Jingwei Wei

Chinese Academy of Sciences | CAS · Key laboratory of molecular imaging

Objective. In the realm of utilizing artificial intelligence (AI) for medical image analysis, the paradigm of "signal-image-knowledge" has remained unchanged. However, the process of "signal to image" inevitably introduces information distortion, ultimately leading to irrecoverable biases in the "image to knowledge" process. Our goal is to skip rec...

The segmentation of liver tumors using multi-phase computed tomography (CT) images has garnered considerable attention in medical signal processing. However, existing multi-phase liver tumor segmentation methods primarily concentrate on feature integration across various phases, neglecting a comprehensive exploration of synergistic relationships am...

Importance Digestive system neoplasms (DSNs) are the leading cause of cancer-related mortality with a 5-year survival rate of less than 20%. Subjective evaluation of medical images including endoscopic images, whole slide images, computed tomography images, and magnetic resonance images plays a vital role in the clinical practice of DSNs, but with...

The high postoperative recurrence rates in hepatocellular carcinoma (HCC) remain a major hurdle in its management. Appropriate staging and treatment selection may alleviate the extent of fatal recurrence. However, effective methods to preoperatively evaluate pathophysiologic and molecular characteristics of HCC are lacking. Imaging plays a central...

Background Histopathological grading is a significant risk factor for postsurgical recurrence in hepatocellular carcinoma (HCC). Preoperative knowledge of histopathological grading could provide instructive guidance for individualized treatment decision‐making in HCC management. Purpose This study aims to develop and validate a newly proposed deep...

Recently, image-based diagnostic technology has made encouraging and astonishing development. Modern medical care and imaging technology are increasingly inseparable. However, the current diagnosis pattern of Signal-to-Image-to-Knowledge inevitably leads to information distortion and noise introduction in the procedure of image reconstruction (Sign...

Background: Lymph node (LN) metastasis is significantly associated with worse prognosis for patients with intrahepatic cholangiocarcinoma (ICC). Improvement in preoperative assessment on LN metastasis helps in treatment decision-making. We aimed to investigate the role of radiomics-based method in predicting LN metastasis for patients with ICC. M...

Background & aims: Microvascular invasion (MVI) is an important risk factor in hepatocellular carcinoma (HCC), but its diagnosis mandates postoperative histopathologic analysis. We aimed to develop and externally validate a predictive scoring system for MVI. Methods: From July 2015 to November 2020, consecutive patients underwent surgery for HCC...

Hepatocellular carcinoma (HCC) remains the most common malignancy to threaten public health globally. With advances in artificial intelligence techniques, radiomics for HCC management provides a novel perspective to solve unmet needs in clinical settings, and reveals pixel-level radiological information for medical imaging big data, correlating the...

The hepatic venous pressure gradient (HVPG) is the gold standard for cirrhotic portal hypertension (PHT), but it is invasive and specialized. Alternative non-invasive techniques are needed to assess the hepatic venous pressure gradient (HVPG). Here, we develop an auto-machine-learning CT radiomics HVPG quantitative model (aHVPG), and then we valida...

This work aimed to develop a noninvasive and reliable computed tomography (CT)-based imaging biomarker to predict early recurrence (ER) of intrahepatic cholangiocarcinoma (ICC) via radiomics analysis. In this retrospective study, a total of 177 ICC patients were enrolled from three independent hospitals. Radiomic features were extracted on CT image...

Preoperative predicting histological grade of hepatocellular carcinoma (HCC) is a crucial issue for the evaluation of patient prognosis and determining clinical treatment strategies. Previous studies have shown the potential of preoperative medical imaging in HCC grading diagnosis, however, there still remain challenges. In this work, we proposed a...

Background Macrovascular invasion (MaVI) occurs in nearly half of hepatocellular carcinoma (HCC) patients at diagnosis or during follow-up, which causes severe disease deterioration, and limits the possibility of surgical approaches. This study aimed to investigate whether computed tomography (CT)-based radiomics analysis could help predict develop...

Hepatocellular carcinoma (HCC) is the sixth most common malignancy and the fourth leading cause of cancer related death worldwide. China covers over half of cases, leading HCC to be a vital threaten to public health. Despite advances in diagnosis and treatments, high recurrence rate remains a major obstacle in HCC management. Multi-omics currently...

Objective To investigate the capability of a radiomics model, which was designed to identify histopathologic growth pattern (HGP) of colorectal liver metastases (CRLMs) based on contrast-enhanced multidetector computed tomography (ceMDCT), to predict early response and 1-year progression free survival (PFS) in patients treated with bevacizumab-cont...

Accurate liver necroinflammatory activity diagnosis could guide the clinical decision‐making in chronic hepatitis B (CHB) patients.This study aimed to build a non‐invasive diagnostic model for liver necroinflammatory activity by incorporating deep learning features and clinico‐biochemical characteristics in CHB patients. A total of 239 CHB patients...

Simple Summary Microvascular invasion (MVI) is an independent risk factor for postoperative recurrence of hepatocellular carcinoma (HCC). Preoperative knowledge of MVI would assist with tailored surgical strategy making to prolong patient survival. Previous radiological studies proved the role of noninvasive medical imaging in MVI prediction. Howev...

