Cancer Imaging is the official journal of the International Cancer Imaging Society (ICIS)
Articles
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Citation: Cancer Imaging 2024 24:82
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Identification of T2W hypointense ring as a novel noninvasive indicator for glioma grade and IDH genotype
This study aimed to evaluate the T2W hypointense ring and T2-FLAIR mismatch signs in gliomas and use these signs to construct prediction models for glioma grading and isocitrate dehydrogenase (IDH) mutation st...
Citation: Cancer Imaging 2024 24:80 -
MRI features and tumor-infiltrating CD8 + T cells-based nomogram for predicting meningioma recurrence risk
This study was based on MRI features and number of tumor-infiltrating CD8 + T cells in post-operative pathology, in predicting meningioma recurrence risk.
Citation: Cancer Imaging 2024 24:79 -
Thoracic high resolution computed tomography evaluation of imaging abnormalities of 108 lung cancer patients with different pulmonary function
Preserved ratio impaired spirometry (PRISm) and chronic obstructive pulmonary disease (COPD) belong to lung function injury. PRISm is a precursor to COPD. We compared and evaluated the different basic informat...
Citation: Cancer Imaging 2024 24:78 -
Prognostic value of the tumor-to-liver density ratio in patients with metastatic colorectal cancer treated with bevacizumab-based chemotherapy. A post-hoc study of the STIC-AVASTIN trial
The Response Evaluation Criteria in Solid Tumors (RECIST) are often inadequate for the early assessment of the response to cancer therapy, particularly bevacizumab-based chemotherapy. In a first cohort of pati...
Citation: Cancer Imaging 2024 24:77 -
CTR > 0.7 predicts the subgroup of lung adenocarcinomas ≤ 2 cm at risk of poor outcome treated by sublobar resection compared to lobar resection
A standard surgical procedure for patients with small early-stage lung adenocarcinomas remains unknown. Hence, we aim in this study to assess the clinical utility of the consolidation-to-tumor ratio (CTR) when...
Citation: Cancer Imaging 2024 24:76 -
Targeted sequencing of DNA/RNA combined with radiomics predicts lymph node metastasis of papillary thyroid carcinoma
The aim of our study is to find a better way to identify a group of papillary thyroid carcinoma (PTC) with more aggressive behaviors and to provide a prediction model for lymph node metastasis to assist in cli...
Citation: Cancer Imaging 2024 24:75 -
Thyroid imaging reporting and data system with MRI morphological features for thyroid nodules: diagnostic performance and unnecessary biopsy rate
To assess MRI-based morphological features in improving the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) for categorizing thyroid nodules.
Citation: Cancer Imaging 2024 24:74 -
Impact of annual trend volume of low-dose computed tomography for lung cancer screening on overdiagnosis, overmanagement, and gender disparities
With the increasing prevalence of nonsmoking-related lung cancer in Asia, Asian countries have increasingly adopted low-dose computed tomography (LDCT) for lung cancer screening, particularly in private screen...
Citation: Cancer Imaging 2024 24:73 -
Whole-tumoral metabolic heterogeneity in 18F-FDG PET/CT is a novel prognostic marker for neuroblastoma
Neuroblastoma (NB) is a highly heterogeneous tumor, and more than half of newly diagnosed NB are associated with extensive metastases. Accurately characterizing the heterogeneity of whole-body tumor lesions re...
Citation: Cancer Imaging 2024 24:72 -
Histogram analysis of multiple diffusion models for predicting advanced non-small cell lung cancer response to chemoimmunotherapy
There is an urgent need to find a reliable and effective imaging method to evaluate the therapeutic efficacy of immunochemotherapy in advanced non-small cell lung cancer (NSCLC). This study aimed to investigat...
Citation: Cancer Imaging 2024 24:71 -
Patient eligibility for trials with imaging response assessment at the time of molecular tumor board presentation
To assess the eligibility of patients with advanced or recurrent solid malignancies presented to a molecular tumor board (MTB) at a large precision oncology center for inclusion in trials with the endpoints ob...
Citation: Cancer Imaging 2024 24:70 -
Does clinical T1N0 GGN really require checking for distant metastasis during initial staging for lung cancer?
Accurate clinical staging is crucial for selection of optimal oncological treatment strategies in non-small cell lung cancer (NSCLC). Although brain MRI, bone scintigraphy and whole-body PET/CT play important ...
