Inter-observer variability of expert-derived morphologic risk predictors in aortic dissection.

OBJECTIVES: Establishing the reproducibility of expert-derived measurements on CTA exams of aortic dissection is clinically important and paramount for ground-truth determination for machine learning. METHODS: Four independent observers retrospectively evaluated CTA exams of 72 patients with uncomplicated Stanford type B aortic dissection and assessed the reproducibility of a recently proposed combination of four morphologic risk predictors (maximum aortic diameter, false lumen circumferential angle, false lumen outflow, and intercostal arteries). For the first inter-observer variability assessment, 47 CTA scans from one aortic center were evaluated by expert-observer 1 in an unconstrained clinical assessment without a standardized workflow and compared to a composite of three expert-observers (observers 2-4) using a standardized workflow. A second inter-observer variability assessment on 30 out of the 47 CTA scans compared observers 3 and 4 with a constrained, standardized workflow. A third inter-observer variability assessment was done after specialized training and tested between observers 3 and 4 in an external population of 25 CTA scans. Inter-observer agreement was assessed with intraclass correlation coefficients (ICCs) and Bland-Altman plots. RESULTS: Pre-training ICCs of the four morphologic features ranged from 0.04 (-0.05 to 0.13) to 0.68 (0.49-0.81) between observer 1 and observers 2-4 and from 0.50 (0.32-0.69) to 0.89 (0.78-0.95) between observers 3 and 4. ICCs improved after training ranging from 0.69 (0.52-0.87) to 0.97 (0.94-0.99), and Bland-Altman analysis showed decreased bias and limits of agreement. CONCLUSIONS: Manual morphologic feature measurements on CTA images can be optimized resulting in improved inter-observer reliability. This is essential for robust ground-truth determination for machine learning models. KEY POINTS: • Clinical fashion manual measurements of aortic CTA imaging features showed poor inter-observer reproducibility. • A standardized workflow with standardized training resulted in substantial improvements with excellent inter-observer reproducibility. • Robust ground truth labels obtained manually with excellent inter-observer reproducibility are key to develop reliable machine learning models.

Ontologies in the New Computational Age of Radiology: RadLex for Semantics and Interoperability in Imaging Workflows.

From basic research to the bedside, precise terminology is key to advancing medicine and ensuring optimal and appropriate patient care. However, the wide spectrum of diseases and their manifestations superimposed on medical team-specific and discipline-specific communication patterns often impairs shared understanding and the shared use of common medical terminology. Common terms are currently used in medicine to ensure interoperability and facilitate integration of biomedical information for clinical practice and emerging scientific and educational applications alike, from database integration to supporting basic clinical operations such as billing. Such common terminologies can be provided in ontologies, which are formalized representations of knowledge in a particular domain. Ontologies unambiguously specify common concepts and describe the relationships between those concepts by using a form that is mathematically precise and accessible to humans and machines alike. RadLex® is a key RSNA initiative that provides a shared domain model, or ontology, of radiology to facilitate integration of information in radiology education, clinical care, and research. As the contributions of the computational components of common radiologic workflows continue to increase with the ongoing development of big data, artificial intelligence, and novel image analysis and visualization tools, the use of common terminologies is becoming increasingly important for supporting seamless computational resource integration across medicine. This article introduces ontologies, outlines the fundamental semantic web technologies used to create and apply RadLex, and presents examples of RadLex applications in everyday radiology and research. It concludes with a discussion of emerging applications of RadLex, including artificial intelligence applications. © RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Medical 3D Printing Dimensional Accuracy for Multi-pathological Anatomical Models 3D Printed Using Material Extrusion.

