Diagnostic Anatomic Imaging for Neuroendocrine Neoplasms: Maximizing Strengths and Mitigating Weaknesses.

ABSTRACT: Neuroendocrine neoplasms are a heterogeneous group of gastrointestinal and lung tumors. Their diverse clinical manifestations, variable locations, and heterogeneity present notable diagnostic challenges. This article delves into the imaging modalities vital for their detection and characterization. Computed tomography is essential for initial assessment and staging. At the same time, magnetic resonance imaging (MRI) is particularly adept for liver, pancreatic, osseous, and rectal imaging, offering superior soft tissue contrast. The article also highlights the limitations of these imaging techniques, such as MRI's inability to effectively evaluate the cortical bone and the questioned cost-effectiveness of computed tomography and MRI for detecting specific gastric lesions. By emphasizing the strengths and weaknesses of these imaging techniques, the review offers insights into optimizing their utilization for improved diagnosis, staging, and therapeutic management of neuroendocrine neoplasms.

Imaging of Neuroendocrine Neoplasms; Principles of Treatment Strategies. What Referring Clinicians Want to Know.

ABSTRACT: Neuroendocrine neoplasms (NENs) are a diverse group of tumors that express neuroendocrine markers and primarily affect the lungs and digestive system. The incidence of NENs has increased over time due to advancements in imaging and diagnostic techniques. Effective management of NENs requires a multidisciplinary approach, considering factors such as tumor location, grade, stage, symptoms, and imaging findings. Treatment strategies vary depending on the specific subtype of NEN. In this review, we will focus on treatment strategies and therapies including the information relevant to clinicians in order to undertake optimal management and treatment decisions, the implications of different therapies on imaging, and how to ascertain their possible complications and treatment effects.

Gamified Crowdsourcing as a Novel Approach to Lung Ultrasound Data Set Labeling: Prospective Analysis.

BACKGROUND: Machine learning (ML) models can yield faster and more accurate medical diagnoses; however, developing ML models is limited by a lack of high-quality labeled training data. Crowdsourced labeling is a potential solution but can be constrained by concerns about label quality. OBJECTIVE: This study aims to examine whether a gamified crowdsourcing platform with continuous performance assessment, user feedback, and performance-based incentives could produce expert-quality labels on medical imaging data. METHODS: In this diagnostic comparison study, 2384 lung ultrasound clips were retrospectively collected from 203 emergency department patients. A total of 6 lung ultrasound experts classified 393 of these clips as having no B-lines, one or more discrete B-lines, or confluent B-lines to create 2 sets of reference standard data sets (195 training clips and 198 test clips). Sets were respectively used to (1) train users on a gamified crowdsourcing platform and (2) compare the concordance of the resulting crowd labels to the concordance of individual experts to reference standards. Crowd opinions were sourced from DiagnosUs (Centaur Labs) iOS app users over 8 days, filtered based on past performance, aggregated using majority rule, and analyzed for label concordance compared with a hold-out test set of expert-labeled clips. The primary outcome was comparing the labeling concordance of collated crowd opinions to trained experts in classifying B-lines on lung ultrasound clips. RESULTS: Our clinical data set included patients with a mean age of 60.0 (SD 19.0) years; 105 (51.7%) patients were female and 114 (56.1%) patients were White. Over the 195 training clips, the expert-consensus label distribution was 114 (58%) no B-lines, 56 (29%) discrete B-lines, and 25 (13%) confluent B-lines. Over the 198 test clips, expert-consensus label distribution was 138 (70%) no B-lines, 36 (18%) discrete B-lines, and 24 (12%) confluent B-lines. In total, 99,238 opinions were collected from 426 unique users. On a test set of 198 clips, the mean labeling concordance of individual experts relative to the reference standard was 85.0% (SE 2.0), compared with 87.9% crowdsourced label concordance (P=.15). When individual experts' opinions were compared with reference standard labels created by majority vote excluding their own opinion, crowd concordance was higher than the mean concordance of individual experts to reference standards (87.4% vs 80.8%, SE 1.6 for expert concordance; P<.001). Clips with discrete B-lines had the most disagreement from both the crowd consensus and individual experts with the expert consensus. Using randomly sampled subsets of crowd opinions, 7 quality-filtered opinions were sufficient to achieve near the maximum crowd concordance. CONCLUSIONS: Crowdsourced labels for B-line classification on lung ultrasound clips via a gamified approach achieved expert-level accuracy. This suggests a strategic role for gamified crowdsourcing in efficiently generating labeled image data sets for training ML systems.

