Sensitization of hepatocellular carcinoma cells to HDACi is regulated through hsa-miR-342-5p/CFL1.

BACKGROUND: Increased prevalence of hepatocellular carcinoma (HCC) remains a global health challenge. HCC chemoresistance is a clinical obstacle for its management. Aberrant miRNA expression is a hallmark for both cancer progression and drug resistance. However, it is unclear which miRNAs are involved in HCC chemoresistance. METHODS: MicroRNA microarray analysis revealed a differential expression profile of microRNAs between the hepatocellular carcinoma HA22T cell line and the HDACi-R cell line, which was validated by quantitative real-time PCR (qRT-PCR). To determine the biological function of miR-342-5p and the mechanism of the microRNA-342-5p/CFL1 axis in hepatocellular carcinoma HDACi resistance, loss- and gain-of-function studies were conducted in vitro. RESULTS: Here we demonstrated the molecular mechanism of histone deacetylase inhibitor (HDACi) resistance in HCC. Differential miRNA expression analysis showed significant down regulation of miR-342-5p in HDACi-R cells than in parental HA22T cells. Mimics of miR-342-5p enhanced apoptosis through upregulation of Bax, cyto-C, cleaved-caspase-3 expressions with concomitant decline in anti-apoptotic protein (Bcl-2) in HDACi-R cells. Although HDACi did not increase cell viability of HDACi-R, overexpression of miR-342-5p decreased cofilin-1 expression, upregulated reactive oxygen species (ROS) mediated apoptosis, and sensitized HDACi-R to HDACi in a dose-dependent manner. CONCLUSION: Our findings demonstrated the critical role of miR-342-5p in HDACi resistance of HCC and that this mechanism might be attributed to miR-342-5p/cofilin-1 regulation.

Multicenter evaluation of the safety and efficacy of selective internal radiation therapy with yttrium-90 resin microspheres in Taiwan: data from the RESIN registry.

BACKGROUND AND AIM: The REgistry of Selective Internal radiation therapy in AsiaNs (RESIN) was a multicenter, single-arm, prospective, observational study of 90Y resin microspheres in patients with hepatocellular carcinoma (HCC) or metastatic colorectal cancer (mCRC) from Taiwan. RESIN is the first real-life clinical study of this therapy in an Asian cohort. Study objectives were to evaluate the safety and efficacy of 90Y resin microspheres. METHODS: Adults with HCC or mCRC scheduled to receive SIRT with 90Y resin microspheres were included. Primary endpoints were best overall response rate (ORR), adverse events, and changes from baseline in liver function. Secondary efficacy endpoints included overall survival (OS). RESULTS: Of 107 enrolled patients, 83 had HCC, and 24 had mCRC. ORR was 55.41% (HCC) and 33.33% (mCRC). Of 58 HCC patients with 6-month post-SIRT data, 13.79% (n = 8) had resection, transplantation, transarterial chemoembolization, or radiofrequency ablation as the result of down-staging or down-sizing of their lesions. One hundred and ten treatment emergent adverse events (TEAEs) were reported in 51 patients, and five serious adverse events (SAEs) were reported in five patients. The most frequent TEAEs were abdominal pain, nausea and decreased appetite (HCC), and abdominal pain, decreased appetite, fatigue, and vomiting (mCRC). Two deaths due to SAEs (probably related to SIRT) were reported, both in patients with extensive HCC, active hepatitis infection, and other comorbidities. Median OS was 24.07 (HCC) and 12.66 (mCRC) months. CONCLUSIONS: Safety and efficacy outcomes with the routine use of SIRT with 90Y resin microspheres in Taiwan are consistent with published data.

Development of a modified 3D region proposal network for lung nodule detection in computed tomography scans: a secondary analysis of lung nodule datasets.

