoabdominal and Complex Abdominal Aortic Aneurysm Repair.

BACKGROUND: Physician modified endografts (PMEGs) have been widely used in the treatment of complex abdominal aortic aneurysm and thoracoabdominal aortic aneurysm, however, previous data are limited to small single center studies and robust data on safety and effectiveness of PMEGs are lacking. We aimed to perform an international multicenter study analyzing the outcomes of PMEGs in complex abdominal aortic aneurysms and thoracoabdominal aortic aneurysms. METHODS: An international multicenter single-arm cohort study was performed analyzing the outcomes of PMEGs in the treatment of elective, symptomatic, and ruptured complex abdominal aortic aneurysms and thoracoabdominal aortic aneurysms. Variables and outcomes were defined according to the Society for Vascular Surgery reporting standards. Device modification and procedure details were collected and analyzed. Efficacy outcomes included technical success and safety outcomes included major adverse events and 30-day mortality. Follow-up outcomes included reinterventions, endoleaks, target vessel patency rates and overall and aortic-related mortality. Multivariable analysis was performed aiming at identifying predictors of technical success, 30-day mortality, and major adverse events. RESULTS: Overall, 1274 patients were included in the study from 19 centers. Median age was 74 (IQR, 68-79), and 75.7% were men; 45.7% were complex abdominal aortic aneurysms, and 54.3% were thoracoabdominal aortic aneurysms; 65.5% patients presented electively, 24.6% were symptomatic, and 9.9% were ruptured. Most patients (83.1%) were submitted to a fenestrated repair, 3.6% to branched repair, and 13.4% to a combined fenestrated and branched repair. Most patients (85.8%) had ≥3 target vessels included. The overall technical success was 94% (94% in elective, 93.4% in symptomatic, and 95.1% in ruptured cases). Thirty-day mortality was 5.8% (4.1% in elective, 7.6% in symptomatic, and 12.7% in ruptured aneurysms). Major adverse events occurred in 25.2% of cases (23.1% in elective, 27.8% in symptomatic, and 30.3% in ruptured aneurysms). Median follow-up was 21 months (5.6-50.6). Freedom from reintervention was 73.8%, 61.8%, and 51.4% at 1, 3, and 5 years; primary target vessel patency was 96.9%, 93.6%, and 90.3%. Overall survival and freedom from aortic-related mortality was 82.4%/92.9%, 69.9%/91.6%, and 55.0%/89.1% at 1, 3, and 5 years. CONCLUSIONS: PMEGs were a safe and effective treatment option for elective, symptomatic, and ruptured complex aortic aneurysms. Long-term data and future prospective studies are needed for more robust and detailed analysis.

Nasopharyngeal airway long noncoding RNAs of infants with bronchiolitis and subsequent risk of developing childhood asthma.

BACKGROUND: Severe bronchiolitis (ie, bronchiolitis requiring hospitalization) during infancy is a major risk factor for developing childhood asthma. However, the biological mechanisms linking these 2 conditions remain unclear. OBJECTIVE: We sought to investigate the longitudinal relationship between nasopharyngeal airway long noncoding RNA (lncRNA) in infants with severe bronchiolitis and subsequent asthma development. METHODS: In this multicenter prospective cohort study of infants with severe bronchiolitis, we performed RNA sequencing of nasopharyngeal airway lncRNAs at index hospitalization. First, we identified differentially expressed lncRNAs (DE-lncRNAs) associated with asthma development by age 6 years. Second, we investigated the associations of DE-lncRNAs with asthma-related clinical characteristics. Third, to characterize the function of DE-lncRNAs, we performed pathway analysis for mRNA targeted by DE-lncRNAs. Finally, we examined the associations of DE-lncRNAs with nasal cytokines at index hospitalization. RESULTS: Among 343 infants with severe bronchiolitis (median age, 3 months), we identified 190 DE-lncRNAs (false-discovery rate [FDR] < 0.05) associated with asthma development (eg, LINC02145, RAMP2-AS1, and PVT1). These DE-lncRNAs were associated with asthma-related clinical characteristics (FDR < 0.05), for example, respiratory syncytial virus or rhinovirus infection, infant eczema, and IgE sensitization. Furthermore, DE-lncRNAs were characterized by asthma-related pathways, including mitogen-activated protein kinase, FcɛR, and phosphatidylinositol 3-kinase (PI3K)-protein kinase B signaling pathways (FDR < 0.05). These DE-lncRNAs were also associated with nasal cytokines (eg, IL-1ß, IL-4, and IL-13; FDR < 0.05). CONCLUSIONS: In a multicenter cohort study of infants with severe bronchiolitis, we identified nasopharyngeal airway lncRNAs associated with childhood asthma development, characterized by asthma-related clinical characteristics, asthma-related pathways, and nasal cytokines. Our approach identifies lncRNAs underlying the bronchiolitis-asthma link and facilitates the early identification of infants at high risk of subsequent asthma development.

Long-term Durability Between Parent and Child Patient Reported Outcomes in Eosinophilic Esophagitis.

