Evaluation of the JF5-based Aspergillus galactomannoprotein lateral flow device for diagnosing invasive aspergillosis in cancer patients.

PURPOSE: Cancer patients are at heightened risk for invasive aspergillosis (IA), a condition associated with elevated mortality risk. The JF5-based Aspergillus Galactomannoprotein Lateral Flow Device (AspLFD) offers rapid point-of-care testing (POCT) for IA. This study evaluated the diagnostic performance of AspLFD in cancer populations. METHODS: This retrospective study examined cancer patient bronchoalveolar lavage fluid (BALF) and serum samples collected between September 2021 and January 2023. Both AspLFD and galactomannan (GM) assays were conducted, and the results were analysed by two independent researchers. RESULTS: This study included 242 samples from 218 cancer patients, with 58 BALF and 184 serum samples. The overall agreement between AspLFD and GM assay results was 92.1%, with a kappa value of 0.552. AspLFD diagnosed proven/probable IA with a sensitivity and specificity of 91.7% and 95.3%, respectively, whereas GM exhibited sensitivity and specificity values of 83.3% and 93.7%, respectively. There were no statistical differences in the sensitivity and specificity between the two methods (P > 0.05). For serum analyses, AspLFD and GM exhibited similar sensitivity (66.7% vs. 66.7%, P > 0.05) and specificity (98.6% vs. 96.6%, P > 0.05) values. However, the sensitivity of the AspLFD was superior to the GM assay (100% vs. 88.9%) in BALF analyses but the difference was not statistically significant (P > 0.05), with no difference in specificity (83.7% vs. 83.7%, P > 0.05). In the solid-tumour cohort, both the AspLFD and GM assay exhibited high sensitivity (100% for both) and specificity (94.2% vs. 92.8%, P > 0.05). CONCLUSION: The AspLFD demonstrated good performance in diagnosing IA in cancer patients, especially those with solid tumours. The AspLFD is thus an alternative POCT, particularly when GM evaluations are not readily available.

Novel biomarkers based on dual-energy computed tomography for risk stratification of very early distant metastasis in colorectal cancer after surgery.

Background: Very early distant metastasis (VEDM) for patients with colorectal cancer (CRC) following surgery suggests failure of local treatment strategy and few biomarkers are available for its effective risk stratification. This study aimed to explore the potential of quantitative dual-energy computed tomography (DECT) spectral parameters and build models to predict VEDM. Methods: Consecutive patients suspected of having CRC and with a clinical indication for enhanced CT from April 2021 to July 2022 at a single institution were prospectively enrolled to undertake spectral CT scanning. The spectral features were extracted by two reviewers and intraclass correlation coefficient (ICC) was used for interobserver agreement evaluation. A total of 16 spectral parameters, including unenhanced effective atomic number, triphasic iodine concentrations (ICs)/normalized ICs (NICs)-A/V/E/1/NIC-A/V/E/spectral curve slopes (λ-A/V/E), two arterial enhancement fractions (AEFs), and venous enhancement fraction (VEF), were determined for analysis. Patients with and without VEDM after surgery were matched using propensity score matching (PSM). The diagnostic performance was assessed using the area under the curve (AUC). Models of multiple modalities were generated. Results: In total, 222 patients were included (141 males, age range, 32-83 years) and 13 patients developed VEDM. Interobserver agreement ranged from good to excellent (ICC, 0.773-0.964). A total of three spectral parameters (VEF, λ-V, and 1/NIC-V) exhibited significant discriminatory ability (P<0.05) in predicting VEDM, with AUCs of 0.822 [95% confidence interval (CI): 0.667-0.926], 0.738 (95% CI: 0.573-0.866), and 0.713 (95% CI: 0.546-0.846) and optimal cutoff points of 67.16%, 2.46, and 2.44, respectively. The performance of these spectral parameters was validated in the entire cohort; the combined spectral model showed comparable efficiency to the combined clinical model [AUC, 0.771 (95% CI: 0.622-0.919) vs. 0.779 (95% CI: 0.663-0.894), P>0.05]; the clinical-spectral model achieved further improved AUC of 0.887 (95% CI: 0.812-0.962), which was significantly higher than the combined clinical model (P=0.015), yet not superior to the combined spectral model (P=0.078). Conclusions: Novel spectral parameters showed potential in predicting VEDM in CRC following surgery in this preliminary study, which were closely related with spectral perfusion in the venous phase. However, further studies with larger samples are warranted.

Nomogram based on preoperative clinical and MRI features to estimate the microvascular invasion status and the prognosis of solitary intrahepatic mass-forming cholangiocarcinoma.