BACKGROUND: Low-dose computed tomography (LDCT) has been shown useful in early lung cancer detection. This study aimed to develop a novel deep learning model for detecting pulmonary nodules on chest LDCT images. METHODS: In this secondary analysis, three lung nodule datasets, including Lung Nodule Analysis 2016 (LUNA16), Lung Nodule Received Operation (LNOP), and Lung Nodule in Health Examination (LNHE), were used to train and test deep learning models. The 3D region proposal network (RPN) was modified via a series of pruning experiments for better predictive performance. The performance of each modified deep leaning model was evaluated based on sensitivity and competition performance metric (CPM). Furthermore, the performance of the modified 3D RPN trained on three datasets was evaluated by 10-fold cross validation. Temporal validation was conducted to assess the reliability of the modified 3D RPN for detecting lung nodules. RESULTS: The results of pruning experiments indicated that the modified 3D RPN composed of the Cross Stage Partial Network (CSPNet) approach to Residual Network (ResNet) Xt (CSP-ResNeXt) module, feature pyramid network (FPN), nearest anchor method, and post-processing masking, had the optimal predictive performance with a CPM of 92.2%. The modified 3D RPN trained on the LUNA16 dataset had the highest CPM (90.1%), followed by the LNOP dataset (CPM: 74.1%) and the LNHE dataset (CPM: 70.2%). When the modified 3D RPN trained and tested on the same datasets, the sensitivities were 94.6%, 84.8%, and 79.7% for LUNA16, LNOP, and LNHE, respectively. The temporal validation analysis revealed that the modified 3D RPN tested on LNOP test set achieved a CPM of 71.6% and a sensitivity of 85.7%, and the modified 3D RPN tested on LNHE test set had a CPM of 71.7% and a sensitivity of 83.5%. CONCLUSION: A modified 3D RPN for detecting lung nodules on LDCT scans was designed and validated, which may serve as a computer-aided diagnosis system to facilitate lung nodule detection and lung cancer diagnosis.

A modified 3D RPN for detecting lung nodules on CT images that exhibited greater sensitivity and CPM than did several previously reported CAD detection models was established.

Therapeutic Decision Making in Prevascular Mediastinal Tumors Using CT Radiomics and Clinical Features: Upfront Surgery or Pretreatment Needle Biopsy?

The study aimed to develop machine learning (ML) classification models for differentiating patients who needed direct surgery from patients who needed core needle biopsy among patients with prevascular mediastinal tumor (PMT). Patients with PMT who received a contrast-enhanced computed tomography (CECT) scan and initial management for PMT between January 2010 and December 2020 were included in this retrospective study. Fourteen ML algorithms were used to construct candidate classification models via the voting ensemble approach, based on preoperative clinical data and radiomic features extracted from the CECT. The classification accuracy of clinical diagnosis was 86.1%. The first ensemble learning model was built by randomly choosing seven ML models from a set of fourteen ML models and had a classification accuracy of 88.0% (95% CI = 85.8 to 90.3%). The second ensemble learning model was the combination of five ML models, including NeuralNetFastAI, NeuralNetTorch, RandomForest with Entropy, RandomForest with Gini, and XGBoost, and had a classification accuracy of 90.4% (95% CI = 87.9 to 93.0%), which significantly outperformed clinical diagnosis (p < 0.05). Due to the superior performance, the voting ensemble learning clinical-radiomic classification model may be used as a clinical decision support system to facilitate the selection of the initial management of PMT.

Prediction of surgical outcomes in severe encapsulating peritoneal sclerosis using a computed tomography scoring system.

BACKGROUND/PURPOSE: Encapsulating peritoneal sclerosis (EPS) is a rare and potential lethal complication of peritoneal dialysis characterized by bowel obstruction. Surgical enterolysis is the only curative therapy. Currently, there are no tools for predicting postsurgical prognosis. This study aimed to identify a computed tomography (CT) scoring system that could predict mortality after surgery in patients with severe EPS. METHODS: This retrospective study enrolled patients with severe EPS who underwent surgical enterolysis in a tertiary referral medical center. The association of CT score with surgical outcomes including mortality, blood loss, and bowel perforation was analyzed. RESULTS: Thirty-four patients who underwent 37 procedures were recruited and divided into a survivor and non-survivor group. The survivor group had higher body mass indices (BMIs, 18.1 vs. 16.7 kg/m2, p = 0.035) and lower CT scores (11 vs. 17, p < 0.001) than the non-survivor group. The receiver operating characteristic curve revealed that a CT score of ≥15 could be considered a cutoff point to predict surgical mortality, with an area under the curve of 0.93, sensitivity of 88.9%, and specificity of 82.1%. Compared with the group with CT scores of <15, the group with CT scores of ≥15 had a lower BMI (19.7 vs. 16.2 kg/m2, p = 0.004), higher mortality (4.2% vs. 61.5%, p < 0.001), greater blood loss (50 vs. 400 mL, p = 0.007), and higher incidence of bowel perforation (12.5% vs. 61.5%, p = 0.006). CONCLUSION: The CT scoring system could be useful in predicting surgical risk in patients with severe EPS receiving enterolysis.

