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https://www.readbyqxmd.com/read/28820287/comparison-of-pet-and-ct-radiomics-for-prediction-of-local-tumor-control-in-head-and-neck-squamous-cell-carcinoma
#1
Marta Bogowicz, Oliver Riesterer, Luisa Sabrina Stark, Gabriela Studer, Jan Unkelbach, Matthias Guckenberger, Stephanie Tanadini-Lang
PURPOSE: An association between radiomic features extracted from CT and local tumor control in the head and neck squamous cell carcinoma (HNSCC) has been shown. This study investigated the value of pretreatment functional imaging (18F-FDG PET) radiomics for modeling of local tumor control. MATERIAL AND METHODS: Data from HNSCC patients (n = 121) treated with definitive radiochemotherapy were used for model training. In total, 569 radiomic features were extracted from both contrast-enhanced CT and 18F-FDG PET images in the primary tumor region...
August 18, 2017: Acta Oncologica
https://www.readbyqxmd.com/read/28819565/genomic-and-immune-heterogeneity-are-associated-with-differential-responses-to-therapy-in-melanoma
#2
Alexandre Reuben, Christine N Spencer, Peter A Prieto, Vancheswaran Gopalakrishnan, Sangeetha M Reddy, John P Miller, Xizeng Mao, Mariana Petaccia De Macedo, Jiong Chen, Xingzhi Song, Hong Jiang, Pei-Ling Chen, Hannah C Beird, Haven R Garber, Whijae Roh, Khalida Wani, Eveline Chen, Cara Haymaker, Marie-Andrée Forget, Latasha D Little, Curtis Gumbs, Rebecca L Thornton, Courtney W Hudgens, Wei-Shen Chen, Jacob Austin-Breneman, Robert Szczepaniak Sloane, Luigi Nezi, Alexandria P Cogdill, Chantale Bernatchez, Jason Roszik, Patrick Hwu, Scott E Woodman, Lynda Chin, Hussein Tawbi, Michael A Davies, Jeffrey E Gershenwald, Rodabe N Amaria, Isabella C Glitza, Adi Diab, Sapna P Patel, Jianhua Hu, Jeffrey E Lee, Elizabeth A Grimm, Michael T Tetzlaff, Alexander J Lazar, Ignacio I Wistuba, Karen Clise-Dwyer, Brett W Carter, Jianhua Zhang, P Andrew Futreal, Padmanee Sharma, James P Allison, Zachary A Cooper, Jennifer A Wargo
Appreciation for genomic and immune heterogeneity in cancer has grown though the relationship of these factors to treatment response has not been thoroughly elucidated. To better understand this, we studied a large cohort of melanoma patients treated with targeted therapy or immune checkpoint blockade (n = 60). Heterogeneity in therapeutic responses via radiologic assessment was observed in the majority of patients. Synchronous melanoma metastases were analyzed via deep genomic and immune profiling, and revealed substantial genomic and immune heterogeneity in all patients studied, with considerable diversity in T cell frequency, and few shared T cell clones (<8% on average) across the cohort...
2017: NPJ Genomic Medicine
https://www.readbyqxmd.com/read/28818991/immune-modulation-therapy-and-imaging-workshop-report
#3
Anthony F Shields, Paula Jacobs, Mario Sznol, Michael M Graham, Ronald Germain, Lawrence Lum, Elaine Jaffee, Elisabeth G E de Vries, Sridhar Nimmagadda, Annick D Van den Abbeele, David Leung, Anna M Wu, Elad Sharon, Lalitha K Shankar
A workshop at the National Cancer Institute May 2, 2016 considered the current state of imaging in assessment of immunotherapy. Immunotherapy has shown some remarkable and prolonged responses in the treatment of tumors. However, responses are variable and frequently delayed, complicating the evaluation of new immunotherapy agents and customizing treatment for individual patients. Early anatomic imaging may show that a tumor has increased in size, but this could represent pseudoprogression. Based on imaging, clinicians must decide if they should stop, pause, or continue treatment...
