Deep Learning Assessment of Small Renal Masses at Contrast-enhanced Multiphase CT.

Background Accurate characterization of suspicious small renal masses is crucial for optimized management. Deep learning (DL) algorithms may assist with this effort. Purpose To develop and validate a DL algorithm for identifying benign small renal masses at contrast-enhanced multiphase CT. Materials and Methods Surgically resected renal masses measuring 3 cm or less in diameter at contrast-enhanced CT were included. The DL algorithm was developed by using retrospective data from one hospital between 2009 and 2021, with patients randomly allocated in a training and internal test set ratio of 8:2. Between 2013 and 2021, external testing was performed on data from five independent hospitals. A prospective test set was obtained between 2021 and 2022 from one hospital. Algorithm performance was evaluated by using the area under the receiver operating characteristic curve (AUC) and compared with the results of seven clinicians using the DeLong test. Results A total of 1703 patients (mean age, 56 years ± 12 [SD]; 619 female) with a single renal mass per patient were evaluated. The retrospective data set included 1063 lesions (874 in training set, 189 internal test set); the multicenter external test set included 537 lesions (12.3%, 66 benign) with 89 subcentimeter (≤1 cm) lesions (16.6%); and the prospective test set included 103 lesions (13.6%, 14 benign) with 20 (19.4%) subcentimeter lesions. The DL algorithm performance was comparable with that of urological radiologists: for the external test set, AUC was 0.80 (95% CI: 0.75, 0.85) versus 0.84 (95% CI: 0.78, 0.88) (P = .61); for the prospective test set, AUC was 0.87 (95% CI: 0.79, 0.93) versus 0.92 (95% CI: 0.86, 0.96) (P = .70). For subcentimeter lesions in the external test set, the algorithm and urological radiologists had similar AUC of 0.74 (95% CI: 0.63, 0.83) and 0.81 (95% CI: 0.68, 0.92) (P = .78), respectively. Conclusion The multiphase CT-based DL algorithm showed comparable performance with that of radiologists for identifying benign small renal masses, including lesions of 1 cm or less. Published under a CC BY 4.0 license. Supplemental material is available for this article.

Body mass index and serum alpha-fetoprotein level associated with PD1 expression and prognosis in patients with hepatocellular carcinoma.

Background: Many factors affect the outcome of treatment with programmed death 1 (PD1) inhibitors for hepatocellular carcinoma (HCC). The objective of this study was to investigate the associations of clinicopathological parameters with PD1 expression and HCC prognosis. Methods: A total of 372 HCC patients (Western population) from The Cancer Genome Atlas (TCGA), and 115 primary HCC tissues and 52 adjacent tissues (Dataset GSE76427, Eastern population) from Gene Expression Omnibus (GEO) database were enrolled in this study. The primary outcome was 2-year relapse-free survival. Kaplan-Meier survival curves with the log-rank test were used to analyze the differences in prognosis between the two groups. X-tile software was used to confirm the optimal cut-off for clinicopathological parameters while assessing the outcome. Immunofluorescence was performed on HCC tissues to evaluate PD1 expression. Results: Expression of PD1 was up-regulated in tumor tissue from both TCGA and GSE76427 patients, which positively correlated with body mass index (BMI), serum alpha-fetoprotein (AFP) level, and prognosis. Patients with higher PD1, lower AFP, or lower BMI had longer overall survival than those with lower PD1, higher AFP, or higher BMI, respectively. AFP and PD1 expression were validated in 17 primary HCC patients from the first affiliated hospital, Zhejiang University School of Medicine. Finally, we confirmed longer relapse-free survival with higher PD1 or lower AFP. Conclusion: The findings indicate that BMI and AFP are associated with PD1 expression and HCC prognosis, offering insight for clinical management and personalized immunotherapy for HCC.

Acute ischemic Stroke combined with Stanford type A aortic dissection: A case report and literature review.

