Center for Devices and Radiological Health

The FDA is developing guidance on the use of “real-world evidence” — health care information from atypical sources, including electronic health records, billing databases, and product and disease registries — to assess the safety and effectiveness of drugs and devices.

The objective of this study was to develop anatomically correct whole body human models of an adult male (34 years old), an adult female (26 years old) and two children (an 11-year-old girl and a six-year-old boy) for the optimized evaluation of electromagnetic exposure. These four models are referred to as the Virtual Family. They are based on high resolution magnetic resonance (MR) images of healthy volunteers. More than 80 different tissue types were distinguished during the segmentation. To improve the accuracy and the effectiveness of the segmentation, a novel semi-automated tool was used to analyze and segment the data. All tissues and organs were reconstructed as three-dimensional (3D) unstructured triangulated surface objects, yielding high precision images of individual features of the body. This greatly enhances the meshing flexibility and the accuracy with respect to thin tissue layers and small organs in comparison with the traditional voxel-based representation of anatomical models. Conformal computational techniques were also applied. The techniques and tools developed in this study can be used to more effectively develop future models and further improve the accuracy of the models for various applications. For research purposes, the four models are provided for free to the scientific community.

the of the magnitude, i.e., intensity, of the field.) It is shown that Rayleigh statistics govern the fist-order behavior of the magnitude; and the autocorrelation of the resulting image speckle is obtained by the methodof Middleton. The corresponding power spectrum follows immediately by Fourier transformation. Theoretical and experimentally determined autocorrelation functions and power spectra derived from B-scans of a scattering phantom containing many scatterers per resolution cell are presented. These functions lead naturally to the definition of the average speckle spot or cell sue, and this inturn is comparable to the resolution cell. Each independent speckle servesas a degreeof freedom that determines the number of samples of tissue available over a target.As the speckle cell size decreases this number increases in a manner predictable from the physical parameters of the cell size. However, it is found that the speckle cellis broadened, the degrees of freedom diminished, when the object structureis correlated. This yields the possibilityof deducing information about the object structure from the second-order statistics of the speckle texture, in addition to that obtainable from the fiistorder statistics.

A method for calculating the electromagnetic scattering from and internal field distribution of arbitrarily shaped, inhomogeneous, dielectric bodies is presented. A volume integral equation is formulated and solved by using the method of moments. Tetrahedral volume elements are used to model a scattering body in which the electrical parameters are assumed constant in each tetrahedron. Special basis functions are defined within the tetrahedral volume elements to insure that the normal electric field satisfies the correct jump condition at interfaces between different dielectric media. An approximate Galerkin testing procedure is used, with special care taken to correctly treat the derivatives in the scalar potential term. Calculated internal field distributions and scattering cross sections of dielectric spheres and rods are compared to and found in agreement with other calculations. The accuracy of the fields calculated by using the tetrahedral cell method is found to be comparable to that of cubical cell methods presently used for modeling arbitrarily shaped bodies, while the modeling flexibility is considerably greater.

The U.S. National Council on Radiation Protection and Measurements and United Nations Scientific Committee on Effects of Atomic Radiation each conducted respective assessments of all radiation sources in the United States and worldwide. The goal of this article is to summarize and combine the results of these two publicly available surveys and to compare the results with historical information. In the United States in 2006, about 377 million diagnostic and interventional radiologic examinations and 18 million nuclear medicine examinations were performed. The United States accounts for about 12% of radiologic procedures and about one-half of nuclear medicine procedures performed worldwide. In the United States, the frequency of diagnostic radiologic examinations has increased almost 10-fold (1950-2006). The U.S. per-capita annual effective dose from medical procedures has increased about sixfold (0.5 mSv [1980] to 3.0 mSv [2006]). Worldwide estimates for 2000-2007 indicate that 3.6 billion medical procedures with ionizing radiation (3.1 billion diagnostic radiologic, 0.5 billion dental, and 37 million nuclear medicine examinations) are performed annually. Worldwide, the average annual per-capita effective dose from medicine (about 0.6 mSv of the total 3.0 mSv received from all sources) has approximately doubled in the past 10-15 years.

Providing therapies tailored to each patient is the vision of precision medicine, enabled by the increasing ability to capture extensive data about individual patients. In this position paper, we argue that the second enabling pillar towards this vision is the increasing power of computers and algorithms to learn, reason, and build the 'digital twin' of a patient. Computational models are boosting the capacity to draw diagnosis and prognosis, and future treatments will be tailored not only to current health status and data, but also to an accurate projection of the pathways to restore health by model predictions. The early steps of the digital twin in the area of cardiovascular medicine are reviewed in this article, together with a discussion of the challenges and opportunities ahead. We emphasize the synergies between mechanistic and statistical models in accelerating cardiovascular research and enabling the vision of precision medicine.