PURPOSE: To develop a nomogram based on preoperative clinical and magnetic resonance imaging (MRI) features for the microvascular invasion (MVI) status in solitary intrahepatic mass-forming cholangiocarcinoma (sIMCC) and to evaluate whether it could predict recurrence-free survival (RFS). METHODS: We included 115 cases who experienced MRI examinations for sIMCC with R0 resection. The preoperative clinical and MRI features were extracted. Independent predictors related to MVI+ were evaluated by stepwise multivariate logistic regression, and a nomogram was constructed. A receiver operating characteristic (ROC) curve was used to assess the predictive ability. All patients were classified into high- and low-risk groups of MVI. Then, the correlations of the nomogram with RFS in patents with sIMCC were analyzed by Kaplan-Meier method. RESULTS: The occurrence rate of MVI+ was 38.3% (44/115). The preoperative independent predictors of MVI+ were carbohydrate antigen 19-9 > 37 U/ml, tumor size > 5 cm, and an ill-defined tumor boundary. Integrating these predictors, the nomogram exerted a favorable diagnostic performance with areas under the ROC curve of 0.767 (95% confidence interval [CI] 0.654-0.881) in the development cohort, and 0.760 (95% CI 0.591-0.929) in the validation cohort. In the RFS analysis, significant differences were observed between the high- and low-risk MVI groups (6-month RFS rates: 64.5% vs. 78.8% and 46.7% vs. 82.4% in the development and validation cohorts, respectively) (P < 0.05). CONCLUSIONS: A nomogram based on clinical and MRI features is a potential biomarker of MVI and may be a potent method to classify the risk of recurrence in patients with sIMCC.

MRI-based Multiregional Radiomics for Pretreatment Prediction of Distant Metastasis After Neoadjuvant Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer.

RATIONALE AND OBJECTIVES: To develop and validate a nomogram based on intratumoral and peritumoral radiomics signatures for pretreatment prediction of distant metastasis-free survival (DMFS) in patients after neoadjuvant chemoradiotherapy (NCRT) with locally advanced rectal cancer (LARC). MATERIALS AND METHODS: This retrospective study included 230 patients (161 training cohort; 69 validation cohort) with LARC who underwent NCRT and surgery. Radiomics features were extracted on T2-weighted images from gross tumor volume (GTV) and volumes of 4-mm, 6-mm, and 8-mm peritumoral regions (PTV4, PTV6, and PTV8). The least absolute shrinkage and selection operator (LASSO)-Cox analysis were used for features selection and models construction. The performance of each model in predicting DMFS was evaluated by the Concordance index (C-index) and time-independent receiver operating characteristic curve (ROC). RESULTS: The PTV4 radiomics model demonstrated superior performance compared to the PTV6 and PTV8 radiomics models, with C-indexes of 0.750 and 0.703 in the training and validation cohorts, respectively. The nomogram was constructed by integrating the GTV radiomics signature, PTV4 radiomics signature, and relevant clinical characteristics, including CA19-9 level, clinical T stage, and clinical N stage. The nomogram achieved C-indexes of 0.831 and 0.748, with corresponding AUCs of 0.872 and 0.808 for 5-year DMFS in the training and validation cohorts, respectively. Kaplan-Meier analysis revealed that a cut-off value of 1.653 effectively stratified patients into high- and low-risk groups for DM (P < 0.001). CONCLUSION: The intra-peritumoral radiomics nomogram is a favorable tool for clinicians to develop personalized systemic treatment and intensive follow-up strategies to improve patient prognosis.

Preoperative MRI features predicting very early recurrence of intrahepatic mass-forming cholangiocarcinoma after R0 resection: a comparison with the AJCC 8th edition staging system.

