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Objective: To evaluate the use of reporting checklists and quality scoring tools for self-reporting purposes in radiomics literature. Methods: Literature search was conducted in PubMed (date, April 23, 2023). The radiomics literature was sampled at random after a sample size calculation with a priori power analysis. A systematic assessment for self-reporting, including the use of documentation such as completed checklists or quality scoring tools, was conducted in original research papers. These eligible papers underwent independent evaluation by a panel of nine readers, with three readers assigned to each paper. Automatic annotation was used to assist in this process. Then, a detailed item-by-item confirmation analysis was carried out on papers with checklist documentation, with independent evaluation of two readers. Results: The sample size calculation yielded 117 papers. Most of the included papers were retrospective (94%; 110/117), single-center (68%; 80/117), based on their private data (89%; 104/117), and lacked external validation (79%; 93/117). Only seven papers (6%) had at least one self-reported document (Radiomics Quality Score (RQS), Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD), or Checklist for Artificial Intelligence in Medical Imaging (CLAIM)), with a statistically significant binomial test (p < 0.001). Median rate of confirmed items for all three documents was 81% (interquartile range, 6). For quality scoring tools, documented scores were higher than suggested scores, with a mean difference of − 7.2 (standard deviation, 6.8). Conclusion: Radiomic publications often lack self-reported checklists or quality scoring tools. Even when such documents are provided, it is essential to be cautious, as the accuracy of the reported items or scores may be questionable. Clinical relevance statement: Current state of radiomic literature reveals a notable absence of self-reporting with documentation and inaccurate reporting practices. This critical observation may serve as a catalyst for motivating the radiomics community to adopt and utilize such tools appropriately, thereby fostering rigor, transparency, and reproducibility of their research, moving the field forward. Key Points: • In radiomics literature, there has been a notable absence of self-reporting with documentation. • Even if such documents are provided, it is critical to exercise caution because the accuracy of the reported items or scores may be questionable. • Radiomics community needs to be motivated to adopt and appropriately utilize the reporting checklists and quality scoring tools. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the usage of a well-known and widely adopted checklist, Checklist for Artificial Intelligence in Medical imaging (CLAIM), for self-reporting through a systematic analysis of its citations. Methods: Google Scholar, Web of Science, and Scopus were used to search for citations (date, 29 April 2023). CLAIM's use for self-reporting with proof (i.e., filled-out checklist) and other potential use cases were systematically assessed in research papers. Eligible papers were evaluated independently by two readers, with the help of automatic annotation. Item-by-item confirmation analysis on papers with checklist proof was subsequently performed. Results: A total of 391 unique citations were identified from three databases. Of the 118 papers included in this study, 12 (10%) provided a proof of self-reported CLAIM checklist. More than half (70; 59%) only mentioned some sort of adherence to CLAIM without providing any proof in the form of a checklist. Approximately one-third (36; 31%) cited the CLAIM for reasons unrelated to their reporting or methodological adherence. Overall, the claims on 57 to 93% of the items per publication were confirmed in the item-by-item analysis, with a mean and standard deviation of 81% and 10%, respectively. Conclusion: Only a small proportion of the publications used CLAIM as checklist and supplied filled-out documentation; however, the self-reported checklists may contain errors and should be approached cautiously. We hope that this systematic citation analysis would motivate artificial intelligence community about the importance of proper self-reporting, and encourage researchers, journals, editors, and reviewers to take action to ensure the proper usage of checklists. Clinical relevance statement: Only a small percentage of the publications used CLAIM for self-reporting with proof (i.e., filled-out checklist). However, the filled-out checklist proofs may contain errors, e.g., false claims of adherence, and should be approached cautiously. These may indicate inappropriate usage of checklists and necessitate further action by authorities. Key Points: • Of 118 eligible papers, only 12 (10%) followed the CLAIM checklist for self-reporting with proof (i.e., filled-out checklist). More than half (70; 59%) only mentioned some kind of adherence without providing any proof. • Overall, claims on 57 to 93% of the items were valid in item-by-item confirmation analysis, with a mean and standard deviation of 81% and 10%, respectively. • Even with the checklist proof, the items declared may contain errors and should be approached cautiously. [ABSTRACT FROM AUTHOR]

Many studies and systematic reviews have been published about MRI of the knee and its structures, discussing detailed anatomy, imaging findings, and correlations between imaging and clinical findings. This paper includes evidence-based recommendations for a general radiologist regarding choice of imaging sequences and reporting basic MRI examinations of the knee. We recommend using clinicians' terminology when it is applicable to the imaging findings, for example, when reporting meniscal, ligament and tendon, or cartilage pathology. The intent is to standardise reporting language and to make reports less equivocal. The aim of the paper is to improve the usefulness of the MRI report by understanding the strengths and limitations of the MRI exam with regard to clinical correlation. We hope the implementation of these recommendations into radiological practice will increase diagnostic accuracy and consistency by avoiding pitfalls and reducing overcalling of pathology on MRI of the knee. Clinical relevance statement: The recommendations presented here are meant to aid general radiologists in planning and assessing studies to evaluate acute and chronic knee findings by advocating the use of unequivocal terminology and discussing the strengths and limitations of MRI examination of the knee. Key Points: • On MRI, the knee should be examined and assessed in three orthogonal imaging planes. • The basic general protocol must yield T2-weighted fluid-sensitive and T1-weighted images. • The radiological assessment should include evaluation of ligamentous structures, cartilage, bony structures and bone marrow, soft tissues, bursae, alignment, and incidental findings. [ABSTRACT FROM AUTHOR]

Objectives: The objective of this systematic review was to offer a comprehensive overview and explore the associated outcomes from imaging referral guidelines on various key stakeholders, such as patients and radiologists. Materials and methods: An electronic database search was conducted in Medline, Embase and Web of Science to retrieve citations published between 2013 and 2023. The search was constructed using medical subject headings and keywords. Only full-text articles and reviews written in English were included. The quality of the included papers was assessed using the mixed methods appraisal tool. A narrative synthesis was undertaken for the selected articles. Results: The search yielded 4384 records. Following the abstract, full-text screening, and removal of duplication, 31 studies of varying levels of quality were included in the final analysis. Imaging referral guidelines from the American College of Radiology were most commonly used. Clinical decision support systems were the most evaluated mode of intervention, either integrated or standalone. Interventions showed reduced patient radiation doses and waiting times for imaging. There was a general reduction in radiology workload and utilisation of diagnostic imaging. Low-value imaging utilisation decreased with an increase in the appropriateness of imaging referrals and ratings and cost savings. Clinical effectiveness was maintained during the intervention period without notable adverse consequences. Conclusion: Using evidence-based imaging referral guidelines improves the quality of healthcare and outcomes while reducing healthcare costs. Imaging referral guidelines are one essential component of improving the value of radiology in the healthcare system. Clinical relevance statement: There is a need for broader dissemination of imaging referral guidelines to healthcare providers globally in tandem with the harmonisation of the application of these guidelines to improve the overall value of radiology within the healthcare system. Key Points: The application of imaging referral guidelines has an impact and effect on patients, radiologists, and health policymakers. The adoption of imaging referral guidelines in clinical practice can impact healthcare costs and improve healthcare quality and outcomes. Implementing imaging referral guidelines contributes to the attainment of value-based radiology. [ABSTRACT FROM AUTHOR]

Objectives: The revised European Society of Musculoskeletal Radiology (ESSR) consensus guidelines on soft tissue tumor imaging represent an update of 2015 after technical advancements, further insights into specific entities, and revised World Health Organization (2020) and AJCC (2017) classifications. This second of three papers covers algorithms once histology is confirmed: (1) standardized whole-body staging, (2) special algorithms for non-malignant entities, and (3) multiplicity, genetic tumor syndromes, and pitfalls. Materials and methods: A validated Delphi method based on peer-reviewed literature was used to derive consensus among a panel of 46 specialized musculoskeletal radiologists from 12 European countries. Statements that had undergone interdisciplinary revision were scored online by the level of agreement (0 to 10) during two iterative rounds, that could result in 'group consensus', 'group agreement', or 'lack of agreement'. Results: The three sections contain 24 statements with comments. Group consensus was reached in 95.8% and group agreement in 4.2%. For whole-body staging, pulmonary MDCT should be performed in all high-grade sarcomas. Whole-body MRI is preferred for staging bone metastasis, with [18F]FDG-PET/CT as an alternative modality in PET-avid tumors. Patients with alveolar soft part sarcoma, clear cell sarcoma, and angiosarcoma should be screened for brain metastases. Special algorithms are recommended for entities such as rhabdomyosarcoma, extraskeletal Ewing sarcoma, myxoid liposarcoma, and neurofibromatosis type 1 associated malignant peripheral nerve sheath tumors. Satisfaction of search should be avoided in potential multiplicity. Conclusion: Standardized whole-body staging includes pulmonary MDCT in all high-grade sarcomas; entity-dependent modifications and specific algorithms are recommended for sarcomas and non-malignant soft tissue tumors. Clinical relevance statement: These updated ESSR soft tissue tumor imaging guidelines aim to provide support in decision-making, helping to avoid common pitfalls, by providing general and entity-specific algorithms, techniques, and reporting recommendations for whole-body staging in sarcoma and non-malignant soft tissue tumors. Key Points: An early, accurate, diagnosis is crucial for the prognosis of patients with soft tissue tumors. These updated guidelines provide best practice expert consensus for standardized imaging algorithms, techniques, and reporting. Standardization can improve the comparability examinations and provide databases for large data analysis. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the intra- and inter-rater reliability of the total radiomics quality score (RQS) and the reproducibility of individual RQS items' score in a large multireader study. Methods: Nine raters with different backgrounds were randomly assigned to three groups based on their proficiency with RQS utilization: Groups 1 and 2 represented the inter-rater reliability groups with or without prior training in RQS, respectively; group 3 represented the intra-rater reliability group. Thirty-three original research papers on radiomics were evaluated by raters of groups 1 and 2. Of the 33 papers, 17 were evaluated twice with an interval of 1 month by raters of group 3. Intraclass coefficient (ICC) for continuous variables, and Fleiss' and Cohen's kappa (k) statistics for categorical variables were used. Results: The inter-rater reliability was poor to moderate for total RQS (ICC 0.30–055, p < 0.001) and very low to good for item's reproducibility (k − 0.12 to 0.75) within groups 1 and 2 for both inexperienced and experienced raters. The intra-rater reliability for total RQS was moderate for the less experienced rater (ICC 0.522, p = 0.009), whereas experienced raters showed excellent intra-rater reliability (ICC 0.91–0.99, p < 0.001) between the first and second read. Intra-rater reliability on RQS items' score reproducibility was higher and most of the items had moderate to good intra-rater reliability (k − 0.40 to 1). Conclusions: Reproducibility of the total RQS and the score of individual RQS items is low. There is a need for a robust and reproducible assessment method to assess the quality of radiomics research. Clinical relevance statement: There is a need for reproducible scoring systems to improve quality of radiomics research and consecutively close the translational gap between research and clinical implementation. Key Points: • Radiomics quality score has been widely used for the evaluation of radiomics studies. • Although the intra-rater reliability was moderate to excellent, intra- and inter-rater reliability of total score and point-by-point scores were low with radiomics quality score. • A robust, easy-to-use scoring system is needed for the evaluation of radiomics research. [ABSTRACT FROM AUTHOR]

