Beyond Prostate Imaging Reporting and Data System: Combining Magnetic Resonance Imaging Prostate Imaging Reporting and Data System and Prostate-Specific Membrane Antigen-Positron Emission Tomography/Computed Tomography PRIMARY Score in a Composite (P) Score for More Accurate Diagnosis of Clinically Significant Prostate Cancer.

PURPOSE: The Prostate Imaging Reporting and Data System (PI-RADS) score is standard of care for clinically significant prostate cancer (csPCa) diagnosis. The PRIMARY score (prostate-specific membrane antigen [PSMA]-positron emission tomography [PET]/CT) also has high diagnostic accuracy for csPCa. This study aimed to develop an easily calculated combined (P) score for csPCa detection (International Society of Urological Pathology [ISUP] ≥2) incorporating separately read PI-RADS and PRIMARY scores, with external validation. MATERIALS AND METHODS: Two datasets of men with suspected PCa, no prior biopsy, recent MRI and 68Ga-PSMA-11-PET/CT, and subsequent transperineal biopsy were evaluated. These included the development sample (n = 291, 56% csPCa) a prospective trial and the validation sample (n = 227, 67% csPCa) a multicenter retrospective database. Primary outcome was detection of csPCa (ISUP ≥2), with ISUP ≥ 3 cancer detection a secondary outcome. Score performance was evaluated by area under the curve, sensitivity, specificity, and decision curve analysis. RESULTS: The 5-point combined (P) score was developed in a prospective dataset. In the validation dataset, csPCa was identified in 0%, 20%, 52%, 96%, and 100% for P score 1 to 5. The area under the curve was 0.93 (95% CI: 0.90-0.96), higher than PI-RADS 0.89 (95% CI: 0.85-0.93, P = .039) and PRIMARY score alone 0.84 (95% CI: 0.79-0.89, P < .001). Splitting scores at 1/2 (negative) vs 3/4/5 (positive), P score sensitivity was 94% (95% CI: 89-97) compared to PI-RADS 89% (95% CI: 83-93) and PRIMARY score 86% (95% CI: 79-91). For ISUP ≥ 3, P score sensitivity was 99% (95% CI: 95-100) vs 94% (95% CI: 88-98) and 92% (95% CI: 85-97) for PI-RADS and PRIMARY scores respectively. A maximum standardized uptake value > 12 (P score 5) was ISUP ≥ 2 in all cases with 93% ISUP ≥ 3. CONCLUSIONS: The P score is easily calculated and improves accuracy for csPCa over both PI-RADS and PRIMARY scores. It should be considered when PSMA-PET is undertaken for diagnosis.

Prostagram magnetic resonance imaging in a screening population: Prostate Imaging-Reporting and Data System or Likert?

OBJECTIVE: To compare biopsy recommendation rates and accuracy of the Prostate Imaging-Reporting and Data System, version 2 (PI-RADSv2) with the Likert scale for detection of clinically significant and insignificant prostate cancer in men screened within the Imperial Prostate 1 Prostate Cancer Screening Trial Using Imaging (IP1-PROSTAGRAM). PATIENTS AND METHODS: Men aged 50-69 years were screened with Prostagram MRI. Scans were prospectively reported using both PI-RADSv2 (excluding dynamic contrast-enhanced sequence score) and 5-point Likert scores by expert uro-radiologists. Systematic and targeted transperineal biopsy was recommended if the scan was scored ≥ 3, based on either reporting system. The proportion of patients recommended for biopsy and detection rates for Grade Groups (GGs) 1 and ≥ 2 were compared. Receiver operating characteristic (ROC) analysis was performed to compare performance. RESULTS: A total of 406 men underwent Prostagram MRI. The median (interquartile range) age and prostate-specific antigen level were 57 (53-61) years and 0.91 (0.56-1.74) ng/mL, respectively. At MRI score ≥ 3, more patients were recommended for biopsy based on Likert criteria (94/406; 23%, 95% confidence interval [CI] 19.2%-27.6%) compared to PI-RADSv2 (72/406; 18%, 95% CI 14.2%-21.9%; P = 0.03). For MRI scores ≥ 4, PI-RADSv2 and Likert scales led to 43/406 (11%, 95% CI 7.9%-14.1%) and 35/406 (9%, 95% CI 6.2%-11.9%) men recommended for biopsy (P = 0.40). For GG ≥ 2 detection, PIRADSv2 and Likert detected 22% (95% CI 11.4%-30.8%, 14/72) and 16% (95% CI 9.5%-25.3%, 15/94), respectively (P = 0.56). For GG1 cancers detection these were 11% (95% CI 4.3%-19.6%, seven of 72) vs 11% (95% CI 4.7%-17.8%, nine of 94; P = 1.00). The accuracy of PI-RADSv2 and Likert scale was similar (area under the ROC curve 0.64 vs 0.65, P = 0.95). CONCLUSIONS: In reporting non-contrast-enhanced Prostagram MRI in a screening population, the PI-RADSv2 and Likert scoring systems were equally accurate; however, Likert scale use led to more men undergoing biopsy without a subsequent increase in significant cancer detection rates. To improve reporting of Prostagram MRI, either the PI-RADSv2 or a modified Likert scale or a standalone scoring system should be developed.

