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In diagnostic medicine, the true disease status of a patient is often represented on an ordinal scale—for example, cancer stage (0, I, II, III, or IV) or coronary artery disease severity measured using the Coronary Artery Disease Reporting and Data System (CAD-RADS) scale (none, minimal, mild, moderate, severe, or occluded). With advances in quantitation of diagnostic images and in artificial intelligence (AI), both supervised and unsupervised algorithms are being developed to help physicians correctly grade disease. Most of the diagnostic accuracy literature deals with binary disease status (disease present or absent); however, tests diagnosing ordinal-scaled diseases should not be reduced to a binary status just to simplify diagnostic accuracy testing. In this paper, we propose different characterizations of ordinal-scale accuracy for different clinical use scenarios, along with methods for comparing tests. In the simplest scenario, just the proportion of correct grades is considered; other scenarios address the magnitude and direction of misgrading; and at the other extreme, a weighted accuracy measure with weights based on the relative costs of different types of misgrading is presented. The various scenarios are illustrated using a coronary artery disease example where the accuracy of AI algorithms in providing patients with the correct CAD-RADS grade is assessed. [ABSTRACT FROM AUTHOR]

Objectives N95 filtering facepiece respirators (N95 FFRs) and surgical masks are comprised of multiple layers of nonwoven polypropylene. Tight-fitting N95 FFRs are respiratory protective devices (RPDs) designed to efficiently filter aerosols. During the COVID-19 pandemic, health care workers (HCWs) throughout the world continue to face shortages of disposable N95 FFRs. Existing version of widely available FDA cleared loose-fitting surgical masks with straps do not provide reliable protection against aerosols. We tested the faceseal of a modified strapless form-fitting sealed version of surgical mask using quantitative fit testing (QNFT) and compared the performance of this mask with that of N95 FFRs and unmodified loose-fitting surgical masks. Methods Twenty HCWs participated in the study (10 women; 10 men; age 23–59 years). To create the sealed surgical masks, we removed the straps from loose-fitting surgical masks, made new folds, and used adhesive medical tape to secure the new design. All participants underwent QNFT with a loose-fitting surgical mask, the sealed surgical mask, and an N95 FFR; fit factors were recorded. Each QNFT was performed using a protocol of four exercises: (i) bending over, (ii) talking, (iii) moving head side to side, and (iv) moving head up and down. When the overall fit factor for the sealed surgical mask or N95 FFR was <100, the participant retook the test. Participants scored the breathability and comfort of the sealed surgical mask and N95 FFR on a visual analog scale (VAS) ranging from 0 (unfavorable) to 10 (favorable). Results The median fit factor for the sealed surgical mask (53.8) was significantly higher than that of the loose-fitting surgical mask (3.0) but lower than that of the N95 FFR (177.0) (P < 0.001), equating to significantly lower inward leakage of ambient aerosols (measuring 0.04–0.06 µm) with the sealed surgical mask (geometric mean 1.79%; geometric standard deviation 1.45%; range 0.97–4.03%) than with the loose-fitting surgical mask (29.5%; 2.01%; 25–100.0%) but still higher than with the N95 FFR (0.66%; 1.46%; 0.50–1.97%) (P < 0.001). Sealed surgical masks led to a marked reduction (range 60–98%) in inward leakage of aerosols in all the participants, compared to loose-fitting surgical masks. Among the exercises, talking had a greater effect on reducing overall fit factor for the sealed surgical mask than for the N95 FFR; when talking was excluded, the fit factor for the sealed surgical mask improved significantly (median 53.8 to 81.5; P < 0.001). The sealed surgical mask, when compared with the N95 FFR, offered better reported breathability (median VAS 9 versus 5; P < 0.001) and comfort (9 versus 5; P < 0.001). Conclusions Widely available loose-fitting surgical masks can be easily modified to achieve faceseal with adhesives. Unlike loose-fitting surgical masks, sealed surgical masks can markedly reduce inward leakage of aerosols and may therefore offer useful levels of respiratory protection during an extreme shortage of N95 FFRs and could benefit HCWs who cannot comply with N95 FFRs due to intolerance. However, because a wide range of surgical masks is commercially available, individual evaluation of such masks is highly recommended before sealed versions are used as RPDs. [ABSTRACT FROM AUTHOR]

An editorial is presented on assessing the performance of a new diagnostic method being a common problem in radiology. Topics include technical advances impacting image acquisition and post-processing showing applications of artificial intelligence; and interchangeability being a statistical method describing the efect of replacing the current test with the new test without the need for a reference standard.

Diagnostic systems designed to detect possibly multiple lesions per patient (e.g. multiple polyps during CT colonoscopy) are often evaluated in "free-response" studies that allow for diagnostic responses unconstrained in their number and locations. Analysis of free-response studies requires extensions of the traditional receiver operating characteristic (ROC) analysis, which are termed free-response ROC (FROC) methodology. Despite substantial developments in this area, FROC tools and approaches are much more cumbersome than traditional ROC methods. Alternative approaches that use well-known ROC tools (e.g. ROI-ROC) require defining and physically delineating regions of interest (ROI) and combine FROC data within ROIs. We propose an approach that allows analyzing FROC data using conventional ROC tools without delineating the actual ROIs or reducing data. The design parameters of FROC study are used to make FROC data analyzable using ROC tools and to calibrate the corresponding FROC and ROC curves on both conceptual and numerical levels. Differences in the performance indices of the nonparametric FROC and the new approach are shown to be asymptotically negligible and typically rather small in practice. Data from a large multi-reader study of colon cancer detection are used to illustrate the new approach. [ABSTRACT FROM AUTHOR]

As imaging technologies and treatment options continue to advance, imaging outcome measures are becoming increasingly utilized as the basis of making major decisions in new drug development and clinical practice. Quantitative imaging biomarkers (QIBs) are now commonly used for subject selection, response assessment, and safety monitoring. Although quantitative measurements can have many advantages compared with subjective, qualitative endpoints, it is important to recognize that QIBs are measured with error. This study uses Monte Carlo simulation to examine the impact of measurement error on a variety of clinical trial designs as well as to test proposed adjustments for measurement error. The focus is on some of the QIBs currently being studied by the Quantitative Imaging Biomarkers Alliance. The results show that the ability of QIBs to discriminate between health states and predict patient outcome is attenuated by measurement error; however, the known technical performance characteristics of QIBs can be used to adjust study sample size, control the misinterpretation rate of imaging findings, and establish statistically valid decision thresholds. We conclude that estimates of the precision and bias of a QIB are important for properly designing clinical trials and establishing the level of imaging standardization required. [ABSTRACT FROM AUTHOR]

Introduction Quantitative imaging biomarkers (QIBs) are being increasingly used in medical practice and clinical trials. An essential first step in the adoption of a quantitative imaging biomarker is the characterization of its technical performance, i.e. precision and bias, through one or more performance studies. Then, given the technical performance, a confidence interval for a new patient's true biomarker value can be constructed. Estimating bias and precision can be problematic because rarely are both estimated in the same study, precision studies are usually quite small, and bias cannot be measured when there is no reference standard. Methods A Monte Carlo simulation study was conducted to assess factors affecting nominal coverage of confidence intervals for a new patient's quantitative imaging biomarker measurement and for change in the quantitative imaging biomarker over time. Factors considered include sample size for estimating bias and precision, effect of fixed and non-proportional bias, clustered data, and absence of a reference standard. Results Technical performance studies of a quantitative imaging biomarker should include at least 35 test-retest subjects to estimate precision and 65 cases to estimate bias. Confidence intervals for a new patient's quantitative imaging biomarker measurement constructed under the no-bias assumption provide nominal coverage as long as the fixed bias is <12%. For confidence intervals of the true change over time, linearity must hold and the slope of the regression of the measurements vs. true values should be between 0.95 and 1.05. The regression slope can be assessed adequately as long as fixed multiples of the measurand can be generated. Even small non-proportional bias greatly reduces confidence interval coverage. Multiple lesions in the same subject can be treated as independent when estimating precision. Conclusion Technical performance studies of quantitative imaging biomarkers require moderate sample sizes in order to provide robust estimates of bias and precision for constructing confidence intervals for new patients. Assumptions of linearity and non-proportional bias should be assessed thoroughly. [ABSTRACT FROM AUTHOR]

