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COVID-19 patients and the radiology department – advice from the European Society of Radiology (ESR) and the European Society of Thoracic Imaging (ESTI)
This document from the European Society of Radiology (ESR) and the European Society of Thoracic Imaging (ESTI) aims to present the main imaging features, and the role of CT scan in the early diagnosis of COVID-19, describing, in particular, the typical findings which make it possible to identify the disease and distinguish it from bacterial causes of infection, and to define which category of patients may benefit from CT imaging. The precautions that must be taken when performing scans to protect radiologists and technologists from infection will be described. The organisational measures that can be taken within radiology departments in order to cope with the influx of patients, while continuing to manage other emergency and time-sensitive activity (e.g. oncology, other infectious diseases etc.), will be discussed.
Key points
• Bilateral ground glass opacities are typical CT manifestations of COVID-19.
• Crazy paving and organising pneumonia pattern are seen at a later stage.
• Extensive consolidation is associated with a poor prognosis.
Journal Article
ESUR/ESUI consensus statements on multi-parametric MRI for the detection of clinically significant prostate cancer: quality requirements for image acquisition, interpretation and radiologists’ training
Objectives
This study aims to define consensus-based criteria for acquiring and reporting prostate MRI and establishing prerequisites for image quality.
Methods
A total of 44 leading urologists and urogenital radiologists who are experts in prostate cancer imaging from the European Society of Urogenital Radiology (ESUR) and EAU Section of Urologic Imaging (ESUI) participated in a Delphi consensus process. Panellists completed two rounds of questionnaires with 55 items under three headings: image quality assessment, interpretation and reporting, and radiologists’ experience plus training centres. Of 55 questions, 31 were rated for agreement on a 9-point scale, and 24 were multiple-choice or open. For agreement items, there was consensus agreement with an agreement ≥ 70% (score 7–9) and disagreement of ≤ 15% of the panellists. For the other questions, a consensus was considered with ≥ 50% of votes.
Results
Twenty-four out of 31 of agreement items and 11/16 of other questions reached consensus. Agreement statements were (1) reporting of image quality should be performed and implemented into clinical practice; (2) for interpretation performance, radiologists should use self-performance tests with histopathology feedback, compare their interpretation with expert-reading and use external performance assessments; and (3) radiologists must attend theoretical and hands-on courses before interpreting prostate MRI. Limitations are that the results are expert opinions and not based on systematic reviews or meta-analyses. There was no consensus on outcomes statements of prostate MRI assessment as quality marker.
Conclusions
An ESUR and ESUI expert panel showed high agreement (74%) on issues improving prostate MRI quality. Checking and reporting of image quality are mandatory. Prostate radiologists should attend theoretical and hands-on courses, followed by supervised education, and must perform regular performance assessments.
Key Points
• Multi-parametric MRI in the diagnostic pathway of prostate cancer has a well-established upfront role in the recently updated European Association of Urology guideline and American Urological Association recommendations
.
• Suboptimal image acquisition and reporting at an individual level will result in clinicians losing confidence in the technique and returning to the (non-MRI) systematic biopsy pathway. Therefore, it is crucial to establish quality criteria for the acquisition and reporting of mpMRI
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• To ensure high-quality prostate MRI, experts consider checking and reporting of image quality mandatory. Prostate radiologists must attend theoretical and hands-on courses, followed by supervised education, and must perform regular self- and external performance assessments
.
Journal Article
Updated prostate imaging reporting and data system (PIRADS v2) recommendations for the detection of clinically significant prostate cancer using multiparametric MRI: critical evaluation using whole-mount pathology as standard of reference
Objectives
To evaluate the recommendations for multiparametric prostate MRI (mp-MRI) interpretation introduced in the recently updated Prostate Imaging Reporting and Data System version 2 (PI-RADSv2), and investigate the impact of pathologic tumour volume on prostate cancer (PCa) detectability on mpMRI.