BACKGROUND: Because young children cannot self-report symptoms, there is a need for parent surrogate reports. While early work suggested parent child alignment for eosinophil esophagitis (EoE) patient reported outcomes (PROs), the longitudinal alignment is unclear. OBJECTIVE: To assess the agreement and longitudinal stability of PROs between children with EoE and their parents. METHODS: 292 parent-child respondents completed 723 completed questionnaires over 5 years in an observational trial in the Consortium of Eosinophilic Gastrointestinal Disease Researchers. The change in and agreement between parent and child Pediatric Eosinophilic Esophagitis Symptom Score version 2 (PEESSv2.0) and Pediatric Quality of Life Eosinophilic Esophagitis Module (PedsQL-EoE) PROs over time were assessed using Pearson correlation and Bland-Altman analyses. Clinical factors influencing PROs and their agreement were evaluated using linear mixed models. RESULTS: The cohort had a median disease duration equalling 3.7 years and was predominantly male (73.6%) and white (85.3%). Child and parent PEESSv2.0 response groups were identified and were stable over time. There was strong correlation between child and parent report (PEESSv2.0 0.83, PedsQL-EoE 0.74) with minimal pairwise differences for symptoms. Longitudinally, parent-reported PedsQL-EoE scores were stable (p ≥ 0.32), whereas child-reported PedsQL-EoE scores improved (p = 0.026). A larger difference in parent and child PedsQL-EoE reports was associated with younger age (p < 0.001) and differences were driven by psychosocial PRO domains. CONCLUSION: There is strong longitudinal alignment between child and parent report using EoE PROs. These data provide evidence that parent report is a stable proxy for objective EoE symptoms in their children.

Analysis of immune-related adverse events in gastrointestinal malignancy patients treated with immune checkpoint inhibitors.

Immune checkpoint inhibitors are becoming an increasingly common treatment for advanced gastrointestinal cancer, but the possibility of immune-related adverse events has raised concerns. This study aimed to evaluate the risks of immune-related adverse events between patients who received immune checkpoint inhibitors and those who received chemotherapy among different types of gastrointestinal cancer. The study utilized data from the multicenter TriNetX database in the United States covering the period between 2015 and 2022. Hazard ratios and 95% confidence intervals were used to describe the relative hazard of immune-related adverse events based on comparing time-to-event rates. Our study revealed that the incidence of immune-related adverse events was significantly higher in patients who received immune checkpoint inhibitors and chemotherapy compared to those who received chemotherapy only in treating gastrointestinal cancer. CTLA-4 inhibitors tended to have a higher rate of immune-related adverse events compared to PD-1/PD-L1 inhibitors. Our study found a lower mortality rate among patients who developed immune-related adverse events compared to those who did not after propensity score matching (HR, 0.661; 95% CI 0.620-0.704; p < .01). We provide important real-world data on the incidence and impact of immune-related adverse events in patients with advanced gastrointestinal cancer treated with immune checkpoint inhibitors. Our study's results support clinicians in making informed decisions about the potential benefits and risks of immune checkpoint inhibitor therapy for patients with gastrointestinal cancer.

Chemotherapy versus chemotherapy plus immune checkpoint inhibitors for the first-line treatment of unresectable thymic carcinoma: A multicenter retrospective study.

Thymic carcinoma (TC) is a rare malignant tumor with a poor prognosis, and there is currently limited data on the use of immunotherapy in patients with unresectable TC. In this study, data of patients with unresectable TC diagnosed from January 2017 were retrospectively collected from multiple centers. Treatment response, progression-free survival (PFS), overall survival (OS), survival-independent prognostic factor, and adverse events (AEs) were further analyzed. As a result, a total of 93 patients with unresectable TC were enrolled, of which 54 received first-line chemotherapy, and 39 received chemotherapy plus immune checkpoint inhibitors (ICIs). The objective response rate was 50% (27/54) in the chemotherapy group and 76.9% (30/39) in the chemotherapy plus ICIs group. The chemotherapy plus ICIs group achieved significant median PFS benefit (8.8 vs. 34.9 months, p < .001) and median OS benefit (41.8 months vs. not reached, p = .025). Multivariate analysis showed that ICIs and local therapy were independent prognostic factors for PFS. In addition, 17 patients developed immune-related AEs (IRAEs), of which 15 (38.5%) had Grade 1 or 2 IRAEs and 2 (5.1%) had Grade 3 IRAEs in the chemotherapy plus ICIs group. In conclusion, the efficacy of chemotherapy plus ICIs is superior to chemotherapy, and the adverse effects are manageable in patients with unresectable TC.

A multicenter study on deep learning for glioblastoma auto-segmentation with prior knowledge in multimodal imaging.