PURPOSE: This study aimed to establish a nomogram based on preoperative magnetic resonance imaging (MRI) features to predict the very early recurrence (VER, less than 6 months) of intrahepatic mass-forming cholangiocarcinoma (IMCC) after R0 resection. METHODS: This study enrolled a group of 193 IMCC patients from our institution between March 2010 and January 2022. Patients were allocated into the development cohort (n = 137) and the validation cohort (n = 56), randomly, and the preoperative clinical and MRI features were collected. Univariate and multivariate stepwise logistic regression assessments were adopted to assess predictors of VER. Nomogram was constructed and certificated in the validation cohort. The performance of the prediction nomogram was evaluated by its discrimination, calibration, and clinical utility. The performance of the nomogram was compared with the T stage of the American Joint Committee on Cancer (AJCC) 8th edition staging system. RESULTS: Fifty-three patients (27.5%) experienced VER of the tumor and 140 patients (72.5%) with non-VER, during the follow-up period. After multivariate stepwise logistic regression, number of lesions, diffuse hypoenhancement on arterial phase, necorsis and suspicious lymph nodes were independently associated with VER. The nomogram demonstrated significantly higher area under the curve (AUC) of 0.813 than T stage (AUC = 0.666, P = 0.006) in the development cohort, whereas in the validation cohort, the nomogram showed better discrimination performance, with an AUC of 0.808 than T stage (0.705) with no significantly difference (P = 0.230). Decision curve analysis reflected the clinical net benefit of the nomogram. CONCLUSION: The nomogram based on preoperative MRI features is a reliable tool to predict VER for patients with IMCC after R0 resection. This nomogram will be helpful to improve survival prediction and individualized treatment.

Predicting the microvascular invasion and tumor grading of intrahepatic mass-forming cholangiocarcinoma based on magnetic resonance imaging radiomics and morphological features.

Background: Preoperative diagnosis of microvascular invasion (MVI) and tumor grading of intrahepatic mass-forming cholangiocarcinoma (IMCC) using imaging findings can facilitate patient treatment decision-making. This study was conducted to establish and validate nomograms based on magnetic resonance imaging (MRI) radiomics and morphological features for predicting the MVI and tumor grading of IMCC before radical hepatectomy. Methods: A total of 235 patients with resected IMCC at the Chinese Academy of Medical Sciences and Peking Union Medical College were divided into a training set (n=167) and a validation set (n=68), retrospectively. Clinical data and MRI morphological features were recorded. Univariate and multivariate analyses were conducted to identify the significant features for the prediction of MVI and tumor grading. Radiomics features were extracted from T2-weighted imaging fat-suppressed and diffusion-weighted imaging (DWI). Radiomics signatures (rad_scores) were built based on the least absolute shrinkage and selection operator (LASSO) method. Then, the nomograms were constructed by combining the rad_scores and the significant clinical or MRI morphologic features. The predictive performances for MVI and tumor grading were evaluated by the area under the receiver operating characteristic curve (AUC), calibration, and clinical utility. Results: Totals of 16 and 9 radiomics features were selected to build the rad_scores for the prediction of MVI and tumor grading for the training and validation set, respectively. The nomogram for the prediction of MVI comprised the morphologic features including number of tumors, tumor margin, and rad_score. For the prediction of tumor grading, the nomogram comprised the number of tumors, tumor necrosis, and rad_score. The best discriminations were observed in the training and validation sets for the MVI nomogram [AUCs of 0.874, 95% confidence interval (CI): (0.822-0.926) and 0.869 (0.783-0955)] and tumor grading nomogram [AUCs of 0.827 (0.763-0.891) and 0.848 (0.759-0.937)]. Decision curve analysis (DCA) further confirmed the clinical utilities of the nomograms. Conclusions: Nomograms based on MRI radiomics and morphological features can effectively predict the individualized risks of MVI and tumor grading for IMCC.

Risk stratification for overall survival and recurrence-free survival after R0 resection for solitary intrahepatic mass-forming cholangiocarcinoma based on preoperative MRI and clinical features.

PURPOSE: This study aimed to establish two nomograms for predicting overall survival (OS) and recurrence-free survival (RFS) in patients with solitary intrahepatic mass-forming cholangiocarcinoma (IMCC) based on preoperative magnetic resonance imaging (MRI) features. METHODS: This retrospective study included 120 consecutive patients who were diagnosed with solitary IMCC. Preoperative MRI and clinical features were collected. Based on the univariate and multivariate Cox regression analyses, two nomograms were constructed to predict OS and RFS, respectively. The effective performance of the nomograms was evaluated using concordance index (C-index). The prognostic stratification systems for OS and RFS were developed and used to classify patients into high- and low-risk groups. RESULTS: Suspicious lymph nodes, arterial phase (AP) enhancement patterns, and bile duct dilatation were independent predictors of OS, while suspicious lymph nodes, AP enhancement patterns, and necrosis were independent predictors of RFS. The nomograms achieved the C-index values of 0.705/0.710 for OS and 0.721/0.759 for RFS in the development/validation cohorts, which were significantly higher than those of the T and TNM stages (P < 0.05). Patients were stratified into high- and low-risk groups, the 1-year OS and RFS rates of high-risk patients were poorer than those of patients with low-risk in the development cohort (OS: 93.5% vs 76.3%, P < 0.001; RFS: 74.5% vs 22.4%, P < 0.001). Similar results were observed in the validation cohort. CONCLUSIONS: Two nomograms were constructed based on preoperative MRI features in patients with solitary IMCC for predicting the OS and RFS and facilitate further prognostic stratification.

