Variable selection for joint models of multivariate skew-normal longitudinal and survival data.

Many joint models of multivariate skew-normal longitudinal and survival data have been presented to accommodate for the non-normality of longitudinal outcomes in recent years. But existing work did not consider variable selection. This article investigates simultaneous parameter estimation and variable selection in joint modeling of longitudinal and survival data. The penalized splines technique is used to estimate unknown log baseline hazard function, the rectangle integral method is adopted to approximate conditional survival function. Monte Carlo expectation-maximization algorithm is developed to estimate model parameters. Based on local linear approximations to conditional expectation of likelihood function and penalty function, a one-step sparse estimation procedure is proposed to circumvent the computationally challenge in optimizing the penalized conditional expectation of likelihood function, which is utilized to select significant covariates and trajectory functions, and identify the departure from normality of longitudinal data. The conditional expectation of likelihood function-based Bayesian information criterion is developed to select the optimal tuning parameter. Simulation studies and a real example from the clinical trial are used to illustrate the proposed methodologies.

Design of a Low-Cost, Self-Adaptive and MRI-Compatible Cardiac Gating System.

OBJECTIVE: Cardiac gating, synchronizing medical scans with cardiac activity, is widely used to make quantitative measurements of physiological events and to obtain high-quality scans free of pulsatile artefacts. This can provide important information for disease diagnosis, targeted control of medical microrobots, etc. The current work proposes a low-cost, self-adaptive, MRI-compatible cardiac gating system. METHOD: The system and its processing algorithm, based on the monitoring and analysis of blood pressure waveforms, are proposed. The system is tested in an in vitro experiment and two living pigs using four-dimensional (4D) flow magnetic resonance imaging (MRI) and two-dimensional phase-contrast (2D-PC) sequences. RESULTS: in vitro and in vivo experiments reveal that the proposed system can provide stable cardiac synchronicity, has good MRI compatibility, and can cope with the fringe magnetic field of the MRI scanner, radiofrequency signals during image acquisition, and heart rate changes. High-resolution 4D flow imaging is successfully acquired both in vivo and in vitro. The difference between the 2D and 4D measurements is ≤ 21%. The incidence of false triggers is 0% in all tests, which is unattainable for other known cardiac gating methods. CONCLUSION: The system has good MRI compatibility and can provide a stable and accurate trigger signal based on pressure waveform. It opens the door to applications where the previous gating methods were difficult to implement or not applicable.

A Multicenter Assessment of Interreader Reliability of LI-RADS Version 2018 for MRI and CT.

Background Various limitations have impacted research evaluating reader agreement for Liver Imaging Reporting and Data System (LI-RADS). Purpose To assess reader agreement of LI-RADS in an international multicenter multireader setting using scrollable images. Materials and Methods This retrospective study used deidentified clinical multiphase CT and MRI and reports with at least one untreated observation from six institutions and three countries; only qualifying examinations were submitted. Examination dates were October 2017 to August 2018 at the coordinating center. One untreated observation per examination was randomly selected using observation identifiers, and its clinically assigned features were extracted from the report. The corresponding LI-RADS version 2018 category was computed as a rescored clinical read. Each examination was randomly assigned to two of 43 research readers who independently scored the observation. Agreement for an ordinal modified four-category LI-RADS scale (LR-1, definitely benign; LR-2, probably benign; LR-3, intermediate probability of malignancy; LR-4, probably hepatocellular carcinoma [HCC]; LR-5, definitely HCC; LR-M, probably malignant but not HCC specific; and LR-TIV, tumor in vein) was computed using intraclass correlation coefficients (ICCs). Agreement was also computed for dichotomized malignancy (LR-4, LR-5, LR-M, and LR-TIV), LR-5, and LR-M. Agreement was compared between research-versus-research reads and research-versus-clinical reads. Results The study population consisted of 484 patients (mean age, 62 years ± 10 [SD]; 156 women; 93 CT examinations, 391 MRI examinations). ICCs for ordinal LI-RADS, dichotomized malignancy, LR-5, and LR-M were 0.68 (95% CI: 0.61, 0.73), 0.63 (95% CI: 0.55, 0.70), 0.58 (95% CI: 0.50, 0.66), and 0.46 (95% CI: 0.31, 0.61) respectively. Research-versus-research reader agreement was higher than research-versus-clinical agreement for modified four-category LI-RADS (ICC, 0.68 vs 0.62, respectively; P = .03) and for dichotomized malignancy (ICC, 0.63 vs 0.53, respectively; P = .005), but not for LR-5 (P = .14) or LR-M (P = .94). Conclusion There was moderate agreement for LI-RADS version 2018 overall. For some comparisons, research-versus-research reader agreement was higher than research-versus-clinical reader agreement, indicating differences between the clinical and research environments that warrant further study. © RSNA, 2023 Supplemental material is available for this article. See also the editorials by Johnson and Galgano and Smith in this issue.