Because there are many potential risks in the MR environment and reports of adverse incidents involving patients, equipment and personnel, the need for a guidance document on MR safe practices emerged. Initially published in 2002, the ACR MR Safe Practices Guidelines established de facto industry standards for safe and responsible practices in clinical and research MR environments. As the MR industry changes the document is reviewed, modified and updated. The most recent version will reflect these changes.

This publication describes uniform definitions for cardiovascular and stroke outcomes developed by the Standardized Data Collection for Cardiovascular Trials Initiative and the U.S. Food and Drug Administration (FDA). The FDA established the Standardized Data Collection for Cardiovascular Trials Initiative in 2009 to simplify the design and conduct of clinical trials intended to support marketing applications. The writing committee recognizes that these definitions may be used in other types of clinical trials and clinical care processes where appropriate. Use of these definitions at the FDA has enhanced the ability to aggregate data within and across medical product development programs, conduct meta-analyses to evaluate cardiovascular safety, integrate data from multiple trials, and compare effectiveness of drugs and devices. Further study is needed to determine whether prospective data collection using these common definitions improves the design, conduct, and interpretability of the results of clinical trials.

Formulas for the potentials due to uniform and Linearly varying source distributions defined on simply shaped domains are systematically developed and presented. Domains considered are infinite planar strips, infinite cylinders of polygonal cross sections, planar surfaces with polygonal boundaries, and volumetric regions with polyhedral boundaries. The expressions obtained are compact in form and their application in the numerical solution of electromagnetics problems by the method of moments is illustrated.

A major challenge in cancer biology is to monitor and understand cancer metabolism in vivo with the goal of improved diagnosis and perhaps therapy. Because of the complexity of biochemical pathways, tracer methods are required for detecting specific enzyme-catalyzed reactions. Stable isotopes such as (13)C or (15)N with detection by nuclear magnetic resonance provide the necessary information about tissue biochemistry, but the crucial metabolites are present in low concentration and therefore are beyond the detection threshold of traditional magnetic resonance methods. A solution is to improve sensitivity by a factor of 10,000 or more by temporarily redistributing the populations of nuclear spins in a magnetic field, a process termed hyperpolarization. Although this effect is short-lived, hyperpolarized molecules can be generated in an aqueous solution and infused in vivo where metabolism generates products that can be imaged. This discovery lifts the primary constraint on magnetic resonance imaging for monitoring metabolism-poor sensitivity-while preserving the advantage of biochemical information. The purpose of this report was to briefly summarize the known abnormalities in cancer metabolism, the value and limitations of current imaging methods for metabolism, and the principles of hyperpolarization. Recent preclinical applications are described. Hyperpolarization technology is still in its infancy, and current polarizer equipment and methods are suboptimal. Nevertheless, there are no fundamental barriers to rapid translation of this exciting technology to clinical research and perhaps clinical care.

Abstract The FDA approved pembrolizumab on June 16, 2020, for the treatment of adult and pediatric patients with unresectable or metastatic tumor mutational burden–high [TMB-H; ≥10 mutations/megabase (mut/Mb)] solid tumors, as determined by an FDA-approved test, that have progressed following prior treatment and who have no satisfactory alternative treatment options. FDA granted the approval based on a clinically important overall response rate (29%; 95% confidence interval, 21–39) and duration of response (57% of responses lasting ≥ 12 months) in the subset of patients with TMB-H solid tumors (n = 102) spanning nine different tumor types enrolled in a multicenter single-arm trial (KEYNOTE-158). The efficacy of pembrolizumab was supported by the results of whole-exome sequencing (WES) analyses of TMB in additional patients enrolled across multiple pembrolizumab clinical trials, and a scientific understanding of the effects of PD-1 inhibition. Overall, the adverse event profile of pembrolizumab was similar to the adverse event profile observed in prior trials that supported the approval of pembrolizumab in other indications. This approval of pembrolizumab is the first time that the FDA has approved a cancer treatment for an indication based on TMB, and the fourth based on the presence of a biomarker rather than the primary site of origin.