A multiple-time-scale comparative study for the added value of magnetic resonance imaging-based radiomics in predicting pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer.

Objective: Radiomics based on magnetic resonance imaging (MRI) shows potential for prediction of therapeutic effect to neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC); however, thorough comparison between radiomics and traditional models is deficient. We aimed to construct multiple-time-scale (pretreatment, posttreatment, and combined) radiomic models to predict pathological complete response (pCR) and compare their utility to those of traditional clinical models. Methods: In this research, 165 LARC patients undergoing nCRT followed by surgery were enrolled retrospectively, which were divided into training and testing sets in the ratio of 7:3. Morphological features on pre- and posttreatment MRI, coupled with clinical data, were evaluated by univariable and multivariable logistic regression analysis for constructing clinical models. Radiomic parameters were derived from pre- and posttreatment T2- and diffusion-weighted images to develop the radiomic signatures. The clinical-radiomics models were then generated. All the models were developed in the training set and then tested in the testing set, the performance of which was assessed using the area under the receiver operating characteristic curve (AUC). Radiomic models were compared with the clinical models with the DeLong test. Results: One hundred and sixty-five patients (median age, 55 years; age interquartile range, 47-62 years; 116 males) were enrolled in the study. The pretreatment maximum tumor length, posttreatment maximum tumor length, and magnetic resonance tumor regression grade were selected as independent predictors for pCR in the clinical models. In the testing set, the pre- and posttreatment and combined clinical models generated AUCs of 0.625, 0.842, and 0.842 for predicting pCR, respectively. The MRI-based radiomic models performed reasonably well in predicting pCR, but neither the pure radiomic signatures (AUCs, 0.734, 0.817, and 0.801 for the pre- and posttreatment and combined radiomic signatures, respectively) nor the clinical-radiomics models (AUCs, 0.734, 0.860, and 0.801 for the pre- and posttreatment and combined clinical-radiomics models, respectively) showed significant added value compared with the clinical models (all P > 0.05). Conclusion: The MRI-based radiomic models exhibited no definite added value compared with the clinical models for predicting pCR in LARC. Radiomic models can serve as ancillary tools for tailoring adequate treatment strategies.

Implication of MRI Risk Stratification System on the Survival Benefits of Adjuvant Chemotherapy After Neoadjuvant Chemoradiotherapy in Patients With Locally Advanced Rectal Cancer.

RATIONALE AND OBJECTIVES: To investigate the implication of a Magnetic resonance imaging (MRI) risk stratification system on the selection of patients with locally advanced rectal cancer (LARC) who can benefit from adjuvant chemotherapy (ACT) after neoadjuvant chemoradiotherapy (NCRT). MATERIALS AND METHODS: This retrospective study included 328 patients with LARC who underwent NCRT and surgery. The median follow-up duration was 79 months (Interquartile range, 66-94 months). Cox logistic regression analysis was used to identify MRI risk factors and develop a risk stratification system to stratify patients into groups with high and low risks. Kaplan-Meier curves of distant metastasis-free survival (DMFS) and overall survival (OS) were used to show the benefits of ACT and stratify results based on the MRI risk stratification system and postoperative pathological staging. RESULTS: An MRI risk stratification system was built based on four MRI risk factors, including MRI-identified T3b-T4 stage, N1-N2 stage, extramural venous invasion, and tumor deposits. 74 (22.6%) patients with 3-4 MRI risk factors were classified into the MRI high-risk group. ACT could significantly improve 5-year DMFS (19.2% versus 52.1%; p < 0.001) and OS (34.6% versus 75.0%; p < 0.001) for patients in the MRI high-risk group, while ACT had no survival benefit for patients in the MRI low-risk group. The benefits of ACT were not observed in patients with any pathological staging subgroups (ypT0-2N0, ypT3-4N0, and ypN+). CONCLUSION: Patients in the MRI high-risk group could benefit from ACT, regardless of postoperative pathological staging. Baseline MRI should be considered more in ACT decision-making.

Predictive factors of microvascular invasion in patients with intrahepatic mass-forming cholangiocarcinoma based on magnetic resonance images.