A precise radiotherapy plan is crucial to ensure accurate segmentation of glioblastomas (GBMs) for radiation therapy. However, the traditional manual segmentation process is labor-intensive and heavily reliant on the experience of radiation oncologists. In this retrospective study, a novel auto-segmentation method is proposed to address these problems. To assess the method's applicability across diverse scenarios, we conducted its development and evaluation using a cohort of 148 eligible patients drawn from four multicenter datasets and retrospective data collection including noncontrast CT, multisequence MRI scans, and corresponding medical records. All patients were diagnosed with histologically confirmed high-grade glioma (HGG). A deep learning-based method (PKMI-Net) for automatically segmenting gross tumor volume (GTV) and clinical target volumes (CTV1 and CTV2) of GBMs was proposed by leveraging prior knowledge from multimodal imaging. The proposed PKMI-Net demonstrated high accuracy in segmenting, respectively, GTV, CTV1, and CTV2 in an 11-patient test set, achieving Dice similarity coefficients (DSC) of 0.94, 0.95, and 0.92; 95% Hausdorff distances (HD95) of 2.07, 1.18, and 3.95 mm; average surface distances (ASD) of 0.69, 0.39, and 1.17 mm; and relative volume differences (RVD) of 5.50%, 9.68%, and 3.97%. Moreover, the vast majority of GTV, CTV1, and CTV2 produced by PKMI-Net are clinically acceptable and require no revision for clinical practice. In our multicenter evaluation, the PKMI-Net exhibited consistent and robust generalizability across the various datasets, demonstrating its effectiveness in automatically segmenting GBMs. The proposed method using prior knowledge in multimodal imaging can improve the contouring accuracy of GBMs, which holds the potential to improve the quality and efficiency of GBMs' radiotherapy.

Acupuncture for hot flashes in hormone receptor-positive breast cancer: A pooled analysis of individual patient data from parallel randomized trials.

BACKGROUND: Hot flashes are a common side effect of endocrine therapy (ET) that contribute to poor quality of life and decreased treatment adherence. METHODS: Patients with breast cancer wo were receiving ET and experiencing hot flashes were enrolled through three parallel, randomized trials conducted in the United States, China, and South Korea. Participants were randomized to either immediate acupuncture (IA) or delayed acupuncture control (DAC). IA participants received 20 acupuncture sessions over 10 weeks, whereas DAC participants received usual care, then crossed over to acupuncture with a reduced intensity. The primary end point was a change in score on the endocrine symptom subscale of the Functional Assessment of Cancer Therapy (FACT)-Endocrine Symptoms between baseline and week 10. Secondary end points included the hot flash score and the FACT-Breast score. A planned pooled analysis of individual patient data was performed using longitudinal mixed models. RESULTS: In total, 158 women with stage 0-III breast cancer were randomized (United States, n = 78; China, n = 40; South Korea, n = 40). At week 10, IA participants reported statistically significant improvements in the endocrine symptom subscale score (mean change ± standard error: 5.1 ± 0.9 vs. 0.2 ± 1.0; p = .0003), the hot flash score (-5.3 ± 0.9 vs. -1.4 ± 0.9; p < .003), and the FACT-Breast total score (8.0 ± 1.6 vs. -0.01 ± 1.6; p = .0005) compared with DAC participants. The effect of the acupuncture intervention differed by site (p = .005). CONCLUSIONS: Acupuncture led to statistically and clinically meaningful improvements in hot flashes, endocrine symptoms, and breast cancer-specific quality of life in women undergoing ET for breast cancer in the United States, China, and South Korea.

Sex and ethnic disparities in hepatitis B evaluation and treatment across the world.

BACKGROUND & AIMS: Oral antiviral therapy with nucleos(t)ide analogues (NAs) for chronic hepatitis B (CHB) is well-tolerated and lifesaving, but real-world data on utilization are limited. We examined rates of evaluation and treatment in patients from the REAL-B consortium. METHODS: This was a cross-sectional study nested within our retrospective multinational clinical consortium (2000-2021). We determined the proportions of patients receiving adequate evaluation, meeting AASLD treatment criteria, and initiating treatment at any time during the study period. We also identified factors associated with receiving adequate evaluation and treatment using multivariable logistic regression analyses. RESULTS: We analyzed 12,566 adult treatment-naïve patients with CHB from 25 centers in 9 countries (mean age 47.1 years, 41.7% female, 96.1% Asian, 49.6% Western region, 8.7% cirrhosis). Overall, 73.3% (9,206 patients) received adequate evaluation. Among the adequately evaluated, 32.6% (3,001 patients) were treatment eligible by AASLD criteria, 83.3% (2,500 patients) of whom were initiated on NAs, with consistent findings in analyses using EASL criteria. On multivariable logistic regression adjusting for age, sex, cirrhosis, and ethnicity plus region, female sex was associated with adequate evaluation (adjusted odds ratio [aOR] 1.13, p = 0.004), but female treatment-eligible patients were about 50% less likely to initiate NAs (aOR 0.54, p <0.001). Additionally, the lowest evaluation and treatment rates were among Asian patients from the West, but no difference was observed between non-Asian patients and Asian patients from the East. Asian patients from the West (vs. East) were about 40-50% less likely to undergo adequate evaluation (aOR 0.60) and initiate NAs (aOR 0.54) (both p <0.001). CONCLUSIONS: Evaluation and treatment rates were suboptimal for patients with CHB in both the East and West, with significant sex and ethnic disparities. Improved linkage to care with linguistically competent and culturally sensitive approaches is needed. IMPACT AND IMPLICATIONS: Significant sex and ethnic disparities exist in hepatitis B evaluation and treatment, with female treatment-eligible patients about 50% less likely to receive antiviral treatment and Asian patients from Western regions also about 50% less likely to receive adequate evaluation or treatment compared to Asians from the East (there was no significant difference between Asian patients from the East and non-Asian patients). Improved linkage to care with linguistically competent and culturally sensitive approaches is needed.