During diagnostic accuracy studies, hypotheses are often tested on more than one accuracy measure. One common example is to make inferences both on the area under the receiver operating characteristic curve (AUC) and on the sensitivity and specificity at a particular operating point. This represents a unique multiple testing situation as the AUC is a function of the sensitivity and specificity. Through a large simulation study, we showed that a naïve approach of testing all three accuracy measures at a 0.05-level greatly elevates the family-wise Type I error rate (i.e., up to 10%). When a gatekeeping approach to controlling the FWER was appropriate (family 1: AUC, family 2: sensitivity and specificity), adjustment in the second family was necessary to control the FWER across all scenarios. When a nonhierarchical approach was appropriate, the methods of Xie (2012) offered increased power over Holm's step-down procedure, but required assumptions about the correlation among the test statistics. In our simulations, the correlation between the test statistics of the AUC and sensitivity and between the test statistics of the AUC and specificity ranged from 0.3 to 0.6, while there was no correlation between the test statistics of the sensitivity and specificity. [ABSTRACT FROM AUTHOR]

Biostatistics is an essential component in most original research studies in imaging. In this article we discuss five key statistical concepts for study design and analyses in modern imaging research: statistical hypothesis testing, particularly focusing on noninferiority studies; imaging outcomes especially when there is no reference standard; dealing with the multiplicity problem without spending all your study power; relevance of confidence intervals in reporting and interpreting study results; and finally tools for assessing quantitative imaging biomarkers. These concepts are presented first as examples of conversations between investigator and biostatistician, and then more detailed discussions of the statistical concepts follow. Three skeletal radiology examples are used to illustrate the concepts. [ABSTRACT FROM AUTHOR]

A characteristic feature of communicating aortic dissections (CD) is the dissection flap between the true and false lumen. However, in intramural hematomas (IMH) a flap is not visible. We aimed to determine if cross-sectional HU variability allow reliable identification of aortic dissections including IMH. We included 362 patients presenting with acute chest pain (CP) or respiratory distress (RD) and underwent contrast-enhanced CTA with or without ECG-gating. In the derivation group we included 72 CP patients with and 74 without AAS. In the validation group we included 108 CP or RD patients with and 108 without AAS. The adventitial border of the aorta was visually identified and measurements were performed at 6 locations along the ascending and descending aorta. At each cross-section 5 circular ROI measurements of HU were made and the maximum HU difference calculated. In the derivation and validation group the maximum difference in HUs at any one location was significantly higher for AAS subjects than controls (validation group: median = 128.5 vs. 34.0, p -value Wilcoxon two-sample test <0.001). In the validation group, the estimated AUC was 0.939 with 95% CIs of [0.906, 0.972], indicating that the maximum difference in HUs is a strong predictor of AAS (p < 0.001). Our data provide evidence that cross-sectional variability of Hounsfield Unit reliably identifies aortic dissection including IMH in dedicated ECG-gated aorta scans but also non-gated chest CTs with limited aortic contrast enhancement. These results suggest that this approach could be feasible for an automated algorithm for identification of AAS. • We examined if cross-sectional Hounsfield Units (HU) variability allow reliable identification of aortic dissections including IMH. • 362 patients presenting with acute chest pain or respiratory distress were included. • the aorta was segmented and HU measurements were made at cross-sections in the ascending and descending aorta. • maximum difference in HUs at any one location was significantly higher for Acute Aortic Syndromes (AAS) subjects than controls. • cross-sectional variability of HU reliably identifies aortic dissection including IMH and could be feasible for an automated identification algorithm. [ABSTRACT FROM AUTHOR]

Quantitative imaging biomarkers are being used increasingly in medicine to diagnose and monitor patients’ disease. The computer algorithms that measure quantitative imaging biomarkers have different technical performance characteristics. In this paper we illustrate the appropriate statistical methods for assessing and comparing the bias, precision, and agreement of computer algorithms. We use data from three studies of pulmonary nodules. The first study is a small phantom study used to illustrate metrics for assessing repeatability. The second study is a large phantom study allowing assessment of four algorithms’ bias and reproducibility for measuring tumor volume and the change in tumor volume. The third study is a small clinical study of patients whose tumors were measured on two occasions. This study allows a direct assessment of six algorithms’ performance for measuring tumor change. With these three examples we compare and contrast study designs and performance metrics, and we illustrate the advantages and limitations of various common statistical methods for quantitative imaging biomarker studies. [ABSTRACT FROM PUBLISHER]

Quantitative biomarkers from medical images are becoming important tools for clinical diagnosis, staging, monitoring, treatment planning, and development of new therapies. While there is a rich history of the development of quantitative imaging biomarker (QIB) techniques, little attention has been paid to the validation and comparison of the computer algorithms that implement the QIB measurements. In this paper we provide a framework for QIB algorithm comparisons. We first review and compare various study designs, including designs with the true value (e.g. phantoms, digital reference images, and zero-change studies), designs with a reference standard (e.g. studies testing equivalence with a reference standard), and designs without a reference standard (e.g. agreement studies and studies of algorithm precision). The statistical methods for comparing QIB algorithms are then presented for various study types using both aggregate and disaggregate approaches. We propose a series of steps for establishing the performance of a QIB algorithm, identify limitations in the current statistical literature, and suggest future directions for research. [ABSTRACT FROM PUBLISHER]

Education has a protective effect against cognitive deficits following various forms of brain insult. Professional fighting (boxing and mixed martial arts) provides a model for assessing the impact of cumulative brain injuries on cognition and brain health. In the current cross-sectional observational study, we explore whether education would be protective against cognitive loss in fighters. We tested 141 professional fighters using a computerized neurocognitive battery, in addition to structural MRI. We used automated segmentation software to compute the volumes of various brain structures. We found fighters with high school education or less to show more associations between fight exposure and cognitive test scores. The relationship between brain structure volume and exposure did not differ based on education. These results are interpreted as putatively showing a protective effect of education on functional integrity in fighters, although longitudinal data and a larger sample size are required to further understand this relationship. [ABSTRACT FROM AUTHOR]

Introduction: The sensitivity of CT based lung cancer screening for the detection of early lung cancer is balanced by the high number of benign lung nodules identified, the unknown consequences of radiation from the test, and the potential costs of a CT based screening program. CAD chest radiography may improve the sensitivity of standard chest radiography while minimizing the risks of CT based screening. Methods: Study subjects were age 40–75 years with 10+ pack-years of smoking and/or an additional risk for developing lung cancer. Subjects were randomized to receive a PA view chest radiograph or placebo control (went through the process of being imaged but were not imaged). Images were reviewed first without then with the assistance of CAD. Actionable nodules were reported and additional evaluation was tracked. The primary outcome was the rate of developing symptomatic advanced stage lung cancer. Results: 1,424 subjects were enrolled. 710 received a CAD chest radiograph, 29 of whom were found to have an actionable lung nodule on prevalence screening. Of the 15 subjects who had a chest CT performed for additional evaluation, a lung nodule was confirmed in 4, 2 of which represented lung cancer. Both of the cancers were seen by the radiologist unaided and were identified by the CAD chest radiograph. The cumulative incidence of symptomatic advanced lung cancer was 0.42 cases per 100 person-years in the control arm; there were no events in the screening arm. Conclusions: Further evaluation is necessary to determine if CAD chest radiography has a role as a lung cancer screening tool. ClinicalTrials.gov identifier NCT01663155 [ABSTRACT FROM AUTHOR]

Current ongoing genome-wide association (GWA) studies represent a powerful approach to uncover common unknown genetic variants causing common complex diseases. The discovery of these genetic variants offers an important opportunity for early disease prediction, prevention, and individualized treatment. We describe here a method of combining multiple genetic variants for early disease prediction, based on the optimality theory of the likelihood ratio (LR). Such theory simply shows that the receiver operating characteristic (ROC) curve based on the LR has maximum performance at each cutoff point and that the area under the ROC curve so obtained is highest among that of all approaches. Through simulations and a real data application, we compared it with the commonly used logistic regression and classification tree approaches. The three approaches show similar performance if we know the underlying disease model. However, for most common diseases we have little prior knowledge of the disease model and in this situation the new method has an advantage over logistic regression and classification tree approaches. We applied the new method to the type 1 diabetes GWA data from the Wellcome Trust Case Control Consortium. Based on five single nucleotide polymorphisms, the test reaches medium level classification accuracy. With more genetic findings to be discovered in the future, we believe a predictive genetic test for type 1 diabetes can be successfully constructed and eventually implemented for clinical use. [ABSTRACT FROM AUTHOR]