Rapid assessment of data systems for COVID-19 vaccination in the WHO African Region.

Most countries in Africa deployed digital solutions to monitor progress in rolling out COVID-19 vaccines. A rapid assessment of existing data systems for COVID-19 vaccines in the African region was conducted between May and July 2022, in 23 countries. Data were collected through interviews with key informants, identified among senior staff within Ministries of Health, using a semi-structured electronic questionnaire. At vaccination sites, individual data were collected in paper-based registers in five countries (21.7%), in an electronic registry in two countries (8.7%), and in the remaining 16 countries (69.6%) using a combination of paper-based and electronic registries. Of the 18 countries using client-based digital registries, 11 (61%) deployed the District Health Information System 2 Tracker, and seven (39%), a locally developed platform. The mean percentage of individual data transcribed in the electronic registries was 61% ± 36% standard deviation. Unreliable Internet coverage (100% of countries), non-payment of data clerks' incentives (89%), and lack of electronic devices (89%) were the main reasons for the suboptimal functioning of digital systems quoted by key informants. It is critical for investments made and experience acquired in deploying electronic platforms for COVID-19 vaccines to be leveraged to strengthen routine immunization data management.

The role of gadolinium-based contrast agents in magnetic resonance imaging structured reporting and data systems (RADS).

Among the 28 reporting and data systems (RADS) available in the literature, we identified 15 RADS that can be used in Magnetic Resonance Imaging (MRI). Performing examinations without using gadolinium-based contrast agents (GBCA) has benefits, but GBCA administration is often required to achieve an early and accurate diagnosis. The aim of the present review is to summarize the current role of GBCA in MRI RADS. This overview suggests that GBCA are today required in most of the current RADS and are expected to be used in most MRIs performed in patients with cancer. Dynamic contrast enhancement is required for correct scores calculation in PI-RADS and VI-RADS, although scientific evidence may lead in the future to avoid the GBCA administration in these two RADS. In Bone-RADS, contrast enhancement can be required to classify an aggressive lesion. In RADS scoring on whole body-MRI datasets (MET-RADS-P, MY-RADS and ONCO-RADS), in NS-RADS and in Node-RADS, GBCA administration is optional thanks to the intrinsic high contrast resolution of MRI. Future studies are needed to evaluate the impact of the high T1 relaxivity GBCA on the assignment of RADS scores.

A qualitative interview study to determine barriers and facilitators of implementing automated decision support tools for genomic data access.