Citation: Cancer Imaging 2024 24:69 -
[18F]FAPI adds value to [18F]FDG PET/CT for diagnosing lymph node metastases in stage I-IIIA non-small cell lung cancer: a prospective study
This study investigates the value of fluorine 18 ([18F])-labeled fibroblast activation protein inhibitor (FAPI) for lymph node (LN) metastases in patients with stage I-IIIA non-small cell lung cancer (NSCLC).
Citation: Cancer Imaging 2024 24:68 -
7 Tesla magnetic resonance spectroscopic imaging predicting IDH status and glioma grading
With the application of high-resolution 3D 7 Tesla Magnetic Resonance Spectroscopy Imaging (MRSI) in high-grade gliomas, we previously identified intratumoral metabolic heterogeneities.
Citation: Cancer Imaging 2024 24:67 -
Prognostic and predictive value of interstitial lung abnormalities and EGFR mutation status in patients with non-small cell lung cancer
To determine the predictive value of interstitial lung abnormalities (ILA) for epidermal growth factor receptor (EGFR) mutation status and assess the prognostic significance of EGFR and ILA in patients with no...
Citation: Cancer Imaging 2024 24:66 -
MR-based radiomics predictive modelling of EGFR mutation and HER2 overexpression in metastatic brain adenocarcinoma: a two-centre study
Magnetic resonance (MR)-based radiomics features of brain metastases are utilised to predict epidermal growth factor receptor (EGFR) mutation and human epidermal growth factor receptor 2 (HER2) overexpression ...
Citation: Cancer Imaging 2024 24:65 -
Applying dynamic contrast-enhanced MRI tracer kinetic models to differentiate benign and malignant soft tissue tumors
To explore the potential of different quantitative dynamic contrast-enhanced (qDCE)-MRI tracer kinetic (TK) models and qDCE parameters in discriminating benign from malignant soft tissue tumors (STTs).
Citation: Cancer Imaging 2024 24:64 -
HCA-DAN: hierarchical class-aware domain adaptive network for gastric tumor segmentation in 3D CT images
Accurate segmentation of gastric tumors from CT scans provides useful image information for guiding the diagnosis and treatment of gastric cancer. However, automated gastric tumor segmentation from 3D CT image...
Citation: Cancer Imaging 2024 24:63 -
A CT based radiomics analysis to predict the CN0 status of thyroid papillary carcinoma: a two- center study
To develop and validate radiomics model based on computed tomography (CT) for preoperative prediction of CN0 status in patients with papillary thyroid carcinoma (PTC).
Citation: Cancer Imaging 2024 24:62 -
Preoperative CT-based radiomic prognostic index to predict the benefit of postoperative radiotherapy in patients with non-small cell lung cancer: a multicenter study
The value of postoperative radiotherapy (PORT) for patients with non-small cell lung cancer (NSCLC) remains controversial. A subset of patients may benefit from PORT. We aimed to identify patients with NSCLC w...
Citation: Cancer Imaging 2024 24:61 -
Impact of deep learning image reconstruction on volumetric accuracy and image quality of pulmonary nodules with different morphologies in low-dose CT
This study systematically compares the impact of innovative deep learning image reconstruction (DLIR, TrueFidelity) to conventionally used iterative reconstruction (IR) on nodule volumetry and subjective image...
Citation: Cancer Imaging 2024 24:60 -
A clinical-radiomics nomogram based on dual-layer spectral detector CT to predict cancer stage in pancreatic ductal adenocarcinoma
This study aimed to evaluate the efficacy of radiomics signatures derived from polyenergetic images (PEIs) and virtual monoenergetic images (VMIs) obtained through dual-layer spectral detector CT (DLCT). Moreo...
Citation: Cancer Imaging 2024 24:55 -
Multi-institutional validation of a radiomics signature for identification of postoperative progression of soft tissue sarcoma
To develop a magnetic resonance imaging (MRI)-based radiomics signature for evaluating the risk of soft tissue sarcoma (STS) disease progression.
Citation: Cancer Imaging 2024 24:59 -
Superiority of 18F-FAPI-42 PET/CT in the detection of primary tumor and management of appendiceal neoplasm to 18F-FDG PET/CT and CE-CT
In the present study, we investigated the value of 18F-fibroblast-activation protein inhibitor (FAPI) positron emission tomography/computed tomography (18F-FAPI-42 PET/CT) to preoperative evaluations of appendice...
Citation: Cancer Imaging 2024 24:58 -
Comparison of quantitative whole body PET parameters on [68Ga]Ga-PSMA-11 PET/CT using ordered Subset Expectation Maximization (OSEM) vs. bayesian penalized likelihood (BPL) reconstruction algorithms in men with metastatic castration-resistant prostate cancer
PSMA PET/CT is a predictive and prognostic biomarker for determining response to [177Lu]Lu-PSMA-617 in patients with metastatic castration resistant prostate cancer (mCRPC). Thresholds defined to date may not be ...