August 17, 2017: Journal of Nuclear Medicine: Official Publication, Society of Nuclear Medicine
https://www.readbyqxmd.com/read/28816643/pharmacometabolomics-informs-quantitative-radiomics-for-glioblastoma-diagnostic-innovation
#4
Theodora Katsila, Minos-Timotheos Matsoukas, George P Patrinos, Dimitrios Kardamakis
Applications of omics systems biology technologies have enormous promise for radiology and diagnostics in surgical fields. In this context, the emerging fields of radiomics (a systems scale approach to radiology using a host of technologies, including omics) and pharmacometabolomics (use of metabolomics for patient and disease stratification and guiding precision medicine) offer much synergy for diagnostic innovation in surgery, particularly in neurosurgery. This synthesis of omics fields and applications is timely because diagnostic accuracy in central nervous system tumors still challenges decision-making...
August 2017: Omics: a Journal of Integrative Biology
https://www.readbyqxmd.com/read/28815452/-18-f-fdg-pet-radiomics-approaches-comparing-and-clustering-features-in-cervical-cancer
#5
Tetsuya Tsujikawa, Tasmiah Rahman, Makoto Yamamoto, Shizuka Yamada, Hideaki Tsuyoshi, Yasushi Kiyono, Hirohiko Kimura, Yoshio Yoshida, Hidehiko Okazawa
OBJECTIVES: The aims of our study were to find the textural features on (18)F-FDG PET/CT which reflect the different histological architectures between cervical cancer subtypes and to make a visual assessment of the association between (18)F-FDG PET textural features in cervical cancer. METHODS: Eighty-three cervical cancer patients [62 squamous cell carcinomas (SCCs) and 21 non-SCCs (NSCCs)] who had undergone pretreatment (18)F-FDG PET/CT were enrolled. A texture analysis was performed on PET/CT images, from which 18 PET radiomics features were extracted including first-order features such as standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG), second- and high-order textural features using SUV histogram, normalized gray-level co-occurrence matrix (NGLCM), and neighborhood gray-tone difference matrix, respectively...
August 16, 2017: Annals of Nuclear Medicine
https://www.readbyqxmd.com/read/28815113/towards-generation-management-and-exploration-of-combined-radiomics-and-pathomics-datasets-for-cancer-research
#6
Joel Saltz, Jonas Almeida, Yi Gao, Ashish Sharma, Erich Bremer, Tammy DiPrima, Mary Saltz, Jayashree Kalpathy-Cramer, Tahsin Kurc
Cancer is a complex multifactorial disease state and the ability to anticipate and steer treatment results will require information synthesis across multiple scales from the host to the molecular level. Radiomics and Pathomics, where image features are extracted from routine diagnostic Radiology and Pathology studies, are also evolving as valuable diagnostic and prognostic indicators in cancer. This information explosion provides new opportunities for integrated, multi-scale investigation of cancer, but also mandates a need to build systematic and integrated approaches to manage, query and mine combined Radiomics and Pathomics data...
2017: AMIA Summits on Translational Science Proceedings
https://www.readbyqxmd.com/read/28807534/computed-tomography-radiomics-predicts-hpv-status-and-local-tumor-control-after-definitive-radiochemotherapy-in-head-and-neck-squamous-cell-carcinoma
#7
Marta Bogowicz, Oliver Riesterer, Kristian Ikenberg, Sonja Stieb, Holger Moch, Gabriela Studer, Matthias Guckenberger, Stephanie Tanadini-Lang
PURPOSE: This study aimed to predict local tumor control (LC) after radiochemotherapy of head and neck squamous cell carcinoma (HNSCC) and human papillomavirus (HPV) status using computed tomography (CT) radiomics. METHODS AND MATERIALS: HNSCC patients treated with definitive radiochemotherapy were included in the retrospective study approved by the local ethical commission (93 and 56 patients in the training and validation cohorts, respectively). Three hundred seventeen CT radiomic features, including those based on shape, intensity, texture, and wavelet transform, were calculated in the primary tumor region...
