Applications and limitations of radiomics

Physics in Medicine and Biology, Journal Year: 2016, Volume and Issue: 61(13), P. R150 - R166

Published: June 8, 2016

Radiomics is an emerging field in quantitative imaging that uses advanced features to objectively and quantitatively describe tumour phenotypes. Radiomic have recently drawn considerable interest due its potential predictive power for treatment outcomes cancer genetics, which may important applications personalized medicine. In this technical review, we challenges of the radiomic field. We will review application areas issues, as well proper practices designs studies.

Language: Английский

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LIFEx: A Freeware for Radiomic Feature Calculation in Multimodality Imaging to Accelerate Advances in the Characterization of Tumor Heterogeneity

Cancer Research, Journal Year: 2018, Volume and Issue: 78(16), P. 4786 - 4789

Published: June 29, 2018

Textural and shape analysis is gaining considerable interest in medical imaging, particularly to identify parameters characterizing tumor heterogeneity feed radiomic models. Here, we present a free, multiplatform, easy-to-use freeware called LIFEx, which enables the calculation of conventional, histogram-based, textural, features from PET, SPECT, MR, CT, US images, or any combination imaging modalities. The application does not require programming skills was developed for professionals. goal that independent multicenter evidence usefulness limitations characterization subsequent patient management can be gathered. Many options are offered interactive textural index increasing reproducibility among centers. software already benefits large user community (more than 800 registered users), interactions within part development strategy.Significance: This study presents user-friendly, multi-platform extract Cancer Res; 78(16); 4786-9. ©2018 AACR.

Language: Английский

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Intratumor heterogeneity in localized lung adenocarcinomas delineated by multiregion sequencing

Science, Journal Year: 2014, Volume and Issue: 346(6206), P. 256 - 259

Published: Oct. 9, 2014

Cancers are composed of populations cells with distinct molecular and phenotypic features, a phenomenon termed intratumor heterogeneity (ITH). ITH in lung cancers has not been well studied. We applied multiregion whole-exome sequencing (WES) on 11 localized adenocarcinomas. All tumors showed clear evidence ITH. On average, 76% all mutations 20 out 21 known cancer gene were identified regions individual tumors, which suggested that single-region may be adequate to identify the majority With median follow-up months after surgery, three patients have relapsed, had significantly larger fractions subclonal their primary than without relapse. These data indicate mutation fraction associated increased likelihood postsurgical relapse

Language: Английский

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Machine Learning methods for Quantitative Radiomic Biomarkers

Scientific Reports, Journal Year: 2015, Volume and Issue: 5(1)

Published: Aug. 17, 2015

Radiomics extracts and mines large number of medical imaging features quantifying tumor phenotypic characteristics. Highly accurate reliable machine-learning approaches can drive the success radiomic applications in clinical care. In this study, fourteen feature selection methods twelve classification were examined terms their performance stability for predicting overall survival. A total 440 extracted from pre-treatment computed tomography (CT) images 464 lung cancer patients. To ensure unbiased evaluation different methods, publicly available implementations along with reported parameter configurations used. Furthermore, we used two independent cohorts training (n = 310 patients) validation 154 patients). We identified that Wilcoxon test based method WLCX (stability 0.84 ± 0.05, AUC 0.65 0.02) a random forest RF (RSD 3.52%, 0.66 0.03) had highest prognostic high against data perturbation. Our variability analysis indicated choice is most dominant source variation (34.21% variance). Identification optimal crucial step towards stable clinically relevant biomarkers, providing non-invasive way monitoring tumor-phenotypic characteristics practice.

Language: Английский

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Review of cancer from perspective of molecular

Journal of Cancer Research and Practice, Journal Year: 2017, Volume and Issue: 4(4), P. 127 - 129

Published: July 10, 2017

Cancer in the broader sense refers to more than 277 different types of cancer disease. Scientists have identified stage cancers, indicating that several gene mutations are involved pathogenesis. These lead abnormal cell proliferation. Genetic disorders caused by heritance or inheritance factors a pivotal role increase growth. With assistance technological advances bioinformatics and molecular techniques, additional information has been obtained can be useful for early diagnosis proper treatment. The effects drugs on patients with predict even manage some aspects side effects. In recent years, carcinogenesis mechanisms detected genetic studies. results these studies led an improved understanding formation. this study, our aim was review cancer.

Language: Английский

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Targeted therapy for hepatocellular carcinoma

Signal Transduction and Targeted Therapy, Journal Year: 2020, Volume and Issue: 5(1)

Published: Aug. 11, 2020

Abstract The last 3 years have seen the emergence of promising targeted therapies for treatment hepatocellular carcinoma (HCC). Sorafenib has been mainstay a decade and newer modalities were ineffective did not confer any increased therapeutic benefit until introduction lenvatinib which was approved based on its non-inferiority to sorafenib. subsequent success regorafenib in HCC patients who progress sorafenib heralded new era second-line quickly followed by ramucirumab, cabozantinib, most influential, immune checkpoint inhibitors (ICIs). Over same period combination therapies, including anti-angiogenesis agents with ICIs, dual ICIs conjunction surgery or other loco-regional extensively investigated shown promise provided basis exciting clinical trials. Work continues develop additional novel could potentially augment presently available options understand underlying mechanisms responsible drug resistance, goal improving survival HCC.