Citation: Cancer Imaging 2024 24:57 -
Head-to-head comparison of [68Ga]Ga-DOTA-FAPI-04 and [18F]FDG PET/CT for the evaluation of tonsil cancer and lymph node metastases: a single-centre retrospective study
This study aimed to compare the diagnostic value of [68 Ga]Ga-DOTA-FAPI-04 and [18F]FDG PET/CT imaging for primary lesions and metastatic lymph nodes in patients with tonsil cancer.
Citation: Cancer Imaging 2024 24:56 -
Radiomics signature for dynamic changes of tumor-infiltrating CD8+ T cells and macrophages in cervical cancer during chemoradiotherapy
Our previous study suggests that tumor CD8+ T cells and macrophages (defined as CD68+ cells) infiltration underwent dynamic and heterogeneous changes during concurrent chemoradiotherapy (CCRT) in cervical canc...
Citation: Cancer Imaging 2024 24:54 -
Relationship of FDG PET/CT imaging features with tumor immune microenvironment and prognosis in colorectal cancer: a retrospective study
Imaging features of colorectal cancers on 2-deoxy-2-[18F]fluoro-d-glucose (FDG) positron emission tomography/computed tomography (PET/CT) have been considered to be affected by tumor characteristics and tumor imm...
Citation: Cancer Imaging 2024 24:53 -
Deep learning radiomics-based prediction model of metachronous distant metastasis following curative resection for retroperitoneal leiomyosarcoma: a bicentric study
Combining conventional radiomics models with deep learning features can result in superior performance in predicting the prognosis of patients with tumors; however, this approach has never been evaluated for t...
Citation: Cancer Imaging 2024 24:52 -
Extracting value from total-body PET/CT image data - the emerging role of artificial intelligence
The evolution of Positron Emission Tomography (PET), culminating in the Total-Body PET (TB-PET) system, represents a paradigm shift in medical imaging. This paper explores the transformative role of Artificial...
Citation: Cancer Imaging 2024 24:51 -
A CT-based radiomics nomogram for predicting histologic grade and outcome in chondrosarcoma
The preoperative identification of tumor grade in chondrosarcoma (CS) is crucial for devising effective treatment strategies and predicting outcomes. The study aims to build and validate a CT-based radiomics n...
Citation: Cancer Imaging 2024 24:50 -
MRI evaluation of vesical imaging reporting and data system for bladder cancer after neoadjuvant chemotherapy
The Vesical Imaging-Reporting and Data System (VI-RADS) has demonstrated effectiveness in predicting muscle invasion in bladder cancer before treatment. The urgent need currently is to evaluate the muscle inva...
Citation: Cancer Imaging 2024 24:49 -
Application of deep learning on mammographies to discriminate between low and high-risk DCIS for patient participation in active surveillance trials
Ductal Carcinoma In Situ (DCIS) can progress to invasive breast cancer, but most DCIS lesions never will. Therefore, four clinical trials (COMET, LORIS, LORETTA, AND LORD) test whether active surveillance for ...
Citation: Cancer Imaging 2024 24:48 -
Bubble-like lucency in pulmonary ground glass nodules on computed tomography: a specific pattern of air-containing space for diagnosing neoplastic lesions
To investigate the computed tomography (CT) characteristics of air-containing space and its specific patterns in neoplastic and non-neoplastic ground glass nodules (GGNs) for clarifying their significance in d...
Citation: Cancer Imaging 2024 24:47 -
Optimizing PSMA scintigraphy for resource limited settings – a retrospective comparative study
PSMA PET/CT is the most sensitive molecular imaging modality for prostate cancer (PCa), yet much of the developing world has little or no access to PET/CT. [99mTc]Tc-PSMA scintigraphy (PS) is a cheaper and more a...
Citation: Cancer Imaging 2024 24:46 -
HCC portal hypertension imaging score derived from CT predicts re-bleeding and mortality after acute variceal bleeding
Risk factors for re-bleeding and death after acute variceal bleeding (AVB) in cirrhotic HCC patients are not fully understood.We aimed to (1) explore how the combination of high-risk esophageal varices, HCC st...
Citation: Cancer Imaging 2024 24:45 -
Habitat-based radiomics analysis for evaluating immediate response in colorectal cancer lung metastases treated by radiofrequency ablation
To create radiomics signatures based on habitat to assess the instant response in lung metastases of colorectal cancer (CRC) after radiofrequency ablation (RFA).
