Jialiang Ren

General Electric | GE

The aim of this study was to use multimodal imaging (contrast-enhanced T1-weighted (T1C), T2-weighted (T2), and diffusion-weighted imaging (DWI)) to develop a radiomics model for preoperatively predicting venous sinus invasion in meningiomas. This prediction would assist in selecting the appropriate surgical approach and forecasting the prognosis o...

Objective To develop and validate a multiparametric MRI-based radiomics model for prediction of microsatellite instability (MSI) status in patients with endometrial cancer (EC). Methods A total of 225 patients from Center I including 158 in the training cohort and 67 in the internal testing cohort, and 132 patients from Center II were included as...

Objective To develop and validate an MR-based radiomics nomogram combining different imaging sequences (ADC mapping and T 2 weighted imaging (T 2 WI)), different tumor regions (combined intra- and peritumoral regions), and different parameters (clinical features, tumor morphological features, and radiomics features) while considering different MR f...

Background: In this study, we used computed tomography (CT)-based radiomics signatures to predict the mutation status of KRAS in patients with colorectal cancer (CRC) and to identify the phase of radiomics signature with the most robust and high performance from triphasic enhanced CT. Methods: This study involved 447 patients who underwent KRAS...

Abstract The purpose of this study was to differentiate the retroperitoneal paragangliomas and schwannomas using computed tomography (CT) radiomics. This study included 112 patients from two centers who pathologically confirmed retroperitoneal pheochromocytomas and schwannomas and underwent preoperative CT examinations. Radiomics features of the en...

Objectives To predict preoperative acute ischemic stroke (AIS) in acute type A aortic dissection (ATAAD).Methods In this multi-center retrospective study, 508 consecutive patients diagnosed as ATAAD between April 2020 and March 2021 were considered for inclusion. The patients were divided into a development cohort and two validation cohorts based o...

Purpose: The purpose of this study was to identify possible association between noncontrast computed tomography (NCCT)-based radiomics features of perihematomal edema (PHE) and poor functional outcome at 90 days after intracerebral hemorrhage (ICH) and to develop a NCCT-based radiomics-clinical nomogram to predict 90-day functional outcomes in pat...

[This corrects the article DOI: 10.3389/fonc.2022.974257.].

Background: The aim of this study was to compare the efficacy and safety of surgical resection (RES) and radiofrequency ablation (RFA) in hepatocellular carcinoma (HCC) patients with cirrhosis and to evaluate short- and long-term clinical outcomes. Methods: The EMBASE, Cochrane Central Register of Control Trials and Medline databases were search...

Background To explore the value of dual-energy spectral CT in distinguishing solitary pulmonary tuberculosis (SP-TB) from solitary lung adenocarcinoma (S-LUAD). Methods A total of 246 patients confirmed SP-TB (n = 86) or S-LUAD (n = 160) were retrospectively included. Spectral CT parameters include CT40keV value, CT70keV value, iodine concentratio...

Objectives: To evaluate the potential of multi b-value DWI in predicting the prognosis of patients with locally advanced rectal cancer (LARC). Methods: From 2015 to 2019, a total of 161 patients with LARC were enrolled and randomly sampled into a training set (n = 113) and validation set (n = 48). Multi b-value DWI (b = 0~1500 s/mm2) scans were...

Background Accurate risk stratification of patients with intracerebral hemorrhage (ICH) could help refine adjuvant therapy selection and better understand the clinical course. We aimed to evaluate the value of radiomics features from hematomal and perihematomal edema areas for prognosis prediction and to develop a model combining clinical and radio...

Predicting brain invasion preoperatively should help to guide surgical decision-making and aid the prediction of meningioma grading and prognosis. However, only a few imaging features have been identified to aid prediction. This study aimed to develop and validate an MRI-based nomogram to predict brain invasion by meningioma. In this retrospective...

Objective To assess the predictive value of magnetic resonance imaging (MRI) radiomics for progression-free survival (PFS) in patients with prostate cancer (PCa). Methods 191 patients with prostate cancer confirmed by puncture biopsy or surgical pathology were included in this retrospective study, including 133 in the training group and 58 in the...

Background: Accurate pre-treatment prediction of neoadjuvant chemotherapy (NACT) resistance in patients with locally advanced gastric cancer (LAGC) is essential for timely surgeries and optimized treatments. We aim to evaluate the effectiveness of deep learning (DL) on computed tomography (CT) images in predicting NACT resistance in LAGC patients....

Background: Genotype status of glioma have important significance to clinical treatment and prognosis. At present, there are few studies on the prediction of multiple genotype status in glioma by method of multi-sequence radiomics. The purpose of the study is to compare the performance of clinical features (age, sex, WHO grade, MRI morphological f...