PURPOSE: The aim of this retrospective study was to develop and validate a preoperative nomogram for predicting microvascular invasion (MVI) in patients with intrahepatic mass-forming cholangiocarcinoma (IMCC) based on magnetic resonance imaging (MRI). METHODS: In this retrospective study, 224 consecutive patients with clinicopathologically confirmed IMCC were enrolled. Patients whose data were collected from February 2010 to December 2020 were randomly divided into the training (131 patients) and internal validation (51 patients) datasets. The data from January 2021 to November 2021 (42 patients) were allocated to the time-independent validation dataset. Univariate and multivariate forward logistic regression analyses were used to identify preoperative MRI features that were significantly related to MVI, which were then used to develop the nomogram. We used the area under the receiver operating characteristic curve (AUC) and calibration curve to evaluate the performance of the nomogram. RESULTS: Interobserver agreement of MRI qualitative features was good to excellent, with κ values of 0.613-0.882. Multivariate analyses indicated that the following variables were independent predictors of MVI: multiple tumours (odds ratio [OR]) = 4.819, 95% confidence interval [CI] 1.562-14.864, P = 0.006), ill-defined margin (OR = 6.922, 95% CI 2.883-16.633, P < 0.001), and carbohydrate antigen 19-9 (CA 19-9) > 37 U/ml (OR = 2.890, 95% CI 1.211-6.897, P = 0.017). A nomogram incorporating these factors was established using well-fitted calibration curves. The nomogram showed good diagnostic efficacy for MVI, with AUC values of 0.838, 0.819, and 0.874 for the training, internal validation, and time-independent validation datasets, respectively. CONCLUSION: A nomogram constructed using independent factors, namely the presence of multiple tumours, ill-defined margins, and CA 19-9 > 37 U/ml could predict the presence of MVI. This can facilitate personalised therapeutic strategy and clinical management in patients with IMCC.

Prediction of lymph node metastasis in stage T1-2 rectal cancers with MRI-based deep learning.

OBJECTIVES: This study aimed to investigate whether a deep learning (DL) model based on preoperative MR images of primary tumors can predict lymph node metastasis (LNM) in patients with stage T1-2 rectal cancer. METHODS: In this retrospective study, patients with stage T1-2 rectal cancer who underwent preoperative MRI between October 2013 and March 2021 were included and assigned to the training, validation, and test sets. Four two-dimensional and three-dimensional (3D) residual networks (ResNet18, ResNet50, ResNet101, and ResNet152) were trained and tested on T2-weighted images to identify patients with LNM. Three radiologists independently assessed LN status on MRI, and diagnostic outcomes were compared with the DL model. Predictive performance was assessed with AUC and compared using the Delong method. RESULTS: In total, 611 patients were evaluated (444 training, 81 validation, and 86 test). The AUCs of the eight DL models ranged from 0.80 (95% confidence interval [CI]: 0.75, 0.85) to 0.89 (95% CI: 0.85, 0.92) in the training set and from 0.77 (95% CI: 0.62, 0.92) to 0.89 (95% CI: 0.76, 1.00) in the validation set. The ResNet101 model based on 3D network architecture achieved the best performance in predicting LNM in the test set, with an AUC of 0.79 (95% CI: 0.70, 0.89) that was significantly greater than that of the pooled readers (AUC, 0.54 [95% CI: 0.48, 0.60]; p < 0.001). CONCLUSION: The DL model based on preoperative MR images of primary tumors outperformed radiologists in predicting LNM in patients with stage T1-2 rectal cancer. KEY POINTS: • Deep learning (DL) models with different network frameworks showed different diagnostic performance for predicting lymph node metastasis (LNM) in patients with stage T1-2 rectal cancer. • The ResNet101 model based on 3D network architecture achieved the best performance in predicting LNM in the test set. • The DL model based on preoperative MR images outperformed radiologists in predicting LNM in patients with stage T1-2 rectal cancer.

Controlled Preparation and Device Application of Sub-5 nm Graphene Nanoribbons and Graphene Nanoribbon/Carbon Nanotube Intramolecular Heterostructures.