Objectives: To perform a Delphi-based consensus on published evidence on image-guided interventional procedures for peripheral nerves of the lower limb (excluding Morton's neuroma) and provide clinical indications.Methods: We report the results of a Delphi-based consensus of 53 experts from the European Society of Musculoskeletal Radiology who reviewed the published literature for evidence on image-guided interventional procedures offered around peripheral nerves in the lower limb (excluding Morton's neuroma) to derive their clinical indications. Experts drafted a list of statements and graded them according to the Oxford Centre for evidence-based medicine levels of evidence. Consensus was considered strong when > 95% of experts agreed with the statement or broad when > 80% but < 95% agreed. The results of the Delphi-based consensus were used to write the paper.Results: Nine statements on image-guided interventional procedures for peripheral nerves of the lower limb have been drafted. All of them received strong consensus. Image-guided pudendal nerve block is safe, effective, and well tolerated with few complications. US-guided perisciatic injection of anesthetic provides good symptom relief in patients with piriformis syndrome; however, the addition of corticosteroids to local anesthetics still has an unclear role. US-guided lateral femoral cutaneous nerve block can be used to provide effective post-operative regional analgesia.Conclusion: Despite the promising results reported by published papers on image-guided interventional procedures for peripheral nerves of the lower limb, there is still a lack of evidence on the efficacy of most procedures.Key Points: • Image-guided pudendal nerve block is safe, effective, and well tolerated with few complications. • US-guided perisciatic injection of anesthetic provides good symptom relief in patients with piriformis syndrome; however, the addition of corticosteroids to local anesthetics still has an unclear role. • US-guided lateral femoral cutaneous nerve block can be used to provide effective post-operative regional analgesia. The volume of local anesthetic affects the size of the blocked sensory area. [ABSTRACT FROM AUTHOR]

Creating a patient-centered experience is becoming increasingly important for radiology departments around the world. The goal of patient-centered radiology is to ensure that radiology services are sensitive to patients' needs and desires. This article provides a framework for addressing the patient's experience by dividing their imaging journey into three distinct time periods: pre-exam, day of exam, and post-exam. Each time period has aspects that can contribute to patient anxiety. Although there are components of the patient journey that are common in all regions of the world, there are also unique features that vary by location. This paper highlights innovative solutions from different parts of the world that have been introduced in each of these time periods to create a more patient-centered experience. Clinical relevance statement: Adopting innovative solutions that help patients understand their imaging journey and decrease their anxiety about undergoing an imaging examination are important steps in creating a patient centered imaging experience. Key points: • Patients often experience anxiety during their imaging journey and decreasing this anxiety is an important component of patient centered imaging. • The patient imaging journey can be divided into three distinct time periods: pre-exam, day of exam, and post-exam. • Although components of the imaging journey are common, there are local differences in different regions of the world that need to be considered when constructing a patient centered experience. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the membranous urethral length (MUL) measurement and its interobserver agreement, and propose literature-based recommendations to standardize MUL measurement for increasing interobserver agreement. MUL measurements based on prostate MRI scans, for urinary incontinence risk assessment before radical prostatectomy (RP), may influence treatment decision-making in men with localised prostate cancer. Before implementation in clinical practise, MRI-based MUL measurements need standardization to improve observer agreement. Methods: Online libraries were searched up to August 5, 2022, on MUL measurements. Two reviewers performed article selection and critical appraisal. Papers reporting on preoperative MUL measurements and urinary continence correlation were selected. Extracted information included measuring procedures, MRI sequences, population mean/median values, and observer agreement. Results: Fifty papers were included. Studies that specified the MRI sequence used T2-weighted images and used either coronal images (n = 13), sagittal images (n = 18), or both (n = 12) for MUL measurements. 'Prostatic apex' was the most common description of the proximal membranous urethra landmark and 'level/entry of the urethra into the penile bulb' was the most common description of the distal landmark. Population mean (median) MUL value range was 10.4–17.1 mm (7.3–17.3 mm), suggesting either population or measurement differences. Detailed measurement technique descriptions for reproducibility were lacking. Recommendations on MRI-based MUL measurement were formulated by using anatomical landmarks and detailed descriptions and illustrations. Conclusions: In order to improve on measurement variability, a literature-based measuring method of the MUL was proposed, supported by several illustrative case studies, in an attempt to standardize MRI-based MUL measurements for appropriate urinary incontinence risk preoperatively. Clinical relevance statement: Implementation of MUL measurements into clinical practise for personalized post-prostatectomy continence prediction is hampered by lack of standardization and suboptimal interobserver agreement. Our proposed standardized MUL measurement aims to facilitate standardization and to improve the interobserver agreement. Key Points: • Variable approaches for membranous urethral length measurement are being used, without detailed description and with substantial differences in length of the membranous urethra, hampering standardization. • Limited interobserver agreement for membranous urethral length measurement was observed in several studies, while preoperative incontinence risk assessment necessitates high interobserver agreement. • Literature-based recommendations are proposed to standardize MRI-based membranous urethral length measurement for increasing interobserver agreement and improving preoperative incontinence risk assessment, using anatomical landmarks on sagittal T2-weighted images. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the model-, code-, and data-sharing practices in the current radiomics research landscape and to introduce a radiomics research database. Methods: A total of 1254 articles published between January 1, 2021, and December 31, 2022, in leading radiology journals (European Radiology, European Journal of Radiology, Radiology, Radiology: Artificial Intelligence, Radiology: Cardiothoracic Imaging, Radiology: Imaging Cancer) were retrospectively screened, and 257 original research articles were included in this study. The categorical variables were compared using Fisher's exact tests or chi-square test and numerical variables using Student's t test with relation to the year of publication. Results: Half of the articles (128 of 257) shared the model by either including the final model formula or reporting the coefficients of selected radiomics features. A total of 73 (28%) models were validated on an external independent dataset. Only 16 (6%) articles shared the data or used publicly available open datasets. Similarly, only 20 (7%) of the articles shared the code. A total of 7 (3%) articles both shared code and data. All collected data in this study is presented in a radiomics research database (RadBase) and could be accessed at https://github.com/EuSoMII/RadBase. Conclusion: According to the results of this study, the majority of published radiomics models were not technically reproducible since they shared neither model nor code and data. There is still room for improvement in carrying out reproducible and open research in the field of radiomics. Clinical relevance statement: To date, the reproducibility of radiomics research and open science practices within the radiomics research community are still very low. Ensuring reproducible radiomics research with model-, code-, and data-sharing practices will facilitate faster clinical translation. Key Points: • There is a discrepancy between the number of published radiomics papers and the clinical implementation of these published radiomics models. • The main obstacle to clinical implementation is the lack of model-, code-, and data-sharing practices. • In order to translate radiomics research into clinical practice, the radiomics research community should adopt open science practices. [ABSTRACT FROM AUTHOR]

Objectives: Clarity regarding accuracy and effectiveness for interventional procedures around the foot and ankle is lacking. Consequently, a board of 53 members of the Ultrasound and Interventional Subcommittees of the European Society of Musculoskeletal Radiology (ESSR) reviewed the published literature to evaluate the evidence on image-guided musculoskeletal interventional procedures around this anatomical region. Methods: We report the results of a Delphi-based consensus of 53 experts from the European Society of Musculoskeletal Radiology who reviewed the published literature for evidence on image-guided interventional procedures offered around foot and ankle in order to derive their clinical indications. Experts drafted a list of statements and graded them according to the Oxford Centre for evidence-based medicine levels of evidence. Consensus was considered strong when > 95% of experts agreed with the statement or broad when > 80% but < 95% agreed. The results of the Delphi-based consensus were used to write the paper that was shared with all panel members for final approval. Results: A list of 16 evidence-based statements on clinical indications for image-guided musculoskeletal interventional procedures in the foot and ankle were drafted after a literature review. The highest level of evidence was reported for four statements, all receiving 100% agreement. Conclusion: According to this consensus, image-guided interventions should not be considered a first-level approach for treating Achilles tendinopathy, while ultrasonography guidance is strongly recommended to improve the efficacy of interventional procedures for plantar fasciitis and Morton's neuroma, particularly using platelet-rich plasma and corticosteroids, respectively. Key Points: • The expert panel of the ESSR listed 16 evidence-based statements on clinical indications of image-guided musculoskeletal interventional procedures in the foot and ankle. • Strong consensus was obtained for all statements. • The highest level of evidence was reached by four statements concerning the effectiveness of US-guided injections of corticosteroid for Morton's neuroma and PRP for plantar fasciitis. [ABSTRACT FROM AUTHOR]

Objectives: To develop and evaluate methods for assembling radiopaque printed paper sheets to realistic patient phantoms for CT dose and image quality testing.Methods: CT images of two patients were radiopaque printed with aqueous potassium iodide solution (0.6 g/ml) on paper. Two methods were developed for assembling the paper sheets to head and neck phantoms. (1) Printed sheets were fed to a paper-based 3D printer along with corresponding 3D printable STL files. (2) Paper stacks of 5-mm thickness were glued with toner, cut to the patient shape and assembled to a phantom. In a sample application study, both phantoms were examined with five different tube current settings. Images were reconstructed using filtered-back projection (FBP) and iterative reconstruction (AIDR 3D) with three strength levels. Dose length product (DLP), signal-to-noise ratios (SNR) and contrast-to-noise ratios (CNRs) were analysed. Data were analysed using 2-way analysis of variance (ANOVA).Results: Both methods achieved anthropomorphic phantoms with detailed patient anatomy. The 3D printer yielded a precise reproduction of the external patient shape, but caused visible glue artefacts. Gluing with toner avoided these artefacts and yielded more flexibility with regard to phantom size. In the sample application study, non-inferior SNR and CNR and up to 83.7% lower DLP were achieved on the phantoms with AIDR 3D compared with FBP.Conclusions: Two methods for assembling radiopaque printed paper sheets to phantoms of individual patients are presented. The sample application demonstrates potential for simulation of patient imaging and systematic CT dose and image quality assessment.Key Points: • Two methods were developed to create realistic CT phantoms of individual patients from radiopaque printed paper sheets. • Analysis of five tube current and four reconstruction settings on two radiopaque 3D printed patient phantoms yielded non-inferior SNR and CNR and up to 83.7% lower dose with iterative reconstruction in comparison with filtered back projection. • Radiopaque 3D printed phantoms can simulate patients and allow systematic analysis of CT dose and image quality parameters. [ABSTRACT FROM AUTHOR]