Medical 3D printing of anatomical models is being increasingly applied in healthcare facilities. The accuracy of such 3D-printed anatomical models is an important aspect of their overall quality control. The purpose of this research was to test whether the accuracy of a variety of anatomical models 3D printed using Material Extrusion (MEX) lies within a reasonable tolerance level, defined as less than 1-mm dimensional error. Six medical models spanning across anatomical regions (musculoskeletal, neurological, abdominal, cardiovascular) and sizes (model volumes ranging from ~ 4 to 203 cc) were chosen for the primary study. Three measurement landing blocks were strategically designed within each of the six medical models to allow high-resolution caliper measurements. An 8-cc reference cube was printed as the 7th model in the primary study. In the secondary study, the effect of model rotation and scale was assessed using two of the models from the first study. All models were 3D printed using an Ultimaker 3 printer in triplicates. All absolute measurement errors were found to be less than 1 mm with a maximum error of 0.89 mm. The maximum relative error was 2.78%. The average absolute error was 0.26 mm, and the average relative error was 0.71% in the primary study, and the results were similar in the secondary study with an average absolute error of 0.30 mm and an average relative error of 0.60%. The relative errors demonstrated certain patterns in the data, which were explained based on the mechanics of MEX 3D printing. Results indicate that the MEX process, when carefully assessed on a case-by-case basis, could be suitable for the 3D printing of multi-pathological anatomical models for surgical planning if an accuracy level of 1 mm is deemed sufficient for the application.

Improved Appropriateness of Advanced Diagnostic Imaging After Implementation of Clinical Decision Support Mechanism.

The Protecting Access to Medicare Act (PAMA) mandates clinical decision support mechanism (CDSM) consultation for all advanced imaging. There are a growing number of studies examining the association of CDSM use with imaging appropriateness, but a paucity of multicenter data. This observational study evaluates the association between changes in advanced imaging appropriateness scores with increasing provider exposure to CDSM. Each provider's first 200 consecutive anonymized requisitions for advanced imaging (CT, MRI, ultrasound, nuclear medicine) using a single CDSM (CareSelect, Change Healthcare) between January 1, 2017 and December 31, 2019 were collected from 288 US institutions. Changes in imaging requisition proportions among four appropriateness categories ("usually appropriate" [green], "may be appropriate" [yellow], "usually not appropriate" [red], and unmapped [gray]) were evaluated in relation to the chronological order of the requisition for each provider and total provider exposure to CDSM using logistic regression fits and Wald tests. The number of providers and requisitions included was 244,158 and 7,345,437, respectively. For 10,123 providers with ≥ 200 requisitions (2,024,600 total requisitions), the fraction of green, yellow, and red requisitions among the last 10 requisitions changed by +3.0% (95% confidence interval +2.6% to +3.4%), -0.8% (95% CI -0.5% to -1.1%), and -3.0% (95% CI 3.3% to -2.7%) in comparison with the first 10, respectively. Providers with > 190 requisitions had 8.5% (95% CI 6.3% to 10.7%) more green requisitions, 2.3% (0.7% to 3.9%) fewer yellow requisitions, and 0.5% (95% CI -1.0% to 2.0%) fewer red (not statistically significant) requisitions relative to providers with ≤ 10 requisitions. Increasing provider exposure to CDSM is associated with improved appropriateness scores for advanced imaging requisitions.

Desktop 3D printed anatomic models for minimally invasive direct coronary artery bypass.

BACKGROUND: Three-dimensional (3D) printing technology has impacted many clinical applications across medicine. However, 3D printing for Minimally Invasive Direct Coronary Artery Bypass (MIDCAB) has not yet been reported in the peer-reviewed literature. The current observational cohort study aimed to evaluate the impact of half scaled (50% scale) 3D printed (3DP) anatomic models in the pre-procedural planning of MIDCAB. METHODS: Retrospective analysis included 12 patients who underwent MIDCAB using 50% scale 3D printing between March and July 2020 (10 males, 2 females). Distances measured from CT scans and 3DP anatomic models were correlated with Operating Room (OR) measurements. The measurements were compared statistically using Tukey's test. The correspondence between the predicted (3DP & CT) and observed best InterCostal Space (ICS) in the OR was recorded. Likert surveys from the 3D printing registry were provided to the surgeon to assess the utility of the model. The OR time saved by planning the procedure using 3DP anatomic models was estimated subjectively by the cardiothoracic surgeon. RESULTS: All 12 patients were successfully grafted. The 3DP model predicted the optimal ICS in all cases (100%). The distances measured on the 3DP model corresponded well to the distances measured in the OR. The measurements were significantly different between the CT and 3DP (p < 0.05) as well as CT and OR (p < 0.05) groups, but not between the 3DP and OR group. The Likert responses suggested high clinical utility of 3D printing. The mean subjectively estimated OR time saved was 40 min. CONCLUSION: The 50% scaled 3DP anatomic models demonstrated high utility for MIDCAB and saved OR time while being resource efficient. The subjective benefits over routine care that used 3D visualization for surgical planning warrants further investigation.

