Contrast Media & Molecular Imaging
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Acceptance rate49%
Submission to final decision42 days
Acceptance to publication26 days
CiteScore4.900
Journal Citation Indicator0.680
Impact Factor3.009

Article of the Year 2021

Preclinical Molecular PET-CT Imaging Targeting CDCP1 in Colorectal Cancer

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 Journal profile

Contrast Media & Molecular Imaging is an exciting journal in the area of contrast agents and molecular imaging, covering all areas of imaging technologies with a special emphasis on MRI and PET.

 Editor spotlight

Chief Editor, Professor Zimmer, focuses on the development and use of PET radiotracers for new applications of PET/MRI imaging in neuroscience and pharmacology.

 Special Issues

Do you think there is an emerging area of research that really needs to be highlighted? Or an existing research area that has been overlooked or would benefit from deeper investigation? Raise the profile of a research area by leading a Special Issue.

Latest Articles

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Research Article

Region-Based Segmentation and Classification for Ovarian Cancer Detection Using Convolution Neural Network

Ovarian cancer is a serious sickness for elderly women. According to data, it is the seventh leading cause of death in women as well as the fifth most frequent disease worldwide. Many researchers classified ovarian cancer using Artificial Neural Networks (ANNs). Doctors consider classification accuracy to be an important aspect of making decisions. Doctors consider improved classification accuracy for providing proper treatment. Early and precise diagnosis lowers mortality rates and saves lives. On basis of ROI (region of interest) segmentation, this research presents a novel annotated ovarian image classification utilizing FaRe-ConvNN (rapid region-based Convolutional neural network). The input photos were divided into three categories: epithelial, germ, and stroma cells. This image is segmented as well as preprocessed. After that, FaRe-ConvNN is used to perform the annotation procedure. For region-based classification, the method compares manually annotated features as well as trained feature in FaRe-ConvNN. This will aid in the analysis of higher accuracy in disease identification, as human annotation has lesser accuracy in previous studies; therefore, this effort will empirically prove that ML classification will provide higher accuracy. Classification is done using a combination of SVC and Gaussian NB classifiers after the region-based training in FaRe-ConvNN. The ensemble technique was employed in feature classification due to better data indexing. To diagnose ovarian cancer, the simulation provides an accurate portion of the input image. FaRe-ConvNN has a precision value of more than 95%, SVC has a precision value of 95.96%, and Gaussian NB has a precision value of 97.7%, with FR-CNN enhancing precision in Gaussian NB. For recall/sensitivity, SVC is 94.31 percent and Gaussian NB is 97.7 percent, while for specificity, SVC is 97.39 percent and Gaussian NB is 98.69 percent using FaRe-ConvNN.

Research Article

Detection of Bone Metastases by 68Ga-DOTA-SSAs and 18F-FDG PET/CT: A Two-Center Head-to-Head Study of Gastroenteropancreatic Neuroendocrine Neoplasms