BACKGROUND: Acute aortic dissection (AAD) is a high mortality disease that can lead to acute ischemic strokes (AIS). Some of the patients with AAD combined with AIS initially present with neurological symptoms, which can easily lead to missed or delayed AAD diagnosis. This is attributed to the lack of physician awareness or the urgency of patient thrombolysis. Intravenous administration of thrombolytic therapy (IVT) for AAD is associated with poor prognostic outcomes. We report a patient with AIS combined with AAD who developed a massive cerebral infarction after receiving IVT for a missed AAD diagnosis. CASE SUMMARY: A 49-year-old man was admitted to a local hospital with an acute onset of left-sided limb weakness accompanied by slurred speech. The patient had a history of hypertension that was not regularly treated with medication. Physical examination revealed incomplete mixed aphasia and left limb hemiparesis. Cranial computed tomography (CT) scan showed bilateral basal ganglia and lateral ventricular paraventricular infarct lesions. The patient was diagnosed with AIS and was administered with IVT. After IVT, patient's muscle strength and consciousness deteriorated. From the local hospital, he was referred to our hospital for further treatment. Emergency head and neck CT angiography (CTA) scans were performed. Results showed multiple cerebral infarctions, and aortic dissection in the ascending aorta, innominate artery, as well as in the right common carotid artery. Then, the CTA of thoracoabdominal aorta was performed, which revealed a Stanford type A aortic dissection and aortic dissection extending from the aortic root to the left external iliac artery. Laceration was located in the lesser curvature of the aortic arch. AAD complicated with AIS was considered, and the patient was immediately subjected to cardiovascular surgery for treatment. The next day, the patient underwent aortic arch and ascending aortic replacement and aortic valvuloplasty. CONCLUSION: Clinical manifestations for AAD combined with AIS are diverse. Some patients may not exhibit typical chest or back pains. Therefore, patients should be carefully evaluated to exclude AAD before administering IVT in order to avoid adverse consequences.

Corrigendum to "Evans Blue Dye: A Revisit of Its Applications in Biomedicine".

[This corrects the article DOI: 10.1155/2018/7628037.].

Identification of key pathways and core genes involved in atherosclerotic plaque progression.

BACKGROUND: Atherosclerosis leads to the occurrence of cardiovascular diseases. However, the molecular mechanisms that contribute to atherosclerotic plaque rupture are incompletely characterized. We aimed to identify the genes related to atherosclerotic plaque progression that could serve as novel biomarkers and interventional targets for plaque progression. METHODS: The datasets of GSE28829 in early vs. advanced atherosclerotic plaques and those of GSE41571 in stable vs. ruptured plaques from Gene Expression Omnibus (GEO) were analyzed by using bioinformatics methods. In addition, we used quantitative reverse transcription polymerase chain reaction (qRT-PCR) to verify the expression level of core genes in a mouse atherosclerosis model. RESULTS: There were 29 common differentially expressed genes (DEGs) between the GSE28829 and GSE41571 datasets, and the DEGs were mainly enriched in the chemokine signaling pathway and the Staphylococcus aureus infection pathway (P<0.05). We identified 6 core genes (FPR3, CCL18, MS4A4A, CXCR4, CXCL2, and C1QB) in the protein-protein interaction (PPI) network, 3 of which (CXCR4, CXCL2, and CCL18) were markedly enriched in the chemokine signaling pathway. qRT-PCR analysis showed that the messenger RNA levels of two core genes (CXCR4 and CXCL2) increased significantly during plaque progression in the mouse atherosclerosis model. CONCLUSIONS: In summary, bioinformatics techniques proved useful for the screening and identification of novel biomarkers of disease. A total of 29 DEGs and 6 core genes were linked to atherosclerotic plaque progression, in particular the CXCR4 and CXCL2 genes.

Effects of preoperative pulmonary function on short-term outcomes and overall survival after video-assisted thoracic surgery lobectomy.

