Simplifying risk stratification for thyroid nodules on ultrasound: validation and performance of an artificial intelligence thyroid imaging reporting and data system.

PURPOSE: To validate the performance of a recently created risk stratification system (RSS) for thyroid nodules on ultrasound, the Artificial Intelligence Thyroid Imaging Reporting and Data System (AI TI-RADS). MATERIALS AND METHODS: 378 thyroid nodules from 320 patients were included in this retrospective evaluation. All nodules had ultrasound images and had undergone fine needle aspiration (FNA). 147 nodules were Bethesda V or VI (suspicious or diagnostic for malignancy), and 231 were Bethesda II (benign). Three radiologists assigned features according to the AI TI-RADS lexicon (same categories and features as the American College of Radiology TI-RADS) to each nodule based on ultrasound images. FNA recommendations using AI TI-RADS and ACR TI-RADS were then compared and sensitivity and specificity for each RSS were calculated. RESULTS: Across three readers, mean sensitivity of AI TI-RADS was lower than ACR TI-RADS (0.69 vs 0.72, p < 0.02), while mean specificity was higher (0.40 vs 0.37, p < 0.02). Overall total number of points assigned by all three readers decreased slightly when using AI TI-RADS (5,998 for AI TI-RADS vs 6,015 for ACR TI-RADS), including more values of 0 to several features. CONCLUSION: AI TI-RADS performed similarly to ACR TI-RADS while eliminating point assignments for many features, allowing for simplification of future TI-RADS versions.

Do Prostate Imaging-Reporting and Data System (PIRADS) lesions predict holmium laser enucleation of prostate outcomes?

INTRODUCTION AND OBJECTIVES: Prostate magnetic resonance imaging (MRI) is used for prostate cancer (PCa) screening and risk stratification and is helpful for surgical planning for patients undergoing holmium laser enucleation of the prostate (HoLEP). There are few studies investigating the correlation between MRI Prostate Imaging-Reporting and Data System (PIRADS) lesion characteristics and HoLEP pathology and outcomes. METHODS: We performed retrospective review of patients who underwent HoLEP between January 2021 and August 2023 by a single surgeon. Preoperative, intraoperative, and postoperative characteristics and outcomes were analyzed for all patients who had a documented preoperative prostate MRI. RESULTS: There were 334 patients without a pre-existing diagnosis of PCa and with a preoperative prostate MRI, of which 140 (42%) had at least one PIRADS lesion. There was a total of 203 PIRADS lesions: 91 (45%) in the peripheral zone (PZ), 106 (52%) in the transition zone (TZ), and 6 (2%) not specified. Incidental PCa was noted in 44 (13%) patients at time of HoLEP. Presence or location of lesion was not significantly associated with rate or grade of incidental PCa on pathology. Greater number of lesions and lesion size correlated with longer procedure times. Lesion number, size, or grade were not found to correlate with cancer grade or rate of cancer. CONCLUSIONS: Grade, presence, location, size, and number of PIRADS lesions on preoperative prostate MRI for patients with an appropriate prior PCa workup were not significantly associated with incidental PCa or higher PCa grade on HoLEP pathology.

Perspectives on technology: Prostate Imaging-Reporting and Data System (PI-RADS) interobserver variability.

OBJECTIVES: To explore the topic of Prostate Imaging-Reporting and Data System (PI-RADS) interobserver variability, including a discussion of major sources, mitigation approaches, and future directions. METHODS: A narrative review of PI-RADS interobserver variability. RESULTS: PI-RADS was developed in 2012 to set technical standards for prostate magnetic resonance imaging (MRI), reduce interobserver variability at interpretation, and improve diagnostic accuracy in the MRI-directed diagnostic pathway for detection of clinically significant prostate cancer. While PI-RADS has been validated in selected research cohorts with prostate cancer imaging experts, subsequent prospective studies in routine clinical practice demonstrate wide variability in diagnostic performance. Radiologist and biopsy operator experience are the most important contributing drivers of high-quality care among multiple interrelated factors including variability in MRI hardware and technique, image quality, and population and patient-specific factors such as prostate cancer disease prevalence. Iterative improvements in PI-RADS have helped flatten the curve for novice readers and reduce variability. Innovations in image quality reporting, administrative and organisational workflows, and artificial intelligence hold promise in improving variability even further. CONCLUSION: Continued research into PI-RADS is needed to facilitate benchmark creation, reader certification, and independent accreditation, which are systems-level interventions needed to uphold and maintain high-quality prostate MRI across entire populations.

