ABSTRACT
Objective: Gastric cancer (GC), one of the highest venous thromboembolism (VTE) incidence rates in cancer, contributes to considerable morbidity, mortality, and, prominently, extra cost. However, up to now, there is not a high-quality VTE model to steadily predict the risk for VTE in China. Consequently, setting up a prediction model to predict the VTE risk is imperative. Methods: Data from 3,092 patients from December 15, 2017, to December 31, 2022, were retrospectively analyzed. Multiple logistic regression analysis was performed to assess risk factors for GC, and a nomogram was constructed based on screened risk factors. A receiver operating curve (ROC) and calibration plot was created to evaluate the accuracy of the nomogram. Results: The risk factors of suffering from VTE were older age (OR = 1.02, 95% CI [1.00-1.04]), Karnofsky Performance Status (KPS) ≥ 70 (OR = 0.45, 95% CI [0.25-0.83]), Blood transfusion (OR = 2.37, 95% CI [1.47-3.84]), advanced clinical stage (OR = 3.98, 95% CI [1.59-9.99]), central venous catheterization (CVC) (OR = 4.27, 95% CI [2.03-8.99]), operation (OR = 2.72, 95% CI [1.55-4.77]), fibrinogen degradation product (FDP) >5 µg/mL (OR = 1.92, 95% CI [1.13-3.25]), and D-dimer > 0.5 mg/L (OR = 2.50, 95% CI [1.19-5.28]). The area under the ROC curve (AUC) was 0.82 in the training set and 0.85 in the validation set. Conclusion: Our prediction model can accurately predict the risk of the appearance of VTE in gastric cancer patients and can be used as a robust and efficient tool for evaluating the possibility of VTE.
Subject(s)
Nomograms , Stomach Neoplasms , Venous Thromboembolism , Humans , Venous Thromboembolism/epidemiology , Venous Thromboembolism/etiology , Venous Thromboembolism/diagnosis , Stomach Neoplasms/complications , Retrospective Studies , Male , Female , Middle Aged , Risk Factors , Aged , China/epidemiology , Risk Assessment/methods , ROC Curve , Fibrin Fibrinogen Degradation Products/analysis , Fibrin Fibrinogen Degradation Products/metabolism , AdultABSTRACT
The diagnostic accuracy of clinically significant prostate cancer (csPCa) of Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) is limited by subjectivity in result interpretation and the false positive results from certain similar anatomic structures. We aimed to establish a new model combining quantitative contrast-enhanced ultrasound, PI-RADSv2, clinical parameters to optimize the PI-RADSv2-based model. The analysis was conducted based on a data set of 151 patients from 2019 to 2022, multiple regression analysis showed that prostate specific antigen density, age, PI-RADSv2, quantitative parameters (rush time, wash-out area under the curve) were independent predictors. Based on these predictors, we established a new predictive model, the AUCs of the model were 0.910 and 0.879 in training and validation cohort, which were higher than those of PI-RADSv2-based model (0.865 and 0.821 in training and validation cohort). Net Reclassification Index analysis indicated that the new predictive model improved the classification of patients. Decision curve analysis showed that in most risk probabilities, the new predictive model improved the clinical utility of PI-RADSv2-based model. Generally, this new predictive model showed that quantitative parameters from contrast enhanced ultrasound could help to improve the diagnostic performance of PI-RADSv2 based model in detecting csPCa.
Subject(s)
Contrast Media , Nomograms , Prostatic Neoplasms , Ultrasonography , Humans , Male , Prostatic Neoplasms/diagnostic imaging , Prostatic Neoplasms/pathology , Ultrasonography/methods , Aged , Middle Aged , Prostate-Specific Antigen/blood , Prostate/diagnostic imaging , Prostate/pathology , Aged, 80 and overABSTRACT
Ovarian cancer, a group of heterogeneous diseases, presents with extensive characteristics with the highest mortality among gynecological malignancies. Accurate and early diagnosis of ovarian cancer is of great significance. Here, we present OvcaFinder, an interpretable model constructed from ultrasound images-based deep learning (DL) predictions, Ovarian-Adnexal Reporting and Data System scores from radiologists, and routine clinical variables. OvcaFinder outperforms the clinical model and the DL model with area under the curves (AUCs) of 0.978, and 0.947 in the internal and external test datasets, respectively. OvcaFinder assistance led to improved AUCs of radiologists and inter-reader agreement. The average AUCs were improved from 0.927 to 0.977 and from 0.904 to 0.941, and the false positive rates were decreased by 13.4% and 8.3% in the internal and external test datasets, respectively. This highlights the potential of OvcaFinder to improve the diagnostic accuracy, and consistency of radiologists in identifying ovarian cancer.