BACKGROUND: Preoperative pulmonary function tests are a necessary preoperative assessment tool for non-small cell lung cancer (NSCLC) patients awaiting surgery. We studied the effects of preoperative pulmonary function on short-term outcomes and overall survival (OS). METHODS: A retrospective cohort study was undertaken with adult NSCLC patients undergoing video-assisted thoracoscopic surgery (VATS) lobectomy between May 2016 and April 2017. The primary exposure variables were the percentage of predicted peak expiratory flow (PEF%), the percentage of predicted forced vital capacity (FVC%), and the percentage of predicted forced expiratory volume in 1 s. The observation outcomes were postoperative pulmonary complications (PPCs), acute kidney injury (AKI), in-hospital mortality, readmission within 30 days, and OS. Univariate and multivariate analyses were performed. RESULTS: Of the 548 patients, postoperative pneumonia was observed in 206 (37.6%). The results of the binary logistics regression analysis showed that relative to the moderate PEF% group, the risk of postoperative pneumonia was significantly increased in the marginal PEF% [odds ratio (OR) 2.076; 95% confidence interval (CI): 1.211-3.558; P=0.008] and excellent PEF% (OR 1.962; 95% CI: 1.129-3.411; P=0.017) groups. Relative to the good FVC% group, the risk of postoperative pneumonia was significantly increased in the marginal FVC% (OR 2.125; 95% CI: 1.226-3.683; P=0.007) and moderate FVC% (OR 2.230; 95% CI: 1.298-3.832; P=0.004) groups. The OS analysis did not reveal any correlations among the pulmonary function parameters and OS in this cohort. CONCLUSIONS: Preoperative PEF% and FVC% are associated with postoperative pneumonia in NSCLC patients undergoing VATS lobectomy. Preoperative PEF% is as important as FVC% in pulmonary function assessment before lung surgery.

Radiomics predict postoperative survival of patients with primary liver cancer with different pathological types.

BACKGROUND: Radiomics can be used to determine the prognosis of liver cancer, but it might vary among cancer types. This study aimed to explore the clinicopathological features, radiomics, and survival of patients with hepatocellular carcinoma (HCC), mass-type cholangiocarcinoma (MCC), and combined hepatocellular-cholangiocarcinoma (CHCC). METHODS: This was a retrospective cohort study of patients with primary liver cancer operated at the department of hepatobiliary surgery of the First Affiliated Hospital of Zhejiang University from 07/2013 to 11/2015. All patients underwent preoperative liver enhanced MRI scans and diffusion-weighted imaging (DWI). The radiomics characteristics of DWI and the enhanced equilibrium phase (EP) images were extracted. The mRMR (minimum redundancy maximum relevance) was applied to filter the parameters. RESULTS: There were 44 patients with MCC, 59 with HCC, and 33 with CHCC. Macrovascular invasion, tumor diameter, positive ferritin preoperatively, positive AFP preoperatively, positive CEA preoperatively, Correlation, Inverse Difference Moment, and Cluster Prominence in model A (DWI and clinicopathological parameters) were independently associated with overall survival (OS) (P<0.05). Lymphadenopathy, gender, positive ferritin preoperatively, positive AFP preoperatively, positive CEA preoperatively, Uniformity, and Cluster Prominence in model B (EP and clinicopathological parameters) were independently associated with OS (P<0.05). Macrovascular invasion, lymphadenopathy, gender, positive ferritin preoperatively, positive CEA preoperatively, Uniformity_EP, GLCMEnergy_DWI, and Cluster Prominence_EP in model C (image texture and clinicopathological parameters) were independently associated with OS (P<0.05). Those factors were used to construct three nomograms to predict OS. CONCLUSIONS: Clinicopathological and radiomics features are independently associated with the OS of patients with primary liver cancer.

Excessive intravenous crystalloid infusion after video-assisted thoracoscopic surgery lobectomy is associated with postoperative pneumonia.

BACKGROUND: Video-assisted thoracoscopic surgery has been widely used in thoracic surgery worldwide. Our goal was to identify the risk factors for postoperative pneumonia in patients undergoing video-assisted thoracoscopic surgery lobectomy. METHODS: A retrospective analysis of adult patients undergoing video-assisted thoracoscopic surgery lobectomy between 2016 and 05 and 2017-04 was performed. We used univariate analyses and multivariate analyses to examine risk factors for postoperative pneumonia after lobectomy. RESULTS: The incidence of postoperative pneumonia was 19.7% (n = 143/727). Patients with postoperative pneumonia had a higher postoperative length of stay and total hospital care costs when compared to those without postoperative pneumonia. Multivariate analysis showed that body mass index grading ≥24.0 kg/m2 (vs. <24.0 kg/m2: odds ratio 1.904, 95% confidence interval 1.294-2.802, P = 0.001) and right lung lobe surgery (vs. left lung lobe surgery: odds ratio 1.836, 95% confidence interval 1.216-2.771, P = 0.004) were independent risk factors of postoperative pneumonia. Total intravenous crystalloid infusion grading in the postoperative 24 h ≥ 1500 mL was also identified as the risk factors (vs. 1000 to < 1500 mL: odds ratio 2.060, 95% confidence interval 1.302-3.260, P = 0.002). CONCLUSIONS: Major risk factors for postoperative pneumonia following video-assisted thoracoscopic surgery lobectomy are body mass index grading ≥24.0 kg/m2, right lung lobe surgery and total intravenous crystalloid infusion grading in the postoperative 24 h ≥ 1500 mL.