Association of Baseline Magnetic Resonance Imaging Prostate Imaging Reporting and Data System Score With Prostate Cancer Active Surveillance Early Biopsy Reclassification: Data From the Michigan Urological Surgery Improvement Collaborative (MUSIC).

PURPOSE: The purpose of our study was to evaluate the association of baseline MRI Prostate Imaging Reporting and Data System (PI-RADS) score with biopsy reclassification in a multicenter active surveillance (AS) cohort. MATERIALS AND METHODS: We identified men in the Michigan Urological Surgery Improvement Collaborative registry (46 hospital-based/academic/private practice urology groups) with National Comprehensive Cancer Network (NCCN) low-risk and favorable intermediate-risk prostate cancer who underwent MRI within 6 months before or after initial biopsy and enrolled in AS from June 2016 to January 2021. The primary objective was to determine the association of baseline MRI PI-RADS score (≥4 lesion) with reclassification to high-grade prostate cancer (≥grade group 3) on surveillance biopsy. Multivariable Cox proportional hazards regression models were constructed and adjusted for pathologic, MRI, and clinical/biopsy factors, with landmark time of 6 months from diagnostic biopsy. We included an interaction term between PI-RADS score and NCCN group in the Cox model. RESULTS: A total of 1491 men were included with median age 64 years (IQR: 59-69) with median follow-up 11.0 months (IQR: 6.0-23.0) after landmark. Baseline PI-RADS ≥ 4 lesion was associated with an increased hazard of biopsy reclassification (HR: 2.3 [95% CI: 1.6-3.2], P < .001), along with grade group 2 vs 1 (HR: 2.5 [95% CI: 1.7-3.7], P < .001), and increasing age (per 10 years; HR: 1.8 [95% CI: 1.4-2.4], P < .001). The interaction between NCCN risk group with MRI findings was not significant (P = .7). CONCLUSIONS: In this multicenter cohort study of real-world data, baseline MRI PI-RADS score was significantly associated with early biopsy reclassification in men undergoing AS with NCCN low- or favorable intermediate-risk prostate cancer.

Meaning of ACR-TIRADS recommendation in favor of follow-up rather than FNAC in thyroid nodules.

Thyroid Imaging Reporting and Data Systems (TIRADSs) have been largely diffused for their high accuracy in risk stratification of thyroid nodules (TNs) and their selection for fine-needle aspiration cytology (FNAC). The most popular TIRADSs are ACR-, EU-, and K-TIRADS, with some discrepancies each other. One major difference is that ACR-TIRADS includes a recommendation in favor of follow-up in TNs having a major diameter insufficient to indicate FNAC. The present study aimed to explore prevalence and significance of this recommendation. EU- and K-TIRADS were used as comparator. A retrospective series of thyroidectomies was searched according to a pre-defined protocol. The study period was 2019-2023. Preoperative ultrasound images were reviewed by radiologists blinded of clinical data. Matching of TIRADS and histology was performed later. Histology was the gold standard. The study series included 39 TNs classified as category 3, 4, or 5 and assessed for follow-up according to ACR-TIRADS. The overall cancer frequency was 25.6%, being 13% in category 3, 20% in category 4, and 83.3% in category 5. The category assessment according to ACR-, EU-, and K-TIRADS was not significantly different. EU-TIRADS indicated FNAC in 10 TNs of which two cancers and eight benign lesions. K-TIRADS recommended FNAC in 32 TNs of which seven cancers and 25 benign lesions. TNs assessed for follow-up according to ACR-TIRADS are cancer in one-fourth of cases. EU- and, especially, K-TIRADS allow us to select for FNAC cancers, with the burden of non-negligible frequency of unnecessary FNACs.

Effects of Implementation of European Thyroid Imaging Reporting and Data System Risk Stratification in a Thyroid Cancer Program in Western Sweden: A Retrospective Cohort Study.