Assessment of Radiology Artificial Intelligence Software: A Validation and Evaluation Framework.

Artificial intelligence (AI) software in radiology is becoming increasingly prevalent and performance is improving rapidly with new applications for given use cases being developed continuously, oftentimes with development and validation occurring in parallel. Several guidelines have provided reporting standards for publications of AI-based research in medicine and radiology. Yet, there is an unmet need for recommendations on the assessment of AI software before adoption and after commercialization. As the radiology AI ecosystem continues to grow and mature, a formalization of system assessment and evaluation is paramount to ensure patient safety, relevance and support to clinical workflows, and optimal allocation of limited AI development and validation resources before broader implementation into clinical practice. To fulfil these needs, we provide a glossary for AI software types, use cases and roles within the clinical workflow; list healthcare needs, key performance indicators and required information about software prior to assessment; and lay out examples of software performance metrics per software category. This conceptual framework is intended to streamline communication with the AI software industry and provide healthcare decision makers and radiologists with tools to assess the potential use of these software. The proposed software evaluation framework lays the foundation for a radiologist-led prospective validation network of radiology AI software. Learning Points: The rapid expansion of AI applications in radiology requires standardization of AI software specification, classification, and evaluation. The Canadian Association of Radiologists' AI Tech & Apps Working Group Proposes an AI Specification document format and supports the implementation of a clinical expert evaluation process for Radiology AI software.

Assessment of hepatic arterial hemodynamics with 4D flow MRI: in vitro analysis of motion and spatial resolution related error and in vivo feasibility study in 20 volunteers.

OBJECTIVES: To assess the ability of four-dimensional (4D) flow MRI to measure hepatic arterial hemodynamics by determining the effects of spatial resolution and respiratory motion suppression in vitro and its applicability in vivo with comparison to two-dimensional (2D) phase-contrast MRI. METHODS: A dynamic hepatic artery phantom and 20 consecutive volunteers were scanned. The accuracies of Cartesian 4D flow sequences with k-space reordering and navigator gating at four spatial resolutions (0.5- to 1-mm isotropic) and navigator acceptance windows (± 8 to ± 2 mm) and one 2D phase-contrast sequence (0.5-mm in -plane) were assessed in vitro at 3 T. Two sequences centered on gastroduodenal and hepatic artery branches were assessed in vivo for intra - and interobserver agreement and compared to 2D phase-contrast. RESULTS: In vitro, higher spatial resolution led to a greater decrease in error than narrower navigator window (30.5 to -4.67% vs -6.64 to -4.67% for flow). In vivo, hepatic and gastroduodenal arteries were more often visualized with the higher resolution sequence (90 vs 71%). Despite similar interobserver agreement (κ = 0.660 and 0.704), the higher resolution sequence had lower variability for area (CV = 20.04 vs 30.67%), flow (CV = 34.92 vs 51.99%), and average velocity (CV = 26.47 vs 44.76%). 4D flow had lower differences between inflow and outflow at the hepatic artery bifurcation (11.03 ± 5.05% and 15.69 ± 6.14%) than 2D phase-contrast (28.77 ± 21.01%). CONCLUSION: High-resolution 4D flow can assess hepatic artery anatomy and hemodynamics with improved accuracy, greater vessel visibility, better interobserver reliability, and internal consistency. KEY POINTS: • Motion-suppressed Cartesian four-dimensional (4D) flow MRI with higher spatial resolution provides more accurate measurements even when accepted respiratory motion exceeds voxel size. • 4D flow MRI with higher spatial resolution provides substantial interobserver agreement for visualization of hepatic artery branches. • Lower peak and average velocities and a trend toward better internal consistency were observed with 4D flow MRI as compared to 2D phase-contrast.