Risk factors of postoperative pulmonary complications after minimally invasive anatomic resection for lung cancer.

PURPOSE: This study investigated the perioperative risk factors of postoperative pulmonary complications (PPCs) after minimally invasive anatomic resection for lung cancer. PATIENTS AND METHODS: We retrospectively reviewed the data from medical records of 729 lung cancer patients undergoing minimally invasive anatomic lung resections between January 2017 and December 2017. Univariate and binary logistic regression analyses were performed to select the independent risk factors for PPCs during the patient's postoperative hospitalization after surgery. RESULTS: The incidence of PPCs was 24.8% (n=181/729). No patient died during the period of hospitalization. Logistic regression analysis revealed that body mass index (BMI) ≥24.0 kg/m2 (vs <24.0 kg/m2: OR 1.514, 95% CI 1.057-2.167, P=0.024), single segmentectomy (vs single lobectomy: OR 2.115, 95% CI 1.150-3.891, P=0.016), bilobectomy or combined lobectomy and segmentectomy (vs single lobectomy: OR 2.731, 95% CI 1.013-7.361, P=0.047), and right lung lobe surgery (vs left lung lobe surgery: OR 1.519, 95% CI 1.046-2.205, P=0.028) were independent risk factors for PPCs in lung cancer patients who received minimally invasive anatomic lung resections. CONCLUSION: Individual factors such as BMI ≥24.0 kg/m2, single segmentectomy, bilobectomy or combined lobectomy and segmentectomy, and right lung lobe surgery were independent risk factors of PPCs, which should be helpful for risk stratification, patient counseling, and perioperative care for lung cancer patients.

Use of a Radiomics Model to Predict Tumor Invasiveness of Pulmonary Adenocarcinomas Appearing as Pulmonary Ground-Glass Nodules.

BACKGROUND: It is important to distinguish the classification of lung adenocarcinoma. A radiomics model was developed to predict tumor invasiveness using quantitative and qualitative features of pulmonary ground-glass nodules (GGNs) on chest CT. MATERIALS AND METHODS: A total of 599 GGNs [including 202 preinvasive lesions and 397 minimally invasive and invasive pulmonary adenocarcinomas (IPAs)] were evaluated using univariate, multivariate, and logistic regression analyses to construct a radiomics model that predicted invasiveness of GGNs. In primary cohort (comprised of patients scanned from August 2012 to July 2016), preinvasive lesions were distinguished from IPAs based on pure or mixed density (PM), lesion shape, lobulated border, and pleural retraction and 35 other quantitative parameters (P <0.05) using univariate analysis. Multivariate analysis showed that PM, lobulated border, pleural retraction, age, and fractal dimension (FD) were significantly different between preinvasive lesions and IPAs. After logistic regression analysis, PM and FD were used to develop a prediction nomogram. The validation cohort was comprised of patients scanned after Jan 2016. RESULTS: The model showed good discrimination between preinvasive lesions and IPAs with an area under curve (AUC) of 0.76 [95% CI: 0.71 to 0.80] in ROC curve for the primary cohort. The nomogram also demonstrated good discrimination in the validation cohort with an AUC of 0.79 [95% CI: 0.71 to 0.88]. CONCLUSIONS: For GGNs, PM, lobulated border, pleural retraction, age, and FD were features discriminating preinvasive lesions from IPAs. The radiomics model based upon PM and FD may predict the invasiveness of pulmonary adenocarcinomas appearing as GGNs.

Evans Blue Dye: A Revisit of Its Applications in Biomedicine.