Combined model integrating deep learning, radiomics, and clinical data to classify lung nodules at chest CT.

OBJECTIVES: The study aimed to develop a combined model that integrates deep learning (DL), radiomics, and clinical data to classify lung nodules into benign or malignant categories, and to further classify lung nodules into different pathological subtypes and Lung Imaging Reporting and Data System (Lung-RADS) scores. MATERIALS AND METHODS: The proposed model was trained, validated, and tested using three datasets: one public dataset, the Lung Nodule Analysis 2016 (LUNA16) Grand challenge dataset (n = 1004), and two private datasets, the Lung Nodule Received Operation (LNOP) dataset (n = 1027) and the Lung Nodule in Health Examination (LNHE) dataset (n = 1525). The proposed model used a stacked ensemble model by employing a machine learning (ML) approach with an AutoGluon-Tabular classifier. The input variables were modified 3D convolutional neural network (CNN) features, radiomics features, and clinical features. Three classification tasks were performed: Task 1: Classification of lung nodules into benign or malignant in the LUNA16 dataset; Task 2: Classification of lung nodules into different pathological subtypes; and Task 3: Classification of Lung-RADS score. Classification performance was determined based on accuracy, recall, precision, and F1-score. Ten-fold cross-validation was applied to each task. RESULTS: The proposed model achieved high accuracy in classifying lung nodules into benign or malignant categories in LUNA 16 with an accuracy of 92.8%, as well as in classifying lung nodules into different pathological subtypes with an F1-score of 75.5% and Lung-RADS scores with an F1-score of 80.4%. CONCLUSION: Our proposed model provides an accurate classification of lung nodules based on the benign/malignant, different pathological subtypes, and Lung-RADS system.

Multidisciplinary Taiwan consensus for the use of conventional TACE in hepatocellular carcinoma treatment.

Developed in early 1980s, transarterial chemoembolization (TACE) with Lipiodol was adopted globally after large-scale randomized control trials and meta-analyses proving its effectiveness were completed. Also known as "conventional TACE" (cTACE), TACE is currently the first-line treatment for patients with unresectable intermediate stage hepatocellular carcinoma (HCC) and delivers both ischemic and cytotoxic effects to targeted tumors. Although new technology and clinical studies have contributed to a more comprehensive understanding of when and how to apply this widely-adopted therapeutic modality, some of these new findings and techniques have yet to be incorporated into a guideline appropriate for Taiwan. In addition, differences in the underlying liver pathologies and treatment practices for transcatheter embolization between Taiwan and other Asian or Western populations have not been adequately addressed, with significant variations in the cTACE protocols adopted in different parts of the world. These mainly revolve around the amount and type of chemotherapeutic agents used, the type of embolic materials, reliance on Lipiodol, and the degree of selectiveness in catheter positioning. Subsequently, interpreting and comparing results obtained from different centers in a systematic fashion remain difficult, even for experienced practitioners. To address these concerns, we convened a panel of experts specializing in different aspects of HCC treatment to devise modernized recommendations that reflect recent clinical experiences, as well as cTACE protocols which are tailored for use in Taiwan. The conclusions of this expert panel are described herein.

Corrigendum: Clinical radiomics-based machine learning versus three-dimension convolutional neural network analysis for differentiation of thymic epithelial tumors from other prevascular mediastinal tumors on chest computed tomography scan.

[This corrects the article DOI: 10.3389/fonc.2023.1105100.].