METhodological RadiomICs Score (METRICS): a quality scoring tool for radiomics research endorsed by EuSoMII.

PURPOSE: To propose a new quality scoring tool, METhodological RadiomICs Score (METRICS), to assess and improve research quality of radiomics studies. METHODS: We conducted an online modified Delphi study with a group of international experts. It was performed in three consecutive stages: Stage#1, item preparation; Stage#2, panel discussion among EuSoMII Auditing Group members to identify the items to be voted; and Stage#3, four rounds of the modified Delphi exercise by panelists to determine the items eligible for the METRICS and their weights. The consensus threshold was 75%. Based on the median ranks derived from expert panel opinion and their rank-sum based conversion to importance scores, the category and item weights were calculated. RESULT: In total, 59 panelists from 19 countries participated in selection and ranking of the items and categories. Final METRICS tool included 30 items within 9 categories. According to their weights, the categories were in descending order of importance: study design, imaging data, image processing and feature extraction, metrics and comparison, testing, feature processing, preparation for modeling, segmentation, and open science. A web application and a repository were developed to streamline the calculation of the METRICS score and to collect feedback from the radiomics community. CONCLUSION: In this work, we developed a scoring tool for assessing the methodological quality of the radiomics research, with a large international panel and a modified Delphi protocol. With its conditional format to cover methodological variations, it provides a well-constructed framework for the key methodological concepts to assess the quality of radiomic research papers. CRITICAL RELEVANCE STATEMENT: A quality assessment tool, METhodological RadiomICs Score (METRICS), is made available by a large group of international domain experts, with transparent methodology, aiming at evaluating and improving research quality in radiomics and machine learning. KEY POINTS: • A methodological scoring tool, METRICS, was developed for assessing the quality of radiomics research, with a large international expert panel and a modified Delphi protocol. • The proposed scoring tool presents expert opinion-based importance weights of categories and items with a transparent methodology for the first time. • METRICS accounts for varying use cases, from handcrafted radiomics to entirely deep learning-based pipelines. • A web application has been developed to help with the calculation of the METRICS score ( https://metricsscore.github.io/metrics/METRICS.html ) and a repository created to collect feedback from the radiomics community ( https://github.com/metricsscore/metrics ).

Bisphenol A activates the Nrf1/2-antioxidant response element pathway in HEK 293 cells.

Bisphenol A (BPA) is used in the production of polycarbonate plastics and epoxy resins for baby bottles, liners of canned food, and many other consumer products. Previously, BPA has been shown to reduce the activity of several antioxidant enzymes, which may contribute to oxidative stress. However, the underlying mechanism of the BPA-mediated effect upon antioxidant enzyme activity is unknown. Antioxidant and phase II metabolizing enzymes protect cells from oxidative stress and are transcriptionally activated by Nrf1 and Nrf2 factors through their cis-regulatory antioxidant response elements (AREs). In this work, we have assessed the effect of BPA on the Nrf1/2-ARE pathway in cultured human embryonic kidney (HEK) 293 cells. Surprisingly, glutathione and reactive oxygen species (ROS) assays revealed that BPA application created a more reduced intracellular environment in cultured HEK 293 cells. Furthermore, BPA increased the transactivation activity of ectopic Nrf1 and Nrf2 and increased the expression of ARE-target genes ho-1 and nqo1 at high (100-200 µM) BPA concentrations only. Our study suggests that BPA activates the Nrf1/2-ARE pathway at high (>10 µM) micromolar concentrations.

