AIMC Topic: Tumor Burden

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PRIMAGE project: predictive in silico multiscale analytics to support childhood cancer personalised evaluation empowered by imaging biomarkers.

European radiology experimental Apr 3, 2020
PRIMAGE is one of the largest and more ambitious research projects dealing with medical imaging, artificial intelligence and cancer treatment in children. It is a 4-year European Commission-financed project that has 16 European partners in the consor...
Decision Support Techniques Phenotype Biomarkers Prognosis Female Humans Artificial Intelligence Glioma Europe Tumor Burden Neuroblastoma Cloud Computing Brain Neoplasms Male Disease Progression Child
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Can a machine-learning model improve the prediction of nodal stage after a positive sentinel lymph node biopsy in breast cancer?

Acta oncologica (Stockholm, Sweden) Mar 9, 2020
The current standard for evaluating axillary nodal burden in clinically node negative breast cancer is sentinel lymph node biopsy (SLNB). However, the accuracy of SLNB to detect nodal stage N2-3 remains debatable. Nomograms can help the decision-mak...
Lymph Nodes Nomograms Lymphatic Metastasis Neoplasm Invasiveness Lymph Node Excision Breast Neoplasms Middle Aged ROC Curve Logistic Models Carcinoma, Ductal, Breast Sentinel Lymph Node Biopsy, Fine-Needle Sentinel Lymph Node Biopsy Axilla Regression Analysis Breast Tumor Burden Humans Machine Learning Aged Aged, 80 and over Adult Retrospective Studies Female
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Pseudo-CT generation from multi-parametric MRI using a novel multi-channel multi-path conditional generative adversarial network for nasopharyngeal carcinoma patients.

Medical physics Feb 21, 2020
PURPOSE: To develop and evaluate a novel method for pseudo-CT generation from multi-parametric MR images using multi-channel multi-path generative adversarial network (MCMP-GAN).
Tumor Burden Nasopharyngeal Carcinoma Tomography, X-Ray Computed Image Processing, Computer-Assisted Humans Magnetic Resonance Imaging Neural Networks, Computer
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A quantitative model based on clinically relevant MRI features differentiates lower grade gliomas and glioblastoma.

European radiology Feb 5, 2020
OBJECTIVES: To establish a quantitative MR model that uses clinically relevant features of tumor location and tumor volume to differentiate lower grade glioma (LRGG, grades II and III) and glioblastoma (GBM, grade IV).
Humans Diagnosis, Differential Glioblastoma Neoplasm Staging Tumor Burden Male Machine Learning Glioma Female Support Vector Machine Adult Magnetic Resonance Imaging Brain Neoplasms
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Deep learning for fully automated tumor segmentation and extraction of magnetic resonance radiomics features in cervical cancer.

European radiology Nov 11, 2019
OBJECTIVE: To develop and evaluate the performance of U-Net for fully automated localization and segmentation of cervical tumors in magnetic resonance (MR) images and the robustness of extracting apparent diffusion coefficient (ADC) radiomics feature...
Female Diffusion Magnetic Resonance Imaging Carcinoma, Squamous Cell Reproducibility of Results Aged Humans Retrospective Studies Aged, 80 and over Middle Aged Image Processing, Computer-Assisted Young Adult Deep Learning Carcinoma Adult Tumor Burden Uterine Cervical Neoplasms
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Utilizing Machine Learning for Pre- and Postoperative Assessment of Patients Undergoing Resection for BCLC-0, A and B Hepatocellular Carcinoma: Implications for Resection Beyond the BCLC Guidelines.

Annals of surgical oncology Nov 6, 2019
BACKGROUND: There is an ongoing debate about expanding the resection criteria for hepatocellular carcinoma (HCC) beyond the Barcelona Clinic Liver Cancer (BCLC) guidelines. We sought to determine the factors that held the most prognostic weight in th...
Male Middle Aged Postoperative Complications Liver Neoplasms Neoplasm Staging Tumor Burden Practice Guidelines as Topic Carcinoma, Hepatocellular Follow-Up Studies Female Aged Survival Rate Biomarkers, Tumor Humans Machine Learning Retrospective Studies Hepatectomy Preoperative Care
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Computer-assisted assessment of colonic polyp histopathology using probe-based confocal laser endomicroscopy.

International journal of colorectal disease Nov 6, 2019
INTRODUCTION: Probe-based confocal laser endomicroscopy (pCLE) is a promising modality for classifying polyp histology in vivo, but decision making in real-time is hampered by high-magnification targeting and by the learning curve for image interpret...
Colonic Polyps Image Interpretation, Computer-Assisted Observer Variation Middle Aged Colonoscopy Diagnosis, Computer-Assisted Clinical Competence Feasibility Studies Colonic Neoplasms Tumor Burden Microscopy, Confocal Female Predictive Value of Tests Humans Reproducibility of Results Machine Learning Aged Aged, 80 and over Male
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ASO Author Reflections: Resection for Hepatocellular Carcinoma Beyond the BCLC Guidelines-How Can Machine Learning Techniques Help?

Annals of surgical oncology Nov 4, 2019
Practice Guidelines as Topic Hepatectomy Machine Learning Liver Neoplasms Carcinoma, Hepatocellular Tumor Burden Humans
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Automatic segmentation of prostate MRI using convolutional neural networks: Investigating the impact of network architecture on the accuracy of volume measurement and MRI-ultrasound registration.

Medical image analysis Sep 11, 2019
Convolutional neural networks (CNNs) have recently led to significant advances in automatic segmentations of anatomical structures in medical images, and a wide variety of network architectures are now available to the research community. For applica...
Tumor Burden Pattern Recognition, Automated Ultrasonography Magnetic Resonance Imaging Humans Neural Networks, Computer Prostatic Neoplasms Male
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Personalized oncology with artificial intelligence: The case of temozolomide.

Artificial intelligence in medicine Aug 12, 2019
PURPOSE: Using artificial intelligence techniques, we compute optimal personalized protocols for temozolomide administration in a population of patients with variability.
Tumor Burden Brain Neoplasms Humans Maximum Tolerated Dose Artificial Intelligence Dose-Response Relationship, Drug Temozolomide Algorithms Bayes Theorem Computer Simulation Models, Biological
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