Abstract: Background: Lung cancer screening, like other screening tests, has the potential to save many lives, yet its benefit has not yet been shown in randomized clinical trials (RCTs). RCTs of screening tests require very large sample sizes and long follow-up periods. Investigators planning these trials need to know how the study design, particularly the length of accrual, the number of incident screens, the length of follow-up, and the method used to interpret the screening test, affect sample size requirements. Methods: In this paper a tiered approach to sample size estimation is presented. The first tier determines the person-years at risk; the second tier considers the characteristics of the study population to estimate the frequency of preclinical disease; the third tier uses the performance of the screening test, the compliance rate, and the benefits of early treatment to estimate the incidence of clinical disease; the disease-specific mortality rates are estimated in the fourth tier. Results: This sample size approach was utilized in planning a RCT of lung cancer screening with chest X-rays and a computer aided detection algorithm. Sample size was determined for various features of the study design, as well as for different assumptions about the cure rate, the treatment complication rate, and the rate of potential misclassification of the primary endpoints. Conclusion: The tiered approach to sample size estimation for RCTs of screening tests allows investigators to assess how features of the study design affect sample size requirements. [Copyright &y& Elsevier]

Abstract: Background: Misclassification of study endpoints in randomized clinical trials of screening tests has been well documented, yet its effect on study power, type I error rate, and risk ratio estimate have not been studied in depth. Methods: We constructed a Markov model to depict the natural history of disease and the effect of screening on it. Using this model we simulated subjects in a two-arm RCT. We varied the type and amount of misclassification, and studied the effect on two endpoints — disease-specific mortality and the incidence of disease-specific symptoms. Results: Failure to identify disease-specific events in a RCT of screening has a small effect on the risk ratio estimate and study power. In contrast, the false identification of events as being attributable to the target disease greatly reduces study power. Conclusions: Investigators of RCTs of screening tests should carefully consider the potential for misclassification and the type of misclassification that their study is as risk for. Studies should be designed to minimize misclassification. The effect of misclassification on power should be considered in sample size calculations. [Copyright &y& Elsevier]

ROC curves and summary measures of accuracy derived from them, such as the area under the ROC curve, have become the standard for describing and comparing the accuracy of diagnostic tests. Methods for estimating ROC curves rely on the existence of a gold standard which dichotomizes patients into disease present or absent. There are, however, many examples of diagnostic tests whose gold standards are not binary-scale, but rather continuous-scale. Unnatural dichotomization of these gold standards leads to bias and inconsistency in estimates of diagnostic accuracy. In this paper, we propose a non-parametric estimator of diagnostic test accuracy which does not require dichotomization of the gold standard. This estimator has an interpretation analogous to the area under the ROC curve. We propose a confidence interval for test accuracy and a statistical test for comparing accuracies of tests from paired designs. We compare the performance (i.e. CI coverage, type I error rate, power) of the proposed methods with several alternatives. An example is presented where the accuracies of two quick blood tests for measuring serum iron concentrations are estimated and compared. Copyright © 2005 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

There are several different statistical methods for analysing multireader ROC studies, with the Dorfman-Berbaum-Metz (DBM) method being the most frequently used. Another method is the corrected F method proposed by Obuchowski and Rockette (OR). The DBM and OR procedures at first appear quite different: DBM is a three-way ANOVA analysis of pseudovalues while OR is a two-way ANOVA analysis of accuracy estimates with correlated errors. We show that the original DBM and OR F statistics for testing the null hypothesis of equal treatments have the same form and will typically have similar values; however, differences in the denominator degrees of freedom will result in differences in p-values even when the F statistics are identical. We show how the methods can be generalized to include variations in the accuracy measure, covariance method, and degrees of freedom. Identical results are obtained when the methods agree with respect to all three of these procedure parameters; hence for a particular choice of procedure parameters the choice of method appears to depend mainly on software preference and availability. The methods are compared using data from a factorial study with two modalities, five readers, and 114 patients. Copyright © 2005 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) systems can potentially aid the diagnostic pathway of prostate cancer by alleviating the increasing workload, preventing overdiagnosis, and reducing the dependence on experienced radiologists. We aimed to investigate the performance of AI systems at detecting clinically significant prostate cancer on MRI in comparison with radiologists using the Prostate Imaging—Reporting and Data System version 2.1 (PI-RADS 2.1) and the standard of care in multidisciplinary routine practice at scale. In this international, paired, non-inferiority, confirmatory study, we trained and externally validated an AI system (developed within an international consortium) for detecting Gleason grade group 2 or greater cancers using a retrospective cohort of 10 207 MRI examinations from 9129 patients. Of these examinations, 9207 cases from three centres (11 sites) based in the Netherlands were used for training and tuning, and 1000 cases from four centres (12 sites) based in the Netherlands and Norway were used for testing. In parallel, we facilitated a multireader, multicase observer study with 62 radiologists (45 centres in 20 countries; median 7 [IQR 5–10] years of experience in reading prostate MRI) using PI-RADS (2.1) on 400 paired MRI examinations from the testing cohort. Primary endpoints were the sensitivity, specificity, and the area under the receiver operating characteristic curve (AUROC) of the AI system in comparison with that of all readers using PI-RADS (2.1) and in comparison with that of the historical radiology readings made during multidisciplinary routine practice (ie, the standard of care with the aid of patient history and peer consultation). Histopathology and at least 3 years (median 5 [IQR 4–6] years) of follow-up were used to establish the reference standard. The statistical analysis plan was prespecified with a primary hypothesis of non-inferiority (considering a margin of 0·05) and a secondary hypothesis of superiority towards the AI system, if non-inferiority was confirmed. This study was registered at ClinicalTrials.gov , NCT05489341. Of the 10 207 examinations included from Jan 1, 2012, through Dec 31, 2021, 2440 cases had histologically confirmed Gleason grade group 2 or greater prostate cancer. In the subset of 400 testing cases in which the AI system was compared with the radiologists participating in the reader study, the AI system showed a statistically superior and non-inferior AUROC of 0·91 (95% CI 0·87–0·94; p<0·0001), in comparison to the pool of 62 radiologists with an AUROC of 0·86 (0·83–0·89), with a lower boundary of the two-sided 95% Wald CI for the difference in AUROC of 0·02. At the mean PI-RADS 3 or greater operating point of all readers, the AI system detected 6·8% more cases with Gleason grade group 2 or greater cancers at the same specificity (57·7%, 95% CI 51·6–63·3), or 50·4% fewer false-positive results and 20·0% fewer cases with Gleason grade group 1 cancers at the same sensitivity (89·4%, 95% CI 85·3–92·9). In all 1000 testing cases where the AI system was compared with the radiology readings made during multidisciplinary practice, non-inferiority was not confirmed, as the AI system showed lower specificity (68·9% [95% CI 65·3–72·4] vs 69·0% [65·5–72·5]) at the same sensitivity (96·1%, 94·0–98·2) as the PI-RADS 3 or greater operating point. The lower boundary of the two-sided 95% Wald CI for the difference in specificity (−0·04) was greater than the non-inferiority margin (−0·05) and a p value below the significance threshold was reached (p<0·001). An AI system was superior to radiologists using PI-RADS (2.1), on average, at detecting clinically significant prostate cancer and comparable to the standard of care. Such a system shows the potential to be a supportive tool within a primary diagnostic setting, with several associated benefits for patients and radiologists. Prospective validation is needed to test clinical applicability of this system. Health~Holland and EU Horizon 2020. [ABSTRACT FROM AUTHOR]