Objectives: Interventional procedures around the knee are widely adopted for treating different musculoskeletal conditions. A panel of experts from the Ultrasound and Interventional Subcommittees of the European Society of Musculoskeletal Radiology (ESSR) reviewed the existing literature to assess the evidence on image-guided musculoskeletal interventional procedures around the knee, with the goal of highlighting some controversies associated with these procedures, specifically the role of imaging guidance, as well as the efficacy of the medications routinely injected.Methods: We report the results of a Delphi-based consensus of 53 experts in musculoskeletal radiology, who reviewed the published literature for evidence on image-guided interventional procedures around the knee to derive a list of pertinent clinical indications.Results: A list of 10 statements about clinical indications of image-guided procedures around the knee was created by a Delphi-based consensus. Only two of them had the highest level of evidence; all of them received 100% consensus.Conclusions: Ultrasonography guidance is strongly recommended for intra-articular and patellar tendinopathy procedures to ensure the precision and efficacy of these treatments. Prospective randomized studies remain warranted to better understand the role of imaging guidance and assess some of the medications used for interventional procedures around the knee.Key Points: • A list of 10 evidence-based statements on clinical indications of image-guided interventional procedures around the knee was produced by an expert panel of the ESSR. • Strong consensus with 100% agreement was obtained for all statements. • Two statements reached the highest level of evidence, allowing us to strongly recommend the use of ultrasonography to guide intra-articular and patellar tendon procedures to ensure higher accuracy and efficacy of these treatments. [ABSTRACT FROM AUTHOR]

Objectives: Position- and posture-dependent deformation of the vascular system is a relatively unexplored field. The goal of this scoping review was to create an overview of existing vascular imaging modalities in different body positions and postures and address the subsequent changes in vascular anatomy. Methods: Scopus, Medline, and Cochrane were searched for literature published between January 1, 2000, and June 30, 2022, incorporating the following categories: image modality, anatomy, orientation, and outcomes. Results: Out of 2446 screened articles, we included 108. The majority of papers used ultrasound (US, n = 74) in different body positions and postures with diameter and cross-sectional area (CSA) as outcome measures. Magnetic resonance imaging (n = 22) and computed tomography (n = 8) were less frequently used but allowed for investigation of other geometrical measures such as vessel curvature and length. The venous system proved more sensitive to postural changes than the arterial system, which was seen as increasing diameters of veins below the level of the heart when going from supine to prone to standing positions, and vice versa. Conclusions: The influence of body positions and postures on vasculature was predominantly explored with US for vessel diameter and CSA. Posture-induced deformation and additional geometrical features that may be of interest for the (endovascular) treatment of vascular pathologies have been limitedly reported, such as length and curvature of an atherosclerotic popliteal artery during bending of the knee after stent placement. The most important clinical implications of positional changes are found in diagnosis, surgical planning, and follow-up after stent placement. Clinical relevance statement: This scoping review presents the current state and opportunities of position- and posture-dependent imaging of vascular structures using various imaging modalities that are relevant in the fields of clinical diagnosis, surgical planning, and follow-up after stent placement. Key Points: • The influence of body positions and postures on the vasculature was predominantly investigated with US for vessel diameter and cross-sectional area. • Research into geometrical deformation, such as vessel length and curvature adaptation, that may be of interest for the (endovascular) treatment of vascular pathologies is limited in different positions and postures. • The most important clinical implications of postural changes are found in diagnosis, surgical planning, and follow-up after stent placement. [ABSTRACT FROM AUTHOR]

Objective: Although artificial intelligence (AI) has demonstrated promise in enhancing breast cancer diagnosis, the implementation of AI algorithms in clinical practice encounters various barriers. This scoping review aims to identify these barriers and facilitators to highlight key considerations for developing and implementing AI solutions in breast cancer imaging. Method: A literature search was conducted from 2012 to 2022 in six databases (PubMed, Web of Science, CINHAL, Embase, IEEE, and ArXiv). The articles were included if some barriers and/or facilitators in the conception or implementation of AI in breast clinical imaging were described. We excluded research only focusing on performance, or with data not acquired in a clinical radiology setup and not involving real patients. Results: A total of 107 articles were included. We identified six major barriers related to data (B1), black box and trust (B2), algorithms and conception (B3), evaluation and validation (B4), legal, ethical, and economic issues (B5), and education (B6), and five major facilitators covering data (F1), clinical impact (F2), algorithms and conception (F3), evaluation and validation (F4), and education (F5). Conclusion: This scoping review highlighted the need to carefully design, deploy, and evaluate AI solutions in clinical practice, involving all stakeholders to yield improvement in healthcare. Clinical relevance statement: The identification of barriers and facilitators with suggested solutions can guide and inform future research, and stakeholders to improve the design and implementation of AI for breast cancer detection in clinical practice. Key Points: • Six major identified barriers were related to data; black-box and trust; algorithms and conception; evaluation and validation; legal, ethical, and economic issues; and education. • Five major identified facilitators were related to data, clinical impact, algorithms and conception, evaluation and validation, and education. • Coordinated implication of all stakeholders is required to improve breast cancer diagnosis with AI. [ABSTRACT FROM AUTHOR]

Objectives: To develop a deep learning methodology that distinguishes early from late stages of avascular necrosis of the hip (AVN) to determine treatment decisions. Methods: Three convolutional neural networks (CNNs) VGG-16, Inception ResnetV2, InceptionV3 were trained with transfer learning (ImageNet) and finetuned with a retrospectively collected cohort of (n = 104) MRI examinations of AVN patients, to differentiate between early (ARCO 1–2) and late (ARCO 3–4) stages. A consensus CNN ensemble decision was recorded as the agreement of at least two CNNs. CNN and ensemble performance was benchmarked on an independent cohort of 49 patients from another country and was compared to the performance of two MSK radiologists. CNN performance was expressed with areas under the curve (AUC), the respective 95% confidence intervals (CIs) and precision, and recall and f1-scores. AUCs were compared with DeLong's test. Results: On internal testing, Inception-ResnetV2 achieved the highest individual performance with an AUC of 99.7% (95%CI 99–100%), followed by InceptionV3 and VGG-16 with AUCs of 99.3% (95%CI 98.4–100%) and 97.3% (95%CI 95.5–99.2%) respectively. The CNN ensemble the same AUCs Inception ResnetV2. On external validation, model performance dropped with VGG-16 achieving the highest individual AUC of 78.9% (95%CI 51.6–79.6%) The best external performance was achieved by the model ensemble with an AUC of 85.5% (95%CI 72.2–93.9%). No significant difference was found between the CNN ensemble and expert MSK radiologists (p = 0.22 and 0.092 respectively). Conclusion: An externally validated CNN ensemble accurately distinguishes between the early and late stages of AVN and has comparable performance to expert MSK radiologists. Clinical relevance statement: This paper introduces the use of deep learning for the differentiation between early and late avascular necrosis of the hip, assisting in a complex clinical decision that can determine the choice between conservative and surgical treatment. Key Points: • A convolutional neural network ensemble achieved excellent performance in distinguishing between early and late avascular necrosis. • The performance of the deep learning method was similar to the performance of expert readers. [ABSTRACT FROM AUTHOR]

In recent years, there has been a dramatic increase in research papers about machine learning (ML) and artificial intelligence in radiology. With so many papers around, it is of paramount importance to make a proper scientific quality assessment as to their validity, reliability, effectiveness, and clinical applicability. Due to methodological complexity, the papers on ML in radiology are often hard to evaluate, requiring a good understanding of key methodological issues. In this review, we aimed to guide the radiology community about key methodological aspects of ML to improve their academic reading and peer-review experience. Key aspects of ML pipeline were presented within four broad categories: study design, data handling, modelling, and reporting. Sixteen key methodological items and related common pitfalls were reviewed with a fresh perspective: database size, robustness of reference standard, information leakage, feature scaling, reliability of features, high dimensionality, perturbations in feature selection, class balance, bias-variance trade-off, hyperparameter tuning, performance metrics, generalisability, clinical utility, comparison with traditional tools, data sharing, and transparent reporting. Key Points • Machine learning is new and rather complex for the radiology community. • Validity, reliability, effectiveness, and clinical applicability of studies on machine learning can be evaluated with a proper understanding of key methodological concepts about study design, data handling, modelling, and reporting. • Understanding key methodological concepts will provide a better academic reading and peer-review experience for the radiology community. [ABSTRACT FROM AUTHOR]

Objectives: Image-guided musculoskeletal interventional procedures around the hip are widely used in daily clinical practice. The need for clarity concerning the actual added value of imaging guidance and types of medications to be offered led the Ultrasound and the Interventional Subcommittees of the European Society of Musculoskeletal Radiology (ESSR) to promote, with the support of its Research Committee, a collaborative project to review the published literature on image-guided musculoskeletal interventional procedures in the lower limb in order to derive a list of clinical indications. Methods: In this article, we report the results of a Delphi-based consensus of 53 experts who reviewed the published literature for evidence on image-guided interventional procedures offered in the joint and soft tissues around the hip in order of their clinical indications. Results: Ten statements concerning image-guided treatment procedures around the hip have been collected by the panel of ESSR experts. Conclusions: This work highlighted that there is still low evidence in the existing literature on some of these interventional procedures. Further large prospective randomized trials are essential to better confirm the benefits and objectively clarify the role of imaging to guide musculoskeletal interventional procedures around the hip. Key Points: • Expert consensus produced a list of 10 evidence-based statements on clinical indications of image-guided interventional procedures around the hip. • The highest level of evidence was only reached for one statement. • Strong consensus was obtained for all statements. [ABSTRACT FROM AUTHOR]

Objectives: To explore whether differences in diffusional kurtosis imaging (DKI) between therapy-naïve high-grade gliomas (HGGs) and low-grade gliomas (LGGs) are related to the cellularity and/or the nuclear-to-cytoplasmic (N/C) ratio. Methods: We analyzed 44 and 40 diffuse glioma samples that were pathologically confirmed as HGGs and IDH1-mutant LGGs, respectively. The DKI parameters included kurtosis metrics (mean kurtosis [MK], axial kurtosis [K//], and radial kurtosis [K⊥]), and the diffusional metrics (fractional anisotropy [FA], mean diffusion [MD], axial diffusion [λ//], and radial diffusion [λ⊥]). The cellularity and the N/C ratio were compared within LGGs and HGGs using the Mann–Whitney U test (significant level, p < 0.007 [0.05/7]); Bonferroni correction). Spearman's correlation analysis was used to calculate the correlation coefficients among DKI metrics, cellularity, and the N/C ratio at a significant level of p = 0.05. Results: Excluding FA, all DKI metrics showed significant differences between HGGs and LGGs (all p ≤ 0.001). The N/C ratio of HGGs was significantly higher than that of LGGs; however, differences in cellularity were not significant between the two glioma groups (p = 0.525). Similarly, excluding FA, all DKI metrics were significantly correlated with the N/C ratio in LGGs, with correlation coefficients of − 0.365 (MD), − 0.313 (λ//), − 0.376 (λ⊥), 0.859 (MK), 0.772 (K//), and 0.842 (K//). There was a non-significant correlation between any DKI parameters and the cellularity in LGGs. Additionally, the cellularity and N/C ratios in HGGs did not correlate with any DKI metrics. Conclusions: DKI differentiate LGGs from HGGs associated with their different N/C ratios. Clinical relevance statement: This study shows that DKI differentiates LGGs from HGGs may correlated with their different N/C ratios, this could provide a possible histopathological mechanism about why DKI can DKI differentiate LGGs from HGGs. Key Points: • Excluding FA, all DKI metrics showed a significant difference between high-grade gliomas and IDH1-mutant low-grade gliomas. • The nuclear-to-cytoplasm ratios in high-grade gliomas were significantly more extensive than that in IDH1-mutant low-grade gliomas, but not the cellularity. • Significant associations were seen between DKI measures and the N/C ratio; a non-significant correlation was noted between any DKI metric and cellularity in glioma specimens. [ABSTRACT FROM AUTHOR]