Data access committees (DAC) gatekeep access to secured genomic and related health datasets yet are challenged to keep pace with the rising volume and complexity of data generation. Automated decision support (ADS) systems have been shown to support consistency, compliance, and coordination of data access review decisions. However, we lack understanding of how DAC members perceive the value add of ADS, if any, on the quality and effectiveness of their reviews. In this qualitative study, we report findings from 13 semi-structured interviews with DAC members from around the world to identify relevant barriers and facilitators to implementing ADS for genomic data access management. Participants generally supported pilot studies that test ADS performance, for example in cataloging data types, verifying user credentials and tagging datasets for use terms. Concerns related to over-automation, lack of human oversight, low prioritization, and misalignment with institutional missions tempered enthusiasm for ADS among the DAC members we engaged. Tensions for change in institutional settings within which DACs operated was a powerful motivator for why DAC members considered the implementation of ADS into their access workflows, as well as perceptions of the relative advantage of ADS over the status quo. Future research is needed to build the evidence base around the comparative effectiveness and decisional outcomes of institutions that do/not use ADS into their workflows.

Using conceptual modeling to improve genome data management.

With advances in genomic sequencing technology, a large amount of data is publicly available for the research community to extract meaningful and reliable associations among risk genes and the mechanisms of disease. However, this exponential growth of data is spread in over thousand heterogeneous repositories, represented in multiple formats and with different levels of quality what hinders the differentiation of clinically valid relationships from those that are less well-sustained and that could lead to wrong diagnosis. This paper presents how conceptual models can play a key role to efficiently manage genomic data. These data must be accessible, informative and reliable enough to extract valuable knowledge in the context of the identification of evidence supporting the relationship between DNA variants and disease. The approach presented in this paper provides a solution that help researchers to organize, store and process information focusing only on the data that are relevant and minimizing the impact that the information overload has in clinical and research contexts. A case-study (epilepsy) is also presented, to demonstrate its application in a real context.

Reliability of extracellular contrast versus gadoxetic acid in assessing small liver lesions using liver imaging reporting and data system v.2018 and European association for the study of the liver criteria.

BACKGROUND & AIMS: The diagnostic accuracy of Liver Imaging Reporting and Data System (LI-RADS) v.2018 and European Association for the Study of the Liver (EASL) criteria for the diagnosis of HCC have been widely evaluated, but their reliability should be investigated. We aimed to assess and compare the reliability of LI-RADS v.2018 and EASL criteria for the diagnosis of HCC using MRI with extracellular contrast agents (ECAs) and gadoxetic acid (GA) and determine the effect of ancillary features on LI-RADS reliability. APPROACH & RESULTS: Ten readers reviewed MRI studies of 92 focal liver lesions measuring <3 cm acquired with ECAs and GA <1 month apart from two prospective trials, assessing EASL criteria, LI-RADS major and ancillary features, and LI-RADS categorization with and without including ancillary features. Inter-reader agreement for definite HCC diagnosis was substantial and similar for the two contrasts for both EASL and LI-RADS criteria. For ECA-MRI and GA-MRI, respectively, inter-reader agreement was k = 0.72 (95% CI, 0.63-0.81) and k = 0.72 (95% CI, 0.63-0.80); for nonrim hyperenhancement, k = 0.63 (95% CI, 0.54-0.72) and k = 0.57 (95% CI, 0.48-0.66); and for nonperipheral washout, k = 0.49 (95% CI, 0.40-0.59) and k = 0.48 (95% CI, 0.37-0.58) for enhancing capsule. The inter-reader agreement for LI-RADS after applying ancillary features remained in the same range of agreement. CONCLUSIONS: Agreement for definite HCC was substantial and similar for both scoring systems and the two contrast agents in small focal liver lesions. Agreement for LI-RADS categorization was lower for both contrast agents, and including LI-RADS ancillary features did not improve agreement.

Updates on LI-RADS Treatment Response Criteria for Hepatocellular Carcinoma: Focusing on MRI.

As the incidence of hepatocellular carcinoma (HCC) and subsequent treatments with liver-directed therapies rise, the complexity of assessing lesion response has also increased. The Liver Imaging Reporting and Data Systems (LI-RADS) treatment response algorithm (LI-RADS TRA) was created to standardize the assessment of response after locoregional therapy (LRT) on contrast-enhanced CT or MRI. Originally created based on expert opinion, these guidelines are currently undergoing revision based on emerging evidence. While many studies support the use of LR-TRA for evaluation of HCC response after thermal ablation and intra-arterial embolic therapy, data suggest a need for refinements to improve assessment after radiation therapy. In this manuscript, we review expected MR imaging findings after different forms of LRT, clarify how to apply the current LI-RADS TRA by type of LRT, explore emerging literature on LI-RADS TRA, and highlight future updates to the algorithm. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

Transforming Public Health Data Systems to Advance the Population's Health.