June 15, 2017: International Journal of Radiation Oncology, Biology, Physics
https://www.readbyqxmd.com/read/28801575/limits-of-radiomic-based-entropy-as-a-surrogate-of-tumor-heterogeneity-roi-area-acquisition-protocol-and-tissue-site-exert-substantial-influence
#8
Laurent Dercle, Samy Ammari, Mathilde Bateson, Paul Blanc Durand, Eva Haspinger, Christophe Massard, Cyril Jaudet, Andrea Varga, Eric Deutsch, Jean-Charles Soria, Charles Ferté
Entropy is a promising quantitative imaging biomarker for characterizing cancer imaging phenotype. Entropy has been associated with tumor gene expression, tumor metabolism, tumor stage, patient prognosis, and treatment response. Our hypothesis states that tumor-specific biomarkers such as entropy should be correlated between synchronous metastases. Therefore, a significant proportion of the variance of entropy should be attributed to the malignant process. We analyzed 112 patients with matched/paired synchronous metastases (SM#1 and SM#2) prospectively enrolled in the MOSCATO-01 clinical trial...
August 11, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28797700/4dct-imaging-to-assess-radiomics-feature-stability-an-investigation-for-thoracic-cancers
#9
Ruben T H M Larue, Lien Van De Voorde, Janna E van Timmeren, Ralph T H Leijenaar, Maaike Berbée, Meindert N Sosef, Wendy M J Schreurs, Wouter van Elmpt, Philippe Lambin
BACKGROUND AND PURPOSE: Quantitative tissue characteristics derived from medical images, also called radiomics, contain valuable prognostic information in several tumour-sites. The large number of features available increases the risk of overfitting. Typically test-retest CT-scans are used to reduce dimensionality and select robust features. However, these scans are not always available. We propose to use different phases of respiratory-correlated 4D CT-scans (4DCT) as alternative. MATERIALS AND METHODS: In test-retest CT-scans of 26 non-small cell lung cancer (NSCLC) patients and 4DCT-scans (8 breathing phases) of 20 NSCLC and 20 oesophageal cancer patients, 1045 radiomics features of the primary tumours were calculated...
August 7, 2017: Radiotherapy and Oncology: Journal of the European Society for Therapeutic Radiology and Oncology
https://www.readbyqxmd.com/read/28755054/mri-features-can-predict-egfr-expression-in-lower-grade-gliomas-a-voxel-based-radiomic-analysis
#10
Yiming Li, Xing Liu, Kaibin Xu, Zenghui Qian, Kai Wang, Xing Fan, Shaowu Li, Yinyan Wang, Tao Jiang
OBJECTIVE: To identify the magnetic resonance imaging (MRI) features associated with epidermal growth factor (EGFR) expression level in lower grade gliomas using radiomic analysis. METHODS: 270 lower grade glioma patients with known EGFR expression status were randomly assigned into training (n=200) and validation (n=70) sets, and were subjected to feature extraction. Using a logistic regression model, a signature of MRI features was identified to be predictive of the EGFR expression level in lower grade gliomas in the training set, and the accuracy of prediction was assessed in the validation set...
July 28, 2017: European Radiology
https://www.readbyqxmd.com/read/28731408/defining-the-biological-basis-of-radiomic-phenotypes-in-lung-cancer
#11
Patrick Grossmann, Olya Stringfield, Nehme El-Hachem, Marilyn M Bui, Emmanuel Rios Velazquez, Chintan Parmar, Ralph Th Leijenaar, Benjamin Haibe-Kains, Philippe Lambin, Robert Gillies, Hugo Jwl Aerts
Medical imaging can visualize characteristics of human cancer noninvasively. Radiomics is an emerging field that translates these medical images into quantitative data to enable phenotypic profiling of tumors. While radiomics has been associated with several clinical endpoints, the complex relationships of radiomics, clinical factors, and tumor biology are largely unknown. To this end, we analyzed two independent cohorts of respectively 262 North American and 89 European patients with lung cancer, and consistently identified previously undescribed associations between radiomic imaging features, molecular pathways, and clinical factors...