Language: Английский

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The urgent need to recover MHC class I in cancers for effective immunotherapy

Current Opinion in Immunology, Journal Year: 2016, Volume and Issue: 39, P. 44 - 51

Published: Jan. 18, 2016

Immune escape strategies aimed to avoid T-cell recognition, including the loss of tumor MHC class I expression, are commonly found in malignant cells. Tumor immune has proven have a negative effect on clinical outcome cancer immunotherapy, treatment with antibodies blocking checkpoint molecules. Hence, there is an urgent need develop novel approaches overcome evasion. antigen presentation often affected human cancers and capacity induce upregulation cell surface expression critical step induction rejection. This review focuses characterization rejection, escape, dormant profiles tumors its microenvironment special emphasis expression. We also discuss possible recover cells harboring reversible/‘soft’ or irreversible/‘hard’ genetic lesions. Such recovery might well synergize complementary forms immunotherapy.

Language: Английский

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Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer

Scientific Reports, Journal Year: 2017, Volume and Issue: 7(1)

Published: Aug. 25, 2017

Quantitative extraction of high-dimensional mineable data from medical images is a process known as radiomics. Radiomics foreseen an essential prognostic tool for cancer risk assessment and the quantification intratumoural heterogeneity. In this work, 1615 radiomic features (quantifying tumour image intensity, shape, texture) extracted pre-treatment FDG-PET CT 300 patients four different cohorts were analyzed locoregional recurrences (LR) distant metastases (DM) in head-and-neck cancer. Prediction models combining clinical variables constructed via random forests imbalance-adjustment strategies using two cohorts. Independent validation prediction performance was carried out on other (LR: AUC = 0.69 CI 0.67; DM: 0.86 0.88). Furthermore, results obtained Kaplan-Meier analysis demonstrated potential radiomics assessing specific outcomes multiple stratification groups. This could have important impact, notably by allowing better personalization chemo-radiation treatments

Language: Английский

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EGFR mutation detection in ctDNA from NSCLC patient plasma: A cross-platform comparison of leading technologies to support the clinical development of AZD9291

Lung Cancer, Journal Year: 2015, Volume and Issue: 90(3), P. 509 - 515

Published: Oct. 18, 2015

ObjectivesTo assess the ability of different technology platforms to detect epidermal growth factor receptor (EGFR) mutations, including T790M, from circulating tumor DNA (ctDNA) in advanced non-small cell lung cancer (NSCLC) patients.Materials and methodsA comparison multiple for detecting EGFR mutations plasma ctDNA was undertaken. Plasma samples were collected patients entering ongoing AURA trial (NCT01802632), investigating safety, tolerability, efficacy AZD9291 with EGFR-sensitizing mutation-positive NSCLC. prior dosing but following clinical progression on a previous EGFR-tyrosine kinase inhibitor (TKI). Extracted analyzed using two non-digital (cobas® Mutation Test therascreen™ amplification refractory mutation system assay) digital (Droplet Digital™ PCR BEAMing [dPCR]).ResultsPreliminary assessment (38 samples) conducted all four platforms. For EGFR-TKI-sensitizing high sensitivity (78–100%) specificity (93–100%) observed tissue as non-reference standard. T790M mutation, outperformed Subsequent 72 additional baseline cobas® dPCR. The demonstrated (82–87%) (97%) mutations. 73% 67%, respectively, Test, 81% 58%, Concordance between >90%, showing that are capable sensitive specific detection NSCLC patient plasma.ConclusionThe dPCR demonstrate detection. Genomic heterogeneity T790M-mediated resistance may explain reduced plasma-based versus tissue. These data support use both development program.

Language: Английский

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SciClone: Inferring Clonal Architecture and Tracking the Spatial and Temporal Patterns of Tumor Evolution

PLoS Computational Biology, Journal Year: 2014, Volume and Issue: 10(8), P. e1003665 - e1003665

Published: Aug. 7, 2014

The sensitivity of massively-parallel sequencing has confirmed that most cancers are oligoclonal, with subpopulations neoplastic cells harboring distinct mutations. A fine resolution view this clonal architecture provides insight into tumor heterogeneity, evolution, and treatment response, all which may have clinical implications. Single analysis already contributes to understanding these phenomena. However, cryptic subclones frequently revealed by additional patient samples (e.g., collected at relapse or following treatment), indicating accurately characterizing a requires analyzing multiple from the same patient. To address need, we present SciClone, computational method identifies number genetic composition variant allele frequencies somatic We use it detect in acute myeloid leukemia breast cancer that, though disease onset, not evident single primary sample. By doing so, can track evolution identify spatial origins resisting therapy.

Language: Английский

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