Quantitative ultrasound, elastography, and machine learning for assessment of steatosis, inflammation, and fibrosis in chronic liver disease.

OBJECTIVE: To develop a quantitative ultrasound (QUS)- and elastography-based model to improve classification of steatosis grade, inflammation grade, and fibrosis stage in patients with chronic liver disease in comparison with shear wave elastography alone, using histopathology as the reference standard. METHODS: This ancillary study to a prospective institutional review-board approved study included 82 patients with non-alcoholic fatty liver disease, chronic hepatitis B or C virus, or autoimmune hepatitis. Elastography measurements, homodyned K-distribution parametric maps, and total attenuation coefficient slope were recorded. Random forests classification and bootstrapping were used to identify combinations of parameters that provided the highest diagnostic accuracy. Receiver operating characteristic (ROC) curves were computed. RESULTS: For classification of steatosis grade S0 vs. S1-3, S0-1 vs. S2-3, S0-2 vs. S3, area under the receiver operating characteristic curve (AUC) were respectively 0.60, 0.63, and 0.62 with elasticity alone, and 0.90, 0.81, and 0.78 with the best tested model combining QUS and elastography features. For classification of inflammation grade A0 vs. A1-3, A0-1 vs. A2-3, A0-2 vs. A3, AUCs were respectively 0.56, 0.62, and 0.64 with elasticity alone, and 0.75, 0.68, and 0.69 with the best model. For classification of liver fibrosis stage F0 vs. F1-4, F0-1 vs. F2-4, F0-2 vs. F3-4, F0-3 vs. F4, AUCs were respectively 0.66, 0.77, 0.72, and 0.74 with elasticity alone, and 0.72, 0.77, 0.77, and 0.75 with the best model. CONCLUSION: Random forest models incorporating QUS and shear wave elastography increased the classification accuracy of liver steatosis, inflammation, and fibrosis when compared to shear wave elastography alone.

Assessment of hepatocellular carcinoma treatment response with LI-RADS: a pictorial review.

Computed tomography (CT) and magnetic resonance imaging (MRI) play critical roles for assessing treatment response of hepatocellular carcinoma (HCC) after locoregional therapy. Interpretation is challenging because posttreatment imaging findings depend on the type of treatment, magnitude of treatment response, time interval after treatment, and other factors. To help radiologists interpret and report treatment response in a clear, simple, and standardized manner, the Liver Imaging Reporting and Data System (LI-RADS) has developed a Treatment Response (LR-TR) algorithm. Introduced in 2017, the system provides criteria to categorize response of HCC to locoregional treatment (e.g., chemical ablation, energy-based ablation, transcatheter therapy, and radiation therapy). LR-TR categories include Nonevaluable, Nonviable, Equivocal, and Viable. LR-TR does not apply to patients on systemic therapies. This article reviews the LR-TR algorithm; discusses locoregional therapies for HCC, treatment concepts, and expected posttreatment findings; and illustrates LI-RADS treatment response assessment with CT and MRI.

Cost-Utility Analysis of Imaging for Surveillance and Diagnosis of Hepatocellular Carcinoma.