We aimed to develop and validate an objective and easy-to-use model for identifying patients with spontaneous intracerebral hemorrhage (ICH) who have a poor 90-day prognosis. This three-center retrospective study included a large cohort of 1,122 patients with ICH who presented within 6 h of symptom onset [training cohort, n = 835; internal validati...

Background This study aimed to noninvasively predict the mutation status of epidermal growth factor receptor (EGFR) molecular subtype in lung adenocarcinoma based on CT radiomics features. Methods In total, 728 patients with lung adenocarcinoma were included, and divided into three groups according to EGFR mutation subtypes. 1727 radiomics feature...

Background Accurate prediction of treatment response to neoadjuvant chemotherapy (NACT) in individual patients with locally advanced gastric cancer (LAGC) is essential for personalized medicine. We aimed to develop and validate a deep learning radiomics nomogram (DLRN) based on pretreatment contrast-enhanced computed tomography (CT) images and clin...

Background To investigate the ability of the CT-based radiomics models for pretreatment prediction of the response to neoadjuvant chemotherapy (NAC) in patients with locally advanced gastric cancer (LAGC). Methods This retrospective analysis included 279 consecutive LAGC patients from center I (training cohort, n=196; internal validation cohort, n...

Preoperative distinction between transitional meningioma and atypical meningioma would aid the selection of appropriate surgical techniques, as well as the prognosis prediction. Here, we aimed to differentiate between these two tumors using radiomic signatures based on preoperative, contrast-enhanced T1-weighted and T2-weighted magnetic resonance i...

Objective: To develop a multiparametric MRI-based radiomics nomogram for predicting lymphovascular invasion (LVI) status and clinical outcomes in patients with breast invasive ductal carcinoma (IDC). Methods: A total of 160 patients with pathologically confirmed breast IDC (training cohort: n = 112; validation cohort: n = 48) who underwent preop...

Objectives: Predicting brain invasion preoperatively should help to guide surgical decision-making and aid the prediction of meningioma grading and prognosis. However, only a few imaging features have been identified to aid prediction. This study aimed to develop and validate an MRI-based nomogram to predict brain invasion by meningioma. Methods: I...

Purpose: In this study, we used computed tomography (CT)-based radiomics signatures to predict the mutation status of KRAS in colorectal cancer (CRC) patients. Methods: This study involved 447 patients who underwent KRAS mutation testing and preoperative triphasic enhanced CT. They were categorised into training (n = 313) and validation cohorts (n...

Objective: To establish a pre-operative acute ischemic stroke risk (AIS) prediction model using the deep neural network in patients with acute type A aortic dissection (ATAAD). Methods: Between January 2015 and February 2019, 300 ATAAD patients diagnosed by aorta CTA were analyzed retrospectively. Patients were divided into two groups according to...

Objective: To develop nomograms that combine clinical characteristics, computed tomographic (CT) features and 18F-fluorodeoxyglucose PET (18F-FDG PET) metabolic parameters for individual prediction of epidermal growth factor receptor (EGFR) mutation status and exon 19 deletion mutation and exon 21 point mutation (21 L858R) subtypes in lung adenoca...

Objective To investigate the potential value of radiomics features based on preoperative multiparameter MRI in predicting disease-free survival (DFS) in patients with local advanced rectal cancer (LARC). Methods We identified 234 patients with LARC who underwent preoperative MRI, including T2-weighted, diffusion kurtosis imaging, and contrast enha...

Objectives To evaluate the predictive value of radiomics features based on multiparameter magnetic resonance imaging (MP-MRI) for peritoneal carcinomatosis (PC) in patients with ovarian cancer (OC). Methods A total of 86 patients with epithelial OC were included in this retrospective study. All patients underwent FS-T2WI, DWI, and DCE-MRI scans, f...

Objective This study aimed to develop a dual-energy spectral computed tomography (DESCT) nomogram that incorporated both clinical factors and DESCT parameters for individual preoperative prediction of lymph node metastasis (LNM) in patients with colorectal cancer (CRC). Material and Methods We retrospectively reviewed 167 pathologically confirmed...

Objective Three models were used to evaluate prostate cancer after androgen deprivation therapy (ADT) and to determine the value of detecting residual lesions after treatment. Methods We retrospectively analysed patients with prostate cancer who received ADT from January 2018 to June 2019. Patients were divided into ADT responder and ADT non-respo...

Background This study aimed to develop and validate a computed tomography (CT)-based radiomics model to predict microsatellite instability (MSI) status in colorectal cancer patients and to identify the radiomics signature with the most robust and high performance from one of the three phases of triphasic enhanced CT. Methods In total, 502 colorect...