Policy Points Accurate and reliable data systems are critical for delivering the essential services and foundational capabilities of public health for a 21st -century public health infrastructure. Chronic underfunding, workforce shortages, and operational silos limit the effectiveness of America's public health data systems, with the country's anemic response to COVID-19 highlighting the results of long-standing infrastructure gaps. As the public health sector begins an unprecedented data modernization effort, scholars and policymakers should ensure ongoing reforms are aligned with the five components of an ideal public health data system: outcomes and equity oriented, actionable, interoperable, collaborative, and grounded in a robust public health system.

Sensor-based cloud computing data system and long distance running fatigue assessment.

Wireless sensor networks are widely used in sports training, medical and health care, smart home, environmental monitoring, cloud data and other fields because of their large scale, self-organization, reliability, dynamic, integration and data centralization. Based on this point, this article conducts a comprehensive analysis and research on cloud computing data systems, and designs and implements a dynamic replication strategy. Since different users have different demands for different data at different times, it is necessary to record and analyze recent users' data access, so as to actively adjust the number and location of data blocks. Subsequently, a multi-source blockchain transmission method was proposed and implemented, which can significantly reduce the time cost of data migration and improve the overall performance of cloud storage data systems. Finally, the article provides an in-depth analysis of long-distance running fatigue. This study will design a simulated specialized exercise load experiment to reproduce the load characteristics of excellent athletes during mid to long distance running, in order to induce exercise fatigue in the main muscles of different parts of their bodies. At the same time, the amplitude frequency joint analysis of the surface changes of EMG signal in this process is carried out. This article conducts research on sensor based cloud computing data systems and long-distance running fatigue assessment, promoting the development of cloud computing data systems and improving long-distance running fatigue assessment methods.

O-RADS MRI After Initial Ultrasound for Adnexal Lesions: AJR Expert Panel Narrative Review.

The Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound (US) and MRI risk stratification systems were developed by an international group of experts in adnexal imaging to aid radiologists in assessing adnexal lesions. The goal of imaging is to appropriately triage patients with adnexal lesions. US is the first-line imaging modality for assessment, whereas MRI can be used as a problem-solving tool. Both US and MRI can accurately characterize benign lesions such as simple cysts, endometriomas, hemorrhagic cysts, and dermoid cysts, avoiding unnecessary or inappropriate surgery. In patients with a lesion that does not meet criteria for one of these benign diagnoses, MRI can further characterize the lesion with an improved specificity for cancer and the ability to provide a probable histologic subtype in the presence of certain MRI features. This allows personalized treatment, including avoiding overly extensive surgery or allowing fertility-sparing procedures for suspected benign, borderline, or low-grade tumors. When MRI findings indicate a risk of an invasive cancer, patients can be expeditiously referred to a gynecologic oncologic surgeon. This narrative review provides expert opinion on the utility of multiparametric MRI when using the O-RADS US and MRI management systems.

Practical Tips for Reporting Adnexal Lesions Using O-RADS MRI.

The Ovarian-Adnexal Reporting and Data System (O-RADS) MRI risk stratification system provides a standardized lexicon and evidence-based risk score for evaluation of adnexal lesions. The goals of the lexicon and risk score are to improve report quality and communication between radiologists and clinicians, reduce variability in the reporting language, and optimize management of adnexal lesions. The O-RADS MRI risk score is based on the presence or absence of specific imaging features, including the lipid content, enhancing solid tissue, number of loculi, and fluid type. The probability of malignancy ranges from less than 0.5% when there are benign features to approximately 90% when there is solid tissue with a high-risk time-intensity curve. This information can aid in optimizing management of patients with adnexal lesions. The authors present an algorithmic approach to the O-RADS MRI risk stratification system and highlight key teaching points and common pitfalls. © RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Traumatic injuries among Alaska's young workers: Linking cases from four data systems.