One-year outcomes of a novel venous stent for symptomatic iliofemoral venous obstruction: prospective cohort study.

BACKGROUND: A stent with characteristics of a hybrid design may have advantages in improving the patency of symptomatic iliofemoral vein obstruction. This study assessed the safety and effectiveness of the V-Mixtent Venous Stent in treating symptomatic iliofemoral outflow obstruction. METHODS: Eligible patients had a Clinical-Etiologic-Anatomic-Physiologic (CEAP) C classification of ≥ 3 or a Venous Clinical Severity Score (VCSS) pain score of ≥ 2. The primary safety endpoint was the rate of major adverse events within 30 days. The primary effectiveness endpoint was the 12-month primary patency rate. Secondary endpoints included changes in VCSS from baseline to 6 and 12 months, alterations in CEAP C classification, Chronic Venous Disease Quality of Life Questionnaire (CIVIQ-14) scores at 12 months, and stent durability measures. RESULTS: Between December 2020 and November 2021, 171 patients were enrolled across 15 institutions. A total of 185 endovenous stents were placed, with 91.81% of subjects receiving one stent and 8.19% receiving 2 stents. Within 30 days, only two major adverse events occurred (1.17%; 95% confidence interval [CI], 0.14-4.16%), below the literature-defined performance goal of 11% (P < .001). The 12-month primary patency rate (91.36%; 95% CI, 85.93-95.19%; P < .001) exceeded the literature-defined performance goal. VCSS changes from baseline demonstrated clinical improvement at 6 months (- 4.30 ± 3.66) and 12 months (- 4.98 ± 3.67) (P < .001). Significant reduction in symptoms, as measured by CEAP C classification and CIVIQ-14, was observed from pre-procedure to 12 months (P < .001). CONCLUSIONS: The 12-month outcomes confirm the safety and effectiveness of the V-Mixtent Venous Stent in managing symptomatic iliofemoral venous outflow obstruction, including clinical symptom improvement compared to before treatment.

Comparative outcomes of aortobifemoral bypass with or without previous endovascular kissing stenting of the aortoiliac bifurcation.

OBJECTIVE: The aim of this multicenter national study was to compare the outcomes of primary open surgery by aorto-bifemoral bypass (ABFB) with those performed after a failed endovascular treatment (EVT) by kissing stent technique for complex aortoiliac occlusive disease (AIOD) lesions (TransAtlantic Inter-Society Consensus [TASC] II C and D). METHODS: All consecutive ABFB cases carried out at 12 vascular surgery centers between 2016 and 2021 were retrospectively collected and analyzed. Data included patients' baseline demographics and clinical characteristics, procedural details, perioperative outcomes, and follow-up results (survival, patency, amputation). The study cohort was divided into two groups based on indications for ABFB: primary treatment vs secondary treatment after EVT failure. RESULTS: Overall, 329 patients underwent ABFB during the study period (71% males; mean age, 64 years), of which 285 were primary treatment and 44 were after prior EVT. At baseline, no significant differences were found between study groups in demographics and clinical characteristics. TASC C and D lesions were similarly represented in the study groups (TASC C: 22% vs 78%; TASC D: 16% vs 84%). No major differences were found between study groups in terms of procedural details, early mortality, and perioperative complications. At 5 years, primary patency rates were significantly higher for primary ABFB (88%; 95% confidence interval [CI], 93.2%-84%) as compared with ABFB after prior EVT (69%; 95% CI 84.9%-55%; log rank P value < .001); however, the 5-year rates of secondary patency (100% vs 95%; 95% CI, 100%-86%) and limb salvage (97%; 95% CI, 99%-96 vs 97%; 95% CI, 100%-94%) were similar between study groups. CONCLUSIONS: Surgical treatment of TASC C/D AIOD with ABFB seems to be equally safe and effective when performed after prior EVT, although primary ABFB seemed to have higher primary patency rates. Despite the need for more frequent reinterventions, secondary patency and limb salvage rates were similar. However, future large prospective trials are required to confirm these findings.

Proximal sealing in the aortic arch for inner curve disease using the Custom Relay® Scalloped and Fenestrated stent graft.