Clinical radiomics-based machine learning versus three-dimension convolutional neural network analysis for differentiation of thymic epithelial tumors from other prevascular mediastinal tumors on chest computed tomography scan.

Purpose: To compare the diagnostic performance of radiomic analysis with machine learning (ML) model with a convolutional neural network (CNN) in differentiating thymic epithelial tumors (TETs) from other prevascular mediastinal tumors (PMTs). Methods: A retrospective study was performed in patients with PMTs and undergoing surgical resection or biopsy in National Cheng Kung University Hospital, Tainan, Taiwan, E-Da Hospital, Kaohsiung, Taiwan, and Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan between January 2010 and December 2019. Clinical data including age, sex, myasthenia gravis (MG) symptoms and pathologic diagnosis were collected. The datasets were divided into UECT (unenhanced computed tomography) and CECT (enhanced computed tomography) for analysis and modelling. Radiomics model and 3D CNN model were used to differentiate TETs from non-TET PMTs (including cyst, malignant germ cell tumor, lymphoma and teratoma). The macro F1-score and receiver operating characteristic (ROC) analysis were performed to evaluate the prediction models. Result: In the UECT dataset, there were 297 patients with TETs and 79 patients with other PMTs. The performance of radiomic analysis with machine learning model using LightGBM with Extra Tree (macro F1-Score = 83.95%, ROC-AUC = 0.9117) had better performance than the 3D CNN model (macro F1-score = 75.54%, ROC-AUC = 0.9015). In the CECT dataset, there were 296 patients with TETs and 77 patients with other PMTs. The performance of radiomic analysis with machine learning model using LightGBM with Extra Tree (macro F1-Score = 85.65%, ROC-AUC = 0.9464) had better performance than the 3D CNN model (macro F1-score = 81.01%, ROC-AUC = 0.9275). Conclusion: Our study revealed that the individualized prediction model integrating clinical information and radiomic features using machine learning demonstrated better predictive performance in the differentiation of TETs from other PMTs at chest CT scan than 3D CNN model.

Short-Term Effects of Genicular Artery Embolization on Symptoms and Bone Marrow Abnormalities in Patients with Refractory Knee Osteoarthritis.

PURPOSE: To evaluate the short-term outcomes of genicular artery embolization (GAE) for knee osteoarthritis (OA) with and without bone marrow lesion (BML) and/or subchondral insufficiency fracture of the knee (SIFK). MATERIALS AND METHODS: This single-institution prospective observational pilot study analyzed 24 knees in 22 patients with mild to moderate knee OA, including 8 knees without BML, 13 knees with BML, and 3 knees with both BML and SIFK. The area and volume of BMLs on magnetic resonance images were measured before and after GAE. Baseline and postoperative pain and physical function were assessed using the visual analog scale (VAS) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). RESULTS: GAE significantly reduced the BML area and volume 3 months after embolization in the knees with BML (both P < .0005). GAE significantly decreased the VAS scores at 3 and 6 months after embolization in patients without BML (both P = .04) and those with BML (both P = .01). GAE also lowered the WOMAC scores 3 months after embolization in patients without and with BML (P = .02 and P = .0002, respectively). However, GAE did not significantly alter the BML area and volume (both P = .25), VAS scores (P = 1.00), and WOMAC scores (P = .08) in patients with BML and SIFK at 3 months after GAE. CONCLUSIONS: This observational pilot study suggested that GAE effectively reduces the BML area and volume and improves pain and physical function in patients with knee OA accompanied by BML but is inefficacious in those with both BML and SIFK.

Improving puncture accuracy in percutaneous CT-guided needle insertion with wireless inertial measurement unit: a phantom study.