BACKGROUND: Young workers (aged 15-24 years) experience higher rates of job-related injury compared with workers aged 25-44 years in the United States. Young workers may have limited or no prior work experience or safety training, which can contribute to their injury risk. In 2018, Alaska had the second highest work-related fatality rate and 14th highest non-fatal injury rate in the United States. This study aimed to characterize nonfatal and fatal occupational injuries among young workers in Alaska. METHODS: To describe injury patterns among Alaska young workers from 2014-2018, we used data from four datasets: Alaska Workers' Compensation, Alaska Occupational Injury Surveillance System, Alaska Trauma Registry, and Alaska Fishermen's Fund. The datasets were merged two at a time and filtered by the worker characteristics (e.g., age and sex) and incident characteristics (e.g., date of injury). Duplicates were then manually identified between the datasets using the variables above. The injury narrative and Occupational Injury and Illness Classification System codes were used last to verify true duplicates. Descriptive analyses were performed after the duplicates were merged. RESULTS: During the 5-year study period 2014-2018, young workers experienced 20 fatal and 12,886 nonfatal injuries. Residents of Alaska comprised 85% of nonfatal and 70% of fatal injuries. The top three major occupation groups with the highest number of injuries were production (1,391, 14%), food preparation (1,225, 12%), and transportation/material moving (1,166, 11%). The most common events leading to injuries were struck by object or equipment (2,027, 21%), overexertion involving outside sources (1,385, 14%), and struck against object or equipment (905, 9%). The most common nature of injuries were sprains/strains/tears (3,024, 29%), cuts/lacerations (1,955, 19%), and bruises/contusions (1,592, 15%). CONCLUSION: Although progress has been made in reducing worker injuries, Alaskan young workers still experience injuries and fatalities frequently. Based on findings, there is a clear need for employers, researchers, public health professionals, parents, and young workers to prioritize young worker safety through an integrated approach, from education and training to adequate workplace supervision and support.

Expanding the Molecular Alphabet of DNA-Based Data Storage Systems with Neural Network Nanopore Readout Processing.

DNA is a promising next-generation data storage medium, but challenges remain with synthesis costs and recording latency. Here, we describe a prototype of a DNA data storage system that uses an extended molecular alphabet combining natural and chemically modified nucleotides. Our results show that MspA nanopores can discriminate different combinations and ordered sequences of natural and chemically modified nucleotides in custom-designed oligomers. We further demonstrate single-molecule sequencing of the extended alphabet using a neural network architecture that classifies raw current signals generated by Oxford Nanopore sequencers with an average accuracy exceeding 60% (39× larger than random guessing). Molecular dynamics simulations show that the majority of modified nucleotides lead to only minor perturbations of the DNA double helix. Overall, the extended molecular alphabet may potentially offer a nearly 2-fold increase in storage density and potentially the same order of reduction in the recording latency, thereby enabling new implementations of molecular recorders.

[Diagnostic Value of American Thyroid Association Guidelines,American College of Radiology Thyroid Imaging Reporting and Data System,and Chinese Thyroid Imaging Reporting and Data System Alone and Combined With BRAFV600E Mutation in Atypia of Undetermined Significance/Follicular Lesion of Undetermined Significance].