Objective: There has been a large amount of research in the field of artificial intelligence (AI) as applied to clinical radiology. However, these studies vary in design and quality and systematic reviews of the entire field are lacking.This systematic review aimed to identify all papers that used deep learning in radiology to survey the literature and to evaluate their methods. We aimed to identify the key questions being addressed in the literature and to identify the most effective methods employed. Methods: We followed the PRISMA guidelines and performed a systematic review of studies of AI in radiology published from 2015 to 2019. Our published protocol was prospectively registered. Results: Our search yielded 11,083 results. Seven hundred sixty-seven full texts were reviewed, and 535 articles were included. Ninety-eight percent were retrospective cohort studies. The median number of patients included was 460. Most studies involved MRI (37%). Neuroradiology was the most common subspecialty. Eighty-eight percent used supervised learning. The majority of studies undertook a segmentation task (39%). Performance comparison was with a state-of-the-art model in 37%. The most used established architecture was UNet (14%). The median performance for the most utilised evaluation metrics was Dice of 0.89 (range.49–.99), AUC of 0.903 (range 1.00–0.61) and Accuracy of 89.4 (range 70.2–100). Of the 77 studies that externally validated their results and allowed for direct comparison, performance on average decreased by 6% at external validation (range increase of 4% to decrease 44%). Conclusion: This systematic review has surveyed the major advances in AI as applied to clinical radiology. Key Points: • While there are many papers reporting expert-level results by using deep learning in radiology, most apply only a narrow range of techniques to a narrow selection of use cases. • The literature is dominated by retrospective cohort studies with limited external validation with high potential for bias. • The recent advent of AI extensions to systematic reporting guidelines and prospective trial registration along with a focus on external validation and explanations show potential for translation of the hype surrounding AI from code to clinic. [ABSTRACT FROM AUTHOR]

Background: Although image-guided interventional procedures of the elbow and wrist are routinely performed, there is poor evidence in the literature concerning such treatments. Our aim was to perform a Delphi-based consensus on published evidence on image-guided interventional procedures around the elbow and wrist and provide clinical indications on this topic.Methods: A board of 45 experts in image-guided interventional musculoskeletal procedures from the European Society of Musculoskeletal Radiology were involved in this Delphi-based consensus study. All panelists reviewed and scored published papers on image-guided interventional procedures around the elbow and wrist updated to September 2018 according to the Oxford Centre for Evidence-based Medicine levels of evidence. Consensus on statements drafted by the panelists about clinical indications was considered as "strong" when more than 95% of panelists agreed and as "broad" if more than 80% agreed.Results: Eighteen statements were drafted, 12 about tendon procedures and 6 about intra-articular procedures. Only statement #15 reached the highest level of evidence (ultrasound-guided steroid wrist injections result in greater pain reduction and greater likelihood of attaining clinically important improvement). Seventeen statements received strong consensus (94%), while one received broad consensus (6%).Conclusions: There is still poor evidence in published papers on image-guided interventional procedures around the elbow and wrist. A strong consensus has been achieved in 17/18 (94%) statements provided by the panel on clinical indications. Large prospective randomized trials are needed to better define the role of these procedures in clinical practice.Key Points: • The panel provided 18 evidence-based statements on clinical indications of image-guided interventional procedures around the elbow and wrist. • Only statement #15 reached the highest level of evidence: ultrasound-guided steroid wrist injections result in greater pain reduction and greater likelihood of attaining clinically important improvement. • Seventeen statements received strong consensus (94%), while broad consensus was obtained by 1 statement (6%). [ABSTRACT FROM AUTHOR]

Artificial intelligence developments are essential to the successful deployment of community-wide, MRI-driven prostate cancer diagnosis. AI systems should ensure that the main benefits of biopsy avoidance are delivered while maintaining consistent high specificities, at a range of disease prevalences. Since all current artificial intelligence / computer-aided detection systems for prostate cancer detection are experimental, multiple developmental efforts are still needed to bring the vision to fruition. Initial work needs to focus on developing systems as diagnostic supporting aids so their results can be integrated into the radiologists' workflow including gland and target outlining tasks for fusion biopsies. Developing AI systems as clinical decision-making tools will require greater efforts. The latter encompass larger multicentric, multivendor datasets where the different needs of patients stratified by diagnostic settings, disease prevalence, patient preference, and clinical setting are considered. AI-based, robust, standard operating procedures will increase the confidence of patients and payers, thus enabling the wider adoption of the MRI-directed approach for prostate cancer diagnosis. Key Points: • AI systems need to ensure that the benefits of biopsy avoidance are delivered with consistent high specificities, at a range of disease prevalence. • Initial work has focused on developing systems as diagnostic supporting aids for outlining tasks, so they can be integrated into the radiologists' workflow to support MRI-directed biopsies. • Decision support tools require a larger body of work including multicentric, multivendor studies where the clinical needs, disease prevalence, patient preferences, and clinical setting are additionally defined. [ABSTRACT FROM AUTHOR]

This review explains in simple terms, accessible to the non-statistician, general principles regarding the correct research methods to develop and then evaluate imaging biomarkers in a clinical setting, including radiomic biomarkers. The distinction between diagnostic and prognostic biomarkers is made and emphasis placed on the need to assess clinical utility within the context of a multivariable model. Such models should not be restricted to imaging biomarkers and must include relevant disease and patient characteristics likely to be clinically useful. Biomarker utility is based on whether its addition to the basic clinical model improves diagnosis or prediction. Approaches to both model development and evaluation are explained and the need for adequate amounts of representative data stressed so as to avoid underpowering and overfitting. Advice is provided regarding how to report the research correctly. Key Points: • Imaging biomarker research is common but methodological errors are encountered frequently that may mean the research is not clinically useful. • The clinical utility of imaging biomarkers is best assessed by their additive effect on multivariable models based on clinical factors known to be important. • The data used to develop such models should be sufficient for the number of variables investigated and the model should be evaluated, preferably using data unrelated to development. [ABSTRACT FROM AUTHOR]

Background: Image-guided interventional procedures of the nerves are commonly performed by physicians from different medical specialties, although there is a lack of clinical indications for these types of procedures. This Delphi-based consensus provided a list of indications on image-guided interventional procedures for nerves of the upper limb based on updated published evidence.Methods: An expert panel of 45 members of the Ultrasound and Interventional Subcommittees of the ESSR participated in this Delphi-based consensus study. After revision of the published papers on image-guided interventional procedures for nerves of the upper limb updated to September 2018, the experts drafted a list of statements according to the Oxford Centre for evidence-based medicine levels of evidence. Consensus on statements regarding clinical indications was considered as strong when more than 95% of experts agreed, and broad if more than 80% agreed.Results: Ten statements were drafted on procedures for nerves of the upper limb. Only two statements reached the highest level of evidence (ultrasound guidance is a safe and effective method for brachial plexus block; ultrasound-guided non-surgical approaches are safe and effective methods to treat carpal tunnel syndrome in the short term, but there is sparse evidence on the mid- and long-term effectiveness of these interventions). Strong consensus was obtained on 6/10 statements (60%), while 4/10 statements reached broad consensus (40%).Conclusions: This Delphi-based consensus study reported poor evidence on image-guided interventional procedures for nerves of the upper limb. Sixty percent of statements on clinical indications provided by the expert board reached a strong consensus.Key Points: • An expert panel of the ESSR provided 10 evidence-based statements on clinical indications for image-guided interventional procedures for nerves of the upper limb • Two statements reached the highest level of evidence • Strong consensus was obtained on 6/10 statements (60%), while 4/10 statements reached broad consensus (40%). [ABSTRACT FROM AUTHOR]

Background: Image-guided interventional procedures around the shoulder are commonly performed in clinical practice, although evidence regarding their effectiveness is scarce. We report the results of a Delphi method review of evidence on literature published on image-guided interventional procedures around the shoulder with a list of clinical indications.Methods: Forty-five experts in image-guided musculoskeletal procedures from the ESSR participated in a consensus study using the Delphic method. Peer-reviewed papers regarding interventional procedures around the shoulder up to September 2018 were scored according to the Oxford Centre for Evidence-based Medicine levels of evidence. Statements on clinical indications were constructed. Consensus was considered as strong if more than 95% of experts agreed and as broad if more than 80% agreed.Results: A total of 20 statements were drafted, and 5 reached the highest level of evidence. There were 10 statements about tendon procedures, 6 about intra-articular procedures, and 4 about intrabursal injections. Strong consensus was obtained in 16 of them (80%), while 4 received broad consensus (20%).Conclusions: Literature evidence on image-guided interventional procedures around the shoulder is limited. A strong consensus has been reached for 80% of statements. The ESSR recommends further research to potentially influence treatment options, patient outcomes, and social impact.Key Points: • Expert consensus produced a list of 20 evidence-based statements on clinical indications of image-guided interventional procedures around the shoulder. • The highest level of evidence was reached for five statements. • Strong consensus was obtained for 16 statements (80%), while 4 received broad consensus (20%). [ABSTRACT FROM AUTHOR]

Objectives: To assess the weight of imaging and imaging specialists (i.e., affiliated to a radiology/nuclear medicine department) in publications in non-imaging journals. Methods: All articles indexed in English on the Embase database between 1989 and 2019 were extracted. The number and affiliation of authors were determined. A naive Bayesian classifier algorithm was trained to classify abstracts as "imaging" or "non-imaging." The main outcome was the number and position of imaging specialists in the authorship of imaging articles published in non-imaging journals. Analyses per medical specialties and per journal impact factor (IF) were performed. Results: A total of 15,787,825 articles were included with 968,259 (6%) "imaging" articles. The proportion of imaging articles increased over time (+ 370%), quicker than the overall academic output. The proportion of imaging specialist among authors grew from 0.58% in 1989–1994 to 1.54% in 2015–2019. About 20% of imaging articles had ≥ 1 imaging specialist among authors. The proportion of imaging articles decreased with the IF (7.3% for IF 0–2.5 vs. 5.1% for IF > 10, p < 0.001), but the proportion of imaging specialist authors in imaging papers with ≥ 1 imaging specialist author increased with the IF (40% for IF 0–2.5, 53% for IF > 10, p < 0.001). There was significant variability across medical specialties. Conclusions: The weight of imaging articles and imaging specialist among authors in non-imaging journals has increased over time but remains limited. Most of the authors of imaging publications are not imaging specialists. Imaging specialists among authors in imaging papers are associated with a greater IF. Key Points: • The proportion of imaging specialist authors in non-imaging journals, though small, has increased significantly. • Marked differences are observed according to medical specialties and the reputation/impact factor of the journal. • Collaboration between imaging specialists and non-specialists is associated with publication in higher impact journals. [ABSTRACT FROM AUTHOR]