Evans blue (EB) dye has owned a long history as a biological dye and diagnostic agent since its first staining application by Herbert McLean Evans in 1914. Due to its high water solubility and slow excretion, as well as its tight binding to serum albumin, EB has been widely used in biomedicine, including its use in estimating blood volume and vascular permeability, detecting lymph nodes, and localizing the tumor lesions. Recently, a series of EB derivatives have been labeled with PET isotopes and can be used as theranostics with a broad potential due to their improved half-life in the blood and reduced release. Some of EB derivatives have even been used in translational applications in clinics. In addition, a novel necrosis-avid feature of EB has recently been reported in some preclinical animal studies. Given all these interesting and important advances in EB study, a comprehensive revisiting of EB has been made in its biomedical applications in the review.

Clinical Characteristics and Outcomes of Propylthiouracil-Induced Antineutrophil Cytoplasmic Antibody-Associated Vasculitis in Patients with Graves' Disease: A Median 38-Month Retrospective Cohort Study from a Single Institution in China.

BACKGROUND: This study sought to investigate the clinical characteristics and outcomes of propylthiouracil (PTU)-induced antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis in patients with Graves' disease. METHODS: Sixteen patients diagnosed with PTU-induced ANCA-associated vasculitis at the authors' hospital from January 2010 to June 2017 were analyzed retrospectively. RESULTS: All 16 patients with PTU-induced ANCA-associated vasculitis were female. The mean age ± standard deviation of the patients was 39.4 ± 15.3 years (range 19-69 years), and the median time of onset was 36 months (range 1-193 months) post-PTU initiation. The median dose at the onset of PTU-induced ANCA-associated vasculitis was 150 mg/day (range 50-300 mg/day). All patients had a positive serum perinuclear staining pattern (p-ANCA) and antibodies directed against myeloperoxidase (anti-MPO). Six patients tested positive for both anti-MPO antibodies and antibodies directed against proteinase-3. Seven (43.8%) patients presented with involvement of a single organ. The kidney was the organ most commonly affected, as 12 (75%) patients were found to have disease involving this organ. PTU was stopped in all patients, corticosteroids were administered to two patients, and immunosuppressive agents and corticosteroids were administered to five patients. Three patients were lost to follow-up. However, the remaining patients achieved remission after a median follow-up period of 38 months (range 6-76 months). Patients who were positive for pANCA and displayed cytoplasmic staining showed negative findings at rates of approximately 53.8% (7/13) and 100% (6/6), respectively, following treatment. CONCLUSIONS: PTU-induced ANCA-positive vasculitis occurs at varying times and after exposure to various doses of PTU. The condition has a milder course and has a better prognosis after PTU cessation.

[Rat endothelial progenitor cells labeled with Molday IONTM EverGreen and in vitro MRI study].

OBJECTIVE: To investigate the feasibility of labeling endothelial progenitor cells (EPCs) with a novel dual modal contrast agent Molday IONTM EverGreen(MIEG) and its performance in vitro MRI. METHODS: EPCs were isolated from rat bone marrow and labeled with 10, 20, 50 µg/mL MIEG, respectively. The labeling rates were identified by Prussian blue staining and fluorescence microscopy. The vitality of EPCs labeled with 20 µg/mL MIEG was detected by trypan blue exclusion test at 1 d, 1 w, 2 w, and 6 w after labeling. EPCs labeled with different concentrations of MIEG were scanned by 3.0T MRI with T1 weighted and T2 weighted imaging. RESULTS: The labeling rates for EPCs labeled with different concentrations of MIEG were greater than 98%,and the cytoplasm of labeled EPCs was present with Prussian blue staining. Although the green lighting level went down, the labeling rate at 6 w after labeling was greater than 90%. Trypan blue exclusion test showed that there was no significant difference in the vitality between EPCs labeled with MIEG at 1 d, 1 w, 2 w and 6 w after labeling and EPCs without labeling (all P>0.05). There was no difference in signal intensity on T1 weighted image among EPCs labeled with different concentrations of MIEG. However, the signal intensity on T2 weighted image was reduced in all labeled groups, and the signal reduction became more apparent with increased concentration of MIEG. CONCLUSIONS: EPCs can be effectively labeled by MIEG without interference on the cell viability at the labeled concentration of 20 µg/mL. The signal intensity change of labeled cells can be detected sensitively by T2 weighted imaging at 3.0T MRI.