Radiomics, The Future Role of Radiologists?

 

This idea was explored by Paul LeTour as he described a recent symposium held at the Radiological Society of North America 2014. “Radiomics, From Clinical Images to Omics” was the title of the symposium that explored the concept that in the future, radiologists won’t simply be interpreters of clinical imaging but instead will manage quantitative imaging and descriptive patient data about disease processes that could enable computer-aided decision support to improve diagnosis and prognosis.

Four speakers discussed this concept, and as an introduction likened radiomics to the role of molecular biology through the use of human genome data leading to new targeted therapies in oncology. The corollary of radiomics being that radiological images are not just pictures, but multitudes of discrete data, and that hundreds of quantitative features such as textural (tumor shape) and functional parameters (intensity variation within the tumor) could be extracted from each image. Through combination of these quantitative data with other genomic and patient parameters, increased accuracy and improved prediction might be possible. For example the combined result might predict a low likelihood of metastasis, thus sparing the patient multiple cycles of chemotherapy, or might indicate a high metastatic potential, suggesting more aggressive therapy.

Reference http://www.rsna.org/NewsDetail.aspx?id=14704&utm_source=Informz&utm_medium=E-Mail&utm_campaign=RSNA+Home+Page

Elucid Bioimaging Inc. is a specialty CRO and leader in quantitative image analysis services to characterize, optimize, and validate imaging biomarkers for drug development to improve the effectiveness and reduce the cost of clinical trials of novel therapies and develop improved tools for medical decisions and patient management.

A Novel Knowledge Framework for Discovery, Development, and Validation of Quantitative Imaging Biomarkers (QIB)

 

Quantitative Imaging Biomarkers are of interest to enable personalized medicine as well as for their potential to accelerate drug development, but their use is hampered by inadequate and inconsistent methodology. A powerful informatics framework developed by Elucid Bioimaging enables prospective as well as retrospective use cases for development, optimization, validation, and discovery of quantitative imaging phenotype data. (http://elucidbio.com/blog/)

A Novel Knowledge Framework for Discovery, Development, and Validation of Quantitative Imaging Biomarkers (QIB)

Quantitative Imaging Biomarkers are of interest to enable personalized medicine as well as for their potential to accelerate drug development, but their use is hampered by inadequate and inconsistent methodology which hampers careful characterization. Before QIB can be recommended in practice guidelines or used in clinical trials, the biomarker must be represented consistently across imaging devices and clinical centers. This representation must support advanced statistical techniques, controlled vocabularies, and service architecture for processing potentially large numbers of images as well as other associated clinical and genomic data. Elucid has developed a sophisticated semantic infrastructure as part of its Computer-Aided-Phenotyping platform which is available to clients through customized system development services. A subset of capability is also available in an open-source version through Elucid’s QI-Bench program used to support collaborative projects. Image data can be stored, queried, and retrieved via SPARQL-endpoints to allow both prospective development and validation as well as retrospective discovery of QIBs of interest. Such QIBs can then be used in the conduct of clinical trials, in translational medicine research, and in the clinical care of patients. (http://www.ncbi.nlm.nih.gov/pubmed/23546775)

The Science of Quantitative Imaging Biomarkers

 

The development and implementation of quantitative imaging biomarkers (QIB) has been hindered by inconsistent and frequently incorrect use of terminology used to describe these biomarkers.   Kessler et al. (2014) recently published an article (http://www.ncbi.nlm.nih.gov/pubmed/24919826) , produced with sponsorship from the Radiological Society of North America (RSNA), to address the terminology and definitions of quantitative imaging biomarkers to be used in scientific studies and regulatory submissions. The Quantitative Imaging Biomarker Alliance(QIBA), organized by RSNA, emphasized “building measuring devices rather than imaging devices”, that is extracting data from images to provide numerical data to the clinicians and regulatory agencies. Terms defined and reviewed in the paper were drawn from national or international standards bodies instead of defining new terms. Quantitative imaging biomarkers are clearly defined, and their “context of use, acquisition parameters, measurement methodology and quantification of their variability and error” are described. This paper provides a firm foundation for use of QIB by clearly defining the attributes of the imaging biomarker to be measured, and by providing a framework for determining its variability and error.

 

Elucid Bioimaging Inc. is a specialty CRO and leader in quantitative image analysis services to characterize, optimize, and validate imaging biomarkers for drug development to improve the effectiveness and reduce the cost of clinical trials of novel therapies and develop improved tools for medical decisions and patient management.

Elucid Bioimaging, Inc. Announces Opening of Enrollment in the Q-CAMP study at LSU Medical Center in New Orleans, LA – August 8, 2014

Elucid Bioimaging, Inc., a specialty Contract Research Organization (CRO) and leader in quantitative image analysis services, is pleased to report the opening of enrollment in the Q-CAMP, Quantitative CArdiovascular Magnetic Resonance Imaging and Profiling of Atherosclerotic Lesions, Study (Clinicaltrial.gov study number NCT02143102) being conducted at the Interim Louisiana State University Hospital in New Orleans, LA.

The 150 patient, observational study will use MRI and Elucid’s vascuCAP™ software analysis program to evaluate the extent, as well as, the structure, composition, and functional aspects of atherosclerotic plaques in human carotid and femoral arteries in patients scheduled to undergo an endarterectomy of the aforementioned vascular beds as part of their routine clinical care. In the first 75 patients, the endarterectomy specimens removed at surgery will allow a direct comparison between the MRI information obtained prior to the surgery and the histopathological analyses of the arterial specimens in order to further develop the vascuCAP™ analysis program. The vascuCAP™ data from the second group of patients will be compared in a blinded fashion with the histology to assess performance of plaque profiling and to build a pilot prediction model for risk scoring.

Elucid Bioimaging Inc. is a specialty CRO and leader in quantitative image analysis services to characterize, optimize, and validate imaging biomarkers for drug development to improve the effectiveness and reduce the cost of clinical trials of novel therapies and develop improved tools for medical decisions and patient management.