Subject(s)
Ovarian Neoplasms , Female , Humans , Ovarian Neoplasms/diagnostic imaging , Area Under Curve , Extremities , Radiologists , Retrospective StudiesABSTRACT
BACKGROUND: Primary prostate cancer with metastasis has a poor prognosis, so assessing its risk of metastasis is essential. METHODS: This study combined comprehensive ultrasound features with tissue proteomic analysis to obtain biomarkers and practical diagnostic image features that signify prostate cancer metastasis. RESULTS: In this study, 17 ultrasound image features of benign prostatic hyperplasia (BPH), primary prostate cancer without metastasis (PPCWOM), and primary prostate cancer with metastasis (PPCWM) were comprehensively analyzed and combined with the corresponding tissue proteome data to perform weighted gene co-expression network analysis (WGCNA), which resulted in two modules highly correlated with the ultrasound phenotype. We screened proteins with temporal expression trends based on the progression of the disease from BPH to PPCWOM and ultimately to PPCWM from two modules and obtained a protein that can promote prostate cancer metastasis. Subsequently, four ultrasound image features significantly associated with the metastatic biomarker HNRNPC (Heterogeneous nuclear ribonucleoprotein C) were identified by analyzing the correlation between the protein and ultrasound image features. The biomarker HNRNPC showed a significant difference in the five-year survival rate of prostate cancer patients (p < 0.0053). On the other hand, we validated the diagnostic efficiency of the four ultrasound image features in clinical data from 112 patients with PPCWOM and 150 patients with PPCWM, obtaining a combined diagnostic AUC of 0.904. In summary, using ultrasound imaging features for predicting whether prostate cancer is metastatic has many applications. CONCLUSION: The above study reveals noninvasive ultrasound image biomarkers and their underlying biological significance, which provide a basis for early diagnosis, treatment, and prognosis of primary prostate cancer with metastasis.
Subject(s)
Genital Neoplasms, Female , Prostatic Hyperplasia , Prostatic Neoplasms , Male , Female , Humans , Proteome , Proteomics , Phenotype , Ultrasonography , Prostatic Neoplasms/diagnostic imaging , Prostatic Neoplasms/genetics , BiomarkersABSTRACT
Background: Desmoid-type fibromatosis (DF) is a locally aggressive tumor characterized by peripheral infiltration of neoplastic cells and remote metastasis disability. This systematic review examined the efficacy and safety of thermal ablative therapy for DF tumors. Methods: A literature search was conducted using PubMed, Web of Science, Cochrane Library, and Embase from January 1, 2000, to November 12, 2022. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement was used to guide literature selection. The inclusion criteria were the following: (I) the patients were diagnosed with aggressive fibromatosis pathologically, (II) the patients were treated by thermal ablations, and (III) a focus on treatment efficacy and safety. Meanwhile, the exclusion criteria were the following: (I) cohorts of patients with hypertrophic scar, Gardner fibroma, or nodular fasciitis; (II) conference abstracts, reviews, case reports, letters to editors, comments, or editorials; (III) number of patients <5; (IV) in vitro or animal experiments; and (V) non-English language articles. The inverse variance method with a random effects model was used to obtain the pooled data. Subgroup analyses were performed to identify treatment factors. Egger test was conducted to assess the risk of publication bias. Results: After literature selection, 694 DF tumors were identified in 23 studies. In terms of modality, 13 studies used cryoablation, 9 studies used high-intensity focused ultrasound (HIFU), and 1 study used microwave ablation (MWA). The pooled symptom relief rate was 90% [95% confidence interval (CI): 80-97%], with that for HIFU being 100% (95% CI: 85-100%), that for cryoablation being 87% (95% CI: 74-97%), and that MWA being 89% (95% CI). The pooled major complication rate was 3% (95% CI: 1-7%), and that for each modality was as follows: HIFU =2% (95% CI: 0-6%), cryoablation =4% (95% CI: 1-8%), MWA =11%, ultrasound =6% (95% CI: 1-13%), computed tomography (CT) =2% (95% CI: 0-7%), and magnetic resonance imaging (MRI) =3% (95% CI: 0-14%). The pooled nonperfused volume rate (NPVR) was 76% (95% CI: 71-81%), and that for each modality was as follows: HIFU =77% (95% CI: 71-85%), cryoablation =74% (95% CI: 69-79%), ultrasound =75% (95% CI: 67-83%), CT =76% (95% CI: 67-87%), and MRI =78% (95% CI: 70-87%). The pooled local control rate was 88% (95% CI: 79-94%) and that for each modality was as follows: HIFU =99% (95% CI: 96-100%), cryoablation =80% (95% CI: 68-90%), and MWA =78%. The differences in major complication rate (P=0.77) and NPVR between imaging-guided modalities (P=0.40) were not significant, nor were the differences in symptom relief rate (P=0.32) and major complication rate (P=0.61) between ablative techniques; however, the differences in local control rate (P=0.01) were significant between ablative techniques. Conclusions: Imaging-guided thermal ablative therapies contribute to symptom relief with a duration of more than 6 months and a low major complication rate of DF tumors.