Background: Significant aortic regurgitation (AR) leads to left ventricular (LV) remodeling; however, little data exist regarding sex-based differences in LV remodeling in this setting. We sought to compare LV remodeling and AR severity, assessed by echocardiography and cardiovascular magnetic resonance (CMR), to discern sex-based differences. Methods: Patients with ≥ moderate chronic AR by echocardiography who underwent CMR within 90 days between December 2005 and October 2015 were included. Nonlinear regression models were built to assess the effect of AR regurgitant fraction (RF) on LV remodeling. A generalized linear model and Bland Altman analyses were constructed to evaluate differences between CMR and echocardiography. Referral for surgical intervention based on symptoms and LV remodeling was evaluated. Results: Of the 243 patients (48.3 ± 16.6 years, 58 (24%) female), 119 (49%) underwent surgical intervention with a primary indication of severe AR, 97 (82%) men, 22 (18%) women. Significant sex differences in LV remodeling emerged on CMR. Women demonstrated significantly smaller LV end-diastolic volume index (LVEDVI) (96.8 ml/m2 vs 125.6 ml/m2, p < 0.001), LV end-systolic volume index (LVESVI) (41.1 vs 54.5 ml/m2, p < 0.001), blunted LV dilation in the setting of increasing AR severity (LVEDVI p value < 0.001, LVESVI p value 0.011), and LV length indexed (8.32 vs 9.69 cm, p < 0.001). On Bland Altman analysis, a significant interaction with sex and LV diameters was evident, demonstrating a significant increase in the difference between CMR and echocardiography measurements as the LV enlarged in women: LVEDVI (p = 0.006), LVESVI (p < 0.001), such that echocardiographic measurements increasingly underestimated LV diameters in women as the LV enlarged. LV length was higher for males with a linear effect from RF (p < 0.001), with LV length increasing at a higher rate with increasing RF for males compared to females (two-way interaction with sex p = 0.005). Sphericity volume index was higher for men after adjusting for a relative wall thickness (p = 0.033). Conclusions: CMR assessment of chronic AR revealed significant sex differences in LV remodeling and significant echocardiographic underestimation of LV dilation, particularly in women. Defining optimal sex-based CMR thresholds for surgical referral should be further developed. Trial registration: NA. [ABSTRACT FROM AUTHOR]

Background: Significant aortic regurgitation (AR) leads to left ventricular (LV) remodeling; however, little data exist regarding sex-based differences in LV remodeling in this setting. We sought to compare LV remodeling and AR severity, assessed by echocardiography and cardiovascular magnetic resonance (CMR), to discern sex-based differences. Methods: Patients with ≥ moderate chronic AR by echocardiography who underwent CMR within 90 days between December 2005 and October 2015 were included. Nonlinear regression models were built to assess the effect of AR regurgitant fraction (RF) on LV remodeling. A generalized linear model and Bland Altman analyses were constructed to evaluate differences between CMR and echocardiography. Referral for surgical intervention based on symptoms and LV remodeling was evaluated. Results: Of the 243 patients (48.3 ± 16.6 years, 58 (24%) female), 119 (49%) underwent surgical intervention with a primary indication of severe AR, 97 (82%) men, 22 (18%) women. Significant sex differences in LV remodeling emerged on CMR. Women demonstrated significantly smaller LV end-diastolic volume index (LVEDVI) (96.8 ml/m2 vs 125.6 ml/m2, p < 0.001), LV end-systolic volume index (LVESVI) (41.1 vs 54.5 ml/m2, p < 0.001), blunted LV dilation in the setting of increasing AR severity (LVEDVI p value < 0.001, LVESVI p value 0.011), and LV length indexed (8.32 vs 9.69 cm, p < 0.001). On Bland Altman analysis, a significant interaction with sex and LV diameters was evident, demonstrating a significant increase in the difference between CMR and echocardiography measurements as the LV enlarged in women: LVEDVI (p = 0.006), LVESVI (p < 0.001), such that echocardiographic measurements increasingly underestimated LV diameters in women as the LV enlarged. LV length was higher for males with a linear effect from RF (p < 0.001), with LV length increasing at a higher rate with increasing RF for males compared to females (two-way interaction with sex p = 0.005). Sphericity volume index was higher for men after adjusting for a relative wall thickness (p = 0.033). Conclusions: CMR assessment of chronic AR revealed significant sex differences in LV remodeling and significant echocardiographic underestimation of LV dilation, particularly in women. Defining optimal sex-based CMR thresholds for surgical referral should be further developed. Trial registration: NA. [ABSTRACT FROM AUTHOR]

Background: Significant aortic regurgitation (AR) leads to left ventricular (LV) remodeling; however, little data exist regarding sex-based differences in LV remodeling in this setting. We sought to compare LV remodeling and AR severity, assessed by echocardiography and cardiovascular magnetic resonance (CMR), to discern sex-based differences. Methods: Patients with ≥ moderate chronic AR by echocardiography who underwent CMR within 90 days between December 2005 and October 2015 were included. Nonlinear regression models were built to assess the effect of AR regurgitant fraction (RF) on LV remodeling. A generalized linear model and Bland Altman analyses were constructed to evaluate differences between CMR and echocardiography. Referral for surgical intervention based on symptoms and LV remodeling was evaluated. Results: Of the 243 patients (48.3 ± 16.6 years, 58 (24%) female), 119 (49%) underwent surgical intervention with a primary indication of severe AR, 97 (82%) men, 22 (18%) women. Significant sex differences in LV remodeling emerged on CMR. Women demonstrated significantly smaller LV end-diastolic volume index (LVEDVI) (96.8 ml/m2 vs 125.6 ml/m2, p < 0.001), LV end-systolic volume index (LVESVI) (41.1 vs 54.5 ml/m2, p < 0.001), blunted LV dilation in the setting of increasing AR severity (LVEDVI p value < 0.001, LVESVI p value 0.011), and LV length indexed (8.32 vs 9.69 cm, p < 0.001). On Bland Altman analysis, a significant interaction with sex and LV diameters was evident, demonstrating a significant increase in the difference between CMR and echocardiography measurements as the LV enlarged in women: LVEDVI (p = 0.006), LVESVI (p < 0.001), such that echocardiographic measurements increasingly underestimated LV diameters in women as the LV enlarged. LV length was higher for males with a linear effect from RF (p < 0.001), with LV length increasing at a higher rate with increasing RF for males compared to females (two-way interaction with sex p = 0.005). Sphericity volume index was higher for men after adjusting for a relative wall thickness (p = 0.033). Conclusions: CMR assessment of chronic AR revealed significant sex differences in LV remodeling and significant echocardiographic underestimation of LV dilation, particularly in women. Defining optimal sex-based CMR thresholds for surgical referral should be further developed. Trial registration: NA. [ABSTRACT FROM AUTHOR]

Objectives: Proton density fat fraction (PDFF) is a validated biomarker of tissue fat quantification. However, validation has been limited to single-center or multi-center series using non-FDA-approved software. Thus, we assess the bias, linearity, and long-term reproducibility of PDFF obtained using commercial PDFF packages from several vendors. Methods: Over 35 months, 438 subjects and 16 volunteers from a multi-center observational trial underwent PDFF MRI measurements using a 3-T MR system from one of three different vendors or a 1.5-T system from one vendor. Fat-water phantom sets were measured as part of each subject's examination. Manual region-of-interest measurements on the %fat image, then cross-sectional bias, linearity, and long-term reproducibility were assessed. Results: Three hundred ninety-two phantom measurements were evaluable (90%). Bias ranged from 2.4 to - 3.8% for the lowest to the highest weight %fat. Regression fits of PDFF against synthesis weight %fat showed negligible non-linear effects and a linear slope of 0.94 (95% confidence interval: 0.938, 0.947). We observed significant vendor (p < 0.001) and field strength (p < 0.001) differences in bias and longitudinal variability. When the results were pooled across sites, vendors, and field strengths, the estimated reproducibility coefficient was 6.93% (95% CI: 6.25%, 7.81%). Conclusions: This study demonstrated good linearity, accuracy, and reproducibility for all investigated manufacturers and field strengths. However, significant vendor-dependent and field strength–dependent bias were found. While longitudinal PDFF measurements may be made using different field strength or vendor MR systems, if the MR system is not the same, based on these results, only PDFF changes ≥ 7% can be considered a true difference. Key Points: • Phantom fat fraction (PDFF) MRI measurements over 35 months demonstrated good linearity, accuracy, and reproducibility for the vendor systems investigated. • Non-linear effects were negligible (linear slope of 0.94) over 0–100% fat; however, significant vendor (p < 0.001) and field strength (p<0.001) differences in bias and longitudinal variability were identified. Bias ranged from 2.4 to - 3.8% for 0–100 weight% fat, respectively. • Measurement bias could affect the accuracy of PDFF in clinical use. As the reproducibility coefficient was 6.93%, only greater changes in % fat can be considered true differences when making longitudinal PDFF measurements on different MR systems. [ABSTRACT FROM AUTHOR]