OBJECTIVE: This study aims to analyze early and midterm results of custom-made proximal scallop and fenestrated stent-grafts for thoracic endovascular aortic repair (TEVAR) with proximal landing zone (PLZ) in the aortic arch. METHODS: All consecutive patients treated with the custom made proximal scalloped and fenestrated Relay stent grafts (Terumo Aortic Bolton Medical Inc., Sunrise, USA) in ten Italian centers between January 2014 and December 2022 were included. The primary endpoints were technical success, incidence of intraoperative major adverse events (MAEs), deployment accuracy, and rate of early neurological complications, endoleaks (Els) and retrograde aortic dissection. RESULTS: During the study period, 49 patients received TEVAR with Relay custom-made endograft in Italy were enrolled. The median patient age was 70.1 years (interquartile range, 23-86 years) and 65.3% were male. The indication for treatment was atherosclerotic aneurysms in 59.2% of cases and penetrating aortic ulcer in 22.4%. The endograft configuration was proximal fenestration in 55.1% and scallop in 44.9%. The PLZ was zone 0 in 25 cases (51%), zone 1 in 14 cases (28.6%), and zone 2 in 10 cases (20.4%). The supra-aortic debranching procedures were 38 (77.5%). Technical success was 97.9% (48/49) due to one case (2.0%) of inaccurate deployment. Intraoperatively, one (2.0%) type Ia and one (2.0%) type III Els were detected. There were no cases of in-hospital mortality, MAEs and retrograde dissection. Three (6.1%) minor strokes (National Institutes of Health Stroke Scale score≤4) were observed. At a mean follow-up time of 36.3 + 21.3 months the rate of type I-III Els and reintervention was 4.1%, respectively. Four patients (8.2%) died during the follow-up period, one (2.1%) from abdominal aortic rupture and three (6.1%) for non-aortic causes. CONCLUSIONS: Our early and midterm outcomes suggest that scalloped and fenestrated TEVAR may provide an acceptable alternative treatment option for aortic arch pathologies. Large-scale studies are needed to assess the long-term durability of this technique.

Midregional proatrial naturetic peptide (MRproANP) and copeptin (COPAVP) as predictors of all-cause mortality in recently diagnosed mild to moderate COPD-results from COSYCONET.

BACKGROUND: MRproANP and COPAVP are prognostic markers for mortality in chronic obstructive pulmonary disease (COPD). Furthermore, these biomarkers predict mortality due to cardiovascular diseases, which are important prognostically determining comorbidities in patients with COPD. However, less is known about these biomarkers in recently diagnosed mild to moderate COPD. Therefore, we analyzed these biomarkers as potential predictors of mortality in recently diagnosed mild to moderate COPD. METHODS: The blood biomarkers considered were copeptin (COPAVP), midregional adrenomedullin (MRproADM), midregional proatrial naturetic peptide (MRproANP), and fibrinogen. Analyses were performed in patients with stable "recently diagnosed mild to moderate COPD" defined by GOLD grades 0-2 and diagnosis of COPD ≤ 5 years prior to inclusion into the COSYCONET cohort (COPD and Systemic Consequences-Comorbidities Network), using Cox regression analysis with stepwise adjustment for multiple COPD characteristics, comorbidities, troponin and NT-proBNP. RESULTS: 655 patients with recently diagnosed mild to moderate COPD were included. In the initial regression model, 43 of 655 patients died during the 6-year follow-up, in the final model 27 of 487. Regression analyses with adjustment for confounders identified COPAVP and MRproANP as statistically robust biomarkers (p < 0.05 each) of all-cause mortality, while MRproADM and fibrinogen were not. The fourth quartile of MRproANP (97 pmol/L) was associated with a hazard ratio of 4.5 (95%CI: 1.6; 12.8), and the fourth quartile of COPAVP (9.2 pmol/L) with 3.0 (1.1; 8.0). The results for MRproANP were confirmed in the total cohort of grade 0-4 (n = 1470 finally). CONCLUSION: In patients with recently diagnosed mild to moderate COPD, elevated values of COPVP and in particular MRproANP were robust, independent biomarkers for all-cause mortality risk after adjustment for multiple other factors. This suggests that these markers might be considered in the risk assessment of early COPD.

Multicenter PET image harmonization using generative adversarial networks.

PURPOSE: To improve reproducibility and predictive performance of PET radiomic features in multicentric studies by cycle-consistent generative adversarial network (GAN) harmonization approaches. METHODS: GAN-harmonization was developed to harmonize whole-body PET scans to perform image style and texture translation between different centers and scanners. GAN-harmonization was evaluated by application to two retrospectively collected open datasets and different tasks. First, GAN-harmonization was performed on a dual-center lung cancer cohort (127 female, 138 male) where the reproducibility of radiomic features in healthy liver tissue was evaluated. Second, GAN-harmonization was applied to a head and neck cancer cohort (43 female, 154 male) acquired from three centers. Here, the clinical impact of GAN-harmonization was analyzed by predicting the development of distant metastases using a logistic regression model incorporating first-order statistics and texture features from baseline 18F-FDG PET before and after harmonization. RESULTS: Image quality remained high (structural similarity: left kidney ≥ 0.800, right kidney ≥ 0.806, liver ≥ 0.780, lung ≥ 0.838, spleen ≥ 0.793, whole-body ≥ 0.832) after image harmonization across all utilized datasets. Using GAN-harmonization, inter-site reproducibility of radiomic features in healthy liver tissue increased at least by ≥ 5 ± 14% (first-order), ≥ 16 ± 7% (GLCM), ≥ 19 ± 5% (GLRLM), ≥ 16 ± 8% (GLSZM), ≥ 17 ± 6% (GLDM), and ≥ 23 ± 14% (NGTDM). In the head and neck cancer cohort, the outcome prediction improved from AUC 0.68 (95% CI 0.66-0.71) to AUC 0.73 (0.71-0.75) by application of GAN-harmonization. CONCLUSIONS: GANs are capable of performing image harmonization and increase reproducibility and predictive performance of radiomic features derived from different centers and scanners.