Purpose. This study aimed to assess the efficacy of dual-tracer [68Ga-DOTA-somatostatin receptor analogs (SSAs) and 18F-fluorodeoxyglucose (FDG)] positron emission tomography/computed tomography (PET/CT) imaging for detecting bone metastases (BMs) in patients with gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs). Methods. We retrospectively enrolled 74 GEP-NEN patients with BMs from two centers, who underwent dual-tracer PET/CT from January 2014 to March 2021. We compared and analyzed effectiveness of the dual PET/CT imaging techniques on the BMs, based on 18F-FDG and 68Ga-DOTA-SSAs. Specifically, we analyzed the imaging results using χ2 tests for classification variables, paired-sample tests for number of BMs, Wilcoxon’s signed rank test for number of lesions, and the Kruskal–Wallis test for standard uptake value (SUV) ratio comparison. The correlation of dual-tracer SUVmax with Ki-67 index was analyzed by Spearman’s correlation coefficient. Results. The detection efficiencies of dual-tracer PET/CT imaging in patients with different pathologies showed discordant for detecting liver metastases and BMs in group neuroendocrine tumor (NET) G3, 68Ga-DOTA-SSAs was better at detecting BMs for NET G3 ( for SUVT/B and for the number of metastatic lesions). In addition, statistical significance was found among osteogenesis group, osteolysis group, and the no-change group (for bone SUVT/B value detected by 18F-FDG and Ki-67 index, osteogenesis group < osteolysis group; for bone SUVT/B detected by 68Ga-DOTA-SSAs, osteogenesis group > the no-change group). What is more, liver and bone SUVmax and Ki-67 index were positively correlated in 18F-FDG imaging ( for liver; for bone), and negatively correlated in 68Ga-DOTA-SSAs imaging ( for liver; for bone). Conclusions. 68Ga-DOTA-SSAs was superior to 18F-FDG for detecting BMs in NET G1/G2 (well and moderately differentiated NETs), as well as in NET G3 (poorly differentiated NETs). Relatively good differentiation was observed in the osteogenesis group. In addition, dual-tracer PET/CT imaging results were observably correlated with tumor differentiation.

Research Article

Study on Intelligent Traditional Chinese Medicine Fumigation for Treating Lumbar Intervertebral Disc Herniation Based on Medical Big Data Mining

With the improvement of the traditional Chinese medicine fumigation (TCMF), more and more people are studying lumbar intervertebral disc herniation (LIDH) by TCMF. In order to clarify the thermodynamic mechanism of TCMF to LIDH and provide a model reference for individualized diagnosis, the lower control system is compiled by the microprocessor, and the upper control system is compiled by computer technology of VB. In this new system, the medical information of patients is recorded in the databases by the upper control system, and clinical diagnosis and treatment experience are packaged in the lower control system. The simulation results and clinical examples show that the new control system of TCMF has better clinical efficacy for LIDH patients, which not only effectively improves the pain symptoms of LIDH patients but is also economical and safe.

Research Article

Quantitative Analysis of Contrast-Enhanced Ultrasound That Can Be Used to Evaluate Angiogenesis during Patellar Tendon Healing in Rats

Objective. To investigate the efficacy of contrast-enhanced ultrasound (CEUS) in quantitatively evaluating angiogenesis during patellar tendon healing in rats. Methods. A total of 40 Sprague–Dawley rats were used in this study. The patellar tendons of 30 rats (60 limbs) that underwent incision and suture were treated as the operation group and monitored after 7, 14, and 28 days. The normal patellar tendons of 10 rats (20 limbs) were treated as the control group and monitored on day 0. The ultrasound examination was used to evaluate the structure and blood perfusion of the patellar tendon. Immunohistochemistry was used to assess angiogenesis, and the biomechanical test was used to verify functional recovery of the patellar tendon. Results. The tendons in the operation group were significantly thickened compared with those in the control group ( < 0.01). The peak intensity (PI) in CEUS of the tendons showed a clear difference at each time point after the surgery ( < 0.01). PI increased in the operation group with a maximum on day 7, and then gradually decreased until day 28 when PI was close to the basic intensity (BI) in the control group ( > 0.05). It was consistent with the change of the CD31-positive staining areas representing angiogenesis of the injured patellar tendons. The PI was positively correlated with the CD31-positive staining area fraction (R = 0.849,  < 0.001). The failure load and tensile strength of the repaired patellar tendons in the operation group increased over time. The PI showed negative correlations with the failure load (R = −0.787,  < 0.001) and tensile strength (R = −0.714,  < 0.001). Conclusion. The PI in CEUS could quantitatively reflect the time-dependent change in the blood supply of the healing site, and the PI correlated with histologic and biomechanical properties of the healing tendon. Quantitative analysis of contrast-enhanced ultrasound could be a useful method to evaluate angiogenesis in healing tendons.