Radiomics is useful for the evaluation of treatment and prognosis in cancer patients with different treatments. In this chapter, radiomics and its application in treatment evaluation is discussed. Radiomics-based prognosis analysis is discussed in detail. Prediction of recurrence, metastasis, or suvival with CT imaging, PET/CT imaging, etc., for va...

This chapter discusses the key technologies and software platforms for radiomics. Initially, tumor detection and tumor segmentation have been discussed. This chapter introduces some widely used feature selection or dimension reduction methods in radiomics and analyzes their application scenarios. At the end of this chapter, the radiomics platform a...

This chapter introduces some typical radiomic studies with practical clinical significance and important reference value in precision diagnosis. The applications of radiomics in cancer screening, staging, histopathological diagnosis, gene mutation, and molecular subtype are summarized. The applications of radiomics in other diseases are also discus...

This book is introduced with the development history of medical imaging. We first described the origin and concept of radiomics. We also discussed core value and method flow of radiomics with its key technologies. The wide clinical applications of radiomics in auxiliary diagnosis and treatment were additionally described. Finally, four classical ca...

Purpose The purpose of this study was to develop and validate a deep learning (DL)‐based radiomics model to predict the response to chemotherapy in colorectal liver metastases (CRLM). Methods In this retrospective study, we enrolled 192 patients diagnosed with CRLM who received first‐line chemotherapy and were followed by response assessment. Tumo...

The cover image is based on the Review Article Radiomics in Liver Diseases: Current Progress and Future Opportunities by Jie Tian, Hanyu Jiang, Jing Wei Wei et al., https://doi.org/10.1111/liv.14555.

Purpose: Developing an MRI-based radiomics model to effectively and accurately predict the predominant histopathologic growth patterns (HGPs) of colorectal liver metastases (CRLMs). Materials and Methods: In this study, 182 resected and histopathological proven CRLMs of chemotherapy-naive patients from two institutions, including 123 replacement CR...

Background Glypican 3 (GPC3) expression has proved to be a critical risk factor related to prognosis in hepatocellular carcinoma (HCC) patients. Purpose To investigate the performance of MRI‐based radiomics signature in identifying GPC3‐positive HCC. Study Type Retrospective. Population An initial cohort of 293 patients with pathologically confi...

Liver diseases, a wide spectrum of pathologies from inflammation to neoplasm, have become an increasingly significant health problem worldwide. Noninvasive imaging plays a critical role in the clinical workflow of liver diseases, but conventional imaging assessment may provide limited information. Accurate detection, characterization and monitoring...

Background: Intracranial hemangiopericytoma (IHPC) and meningioma are both meningeal neoplasms, but they have extremely different malignancy and outcomes. Because of their similar radiological characteristics, they are difficult to distinguish prior to surgery, leading to a high rate of misdiagnosis. Methods: We enrolled 292 patients (IHPC, 155; me...

Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading rapidly around the world, resulting in a massive death toll. Lung infection or pneumonia is the common complication of COVID-19, and imaging techniques, especially computed tomography (CT), have played an important role in dia...

Background The diagnosis performance of B-mode ultrasound (US) for focal liver lesions (FLLs) is relatively limited. We aimed to develop a deep convolutional neural network of US (DCNN-US) for aiding radiologists in classification of malignant from benign FLLs. Materials and Methods This study was conducted in 13 hospitals and finally 2,143 patien...

Background: Biopsy Gleason score (GS) is crucial for prostate cancer (PCa) treatment decision-making. Upgrading in GS from biopsy to radical prostatectomy (RP) puts a proportion of patients at risk of undertreatment. Purpose: To develop and validate a radiomics model based on multiparametric magnetic resonance imaging (mp-MRI) to predict PCa upg...

Objectives We aimed to develop a radiomics-based model derived from gadoxetic acid–enhanced MR images to preoperatively identify cytokeratin (CK) 19 status of hepatocellular carcinoma (HCC). Methods A cohort of 227 patients with single HCC was classified into a training set (n = 159) and a time-independent validated set (n = 68). A total of 647 ra...

Background: Whether men with a prostate-specific antigen (PSA) level of 4-10 ng/mL should be recommended for a biopsy is clinically challenging. Purpose: To develop and validate a radiomics model based on multiparametric MRI (mp-MRI) in patients with PSA levels of 4-10 ng/mL to predict prostate cancer (PCa) preoperatively and reduce unnecessary...

Background: Predicting early recurrence (ER) after radical therapy for HCC patients is critical for the decision of subsequent follow-up and treatment. Radiomic features derived from the medical imaging show great potential to predict prognosis. Here we aim to develop and validate a radiomics nomogram that could predict ER after curative ablation....

Objectives To predict histopathologic growth patterns (HGPs) in colorectal liver metastases (CRLMs) with a noninvasive radiomics model. Methods Patients with chemotherapy-naive CRLMs who underwent abdominal contrast-enhanced multidetector CT (MDCT) followed by partial hepatectomy between January 2007 and January 2019 from two institutions were inc...