Objective To explore the diagnostic efficacy of American Thyroid Association(ATA)guidelines,American College of Radiology Thyroid Imaging Report and Data System(ACR-TIRADS),and Chinese Thyroid Imaging Reporting and Data System(C-TIRADS)alone and combined with BRAFV600E mutation in atypia of undetermined significance/follicular lesion of undetermined significance(AUS/FLUS).Methods A total of 138 patients who underwent ultrasound-guided fine needle aspiration(FNA)in the Chinese PLA General Hospital from January 2020 to May 2023 were selected.The clinicopathological and ultrasound characteristics were retrospectively analyzed for each nodule.Each nodule underwent preoperative BRAFV600E mutation testing and was diagnosed according to the ATA guidelines,ACR-TIRADS,and C-TIRADS.The diagnostic efficacy of ATA guidelines,ACR-TIRADS,and C-TIRADS alone and combined with BRAFV600E mutation was assessed based on the results of histopathological diagnosis.Results The 138 AUS/FLUS thyroid nodules included 45(32.6%)benign ones and 93(67.4%)malignant ones.The patient age(t=1.444,P=0.151),gender(χ2=0.259,P=0.611),and location of nodules(χ2=2.055,P=0.358)had no statistical significance for the differentiation between benign and malignant nodules,while nodule size(Z=2.500,P=0.012),echo(χ2=14.693,P<0.001),composition(χ2=17.075,P<0.001),aspect ratio ≥1(χ2=9.477,P=0.002),and microcalcification(χ2=6.892,P=0.009)were of significance for the differentiation.When applied alone,BRAFV600E mutation showed high specificity(95.56%)and positive predictive value(95.65%).Among the three ultrasound grading systems,ACR-TIRADS had the highest sensitivity(χ2=37.923,P<0.001;χ2=40.462,P<0.001)and accuracy(χ2=81.595,P<0.001;χ2=76.912,P<0.001),while C-TIRADS had the highest specificity(χ2=11.746,P<0.001;χ2=21.235,P<0.001).However,the three systems showed no statistically significant difference in the diagnostic efficiency when applied alone(Z=1.177,P=0.239;Z=0.213,P=0.831;Z=1.016,P=0.310).The combination of BRAFV600E mutation with ACR-TIRADS or C-TIRADS improved the diagnostic efficacy of BRAFV600E mutation in distinguishing the benign and malignant AUS/FLUS nodules(Z=2.107,P=0.035;Z=2.752,P=0.006).The combination of ATA guidelines with BRAFV600E mutation increased the diagnostic accuracy of BRAFV600E mutation(χ2=20.679,P<0.001),while it had no statistically significant difference in distinguishing the benign and malignant AUS/FLUS nodules(Z=1.321,P=0.186).The combination of ATA guidelines,ACR-TIRADS,or C-TIRADS with BRAFV600E mutation improved the diagnostic efficacy of ultrasound grading systems for AUS/FLUS nodules(Z=2.770,P=0.006;Z=2.770,P=0.006;Z=2.890,P=0.004).Specifically,ACR-TIRADS combined with BRAFV600E mutation showed the highest sensitivity(χ2=4.712,P=0.030;χ2=4.712,P=0.030),while C-TIRADS combined with BRAFV600E mutation showed the highest accuracy(χ2=77.627,P<0.001;χ2=85.827,P<0.001).However,there were no statistically significant differences in diagnostic performance between the combinations(Z=1.276,P=0.202;Z=0.808,P=0.419;Z=1.615,P=0.106).Conclusion ATA guidelines,ACR-TIRADS,and C-TIRADS combined with BRAFV600E mutation can improve the diagnostic efficacy of BRAFV600E mutation or ultrasound grading system alone in AUS/FLUS nodules,which can facilitate the further management and treatment of such patients.

Thy-Wise: An interpretable machine learning model for the evaluation of thyroid nodules.

Current risk stratification systems for thyroid nodules suffer from low specificity and high biopsy rates. Recently, machine learning (ML) is introduced to assist thyroid nodule diagnosis but lacks interpretability. Here, we developed and validated ML models on 3965 thyroid nodules, as compared to the American College of Radiology Thyroid Imaging, Reporting and Data System (ACR TI-RADS). Subsequently, a SHapley Additive exPlanation (SHAP) algorithm was leveraged to interpret the results of the best-performing ML model. Clinical characteristics including thyroid-function tests were collected from medical records. Five ACR TI-RADS ultrasonography (US) categories plus nodule size were assessed by experienced radiologists. Random forest (RF), support vector machine (SVM) and extreme gradient boosting (XGBoost) were used to build US-only and US-clinical ML models. The ML models and ACR TI-RADS were compared in terms of diagnostic performance and unnecessary biopsy rate. Among the ML models, the US-only RF model (hereafter, Thy-Wise) achieved the optimal performance. Compared to ACR TI-RADS, Thy-Wise showed higher accuracy (82.4% vs 74.8% for the internal validation; 82.1% vs 73.4% for external validation) and specificity (78.7% vs 68.3% for internal validation; 78.5% vs 66.9% for external validation) while maintaining sensitivity (91.7% vs 91.2% for internal validation; 91.9% vs 91.1% for external validation), as well as reduced unnecessary biopsies (15.3% vs 32.3% for internal validation; 15.7% vs 47.3% for external validation). The SHAP-based interpretation of Thy-Wise enables clinicians to better understand the reasoning behind the diagnosis, which may facilitate the clinical translation of this model.