July 21, 2017: ELife
https://www.readbyqxmd.com/read/28722083/-a-perception-of-the-development-trend-of-radiological-t-staging-in-gastric-cancer-through-uicc-ajcc-8-th-edition
#12
Lei Tang
More and more emphases were put on pre-therapy staging following the promotion of multidisciplinary team(MDT) collaboration and individualized medicine in gastric cancer. However, the accuracy of traditional radiology staging system which applies mechanically pathological staging is not satisfactory during clinical practice, therefore, the objectivity of treatment decisions is affected. Under such conditions, the newly introduced staging system from Union for International Cancer Control/American Joint Committee on Cancer(UICC/AJCC)(8(th) edition) divided out an independent cTNM system for the first time, and summarized the application range, operation specification and staging criteria...
July 25, 2017: Zhonghua Wei Chang Wai Ke za Zhi, Chinese Journal of Gastrointestinal Surgery
https://www.readbyqxmd.com/read/28717412/diffusion-magnetic-resonance-imaging-a-molecular-imaging-tool-caught-between-hope-hype-and-the-real-world-of-personalized-oncology
#13
REVIEW
Abhishek Mahajan, Sneha S Deshpande, Meenakshi H Thakur
"Personalized oncology" is a multi-disciplinary science, which requires inputs from various streams for optimal patient management. Humongous progress in the treatment modalities available and the increasing need to provide functional information in addition to the morphological data; has led to leaping progress in the field of imaging. Magnetic resonance imaging has undergone tremendous progress with various newer MR techniques providing vital functional information and is becoming the cornerstone of "radiomics/radiogenomics"...
June 28, 2017: World Journal of Radiology
https://www.readbyqxmd.com/read/28712700/radiomic-analysis-of-dce-mri-for-prediction-of-response-to-neoadjuvant-chemotherapy-in-breast-cancer-patients
#14
Ming Fan, Guolin Wu, Hu Cheng, Juan Zhang, Guoliang Shao, Lihua Li
OBJECTIVES: To enhance the accurate prediction of the response to neoadjuvant chemotherapy (NAC) in breast cancer patients by using a quantitative analysis of dynamic enhancement magnetic resonance imaging (DCE-MRI). MATERIALS AND METHODS: A dataset of 57 cancer patients with breast DCE-MR images acquired before NAC was used. Among them, 47 patients were Responders, and 10 patients were non-Responders based on the RECIST criteria. The breast regions were segmented on the MR images, and a total of 158 radiomic features were computed to represent the morphologic, dynamic, and the texture of the tumors as well as the background parenchymal features...
June 28, 2017: European Journal of Radiology
https://www.readbyqxmd.com/read/28711211/advanced-tissue-characterization-and-texture-analysis-using-dual-energy-computed-tomography-horizons-and-emerging-applications
#15
REVIEW
Reza Forghani, Ashok Srinivasan, Behzad Forghani
In the last article of this issue, advanced analysis capabilities of DECT is reviewed, including spectral Hounsfield unit attenuation curves, virtual monochromatic images, material decomposition maps, tissue effective Z determination, and other advanced post-processing DECT tools, followed by different methods of analysis of the attenuation curves generated using DECT. The article concludes with exciting future horizons and potential applications, such as the use of the rich quantitative data in dual energy CT scans for texture or radiomic analysis and the use of machine learning methods for generation of prediction models using spectral data...