Objective: To identify adhesive renal venous tumor thrombus (RVTT) of renal cell carcinoma (RCC) by contrast-enhancement CT (CECT). Materials and methods: Our retrospective study included 53 patients who underwent preoperative CECT and pathologically confirmed RCC combined with RVTT. They were divided into two groups based on the intra-operative findings of RVTT adhesion to the venous wall, with 26 cases in the adhesive RVTT group (ARVTT) and 27 cases in the non-adhesive group (NRVTT). The location, maximum diameter (MD) and CT values of tumors, the maximum length (ML) and width (MW) of RVTT, and length of inferior vena cava tumor thrombus were compared between the two groups. The presence of renal venous wall involvement, renal venous wall inflammation, and enlarged retroperitoneal lymph node was compared between the two groups. A receiver operating characteristic curve was used to analyze the diagnostic performance. Results: The MD of RCC and the ML and MW of the RVTT were all larger in the ARVTT group than in the NRVTT group (p = 0.042, p < 0.001, and p = 0.002). The proportion of renal vein wall involvement and renal vein wall inflammation were higher in the ARVTT group than in NRVTT groups (both p < 0.001). The multivariable model including ML and vascular wall inflammation to predict ARVTT could achieve the best diagnostic performance with the area under the curve, sensitivity, specificity, and accuracy of 0.91, 88.5%, 96.3%, and 92.5%, respectively. Conclusion: The multivariable model acquired by CECT images could be used to predict RVTT adhesion. Clinical relevance statement: For RCC patients with tumor thrombus, contrast-enhanced CT could noninvasively predict the adhesion of tumor thrombus, thus predicting the difficulty of surgery and contributing to the selection of an appropriate treatment plan. Key Points: • The length and width of the tumor thrombus could be used to predict its adhesion to the vessel wall. • Adhesion of the tumor thrombus can be reflected by inflammation of the renal vein wall. • The multivariable model from CECT can well predict whether the tumor thrombus adhered to the vein wall. [ABSTRACT FROM AUTHOR]

Objectives: Post-mortem interval (PMI) estimation has long been relying on sequential post-mortem changes on the body as a function of extrinsic, intrinsic, and environmental factors. Such factors are difficult to account for in complicated death scenes; thus, PMI estimation can be compromised. Herein, we aimed to evaluate the use of post-mortem CT (PMCT) radiomics for the differentiation between early and late PMI. Methods: Consecutive whole-body PMCT examinations performed between 2016 and 2021 were retrospectively included (n = 120), excluding corpses without an accurately reported PMI (n = 23). Radiomics data were extracted from liver and pancreas tissue and randomly split into training and validation sets (70:30%). Following data preprocessing, significant features were selected (Boruta selection) and three XGBoost classifiers were built (liver, pancreas, combined) to differentiate between early (< 12 h) and late (> 12 h) PMI. Classifier performance was assessed with receiver operating characteristics (ROC) curves and areas under the curves (AUC), which were compared by bootstrapping. Results: A total of 97 PMCTs were included, representing individuals (23 females and 74 males) with a mean age of 47.1 ± 23.38 years. The combined model achieved the highest AUC reaching 75% (95%CI 58.4–91.6%) (p = 0.03 compared to liver and p = 0.18 compared to pancreas). The liver-based and pancreas-based XGBoost models achieved AUCs of 53.6% (95%CI 34.8–72.3%) and 64.3% (95%CI 46.7–81.9%) respectively (p > 0.05 for the comparison between liver- and pancreas-based models). Conclusion: The use of radiomics analysis on PMCT examinations differentiated early from late PMI, unveiling a novel image-based method with important repercussions in forensic casework. Clinical relevance statement: This paper introduces the employment of radiomics in forensic diagnosis by presenting an effective automated alternative method of estimating post-mortem interval from targeted tissues, thus paving the way for improvement in speed and quality of forensic investigations. Key Points: • A combined liver-pancreas radiomics model differentiated early from late post-mortem intervals (using a 12-h threshold) with an area under the curve of 75% (95%CI 58.4–91.6%). • XGBoost models based on liver-only or pancreas-only radiomics demonstrated inferior performance to the combined model in predicting the post-mortem interval. [ABSTRACT FROM AUTHOR]

Objectives: To analyze the performance of deep learning in isodense/obscure masses in dense breasts. To build and validate a deep learning (DL) model using core radiology principles and analyze its performance in isodense/obscure masses. To show performance on screening mammography as well as diagnostic mammography distribution. Methods: This was a retrospective, single-institution, multi-centre study with external validation. For model building, we took a 3-pronged approach. First, we explicitly taught the network to learn features other than density differences: such as spiculations and architectural distortion. Second, we used the opposite breast to enable the detection of asymmetries. Third, we systematically enhanced each image by piece-wise-linear transformation. We tested the network on a diagnostic mammography dataset (2569 images with 243 cancers, January to June 2018) and a screening mammography dataset (2146 images with 59 cancers, patient recruitment from January to April 2021) from a different centre (external validation). Results: When trained with our proposed technique (and compared with baseline network), sensitivity for malignancy increased from 82.7 to 84.7% at 0.2 False positives per image (FPI) in the diagnostic mammography dataset, 67.9 to 73.8% in the subset of patients with dense breasts, 74.6 to 85.3 in the subset of patients with isodense/obscure cancers and 84.9 to 88.7 in an external validation test set with a screening mammography distribution. We showed that our sensitivity exceeded currently reported values (0.90 at 0.2 FPI) on a public benchmark dataset (INBreast). Conclusion: Modelling traditional mammographic teaching into a DL framework can help improve cancer detection accuracy in dense breasts. Clinical relevance statement: Incorporating medical knowledge into neural network design can help us overcome some limitations associated with specific modalities. In this paper, we show how one such deep neural network can help improve performance on mammographically dense breasts. Key Points: • Although state-of-the-art deep learning networks achieve good results in cancer detection in mammography in general, isodense, obscure masses and mammographically dense breasts posed a challenge to deep learning networks. • Collaborative network design and incorporation of traditional radiology teaching into the deep learning approach helped mitigate the problem. • The accuracy of deep learning networks may be translatable to different patient distributions. We showed the results of our network on screening as well as diagnostic mammography datasets. [ABSTRACT FROM AUTHOR]

Objectives: We present a 3-D approach to joint space width (JSW) measurement across the ankle from weight-bearing CT (WBCT) to demonstrate inter-operator reproducibility, test-retest repeatability, and how differences in angulation affect ankle JSW distribution. Methods: One side from repeat WBCT imaging of both feet and ankles was analysed from 23 individuals as part of their routine clinical care pathway. Joint space mapping was performed at four facets across the talus: talonavicular, talar dome and medial gutter (dome-medial), lateral gutter, and posterior subtalar. Inter-operator reproducibility was calculated for two users, while test-retest repeatability was calculated by comparing the two visits, both presented as Bland-Altman statistics. Statistical parametric mapping determined any significant relationships between talocrural joint space angulation and 3-D JSW distribution. Results: The average ± standard deviation interval between imaging was 74.0 ± 29.6 days. Surface averaged bias ± limits of agreement were similar for reproducibility and repeatability, the latter being: talonavicular 0.01 ± 0.26 mm, dome-medial 0.00 ± 0.28 mm, lateral gutter − 0.02 ± 0.40 mm, and posterior subtalar 0.02 ± 0.34 mm. Results are presented as 3-D distribution maps, with optimum test–retest repeatability reaching a smallest detectable difference of ± 0.15 mm. Conclusions: Joint space mapping is a robust approach to 3-D quantification of JSW measurement, inter-operator reproducibility, and test–retest repeatability at the ankle, with sensitivity reaching a best value of ± 0.15 mm. Standardised imaging protocols and optimised metal artefact reduction will be needed to further understand the clinical value of these 3-D measures derived from WBCT. Clinical relevance statement: Weight-bearing computed tomography is an increasingly important tool in the clinical assessment of orthopaedic ankle disorders. This paper establishes the performance of measuring 3-D joint space width using this technology, which is an important surrogate marker for severity of osteoarthritis. Key Points: • Joint space width values and error metrics from across the ankle measured from weight-bearing CT can be presented as 3-D maps that show topographic variation. • The best sensitivity for detecting meaningful change in 3-D joint space width at the ankle was ± 0.15 mm, a value less than the isotropic imaging voxel dimensions. • Standardised imaging protocols and optimised metal artefact reduction will be needed to understand the clinical value of 3-D measures from weight-bearing CT. [ABSTRACT FROM AUTHOR]

In Europe, lung cancer ranks third among the most common cancers, remaining the biggest killer. Since the publication of the first European Society of Radiology and European Respiratory Society joint white paper on lung cancer screening (LCS) in 2015, many new findings have been published and discussions have increased considerably. Thus, this updated expert opinion represents a narrative, non-systematic review of the evidence from LCS trials and description of the current practice of LCS as well as aspects that have not received adequate attention until now. Reaching out to the potential participants (persons at high risk), optimal communication and shared decision-making will be key starting points. Furthermore, standards for infrastructure, pathways and quality assurance are pivotal, including promoting tobacco cessation, benefits and harms, overdiagnosis, quality, minimum radiation exposure, definition of management of positive screen results and incidental findings linked to respective actions as well as cost-effectiveness. This requires a multidisciplinary team with experts from pulmonology and radiology as well as thoracic oncologists, thoracic surgeons, pathologists, family doctors, patient representatives and others. The ESR and ERS agree that Europe's health systems need to adapt to allow citizens to benefit from organised pathways, rather than unsupervised initiatives, to allow early diagnosis of lung cancer and reduce the mortality rate. Now is the time to set up and conduct demonstration programmes focusing, among other points, on methodology, standardisation, tobacco cessation, education on healthy lifestyle, cost-effectiveness and a central registry.Key Points• Pulmonologists and radiologists both have key roles in the set up of multidisciplinary LCS teams with experts from many other fields.• Pulmonologists identify people eligible for LCS, reach out to family doctors, share the decision-making process and promote tobacco cessation.• Radiologists ensure appropriate image quality, minimum dose and a standardised reading/reporting algorithm, together with a clear definition of a "positive screen".• Strict algorithms define the exact management of screen-detected nodules and incidental findings.• For LCS to be (cost-)effective, it has to target a population defined by risk prediction models. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to examine the equivalence of computed tomography (CT)–based synthetic T1-weighted imaging (T1WI) to conventional T1WI for the quantitative assessment of brain morphology. Materials and methods: This prospective study examined 35 adult patients undergoing brain magnetic resonance imaging (MRI) and CT scans. An image synthesis method based on a deep learning model was used to generate synthetic T1WI (sT1WI) from CT data. Two senior radiologists used sT1WI and conventional T1WI on separate occasions to independently measure clinically relevant brain morphological parameters. The reliability and consistency between conventional and synthetic T1WI were assessed using statistical consistency checks, comprising intra-reader, inter-reader, and inter-method agreement. Results: The intra-reader, inter-reader, and inter-method reliability and variability mostly exhibited the desired performance, except for several poor agreements due to measurement differences between the radiologists. All the measurements of sT1WI were equivalent to that of T1WI at 5% equivalent intervals. Conclusion: This study demonstrated the equivalence of CT-based sT1WI to conventional T1WI for quantitatively assessing brain morphology, thereby providing more information on imaging diagnosis with a single CT scan. Clinical relevance statement: Real-time synthesis of MR images from CT scans reduces the time required to acquire MR signals, improving the efficiency of the treatment planning system and providing benefits in the clinical diagnosis of patients with contraindications such as presence of metal implants or claustrophobia. Key Points: • Deep learning–based image synthesis methods generate synthetic T1-weighted imaging from CT scans. • The equivalence of synthetic T1-weighted imaging and conventional MRI for quantitative brain assessment was investigated. • Synthetic T1-weighted imaging can provide more information per scan and be used in preoperative diagnosis and radiotherapy. [ABSTRACT FROM AUTHOR]

