Buckler A.J.,BBMSC |
Ouellette M.,BBMSC |
Danagoulian J.,BBMSC |
Wernsing G.,BBMSC |
And 5 more authors.
Journal of Digital Imaging
A widening array of novel imaging biomarkers is being developed using ever more powerful clinical and preclinical imaging modalities. These biomarkers have demonstrated effectiveness in quantifying biological processes as they occur in vivo and in the early prediction of therapeutic outcomes. However, quantitative imaging biomarker data and knowledge are not standardized, representing a critical barrier to accumulating medical knowledge based on quantitative imaging data. We use an ontology to represent, integrate, and harmonize heterogeneous knowledge across the domain of imaging biomarkers. This advances the goal of developing applications to (1) improve precision and recall of storage and retrieval of quantitative imaging-related data using standardized terminology; (2) streamline the discovery and development of novel imaging biomarkers by normalizing knowledge across heterogeneous resources; (3) effectively annotate imaging experiments thus aiding comprehension, re-use, and reproducibility; and (4) provide validation frameworks through rigorous specification as a basis for testable hypotheses and compliance tests. We have developed the Quantitative Imaging Biomarker Ontology (QIBO), which currently consists of 488 terms spanning the following upper classes: experimental subject, biological intervention, imaging agent, imaging instrument, image post-processing algorithm, biological target, indicated biology, and biomarker application. We have demonstrated that QIBO can be used to annotate imaging experiments with standardized terms in the ontology and to generate hypotheses for novel imaging biomarker-disease associations. Our results established the utility of QIBO in enabling integrated analysis of quantitative imaging data. © 2013 Society for Imaging Informatics in Medicine. Source
Gimenez F.J.,Biomedical Informatics Training Program |
Wu Y.,University of Wisconsin - Madison |
Burnside E.S.,University of Wisconsin - Madison |
Rubin D.L.,Stanford University
AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
Mammography has been shown to improve outcomes of women with breast cancer, but it is subject to inter-reader variability. One well-documented source of such variability is in the content of mammography reports. The mammography report is of crucial importance, since it documents the radiologist's imaging observations, interpretation of those observations in terms of likelihood of malignancy, and suggested patient management. In this paper, we define an incompleteness score to measure how incomplete the information content is in the mammography report and provide an algorithm to calculate this metric. We then show that the incompleteness score can be used to predict errors in interpretation. This method has 82.6% accuracy at predicting errors in interpretation and can possibly reduce total diagnostic errors by up to 21.7%. Such a method can easily be modified to suit other domains that depend on quality reporting. Source
Newburger D.E.,Biomedical Informatics Training Program |
Kashef-Haghighi D.,Stanford University |
Weng Z.,Stanford University |
Salari R.,Stanford University |
And 9 more authors.
Cancer evolution involves cycles of genomic damage, epigenetic deregulation, and increased cellular proliferation that eventually culminate in the carcinoma phenotype. Early neoplasias, which are often found concurrently with carcinomas and are histologically distinguishable from normal breast tissue, are less advanced in phenotype than carcinomas and are thought to represent precursor stages. To elucidate their role in cancer evolution we performed comparative wholegenome sequencing of early neoplasias, matched normal tissue, and carcinomas from six patients, for a total of 31 samples. By using somatic mutations as lineage markers we built trees that relate the tissue samples within each patient. On the basis of these lineage trees we inferred the order, timing, and rates of genomic events. In four out of six cases, an early neoplasia and the carcinoma share a mutated common ancestor with recurring aneuploidies, and in all six cases evolution accelerated in the carcinoma lineage. Transition spectra of somatic mutations are stable and consistent across cases, suggesting that accumulation of somatic mutations is a result of increased ancestral cell division rather than specific mutational mechanisms. In contrast to highly advanced tumors that are the focus of much of the current cancer genome sequencing, neither the early neoplasia genomes nor the carcinomas are enriched with potentially functional somatic point mutations. Aneuploidies that occur in common ancestors of neoplastic and tumor cells are the earliest events that affect a large number of genes and may predispose breast tissue to eventual development of invasive carcinoma. © 2013, Published by Cold Spring Harbor Laboratory Press. Source
Bishara A.,Stanford University |
Liu Y.,Stanford University |
Weng Z.,Stanford University |
Kashef-Haghighi D.,Stanford University |
And 4 more authors.