OBJECTIVES: A novel method applying inertial measurement units (IMUs) was developed to assist CT-guided puncture, which enables real-time displays of planned and actual needle trajectories. The method was compared with freehand and laser protractor-assisted methods. METHODS: The phantom study was performed by three operators with 8, 2, and 0 years of experience in CT-guided procedure conducted five consecutive needle placements for three target groups using three methods (freehand, laser protractor-assisted, or IMU-assisted method). The endpoints included mediolateral angle error and caudocranial angle error of the first pass, the procedure time, the total number of needle passes, and the radiation dose. RESULTS: There was a significant difference in the number of needle passes (IMU 1.2 ± 0.42, laser protractor 2.9 ± 1.6, freehand 3.6 ± 2.0 time, p < 0.001), the procedure time (IMU 3.0 ± 1.2, laser protractor 6.4 ± 2.9, freehand 6.2 ± 3.1 min, p < 0.001), the mediolateral angle error of the first pass (IMU 1.4 ± 1.2, laser protractor 1.6 ± 1.3, freehand 3.7 ± 2.5 degree, p < 0.001), the caudocranial angle error of the first pass (IMU 1.2 ± 1.2, laser protractor 5.3 ± 4.7, freehand 3.9 ± 3.1 degree, p < 0.001), and the radiation dose (IMU 250.5 ± 74.1, laser protractor 484.6 ± 260.2, freehand 561.4 ± 339.8 mGy-cm, p < 0.001) among three CT-guided needle insertion methods. CONCLUSION: The wireless IMU improves the angle accuracy and speed of CT-guided needle punctures as compared with laser protractor guidance and freehand techniques. KEY POINTS: • The IMU-assisted method showed a significant decrease in the number of needle passes (IMU 1.2 ± 0.42, laser protractor 2.9 ± 1.6, freehand 3.6 ± 2.0 time, p < 0.001). • The IMU-assisted method showed a significant decrease in the procedure time (IMU 3.0 ± 1.2, laser protractor 6.4 ± 2.9, freehand 6.2 ± 3.1 min, p < 0.001). • The IMU-assisted method showed a significant decrease in the mediolateral angle error of the first pass and the caudocranial angle error of the first pass.

Clinical outcomes of percutaneous transhepatic biliary drainage at different Couinaud's hepatic entry segments for treating obstructive jaundice.

Introduction: Percutaneous transhepatic biliary drainage (PTBD) is a common procedure for biliary obstructive jaundice caused by biliary tract obstruction. In clinical practice, PTBD can be carried out at right- or left-sided approach. However, different hepatic entry site may affect success rates and complications. Couinaud classification of liver anatomy further divides the liver into functionally independent segments (segment 2/3, segment 5/6, and segment 7/8). Therefore, this study aimed to elucidate whether different Couinaud hepatic segments as PTBD entry site are associated with high PTBD success and low complications. Methods: A total of 617 patients who underwent PTBD were retrospectively reviewed. Univariate and multivariate logistic regression analyses were performed to identify entry segments associated with PTBD success, bilirubin reduction, and complications. Results: With higher hepatic segment of PTBD entry site (segment 2/3, 5/6, and 7/8), the trend of PTBD success rate (82.0%, 71.7% and 60.7%; P<0.001) and bilirubin reduction (93.2%, 89.5%, and 82.0%; P=0.012) decreased. Furthermore, PTBD entry at segment 7/8 (42.6%) had highest complication rate than segment 5/6 (6.4%) and 2/3 (9.4%). Univariate and multivariate logistic regression analyses showed that PTBD entry segment was an independent factor associated with PTBD success, bilirubin reduction, and complications. Compared to segment 7/8, segment 2/3 and 5/6 had higher odds of PTBD success (aOR=2.699 and aOR=1.454, respectively) and bilirubin reduction (aOR=3.472 and aOR=2.361, respectively) and associated with lower risk of complications (aOR=0.143 and aOR=0.098, respectively). No independent risk factor for PTBD success and bilirubin reduction were identified in intrahepatic tumors. Moreover, for extrahepatic tumors, PTBD entry at segment 2/3 and segment 5/6 was more likely achieve PTBD success (aOR=3.037 and aOR=1.929, respectively), bilirubin reduction (aOR=3.069 and aOR=3.515) and low complications (aOR=0.102 and aOR=0.126, respectively). Discussion: Good clinical outcomes were observed for PTBD entry at segments 5/6 and 2/3. In contrast, segment 7/8 had the lowest success rate, smallest bilirubin reduction, and the highest complication rate. For patients with obstructive jaundice, PTBD entry in hepatic segments 2/3 and 5/6 is recommended to achieve high success rates and low complications.