ADVERTISEMENT RETURN TO ISSUEPREVReviewNEXTAnalyzing Nanomaterial Bioconjugates: A Review of Current and Emerging Purification and Characterization TechniquesKim E. Sapsford*†, Katherine M. Tyner‡, Benita J. Dair§, Jeffrey R. Deschamps∥, and Igor L. Medintz*∥View Author Information§ †Division of Biology, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, ‡Division of Drug Safety Research, Office of Testing and Research, Office of Pharmaceutical Science Center for Drug Evaluation and Research, and §Division of Chemistry and Materials Science, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland 20993, United States∥ Center for Bio/Molecular Science and Engineering, Code 6900, U.S. Naval Research Laboratory, 4555 Overlook Avenue, S.W. Washington, DC 20375, United StatesE-mail: [email protected] (K.E.S.); [email protected] (I.L.M.).Cite this: Anal. Chem. 2011, 83, 12, 4453–4488Publication Date (Web):May 5, 2011Publication History Published online5 May 2011Published inissue 15 June 2011https://doi.org/10.1021/ac200853aCopyright © This article not subject to U.S. Copyright. Published 2011 by the American Chemical SocietyRIGHTS & PERMISSIONSArticle Views9915Altmetric-Citations381LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit Read OnlinePDF (13 MB) Get e-AlertsSUBJECTS:Fluorescence,Metal nanoparticles,Nanoparticles,Peptides and proteins,Quantum dots Get e-Alerts

On December 19, 2014, the FDA approved olaparib capsules (Lynparza; AstraZeneca) for the treatment of patients with deleterious or suspected deleterious germline BRCA-mutated (gBRCAm) advanced ovarian cancer who have been treated with three or more prior lines of chemotherapy. The BRACAnalysis CDx (Myriad Genetic Laboratories, Inc.) was approved concurrently. An international multicenter, single-arm trial enrolled 137 patients with measurable gBRCAm-associated ovarian cancer treated with three or more prior lines of chemotherapy. Patients received olaparib at a dose of 400 mg by mouth twice daily until disease progression or unacceptable toxicity. The objective response rate (ORR) was 34% with median response duration of 7.9 months in this cohort. The most common adverse reactions (≥20%) in patients treated with olaparib were anemia, nausea, fatigue (including asthenia), vomiting, diarrhea, dysgeusia, dyspepsia, headache, decreased appetite, nasopharyngitis/pharyngitis/upper respiratory infection, cough, arthralgia/musculoskeletal pain, myalgia, back pain, dermatitis/rash, and abdominal pain/discomfort. Myelodysplatic syndrome and/or acute myeloid leukemia occurred in 2% of the patients enrolled on this trial.

Transducer design and phased array beam steering are developed for a volumetric ultrasound scanner that enables the 3-D visualization of dynamic structures in real time. The authors describe the design considerations and preliminary evaluation of a high-speed, online volumetric ultrasound imaging system that uses the principles of pulse-echo, phased array scanning with a 2-D array transducer. Several 2-D array designs are analyzed for resolution and main lobe-side lobe ratio by simulation using 2-D fast Fourier transform methods. Fabrication techniques are described for 2-D array transducer. Experimental measurements of pulse-echo point spread responses for 2-D arrays agree with the simulations. Measurements of pulse-echo sensitivity, bandwidth, and crosstalk are included.

A method for estimating structural properties of random media is described. The size, number density, and scattering strength of particles are estimated from an analysis of the radio frequency (rf) echo signal power spectrum. Simple correlation functions and the accurate scattering theory of Faran [J.J. Faran, J. Acoust. Soc. Am. 23, 405-418 (1951)], which includes the effects of shear waves, were used separately to model backscatter from spherical particles and thereby describe the structures of the medium. These methods were tested using both glass sphere-in-agar and polystyrene sphere-in-agar scattering media. With the appropriate correlation function, it was possible to measure glass sphere diameters with an accuracy of 20%. It was not possible to accurately estimate the size of polystyrene spheres with the simple spherical and Gaussian correlation models examined because of a significant shear wave contribution. Using the Faran scattering theory for spheres, however, the accuracy for estimating diameters was improved to 10% for both glass and polystyrene scattering media. It was possible to estimate the product of the average scattering particle number density and the average scattering strength per particle, but with lower accuracy than the size estimates. The dependence of the measurement accuracy on the inclusion of shear waves, the wavelength of sound, and medium attenuation are considered, and the implications for describing the structure of biological soft tissues are discussed.

Deep ultraviolet (UV) irradiation is shown to modify organosilane self-assembled monolayer (SAM) films by a photocleavage mechanism, which renders the surface amenable to further SAM modification. Patterned UV exposure creates alternating regions of intact SAM film and hydrophilic, reactive sites. The exposed regions can undergo a second chemisorption reaction to produce an assembly of SAMs in the same molecular plane with similar substrate attachment chemistry. The UV-patterned films are used as a template for selective buildup of fluorophores, metals, and biological cells.