OBJECTIVE: The European Thyroid Imaging Reporting and Data System (EU-TIRADS) allows for selective fine needle aspiration cytology (FNAC). In 2017, EU-TIRADS was implemented as part of a nationwide standardized care bundle for thyroid cancer in Western Sweden with a population of approximately 1.7 million. The objective of this study was to investigate the clinical value of EU-TIRADS attempting to reduce the number of unnecessary FNACs in referred patients with thyroid nodules. METHODS: The study cohort consisted of all patients referred to Sahlgrenska University Hospital due to a palpable, newly detected or growing thyroid nodules or a positron emission tomography-positive finding for examination with thyroid ultrasound and selective cytology between 2018 and 2022. Medical records on EU-TIRADS classification, corresponding FNAC results, and histopathologic diagnosis were retrospectively collected. Adherence to the EU-TIRADS guidelines, use of selective FNAC, and rate of malignancy in patients who underwent surgery were assessed. RESULTS: In total, 1246 thyroid nodules in 990 patients were evaluated. The distributions of EU-TIRADS 2 to 5 (number [percentage]) for all examined nodules were 63 (5%), 462 (37%), 443 (36%), and 278 (22%), respectively. FNAC was omitted in 7% of the investigated patients. FNAC was performed in 124 nodules (10%) despite not fulfilling the EU-TIRADS criteria or absence of positron emission tomography-positive findings. The rate of malignancy was 33% and 1/50 in patients who underwent "unnecessary" FNAC. CONCLUSION: Implementation of EU-TIRADS in routine management of thyroid nodules led to the selective use of FNAC; however, the clinical impact was limited. This study provides real-world data on the value and magnitude of diagnostic improvement by implementing EU-TIRADS in clinical practice.

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.

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.

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.

Counting Farm Injuries and Fatalities: An Assessment of Irish Occupational Health and Safety Surveillance Data Systems.

OBJECTIVE: Generation of reliable data underpins the effectiveness of Occupational Health and Safety (OHS) surveillance systems. Despite the importance of understanding OHS data systems, there are few papers that provide overviews of their structure and/or content. This paper introduces a basic framework for assessing OHS data systems that will be of use to researchers internationally. We applied this approach to assess the Irish OHS data system by undertaking a data mapping exercise. METHOD: We developed a checklist based on recommendations of monitoring and measurement of OHS proposed by the National Academies of Sciences, Engineering, and Medicine (USA). An assessment of published reports that present systematic OHS surveillance data was undertaken to identify the institutions or organisations responsible for collecting and curating the data, their remit, and, associated with this, their respective case definitions. We then provide an overview of the variables collected and these are then mapped against the checklist. RESULTS: The assessment highlights that whilst the farm fatalities dataset provides complete coverage of all fatalities, regardless of age or employment status, the same is not true of the three non-fatal injuries datasets reviewed. There are important differences in the data collection methods and, associated with this, which populations are covered. PRACTICAL APPLICATION: The assessment approach provides valuable insights into the strengths and weaknesses of a critical element of OHS surveillance systems, namely the production of datasets. This knowledge is important for researchers as understanding the data that informs their research is fundamental to good science. It is critical for policy-makers and other stakeholders to understand the strengths and weaknesses on which OHS policy, strategies, or education and training interventions are developed.

Systematic training of LI-RADS CT v2018 improves interobserver agreements and performances in LR categorization for focal liver lesions.

AIM: To retrospectively explored whether systematic training in the use of Liver Imaging Reporting and Data System (LI-RADS) v2018 on computed tomography (CT) can improve the interobserver agreements and performances in LR categorization for focal liver lesions (FLLs) among different radiologists. MATERIALS AND METHODS: A total of 18 visiting radiologists and the liver multiphase CT images of 70 hepatic observations in 63 patients at high risk of HCC were included in this study. The LI-RADS v2018 training procedure included three thematic lectures, with an interval of 1 month. After each seminar, the radiologists had 1 month to adopt the algorithm into their daily work. The interobserver agreements and performances in LR categorization for FLLs among the radiologists before and after training were compared. RESULTS: After training, the interobserver agreements in classifying the LR categories for all radiologists were significantly increased for most LR categories (P < 0.001), except for LR-1 (P = 0.053). After systematic training, the areas under the curve (AUCs) for LR categorization performance for all participants were significantly increased for most LR categories (P < 0.001), except for LR-1 (P = 0.062). CONCLUSION: Systematic training in the use of the LI-RADS can improve the interobserver agreements and performances in LR categorization for FLLs among radiologists with different levels of experience.