The Future Is Beyond Bright: The Evolving Role of Quantitative US for Fatty Liver Disease.

Nonalcoholic fatty liver disease (NAFLD) is a common cause of morbidity and mortality. Nonfocal liver biopsy is the historical reference standard for evaluating NAFLD, but it is limited by invasiveness, high cost, and sampling error. Imaging methods are ideally situated to provide quantifiable results and rule out other anatomic diseases of the liver. MRI and US have shown great promise for the noninvasive evaluation of NAFLD. US is particularly well suited to address the population-level problem of NAFLD because it is lower-cost, more available, and more tolerable to a broader range of patients than MRI. Noninvasive US methods to evaluate liver fibrosis are widely available, and US-based tools to evaluate steatosis and inflammation are gaining traction. US techniques including shear-wave elastography, Doppler spectral imaging, attenuation coefficient, hepatorenal index, speed of sound, and backscatter-based estimation have regulatory clearance and are in clinical use. New methods based on channel and radiofrequency data analysis approaches have shown promise but are mostly experimental. This review discusses the advantages and limitations of clinically available and experimental approaches to sonographic liver tissue characterization for NAFLD diagnosis as well as future applications and strategies to overcome current limitations.

Repeatability of MRI Biomarkers in Nonalcoholic Fatty Liver Disease: The NIMBLE Consortium.

Background There is a need for reliable noninvasive methods for diagnosing and monitoring nonalcoholic fatty liver disease (NAFLD). Thus, the multidisciplinary Non-invasive Biomarkers of Metabolic Liver disease (NIMBLE) consortium was formed to identify and advance the regulatory qualification of NAFLD imaging biomarkers. Purpose To determine the different-day same-scanner repeatability coefficient of liver MRI biomarkers in patients with NAFLD at risk for steatohepatitis. Materials and Methods NIMBLE 1.2 is a prospective, observational, single-center short-term cross-sectional study (October 2021 to June 2022) in adults with NAFLD across a spectrum of low, intermediate, and high likelihood of advanced fibrosis as determined according to the fibrosis based on four factors (FIB-4) index. Participants underwent up to seven MRI examinations across two visits less than or equal to 7 days apart. Standardized imaging protocols were implemented with six MRI scanners from three vendors at both 1.5 T and 3 T, with central analysis of the data performed by an independent reading center (University of California, San Diego). Trained analysts, who were blinded to clinical data, measured the MRI proton density fat fraction (PDFF), liver stiffness at MR elastography (MRE), and visceral adipose tissue (VAT) for each participant. Point estimates and CIs were calculated using χ2 distribution and statistical modeling for pooled repeatability measures. Results A total of 17 participants (mean age, 58 years ± 8.5 [SD]; 10 female) were included, of which seven (41.2%), six (35.3%), and four (23.5%) participants had a low, intermediate, or high likelihood of advanced fibrosis, respectively. The different-day same-scanner mean measurements were 13%-14% for PDFF, 6.6 L for VAT, and 3.15 kPa for two-dimensional MRE stiffness. The different-day same-scanner repeatability coefficients were 0.22 L (95% CI: 0.17, 0.29) for VAT, 0.75 kPa (95% CI: 0.6, 0.99) for MRE stiffness, 1.19% (95% CI: 0.96, 1.61) for MRI PDFF using magnitude reconstruction, 1.56% (95% CI: 1.26, 2.07) for MRI PDFF using complex reconstruction, and 19.7% (95% CI: 15.8, 26.2) for three-dimensional MRE shear modulus. Conclusion This preliminary study suggests that thresholds of 1.2%-1.6%, 0.22 L, and 0.75 kPa for MRI PDFF, VAT, and MRE, respectively, should be used to discern measurement error from real change in patients with NAFLD. ClinicalTrials.gov registration no. NCT05081427 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Kozaka and Matsui in this issue.