Citation: Cancer Imaging 2024 24:44 -
A hierarchical fusion strategy of deep learning networks for detection and segmentation of hepatocellular carcinoma from computed tomography images
Automatic segmentation of hepatocellular carcinoma (HCC) on computed tomography (CT) scans is in urgent need to assist diagnosis and radiomics analysis. The aim of this study is to develop a deep learning base...
Citation: Cancer Imaging 2024 24:43 -
Prognostic PET [11C]-acetate uptake is associated with hypoxia gene expression in patients with late-stage hepatocellular carcinoma – a bench to bed study
Positron Emission Tomography (PET) with combined [18F]-FDG and [11C]-acetate (dual-tracer) is used for the management of hepatocellular carcinoma (HCC) patients, although its prognostic value and underlying molec...
Citation: Cancer Imaging 2024 24:42 -
Correction: Deep learning-based metastasis detection in patients with lung cancer to enhance reproducibility and reduce workload in brain metastasis screening with MRI: a multi-center study
Citation: Cancer Imaging 2024 24:41 -
Development of a modified 3D region proposal network for lung nodule detection in computed tomography scans: a secondary analysis of lung nodule datasets
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.
Citation: Cancer Imaging 2024 24:40 -
The potential value of ultrasound in predicting local refractory/relapse events in primary thyroid lymphoma patients
Primary thyroid lymphoma (PTL) is a rare malignant disorder, and ultrasound plays an important role in PTL diagnosis and follow-up surveillance. Prediction of refractory/relapse events in PTL patients is an es...
Citation: Cancer Imaging 2024 24:39 -
Dual-energy computed tomography in a multiparametric regression model for diagnosing lymph node metastases in pancreatic ductal adenocarcinoma
To investigate the diagnostic value of dual-energy computed tomography (DECT) quantitative parameters in the identification of regional lymph node metastasis in pancreatic ductal adenocarcinoma (PDAC).
Citation: Cancer Imaging 2024 24:38 -
Assessment of perineural spread in advanced cutaneous squamous cell carcinomas treated with immunotherapy
Cutaneous squamous cell carcinoma (CSCC) has a propensity for perineural spread (PNS) which is associated with poorer treatment outcomes. Immunotherapy is the new standard of care treatment for advanced CSCC r...
Citation: Cancer Imaging 2024 24:37 -
Artificial intelligence-based MRI radiomics and radiogenomics in glioma
The specific genetic subtypes that gliomas exhibit result in variable clinical courses and the need to involve multidisciplinary teams of neurologists, epileptologists, neurooncologists and neurosurgeons. Curr...
Citation: Cancer Imaging 2024 24:36 -
Predictive value of background parenchymal enhancement on breast magnetic resonance imaging for pathological tumor response to neoadjuvant chemotherapy in breast cancers: a systematic review
This review aimed to assess the predictive value of background parenchymal enhancement (BPE) on breast magnetic resonance imaging (MRI) as an imaging biomarker for pathologic complete response (pCR) after neoa...
Citation: Cancer Imaging 2024 24:35 -
Clinical outcomes of percutaneous microwave ablation for pulmonary oligometastases from hepatocellular carcinoma: a retrospective, multicenter study
Pulmonary oligometastases are common in hepatocellular carcinoma (HCC), however, the existing therapeutic options have several limitations. This study aimed to assess the safety and efficacy of microwave ablat...
Citation: Cancer Imaging 2024 24:34 -
Amide proton transfer-weighted imaging and stretch-exponential model DWI based 18F-FDG PET/MRI for differentiation of benign and malignant solitary pulmonary lesions
To differentiate benign and malignant solitary pulmonary lesions (SPLs) by amide proton transfer-weighted imaging (APTWI), mono-exponential model DWI (MEM-DWI), stretched exponential model DWI (SEM-DWI), and 18F-...
Citation: Cancer Imaging 2024 24:33 -
Deep learning-based metastasis detection in patients with lung cancer to enhance reproducibility and reduce workload in brain metastasis screening with MRI: a multi-center study
To assess whether a deep learning-based system (DLS) with black-blood imaging for brain metastasis (BM) improves the diagnostic workflow in a multi-center setting.
Citation: Cancer Imaging 2024 24:32
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Citation Impact 2023
Journal Impact Factor: 3.5
5-year Journal Impact Factor: 4.3
Source Normalized Impact per Paper (SNIP): 1.416
SCImago Journal Rank (SJR): 1.227Speed 2023
Submission to first editorial decision (median days): 13
Submission to acceptance (median days): 123Usage 2023
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