Objective: To present MRI distribution of active osteitis in a single tertiary referral center cohort of patients with chronic nonbacterial osteomyelitis (CNO). Methods: Two musculoskeletal radiologists retrospectively reviewed MRI examinations of all patients with a final clinical diagnosis of CNO over 15 years. Sites of active osteitis at any time during the course of disease were divided into seven groups: (A) mandible, sternum, clavicles, or scapulas; (B) upper extremities; (C) subchondral sacrum and ilium immediately subjacent to sacroiliac joints (active osteitis denoting "active sacroiliitis" here); (D) pelvis and proximal 1/3 of femurs (excluding group C); (E) bones surrounding knees including distal 2/3 of femurs and 1/2 of proximal tibias and fibulas; (F) distal legs (including distal 1/2 of tibias and fibulas), ankles, or feet; (G) spine (excluding group C). Temporal changes of lesions in response to treatment (or other treatment-related changes such as pamidronate lines) were not within the scope of the study. Results: Among 97 CNO patients (53 males [55%], 44 females; age at onset, mean ± SD, 8.5 ± 3.2 years; age at diagnosis, 10.3 ± 3.3 years), whole-body (WB) MRI was performed in 92%, mostly following an initial targeted MRI (94%). A total of 557 (346 targeted and 211 WB) MRIs were analyzed. Biopsy was obtained in 39 patients (40%), all consistent with CNO or featuring supporting findings. The most common locations for active osteitis were groups D (78%; 95% CI 69‒85%) and C (72%; 95% CI 62‒80%). Conclusion: Pelvis and hips were preferentially involved in this cohort of CNO patients along with a marked presence of active sacroiliitis. Clinical relevance statement: When suggestive findings of CNO are identified elsewhere in the body, the next targeted site of MRI should be the pelvis (entirely including sacroiliac joints) and hips, if whole-body MRI is not available or feasible. Key Points: • Heavy reliance on MRI for diagnosis of CNO underscores the importance of suggestive distribution patterns. • Pelvis and hips are the most common (78%) sites of CNO involvement along with active sacroiliitis (72%). • Pelvis including sacroiliac joints and hips should be targeted on MRI when CNO is suspected. [ABSTRACT FROM AUTHOR]

Objective: To investigate the microstructural properties of T2 lesion and normal-appearing white matter (NAWM) in 20 white matter tracts between multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) and correlations between the tissue damage and clinical variables. Methods: The white matter (WM) compartment of the brain was segmented for 56 healthy controls (HC), 48 patients with MS, and 38 patients with NMOSD, and for the patients further subdivided into T2 lesion and NAWM. Subsequently, the diffusion tensor imaging (DTI) tissue characterization parameters of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were compared for 20 principal white matter tracts. The correlation between tissue damage and clinical variables was also investigated. Results: The higher T2 lesion volumes of 14 fibers were shown in MS compared to NMOSD. MS showed more microstructure damage in 13 fibers of T2 lesion, but similar microstructure in seven fibers compared to NMOSD. MS and NMOSD had microstructure damage of NAWM in 20 fibers compared to WM in HC, with more damage in 20 fibers in MS compared to NMOSD. MS patients showed higher correlation between the microstructure of T2 lesion areas and NAWM. The T2 lesion microstructure damage was correlated with duration and impaired cognition in MS. Conclusions: Patients with MS and NMOSD show different patterns of microstructural damage in T2 lesion and NAWM areas. The prolonged disease course of MS may aggravate the microstructural damage, and the degree of microstructural damage is further related to cognitive impairment. Clinical relevance statement: Microstructure differences between T2 lesion areas and normal-appearing white matter help distinguish multiple sclerosis and neuromyelitis optica spectrum disorder. In multiple sclerosis, lesions rather than normal-appearing white matter should be a concern, because the degree of lesion severity correlated both with normal-appearing white matter damage and cognitive impairment. Key Points: • Multiple sclerosis and neuromyelitis optica spectrum disorder have different damage patterns in T2 lesion and normal-appearing white matter areas. • The microstructure damage of normal-appearing white matter is correlated with the microstructure of T2 lesion in multiple sclerosis and neuromyelitis optica spectrum disorder. • The microstructure damage of T2 lesion in multiple sclerosis is correlated with duration and cognitive impairment. [ABSTRACT FROM AUTHOR]

Purpose: This work aims to compare the interval cancer rate and interval cancer characteristics between women screened with digital breast tomosynthesis (DBT) + digital mammography (DM) and those screened with DM alone. Methods: The interval cancer rate and interval cancer characteristics of the study population included in the Córdoba Breast Tomosynthesis Screening Trial (CBTST) were compared to a contemporary control population screened with DM. The tumour characteristics of screen-detected and interval cancers were also compared. Contingency tables were used to compare interval cancer rates. The chi-square test and Fisher's exact test were used to compare the qualitative characteristics of the cancers whereas Student's t test and the Mann–Whitney U test were used to analyse quantitative features. Results: A total of 16,068 screening exams with DBT + DM were conducted within the CBTST (mean age 57.59 ± 5.9 [SD]) between January 2015 and December 2016 (study population). In parallel, 23,787 women (mean age 58.89 ± 5.9 standard deviation [SD]) were screened with DM (control population). The interval cancer rate was lower in the study population than in the control population (15 [0.93‰; 95% confidence interval (CI): 0.73, 1.14] vs 43 [1.8‰; 95% CI: 1.58, 2.04] respectively; p = 0.045). The difference in rate was more marked in women with dense breasts (0.95‰ in the study population vs 3.17‰ in the control population; p = 0.031). Interval cancers were smaller in the study population than in the control population (p = 0.031). Conclusions: The interval cancer rate was lower in women screened with DBT + DM compared to those screened with DM alone. These differences were more pronounced in women with dense breasts. Clinical relevance statement: Women screened using tomosynthesis and digital mammography had a lower rate of interval cancer than women screened with digital mammography, with the greatest difference in the interval cancer rate observed in women with dense breasts. Key Points: • The interval cancer rate was lower in the study population (digital breast tomosynthesis [DBT] + digital mammography [DM]) than in the control population (DM). • The difference in interval cancer rates was more pronounced in women with dense breasts. • Interval cancers were smaller in the study population (DBT + DM) than in the control population (DM). [ABSTRACT FROM AUTHOR]

Objectives: It is unclear which selection strategy, plain CT vs. CT perfusion (CTP), is more powerful in predicting outcome after mechanical thrombectomy (MT). We aimed to compare the effect of plain CT and CTP in predicting outcome after MT within 6 h. Methods: We conducted a prospective analysis of a retrospective cohort from our single-center study, which had occlusion of the internal carotid artery and middle cerebral artery up to the proximal M2 segment and received MT within 6 h. According to the Alberta Stroke Program Early CT Score (ASPECTS), patients were divided into a high-ASPECTS group (≥ 6) and a low ASPECTS group (< 6). Similarly, patients were divided into mismatch and no-mismatch groups according to the DEFUSE3 criteria for CTP. A good outcome was defined as a 90-day modified Rankin Scale (mRS) score of ≤ 3. Univariate and binary logistic regression analyses were used to investigate the association between different imaging modality and 90-day mRS score, and mortalities, respectively. Results: The high ASPECTS group included 307 patients (89.2%). The mismatch group included 189 (54.9%) patients meeting the DEFUSE3 criterion. Compared to the low ASPECTS group, the high ASPECTS group had a good outcome (odds ratio (OR), 2.285; [95% confidence interval (CI) (1.106, 4.723)], p = 0.026) and lower mortality (OR, 0.350; [95% CI (0.163, 0.752)], p = 0.007). However, there were no significant differences in good outcomes and mortality between the mismatch and no-mismatch groups. Conclusions: Compared with plain CT, CTP does not provide additional benefits in the selection of patients suitable for MT within 6 h. Clinical relevance statement: CT perfusion is not superior to plain CT for the prediction of clinical outcomes when selecting patients for mechanical thrombectomy in the first 6 h. In that clinical setting, plain CT may be safe in the absence of perfusion data. Key Points: • The advantage of CT perfusion (CTP) over CT in pre-mechanical thrombectomy (MT) screening has not been proven for patients with a large infarct core. • CTP is not better than plain CT in predicting good outcome following MT within 6 h. • Plain CT is sufficient for selecting patients suitable for MT within 6 h of large artery occlusion. [ABSTRACT FROM AUTHOR]

Objectives: Cardiac motion artifacts hinder the assessment of coronary arteries in coronary computed tomography angiography (CCTA). We investigated the impact of motion compensation reconstruction (MCR) on motion artifacts in CCTA at various heart rates (HR) using a dynamic phantom. Materials and methods: An artificial hollow coronary artery (5-mm diameter lumen) filled with iodinated contrast agent (400 HU at 120 kVp), positioned centrally in an anthropomorphic chest phantom, was scanned using a dual-layer spectral detector CT. The artery was translated at constant horizontal velocities (0–80 mm/s, increment of 10 mm/s). For each velocity, five CCTA scans were repeated using a clinical protocol. Motion artifacts were quantified using the in-plane motion area. Regression analysis was performed to calculate the reduction in motion artifacts provided by MCR, by division of the slopes of non-MCR and MCR fitted lines. Results: Reference mean (95% confidence interval) motion artifact area was 24.9 mm2 (23.8, 26.0). Without MCR, motion artifact areas for velocities exceeding 20 mm/s were significantly larger (up to 57.2 mm2 (40.1, 74.2)) than the reference. With MCR, no significant differences compared to the reference were shown for all velocities, except for 70 mm/s (29.0 mm2 (27.0, 31.0)). The slopes of the fitted data were 0.44 and 0.04 for standard and MCR reconstructions, respectively, resulting in an 11-time motion artifact reduction. Conclusion: MCR may improve CCTA assessment in patients by reducing coronary artery motion artifacts, especially in those with elevated HR who cannot receive beta blockers or do not attain the targeted HR. Clinical relevance statement: This vendor-specific motion compensation reconstruction may improve coronary computed tomography angiography assessment in patients by reduction of coronary artery motion artifacts, especially in those with elevated various heart rates (HR) who cannot receive beta blockers or do not attain the targeted HR. Key Points: • Motion artifacts are known to hinder the assessment of coronary arteries on coronary CT angiography (CCTA), leading to more non-diagnostic scans. • This dynamic phantom study shows that motion compensation reconstruction (MCR) reduces motion artifacts at various velocities, which may help to decrease the number of non-diagnostic scans. • MCR in this study showed to reduce motion artifacts 11-fold. [ABSTRACT FROM AUTHOR]