Introduction: Little is known about gender differences in ischemic mitral regurgitation (MR). Hypothesis: We hypothesized that women with ischemic cardiomyopathy (ICM) have greater degrees of MR leading to worse outcomes. Methods: We retrospectively evaluated ICM patients with cardiac magnetic resonance imaging (cMRI) and ECHO between 2002-06 and recorded treatment and survival outcomes. Generalized linear models were constructed to assess gender effects on LV and RV size, left atrial strain, and total scar burden and peri-infarct zone (PIZ) area (defined as signal intensity > 2 standard deviations and between 2 and 3 standard deviations of non-infarcted myocardium on delayed enhancement imaging, respectively). The effect of gender on MR severity by ECHO was assessed by a chi-square test. A Cox proportional hazards model was used to assess the interaction of gender and MR severity as a predictor of all-cause mortality adjusting for comorbidities, treatment (medical therapy vs revascularization), total scar and device therapy. Results: We studied 483 patients (25% women). Table 1 summarizes baseline characteristics and effect of gender on cMRI and ECHO data. Women had worse MR despite smaller indexed LV and RV volumes, and similar total scar burden and PIZ area. Estimated hazard ratios of worse outcomes in women with moderate or worse MR were higher than in men (HR >1) (Figure 1). Conclusions: Women with ICM have more severe MR despite smaller indexed LV and RV size and similar scar burden, and are at higher risk of worse outcomes than men with moderate or greater MR. Further research on how women with ICM remodel differently than men is needed to clarify these differences. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the feasibility of producing 2-dimensional (2D) virtual noncontrast images and 3-dimensional (3D) bone models from dual-energy computed tomography (DECT) arthrograms and to determine whether this is best accomplished using 190 keV virtual monoenergetic images (VMI) or virtual unenhanced (VUE) images. Materials and methods: VMI and VUE images were retrospectively reconstructed from patients with internal derangement of the shoulder or knee joint who underwent DECT arthrography between September 2017 and August 2019. A region of interest was placed in the area of brightest contrast, and the mean attenuation (in Hounsfield units [HUs]) was recorded. Two blinded musculoskeletal radiologists qualitatively graded the 2D images and 3D models using scores ranging from 0 to 3 (0 considered optimal). Results: Twenty-six patients (mean age ± SD, 57.5 ± 16.8 years; 6 women) were included in the study. The contrast attenuation on VUE images (overall mean ± SD, 10.5 ± 16.4 HU; knee, 19.3 ± 10.7 HU; shoulder, 5.0 ± 17.2 HU) was significantly lower (p < 0.001 for all comparisons) than on VMI (overall mean ± SD, 107.7 ± 43.8 HU; knee, 104.6 ± 31.1 HU; shoulder, 109.6 ± 51.0 HU). The proportion of cases with optimal scores (0 or 1) was significantly higher with VUE than with VMI for both 2D and 3D images (p < 0.001). Conclusions: DECT arthrography can be used to produce 2D virtual noncontrast images and to generate 3D bone models. The VUE technique is superior to VMI in producing virtual noncontrast images. [ABSTRACT FROM AUTHOR]

Background: Standard measures of response such as Response Evaluation Criteria in Solid Tumors are ineffective for bone lesions, often making breast cancer patients that have bone-dominant metastases ineligible for clinical trials with potentially helpful therapies. In this study we prospectively evaluated the test-retest uptake variability of 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) in a cohort of breast cancer patients with bone-dominant metastases to determine response criteria. The thresholds for 95% specificity of change versus no-change were then applied to a second cohort of breast cancer patients with bone-dominant metastases. Methods: For this study, nine patients with 38 bone lesions were imaged with 18F-FDG in the same calibrated scanner twice within 14 days. Tumor uptake was quantified by the most commonly used PET parameter, the maximum tumor voxel normalized by dose and body weight (SUVmax) and also by the mean of a 1-cc maximal uptake volume normalized by dose and lean-body-mass (SULpeak). The asymmetric repeatability coefficients with confidence intervals for SUVmax and SULpeak were used to determine the limits of 18F-FDG uptake variability. A second cohort of 28 breast cancer patients with bone-dominant metastases that had 146 metastatic bone lesions was imaged with 18F-FDG before and after standard-of-care therapy for response assessment. Results: The mean relative difference of SUVmax and SULpeak in 38 bone tumors of the first cohort were 4.3% and 6.7%. The upper and lower asymmetric limits of the repeatability coefficient were 19.4% and − 16.3% for SUVmax, and 21.2% and − 17.5% for SULpeak. 18F-FDG repeatability coefficient confidence intervals resulted in the following patient stratification using SULpeak for the second patient cohort: 11-progressive disease, 5-stable disease, 7-partial response, and 1-complete response with three inevaluable patients. The asymmetric repeatability coefficients response criteria for SULpeak changed the status of 3 patients compared to the standard Positron Emission Tomography Response Criteria in Solid Tumors of ± 30% SULpeak. Conclusion: In evaluating bone tumor response for breast cancer patients with bone-dominant metastases using 18F-FDG SUVmax, the repeatability coefficients from test-retest studies show that reductions of more than 17% and increases of more than 20% are unlikely to be due to measurement variability. Serial 18F-FDG imaging in clinical trials investigating bone lesions in these patients, such as the ECOG-ACRIN EA1183 trial, benefit from confidence limits that allow interpretation of response. [ABSTRACT FROM AUTHOR]

Purpose: Multiple commercial, open‐source, and academic software tools exist for objective quantification of lung density in computed tomography (CT) images. The purpose of this study was to evaluate the intersoftware reproducibility of CT lung density measurements. Methods: Computed tomography images from 50 participants from the COPDGeneTM cohort study were randomly selected for analysis; n = 10 participants across each global initiative for chronic obstructive lung disease (GOLD) grade (GOLD 0–IV). Academic‐based groups (n = 4) and commercial vendors (n = 4) participated anonymously to generate CT lung density measurements using their software tools. Computed tomography total lung volume (TLV), percentage of the low attenuation areas in the lung with Hounsfield unit (HU) values below −950HU (LAA950), and the HU value corresponding to the 15th percentile on the parenchymal density histogram (Perc15) were included in the analysis. The intersoftware bias and reproducibility coefficient (RDC) was generated with and without quality assurance (QA) for manual correction of the lung segmentation; intrasoftware bias and RDC was also generated by repeated measurements on the same images. Results: Intersoftware mean bias was within ±0.22 mL, ±0.46%, and ±0.97 HU for TLV, LAA950 and Perc15, respectively. The RDC was 0.35 L, 1.2% and 1.8 HU for TLV, LAA950 and Perc15, respectively. Intersoftware RDC remained unchanged following QA: 0.35 L, 1.2% and 1.8 HU for TLV, LAA950 and Perc15, respectively. All software investigated had an intrasoftware RDC of 0. The RDC was comparable for TLV, LAA950 and Perc15 measurements, respectively, for academic‐based groups/commercial vendor‐based software tools: 0.39 L/0.32 L, 1.2%/1.2%, and 1.7 HU/1.6 HU. Multivariable regression analysis showed that academic‐based software tools had greater within‐subject standard deviation of TLV than commercial vendors, but no significant differences between academic and commercial groups were found for LAA950 or Perc15 measurements. Conclusions: Computed tomography total lung volume and lung density measurement bias and reproducibility was reported across eight different software tools. Bias was negligible across vendors, reproducibility was comparable for software tools generated by academic‐based groups and commercial vendors, and segmentation QA had negligible impact on measurement variability between software tools. In summary, results from this study report the amount of additional measurement variability that should be accounted for when using different software tools to measure lung density longitudinally with well‐standardized image acquisition protocols. However, intrasoftware reproducibility was deterministic for all cases so use of the same software tool to reduce variability for serial studies is highly recommended. [ABSTRACT FROM AUTHOR]