Pulse-Echo Quantitative US Biomarkers for Liver Steatosis: Toward Technical Standardization.

Excessive liver fat (steatosis) is now the most common cause of chronic liver disease worldwide and is an independent risk factor for cirrhosis and associated complications. Accurate and clinically useful diagnosis, risk stratification, prognostication, and therapy monitoring require accurate and reliable biomarker measurement at acceptable cost. This article describes a joint effort by the American Institute of Ultrasound in Medicine (AIUM) and the RSNA Quantitative Imaging Biomarkers Alliance (QIBA) to develop standards for clinical and technical validation of quantitative biomarkers for liver steatosis. The AIUM Liver Fat Quantification Task Force provides clinical guidance, while the RSNA QIBA Pulse-Echo Quantitative Ultrasound Biomarker Committee develops methods to measure biomarkers and reduce biomarker variability. In this article, the authors present the clinical need for quantitative imaging biomarkers of liver steatosis, review the current state of various imaging modalities, and describe the technical state of the art for three key liver steatosis pulse-echo quantitative US biomarkers: attenuation coefficient, backscatter coefficient, and speed of sound. Lastly, a perspective on current challenges and recommendations for clinical translation for each biomarker is offered.

Shear-Wave Elastography of the Breast: Impact of Technical Image Quality Parameters on Diagnostic Accuracy.

OBJECTIVE. The purpose of this study is to determine the impact of shear-wave elastography (SWE) image quality parameters on the diagnostic performance of elasticity measurements in classifying breast lesions. MATERIALS AND METHODS. This retrospective study included 281 breast lesions that underwent SWE and ultrasound-guided biopsy performed between October 1, 2017, and August 31, 2018. Three readers who were blinded to pathologic outcomes independently scored the image quality of each SWE image (with low quality denoted by a score of 0 and high quality indicated by a score of 1) on the basis of five parameters: B-mode visualization of the lesion on a dual-panel display, SWE red pattern (denoting high stiffness) in the near field of the FOV, appearance of the surrounding tissue, FOV placement, and ROI placement for the maximum (Emax), minimum (Emin), mean (Emean), and SD (ESD) of Young modulus elasticity measurements. Using ROC analysis, we compared the performance of Emax, Emean, and ESD in diagnosing malignancy on low- and high-quality images on the basis of consensus (i.e., majority) scores for each individual quality parameter as well as two models combining a few of the quality parameters. RESULTS. Three quality parameters (B-mode visualization of the lesion, presence of a near-field red pattern, and the appearance of the surrounding tissue) showed moderate-to-substantial interobserver agreement. SWE images were considered high quality (n = 167) if both B-mode visualization and near-field red pattern received a consensus score of 1, and they were considered low quality (n = 114) if either parameter received a consensus score of 0. High-quality images had a statistically higher AUC value than low-quality images when Emax (p < .001), Emean (p = .002), and ESD (p < .001) were used as classifiers of malignancy. CONCLUSION. Quality parameters can support radiologists who are performing and interpreting breast SWE images. These quality parameters have the potential to improve the accuracy of SWE in differentiating malignant from benign breast lesions.

Variation of Shear Wave Elastography With Preload in the Thyroid: Quantitative Validation.