Testing the generalizability and effectiveness of deep learning models among clinics: sperm detection as a pilot study.

BACKGROUND: Deep learning has been increasingly investigated for assisting clinical in vitro fertilization (IVF). The first technical step in many tasks is to visually detect and locate sperm, oocytes, and embryos in images. For clinical deployment of such deep learning models, different clinics use different image acquisition hardware and different sample preprocessing protocols, raising the concern over whether the reported accuracy of a deep learning model by one clinic could be reproduced in another clinic. Here we aim to investigate the effect of each imaging factor on the generalizability of object detection models, using sperm analysis as a pilot example. METHODS: Ablation studies were performed using state-of-the-art models for detecting human sperm to quantitatively assess how model precision (false-positive detection) and recall (missed detection) were affected by imaging magnification, imaging mode, and sample preprocessing protocols. The results led to the hypothesis that the richness of image acquisition conditions in a training dataset deterministically affects model generalizability. The hypothesis was tested by first enriching the training dataset with a wide range of imaging conditions, then validated through internal blind tests on new samples and external multi-center clinical validations. RESULTS: Ablation experiments revealed that removing subsets of data from the training dataset significantly reduced model precision. Removing raw sample images from the training dataset caused the largest drop in model precision, whereas removing 20x images caused the largest drop in model recall. by incorporating different imaging and sample preprocessing conditions into a rich training dataset, the model achieved an intraclass correlation coefficient (ICC) of 0.97 (95% CI: 0.94-0.99) for precision, and an ICC of 0.97 (95% CI: 0.93-0.99) for recall. Multi-center clinical validation showed no significant differences in model precision or recall across different clinics and applications. CONCLUSIONS: The results validated the hypothesis that the richness of data in the training dataset is a key factor impacting model generalizability. These findings highlight the importance of diversity in a training dataset for model evaluation and suggest that future deep learning models in andrology and reproductive medicine should incorporate comprehensive feature sets for enhanced generalizability across clinics.

Identification of prognostic signatures in remnant gastric cancer through an interpretable risk model based on machine learning: a multicenter cohort study.

OBJECTIVE: The purpose of this study was to develop an individual survival prediction model based on multiple machine learning (ML) algorithms to predict survival probability for remnant gastric cancer (RGC). METHODS: Clinicopathologic data of 286 patients with RGC undergoing operation (radical resection and palliative resection) from a multi-institution database were enrolled and analyzed retrospectively. These individuals were split into training (80%) and test cohort (20%) by using random allocation. Nine commonly used ML methods were employed to construct survival prediction models. Algorithm performance was estimated by analyzing accuracy, precision, recall, F1-score, area under the receiver operating characteristic curve (AUC), confusion matrices, five-fold cross-validation, decision curve analysis (DCA), and calibration curve. The best model was selected through appropriate verification and validation and was suitably explained by the SHapley Additive exPlanations (SHAP) approach. RESULTS: Compared with the traditional methods, the RGC survival prediction models employing ML exhibited good performance. Except for the decision tree model, all other models performed well, with a mean ROC AUC above 0.7. The DCA findings suggest that the developed models have the potential to enhance clinical decision-making processes, thereby improving patient outcomes. The calibration curve reveals that all models except the decision tree model displayed commendable predictive performance. Through CatBoost-based modeling and SHAP analysis, the five-year survival probability is significantly influenced by several factors: the lymph node ratio (LNR), T stage, tumor size, resection margins, perineural invasion, and distant metastasis. CONCLUSIONS: This study established predictive models for survival probability at five years in RGC patients based on ML algorithms which showed high accuracy and applicative value.

Efficacy of adding levofloxacin to gemcitabine and nanoparticle-albumin-binding paclitaxel combination therapy in patients with advanced pancreatic cancer: study protocol for a multicenter, randomized phase 2 trial (T-CORE2201).