Background: Injecting bioactive substances into the knee is common in orthopaedic practice, and recently it has been shown to mitigate risk factors for posttraumatic osteoarthritis. Therefore, understanding the influence of these injections on postoperative infection rate is imperative. Hypothesis: Postinjury aspiration and corticosteroid injection (CSI) of the knee before anterior cruciate ligament (ACL) reconstruction (ACLR) would not increase the risk of postoperative infection. Study Design: Cohort Study; Level of evidence, 3. Methods: All patients between the ages of 10 and 65 years who underwent primary bone–patellar tendon–bone ACLR by 1 fellowship-trained sports medicine orthopaedic surgeon between January 1, 2011, and September 8, 2020, at 1 of 2 major academic centers were evaluated for inclusion. A total of 693 patients were included, with 273 patients receiving postinjury and preoperative aspiration and CSI. A postoperative infection was defined as a patient returning to the operating room for an intra-articular washout. The intervals—measured in days—between the CSI and ACLR and between ACLR and the final follow-up were recorded. To further evaluate the infection risk in each cohort (total cohort; aspiration and injection cohort; no aspiration and injection cohort), the upper 95% confidence bound for the infection risk was calculated for each cohort. Results: There were no postoperative infections in the 693 patients included in this study. The upper 95% confidence bounds were 0.4%, 1.1%, and 0.7% for the total cohort, the cohort that underwent aspiration and injection, and the cohort that did not, respectively. The median number of days between the surgical date and that of the aspiration and injection was 34 days, and the mean follow-up for the entire cohort was 337.4 days (95% CI, 307.6-367.3). Conclusion: Postinjury and preoperative aspiration and CSI is a safe intervention that can be used before ACLR. Future studies with larger sample sizes, longer patient follow-ups, and multiple surgeons would be helpful to both better understand infection risk and better identify the influence of CSI on preventing posttraumatic osteoarthritis. [ABSTRACT FROM AUTHOR]

Purpose: To compare diagnostic performance of a 5-min knee MRI protocol to that of a standard knee MRI.Materials and Methods: One hundred 3 T (100 patients, mean 38.8 years) and 50 1.5 T (46 patients, mean 46.4 years) MRIs, consisting of 5 fast, 2D multi-planar fast-spin-echo (FSE) sequences and five standard multiplanar FSE sequences, from two academic centers (1/2015-1/2016), were retrospectively reviewed by four musculoskeletal radiologists. Agreement between fast and standard (interprotocol agreement) and between standard (intraprotocol agreement) readings for meniscal, ligamentous, chondral, and bone pathology was compared for interchangeability. Frequency of major findings, sensitivity, and specificity was also tested for each protocol.Results: Interprotocol agreement using fast MRI was similar to intraprotocol agreement with standard MRI (83.0-99.5%), with no excess disagreement (≤ 1.2; 95% CI, -4.2 to 3.8%), across all structures. Frequency of major findings (1.1-22.4% across structures) on fast and standard MRI was not significantly different (p ≥ 0.215), except more ACL tears on fast MRI (p = 0.021) and more cartilage defects on standard MRI (p < 0.001). Sensitivities (59-100%) and specificities (73-99%) of fast and standard MRI were not significantly different for meniscal and ligament tears (95% CI for difference, -0.08-0.08). For cartilage defects, fast MRI was slightly less sensitive (95% CI for difference, -0.125 to -0.01) but slightly more specific (95% CI for difference, 0.01-0.5) than standard MRI.Conclusion: A fast 5-min MRI protocol is interchangeable with and has similar accuracy to a standard knee MRI for evaluating internal derangement of the knee. [ABSTRACT FROM AUTHOR]

Background: Accurate and consistent regional lymph node classification is an important element in the staging and multidisciplinary management of lung cancer. Regional lymph node definition sets-lymph node maps-have been created to standardize regional lymph node classification. In 2009, the International Association for the Study of Lung Cancer (IASLC) introduced a lymph node map to supersede all preexisting lymph node maps. Our aim was to study if and how lung cancer specialists apply the IASLC lymph node map when classifying thoracic lymph nodes encountered on CT scans during lung cancer staging.Methods: From April 2013 through July 2013, invitations were distributed to all members of the Fleischner Society, Society of Thoracic Radiology, General Thoracic Surgical Club, and the American Association of Bronchology and Interventional Pulmonology to participate in an anonymous online image-based and text-based 20-question survey regarding lymph node classification for lung cancer staging on CT imaging.Results: Three hundred thirty-seven people responded (approximately 25% participation). Respondents consisted of self-reported thoracic radiologists (n = 158), thoracic surgeons (n = 102), and pulmonologists who perform endobronchial ultrasonography (n = 77). Half of the respondents (50%; 95% CI, 44%-55%) reported using the IASLC lymph node map in daily practice, with no significant differences between subspecialties. A disparity was observed between the IASLC definition sets and their interpretation and application on CT scans, in particular for lymph nodes near the thoracic inlet, anterior to the trachea, anterior to the tracheal bifurcation, near the ligamentum arteriosum, between the bronchus intermedius and esophagus, in the internal mammary space, and adjacent to the heart.Conclusions: Use of older lymph node maps and inconsistencies in interpretation and application of definitions in the IASLC lymph node map may potentially lead to misclassification of stage and suboptimal management of lung cancer in some patients. [ABSTRACT FROM AUTHOR]

Location bias occurs when a reader detects a false lesion in a subject with disease and the falsely detected lesion is considered a true positive. In this study, we examine the effect of location bias in two large MRMC ROC studies, comparing three ROC scoring methods. We compare one method that only uses the maximum confidence score and does not take location bias into account (maxROC), and two methods that take location bias into account: the region of interest ROC (ROI–ROC) and the free-response ROC (FROC). In both studies, when comparing two modalities' ROC areas without adjusting for location bias, the effect size depends on the difference in the frequency of location bias between the two modalities. When the difference in frequency is small, the effect size is similar whether the location bias is corrected for or not. However, when the frequency of location bias is dissimilar, failure to correct for the location bias favors the modality with higher false positive rate. Location bias should be corrected when the next step in the clinical management of the patient depends on the specific location of the detected lesion and/or when the frequency of the bias is dissimilar between the two modalities. [ABSTRACT FROM AUTHOR]

Background Cerebral angiography remains the gold standard for the detection of mycotic aneurysms, and it has been estimated that ruptured mycotic aneurysms result in 5% of the neurological complications of patients with infective endocarditis (IE). Objective To determine the diagnostic yield of cerebral angiography in the above patient population and to assess patient factors that might suggest greater or lesser utility. Methods We retrospectively reviewed 168 patients who underwent cerebral angiography with a diagnosis of IE or infected left ventricular assist device at the Cleveland Clinic between January 2003 and March 2010 in accordance with institutional review board guidelines. Chart and imaging review was performed. Results 15/168 patients (8.9%) had mycotic aneurysms; 93.3% (14/15) of the patients with mycotic aneurysms presented with CNS hemorrhage and 66.7% (10/15) had acute ischemic findings. Of the 15 patients with mycotic aneurysms on angiography, seven underwent CT angiography and six underwent MR angiography, which showed mycotic aneurysms in three (42.9%) and two cases (one of which was questionable; 33.3%), respectively. Conclusions Patients with IE or similar sources of central bacterial emboli are prone to neurovascular complications. Approximately 9% of patients with IE at our institution who undergo cerebral angiography have mycotic aneurysms. Presentation with hemorrhage appears to be more predictive of aneurysm, as approximately 22% of patients with IE and hemorrhage were found to have an aneurysm compared with only 1% when hemorrhage was absent. Thus, patients with IE presenting with intracranial hemorrhage should undergo vascular imaging, preferably with cerebral angiography. [ABSTRACT FROM AUTHOR]