OBJECTIVES: Thyroid shear wave elastography (SWE) has been shown to have advantages compared to biopsy or other imaging modalities in the evaluation of thyroid nodules. However, studies show variability in its assessment. The objective of this study was to evaluate whether stiffness measurements of the normal thyroid, as estimated by SWE, varied due to preload force or the pressure applied between the transducer and the patient. METHODS: In this study, a measurement system was attached to the ultrasound transducer to measure the applied load. Shear wave elastographic measurements were obtained from the left lobe of the thyroid at applied transducer forces between 2 and 10 N. A linear mixed-effects model was constructed to quantify the association between the preload force and stiffness while accounting for correlations between repeated measurements within each participant. The preload force effect on elasticity was modeled by both linear and quadratic terms to account for a possible nonlinear association between these variables. RESULTS: Nineteen healthy volunteers without known thyroid disease participated in the study. The participants had a mean age ± SD of 36 ± 8 years; 74% were female; 74% had a normal body mass index; and 95% were white non-Hispanic/Latino. The estimated elastographic value at a 2-N preload force was 16.7 kPa (95% confidence interval, 14.1-19.3 kPa), whereas the value at 10 N was 29.9 kPa (95% confidence interval, 24.9-34.9 kPa). CONCLUSIONS: The preload force was significantly and nonlinearly associated with SWE estimates of thyroid stiffness. Quantitative standardization of preload forces in the assessment of thyroid nodules using elastography is an integral factor for improving the accuracy of thyroid nodule evaluation.

Cervical Extension of the Normal Thymus in Children and Adolescents: Sonographic Features and Prevalence.

OBJECTIVE: This study aims to confirm the prevalence of incidental cervical extension of normal thymus in children and adolescents undergoing neck ultrasound and describe the ultrasound appearance to minimize future misdiagnosis. MATERIALS AND METHODS: This retrospective study was conducted in a single institution. Thyroid and lower neck ultrasound images of the consecutive pediatric subjects between January 1, 2011 and September 30, 2017 were independently reviewed by 2 radiologists for the presence of cervical thymus. When identified on sonographic images, cervical thymus was described on the basis of echogenicity, location, and shape. RESULTS: In 278 consecutive cases, the 2 reviewers identified 105 (37.8%) and 103 (37.1%) cases respectively as having sonographically visible tissue in the expected location of cervical extension of the thymus. The internal echotexture was variable with 38.1% of cases being hypoechoic, 37.1% mixed, and 24.8% hyperechoic. Cervical extension of the thymus was most commonly (65.0%) to the left of the trachea or (30.9%) bilateral/anterior to the trachea; isolated right paratracheal thymus was uncommon. Thymic shape was variable: quadrilateral (30.9%), oval (29.9%), triangular (25.8%), and other (13.4%). The logistic regression model including age, gender, and BMI z-scores showed that, when controlled for sex and BMI z-scores, younger age was a predictor for the presence of cervical thymic extension (p < .001). CONCLUSION: Cervical thymic extension is sonographically visible as a soft tissue mass of variable appearance in about a third of children and adolescents undergoing neck ultrasonography with decreasing prevalence with age. Sonographically visible cervical thymic tissue is more common in younger patients.

Radiological Society of North America/Quantitative Imaging Biomarker Alliance Shear Wave Speed Bias Quantification in Elastic and Viscoelastic Phantoms.

OBJECTIVES: To quantify the bias of shear wave speed (SWS) measurements between different commercial ultrasonic shear elasticity systems and a magnetic resonance elastography (MRE) system in elastic and viscoelastic phantoms. METHODS: Two elastic phantoms, representing healthy through fibrotic liver, were measured with 5 different ultrasound platforms, and 3 viscoelastic phantoms, representing healthy through fibrotic liver tissue, were measured with 12 different ultrasound platforms. Measurements were performed with different systems at different sites, at 3 focal depths, and with different appraisers. The SWS bias across the systems was quantified as a function of the system, site, focal depth, and appraiser. A single MRE research system was also used to characterize these phantoms using discrete frequencies from 60 to 500 Hz. RESULTS: The SWS from different systems had mean difference 95% confidence intervals of ±0.145 m/s (±9.6%) across both elastic phantoms and ± 0.340 m/s (±15.3%) across the viscoelastic phantoms. The focal depth and appraiser were less significant sources of SWS variability than the system and site. Magnetic resonance elastography best matched the ultrasonic SWS in the viscoelastic phantoms using a 140 Hz source but had a - 0.27 ± 0.027-m/s (-12.2% ± 1.2%) bias when using the clinically implemented 60-Hz vibration source. CONCLUSIONS: Shear wave speed reconstruction across different manufacturer systems is more consistent in elastic than viscoelastic phantoms, with a mean difference bias of < ±10% in all cases. Magnetic resonance elastographic measurements in the elastic and viscoelastic phantoms best match the ultrasound systems with a 140-Hz excitation but have a significant negative bias operating at 60 Hz. This study establishes a foundation for meaningful comparison of SWS measurements made with different platforms.