External Validation of O-RADS US Risk Stratification and Management System.

Background The Ovarian-Adnexal Reporting and Data System (O-RADS) US risk stratification and management system (O-RADS US) was designed to improve risk assessment and management of ovarian and adnexal lesions. Validation studies including both surgical and nonsurgical treatment as the reference standard remain lacking. Purpose To externally validate O-RADS US in women who underwent either surgical or nonsurgical treatment and to determine if incorporating acoustic shadowing as a benign finding improves diagnostic performance. Materials and Methods This retrospective study included consecutive women who underwent pelvic US between August 2015 and April 2017 at a tertiary referral oncology center. Two independent readers blinded to clinical and histologic outcome assigned an O-RADS risk category and an International Ovarian Tumor Analysis (IOTA) Assessment of Different NEoplasias in the adneXa (ADNEX) model risk of malignancy score to assessable lesions. Reference standards were surgical histopathology or 2-year imaging follow-up. Receiver operating characteristic (ROC) curve analysis was used to evaluate performance of the O-RADS US, ADNEX, and modified O-RADS models incorporating acoustic shadowing. Results In total, 227 women (mean age, 52 years ± 16 [SD]) with 262 ovarian or adnexal lesions were evaluated. Of these lesions, 187 (71%) were benign and 75 (29%) were malignant. The proportion of malignancy was 0% (0 of 100) for O-RADS 2, 3% (one of 32) for O-RADS 3, 35% (22 of 63) for O-RADS 4, and 78% (52 of 67) for O-RADS 5. The area under the ROC curve (AUC) for O-RADS and ADNEX was 0.91 (95% CI: 0.88, 0.94) and 0.95 (95% CI: 0.92, 0.97; P = .01), respectively. The addition of acoustic shadowing as a benign finding improved O-RADS AUC to 0.94 (95% CI: 0.91, 0.96; P = .01). Use of O-RADS 4 as a threshold yielded a sensitivity of 99% (74 of 75; 95% CI: 96, 100) and a specificity of 70% (131 of 187; 95% CI: 64, 77). Conclusion In a tertiary referral oncology center, the Ovarian-Adnexal Reporting and Data System US risk stratification and management system enabled accurate distinction of benign from malignant ovarian and adnexal lesions. Adding acoustic shadowing as a benign finding improved its diagnostic performance. © RSNA, 2022 See also the editorial by Levine in this issue.

Multiparametric MRI Evaluation of VI-RADS for Bladder Tumors Located at the Ureteral Orifice.

Background The Vesical Imaging Reporting and Data System (VI-RADS) based on multiparametric MRI scans standardizes preoperative bladder cancer staging. However, limitations have been reported for VI-RADS, particularly for ureteral orifice tumors. Purpose To investigate the diagnostic performance and interobserver agreement of VI-RADS in evaluating muscle invasion for bladder tumors located at the ureteral orifice. Materials and Methods In this retrospective study, patients with histopathologically confirmed bladder cancer occurring at the ureteral orifice from January 2012 to November 2021 were analyzed. Two blinded radiologists independently scored multiparametric MRI scans according to VI-RADS. Interobserver agreement of the VI-RADS scores was evaluated with weighted κ analysis. Receiver operating characteristic curve analysis was used to evaluate the diagnostic performance of the VI-RADS scores in the prediction of muscle invasion. Results A total of 78 patients (mean age, 67 years ± 7 [SD]; age range, 46-90 years; 67 men) were included in the final analysis: 25 with non-muscle-invasive bladder cancer and 53 with muscle-invasive bladder cancer (MIBCa). At consensus reading, one (1%) case was scored as VI-RADS 1, 27 cases (35%) were scored as VI-RADS 2, six (8%) were scored as VI-RADS 3, 10 (13%) were scored as VI-RADS 4, and 34 (44%) were scored as VI-RADS 5. On comparison of the VI-RADS score with histopathologic findings, it was confirmed that the presence of muscle invasion was 0% (zero of one) for VI-RADS 1, 15% (four of 27) for VI-RADS 2, 83% (five of six) for VI-RADS 3, 100% (10 of 10) for VI-RADS 4, and 100% (34 of 34) for VI-RADS 5. The area under the receiver operating characteristic curve of VI-RADS in the detection of MIBCa was 0.96 (95% CI: 0.92, 1.00). Conclusion The Vesical Imaging Reporting and Data System could be used to accurately predict muscle invasion for bladder tumors occurring at the ureteral orifice. © RSNA, 2022 Online supplemental material is available for this article.