Objective: Iterative metal artifact reduction (IMAR) is a sinogram inpainting technique that incorporates high-frequency data from standard weighted filtered back projection (WFBP) reconstructions to reduce metal artifact on computed tomography (CT). This study was designed to compare the image quality of IMAR and WFBP in total shoulder arthroplasties (TSA); determine the optimal amount of WFBP high-frequency data needed for IMAR; and compare image quality of the standard 3D technique with that of a faster 2D technique. Materials and methods: Eight patients with nine TSA underwent CT with standardized parameters: 140 kVp, 300 mAs, 0.6 mm collimation and slice thickness, and B30 kernel. WFBP, three 3D IMAR algorithms with different amounts of WFBP high-frequency data (IMARlo, lowest; IMARmod, moderate; IMARhi, highest), and one 2D IMAR algorithm were reconstructed. Differences in attenuation near hardware and away from hardware were measured and compared using repeated measures ANOVA. Five readers independently graded image quality; scores were compared using Friedman's test. Results: Attenuation differences were smaller with all 3D IMAR techniques than with WFBP ( p < 0.0063). With increasing high-frequency data, the attenuation difference increased slightly (differences not statistically significant). All readers ranked IMARmod and IMARhi more favorably than WFBP ( p < 0.05), with IMARmod ranked highest for most structures. The attenuation difference was slightly higher with 2D than with 3D IMAR, with no significant reader preference for 3D over 2D. Conclusions: IMAR significantly decreases metal artifact compared to WFBP both objectively and subjectively in TSA. The incorporation of a moderate amount of WFBP high-frequency data and use of a 2D reconstruction technique optimize image quality and allow for relatively short reconstruction times. [ABSTRACT FROM AUTHOR]

A correction to the article "Sex-based differences in left ventricular remodeling in patients with chronic aortic regurgitation: A multi-modality study" that was published in the June 28, 2022 online issue is presented.

Longitudinal and behavioral preclinical animal studies generate complex data, which may not be well matched to statistical approaches common in this literature. Analyses that do not adequately account for complexity may result in overly optimistic study conclusions, with consequences for reproducibility and translational decision-making. Recent work interrogating methodological shortcomings in animal research has not yet comprehensively investigated statistical shortcomings in the analysis of complex longitudinal and behavioral data. To this end, the current cross-sectional meta-research study rigorously reviewed published mouse or rat controlled experiments for motor rehabilitation in three neurologic conditions to evaluate statistical choices and reporting. Medline via PubMed was queried in February 2020 for English-language articles published January 1, 2017- December 31, 2019. Included were articles that used rat or mouse models of stroke, Parkinson's disease, or traumatic brain injury, employed a therapeutic controlled experimental design to determine efficacy, and assessed at least one functional behavioral assessment or global evaluation of function. 241 articles from 99 journals were evaluated independently by a team of nine raters. Articles were assessed for statistical handling of non-independence, animal attrition, outliers, ordinal data, and multiplicity. Exploratory analyses evaluated whether transparency or statistical choices differed as a function of journal factors. A majority of articles failed to account for sources of non-independence in the data (74–93%) and/or did not analytically account for mid-treatment animal attrition (78%). Ordinal variables were often treated as continuous (37%), outliers were predominantly not mentioned (83%), and plots often concealed the distribution of the data (51%) Statistical choices and transparency did not differ with regards to journal rank or reporting requirements. Statistical misapplication can result in invalid experimental findings and inadequate reporting obscures errors. Clinician-scientists evaluating preclinical work for translational promise should be mindful of commonplace errors. Interventions are needed to improve statistical decision-making in preclinical behavioral neurosciences research. [ABSTRACT FROM AUTHOR]

Background: Patients undergoing anterior cruciate ligament reconstruction (ACLR) are at an increased risk for posttraumatic osteoarthritis (PTOA). While we have previously shown that meniscal treatment with ACLR predicts more radiographic PTOA at 2 to 3 years postoperatively, there are a limited number of similar studies that have assessed cartilage directly with magnetic resonance imaging (MRI). Hypothesis: Meniscal repair or partial meniscectomy at the time of ACLR independently predicts more articular cartilage damage on 2- to 3-year postoperative MRI compared with a healthy meniscus or a stable untreated tear. Study Design: Cohort study; Level of evidence, 2. Methods: A consecutive series of patients undergoing ACLR from 1 site within the prospective, nested Multicenter Orthopaedic Outcomes Network (MOON) cohort underwent bilateral knee MRI at 2 to 3 years postoperatively. Patients were aged <36 years without previous knee injuries, were injured while playing sports, and had no history of concomitant ligament surgery or contralateral knee surgery. MRI scans were graded by a board-certified musculoskeletal radiologist using the modified MRI Osteoarthritis Knee Score (MOAKS). A proportional odds logistic regression model was built to predict a MOAKS-based cartilage damage score (CDS) relative to the contralateral control knee for each compartment as well as for the whole knee, pooled by meniscal treatment, while controlling for sex, age, body mass index, baseline Marx activity score, and baseline operative cartilage grade. For analysis, meniscal injuries surgically treated with partial meniscectomy or meniscal repair were grouped together. Results: The cohort included 60 patients (32 female; median age, 18.7 years). Concomitant meniscal treatment at the time of index ACLR was performed in 17 medial menisci (13 meniscal repair and 4 partial meniscectomy) and 27 lateral menisci (3 meniscal repair and 24 partial meniscectomy). Articular cartilage damage was worse in the ipsilateral reconstructed knee (P <.001). A meniscal injury requiring surgical treatment with ACLR predicted a worse CDS for medial meniscal treatment (medial compartment CDS: P =.005; whole joint CDS: P <.001) and lateral meniscal treatment (lateral compartment CDS: P =.038; whole joint CDS: P =.863). Other predictors of a worse relative CDS included age for the medial compartment (P <.001), surgically observed articular cartilage damage for the patellofemoral compartment (P =.048), and body mass index (P =.007) and age (P =.020) for the whole joint. Conclusion: A meniscal injury requiring surgical treatment with partial meniscectomy or meniscal repair at the time of ACLR predicted worse articular cartilage damage on MRI at 2 to 3 years after surgery. Further research is required to differentiate between the effects of partial meniscectomy and meniscal repair. [ABSTRACT FROM AUTHOR]

Background: High levels of humeral torsion allow baseball pitchers to achieve maximum external rotation in the late cockingphase of pitching with lower twisting and shear forces on the long head of the biceps tendon and rotator cuff tendons.Hypothesis: Humeral torsion is inversely related to the incidence and severity of shoulder injuries and other upper extremityinjuries in professional baseball pitchers.Study Design: Case-control study; Level of evidence, 3.Methods: A total of 25 professional pitchers from a single Major League Baseball organization were prospectively recruited intothis study. Computed tomography (CT) was performed on dominant and nondominant humeri, and image data were processedwith a 3-dimensional volume-rendering postprocessing program. The software program was then modified to model a simplifiedthrowing motion and to measure potential internal impingement distances in a small subset of players. Players were followed for 2years after CT, and the number of days missed from pitching activities was recorded as a measure of injury severity andincidence.Results: The mean dominant humeral torsion was 38.5° ± 8.9°; the mean nondominant humeral torsion was 27.6° ± 8.0°. Thedifference between dominant and nondominant torsions was significant (P<.0001). Among the 11 pitchers (44%) injured duringfollow-up, 5 players had shoulder injuries, 7 had elbow injuries, and 2 had finger injuries. Dominant humeral torsion was a statisticallysignificant predictor of severe injuries (≥30 days; P = .048) but not of milder injuries. Among injured players, higher numbersof days missed because of injury were strongly correlated with lower degrees of dominant humeral torsion (r = 20.78; P = .005)and smaller differences between dominant and nondominant humeral torsions (r = 20.59; P = .055). There was no significantassociation between the incidence of shoulder injury and minimum glenoid-tuberosity distance in the dominant or nondominantshoulder or degree of dominant glenoid version.Conclusion: A strong relationship was found between lower degrees of dominant humeral torsion and more severe upperextremity injuries as well as a trend relating lower side-to-side differences in torsion with more severe dominant upper extremityinjuries. In addition, there was a higher incidence of severe injuries in players with lower degrees of dominant torsion. If futurestudies confirm these results, humeral torsion measurements could play a role in risk assessment in pitchers. [ABSTRACT FROM AUTHOR]