OBJECTIVE. The purpose of this study is to compare imaging-based surveillance and diagnostic strategies in patients at risk for hepatocellular carcinoma (HCC) while taking into account technically inadequate examinations and patient compliance. MATERIALS AND METHODS. A Markov model simulated seven strategies for HCC surveillance and diagnosis in patients with cirrhosis: strategy A, ultrasound (US) for surveillance and CT for diagnosis; strategy B, US for surveillance and complete MRI for diagnosis; strategy C, US for surveillance and CT for inadequate or positive surveillance; strategy D, US for surveillance and complete MRI for inadequate or positive surveillance; strategy E, surveillance and diagnosis with CT followed by complete MRI for inadequate surveillance; strategy F, surveillance and diagnosis with complete MRI followed by CT for inadequate surveillance; and strategy G, surveillance with abbreviated MRI followed by CT for inadequate surveillance or complete MRI for positive surveillance. Two compliance scenarios were evaluated: optimal and conservative. For each scenario, the most cost-effective strategy was based on a willingness-to-pay threshold of $50,000 (Canadian) per quality-adjusted life year (QALY). Sensitivity analyses were performed. RESULTS. Base-case analysis revealed that strategy E was the most cost-effective when compliance was optimal ($13,631/QALY), and strategy G was the most cost-effective when compliance was conservative ($39,681/QALY). Sensitivity analyses supported the base-case analysis in the optimal compliance scenario, but several parameters altered the most cost-effective strategy in the conservative compliance scenario. CONCLUSION. In an optimal compliance scenario, CT for HCC surveillance and diagnosis and complete MRI for inadequate CT was most cost-effective. In a conservative compliance scenario, abbreviated MRI may be an alternative to US-based surveillance.

Quantitative ultrasound and machine learning for assessment of steatohepatitis in a rat model.

OBJECTIVES: To develop a machine learning model based on quantitative ultrasound (QUS) parameters to improve classification of steatohepatitis with shear wave elastography in rats by using histopathology scoring as the reference standard. METHODS: This study received approval from the institutional animal care committee. Sixty male Sprague-Dawley rats were either fed a standard chow or a methionine- and choline-deficient diet. Ultrasound-based radiofrequency images were recorded in vivo to generate QUS and elastography maps. Random forests classification models and a bootstrap method were used to identify the QUS parameters that improved the classification accuracy of elastography. Receiver-operating characteristic analyses were performed. RESULTS: For classification of not steatohepatitis vs borderline or steatohepatitis, the area under the receiver-operating characteristic curve (AUC) increased from 0.63 for elastography alone to 0.72 for a model that combined elastography and QUS techniques (p < 0.001). For detection of liver steatosis grades 0 vs ≥ 1, ≤ 1 vs ≥ 2, ≤ 2 vs 3, respectively, the AUCs increased from 0.70, 0.65, and 0.69 to 0.78, 0.78, and 0.75 (p < 0.001). For detection of liver inflammation grades 0 vs ≥ 1, ≤ 1 vs ≥ 2, ≤ 2 vs 3, respectively, the AUCs increased from 0.58, 0.77, and 0.78 to 0.66, 0.84, and 0.87 (p < 0.001). For staging of liver fibrosis grades 0 vs ≥ 1, ≤ 1 vs ≥ 2, and ≤ 2 vs ≥ 3, respectively, the AUCs increased from 0.79, 0.92, and 0.91 to 0.85, 0.98, and 0.97 (p < 0.001). CONCLUSION: QUS parameters improved the classification accuracy of steatohepatitis, liver steatosis, inflammation, and fibrosis compared to shear wave elastography alone. KEY POINTS: • Quantitative ultrasound and shear wave elastography improved classification accuracy of liver steatohepatitis and its histological features (liver steatosis, inflammation, and fibrosis) compared to elastography alone. • A machine learning approach based on random forest models and incorporating local attenuation and homodyned-K tissue modeling shows promise for classification of nonalcoholic steatohepatitis. • Further research should be performed to demonstrate the applicability of this multi-parametric QUS approach in a human cohort and to validate the combinations of parameters providing the highest classification accuracy.

Dual enzyme-assisted one-step isothermal real-time amplification assay for ultrasensitive detection of polynucleotide kinase activity.