Utility and Costs During the Initial Year of 3D Printing in an Academic Hospital.

OBJECTIVE: There is a paucity of utility and cost data regarding the launch of 3D printing in a hospital. The objective of this project is to benchmark utility and costs for radiology-based in-hospital 3D printing of anatomic models in a single, adult academic hospital. METHODS: All consecutive patients for whom 3D printed anatomic models were requested during the first year of operation were included. All 3D printing activities were documented by the 3D printing faculty and referring specialists. For patients who underwent a procedure informed by 3D printing, clinical utility was determined by the specialist who requested the model. A new metric for utility termed Anatomic Model Utility Points with range 0 (lowest utility) to 500 (highest utility) was derived from the specialist answers to Likert statements. Costs expressed in United States dollars were tallied from all 3D printing human resources and overhead. Total costs, focused costs, and outsourced costs were estimated. The specialist estimated the procedure room time saved from the 3D printed model. The time saved was converted to dollars using hospital procedure room costs. RESULTS: The 78 patients referred for 3D printed anatomic models included 11 clinical indications. For the 68 patients who had a procedure, the anatomic model utility points had an overall mean (SD) of 312 (57) per patient (range, 200-450 points). The total operation cost was $213,450. The total cost, focused costs, and outsourced costs were $2,737, $2,180, and $2,467 per model, respectively. Estimated procedure time saved had a mean (SD) of 29.9 (12.1) min (range, 0-60 min). The hospital procedure room cost per minute was $97 (theoretical $2,900 per patient saved with model). DISCUSSION: Utility and cost benchmarks for anatomic models 3D printed in a hospital can inform health care budgets. Realizing pecuniary benefit from the procedure time saved requires future research.

Self-organizing ontology of biochemically relevant small molecules.

BACKGROUND: The advent of high-throughput experimentation in biochemistry has led to the generation of vast amounts of chemical data, necessitating the development of novel analysis, characterization, and cataloguing techniques and tools. Recently, a movement to publically release such data has advanced biochemical structure-activity relationship research, while providing new challenges, the biggest being the curation, annotation, and classification of this information to facilitate useful biochemical pattern analysis. Unfortunately, the human resources currently employed by the organizations supporting these efforts (e.g. ChEBI) are expanding linearly, while new useful scientific information is being released in a seemingly exponential fashion. Compounding this, currently existing chemical classification and annotation systems are not amenable to automated classification, formal and transparent chemical class definition axiomatization, facile class redefinition, or novel class integration, thus further limiting chemical ontology growth by necessitating human involvement in curation. Clearly, there is a need for the automation of this process, especially for novel chemical entities of biological interest. RESULTS: To address this, we present a formal framework based on Semantic Web technologies for the automatic design of chemical ontology which can be used for automated classification of novel entities. We demonstrate the automatic self-assembly of a structure-based chemical ontology based on 60 MeSH and 40 ChEBI chemical classes. This ontology is then used to classify 200 compounds with an accuracy of 92.7%. We extend these structure-based classes with molecular feature information and demonstrate the utility of our framework for classification of functionally relevant chemicals. Finally, we discuss an iterative approach that we envision for future biochemical ontology development. CONCLUSIONS: We conclude that the proposed methodology can ease the burden of chemical data annotators and dramatically increase their productivity. We anticipate that the use of formal logic in our proposed framework will make chemical classification criteria more transparent to humans and machines alike and will thus facilitate predictive and integrative bioactivity model development.

Prototype semantic infrastructure for automated small molecule classification and annotation in lipidomics.