[18F]-Alfatide PET imaging of integrin αvß3 for the non-invasive quantification of liver fibrosis.

BACKGROUND & AIMS: The vitronectin receptor integrin αvß3 drives fibrogenic activation of hepatic stellate cells (HSCs). Molecular imaging targeting the integrin αvß3 could provide a non-invasive method for evaluating the expression and the function of the integrin αvß3 on activated HSCs (aHSCs) in the injured liver. In this study, we sought to compare differences in the uptake of [18F]-Alfatide between normal and injured liver to evaluate its utility for assessment of hepatic fibrogenesis. METHODS: PET with [18F]-Alfatide, non-enhanced CT, histopathology, immunofluorescence staining, immunoblotting and gene analysis were performed to evaluate and quantify hepatic integrin αvß3 levels and liver fibrosis progression in mouse models of fibrosis (carbon tetrachloride [CCl4] and bile duct ligation [BDL]). The liver AUC divided by the blood AUC over 30 min was used as an integrin αvß3-PET index to quantify fibrosis progression. Ex vivo analysis of frozen liver tissue from patients with fibrosis and cirrhosis verified the animal findings. RESULTS: Fibrotic mouse livers showed enhanced [18F]-Alfatide uptake and retention compared to control livers. The radiotracer was demonstrated to bind specifically with integrin αvß3, which is mainly expressed on aHSCs. Autoradiography and histopathology confirmed the PET imaging results. Further, the mRNA and protein level of integrin αvß3 and its signaling complex were higher in CCl4 and BDL models than controls. The results obtained from analyses on human fibrotic liver sections supported the animal findings. CONCLUSIONS: Imaging hepatic integrin αvß3 with PET and [18F]-Alfatide offers a potential non-invasive method for monitoring the progression of liver fibrosis. LAY SUMMARY: Integrin αvß3 expression on activated hepatic stellate cells (aHSCs) is associated with HSC proliferation during hepatic fibrogenesis. Herein, we show that a radioactive tracer, [18F]-Alfatide, binds to integrin αvß3 with high affinity and specificity. [18F]-Alfatide could thus be used as a non-invasive imaging biomarker to track hepatic fibrosis progression.

Abdominal Imaging Findings in COVID-19: Preliminary Observations.