ABSTRACT
Background: Ultrasound has advantages in prostate cancer (PCa) detection and biopsy guidance but lacks a comprehensive quantitative evaluation model with multiparametric features. We aimed to construct a biparametric ultrasound (BU) scoring system for PCa risk assessment and to provide an option for clinically significant prostate cancer (csPCa) detection. Methods: From January 2015 to December 2020, 392 consecutive patients at Chongqing University Cancer Hospital who underwent BU (grayscale, Doppler flow imaging, and contrast-enhanced ultrasound) and multiparametric magnetic resonance imaging (mpMRI) before biopsy were retrospectively enrolled in the training set to construct the scoring system. From January 2021 to May 2022, 166 consecutive patients at Chongqing University Cancer Hospital were retrospectively enrolled in the validation set. The ultrasound system was compared with mpMRI, and the gold standard was a biopsy. The primary outcome was the detection of csPCa in any area with a Gleason score (GS) ≥3+4, and the secondary outcome was defined as a GS ≥4+3 and/or maximum cancer core length (MCCL) ≥6 mm. Results: Malignant association features in the nonenhanced biparametric ultrasound (NEBU) scoring system included echogenicity, capsule, and gland asymmetrical vascularity. In the biparametric ultrasound scoring system (BUS), the feature of contrast agent arrival time was added. In the training set, the area under the curves (AUCs) of the NEBU scoring system, BUS, and mpMRI were 0.86 [95% confidence interval (CI): 0.82-0.90], 0.86 (95% CI: 0.82-0.90), and 0.86 (95% CI: 0.83-0.90), respectively (P>0.05). Similar results were also observed in the validation set, in which the areas under the curves were 0.89 (95% CI: 0.84-0.94), 0.90 (95% CI: 0.85-0.95), and 0.88 (95% CI: 0.82-0.94), respectively (P>0.05). Conclusions: We constructed a BUS that showed efficacy and value for csPCa diagnosis as compared with mpMRI. However, in limited circumstances, the NEBU scoring system may also be an option.
ABSTRACT
Through digital rectal examinations (DRE) and routine prostate-specific antigen (PSA) screening, early prostate cancer (PC) treatment has become possible. However, PC is a complex and heterogeneous disease. In vivo, cancer cells can invade adjacent tissues and metastasize to other tissues resulting in hard cures. Therefore, the key to improving PC patients' survival time is preventing cancer cells' metastasis. We used mass spectrometry to profile primary PC in patients with versus without metastatic PC. We named these two groups of PC patients as high-risk primary PC (n = 11) and low-risk primary PC (n = 7), respectively. At the same time, patients with benign prostatic hyperplasia (BPH, n = 6) were used as controls to explore the possible factors driving PC metastasis. Based on comprehensive mass spectrometry analysis and biological validation, we found significant upregulation of MRPL4 expression in high-risk primary PC relative to low-risk primary PC and BPH. Further, through research of the extensive clinical cohort data in the database, we discovered that MRPL4 could be a high-risk factor for PC and serve as a potential diagnostic biomarker. The MRPL4 might be used as an auxiliary indicator for clinical status/stage of primary PC to predict patient survival time.