Safety and Efficacy of Drug-Eluting Beads Trans-Arterial Chemoembolization for Hepatocellular Carcinoma in Taiwan (SERENADE-T).

Purpose: The aim of this retrospective study was to evaluate the safety and efficacy of patients with hepatocellular carcinoma treated with drug-eluting bead with doxorubicin transarterial chemoembolization (DEBDOX-TACE) in Taiwan. Patients and Methods: We retrospectively investigated 630 hepatocellular carcinoma patients who underwent DEBDOX-TACE in multiple institutions from 2011 to 2016 in Taiwan. Tumor response was assessed per modified response evaluation criteria in solid tumors, overall survival, and safety. Results: This study included 630 patients who underwent DEBDOX-TACE, participants' mean age was 66 years, 68.1% males and 15.6% females. The mean doxorubicin dose administered via DEBDOX-TACE was 56 mg. Complete and partial response rates were 14.6% and 49.2%, respectively, with a disease control rate of 84.6%. The median overall survival was 29.2 months. The most common post-embolization symptom was abdominal pain (22.4%). No hepatic encephalopathy and no procedure-related death were found. Conclusion: Real-world data from Taiwan demonstrated that DEBDOX-TACE for hepatocellular carcinoma can achieve high tumor response rate with low adverse events.

Trial Designs for Integrating Novel Therapeutics into the Management of Intermediate-Stage Hepatocellular Carcinoma.

Intermediate-stage hepatocellular carcinoma (HCC) consists of heterogeneous groups of patients in terms of tumor burden and organ function reserves. Although liver-directed therapy (LDT), including trans-catheter arterial chemoembolization, radiofrequency ablation or even surgical resection, is the recommended frontline treatment modality, intrahepatic and distant failures are common. The recent advances in systemic treatment, notably the introduction of immune checkpoint inhibitor (ICI)-based therapy, have significantly improved the objective tumor response rate, quality of response and overall survival in patients with recurrent and advanced HCC. Whether the combination of systemic treatment and LDT can further improve the outcome of patients with intermediate-stage HCC is currently being extensively evaluated. In this article, the recent clinical trials incorporating different ICI-based combinations with different LDT for intermediate-stage HCC were reviewed focusing on trial design issues, including patient selection, endpoint definition, and biomarker development. The strength and caveats of different combination strategies and novel biomarker development were discussed.

Calreticulin nuclear translocalization alleviates CaM/CaMKII/CREB signaling pathway to enhance chemosensitivity in HDAC inhibitor-resistant hepatocellular carcinoma cells.

Calreticulin (CRT) is located in the endoplasmic reticulum (ER), it helps proteins fold correctly inside the ER, and acts as a modulator of Ca2+ homeostasis. Aberrant expression of CRT is implicated in several cancer types, qualifying CRT as a potential therapeutic target. However, it remains unclear how CRT affects specific oncogenic pathways. In this study, we used histone deacetylase inhibitors (HDACis) to establish drug-resistant liver cancer cells and further analyzed the molecular mechanism of development of drug resistance in those cells. The 2D gel electrophoresis and RT-PCR data showed that CRT was downregulated in HDACis-resistant cells by comparing with HA22T parental cells. We previously elucidated the development of drug-resistance in HCC cells via activation of PP1-eIF2α pathway, but not via ER stress pathway. Here, we show that thapsigargin induced ER stress through mechanism other than ER stress downstream protein GRP78-PERK to regulate CRT expression in HDACis-R cells. Moreover, the expression level of CRT was not the main cause of apoptosis in HDACis-resistant cells. Mechanistic studies identified the apoptosis factors in the nucleus-the HDACis-mediated overexpression of CRT, CRT translocation to the cell nucleus, and reduced CaM/CaMKII/CREB pathway-that led to chemosensitivity in HDACis-R HCC cells.

Improved survival with induction chemotherapy and conversion surgery in locally advanced unresectable pancreatic cancer: a single institution experience.