Review Article

Artificial Intelligence and Deep Learning Assisted Rapid Diagnosis of COVID-19 from Chest Radiographical Images: A Survey

Artificial Intelligence (AI) has been applied successfully in many real-life domains for solving complex problems. With the invention of Machine Learning (ML) paradigms, it becomes convenient for researchers to predict the outcome based on past data. Nowadays, ML is acting as the biggest weapon against the COVID-19 pandemic by detecting symptomatic cases at an early stage and warning people about its futuristic effects. It is observed that COVID-19 has blown out globally so much in a short period because of the shortage of testing facilities and delays in test reports. To address this challenge, AI can be effectively applied to produce fast as well as cost-effective solutions. Plenty of researchers come up with AI-based solutions for preliminary diagnosis using chest CT Images, respiratory sound analysis, voice analysis of symptomatic persons with asymptomatic ones, and so forth. Some AI-based applications claim good accuracy in predicting the chances of being COVID-19-positive. Within a short period, plenty of research work is published regarding the identification of COVID-19. This paper has carefully examined and presented a comprehensive survey of more than 110 papers that came from various reputed sources, that is, Springer, IEEE, Elsevier, MDPI, arXiv, and medRxiv. Most of the papers selected for this survey presented candid work to detect and classify COVID-19, using deep-learning-based models from chest X-Rays and CT scan images. We hope that this survey covers most of the work and provides insights to the research community in proposing efficient as well as accurate solutions for fighting the pandemic.

Research Article

Lymph Node Metastases Detection Using Gd2O3@PCD as Novel Multifunctional Contrast Imaging Agent in Metabolic Magnetic Resonance Molecular Imaging

Axillary lymph node detection is crucial to staging and prognosis of the lymph node metastatic spread in breast cancer. Currently, lymphoscintigraphy and blue dye, as the conventional methods to localize sentinel lymph nodes (SLNs), are invasive and can only be performed during surgery. This study has had a novel hybrid gadolinium oxide nanoparticle coating with Cyclodextrin-based polyester as a high-relaxivity T1 magnetic resonance molecular imaging (MRMI) contrast agent (CA). Twelve female BALB/c mice were randomly divided into three groups of four mice; each group was injected with 4T1 cells to obtain metastasis lymph nodes and diagnosed by using the 3D T1W (VIBE) MRI (Siemens 3T, Prisma). The synthesized Gd2O3@PCD nanoparticles with a suitable particle size range of 20–40 nm have had much higher longitudinal relaxivity (r1) for Gd2O3@PCD and Gd-DOTA (Dotarem) with the values of 3.98 mM−1·s−1 ± 0.003 and 2.71 mM−1·s−1 ± 0.005, respectively. Identical MR images in coronal views were subsequently obtained to create time-intensity curves of the right axillary lymph nodes and to measure the contrast ratio (CR). The peak CR and qualitative assessment of axillary lymph nodes at five-time points were evaluated. After subcutaneous injection, the contrast ratio of axillary lymph node and tumor in mice exhibited CR peak of Gd2O3@PCD and Dotarem with the values of 2.21 ± 0.06 and 0.40 ± 0.004 for lymph node and 2.54 ± 0.04 and 1.21 ± 0.007 for the tumor, respectively. Furthermore, the lumbar-aortic lymph node is weakly visible in the original coronal image. In conclusion, the use of Gd2O3@PCD nanoparticles as novel MRMI CAs enables high resolution for the detection of lymph node metastasis in mice with the potential capability for breast cancer diagnostic imaging.

Contrast Media &#x26; Molecular Imaging
Publishing Collaboration
More info
Wiley Hindawi logo
 Journal metrics
See full report
Acceptance rate49%
Submission to final decision42 days
Acceptance to publication26 days
CiteScore4.900
Journal Citation Indicator0.680
Impact Factor3.009
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Article of the Year Award: Outstanding research contributions of 2021, as selected by our Chief Editors. Read the winning articles.