Background: Epsilon aminocaproic acid (EACA) has been used in the past to prevent cerebral aneurysm rerupture. Recent studies have indicated that short-term treatment with EACA can lower rebleeding rates without significantly increasing ischemic or thrombotic complications or permanent shunt rates. The goal of this study is to determine the efficacy of EACA in the prevention of aneurysm rerupture at a high volume subarachnoid hemorrhage center. Methods: We conducted a retrospective study of 355 consecutive subarachnoid hemorrhage patients over a 2-year period under our current protocol for EACA use. Patients were divided by presentation time to our institution and whether the patient received EACA. The primary endpoints of the study were rebleeding rates, ischemic complications, thrombotic complications, vasospasm, shunt rates, and outcomes. Results: Rerupture rates were reduced by half in the entire pool of patients on EACA after controlling for Hunt and Hess Scores and Fisher Scores. In patients who received early aneurysm treatment, this effect persisted but was non-statistically significant due to the small numbers of reruptures. In addition, there was no evidence to suggest that EACA increased ischemic or thrombotic complications, vasospasm, or VPS rates. In patients presenting earlier than 24 h to our institution, there was a non-significant trend toward worse outcomes after EACA use. This trend was reversed in patients arriving after 24 h. Conclusion: There is evidence to suggest that EACA is protective from aneurysm rerupture without significant ischemic or thrombotic complications when used for less than 72 h. However, if the aneurysm is treated, this effect is modest indicating that early aneurysm treatment remains the gold standard for rerupture prevention. [ABSTRACT FROM AUTHOR]

Abstract: Objective: The aim of the work described here was to characterize quality of life (QOL) and its determinants in a large cohort of adult patients with epilepsy. Methods: Validated measures reflecting disease severity and psychosocial functioning were electronically collected on all outpatients seen during 2009. Multivariate regression adjusting for repeated measures identified determinants of QOL, as defined by the Quality of Life in Epilepsy Questionnaire-10 (QOLIE-10). Results: Seven thousand seven hundred eighty-four visits from patients with epilepsy were identified. The questionnaire completion rate was 77%, yielding 5960 records corresponding to 1931 individual patients for analysis. Following multivariate modeling, the two most clinically significant QOL predictors were seizure severity (mean QOLIE-10 score=28.8 if LSSS>40 vs 19.2 otherwise) and depression (mean QOLIE-10 score=31.7 if PHQ-9≥10 vs 19.3 otherwise). Conclusions: Optimizing quality of life in patients with epilepsy requires an approach that extends beyond controlling seizures. Collection of validated health status measures improving patient management is possible within the setting of routine clinical care. [Copyright &y& Elsevier]

Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials. Key Points: • Data-driven processes like radiomics risk false discoveries due to high-dimensionality of the dataset compared to sample size, making adequate diversity of the data, cross-validation and external validation essential to mitigate the risks of spurious associations and overfitting. • Use of radiomic signatures within clinical trials requires multistep standardisation of image acquisition, image analysis and data mining processes. • Biological correlation may be established after clinical validation but is not mandatory. [ABSTRACT FROM AUTHOR]

Purpose: To compare the bias and inherent reliability of the quantitative (T1 and T2) imaging metrics generated from the magnetic resonance fingerprinting (MRF) technique using the ISMRM/NIST system phantom in an international multicenter setting. Method: ISMRM/NIST MRI system phantom provides standard reference T1 and T2 relaxation values (vendor‐provided) for each of the 14 vials in T1 and T2 arrays. MRF‐SSFP scans repeated over 30 days on GE 1.5 and 3.0 T scanners at three collaborative centers. MRF estimated T1, and T2 values averaged over 30 days were compared with the phantom vendor‐provided and spin‐echo (SE) based convention gold standard (GS) method. Repeatability and reproducibility were characterized by the within‐case coefficient of variation (wCV) of the MRF data acquired over 30 days, along with the biases. Result: For the wide ranges of MRF estimated T1 values, vials #1‐8 (T1 relaxation time between 2033 and 184 ms) exhibited a wCV less than 3% and 4%, respectively, on 3.0 and 1.5 T scanners. T2 values in vials #1‐8 (T2 relaxation, 1044‐45 ms) have shown wCV to be <7% on both 3.0 and 1.5 T scanners. A stronger linear correlation overall for T1 (R2 = 0.9960 and 0.9963 at center‐1 and center‐2 on 3.0 T scanner, and R2 = 0.9951 and 0.9988 at center‐1 and center‐3 on 1.5 T scanner) compared to T2 (R2 = 0.9971 and 0.9972 at center‐1 and center‐2 on 3.0 T scanner, and R2 = 0.9815 and 0.9754 at center‐1 and center‐3 on 1.5 T scanner). Bland–Altman (BA) analysis showed MRF based T1 and T2 values were within the limit of agreement (LOA) except for one data point. The mean difference or bias and 95% lower bound (LB) and upper bound (UB) LOA are reported in the format; mean bias: 95% LB LOA: 95% UB LOA. The biases for T1 values were 21.34: −50.00: 92.69, 21.32: −47.29: 89.94 ms, and for T2 values were −19.88: −42.37: 2.61, −19.06: −43.58: 5.45 ms on 3.0 T scanner at center‐1 and center‐2, respectively. Similarly, on 1.5 T scanner biases for T1 values were 26.54: −53.41: 106.50, 9.997: −51.94: 71.94 ms, and for T2 values were −23.84: −135.40: 87.76, −37.30: 134.30: 59.73 ms at center‐1 and center‐3, respectively. Additionally, the correlation between the SE based GS and MRF estimated T1 and T2 values (R2 = 0.9969 and 0.9977) showed a similar trend as we observed between vendor‐provided and MRF estimated T1 and T2 values (R2 = 0.9963 and 0.9972). In addition to correlation, BA analysis showed that all the vials are within the LOA between the GS and vendor‐provided for the T1 values and except one vial for T2. All the vials are within the LOA between GS and MRF except one vial in T1 and T2 array. The wCV for reproducibility was <3% for both T1 and T2 values in vials #1‐8, for all the 14 vials, wCV calculated for reproducibility was <4% for T1 values and <5% for T2. Conclusion: This study shows that MRF is highly repeatable (wCV <4% for T1 and <7% for T2) and reproducible (wCV < 3% for both T1 and T2) in certain vials (vials #1‐8). [ABSTRACT FROM AUTHOR]

Objective: To determine whether a simulated low-dose metal artifact reduction (MAR) CT technique is comparable with a clinical dose MAR technique for shoulder arthroplasty evaluation. Materials and methods: Two shoulder arthroplasties in cadavers and 25 shoulder arthroplasties in patients were scanned using a clinical dose (140 kVp, 300 qrmAs); cadavers were also scanned at half dose (140 kVp, 150 qrmAs). Images were reconstructed using a MAR CT algorithm at full dose and a noise-insertion algorithm simulating 50% dose reduction. For the actual and simulated half-dose cadaver scans, differences in SD for regions of interest were assessed, and streak artifact near the arthroplasty was graded by 3 blinded readers. Simulated half-dose scans were compared with full-dose scans in patients by measuring differences in implant position and by comparing readers' grades of periprosthetic osteolysis and muscle atrophy. Results: The mean difference in SD between actual and simulated half-dose methods was 2.42 HU (95% CI [1.4, 3.4]). No differences in streak artifact grades were seen in 13/18 (72.2%) comparisons in cadavers. In patients, differences in implant position measurements were within 1° or 1 mm in 149/150 (99.3%) measurements. The inter-reader agreement rates were nearly identical when readers were using full-dose (77.3% [232/300] for osteolysis and 76.9% [173/225] for muscle atrophy) and simulated half-dose (76.7% [920/1200] for osteolysis and 74.0% [666/900] for muscle atrophy) scans. Conclusion: A simulated half-dose MAR CT technique is comparable both quantitatively and qualitatively with a standard-dose technique for shoulder arthroplasty evaluation, demonstrating that this technique could be used to reduce dose in arthroplasty imaging. [ABSTRACT FROM AUTHOR]