Narrow graphene nanoribbons (GNRs) and GNR/single-walled carbon nanotube (SWNT) intramolecular heterojunctions are ideal candidates to construct next-generation electronic and optoelectronic devices. However, the fabrication of high-quality long sub-5 nm wide GNRs and GNR/SWNT heterojunctions is a great challenge. Here, we report a method to produce high-quality sub-5 nm wide GNRs with smooth edges and GNR/SWNT intramolecular heterostructures via palladium-catalyzed full and partial unzipping of SWNTs, respectively. The resulting GNRs could be as narrow as 2.2 nm and had an average length of over 1 µm. By adjusting the unzipping time and the deposited positions of palladium nanoparticles, controlled multiple GNR/SWNT heterostructures were also fabricated on an individual parent SWNT. A GNR field-effect transistor (FET) constructed by a 3.1 nm wide GNR could simultaneously achieve a high on/off current ratio of 1.1 × 104 and a large mobility of 598 cm2 V-1 s-1. The photovoltaic device based on a single GNR (2.4 nm in width)/SWNT (0.8 nm in diameter) heterojunction exhibited a large open-circuit voltage (Voc) of 0.52 V and a high external power conversion efficiency (η) of 4.7% under the 1550 nm wavelength illumination of 931 mW cm-2. Our method provides a pathway to controllably prepare high-quality sub-5 nm GNRs and GNR/SWNT heterojunctions for fundamental studies and practical applications in the electronic and optoelectronic fields.

Risk stratification for 1- to 2-cm gastric gastrointestinal stromal tumors: visual assessment of CT and EUS high-risk features versus CT radiomics analysis.

OBJECTIVES: To investigate the ability of CT and endoscopic sonography (EUS) in predicting the malignant risk of 1-2-cm gastric gastrointestinal stromal tumors (gGISTs) and to clarify whether radiomics could be applied for risk stratification. METHODS: A total of 151 pathologically confirmed 1-2-cm gGISTs from seven institutions were identified by contrast-enhanced CT scans between January 2010 and March 2021. A detailed description of EUS morphological features was available for 73 gGISTs. The association between EUS or CT high-risk features and pathological malignant potential was evaluated. gGISTs were randomly divided into three groups to build the radiomics model, including 74 in the training cohort, 37 in validation cohort, and 40 in testing cohort. The ROIs covering the whole tumor volume were delineated on the CT images of the portal venous phase. The Pearson test and least absolute shrinkage and selection operator (LASSO) algorithm were used for feature selection, and the ROC curves were used to evaluate the model performance. RESULTS: The presence of EUS- and CT-based morphological high-risk features, including calcification, necrosis, intratumoral heterogeneity, irregular border, or surface ulceration, did not differ between very-low and intermediate risk 1-2-cm gGISTs (p > 0.05). The radiomics model consisting of five radiomics features showed favorable performance in discrimination of malignant 1-2-cm gGISTs, with the AUC of the training, validation, and testing cohort as 0.866, 0.812, and 0.766, respectively. CONCLUSIONS: Instead of CT- and EUS-based morphological high-risk features, the CT radiomics model could potentially be applied for preoperative risk stratification of 1-2-cm gGISTs. KEY POINTS: • The presence of EUS- and CT-based morphological high-risk factors, including calcification, necrosis, intratumoral heterogeneity, irregular border, or surface ulceration, did not correlate with the pathological malignant potential of 1-2-cm gGISTs. • The CT radiomics model could potentially be applied for preoperative risk stratification of 1-2-cm gGISTs.

RUNX2 facilitates aggressiveness and chemoresistance of triple negative breast cancer cells via activating MMP1.

Breast cancer remains the most common malignancy in women and constantly threatens the lives of patients worldwide. State-of-the-art renewal has indicated the involvement of RUNX-associated transcription factor 2 (RUNX2) in tumorigenesis and cancer progression, yet the detailed information during breast cancer is largely obscure. Herein, we took advantage of breast cancer cell lines and in vivo tumorigenicity test as well as multifaceted phenotypic analyses (e.g., RNA-sequencing, ChIP and qRT-PCR assay) to verify the pathogenic mechanism of RUNX2 in triple negative breast cancer aggressiveness and chemoresistance. Strikingly, the proliferation, migration, invasion and chemoresistance of resistant cell lines in triple negative breast cancer was effectively suppressed by RUNX2 silencing, and the in vivo tumorigenicity was significantly weakened as well. Furthermore, with the aid of transcriptomic and bioinformatic analyses, we found MMP1 was highly expressed in triple negative breast cancer (TNBC) and showed a strong correlation with the poor prognosis of the patients, which was consistent with the expression pattern of RUNX2. Finally, by conducting ChIP and qRT-PCR assessment, we verified that RUNX2 functioned via directly binding to the specific motifs in the promoter of MMP1 and thus activating the transcriptional process. Collectively, our data demonstrated the facilitating effect of RUNX2 during triple negative breast cancer progression by directly orchestrating the expression of MMP1, which supplied overwhelming new references for RUNX2-MMP1 axis serving as a novel candidate for breast cancer diagnosis and treatment.

Application value of modified skin expansion in PICC catheterization under the guidance of B-ultrasound in gastrointestinal cancer patients with chemotherapy.