Objectives: Cardiovascular magnetic resonance (CMR) imaging is routinely performed for assessing right ventricular (RV) systolic but not diastolic function. We aimed to investigate CMR-based assessment of RV diastolic function in pediatric patients with repaired tetralogy of Fallot (rTOF), compared to transthoracic echocardiography (TTE) measurements. Methods: A total of 130 consecutive pediatric patients with rTOF who underwent clinically indicated CMR and same-day TTE were included. Forty-three controls were recruited. Phase-contrast images were used to measure trans-tricuspid valve flow velocities during early (E) and late diastolic (A) phases (measured in cm/s). Feature tracking of the tricuspid annulus was performed to derive early (e′) and late diastolic (a′) myocardial velocities (measured in cm/s). RV diastolic function was evaluated by E/A ratio, E/e′ ratio, and E-wave deceleration time (measured in milliseconds). Regression analyses were utilized to identify potential variables associated with RV diastolic dysfunction (DD). The performance of CMR-derived parameters in diagnosing RV DD was assessed using receiver-operating characteristic analyses. Results: Good agreement was found between CMR and TTE measurements (ICC 0.70–0.89). Patients with RV DD (n = 67) showed significantly different CMR-derived parameters including E and e′ velocities, and E/A and E/e′ ratio, compared to patients without DD (n = 63) (all p < 0.05). CMR-derived E and e′ velocities and E/e′ ratio were independent predictors of RV DD. E/e′ of 5.8 demonstrated the highest discrimination of RV DD (AUC 0.76, sensitivity 70%, specificity 86%). Conclusions: CMR-derived parameters showed good agreement with TTE parameters in determining RV DD. CMR-derived E/e′ was proved to be the most effective in identifying RV DD. Clinical relevance statement: This study demonstrated the feasibility and efficacy of CMR in assessing diastolic function in pediatric patients. RV DD was presented in over half of patients according to current TTE guidelines, highlighting the need for assessing RV diastolic function during follow-up. Key Points: • Routinely acquired cine and phase-contrast cardiovascular magnetic resonance (CMR) images yielded right ventricular (RV) diastolic parameters which demonstrated good agreement with transthoracic echocardiography (TTE) measurements. • There was a high prevalence of RV diastolic function impairment in pediatric patients with repaired tetralogy of Fallot (rTOF). • CMR is a reliable complementary modality of TTE for RV diastolic function evaluation. [ABSTRACT FROM AUTHOR]

Objectives: The aim of our study was to examine how breast radiologists would be affected by high cancer prevalence and the use of artificial intelligence (AI) for decision support. Materials and method: This reader study was based on selection of screening mammograms, including the original radiologist assessment, acquired in 2010 to 2013 at the Karolinska University Hospital, with a ratio of 1:1 cancer versus healthy based on a 2-year follow-up. A commercial AI system generated an exam-level positive or negative read, and image markers. Double-reading and consensus discussions were first performed without AI and later with AI, with a 6-week wash-out period in between. The chi-squared test was used to test for differences in contingency tables. Results: Mammograms of 758 women were included, half with cancer and half healthy. 52% were 40–55 years; 48% were 56–75 years. In the original non-enriched screening setting, the sensitivity was 61% (232/379) at specificity 98% (323/379). In the reader study, the sensitivity without and with AI was 81% (307/379) and 75% (284/379) respectively (p < 0.001). The specificity without and with AI was 67% (255/379) and 86% (326/379) respectively (p < 0.001). The tendency to change assessment from positive to negative based on erroneous AI information differed between readers and was affected by type and number of image signs of malignancy. Conclusion: Breast radiologists reading a list with high cancer prevalence performed at considerably higher sensitivity and lower specificity than the original screen-readers. Adding AI information, calibrated to a screening setting, decreased sensitivity and increased specificity. Clinical relevance statement: Radiologist screening mammography assessments will be biased towards higher sensitivity and lower specificity by high-risk triaging and nudged towards the sensitivity and specificity setting of AI reads. After AI implementation in clinical practice, there is reason to carefully follow screening metrics to ensure the impact is desired. Key Points: • Breast radiologists' sensitivity and specificity will be affected by changes brought by artificial intelligence. • Reading in a high cancer prevalence setting markedly increased sensitivity and decreased specificity. • Reviewing the binary reads by AI, negative or positive, biased screening radiologists towards the sensitivity and specificity of the AI system. [ABSTRACT FROM AUTHOR]

Objectives: Magnetic resonance–guided focused ultrasound (MRgFUS) thalamotomy is a novel, minimally invasive ablative treatment for essential tremor (ET). The use of a four-tract probabilistic tractography technique, targeting the intersection between the dentato-rubro-thalamic tracts (both decussating and non-decussating), while evaluating the corticospinal tract and the medial lemniscus, may obtain immediate clinical results with reduced adverse events. Our aim is to present our experience with the four-tract technique for patients undergoing ET treatment with MRgFUS. Methods: Retrospective analysis of a prospective database of consecutive patients undergoing ET treatment in a single center from February 2022 to February 2023. Procedural parameters were collected, and tremor improvement was assessed with the Clinical Rating Scale for Tremor (CRST) at baseline and at 3 and 6 months. Adverse events were also reported. Results: Forty-three patients (median age, 72 years [interquartile range, 66–76]; 22 females) were evaluated. Tremor improved significatively in all CRST subsections at 3 months, including the CRST part A + B treated hand tremor (22 [19–27] vs 4 [2–7], p < 0.001) and CRST part C (16 [13–19] vs 3 [1–4], p < 0.001). Differences persisted significant at 6 months. Adverse events were few (4.1% of paresthesias and 12.5% of objective gait disturbance at follow-up) and recorded as mild. The median number of sonications was 7 [6–8] and mean operative time 68.7 ± 24.2 min. Conclusion: Our data show support for the feasibility and benefits of systematic targeting approach with four-tract probabilistic tractography for treating ET using MRgFUS. Clinical relevance statement: An approach with four-tract probabilistic tractography for treating essential tremor (ET) patients with magnetic resonance–guided focused ultrasound decreases interindividual variability with good clinical outcomes, low number of sonications, few adverse effects, and short procedure times. Key Points: • The optimal target for the treatment of essential tremor with MR-guided focused ultrasound remains unknown. • Four-tract probabilistic tractography is a feasible technique that reduces interindividual variability, with good clinical results, few side effects, and short operative time. • The four-tract tractography approach can be performed using different MRI scanners and post-processing software in comparison with the initial description of the technique. [ABSTRACT FROM AUTHOR]

The population ageing process worldwide is leading to an increasing number of women in the perimenopausal phase. Many of the perimenopausal symptoms, such as headache, depression, insomnia, and cognitive decline, are neurological in nature. Therefore, the study of the perimenopausal brain is of great importance. In addition, relevant studies can also provide an imaging basis for multiple therapies to treat perimenopausal symptoms. Because of its non-invasive nature, magnetic resonance imaging (MRI) has now been widely applied to the study of perimenopausal brains, revealing alterations in the brain associated with symptoms during the menopause transition. In this review, we collected papers and works of literature on the perimenopausal brain using MRI techniques in the Web of Science database. We firstly described the general principles and analysis methods of different MRI modalities briefly and then reviewed the structural, functional, perfusion, and metabolic compounds changes in the brain of perimenopausal women respectively, and described the latest advances in probing the perimenopausal brain using MRI, resulting in summary diagrams and figures. Based on the summary of existing works of the literature, this review further provided a perspective on multi-modal MRI studies in the perimenopausal brain, suggesting that population-based, multi-center, and longitudinal studies will be beneficial to the comprehensive understanding of changes in the perimenopausal brain. In addition, we found a hint towards neural heterogeneity in the perimenopausal brain, which should be addressed by future MRI studies to provide more help for the precise diagnosis and personalized treatment of perimenopausal symptoms. Key Points: • Perimenopause is not only a physiological transition but also a period of neurological transition. • Multi-modal MRI studies have revealed that perimenopause is accompanied by alterations in the brain, which is implicated in many perimenopausal symptoms. • The diversity in the multi-modal MRI findings may give a hint to neural heterogeneity in the perimenopausal brain. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the methodological rigor of radiomics-based studies using noninvasive imaging in ovarian setting. Methods: Multiple medical literature archives (PubMed, Web of Science, and Scopus) were searched to retrieve original studies focused on computed tomography (CT), magnetic resonance imaging (MRI), ultrasound (US), or positron emission tomography (PET) radiomics for ovarian disorders' assessment. Two researchers in consensus evaluated each investigation using the radiomics quality score (RQS). Subgroup analyses were performed to assess whether the total RQS varied according to first author category, study aim and topic, imaging modality, and journal quartile. Results: From a total of 531 items, 63 investigations were finally included in the analysis. The studies were greatly focused (94%) on the field of oncology, with CT representing the most used imaging technique (41%). Overall, the papers achieved a median total RQS 6 (IQR, −0.5 to 11), corresponding to a percentage of 16.7% of the maximum score (IQR, 0–30.6%). The scoring was low especially due to the lack of prospective design and formal validation of the results. At subgroup analysis, the 4 studies not focused on oncological topic showed significantly lower quality scores than the others. Conclusions: The overall methodological rigor of radiomics studies in the ovarian field is still not ideal, limiting the reproducibility of results and potential translation to clinical setting. More efforts towards a standardized methodology in the workflow are needed to allow radiomics to become a viable tool for clinical decision-making. Key Points: • The 63 included studies using noninvasive imaging for ovarian applications were mostly focused on oncologic topic (94%). • The included investigations achieved a median total RQS 6 (IQR, −0.5 to 11), indicating poor methodological rigor. • The RQS was low especially due to the lack of prospective design and formal validation of the results. [ABSTRACT FROM AUTHOR]

The European Society of Cardiovascular Radiology (ESCR) is the European specialist society of cardiac and vascular imaging. This society's highest priority is the continuous improvement, development, and standardization of education, training, and best medical practice, based on experience and evidence. The present intra-society consensus is based on the existing scientific evidence and on the individual experience of the members of the ESCR writing group on carotid diseases, the members of the ESCR guidelines committee, and the members of the executive committee of the ESCR. The recommendations published herein reflect the evidence-based society opinion of ESCR. We have produced a twin-papers consensus, indicated through the documents as respectively "Part I" and "Part II." The first document (Part I) begins with a discussion of features, role, indications, and evidence for CT and MR imaging-based diagnosis of carotid artery disease for risk stratification and prediction of stroke (Section I). It then provides an extensive overview and insight into imaging-derived biomarkers and their potential use in risk stratification (Section II). Finally, detailed recommendations about optimized imaging technique and imaging strategies are summarized (Section III). The second part of this consensus paper (Part II) is focused on structured reporting of carotid imaging studies with CT/MR. Key Points: • CT and MR imaging-based evaluation of carotid artery disease provides essential information for risk stratification and prediction of stroke. • Imaging-derived biomarkers and their potential use in risk stratification are evolving; their correct interpretation and use in clinical practice must be well-understood. • A correct imaging strategy and scan protocol will produce the best possible results for disease evaluation. [ABSTRACT FROM AUTHOR]