Background Angiotensin-converting enzyme 2, a target of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), demonstrates its highest surface expression in the lung, small bowel, and vasculature, suggesting abdominal viscera may be susceptible to injury. Purpose To report abdominal imaging findings in patients with coronavirus disease 2019. Materials and Methods In this retrospective cross-sectional study, patients consecutively admitted to a single quaternary care center from March 27 to April 10, 2020, who tested positive for SARS-CoV-2 were included. Abdominal imaging studies performed in these patients were reviewed, and salient findings were recorded. Medical records were reviewed for clinical data. Univariable analysis and logistic regression were performed. Results A total of 412 patients (average age, 57 years; range, 18 to >90 years; 241 men, 171 women) were evaluated. A total of 224 abdominal imaging studies were performed (radiography, n = 137; US, n = 44; CT, n = 42; MRI, n = 1) in 134 patients (33%). Abdominal imaging was associated with age (odds ratio [OR], 1.03 per year of increase; P = .001) and intensive care unit (ICU) admission (OR, 17.3; P < .001). Bowel-wall abnormalities were seen on 31% of CT images (13 of 42) and were associated with ICU admission (OR, 15.5; P = .01). Bowel findings included pneumatosis or portal venous gas, seen on 20% of CT images obtained in patients in the ICU (four of 20). Surgical correlation (n = 4) revealed unusual yellow discoloration of the bowel (n = 3) and bowel infarction (n = 2). Pathologic findings revealed ischemic enteritis with patchy necrosis and fibrin thrombi in arterioles (n = 2). Right upper quadrant US examinations were mostly performed because of liver laboratory findings (87%, 32 of 37), and 54% (20 of 37) revealed a dilated sludge-filled gallbladder, suggestive of bile stasis. Patients with a cholecystostomy tube placed (n = 4) had negative bacterial cultures. Conclusion Bowel abnormalities and gallbladder bile stasis were common findings on abdominal images of patients with coronavirus disease 2019. Patients who underwent laparotomy often had ischemia, possibly due to small-vessel thrombosis. © RSNA, 2020.

Liver fibrosis imaging: A clinical review of ultrasound and magnetic resonance elastography.

Liver fibrosis is a histological hallmark of most chronic liver diseases, which can progress to cirrhosis and liver failure, and predisposes to hepatocellular carcinoma. Accurate diagnosis of liver fibrosis is necessary for prognosis, risk stratification, and treatment decision-making. Liver biopsy, the reference standard for assessing liver fibrosis, is invasive, costly, and impractical for surveillance and treatment response monitoring. Elastography offers a noninvasive, objective, and quantitative alternative to liver biopsy. This article discusses the need for noninvasive assessment of liver fibrosis and reviews the comparative advantages and limitations of ultrasound and magnetic resonance elastography techniques with respect to their basic concepts, acquisition, processing, and diagnostic performance. Variations in clinical contexts of use and common pitfalls associated with each technique are considered. In addition, current challenges and future directions to improve the diagnostic accuracy and clinical utility of elastography techniques are discussed. Level of Evidence: 5 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:25-42.

Differentiation of regenerative nodule, dysplastic nodule, and small hepatocellular carcinoma in cirrhotic patients: a contrast-enhanced ultrasound-based multivariable model analysis.

OBJECTIVE: To develop a contrast-enhanced ultrasound (CEUS)-based model for differentiating cirrhotic liver lesions and for active surveillance of hepatocellular carcinoma (HCC). METHODS: Patients with focal liver lesions (FLLs) with biopsy/resection-proven pathology and pre-procedure CEUS were enrolled from our institution between January 2011 and November 2014. Univariable and multivariable regression models were constructed using qualitative CEUS features and/or contrast arrival time ratio (CATR). The optimism-adjusted Harrell's generalized concordance index (CH) was used to quantify the discriminatory ability of each CEUS feature and model. RESULTS: A total of 149 patients (113 men and 36 women) with 162 FLLs were enrolled with mean age 53.4 ± 12.7 years. A 0.1-unit reduction in CATR was associated with a 68% increase in the odds of having a higher nodule ranking (RN < DN < small HCC) (OR, 0.32; 95% CI, 0.20-0.50, p < .001). Arterial phase hypoenhancement and isoenhancement were inversely associated with a higher nodule ranking compared to hyperenhancement. Late-phase isoenhancement was associated with lower odds of a higher nodule ranking. The CEUS + CATR model (CH 0.92, 0.89-0.95) provided greater discriminatory ability when compared to the CATR model (ΔCH 0.09, 0.04-0.13, p < .001) and the CEUS model (ΔCH 0.03, 0.01-0.05, p = .02). CONCLUSIONS: Our results provide preliminary evidence that multivariable regression model constructed using both qualitative CEUS features and CATR provides the greatest discriminatory ability to differentiate RN, DN, and small HCC in patients with cirrhosis, and might allow for active surveillance of the progression of cirrhotic liver lesions. KEY POINTS: • Proportional odds logistic regression models based on qualitative CEUS features and/or CATR can be used for differentiating cirrhotic liver lesions and for active surveillance of HCC. • The reduction of CATR (RN < DN < small HCC) was strongly associated with high-risk cirrhotic liver nodules. • Inclusion of CATR in the CEUS prediction model significantly improved its performance for cirrhotic liver lesions risk-stratification.

