scholarly journals Advances in the application of artificial intelligence in solid tumor imaging

2021 ◽  
Vol 2 (2) ◽  
pp. 12-24
Author(s):  
Ying Shao ◽  
Yu-Xuan Zhang ◽  
Huan-Huan Chen ◽  
Shan-Shan Lu ◽  
Shi-Chang Zhang ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Solid Tumor ◽  
Tumor Imaging

scholarly journals Current and Potential Applications of Artificial Intelligence in Gastrointestinal Stromal Tumor Imaging

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Cai-Wei Yang ◽  
Xi-Jiao Liu ◽  
Si-Yun Liu ◽  
Shang Wan ◽  
Zheng Ye ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Tumor Imaging ◽  
Therapy Response ◽  
Imaging Method ◽  
Mesenchymal Tumors ◽  
Potential Applications ◽  
Intellectual Capacity ◽  
Prediction Of Prognosis ◽  
Current Guidelines

The most common mesenchymal tumors are gastrointestinal stromal tumors (GISTs), which have malignant potential and can occur anywhere along the gastrointestinal system. Imaging methods are important and indispensable of GISTs in diagnosis, risk staging, therapy, and follow-up. The recommended imaging method for staging and follow-up is computed tomography (CT) according to current guidelines. Artificial intelligence (AI) applies and elaborates theses, procedures, modes, and utilization systems for simulating, enlarging, and stretching the intellectual capacity of humans. Recently, researchers have done a few studies to explore AI applications in GIST imaging. This article reviews the present AI studies in GISTs imaging, including preoperative diagnosis, risk stratification and prediction of prognosis, gene mutation, and targeted therapy response.

Formulation and preclinical evaluation of 99mTc–gemcitabine as a novel radiopharmaceutical for solid tumor imaging

2014 ◽  
Vol 302 (1) ◽  
pp. 179-186 ◽  
Author(s):  
A. B. Ibrahim ◽  
T. M. Sakr ◽  
O. M. A. Khoweysa ◽  
M. A. Motaleb ◽  
A. Abd El-Bary ◽  
...  
Keyword(s):  
Solid Tumor ◽  
Tumor Imaging ◽  
Preclinical Evaluation

scholarly journals Correction to: Characterization of the first fully human anti-TEM1 scFv in models of solid tumor imaging and immunotoxin-based therapy

2018 ◽  
Vol 67 (2) ◽  
pp. 329-339 ◽  
Author(s):  
Xiaopeng Yuan ◽  
Mingjuan Yang ◽  
Xiang Chen ◽  
Xuhua Zhang ◽  
Shrey Sukhadia ◽  
...  
Keyword(s):  
Solid Tumor ◽  
Tumor Imaging

99mTc-citrate-gold nanoparticles as a tumor tracer: synthesis, characterization, radiolabeling and in-vivo studies

2020 ◽  
Vol 108 (10) ◽  
pp. 809-819 ◽  
Author(s):  
Basma M. Essa ◽  
Ahmed A. El-Mohty ◽  
Maher A. El-Hashash ◽  
Tamer M. Sakr
Keyword(s):  
Drug Delivery ◽  
Gold Nanoparticles ◽  
Drug Delivery System ◽  
Delivery System ◽  
Solid Tumor ◽  
Tumor Imaging ◽  
In Vivo Studies ◽  
Post Injection ◽  
Tumor Bearing

AbstractTargeted drug delivery system can reduce the side effects of high drug concentration by improving drug pharmacokinetics at lower doses. Citrate-gold nanoparticles (AuNPs) as a drug delivery system were synthesized via green nanotechnology technique to be used as a new imaging platform for tumor targeting. Citrate-AuNPs were synthesized with core size of 10 nm. Citrate-AuNPs were labeled with technetium-99m (99mTc) with radiochemical yield of 95.20 ± 2.70% with good in-vitro stability in both saline and human serum and well in-vivo studied in both normal and solid tumor bearing mice. The in-vivo biodistribution study of [99mTc]Tc-citrate-AuNPs in solid tumor bearing mice (as preliminary study) showed a high accumulation in tumor site with tumor/muscle of 4.35 ± 0.22 after 30 min post injection. The direct intratumoral (I.T) injection of [99mTc]Tc-citrate-AuNPs showed that this complex was retained in the tumor up to 77.86 ± 1.90 % at 5 min and still around 50.00 ± 1.42 % after 30 min post injection (p.i.). The newly presented nano-platform could be presented as a new potential radiopharmaceutical tumor imaging probe.

Artificial Intelligence and Deep Learning in Neuroradiology: Exploring the New Frontier

2020 ◽  
pp. 084653712095429
Author(s):  
Hussam Kaka ◽  
Euan Zhang ◽  
Nazir Khan
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Multiple Sclerosis ◽  
Deep Learning ◽  
Intracranial Aneurysm ◽  
Intracranial Hemorrhage ◽  
Tumor Imaging ◽  
Stroke Imaging ◽  
Spine Imaging ◽  
New Frontier

There have been many recently published studies exploring machine learning (ML) and deep learning applications within neuroradiology. The improvement in performance of these techniques has resulted in an ever-increasing number of commercially available tools for the neuroradiologist. In this narrative review, recent publications exploring ML in neuroradiology are assessed with a focus on several key clinical domains. In particular, major advances are reviewed in the context of: (1) intracranial hemorrhage detection, (2) stroke imaging, (3) intracranial aneurysm screening, (4) multiple sclerosis imaging, (5) neuro-oncology, (6) head and tumor imaging, and (7) spine imaging.

Artificial Intelligence for solid tumor diagnosis in digital pathology

2021 ◽  
Author(s):  
Christophe Klein ◽  
Qinghe Zeng ◽  
Floriane Arbaretaz ◽  
Estelle Devêvre ◽  
Julien Calderaro ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Solid Tumor ◽  
Digital Pathology ◽  
Tumor Diagnosis
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