Although an increasing amount of human genetic variation is being identified and recorded, determining variants within repeated sequences of the human genome remains a challenge. Most population and genome-wide association studies have therefore been unable to consider variation in these regions. Core to the problem is the lack of a sequencing technology that produces reads with sufficient length and accuracy to enable unique mapping. Here, we present a novel methodology of using read clouds, obtained by accurate short-read sequencing of DNA derived from long fragment libraries, to confidently align short reads within repeat regions and enable accurate variant discovery. Our novel algorithm, Random Field Aligner (RFA), captures the relationships among the short reads governed by the long read process via a Markov Random Field.We utilized a modified version of the Illumina TruSeq synthetic long-read protocol, which yielded shallow-sequenced read clouds. We test RFA through extensive simulations and apply it to discover variants on the NA12878 human sample, for which shallow TruSeq read cloud sequencing data are available, and on an invasive breast carcinoma genome that we sequenced using the same method. We demonstrate that RFA facilitates accurate recovery of variation in 155 Mb of the human genome, including 94% of 67 Mb of segmental duplication sequence and 96% of 11 Mb of transcribed sequence, that are currently hidden from short-read technologies. © 2015 Bishara et al. Source
Woo C.Y.,Stanford University |
Strandberg E.J.,Biomedical Informatics Training Program |
Schmiegelow M.D.,Research Unit 1 |
Schmiegelow M.D.,Stanford University |
And 4 more authors.
Annals of Internal Medicine
Background: Cardiac resynchronization therapy (CRT) reduces mortality and heart failure hospitalizations in patients with mild heart failure. Objective: To estimate the cost-effectiveness of adding CRT to an implantable cardioverter-defibrillator (CRT-D) compared with implantable cardioverter-defibrillator (ICD) alone among patients with left ventricular systolic dysfunction, prolonged intraventricular conduction, and mild heart failure. Design: Markov decision model. Data Sources: Clinical trials, clinical registries, claims data from Centers for Medicare & Medicaid Services, and Centers for Disease Control and Prevention life tables. Target Population: Patients aged 65 years or older with a left ventricular ejection fraction (LVEF) of 30% or less, QRS duration of 120 milliseconds or more, and New York Heart Association (NYHA) class I or II symptoms. Time Horizon: Lifetime. Perspective: Societal. Intervention: CRT-D or ICD alone. Outcome Measures: Life-years, quality-adjusted life-years (QALYs), costs, and incremental cost-effectiveness ratios (ICERs). Results of Base-Case Analysis: Use of CRT-D increased life expectancy (9.8 years versus 8.8 years), QALYs (8.6 years versus 7.6 years), and costs ($286 500 versus $228 600), yielding a cost per QALY gained of $61 700. Results of Sensitivity Analyses: The cost-effectiveness of CRT-D was most dependent on the degree of mortality reduction: When the risk ratio for death was 0.95, the ICER increased to $119 600 per QALY. More expensive CRT-D devices, shorter CRT-D battery life, and older age also made the costeffectiveness of CRT-D less favorable. Limitations: The estimated mortality reduction for CRT-D was largely based on a single trial. Data on patients with NYHA class I symptoms were limited. The cost-effectiveness of CRT-D in patients with NYHA class I symptoms remains uncertain. Conclusion: In patients with an LVEF of 30% or less, QRS duration of 120 milliseconds or more, and NYHA class II symptoms, CRT-D appears to be economically attractive relative to ICD alone when a reduction in mortality is expected. © 2015 American College of Physicians. Source