Portal Venous Pulsatility Index: A Novel Biomarker for Diagnosis of High-Risk Nonalcoholic Fatty Liver Disease.

OBJECTIVE. The purpose of this study was to assess the accuracy of portal vein pulsatility for noninvasive diagnosis of high-risk nonalcoholic fatty liver disease (NAFLD). MATERIALS AND METHODS. This retrospective study included patients with biopsy-proven diagnosis of NAFLD who underwent duplex Doppler ultrasound assessment of the main portal vein within 1 year of liver biopsy (January 2014 to February 2018). Doppler ultrasound images were reviewed. The spectral waveform was used to measure the maximum (Vmax) and minimum (Vmin) velocity of blood in the portal veins. Venous pulsatility index (VPI) defined as (Vmax - Vmin) / Vmax was calculated. ROC curve analysis was used to calculate AUC as a measure of accuracy to determine the value of this index for diagnosis of high-risk NAFLD and compared with that of the following four clinical decision aids: NAFLD fibrosis score (FS), fibrosis-4 index (FIB-4), BARD score (body mass index, aspartate aminotransferase [AST]-to-alanine aminotransferase ratio, diabetes mellitus), and AST-to-platelet ratio index (APRI). The value of adding VPI to these indexes was also investigated. RESULTS. Of 123 study subjects, 33 (26.8%) had high-risk NAFLD and were found to have a lower VPI than the other 90 subjects (0.19 vs 0.32; p < 0.001). VPI, NAFLD FS, FIB-4, and APRI had statistically significant diagnostic values for high-risk NAFLD. VPI had the highest optimism-corrected AUC (VPI, 0.84 [95% CI, 0.77-0.91]; NAFLD FS, 0.74 [95% CI, 0.63-0.83]; FIB-4, 0.81 [95% CI, 0.72-0.89]; APRI, 0.73 [95% CI, 0.61-0.82]). Addition of VPI to any of the four scoring systems significantly improved the diagnostic value of the score for high-risk NAFLD. CONCLUSION. VPI may be an accurate noninvasive biomarker for diagnosis of high-risk NAFLD.

Imaging-Related Risk Factors for Bleeding Complications of US-Guided Native Renal Biopsy: A Propensity Score Matching Analysis.

PURPOSE: To evaluate imaging-related hemorrhagic risk factors for ultrasound (US)-guided native kidney biopsy. MATERIALS AND METHODS: A retrospective review was conducted of adult patients who underwent US-guided native kidney biopsy at a single center between January 2006 and March 2016 and identified 37 of 551 patients (6.72%) with postbiopsy bleeding complications, including 11 major complications (2.00%; n = 11) and 26 minor complications (4.72%; n = 26). Ten patients with major complications and 20 with minor complications were matched with 20 control subjects each by propensity score matching based on age, needle size, number of cores, blood pressure, partial thromboplastin time, prothrombin time, platelet count, and estimated glomerular filtration rate. RESULTS: Biopsy needle passing through the renal sinus was identified in the patients with major (6 of 10; 60%) and minor complications (8 of 20; 40.0%) but not in the control groups. For patients with major complications, the needle-sinus distance was significantly shorter (5.11 mm ± 7.32 vs 11.14 mm ± 3.54; P = .023) and the needle-capsule distance was significantly longer (17.52 mm ± 8.04 vs 9.28 mm ± 3.29; P = .0004) than in control subjects. The bimodal distribution of cortical tangential angles (< 30° or ≥ 60°) in minor complication cases (17 of 20; 85.0%) was significantly greater than in the control group (8 of 20; 40.0%; odds ratio = 8.50; P = .004). CONCLUSIONS: This study identifies imaging risk factors in US-guided native kidney biopsy and recommends an algorithm to manage them, including appropriate needle path position between the renal capsule and sinus and proper needle cortical tangential angle.