BACKGROUND: Advanced pancreatic cancer is one of the leading causes of cancer-related deaths. For patients with advanced pancreatic cancer, gemcitabine and nanoparticle albumin-binding paclitaxel (nabPTX) combination (GEM/nabPTX) therapy is one of the recommended first-line treatments. Several retrospective studies have suggested that the addition of levofloxacin improves the efficacy of GEM/nabPTX therapy in patients with advanced pancreatic cancer. This prospective study aims to evaluate whether the addition of antibiotics improves the treatment efficacy of GEM/nabPTX as a first-line chemotherapy in patients with advanced pancreatic cancer. METHODS: This multicenter, prospective, randomized, phase 2 trial will included 140 patients. Patients with advanced pancreatic cancer will be randomized in a 1:1 ratio to either the GEM/nabPTX therapy group or the GEM/nabPTX plus levofloxacin group. The primary endpoint for the two groups is median progression-free survival time (mPFS) for the full analysis set (FAS). The secondary endpoints for the two groups are median overall survival (mOS), response rate (RR), disease control rate (DCR), and adverse event (AE) for the FAS and mPFS, mOS, RR, DCR, and AE for the per-protocol set. This study will enroll patients treated with GEM/nabPTX as the first-line chemotherapy for stage IV pancreatic adenocarcinoma. DISCUSSION: GEM/nabPTX is a standard first-line chemotherapy regimen for patients with advanced pancreatic cancer. Recently, the superiority of 5-fluorouracil, liposomal irinotecan, and oxaliplatin combination therapy (NALIRIFOX) to GEM/nabPTX as first-line therapy for pancreatic cancer has been reported. However, the efficacy of NALIRIFOX is inadequate. Based on previous retrospective studies, it is hypothesized that treatment efficacy will improve when levofloxacin is added to GEM/nabPTX therapy. If the AEs (such as leukopenia, neutropenia, and peripheral neuropathy) that occur at an increased rate with levofloxacin and GEM/nabPTX combination therapy can be carefully monitored and properly managed, this simple intervention can be expected to improve the prognosis of patients with advanced pancreatic cancer. TRIAL REGISTRATION: This study was registered with the Japan Registry of Clinical Trials (jRCT; registry number: jRCTs021230005).

Gray matter atrophy is constrained by normal structural brain network architecture in depression.

BACKGROUND: There is growing evidence that gray matter atrophy is constrained by normal brain network (or connectome) architecture in neuropsychiatric disorders. However, whether this finding holds true in individuals with depression remains unknown. In this study, we aimed to investigate the association between gray matter atrophy and normal connectome architecture at individual level in depression. METHODS: In this study, 297 patients with depression and 256 healthy controls (HCs) from two independent Chinese dataset were included: a discovery dataset (105 never-treated first-episode patients and matched 130 HCs) and a replication dataset (106 patients and matched 126 HCs). For each patient, individualized regional atrophy was assessed using normative model and brain regions whose structural connectome profiles in HCs most resembled the atrophy patterns were identified as putative epicenters using a backfoward stepwise regression analysis. RESULTS: In general, the structural connectome architecture of the identified disease epicenters significantly explained 44% (±16%) variance of gray matter atrophy. While patients with depression demonstrated tremendous interindividual variations in the number and distribution of disease epicenters, several disease epicenters with higher participation coefficient than randomly selected regions, including the hippocampus, thalamus, and medial frontal gyrus were significantly shared by depression. Other brain regions with strong structural connections to the disease epicenters exhibited greater vulnerability. In addition, the association between connectome and gray matter atrophy uncovered two distinct subgroups with different ages of onset. CONCLUSIONS: These results suggest that gray matter atrophy is constrained by structural brain connectome and elucidate the possible pathological progression in depression.

Harmonizing T1-Weighted Images to Improve Consistency of Brain Morphology Among Different Scanner Manufacturers in Alzheimer's disease.

BACKGROUND: Brain MRI scanner variability can introduce bias in measurements. Harmonizing scanner variability is crucial. PURPOSE: To develop a harmonization method aimed at removing scanner variability, and to evaluate the consistency of results in multicenter studies. STUDY TYPE: Retrospective. POPULATION: Multicenter data from 170 healthy participants (males/females = 98/72; age = 73.8 ± 7.3) and 170 Alzheimer's disease patients (males/females = 98/72; age = 76.2 ± 8.5) were compared with reference data from another 340 participants. FIELD STRENGTH/SEQUENCE: 3-T, magnetization prepared rapid gradient echo and turbo field echo; 1.5-T, inversion recovery prepared fast spoiled gradient echo T1-weighted sequences. ASSESSMENT: Gray matter (GM) brain images, obtained through segmentation of T1-weighted images, were utilized to evaluate the performance of the harmonization method using common orthogonal basis extraction (HCOBE) and four other methods (removal of artificial voxel effect by linear regression, RAVEL; Z_score; general linear model, GLM; ComBat). Linear discriminant analysis (LDA) was used to access the effectiveness of different methods in reducing scanner variability. The performance of harmonization methods in preserving GM volumes heterogeneity was evaluated by the similarity of the relationship between GM proportion and age in the reference and multicenter data. Furthermore, the consistency of the harmonized multicenter data with the reference data were evaluated based on classification results (train/test = 7/3) and brain atrophy. STATISTICAL TESTS: Two-sample t-tests, area under the curve (AUC), and Dice coefficients were used to analyze the consistency of results from the reference and harmonized multicenter data. A P-value <0.01 was considered statistically significant. RESULTS: HCOBE reduced the scanner variability from 0.09 before harmonization to 0.003 (ideal: 0, RAVEL/Z_score/GLM/ComBat = 0.087/0.003/0.006/0.013). GM volumes showed no significant difference (P = 0.52) between the reference and HCOBE-harmonized multicenter data. Consistency evaluation showed that AUC values of 0.95 for both reference and HCOBE-harmonized multicenter data (RAVEL/Z_score/GLM/ComBat = 0.86/0.86/0.84/0.89), and the Dice coefficient increased from 0.73 before harmonization to 0.82 (ideal: 1, RAVEL/Z_score/GLM/ComBat = 0.39/0.64/0.59/0.74). DATA CONCLUSION: HCOBE may help to remove scanner variability and could improve the consistency of results in multicenter studies. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 1.