Subject(s)
Prostatic Hyperplasia , Prostatic Neoplasms , Male , Humans , Prostatic Hyperplasia/diagnosis , Prostatic Hyperplasia/metabolism , Proteomics , Prostate-Specific Antigen , Prostatic Neoplasms/diagnosis , Prostatic Neoplasms/pathology , Prostate/metabolism , Risk Factors , Biomarkers, TumorABSTRACT
BACKGROUND: Ovarian cancer seriously threatens the lives and health of women, and early diagnosis and treatment are still challenging. Pre-targeting is a promising strategy to improve the treatment efficacy of ovarian cancer and the results of ultrasound imaging. PURPOSE: To explore the effects of a pre-targeting strategy using streptavidin (SA) and paclitaxel (PTX)-loaded phase-shifting poly lactic-co-glycolic acid (PLGA) nanoparticles with perfluoro-n-pentane (PTX-PLGA-SA/PFPs) on the treatment and ultrasound imaging of ovarian cancer. METHODS: PTX-PLGA/PFPs were prepared with a single emulsion (O/W) solvent evaporation method and SA was attached using carbodiimide. The encapsulation efficiency of PTX and the release characteristics were assessed with high performance liquid chromatography. The phase-change characteristics of the PTX-PLGA-SA/PFPs were investigated. The anti-carcinoembryonic antigen (CEA) antibody (Ab) was covalently attached to PTX-PLGA/PFPs via carbodiimide to create PTX-PLGA-Ab/PFPs. The targeting efficiency of the nanoparticles and the viability of ovarian cancer SKOV3 cells were evaluated in each group using a microscope, flow cytometry, and cell counting kit 8 assays. RESULTS: THE PTX-PLGA-SA/PFPs were spheres with a size of 383.0 ± 75.59 nm. The encapsulation efficiency and loading capability of the nanoparticles for PTX were 71.56 ± 6.51% and 6.57 ± 0.61%, respectively. PTX was burst-released up to 70% in 2-3 d. When irradiated at 7.5 W for 3 min, the PTX-PLGA-SA/PFPs visibly enhanced the ultrasonography images (P < 0.05). At temperatures of 45°C and 60°C the nanoparticles phase-shifted into micro-bubbles and the sizes increased. The binding efficiencies of SA and Ab to the PTX-PLGA/PFPs were 97.16 ± 1.20% and 92.74 ± 5.75%, respectively. Pre-targeting resulted in a high binding efficacy and killing effect on SKOV3 cells (P < 0.05). CONCLUSIONS: The two-step pre-targeting process can significantly enhance the targeting ability of PTX-loaded PLGA nanoparticles for ovarian cancer cells and substantially improve the therapeutic efficacy. This technique provides a new method for ultrasonic imaging and precise chemotherapy for ovarian cancer.
ABSTRACT
The analysis of plant growth regulators presents a challenge due to their trace quantities and complex matrices. A novel, simple, and effective analytical method for the determination of three trace acidic plant growth regulators in Anoectochilus roxburghii (Wall.) Lindl was developed to address this issue. Three-phase hollow fiber liquid-phase microextraction combined with high-performance liquid chromatography was applied for the enrichment, purification, and determination of three acidic plant growth regulators, namely, indole-3-acetic-acid, indole-3-butyric-acid, and (+)-abscisic acid. The factors affecting extraction performance, including extractant species, pH of donor and acceptor phases, salt addition dosage, extraction time, temperature, and stirring rate, were investigated and optimized. Under optimum conditions, the proposed method provided good linearity (R2 , 0.9994-0.9999), low limit of detection (0.038-0.12 ng/mL), and acceptable relative recoveries (56.7-117.6%). The enrichment factors were between 153 and 328. The developed method was successfully applied to the enrichment and determination of plant growth regulators in Anoectochilus roxburghii (Wall.) Lindl and exhibited increased purification capacity, higher sensitivity, and decreased organic solvent consumption compared with conventional sample preparation methods. This method may provide a testing platform for the monitoring of plant growth regulator residues, ensuring the safe and effective use of traditional Chinese medicine.