Data Engineering for Machine Learning in Women's Imaging and Beyond.

OBJECTIVE. Data engineering is the foundation of effective machine learning model development and research. The accuracy and clinical utility of machine learning models fundamentally depend on the quality of the data used for model development. This article aims to provide radiologists and radiology researchers with an understanding of the core elements of data preparation for machine learning research. We cover key concepts from an engineering perspective, including databases, data integrity, and characteristics of data suitable for machine learning projects, and from a clinical perspective, including the HIPAA, patient consent, avoidance of bias, and ethical concerns related to the potential to magnify health disparities. The focus of this article is women's imaging; nonetheless, the principles described apply to all domains of medical imaging. CONCLUSION. Machine learning research is inherently interdisciplinary: effective collaboration is critical for success. In medical imaging, radiologists possess knowledge essential for data engineers to develop useful datasets for machine learning model development.

Diagnostic Performance of Shear Wave Elastography in Patients With Autoimmune Liver Disease.

OBJECTIVES: To assess performance of shear wave elastography for evaluation of fibrosis and the histologic stage in patients with autoimmune liver disease (ALD) and to validate previously established advanced fibrosis cutoff values in this cohort. METHODS: Shear wave elastography was performed on patients with ALD with an Aixplorer ultrasound system (SuperSonic Imagine, Aix-en-Provence, France) using an SC6-1 transducer. The median estimated tissue Young modulus was calculated from sets of 8 to 10 elastograms. A blinded, subspecialty-trained pathologist reviewed biopsy specimens. The METAVIR classification was used to stage liver fibrosis and necroinflammation. Steatosis was graded from 0 to 4+. The Kendall τ-b correlation test was performed to identify the correlation between the estimated tissue Young modulus and fibrosis, steatosis, and the necroinflammatory score. The Spearman correlation test was performed to identify the correlation between the estimated tissue Young modulus and clinical data. The diagnostic performance of shear wave elastography for differentiating METAVIR stage F2 or higher from F0 and F1 fibrosis was evaluated by a receiver operating characteristic (ROC) curve analysis. RESULTS: Fifty-one patients with ALD were analyzed. The estimated tissue Young modulus was positively correlated with the fibrosis stage and necroinflammation score (r = 0.386; P < .001; r = 0.338; P = .002, respectively) but not steatosis (r = -0.091; P = .527). Serum aspartate aminotransferase, alanine aminotransferase, and total bilirubin values were positively correlated with the estimated tissue Young modulus (r = 0.501; P < .001; r = 0.44; P = .001; r = 0.291; P = .038). The serum albumin value was negatively correlated (r = -0.309; P = .033). The area under the ROC curve was 0.781 (95% confidence interval, 0.641-0.921) for distinguishing F2 or greater fibrosis from F0 and F1 fibrosis. Based on the ROC curve, an optimal cutoff value of 9.15 kPa was identified (sensitivity, 83.3%; specificity, 72.7%). CONCLUSIONS: Shear wave elastography is a novel noninvasive adjunct to liver biopsy in evaluation and staging of patients with ALD, showing the potential for serial evaluations of disease progression and treatment responses.

Current Applications and Future Impact of Machine Learning in Radiology.

Recent advances and future perspectives of machine learning techniques offer promising applications in medical imaging. Machine learning has the potential to improve different steps of the radiology workflow including order scheduling and triage, clinical decision support systems, detection and interpretation of findings, postprocessing and dose estimation, examination quality control, and radiology reporting. In this article, the authors review examples of current applications of machine learning and artificial intelligence techniques in diagnostic radiology. In addition, the future impact and natural extension of these techniques in radiology practice are discussed.