OBJECTIVE: To investigate the clinical value of modified skin expansion in peripherally inserted central venous catheter (PICC) catheterization under the guidance of B-ultrasound in gastrointestinal cancer patients with chemotherapy. METHODS: In this retrospective study, 60 gastrointestinal cancer patients with chemotherapy were included and divided into an experimental group (treated with modified skin expansion in PICC catheterization under the guidance of B-ultrasound) and a control group (treated with the longitudinal skin expansion in PICC catheterization under the guidance of B-ultrasound). The bleeding volume, pain score, success rate of one-time PICC catheterization and the incidence of complication were compared between the two groups. RESULTS: The modified skin expansion in PICC catheterization under the guidance of B-ultrasound had obvious effect on gastrointestinal cancer patients with chemotherapy. The VAS scores were significantly lower after PICC catheterization in the experimental group compared with the control group (P < 0.05). The success rate of one-time PICC catheterization in the experimental group was significantly higher than that in the control group. Moreover, the incidence of complication and massive bleeding during puncture and 24 hours after puncture was significantly lower in the observation group compared with that in the control group. CONCLUSIONS: Modified skin expansion in PICC catheterization under the guidance of B-ultrasound in gastrointestinal cancer patients with chemotherapy can improve the success rate of one-time sheath delivery, effectively reduce the amount of blood leakage after catheterization, reduce patients' pain and reduce the incidence of complications.

Predicting perineural invasion using histogram analysis of zoomed EPI diffusion-weighted imaging in rectal cancer.

PURPOSE: To investigate the utility of histogram analysis of zoomed EPI diffusion-weighted imaging (DWI) for predicting the perineural invasion (PNI) status of rectal cancer (RC). METHODS: This prospective study evaluated 94 patients diagnosed with histopathologically confirmed RC between July 2020 and July 2021. Patients underwent preoperative rectal magnetic resonance imaging (MRI) examinations, including the zoomed EPI DWI sequence. Ten whole-tumor histogram parameters of each patient were derived from zoomed EPI DWI. Reproducibility was evaluated according to the intra-class correlation coefficient (ICC). The association of the clinico-radiological and histogram features with PNI status was assessed using univariable analysis for trend and multivariable logistic regression analysis with ß value calculation. Receiver operating characteristic (ROC) curve analysis was conducted to assess the diagnostic performance. RESULTS: Forty-two patients exhibited positive PNI. The inter- and intraobserver agreements were excellent for the histogram parameters (all ICCs > 0.80). The maximum (p = 0.001), energy (p = 0.021), entropy (p = 0.021), kurtosis (p < 0.001), and skewness (p < 0.001) were significantly higher in the positive PNI group than in the negative PNI group. Multivariable analysis showed that higher MRI T stage [ß = 2.154, 95% confidence interval (CI) 0.932-3.688; p = 0.002] and skewness (ß = 0.779, 95% CI 0.255-1.382; p = 0.006) were associated with positive PNI. The model combining skewness and MRI T stage had an area under the ROC curve of 0.811 (95% CI 0.724-0.899) for predicting PNI status. CONCLUSION: Histogram parameters in zoomed EPI DWI can help predict the PNI status in RC.

Selecting Candidates for Organ-Preserving Strategies After Neoadjuvant Chemoradiotherapy for Rectal Cancer: Development and Validation of a Model Integrating MRI Radiomics and Pathomics.

BACKGROUND: Histopathologic evaluation after surgery is the gold standard to evaluate treatment response to neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC). However, it cannot be used to guide organ-preserving strategies due to poor timeliness. PURPOSE: To develop and validate a multiscale model incorporating radiomics and pathomics features for predicting pathological good response (pGR) of down-staging to stage ypT0-1N0 after nCRT. STUDY TYPE: Retrospective. POPULATION: A total of 153 patients (median age, 55 years; 109 men; 107 training group; 46 validation group) with clinicopathologically confirmed LARC. FIELD STRENGTH/SEQUENCE: A 3.0-T; fast spin echo T2 -weighted and single-shot EPI diffusion-weighted images. ASSESSMENT: The differences in clinicoradiological variables between pGR and non-pGR groups were assessed. Pretreatment and posttreatment radiomics signatures, and pathomics signature were constructed. A multiscale pGR prediction model was established. The predictive performance of the model was evaluated and compared to that of the clinicoradiological model. STATISTICAL TESTS: The χ2 test, Fisher's exact test, t-test, the minimum redundancy maximum relevance algorithm, the least absolute shrinkage and selection operator logistic regression algorithm, regression analysis, receiver operating characteristic curve (ROC) analysis, Delong method. P < 0.05 indicated a significant difference. RESULTS: Pretreatment radiomics signature (odds ratio [OR] = 2.53; 95% CI: 1.58-4.66), posttreatment radiomics signature (OR = 9.59; 95% CI: 3.04-41.46), and pathomics signature (OR = 3.14; 95% CI: 1.40-8.31) were independent factors for predicting pGR. The multiscale model presented good predictive performance with areas under the curve (AUC) of 0.93 (95% CI: 0.88-0.98) and 0.90 (95% CI: 0.78-1.00) in the training and validation groups, those were significantly higher than that of the clinicoradiological model with AUCs of 0.69 (95% CI: 0.55-0.82) and 0.68 (95% CI: 0.46-0.91) in both groups. DATA CONCLUSION: A model incorporating radiomics and pathomics features effectively predicted pGR after nCRT in patients with LARC. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 4.