Computer simulation is a convenient and frequently used tool in the study of x-ray mammography, for the design of novel detector systems, the evaluation of dose deposition, x-ray technique optimization, and other applications. An important component in the simulation process is the accurate computer-generation of x-ray spectra. A computer model for the generation of x-ray spectra in the mammographic energy range from 18 kV to 40 kV has been developed. The proposed model requires no assumptions concerning the physics of x-ray production in an x-ray tube, but rather makes use of x-ray spectra recently measured experimentally in the laboratories of the Center for Devices and Radiological Health. Using x-ray spectra measured for molybdenum, rhodium, and tungsten anode x-ray tubes at 13 different kV's (18, 20, 22, ..., 42 kV), a spectral model using interpolating polynomials was developed. At each energy in the spectrum, the x-ray photon fluence was fit using 2, 3, or 4 term (depending on the energy) polynomials as a function of the applied tube voltage (kV). Using the polynomial fit coefficients determined at each 0.5 keV interval in the x-ray spectrum, accurate x-ray spectra can be generated for any arbitrary kV between 18 and 40 kV. Each anode material (Mo, Rh, W) uses a different set of polynomial coefficients. The molybdenum anode spectral model using interpolating polynomials is given the acronym MASMIP, and the rhodium and tungsten spectral models are called RASMIP and TASMIP, respectively. It is shown that the mean differences in photon fluence calculated over the energy channels and over the kV range from 20 to 40 kV were -0.073% (sigma = 1.58%) for MASMIP, -0.145% (sigma = 1.263%) for RASMIP, and 0.611% (sigma = 2.07%) for TASMIP. The polynomial coefficients for all three models are given in an Appendix. A short C subroutine which uses the polynomial coefficients and generates x-ray spectra based on the proposed model is available on the World Wide Web at http:/(/)www.aip.org/epaps/epaps.html.

C MRI might fill existing needs in current clinical research and practice, and complement existing metabolic imaging modalities. Financial sponsorship and integration of academia, industry, and government efforts will be important factors in translating the technology for clinical research in oncology. This white paper is intended to provide recommendations with this goal in mind.

Tremendous efforts have been made over the past few decades to discover novel cancer biomarkers for use in clinical practice. However, a striking discrepancy exists between the effort directed toward biomarker discovery and the number of markers that make it into clinical practice. One of the confounding issues in translating a novel discovery into clinical practice is that quite often the scientists working on biomarker discovery have limited knowledge of the analytical, diagnostic, and regulatory requirements for a clinical assay. This review provides an introduction to such considerations with the aim of generating more extensive discussion for study design, assay performance, and regulatory approval in the process of translating new proteomic biomarkers from discovery into cancer diagnostics. We first describe the analytical requirements for a robust clinical biomarker assay, including concepts of precision, trueness, specificity and analytical interference, and carryover. We next introduce the clinical considerations of diagnostic accuracy, receiver operating characteristic analysis, positive and negative predictive values, and clinical utility. We finish the review by describing components of the FDA approval process for protein-based biomarkers, including classification of biomarker assays as medical devices, analytical and clinical performance requirements, and the approval process workflow. While we recognize that the road from biomarker discovery, validation, and regulatory approval to the translation into the clinical setting could be long and difficult, the reward for patients, clinicians and scientists could be rather significant.

The area under the receiver operating characteristic curve is often used as a summary index of the diagnostic ability in evaluating biomarkers when the clinical outcome (truth) is binary. When the clinical outcome is right-censored survival time, the C index, motivated as an extension of area under the receiver operating characteristic curve, has been proposed by Harrell as a measure of concordance between a predictive biomarker and the right-censored survival outcome. In this work, we investigate methods for statistical comparison of two diagnostic or predictive systems, of which they could either be two biomarkers or two fixed algorithms, in terms of their C indices. We adopt a U-statistics-based C estimator that is asymptotically normal and develop a nonparametric analytical approach to estimate the variance of the C estimator and the covariance of two C estimators. A z-score test is then constructed to compare the two C indices. We validate our one-shot nonparametric method via simulation studies in terms of the type I error rate and power. We also compare our one-shot method with resampling methods including the jackknife and the bootstrap. Simulation results show that the proposed one-shot method provides almost unbiased variance estimations and has satisfactory type I error control and power. Finally, we illustrate the use of the proposed method with an example from the Framingham Heart Study.