August 2017: Neuroimaging Clinics of North America
https://www.readbyqxmd.com/read/28710497/deep-learning-based-radiomics-dlr-and-its-usage-in-noninvasive-idh1-prediction-for-low-grade-glioma
#16
Zeju Li, Yuanyuan Wang, Jinhua Yu, Yi Guo, Wei Cao
Deep learning-based radiomics (DLR) was developed to extract deep information from multiple modalities of magnetic resonance (MR) images. The performance of DLR for predicting the mutation status of isocitrate dehydrogenase 1 (IDH1) was validated in a dataset of 151 patients with low-grade glioma. A modified convolutional neural network (CNN) structure with 6 convolutional layers and a fully connected layer with 4096 neurons was used to segment tumors. Instead of calculating image features from segmented images, as typically performed for normal radiomics approaches, image features were obtained by normalizing the information of the last convolutional layers of the CNN...
July 14, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28708732/investigating-the-robustness-neighborhood-gray-tone-difference-matrix-and-gray-level-co-occurrence-matrix-radiomic-features-on-clinical-computed-tomography-systems-using-anthropomorphic-phantoms-evidence-from-a-multivendor-study
#17
Usman Mahmood, Aditya P Apte, Joseph O Deasy, C Ross Schmidtlein, Amita Shukla-Dave
OBJECTIVE: The aim of this study was to determine if optimized imaging protocols across multiple computed tomography (CT) vendors could result in reproducible radiomic features calculated from an anthropomorphic phantom. METHODS: Materials with varying degrees of heterogeneity were placed throughout the lungs of the phantom. Twenty scans of the phantom were acquired on 3 CT manufacturers with chest CT protocols that had optimized protocol parameters. Scans were reconstructed using vendor-specific standards and lung kernels...
July 13, 2017: Journal of Computer Assisted Tomography
https://www.readbyqxmd.com/read/28693537/erratum-to-intratumoral-and-peritumoral-radiomics-for-the-pretreatment-prediction-of-pathological-complete-response-to-neoadjuvant-chemotherapy-based-on-breast-dce-mri
#18
Nathaniel M Braman, Maryam Etesami, Prateek Prasanna, Christina Dubchuk, Hannah Gilmore, Pallavi Tiwari, Donna Plecha, Anant Madabhushi
No abstract text is available yet for this article.
July 10, 2017: Breast Cancer Research: BCR
https://www.readbyqxmd.com/read/28689314/overview-of-deep-learning-in-medical-imaging
#19
REVIEW
Kenji Suzuki
The use of machine learning (ML) has been increasing rapidly in the medical imaging field, including computer-aided diagnosis (CAD), radiomics, and medical image analysis. Recently, an ML area called deep learning emerged in the computer vision field and became very popular in many fields. It started from an event in late 2012, when a deep-learning approach based on a convolutional neural network (CNN) won an overwhelming victory in the best-known worldwide computer vision competition, ImageNet Classification...
July 8, 2017: Radiological Physics and Technology
https://www.readbyqxmd.com/read/28688683/predictive-and-prognostic-value-of-ct-based-radiomics-signature-in-locally-advanced-head-and-neck-cancers-patients-treated-with-concurrent-chemoradiotherapy-or-bioradiotherapy-and-its-added-value-to-human-papillomavirus-status
#20
Dan Ou, Pierre Blanchard, Silvia Rosellini, Antonin Levy, France Nguyen, Ralph T H Leijenaar, Ingrid Garberis, Philippe Gorphe, François Bidault, Charles Ferté, Charlotte Robert, Odile Casiraghi, Jean-Yves Scoazec, Philippe Lambin, Stephane Temam, Eric Deutsch, Yungan Tao
OBJECTIVES: To explore prognostic and predictive value of radiomics in patients with locally advanced head and neck squamous cell carcinomas (LAHNSCC) treated with concurrent chemoradiotherapy (CRT) or bioradiotherapy (BRT). MATERIALS AND METHODS: Data of 120 patients (CRT vs. BRT matched 2:1) were retrospectively analyzed. A total of 544 radiomics features of the primary tumor were extracted from radiotherapy planning computed tomography scans. Cox proportional hazards models were used to examine the association between survival and radiomics features with false discovery rate correction...
August 2017: Oral Oncology
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