Correlation of TIRADS scoring in thyroid nodules with preoperative fine needle aspiration biopsy and postoperative specimen pathology.

INTRODUCTION: The aim of our study is to determine the value of Thyroid Imaging Reporting and Data Systems (TIRADS) scoring in predicting malignancy in thyroid nodules by examining its relationship with fine needle aspiration biopsy and postoperative histopathological results. MATERIALS AND METHODS: In this study, patients who underwent surgery after ultrasonographic examination and fine needle aspiration biopsy for thyroid nodules at the General Surgery Clinic of Çukurova University Faculty of Medicine between January 2014 and November 2021 were retrospectively analyzed. The thyroid ultrasonography and fine needle aspiration biopsy of the included patients were performed by a clinician with 15 years of experience. The ultrasonographic features of the nodules were re-evaluated by the same clinician, and the American College of Radiology (ACR) TIRADS score was determined. Fine needle aspiration biopsy results were grouped according to Bethesda criteria. Postoperative histopathological examination results were divided into two groups: benign and malignant. The ACR TIRADS score was compared with fine needle aspiration biopsy and histopathological results. The performance of the ACR TIRADS score in predicting malignancy was determined. RESULTS: 79.8% of the 397 patients were female, and the mean age was 50.9 ± 12.8 years. The mean diameter of the nodules was 27.4 ± 15.8 mm. There was a significant, positive, but weak correlation between ACR TIRADS and Bethesda (p < 0.001) (r = 0.33). When the ACR TIRADS score was compared with histopathological results, it was found that the rate of malignancy increased as the TIRADS score increased (p < 0.001). The rates of malignancy diagnosis were 0% for TR1, 13.2% for TR2, 21.7% for TR3, 50.3% for TR4, and 72.4% for TR5. The area under the receiver operating characteristic curve for TIRADS in predicting malignancy was 0.747 (95% CI: 0.699-0.796, p < 0.001). TIRADS can distinguish malignancy with 75% accuracy. The optimal cutoff point was determined as TR4 with 80.3% sensitivity and 60.8% specificity. CONCLUSION: The ACR TIRADS scoring system is an effective risk classification system for thyroid nodules, providing 75% accuracy in predicting malignancy, with 80.3% sensitivity and 60.8% specificity values.

Adapting national data systems for donor transition: comparative analysis of experience from Georgia and China.

Health management information systems (HMISs) are essential in programme planning, budgeting, monitoring and evidence-informed decision-making. This paper focuses on donor transitions in two upper-middle-income countries, China and Georgia, and explores how national HMIS adaptations were made and what facilitated or limited successful and sustainable transitions. This comparative analytical case study uses a policy triangle framework and a mixed-methods approach to explore how and why adaptations in the HMIS occurred under the Gavi Alliance and the Global Fund-supported programmes in China and Georgia. A review of published and grey literature, key informant interviews and administrative data analysis informed the study findings. Contextual factors such as the global and country context, and health system and programme needs drove HMIS developments. Other factors included accountability on a national and international level; improvements in HMIS governance by establishing national regulations for clear mandates of data collection and reporting rules and creating institutional spaces for data use; investing in hardware, software and human resources to ensure regular and reliable data generation; and capacitating national players to use data in evidence-based decision-making for programme and transition planning, budgeting and outcome monitoring. Not all the HMIS initiatives supported by donors were sustained and transitioned. For the successful adaptation and sustainable transition, five interlinked and closely coordinated support areas need to be considered: (1) coupling programme design with a good understanding of the country context while considering domestic and external demands for information, (2) regulating appropriate governance and management arrangements enhancing country ownership, (3) avoiding silo HMIS solutions and taking integrative approach, (4) ensuring the transition of funding onto domestic budget and enforcing fulfilment of the government's financial commitments and finally (5) investing in technologies and skilled human resources for the HMIS throughout all levels of the health system. Neglecting any of these elements risks not delivering sustainable outcomes.