BACKGROUND: The development of high-throughput experimentation has led to astronomical growth in biologically relevant lipids and lipid derivatives identified, screened, and deposited in numerous online databases. Unfortunately, efforts to annotate, classify, and analyze these chemical entities have largely remained in the hands of human curators using manual or semi-automated protocols, leaving many novel entities unclassified. Since chemical function is often closely linked to structure, accurate structure-based classification and annotation of chemical entities is imperative to understanding their functionality. RESULTS: As part of an exploratory study, we have investigated the utility of semantic web technologies in automated chemical classification and annotation of lipids. Our prototype framework consists of two components: an ontology and a set of federated web services that operate upon it. The formal lipid ontology we use here extends a part of the LiPrO ontology and draws on the lipid hierarchy in the LIPID MAPS database, as well as literature-derived knowledge. The federated semantic web services that operate upon this ontology are deployed within the Semantic Annotation, Discovery, and Integration (SADI) framework. Structure-based lipid classification is enacted by two core services. Firstly, a structural annotation service detects and enumerates relevant functional groups for a specified chemical structure. A second service reasons over lipid ontology class descriptions using the attributes obtained from the annotation service and identifies the appropriate lipid classification. We extend the utility of these core services by combining them with additional SADI services that retrieve associations between lipids and proteins and identify publications related to specified lipid types. We analyze the performance of SADI-enabled eicosanoid classification relative to the LIPID MAPS classification and reflect on the contribution of our integrative methodology in the context of high-throughput lipidomics. CONCLUSIONS: Our prototype framework is capable of accurate automated classification of lipids and facile integration of lipid class information with additional data obtained with SADI web services. The potential of programming-free integration of external web services through the SADI framework offers an opportunity for development of powerful novel applications in lipidomics. We conclude that semantic web technologies can provide an accurate and versatile means of classification and annotation of lipids.

Stability of carbon-centered radicals: effect of functional groups on the energetics of addition of molecular oxygen.

In this paper we examine a series of hydrocarbons with structural features which cause a weakening of the C-H bond. We use theoretical calculations to explore whether the carbon-centered radicals R(*) which are created after breaking the bond can be stabilized enough so that they resist the addition of molecular oxygen, i.e. where the reaction R(*) + O(2) --> ROO(*) becomes energetically unfavorable. Calculations using a B3LYP-based method provide accurate bond dissociation enthalpies (BDEs) for R-H and R-OO(*) bonds, as well as Gibbs free energy changes for the addition reaction. The data show strong correlations between R-OO(*) and R-H BDEs for a wide variety of structures. They also show an equally strong correlation between the R-OO(*) BDE and the unpaired spin density at the site of addition. Using these data we examine the major functional group categories proposed in several experimental studies, and assess their relative importance. Finally, we combine effects to try to optimize resistance to the addition of molecular oxygen, an important factor in designing carbon-based antioxidants.

Cytotoxicity and cytoprotective activity in naphthalenediols depends on their tendency to form naphthoquinones.

We consider the cytotoxicity and the protection against oxidative stress for members of the naphthalenediol family and the known antioxidant epigallocatechin gallate (EGCG). Compounds include the 1,2-naphthalenediol (1,2-ND), 1,4-ND, 2,3-ND, 1,8-ND, and 1,4-dipropyl-2,3-naphthalenediol (DPND). The cell line is an adherent clone of rat pheochromocytoma (PC12-AC). Oxidative stress was induced by the peroxyl radical generator AAPH. The relative order of cytotoxicity was 1,4-ND > 1,2-ND > DPND > 2,3-ND > 1,8-ND > EGCG, with EC(50)'s of 15, 40, 160, >250, >250, >>250 muM, respectively. Despite their high toxicity, both 1,4-ND and 1,2-ND showed narrow zones of protective behavior whereas DPND, 2,3-ND and 1,8-ND and especially EGCG showed an extended protective range. The total protection obtained for the combination of cells/oxidative stressor/protective compounds (PC12-AC/AAPH/naphthalenediols) was defined by an integrated measure, the cytoprotective area (CPA). We relate the observed cytotoxicity and CPA to the different electronic structures of the naphthalenediols, characterized by the first and second bond dissociation enthalpies and the pK(a)'s for parent (diol) and semiquinone. Since the 2,3- and 1,8-naphthalenediols do not form quinones, their cytotoxicity is much lower than for the compounds which do. Thus selected members of the naphthalenediol family show promise as antioxidants.