Subject(s)
Liquid Phase Microextraction , Orchidaceae/chemistry , Plant Growth Regulators/analysis , Chromatography, High Pressure Liquid , Hydrogen-Ion Concentration , Particle Size , Porosity , Surface PropertiesABSTRACT
A novel, simple, and efficacious analytical method for determining of nucleotides in Anoectochilus roxburghii (Wall.) Lindl (A. roxburghii) was developed. Magnetic dispersive solid-phase micro-extraction (MDSPME) combined with high-performance liquid chromatography was applied for extraction and determination of three nucleotides, such as adenosine-5'-monophosphate (AMP), uridine-5'-monophosphate (UMP) and guanosine-5'-monophosphate (GMP) in A. roxburghii from different sources. The structure and morphology of magnetic nanoparticles, Fe3O4@GO, were illustrated by Fourier-transform infrared (FTIR), X-ray diffraction (XRD), transmission electron microscopy (TEM), and Thermagravimetric analysis (TGA) techniques. The effects of different extraction conditions on extraction efficiency were investigated and optimized. The optimum extraction conditions were performed as follows: 40.0â¯mg Fe3O4@GO were dispersed in 30â¯mL adsorption solution (pH 3.50, 2⯵g/mL), 50â¯mM NaOH was employed for elution with 12â¯min of ultra-sonication at 40⯰C. Under the aforementioned extraction conditions, the Fe3O4@GO nano-adsorbent obtained an excellent adsorption property. The corresponding linearity range for all three analytes exhibited a good linearity (r2â¯≥â¯0.9982) and notable added recoveries ranging from 88.4% to 109.8%, whereas the limit of quantitation was between 0.8-8â¯ng/mL. The enrichment factors (EF) were between 174 and 255. The proposed method showed the advantages of full purification, high EF, simplicity, and good recovery. The method was also successfully applied to nucleotides extraction and determination in A. roxburghii, showing superior reproducibility and high sensitivity. Based on this, the method could be expected to provide a novel experimental means and developmental direction for improving pretreatment and purification of nucleotides, reducing matrix effects as much as possible, in traditional Chinese medicinal materials or biological specimens.
Subject(s)
Chromatography, High Pressure Liquid , Nucleotides/analysis , Orchidaceae/chemistry , Solid Phase Microextraction , Adsorption , Drugs, Chinese Herbal/analysis , Hydrogen-Ion Concentration , Iron/chemistry , Limit of Detection , Magnetics , Magnetite Nanoparticles/chemistry , Mass Spectrometry , Medicine, Chinese Traditional , Metal Nanoparticles/chemistry , Solvents , Sonication , Spectroscopy, Fourier Transform InfraredABSTRACT
BACKGROUND: In order to better monitor non-alcoholic fatty liver disease (NAFLD) patients at higher risk for HCC, there is a need for non-invasive diagnostic approaches to screen for the presence of advanced fibrosis in these patients. The aim of this systematic review and meta-analysis will be to evaluate the diagnostic efficacy of ARFI elastography in detecting hepatic fibrosis in NAFLD patients. METHODS: Relevant studies were identified from systematic searches of several major electronic databases (PubMed, EMBASE, and the Cochrane Central Register of Controlled Trials). The primary outcomes were the summary sensitivity, summary specificity, the diagnostic odds ratio, and the summary receiver operating characteristic curve (SROC) of ARFI elastography in detecting significant fibrosis (defined as 4>F≥2) in NAFLD patients. Study quality was assessed using the Quality Assessment of Studies of Diagnostic Accuracy included in Systematic Review (QUADAS-2). RESULTS: The summary sensitivity and specificity of ARFI in detecting significant fibrosis were 80.2% (95% confidence interval (CI): 0.758-0.842; p = 0.0000) and 85.2% (95% CI: 0.808-0.890), p = 0.1617), respectively. The pooled diagnostic odds ratio of ARFI in detecting significant fibrosis was 30.13 (95% CI: 12.08-75; chi-squared = 14.59, p = 0.0237). The area under the SROC curve (AUC) was 0.898 (standard error (SE): 0.031) with a Q* index of 0.830 (SE: 0.033). CONCLUSIONS: ARFI elastography appears to be modestly accurate in detecting significant fibrosis in NAFLD patients. Future studies in this field should provide head-to-head comparisons of ARFI elastography versus other elastographic imaging modalities in NAFLD patients.