Both efficacy and tolerability are critical issues in choosing neoadjuvant chemotherapy in patients with unresectable locally advanced pancreatic cancer (LAPC). The optimal regimen and the impact of conversion surgery on patient survival remains insufficiently reported in Asain population. Therefore, we conducted a retrospective study aiming to evaluate the resection rate after different induction chemotherapy regimen and its impact toward survival. All patients with pancreatic cancer treated in our institute from 2013 to 2020, a total of 730 patients, were reviewed and 131 patients with LAPC were identified. For cohort homogeneity, 14 patients receiving induction concurrent chemoradiotherapy initially were excluded and 117 patients receiving induction chemotherapy were included in the study. Most patients (90 of 117, 77%) received triplet induction chemotherapy, including the combination of S1, leucovorin, oxaliplatin and gemcitabine (SLOG) in 48, modified FOLFIRINOX in 21 and the combination of gemcitabine, oxaliplatin, fluorouracil and leucovorin (GOFL) in 21. The tumor response rate (19%-33%), the surgical exploration rate (38%-52%) and the mOS (15.4-23.0 months) were not significantly different among the three triplets. Both GOFL and SLOG regimen had comparable efficacy and less neutropenia as compared to mFOLFIRINOX. Conversion surgery was performed in 34 of 117 (29%) patients after induction chemotherapy. The median overall survival (mOS) in patients with and without conversion surgery were 29.1 and 14.1 months, respectively (P<0.0001). Radiological response alone was not a reliable indicator of successful conversion surgery. Patients who underwent conversion surgery had significantly better survival and thus highlighted the importance of surgical exploration in all patients who did not have progressive disease after induction chemotherapy.

Outcomes of Mechanical Thrombectomy for Acute Ischemic Stroke When Multiple Passes Are Required and Associated Risk Factors.

INTRODUCTION: This study aimed to evaluate the outcomes of mechanical thrombectomy for acute ischemic stroke when multiple passes are required and to identify the associated risk factors. METHODS: Consecutive patients with acute ischemic stroke treated with mechanical thrombectomy at the Neurology Department of Ninth People's Hospital and the Neurosurgery Department of Xinhua Hospital of Shanghai Jiao Tong University School of Medicine from 2013 to 2018 were included. Patients were divided into 2 groups: those who received ≤2 passes and those who received >2 passes. Outcomes of the 2 groups were compared. Multivariate linear regression was used to determine factors associated with the need for >2 passes. All patient data were reviewed retrospectively. RESULTS: A total of 122 patients were included, of whom 83 patients required ≤2 passes and 39 patients required >2 passes. After adjusting for sex, atrial fibrillation history, smoking history, and involvement of middle cerebral artery and internal cerebral artery, the National Institutes of Health Stroke Scale (NIHSS) score was associated with a 1.08-times greater risk of >2 passes (95% confidence interval [CI]: 1.01-1.17), and internal carotid artery with a 5.13-times greater risk of >2 passes (95% CI: 1.02-25.69). Having more than 2 passes was associated with significantly higher 7-day (25.6% vs. 6%), 90-day mortality rates (34.2% vs. 16%) and a significantly lower recanalization rate (66.7% vs. 89.2%). CONCLUSION: Needing more than 2 passes during mechanical thrombectomy is associated with poorer outcomes. Higher preprocedural NIHSS scores and internal carotid artery thrombi are associated with more than 2 passes.

An MRI-Based Clinical-Perfusion Model Predicts Pathological Subtypes of Prevascular Mediastinal Tumors.

This study aimed to build machine learning prediction models for predicting pathological subtypes of prevascular mediastinal tumors (PMTs). The candidate predictors were clinical variables and dynamic contrast-enhanced MRI (DCE-MRI)-derived perfusion parameters. The clinical data and preoperative DCE-MRI images of 62 PMT patients, including 17 patients with lymphoma, 31 with thymoma, and 14 with thymic carcinoma, were retrospectively analyzed. Six perfusion parameters were calculated as candidate predictors. Univariate receiver-operating-characteristic curve analysis was performed to evaluate the performance of the prediction models. A predictive model was built based on multi-class classification, which detected lymphoma, thymoma, and thymic carcinoma with sensitivity of 52.9%, 74.2%, and 92.8%, respectively. In addition, two predictive models were built based on binary classification for distinguishing Hodgkin from non-Hodgkin lymphoma and for distinguishing invasive from noninvasive thymoma, with sensitivity of 75% and 71.4%, respectively. In addition to two perfusion parameters (efflux rate constant from tissue extravascular extracellular space into the blood plasma, and extravascular extracellular space volume per unit volume of tissue), age and tumor volume were also essential parameters for predicting PMT subtypes. In conclusion, our machine learning-based predictive model, constructed with clinical data and perfusion parameters, may represent a useful tool for differential diagnosis of PMT subtypes.