Mechanism of cytotoxicity of catechols and a naphthalenediol in PC12-AC cells: the connection between extracellular autoxidation and molecular electronic structure.

ortho-Hydroxyphenols (catechols) form a common structural unit in naturally occurring antioxidants such as polyphenols. They also show pro-oxidant characteristics which depend on their particular structure. Here we examined the acetylated versions of three catechols and a naphthalenediol for cytotoxicity to adrenal PC12-AC cells. We found that the three catechols H1 (a p-methoxycatechol), H2 (a catechol analog of alpha-tocopherol), and H4 (a dioxymethylene-substituted catechol) strongly upregulate glutathione (GSH) in 24 h, whereas 1,4-dipropyl-2,3-naphthalenediol (DPND) does not. Upregulation of GSH is primarily caused by oxidative stress in the form of hydrogen peroxide generation, and both GSH upregulation and the rate of H(2)O(2) generation correlate well with the cytotoxicity. The major source of H(2)O(2) is autoxidation in the extracellular space, which results from transport of the (deacetylated) hydroquinone form outside the cell, rather than internal redox cycling. DPND is much less cytotoxic than any of the catechols. We show that this is because it cannot form a naphthoquinone due to the energy penalty associated with the loss of aromaticity in the benzene ring adjacent to the diol functional group. The relevance of these results to the design of antioxidants is discussed.

Chemical Entity Semantic Specification: Knowledge representation for efficient semantic cheminformatics and facile data integration.

BACKGROUND: Over the past several centuries, chemistry has permeated virtually every facet of human lifestyle, enriching fields as diverse as medicine, agriculture, manufacturing, warfare, and electronics, among numerous others. Unfortunately, application-specific, incompatible chemical information formats and representation strategies have emerged as a result of such diverse adoption of chemistry. Although a number of efforts have been dedicated to unifying the computational representation of chemical information, disparities between the various chemical databases still persist and stand in the way of cross-domain, interdisciplinary investigations. Through a common syntax and formal semantics, Semantic Web technology offers the ability to accurately represent, integrate, reason about and query across diverse chemical information. RESULTS: Here we specify and implement the Chemical Entity Semantic Specification (CHESS) for the representation of polyatomic chemical entities, their substructures, bonds, atoms, and reactions using Semantic Web technologies. CHESS provides means to capture aspects of their corresponding chemical descriptors, connectivity, functional composition, and geometric structure while specifying mechanisms for data provenance. We demonstrate that using our readily extensible specification, it is possible to efficiently integrate multiple disparate chemical data sources, while retaining appropriate correspondence of chemical descriptors, with very little additional effort. We demonstrate the impact of some of our representational decisions on the performance of chemically-aware knowledgebase searching and rudimentary reaction candidate selection. Finally, we provide access to the tools necessary to carry out chemical entity encoding in CHESS, along with a sample knowledgebase. CONCLUSIONS: By harnessing the power of Semantic Web technologies with CHESS, it is possible to provide a means of facile cross-domain chemical knowledge integration with full preservation of data correspondence and provenance. Our representation builds on existing cheminformatics technologies and, by the virtue of RDF specification, remains flexible and amenable to application- and domain-specific annotations without compromising chemical data integration. We conclude that the adoption of a consistent and semantically-enabled chemical specification is imperative for surviving the coming chemical data deluge and supporting systems science research.

Semantic Web integration of Cheminformatics resources with the SADI framework.