Paracrine Effects of Recombinant Human Adiponectin Promote Bone Regeneration.

Bone regeneration is a delicate physiological process. Non-union and delayed fracture healing remains a great challenge in clinical practice nowadays. Bone and fat hold a close relationship to remain balanced through hormones and cytokines. Adiponectin is a well-known protein to maintain the hemostasis, which may be an interesting target for fracture healing. Herein, we provided a facile and efficient method to obtain high-purity and high-yield recombinant human adiponectin (ADPN). The biocompatibility and the pharmaceutical behaviors were evaluated in Sprague-Dawley rats. The paracrine effects of adiponectin on bone fracture healing were investigated with a rat tibia fracture model via intrabone injection. Significantly accelerated bone healing was observed in the medulla injection group, indicating the paracrine effects of adiponectin could be potentially utilized for clinical treatments. The underlying mechanism was primarily assessed, and the expression of osteogenic markers, including bone morphogenic protein 2, alkaline phosphatase, and osteocalcin, along with adiponectin receptor 1 (AdipoR1), was markedly increased at the fracture site. The increased bone healing of ADPN treatment may result from both enhanced osteogenic proliferation as well as differentiation. Cell experiments confirmed that the expression of osteogenesis markers increased significantly in ADPN treatment groups, while it decreased when the expression of AdipoR1 was knocked down by siRNA. Our study provided a feasible and efficacious way for bone fracture treatment with local administration of ADPN, which could be rapidly translated into the clinics.

Photodynamic therapy for synovial hyperplasia in patients with refractory rheumatoid arthritis: a study protocol for a randomized, double-blind, blank-controlled prospective trial.

BACKGROUND: Persistent synovial hyperplasia with inflammation in rheumatoid arthritis is one of the main pathogeneses of refractory rheumatoid arthritis (RRA). Photodynamic therapy (PDT) causes less trauma than steroid injections or arthroscopic synovectomy while providing stronger targeting and more durable curative effects. The aim of this trial was to evaluate the short-, medium-, and long-term clinical efficacy of PDT when applied as a treatment for RRA synovial hyperplasia and synovitis. METHODS AND ANALYSIS: This protocol is for a single-center, randomized, double-blind, blank-controlled prospective trial. A sample of 126 RRA patients will be randomly divided into 3 groups: the control group, the "PDT once" group, and the "PDT twice" group, with 42 participants per group. The trial will be conducted by the Rheumatology and Immunology Department of the Integrated Hospital of Traditional Chinese Medicine, Southern Medical University. The Ultrasound Compound Score of Synovitis (UCSS) has been selected as the primary outcome measure. The secondary outcome measures include knee joint clinical assessments, ratio of relapse, duration of remission, Disease Activity Score in 28 joints (DAS28), inflammation indexes, serum concentrations of specific antibodies, and changes in articular structures as detected by X-ray scans in the 48th week. The improvement ratios of the UCSS at the 8th, 24th, and 48th weeks (compared with baseline) reflect short-, medium-, and long-term time frames, respectively. ETHICS AND DISSEMINATION: The protocol was approved by the Medical Ethics Committee of the Integrated Hospital of Traditional Chinese Medicine, Southern Medical University, China (Approval No. granted by the ethics committee: NFZXYEC-2017-005) and then entered in the Chinese Clinical Trials Registry under registration number ChiCTR1800014918 (approval date: February 21, 2018). All procedures are in accordance with Chinese laws and regulations and with the Declaration of Helsinki by the World Medical Association (WMA). Any modifications of this protocol during execution will need additional approval from the Ethics Committee of our hospital. TRIAL REGISTRATION NUMBER: ChiCTR1800014918 .