A novel, simple, one-step and one-tube detection method was developed for ultrasensitive detection of polynucleotide kinase (PNK) activity on the basis of dual enzyme-synergistic signal amplification. This method was also demonstrated to work well for PNK inhibitor screening and endogenous PNK detection in cell lysates at a single-cell level.

Diagnostic performance of intravoxel incoherent motion diffusion-weighted imaging and dynamic contrast-enhanced MRI for assessment of anal fistula activity.

OBJECTIVE: To evaluate intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) sequences for quantitative characterization of anal fistula activity. METHODS: This retrospective study was approved by the institutional review board. One hundred and two patients underwent MRI for clinical suspicion of anal fistula. Forty-three patients with demonstrable anal fistulas met the inclusion criteria. Quantitative analysis included measurement of DCE and IVIM parameters. The reference standard was clinical activity based on medical records. Statistical analyses included Bayesian analysis with Markov Chain Monte Carlo, multivariable logistic regression, and receiver operating characteristic analyses. RESULTS: Brevity of enhancement, defined as the time difference between the wash-in and wash-out, was longer in active than inactive fistulas (p = 0.02). Regression coefficients of multivariable logistic regression analysis revealed that brevity of enhancement increased and normalized perfusion area under curve decreased with presence of active fistulas (p = 0.03 and p = 0.04, respectively). By cross-validation, a logistic regression model that included quantitative perfusion parameters (DCE and IVIM) performed significantly better than IVIM only (p < 0.001). Area under the curves for distinguishing patients with active from those with inactive fistulas were 0.669 (95% confidence interval [CI]: 0.500, 0.838) for a model with IVIM only, 0.860 (95% CI: 0.742, 0.977) for a model with IVIM and brevity of enhancement, and 0.921 (95% CI: 0.846, 0.997) for a model with IVIM and all DCE parameters. CONCLUSION: The inclusion of brevity of enhancement measured by DCE-MRI improved assessment of anal fistula activity over IVIM-DWI only.

Influence analysis for skew-normal semiparametric joint models of multivariate longitudinal and multivariate survival data.

The normality assumption of measurement error is a widely used distribution in joint models of longitudinal and survival data, but it may lead to unreasonable or even misleading results when longitudinal data reveal skewness feature. This paper proposes a new joint model for multivariate longitudinal and multivariate survival data by incorporating a nonparametric function into the trajectory function and hazard function and assuming that measurement errors in longitudinal measurement models follow a skew-normal distribution. A Monte Carlo Expectation-Maximization (EM) algorithm together with the penalized-splines technique and the Metropolis-Hastings algorithm within the Gibbs sampler is developed to estimate parameters and nonparametric functions in the considered joint models. Case deletion diagnostic measures are proposed to identify the potential influential observations, and an extended local influence method is presented to assess local influence of minor perturbations. Simulation studies and a real example from a clinical trial are presented to illustrate the proposed methodologies. Copyright © 2017 John Wiley & Sons, Ltd.

Cost-utility analysis of nonalcoholic steatohepatitis screening.

OBJECTIVES: Nonalcoholic fatty liver disease (NAFLD) is the most common liver disease in Western countries. No studies have examined the cost-effectiveness of screening its advanced form, nonalcoholic steatohepatitis (NASH). METHODS: We performed a cost-utility analysis of annual noninvasive screening strategies using third-party payer perspective in a general population in comparison to screening a high-risk obese or diabetic population. Screening algorithms involved well-studied techniques, including NAFLD fibrosis score, transient elastography (TE), and acoustic radiation force impulse (ARFI) imaging for detecting advanced fibrosis (≥ F3); and plasma cytokeratin (CK)-18 for NASH detection. Liver biopsy and magnetic resonance elastography (MRE) were compared as confirmation methods. Canadian dollar (CAD or C$) costs were adjusted for inflation and discounted at 5%. Incremental cost-effectiveness ratio (ICER) of ≤C$ 50,000 was considered cost-effective. RESULTS: Compared with no screening, screening with NAFLD fibrosis score/TE/CK-18 algorithm with MRE as confirmation for advanced fibrosis had an ICER of C$ 26,143 per quality-adjusted life year (QALY) gained. Screening in high-risk obese or diabetic populations was more cost-effective, with an ICER of C$ 9,051 and C$ 7,991 per quality-adjusted life-year (QALY) gained, respectively. Liver biopsy confirmation was not found to be cost-effective. CONCLUSIONS: Our model suggests that annual NASH screening in high-risk obese or diabetic populations can be cost-effective. KEY POINTS: • This cost-utility analysis suggests that screening for nonalcoholic steatohepatitis may be cost-effective. • In particular, screening of high-risk obese or diabetic populations is more cost-effective. • Magnetic resonance elastography was more cost-effective to confirm disease compared to biopsy. • More studies are needed to determine quality of life in nonalcoholic steatohepatitis. • More management strategies for nonalcoholic steatohepatitis are also needed.