Purpose: To develop a model to select appropriate candidates for irradiation stent placement among patients with unresectable pancreatic cancer with malignant biliary obstruction (UPC-MBO). Methods: This retrospective study included 106 patients treated with an irradiation stent for UPC-MBO. These patients were randomly divided into a training grou...

Objectives: Models should be developed to assist choice between liver resection (LR) and transarterial chemoembolization (TACE) for hepatocellular carcinoma. Methods: After separating 520 cases from 5 hospitals into training (n = 302) and validation (n = 218) data sets, we weighted the cases to control baseline difference and ensured the causal...

In hepatocellular carcinoma (HCC), patients at early stages are recommended to accept surgical resection as primary treatment by internationally endorsed guidelines. Nevertheless, post-surgical recurrence is one of the main threats that lead to death, with 5-year recurrence rate of over 70%. How to select patients at high risk of recurrence is esse...

Objective To develop and validate a radiomics-based nomogram for preoperatively predicting grade 1 and grade 2/3 tumors in patients with pancreatic neuroendocrine tumors (PNETs). Methods One hundred thirty-eight patients derived from two institutions with pathologically confirmed PNETs (104 in the training cohort and 34 in the validation cohort) w...

e14623 Background: To investigate whether preoperative imaging-based analysis could help to predict future macrovascular invasion (MaVI) occurrence in hepatocellular carcinoma (HCC). Methods: A cohort of 224 patients with HCC was enrolled from five independent medical centers (training cohort: n = 154; independent validation cohort: n = 70). Predic...

Objectives: To assess whether radiomics signature can identify aggressive behavior and predict recurrence of hepatocellular carcinoma (HCC) after liver transplantation. Methods: Our study consisted of a training dataset (n = 93) and a validation dataset (40) with clinically confirmed HCC after liver transplantation from October 2011 to December...

Objectives To develop and validate a radiomics nomogram to preoperative prediction of isocitrate dehydrogenase (IDH) genotype for astrocytomas, which might contribute to the pretreatment decision-making and prognosis evaluating. Methods One hundred five astrocytomas (Grades II–IV) with contrast-enhanced T1-weighted imaging (CE-T1WI), T2 fluid-atte...

Objectives To develop and validate a radiomics nomogram for preoperative prediction of microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC). Methods The study included 157 patients with histologically confirmed HCC with or without MVI, and 110 patients were allocated to the training dataset and 47 to the validation dataset....

Medical imaging can assess the tumor and its environment in their entirety, which makes it suitable for monitoring the temporal and spatial characteristics of the tumor. Progress in computational methods, especially in artificial intelligence for medical image process and analysis, has converted these images into quantitative and minable data assoc...

Objectives Immunoscore evaluates the density of CD3+ and CD8+ T cells in both the tumor core and invasive margin. Pretreatment prediction of immunoscore in hepatocellular cancer (HCC) is important for precision immunotherapy. We aimed to develop a radiomics model based on gadolinium-ethoxybenzyl-diethylenetriamine (Gd-EOB-DTPA)-enhanced MRI for pre...

Background: Radiomics has emerged as a new approach that can help identify imaging information associated with tumor pathophysiology. We developed and validated a radiomics nomogram for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Methods: Two hundred and eight patients with pathologically confirmed...

PurposeTo perform radiomics analysis for non-invasively predicting chromosome 1p/19q co-deletion in World Health Organization grade II and III (lower-grade) gliomas. Methods This retrospective study included 277 patients histopathologically diagnosed with lower-grade glioma. Clinical parameters were recorded for each patient. We performed a radiomi...

Objectives: Oxygen 6-methylguanine-DNA methyltransferase (MGMT) promoter methylation is a significant prognostic biomarker in astrocytomas, especially for temozolomide (TMZ) chemotherapy. This study aimed to preoperatively predict MGMT methylation status based on magnetic resonance imaging (MRI) radiomics and validate its value for evaluation of T...

Micro-vascular invasion (MVI) is underscored as a judicious risk factor for early-stage recurrence and poor prognosis of hepatocellular carcinoma (HCC). Preoperative knowledge of MVI would assist in therapy decision making beforehand, thus prolong the survival of HCC patients. However, current diagnosis of MVI could only be obtained by pathological...

Purpose To investigate the association between imaging features and low-grade gliomas (LGG) related epilepsy, and to propose a radiomics-based model for the prediction of LGG-associated epilepsy. Methods This retrospective study consecutively enrolled 286 patients with LGGs (194 in the primary cohort and 92 in the validation cohort). T2-weighted M...

Radiomics, as a newly emerging technology, converts medical images into high-dimensional data via high-throughput extraction of quantitative features, followed by subsequent data analysis for decision support. It identifies general diagnostic or prognostic phenotypes with target clinical need, providing an unprecedented opportunity to improve indiv...

2043 Background: Oligodendroglial tumor (OT) is one of the main types of gliomas, which is incurable in current situation. As a tumor-specific genetic alteration of OTs, loss of heterozygosity (LOH) on chromosome 1p/19q indicates a preferable response to chemo/radiotherapy and a better survial, which could be used as a key molecular signature for p...