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.

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.

Modified American College of Radiology Thyroid Imaging Reporting and Data System and Modified Artificial Intelligence Thyroid Imaging Reporting and Data System for Thyroid Nodules: A Multicenter Retrospective Study.

Background: Risk stratification systems for thyroid nodules are limited by low specificity. The fine-needle aspiration (FNA) biopsy size thresholds and stratification criteria are based on evidence from the literature and expert consensus. Our aims were to investigate the optimal FNA biopsy size thresholds in the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) and artificial intelligence (AI) TI-RADS and to revise the stratification criteria in AI TI-RADS. Methods: A total of 2596 thyroid nodules (in 2511 patients) on ultrasound examination with definite pathological diagnoses were retrospectively identified from January 2017 to September 2021 in 6 participating Chinese hospitals. The modified criteria for ACR TI-RADS were as follows: (1) no FNA for TR3; (2) FNA threshold for TR4 increased to 2.5 cm. The modified criteria for AI TI-RADS were as follows: (1) 6-point nodules upgraded to TR5; (2) no FNA for TR3; (3) FNA threshold for TR4 increased to 2.5 cm. The diagnostic performance and the unnecessary FNA rate (UFR) of modified versions were compared with the original ACR TI-RADS. Results: Compared with the original ACR TI-RADS, the modified ACR (mACR) TI-RADS yielded higher specificity (73% vs. 46%), accuracy (74% vs. 51%), area under the receiver operating characteristic curve (AUC; 0.80 vs. 0.70), and lower UFR (25% vs. 48%; all p < 0.001), although the sensitivity was slightly decreased (87% vs. 93%, p = 0.057). Compared with the original ACR TI-RADS, the modified AI (mAI) TI-RADS yielded higher specificity (73% vs. 46%), accuracy (75% vs. 51%), AUC (0.81 vs. 0.70), and lower UFR (24% vs. 48%; all p < 0.001), although the sensitivity tended to be slightly decreased (89% vs. 93%, p = 0.13). There was no significant difference between the mACR TI-RADS and mAI TI-RADS in the diagnostic performance and UFR (all p > 0.05). Conclusions: The revised FNA thresholds and the stratification criteria of the mACR TI-RADS and mAI TI-RADS may be associated with improvements in specificity and accuracy, without significantly sacrificing sensitivity for malignancy detection.

Achieving COVID-19 and Routine Immunization Data Systems Integration on the Electronic Management of Immunization Data System in Nigeria.

BACKGROUND: In 2021, Nigeria developed a novel Electronic Management of Immunization Data (EMID) system to address COVID-19 data management challenges and ensure the successful implementation of its COVID-19 vaccine deployment plan. The EMID system was envisioned to be interoperable with the DHIS2 national data management system and serve as a gateway into the integration of other primary health care (PHC) service data management. However, the EMID system faced challenges, including inability to filter reports, missing or loss of data, and difficulties with data synchronization, which curtailed its potential to meet the country's needs for COVID-19 data management and negatively impacted system scalability to enable integration with other PHC data systems. METHODS: Multilayered stakeholder interviews were conducted to determine the optimal functionality requirements for the EMID system. Based on these findings, an optimization plan was designed and implemented to address identified gaps and create a more stable and scalable system to enable further system integrations. Following optimization, a routine immunization module was developed and integrated with the EMID system as a first step to achieving an integrated data management system for PHC services in Nigeria. RESULTS: The integrated system currently provides an opportunity to address data fragmentation and strengthen PHC service delivery in Nigeria. By allowing 1 health care worker to deliver both vaccinations, there is also potential for reduction in cost and redundancies, informing redistribution of the health workforce and overall system strengthening. CONCLUSION: The journey from the initial challenges faced by the EMID system to the development of an integrated system for PHC services in Nigeria has been a transformative one. Through a thorough optimization process, training and capacity-building, stakeholder-driven improvements, and an elicitation exercise, the EMID system has evolved into a powerful tool for addressing data fragmentation and enhancing public health service delivery in the country.