Background: The usefulness of a dual-energy spectral computed tomography (DESCT)-based nomogram in discriminating between histological grades of colorectal adenocarcinoma (CRAC) is unclear. This study aimed to develop such a nomogram and assess its ability to preoperatively discriminate between histological grades in CRAC patients. Methods: Prim...

Objectives The aim of this study was to investigate the diagnostic abilities of both pericoronary adipose tissue (PCAT) CT attenuation and volume for the predication hemodynamic significance of coronary artery stenosis as evaluated by fractional flow reserve (FFR). Methods Patients with ≥ 30% in at least 1 major epicardial coronary artery were ret...

Purpose: We aimed to explore whether multiparametric magnetic resonance imaging (MRI)-based radiomics combined with selected blood inflammatory markers could effectively predict the grade and proliferation in glioma patients. Methods: This retrospective study included 152 patients histopathologically diagnosed with glioma. Stratified sampling wa...

Purpose This study was designed to evaluate the predictive performance of contrast-enhanced CT-based radiomic features for the personalized, differential diagnosis of esophagogastric junction (EGJ) adenocarcinoma at stages T3 and T4a. Methods Two hundred patients with T3 (n = 44) and T4a (n = 156) EGJ adenocarcinoma lesions were enrolled in this s...

Patients with epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma can benefit from targeted therapy. However, noninvasively determination of EGFR mutation status before targeted therapy remains a challenge. This study constructed a nomogram based on a combination of radiomics features with the clinical and radiological features...

Background: To develop and validate a fully automated deep learning-based segmentation algorithm to segment pulmonary lobe on low-dose computed tomography (LDCT) images. Methods: This study presents an automatic segmentation of pulmonary lobes using a fully convolutional neural network named dense V-network (DenseVNet) on lung cancer screening L...

Rationale and Objectives To compare the ability of radiomics models including the perinodular parenchyma and standard nodular radiomics model in lung cancer diagnosis of solid pulmonary nodules smaller than 2 cm. Materials and Methods In this retrospective study, the computed tomography (CT) scans of 206 patients with a lung nodule from a single i...

Cases of extrahepatic bile duct carcinoma are mostly adenocarcinomas and extrahepatic bile duct squamous cell carcinomas are rare. We report here a case of choledochal squamous cell carcinoma in a young woman who underwent surgery and chemotherapy. The woman presented with abdominal discomfort. A physical examination showed tenderness in the upper...

Background and purpose: We aimed to develop a radiomics model for the prediction of survival and chemotherapeutic benefits using pretreatment multiparameter MR images and clinicopathological features in patients with locally advanced rectal cancer (LARC). Materials and methods: 186 consecutive patients with LARC underwent feature extraction from...

Objective: To develop and validate a radiomics predictive model based on multiparameter MR imaging features and clinical features to predict lymph node metastasis (LNM) in patients with cervical cancer. Material and Methods: A total of 168 consecutive patients with cervical cancer from two centers were enrolled in our retrospective study. A total o...

Background: Distant metastasis is the major cause of treatment failure in locally advanced rectal cancer (LARC). Adjuvant chemotherapy (AC) is usually used for distant control. However, only certain subgroups of patients could benefit from AC. Our aim was to develop a radiomics model for the prediction of survival and chemotherapeutic benefits usin...

Aquaporins (AQP) are not only water channel protein, but also potential prognostic indicator and therapeutic target for rectal cancer. Some previous studies have demonstrated the AQP expression could be estimated by ADCaqp value derived from ultra-high b-value diffusion-weighted imaging (DWI). We aim to determine whether ADCaqp could be a new and s...

Objective To compare the performance of clinical features, conventional MR image features, ADC value, T2WI, DWI, DCE-MRI radiomics, and a combined multiple features model in predicting the type of epithelial ovarian cancer (EOC).Methods In this retrospective analysis, 61 EOC patients were confirmed by histology. Significant features (p < 0.05) by m...

Rationale and Objectives Signal intensity of the lumbar spine in magnetic resonance imaging (MRI) correlates to bone mineral density (BMD). This study aims to explore a lumbar spine magnetic resonance imaging based on the radiomics model for detecting osteoporosis. Materials and Methods A total of 109 patients, who underwent both dual-energy X-ray...

PurposeThe pathological risk degree of gastrointestinal stromal tumors (GISTs) has become an issue of great concern. Computed tomography (CT) is beneficial for showing adjacent tissues in detail and determining metastasis or recurrence of GISTs, but its function is still limited. Radiomics has recently shown a great potential in aiding clinical dec...

Objective: To develop a T2-weighted (T2W) image-based radiomics signature for the individual prediction of KRAS mutation status in patients with rectal cancer. Methods: Three hundred four consecutive patients from center I with pathologically diagnosed rectal adenocarcinoma (training dataset, n = 213; internal validation dataset, n = 91) were en...