Objectives: Automatic bone lesions detection and classifications present a critical challenge and are essential to support radiologists in making an accurate diagnosis of bone lesions. In this paper, we aimed to develop a novel deep learning model called You Only Look Once (YOLO) to handle detecting and classifying bone lesions on full-field radiographs with limited manual intervention. Methods: In this retrospective study, we used 1085 bone tumor radiographs and 345 normal bone radiographs from two centers between January 2009 and December 2020 to train and test our YOLO deep learning (DL) model. The trained model detected bone lesions and then classified these radiographs into normal, benign, intermediate, or malignant types. The intersection over union (IoU) was used to assess the model's performance in the detection task. Confusion matrices and Cohen's kappa scores were used for evaluating classification performance. Two radiologists compared diagnostic performance with the trained model using the external validation set. Results: In the detection task, the model achieved accuracies of 86.36% and 85.37% in the internal and external validation sets, respectively. In the DL model, radiologist 1 and radiologist 2 achieved Cohen's kappa scores of 0.8187, 0.7927, and 0.9077 for four-way classification in the external validation set, respectively. The YOLO DL model illustrated a significantly higher accuracy for intermediate bone tumor classification than radiologist 1 (95.73% vs 88.08%, p = 0.004). Conclusions: The developed YOLO DL model could be used to assist radiologists at all stages of bone lesion detection and classification in full-field bone radiographs. Key Points: • YOLO DL model can automatically detect bone neoplasms from full-field radiographs in one shot and then simultaneously classify radiographs into normal, benign, intermediate, or malignant. • The dataset used in this retrospective study includes normal bone radiographs. • YOLO can detect even some challenging cases with small volumes. [ABSTRACT FROM AUTHOR]

In 2012, the European Society of Urogenital Radiology (ESUR) released a foundational paper on how to perform, interpret, and report prostate MRI, with the introduction of Prostate Imagining Reporting and Data System (PI-RADS) [[1]]. Recently, the American College of Radiology (ACR) launched an accreditation programme of imaging centres for not only diagnostic imaging, breast imaging, lung cancer screening, but also for PCa screening [[11]]. [Extracted from the article]

Objectives: Map the current landscape of commercially available artificial intelligence (AI) software for radiology and review the availability of their scientific evidence.Methods: We created an online overview of CE-marked AI software products for clinical radiology based on vendor-supplied product specifications ( www.aiforradiology.com ). Characteristics such as modality, subspeciality, main task, regulatory information, deployment, and pricing model were retrieved. We conducted an extensive literature search on the available scientific evidence of these products. Articles were classified according to a hierarchical model of efficacy.Results: The overview included 100 CE-marked AI products from 54 different vendors. For 64/100 products, there was no peer-reviewed evidence of its efficacy. We observed a large heterogeneity in deployment methods, pricing models, and regulatory classes. The evidence of the remaining 36/100 products comprised 237 papers that predominantly (65%) focused on diagnostic accuracy (efficacy level 2). From the 100 products, 18 had evidence that regarded level 3 or higher, validating the (potential) impact on diagnostic thinking, patient outcome, or costs. Half of the available evidence (116/237) were independent and not (co-)funded or (co-)authored by the vendor.Conclusions: Even though the commercial supply of AI software in radiology already holds 100 CE-marked products, we conclude that the sector is still in its infancy. For 64/100 products, peer-reviewed evidence on its efficacy is lacking. Only 18/100 AI products have demonstrated (potential) clinical impact.Key Points: • Artificial intelligence in radiology is still in its infancy even though already 100 CE-marked AI products are commercially available. • Only 36 out of 100 products have peer-reviewed evidence of which most studies demonstrate lower levels of efficacy. • There is a wide variety in deployment strategies, pricing models, and CE marking class of AI products for radiology. [ABSTRACT FROM AUTHOR]

Objective: The goals of this study were (i) to assess the association between hip capsule morphology and pain in patients without any other MRI abnormalities that would correlate with pain and (ii) to investigate whether hip capsule morphology in hip pain patients is different from that of controls. Methods: In this study, 76 adults with hip pain who did not show any structural abnormalities on MRI and 46 asymptomatic volunteers were included. Manual segmentation of the anterior and posterior hip capsules was performed. Total and mean anterior hip capsule area, posterior capsule area, anterior-to-posterior capsule area ratio, and medial-to-lateral area ratio in the anterior capsule were quantified. Differences between the pain and control groups were evaluated using logistic regression models. Results: Patients with hip pain showed a significantly lower anterior-to-posterior area ratio as compared with the control group (p = 0.002). The pain group's posterior hip capsule area was significantly larger than that of controls (p = 0.001). Additionally, the ratio between the medial and lateral sections of the anterior capsule was significantly lower in the pain group (p = 0.004). Conclusions: Patients with hip pain are more likely to have thicker posterior capsules and a lower ratio of the anterior-to-posterior capsule area and thinner medial anterior capsules with a lower ratio of the medial-to-lateral anterior hip capsule compartment, compared with controls. Clinical relevance statement: During MRI evaluations of patients with hip pain, morphology of the hip capsule should be assessed. This study aims to be a foundation for future analyses to identify thresholds distinguishing normal from abnormal hip capsule measurements. Key Points: • Even with modern image modalities such as MRI, one of the biggest challenges in handling hip pain patients is finding a structural link for their pain. • Hip capsule morphologies that correlated with hip pain showed a larger posterior hip capsule area and a lower anterior-to-posterior capsule area ratio, as well as a smaller medial anterior capsule area with a lower medial-to-lateral anterior hip capsule ratio. • The hip capsule morphology is correlated with hip pain in patients who do not show other morphology abnormalities in MRI and should get more attention in clinical practice. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to evaluate the performance of artificial intelligence (AI) software in bone age (BA) assessment, according to the Greulich and Pyle (G&P) method in a German pediatric cohort. Materials and methods: Hand radiographs of 306 pediatric patients aged 1–18 years (153 boys, 153 girls, 18 patients per year of life)—including a subgroup of patients in the age group for which the software is declared (243 patients)—were analyzed retrospectively. Two pediatric radiologists and one endocrinologist made independent blinded BA reads. Subsequently, AI software estimated BA from the same images. Both agreements, accuracy, and interchangeability between AI and expert readers were assessed. Results: The mean difference between the average of three expert readers and AI software was 0.39 months with a mean absolute difference (MAD) of 6.8 months (1.73 months for the mean difference and 6.0 months for MAD in the intended use subgroup). Performance in boys was slightly worse than in girls (MAD 6.3 months vs. 5.6 months). Regression analyses showed constant bias (slope of 1.01 with a 95% CI 0.99–1.02). The estimated equivalence index for interchangeability was − 14.3 (95% CI −27.6 to − 1.1). Conclusion: In terms of BA assessment, the new AI software was interchangeable with expert readers using the G&P method. Clinical relevance statement: The use of AI software enables every physician to provide expert reader quality in bone age assessment. Key Points: • A novel artificial intelligence–based software for bone age estimation has not yet been clinically validated. • Artificial intelligence showed a good agreement and high accuracy with expert radiologists performing bone age assessment. • Artificial intelligence showed to be interchangeable with expert readers. [ABSTRACT FROM AUTHOR]

Objectives: Significant atherosclerotic stenosis or occlusion in the distal internal carotid artery (ICA) may induce diffuse wall thickening (DWT) in the upstream arterial wall. This study aimed to assess the association of atherosclerotic steno-occlusive diseases in the distal ICA with DWT in the upstream ipsilateral ICA. Methods: Individuals with atherosclerotic stenosis in the distal ICA, detected by carotid MR vessel wall imaging using 3D pre- and post-contrast T1 volume isotropic turbo spin-echo acquisition (T1-VISTA) sequence, were enrolled. The associations of vessel wall thickening, the longitudinal extent of DWT, enhancement of the upstream ipsilateral ICA, and stenosis degree in the distal ICA were examined. Results: Totally 64 arteries in 55 patients with atherosclerotic steno-occlusive distal ICAs were included. Significant correlations were found between distal ICA stenosis and DWT in the petrous ICA (r = 0.422, p = 0.001), DWT severity (r = 0.474, p < 0.001), the longitudinal extent of DWT in the ICA (r = 0.671, p < 0.001), enhancement in the petrous ICA (r = 0.409, p = 0.001), and enhancement degree (r = 0.651, p < 0.001). In addition, high degree of enhancement was correlated with both increased wall thickness and increased prevalence of DWT in the petrous ICA (both p < 0.001). Conclusions: DWT of the petrous ICA is commonly detected in patients with atherosclerotic steno-occlusive disease in the distal ICA. The degree of stenosis in the distal ICA is associated with wall thickening and its longitudinal extent in the upstream segments. Clinical relevance statement: Diffuse wall thickening is a common secondary change in atherosclerotic steno-occlusive disease in the intracranial carotid. This phenomenon constitutes a confounding factor in the distinction between atherosclerosis and inflammatory vasculopathies, and could be reversed after alleviated atherosclerotic stenosis. Key Points: • Diffuse wall thickening of the petrous internal carotid artery is commonly detected in patients with atherosclerotic steno-occlusive disease in the distal internal carotid artery. • The phenomenon of diffuse wall thickening could be reversed after stenosis alleviation. • Carotid artery atherosclerosis with diffuse wall thickening should warrant a differential diagnosis from other steno-occlusive diseases, including moyamoya diseases and Takayasu aortitis. [ABSTRACT FROM AUTHOR]

Objectives: To compare cardiac computed tomography (CCT) and cardiac magnetic resonance (CMR) for the quantitative assessment of the left ventricular (LV) trabeculated layer in patients with suspected noncompaction cardiomyopathy (NCCM). Materials and methods: Subjects with LV excessive trabeculation who underwent both CMR and CCT imaging as part of the prospective international multicenter NONCOMPACT clinical study were included. For each subject, short-axis CCT and CMR slices were matched. Four quantitative metrics were estimated: 1D noncompacted-to-compacted ratio (NCC), trabecular-to-myocardial area ratio (TMA), trabecular-to-endocardial cavity area ratio (TCA), and trabecular-to-myocardial volume ratio (TMV). In 20 subjects, end-diastolic and mid-diastolic CCT images were compared for the quantification of the trabeculated layer. Relationships between the metrics were investigated using linear regression models and Bland-Altman analyses. Results: Forty-eight subjects (49.9 ± 12.8 years; 28 female) were included in this study. NCC was moderately correlated (r = 0.62), TMA and TMV were strongly correlated (r = 0.78 and 0.78), and TCA had excellent correlation (r = 0.92) between CMR and CCT, with an underestimation bias from CCT of 0.3 units, and 5.1, 4.8, and 5.4 percent-points for the 4 metrics, respectively. TMA, TCA, and TMV had excellent correlations (r = 0.93, 0.96, 0.94) and low biases (− 3.8, 0.8, − 3.8 percent-points) between the end-diastolic and mid-diastolic CCT images. Conclusions: TMA, TCA, and TMV metrics of the LV trabeculated layer in patients with suspected NCCM demonstrated high concordance between CCT and CMR images. TMA and TCA were highly reproducible and demonstrated minimal differences between mid-diastolic and end-diastolic CCT images. Clinical relevance statement: The results indicate similarity of CCT to CMR for quantifying the LV trabeculated layer, and the small differences in quantification between end-diastole and mid-diastole demonstrate the potential for quantifying the LV trabeculated layer from clinically performed coronary CT angiograms. Key Points: • Data on cardiac CT for quantifying the left ventricular trabeculated layer are limited. • Cardiac CT yielded highly reproducible metrics of the left ventricular trabeculated layer that correlated well with metrics defined by cardiac MR. • Cardiac CT appears to be equivalent to cardiac MR for the quantification of the left ventricular trabeculated layer. [ABSTRACT FROM AUTHOR]