American Thyroid Association and Thyroid Imaging Reporting and Data System developed by the American College of Radiology: which one is better at predicting malignancy risk?

OBJECTIVE: The aim of this study was to compare the capacity of American Thyroid Association and Thyroid Imaging Reporting and Data System developed by the American College of Radiology in predicting malignancy risk of thyroid nodules and to verify which one is better at avoiding unnecessary fine needle aspiration. METHODS: This was a cross-sectional study with 565 thyroid nodules, followed at a tertiary care hospital, in an iodine-replete area. Those were classified as American Thyroid Association and Thyroid Imaging Reporting and Data System developed by the American College of Radiology systems and stratified according to the Bethesda classification of fine needle aspiration. The values of sensibility, specificity, positive predictive value, and negative predictive value accuracy were calculated. Also, the percentage of unnecessary biopsies was presented. RESULTS: The mean age of the individuals was 58.2±13.5 [26-90] years for benign nodules and 41.7±15.6 [23-66] years for malignant nodules (p=0.002). Regarding gender, 92.6% (n=150) of the individuals with benign nodules and 85.7% (n=06) with malignant nodules were females (p=0.601). For American Thyroid Association, 90.9% of sensibility, 51.4% of specificity, 52.6% of accuracy, 10.2% of positive predictive value, and 98.9% of negative predictive value were found. For Thyroid Imaging Reporting and Data System developed by the American College of Radiology, 90.9% of sensibility, 49.7% of specificity, 52.1% of accuracy, 9.9% of positive predictive value, and 98.9% of negative predictive value were found. .Notably, 12.3% of unnecessary fine needle aspiration were found in American Thyroid Association and 44.4% were found in Thyroid Imaging Reporting and Data System developed by the American College of Radiology. CONCLUSION: Both Thyroid Imaging Reporting and Data System developed by the American College of Radiology and American Thyroid Association are able to predict the malignancy risk of thyroid nodules. Thyroid Imaging Reporting and Data System developed by the American College of Radiology was better at avoiding unnecessary fine needle aspiration.

Performance of Neck Imaging Reporting and Data System (NI-RADS) for Diagnosis of Recurrence of Head and Neck Squamous Cell Carcinoma: A Systematic Review and Meta-analysis.

BACKGROUND: The Neck Imaging Reporting and Data System (NI-RADS) is a reporting template used in head and neck cancer posttreatment follow-up imaging. PURPOSE: Our aim was to evaluate the pooled detection rates of the recurrence of head and neck squamous cell carcinoma based on each NI-RADS category and to compare the diagnostic accuracy between NI-RADS 2 and 3 cutoffs. DATA SOURCES: The MEDLINE, Scopus, and EMBASE databases were searched. STUDY SELECTION: This systematic review identified 7 studies with a total of 694 patients (1233 lesions) that were eligible for the meta-analysis. DATA ANALYSIS: The meta-analysis of pooled recurrence detection rate estimates for each NI-RADS category and the diagnostic accuracy of recurrence with NI-RADS 3 or 2 as the cutoff was performed. DATA SYNTHESIS: The estimated recurrence rates in each category for primary lesions were 74.4% for NI-RADS 3, 29.0% for NI-RADS 2, and 4.2% for NI-RADS 1. The estimated recurrence rates in each category for cervical lymph nodes were 73.3% for NI-RADS 3, 14.3% for NI-RADS 2, and 3.5% for NI-RADS 1. The area under the curve of the summary receiver operating characteristic for recurrence detection with NI-RADS 3 as the cutoff was 0.887 and 0.983, respectively, higher than 0.869 and 0.919 for the primary sites and cervical lymph nodes, respectively, with NI-RADS 2 as the cutoff. LIMITATIONS: Given the heterogeneity of the data of the studies, the conclusions should be interpreted with caution. CONCLUSIONS: This meta-analysis revealed estimated recurrence rates for each NI-RADS category for primary lesions and cervical lymph nodes and showed that NI-RADS 3 has a high diagnostic performance for detecting recurrence.