Simultaneous assessment of liver volume and whole liver fat content: a step towards one-stop shop preoperative MRI protocol.

OBJECTIVE: The purpose of this study was to evaluate the ability of a whole liver volume (WLV) segmentation algorithm to measure fat fraction (FF). METHODS: Twenty consecutive patients with histologically proven fatty liver disease underwent dual-echo in-phase/out-of-phase MRI and magnetic resonance spectroscopy (MRS) at 1.5 T. Two readers independently performed semiautomatic 3D liver segmentation on the out-of-phase sequences using an active contour model. FF was calculated for voxels, segments and WLV. Segmentation inter-observer reproducibility was assessed by intra-class correlation coefficient (ICC) for WLV and FF. Fat fraction correlation and agreement as determined by histology, MRS and MRI were determined. RESULTS: ICC was 0.999 (95% CI: 0.999-1, P < 0.001) for WLV FF calculation and 0.996 (95% CI: 0.990-0.998, P < 0.001) for whole liver volume calculations. Strong correlations were found between FF measured by histology, MRS and WLV-MRI. A Bland-Altman analysis showed a good agreement between FF measured by MRS and WLV-MRI. No systematic variations of FF was found between segments when analyzed by ANOVA (F = 1.78, P = 0.096). CONCLUSION: This study shows that a reproducible whole liver volume segmentation method to measure fat fraction can be performed. This strategy may be integrated to a "one-stop shop" protocol in liver surgery planning.

Comparative study of the specificities of needling acupoints DU20, DU26 and HT7 in intervening vascular dementia in different areas in the brain on the basis of scale assessment and cerebral functional imaging.

OBJECTIVE: Using methods of clinical scale assessment and cerebral functional imaging to compare the relative specificity of needling acupoints Baihui (DU20), Shuigou (DU26) and Shenmen (HT7) in intervening vascular dementia (VD) in different areas in the brain. METHODS: Fifty patients with VD were randomized into 5 groups. Needling on conventionally used acupoints of hand and foot three Yang-meridians aiming at hemiplegia was applied to the patients in Group A, and needling on DU20 to Group B, on DU26 to Group C, on HT7 to Group D and on all the three to Group E was applied additionally. Assessments of Mini Mental State Examination (MMSE), Activities of Daily Living (ADL) and Family Attitude Questionnaire (FAQ) were made. And the positron emission computerized tomography (PET) and single photon emission computerized tomography (SPECT) examinations were conducted in 5 selected patients from each group before and after treatment. RESULTS: Needling on conventional acupoints plus DU20 could effect the inner temporal system, thalamencephalon system and prefrontal cortical system to improve memory and executive capacity of VD patients; conventional acupoints plus DU26 could effect more to the prefrontal cortical system to obviously elevate the executive capacity; that plus HT7 would reveal an effect similar to but rather weaker than plus DU20, and effect more to memory; and that plus all the three simultaneously could effect rather roundly multiple aspects of the nervous system related to intellectual activities, to elevate the recognition and enhance the executive capacity. CONCLUSION: Needling on various acupoints like DU20, DU26 and HT7 have effects on different brain areas.