Reproducible Radiomics Features from Multi-MRI-Scanner Test-Retest-Study: Influence on Performance and Generalizability of Models.

BACKGROUND: Radiomics models trained on data from one center typically show a decline of performance when applied to data from external centers, hindering their introduction into large-scale clinical practice. Current expert recommendations suggest to use only reproducible radiomics features isolated by multiscanner test-retest experiments, which might help to overcome the problem of limited generalizability to external data. PURPOSE: To evaluate the influence of using only a subset of robust radiomics features, defined in a prior in vivo multi-MRI-scanner test-retest-study, on the performance and generalizability of radiomics models. STUDY TYPE: Retrospective. POPULATION: Patients with monoclonal plasma cell disorders. Training set (117 MRIs from center 1); internal test set (42 MRIs from center 1); external test set (143 MRIs from center 2-8). FIELD STRENGTH/SEQUENCE: 1.5T and 3.0T; T1-weighted turbo spin echo. ASSESSMENT: The task for the radiomics models was to predict plasma cell infiltration, determined by bone marrow biopsy, noninvasively from MRI. Radiomics machine learning models, including linear regressor, support vector regressor (SVR), and random forest regressor (RFR), were trained on data from center 1, using either all radiomics features, or using only reproducible radiomics features. Models were tested on an internal (center 1) and a multicentric external data set (center 2-8). STATISTICAL TESTS: Pearson correlation coefficient r and mean absolute error (MAE) between predicted and actual plasma cell infiltration. Fisher's z-transformation, Wilcoxon signed-rank test, Wilcoxon rank-sum test; significance level P < 0.05. RESULTS: When using only reproducible features compared with all features, the performance of the SVR on the external test set significantly improved (r = 0.43 vs. r = 0.18 and MAE = 22.6 vs. MAE = 28.2). For the RFR, the performance on the external test set deteriorated when using only reproducible instead of all radiomics features (r = 0.33 vs. r = 0.44, P = 0.29 and MAE = 21.9 vs. MAE = 20.5, P = 0.10). CONCLUSION: Using only reproducible radiomics features improves the external performance of some, but not all machine learning models, and did not automatically lead to an improvement of the external performance of the overall best radiomics model. TECHNICAL EFFICACY: Stage 2.

A multi-center study to predict the risk of intraoperative hypothermia in gynecological surgery patients using preoperative variables.

OBJECTIVES: Hypothermia is highly common in patients undergoing gynecological surgeries under general anesthesia, so the length of hospitalization and even the risk of mortality are substantially increased. Our aim was to develop a simple and practical model to preoperatively identify gynecological surgery patients at risk of intraoperative hypothermia. METHODS: In this retrospective study, we collected data from 802 patients who underwent gynecological surgery at three medical centers from June 2022 to August 2023. We further allocated the patients to a training group, an internal validation group, or an external validation group. The preliminary predictive factors for intraoperative hypothermia in gynecological patients were determined using the least absolute shrinkage and selection operator (LASSO) method. The final predictive factors were subsequently identified through multivariate logistic regression analysis, and a nomogram for predicting the occurrence of hypothermia was established. RESULTS: A total of 802 patients were included, with 314 patients in the training cohort (mean age 48.5 ± 12.6 years), 130 patients in the internal validation cohort (mean age 49.9 ± 12.5 years), and 358 patients in the external validation cohort (mean age 47.6 ± 14.0 years). LASSO regression and multivariate logistic regression analyses indicated that body mass index, minimally invasive surgery, baseline heart rate, baseline body temperature, history of previous surgery, and aspartate aminotransferase level were associated with intraoperative hypothermia in gynecological surgery patients. This nomogram was constructed based on these six variables, with a C-index of 0.712 for the training cohort. CONCLUSIONS: We established a practical predictive model that can be used to preoperatively predict the occurrence of hypothermia in gynecological surgery patients. CLINICAL TRIAL REGISTRATION: chictr.org.cn, identifier ChiCTR2300071859.