Differential diagnosis of thyroid nodules by the Demetics ultrasound-assisted diagnosis system and contrast-enhanced ultrasound combined with thyroid image reporting and data systems.

BACKGROUND: More and more new ultrasound techniques with their own characteristics are applied in the differential diagnosis of thyroid nodules. This study amied to assess and compare the diagnostic value of the Demetics ultrasound-assisted diagnosis system and contrast-enhanced ultrasound (CEUS) combined with the Thyroid Image Reporting and Data Systems (TI-RADS) for thyroid nodules. DESIGN AND PATIENTS: A total of 600 thyroid nodules with pathological findings were retrospectively analysed. Demetics and CEUS were performed for all nodules. The diagnostic efficacy of Demetics and CEUS for nodules of different sizes was evaluated and compared in terms of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+) and negative likelihood ratio (LR-). The characteristics of nodules diagnosed and misdiagnosed by Demetics were compared to analyse the factors affecting the diagnostic accuracy of Demetics. The necessity of CEUS for nodules that are prone to misdiagnosis in Demetics was assessed. RESULTS: Both Demetics and CEUS can be used for the differential diagnosis of benign and malignant thyroid nodules of different sizes. The diagnostic agreement between Demetics and CEUS for thyroid nodules of different sizes was moderate, substantial and fair, respectively. The sensitivity and NPV of Demetics were higher than those of CEUS, and the specificity, PPV and LR+ of CEUS were higher than that of Demetics. The LR- of Demetics was lower than those of CEUS. There were significant differences in age, calcification and margin in analysing the factors affecting Demetics. CEUS correctly diagnosed 50 of the 101 nodules misdiagnosed by Demetics. CONCLUSIONS: Demetics showed high sensitivity in diagnosing thyroid nodules, while CEUS showed high specificity. In clinical practice, CEUS can further improve the diagnostic accuracy for nodules that are easily misdiagnosed by Demetics.

Prognostic implications of CT/MRI LI-RADS in hepatocellular carcinoma: State of the art and future directions.

Hepatocellular carcinoma (HCC) is the fourth most lethal malignancy with an increasing incidence worldwide. Management of HCC has followed several clinical staging systems that rely on tumour morphologic characteristics and clinical variables. However, these algorithms are unlikely to profile the full landscape of tumour aggressiveness and allow accurate prognosis stratification. Noninvasive imaging biomarkers on computed tomography (CT) or magnetic resonance imaging (MRI) exhibit a promising prospect to refine the prognostication of HCC. The Liver Imaging Reporting and Data System (LI-RADS) is a comprehensive system for standardizing the terminology, techniques, interpretation, reporting and data collection of liver imaging. At present, it has been widely accepted as an effective diagnostic system for HCC in at-risk patients. Emerging data have provided new insights into the potential of CT/MRI LI-RADS in HCC prognostication, which may help refine the prognostic paradigm of HCC that promises to direct individualized management and improve patient outcomes. Therefore, this review aims to summarize several prognostic imaging features at CT/MRI for patients with HCC; the available evidence regarding the use of LI-RDAS for evaluation of tumour biology and clinical outcomes, pitfalls of current literature, and future directions for LI-RADS in the management of HCC.