BACKGROUND: The diversity and the largely independent nature of chemical research efforts over the past half century are, most likely, the major contributors to the current poor state of chemical computational resource and database interoperability. While open software for chemical format interconversion and database entry cross-linking have partially addressed database interoperability, computational resource integration is hindered by the great diversity of software interfaces, languages, access methods, and platforms, among others. This has, in turn, translated into limited reproducibility of computational experiments and the need for application-specific computational workflow construction and semi-automated enactment by human experts, especially where emerging interdisciplinary fields, such as systems chemistry, are pursued. Fortunately, the advent of the Semantic Web, and the very recent introduction of RESTful Semantic Web Services (SWS) may present an opportunity to integrate all of the existing computational and database resources in chemistry into a machine-understandable, unified system that draws on the entirety of the Semantic Web. RESULTS: We have created a prototype framework of Semantic Automated Discovery and Integration (SADI) framework SWS that exposes the QSAR descriptor functionality of the Chemistry Development Kit. Since each of these services has formal ontology-defined input and output classes, and each service consumes and produces RDF graphs, clients can automatically reason about the services and available reference information necessary to complete a given overall computational task specified through a simple SPARQL query. We demonstrate this capability by carrying out QSAR analysis backed by a simple formal ontology to determine whether a given molecule is drug-like. Further, we discuss parameter-based control over the execution of SADI SWS. Finally, we demonstrate the value of computational resource envelopment as SADI services through service reuse and ease of integration of computational functionality into formal ontologies. CONCLUSIONS: The work we present here may trigger a major paradigm shift in the distribution of computational resources in chemistry. We conclude that envelopment of chemical computational resources as SADI SWS facilitates interdisciplinary research by enabling the definition of computational problems in terms of ontologies and formal logical statements instead of cumbersome and application-specific tasks and workflows.

Polypyrroles as antioxidants: kinetic studies on reactions of bilirubin and biliverdin dimethyl esters and synthetic model compounds with peroxyl radicals in solution. Chemical calculations on selected typical structures.

[reaction: see text] Rate constants for hydrogen-atom transfer (HAT) from bilirubin dimethyl ester (BRDE) and biliverdin dimethyl ester (BVDE) to peroxyl radicals during inhibited autoxidation of styrene initiated by azo-bisisobutyronitrile (AIBN) were k(inh)(BRDE) = 22.5 x 10(4) and k(inh)(BVDE) = 10.2 x 10(4) M(-1) s(-1), and the stoichiometric factors (n) were 2.0 and 2.7, respectively. A synthetic tetrapyrrole (bis(dipyrromethene)) containing the alpha-central (2,2') CH2 linkage gave k(inh) = 39.9 x 10(4) M(-1) s(-1) and n = 2.3, whereas the beta-linked (3,3') isomer was not an active antioxidant. Several dipyrrinones were synthesized as mimics of the two outer heterocyclic rings of bilirubin and biliverdin. The dipyrrinones containing N-H groups in each ring were active antioxidants, whereas those lacking two such "free" N-H groups, such as N-CH3 dipyrrinones and dipyrromethenes, did not exhibit antioxidant activity. Overall, the relative k(inh) values compared to those of phenolic antioxidants, 2,6-di-tert-butyl-4-methoxyphenol (DBHA) and 2,6-di-tert-butyl-4-methylphenol (BHT), were 2,2'-bis(dipyrromethene) > BRDE > DBHA > dipyrrinones > BVDE > BHT. This general trend in antioxidant activities was also observed for the inhibited autoxidation of cumene initiated by AIBN. Chemical calculations of the N-H bond dissociation enthalpies (BDEs) of the typical structures support a HAT mechanism from N-H groups to trap peroxyl radicals. Intramolecular hydrogen bonding of intermediate nitrogen radicals has a major influence on the antioxidant activities of all compounds studied. Indeed, chemical calculations showed that the initial nitrogen radical from a dipyrrinone is stabilized by 9.0 kcal/mol because of H-bonding between the N-H remaining on one ring and the ground-state pyrrolyl radical of the adjacent ring in the natural zusammen structure. The calculated minimum structure of bilirubin shows strong intramolecular H-bonding of the N-H groups with carbonyl groups resulting in the known "ridge-tile" structure which is not an active HAT antioxidant. The calculated minimum structure of biliverdin is planar. BRDE is readily converted into BVDE by reaction with the electron-deficient DPPH* radical under argon in chlorobenzene. An electron-transfer mechanism is proposed for the initiating step in this reaction, and this is supported by the relatively low ionizing potential of a model dipyrrole representing the two central rings of bilirubin.