Computed Tomography-Guided Transthoracic Needle Biopsy: Predictors for Diagnostic Failure and Tissue Adequacy for Molecular Testing.

Background: Adequate and representative tissue from lung tumor is important in the era of precision medicine. The aim of this study is to identify detailed procedure-related variables and factors influencing diagnostic success and tissue adequacy for molecular testing in CT-guided TTNB. Methods: Consecutive patients undergoing CT-guided TTNB were retrospectively enrolled between January 2013 and May 2020. Multivariate analysis was performed for predictors for diagnostic accuracy and tissue adequacy for molecular testing. Logistic regression was used to identify risk factors for procedure-related complications. Results: A total of 2,556 patients undergoing CT-guided TTNB were enrolled and overall success rate was 91.5% (2,338/2,556). For lung nodules ≤3 cm, predictors for diagnostic success included coaxial needle use [OR = 0.34 (0.16-0.71), p = 0.004], CT scan slice thickness of 2.5 mm [OR = 0.42 (0.15-0.82), p = 0.011] and additional prefire imaging [OR = 0.31 (0.14-0.68), p = 0.004]. For lung tumor >3 cm, ground glass opacity part more than 50% [OR = 7.53 (2.81-20.23), p < 0.001] or presence of obstructive pneumonitis [OR = 2.31 (1.53-3.48), p < 0.001] had higher risk of diagnostic failure. For tissue adequacy, tissue submitted in two cassettes (98.9 vs. 94.9%, p = 0.027) was a positive predictor; while male (5.7 vs. 2.5%, p = 0.032), younger age (56.61 ± 11.64 vs. 65.82 ± 11.98, p < 0.001), and screening for clinical trial (18.5 vs. 0.7%, p < 0.001) were negative predictors. Conclusions: Using a coaxial needle, with thin CT slice thickness (2.5 mm), and obtaining additional prefire imaging improved diagnostic success, while obtaining more than two tissue cores and submitting in two cassettes improved tissue adequacy for molecular testing.

The short-term safety and efficacy of TANDEM microspheres of various sizes and doxorubicin loading concentrations for hepatocellular carcinoma treatment.

Drug-eluting bead transarterial chemoembolization (DEB-TACE) is the most common treatment for unresectable hepatocellular carcinoma (HCC). However, the effect of drug loading concentration and microsphere size on treatment outcomes remains unclear. This retrospective study compares the outcomes of 87 HCC patients who underwent DEB-TACE with half-loaded or full-loaded doxorubicin (maximum capacity 50 mg/mL) in 75-µm or 100-µm microspheres. Treatment with 100-µm microspheres resulted in significantly lower rates of procedure-related complications (6.6% vs. 26.9%; P < 0.05), post-embolization syndrome (32.8% vs. 61.5%, P < 0.05), SIR complications (32.8% vs. 61.5%; P < 0.01) and adverse events involving abdominal pain (19.7% vs. 42.3%; P < 0.05). Half-load doxorubicin microspheres resulted in greater treatment response (OR, 4.00; 95% CI 1.06-15.13; P, 0.041) and shorter hospital stays (OR, - 1.72; 95% CI - 2.77-0.68; P, 0.001) than did microspheres loaded to full capacity. Stratified analysis further showed that patients treated with 100-µm half-load doxorubicin microspheres had a higher CR (63.6% vs 18.0%) and ORR (90.9 vs 54.0%) and a shorter hospital stay (1.6 ± 1.3 vs 4.2 ± 2.3 days) than did those treated with full-load microspheres (P < 0.05). Thus, the drug-loading concentration of microspheres in DEB-TACE should be carefully considered.