Methods
This was an institutional review board (IRB)-approved, retrospective study of 150 PCa patients who underwent mp-MRI before prostatectomy; 169 tumours ≥0.5-mL (any Gleason Score [GS]) and 37 tumours <0.5-mL (GS ≥4+3) identified on whole-mount pathology maps were located on mp-MRI consisting of T2-weighted imaging (T2WI), diffusion-weighted (DW)-MRI, and dynamic contrast-enhanced (DCE)-MRI. Corresponding PI-RADSv2 scores were assigned on each sequence and combined as recommended by PI-RADSv2. We calculated the proportion of PCa foci on whole-mount pathology correctly identified with PI-RADSv2 (dichotomized scores 1–3 vs. 4–5), stratified by pathologic tumour volume.
Results
PI-RADSv2 allowed correct identification of 118/125 (94 %; 95 %CI: 90–99 %) peripheral zone (PZ) and 42/44 (95 %; 95 %CI: 89–100 %) transition zone (TZ) tumours ≥0.5 mL, but only 7/27 (26 %; 95 %CI: 10–42 %) PZ and 2/10 (20 %; 95 %CI: 0–52 %) TZ tumours with a GS ≥4+3, but <0.5 mL. DCE-MRI aided detection of 4/125 PZ tumours ≥0.5 mL and 0/27 PZ tumours <0.5 mL.
Conclusions
PI-RADSv2 correctly identified 94–95 % of PCa foci ≥0.5 mL, but was limited for the assessment of GS ≥4+3 tumours ≤0.5 mL. DCE-MRI offered limited added value to T2WI+DW-MRI.
Key points
• PI-RADSv2 correctly identified 95 % of PCa foci ≥0.5 mL
• PI-RADSv2 was limited for the assessment of GS ≥4+3 tumours ≤0.5 mL
• DCE-MRI offered limited added value to T2WI+DW-MRI
Journal Article
A deep learning algorithm using CT images to screen for Corona virus disease (COVID-19)
Objective
The outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2) has caused more than 26 million cases of Corona virus disease (COVID-19) in the world so far. To control the spread of the disease, screening large numbers of suspected cases for appropriate quarantine and treatment are a priority. Pathogenic laboratory testing is typically the gold standard, but it bears the burden of significant false negativity, adding to the urgent need of alternative diagnostic methods to combat the disease. Based on COVID-19 radiographic changes in CT images, this study hypothesized that artificial intelligence methods might be able to extract specific graphical features of COVID-19 and provide a clinical diagnosis ahead of the pathogenic test, thus saving critical time for disease control.
Methods
We collected 1065 CT images of pathogen-confirmed COVID-19 cases along with those previously diagnosed with typical viral pneumonia. We modified the inception transfer-learning model to establish the algorithm, followed by internal and external validation.
Results
The internal validation achieved a total accuracy of 89.5% with a specificity of 0.88 and sensitivity of 0.87. The external testing dataset showed a total accuracy of 79.3% with a specificity of 0.83 and sensitivity of 0.67. In addition, in 54 COVID-19 images, the first two nucleic acid test results were negative, and 46 were predicted as COVID-19 positive by the algorithm, with an accuracy of 85.2%.
Conclusion
These results demonstrate the proof-of-principle for using artificial intelligence to extract radiological features for timely and accurate COVID-19 diagnosis.
Key Points
• The study evaluated the diagnostic performance of a deep learning algorithm using CT images to screen for COVID-19 during the influenza season.
• As a screening method, our model achieved a relatively high sensitivity on internal and external CT image datasets.
• The model was used to distinguish between COVID-19 and other typical viral pneumonia, both of which have quite similar radiologic characteristics.
Journal Article
ESR paper on structured reporting in radiology
Structured reporting is emerging as a key element of optimising radiology’s contribution to patient outcomes and ensuring the value of radiologists’ work. It is being developed and supported by many national and international radiology societies, based on the recognised need to use uniform language and structure to accurately describe radiology findings. Standardisation of report structures ensures that all relevant areas are addressed. Standardisation of terminology prevents ambiguity in reports and facilitates comparability of reports. The use of key data elements and quantified parameters in structured reports (“radiomics”) permits automatic functions (e.g. TNM staging), potential integration with other clinical parameters (e.g. laboratory results), data sharing (e.g. registries, biobanks) and data mining for research, teaching and other purposes. This article outlines the requirements for a successful structured reporting strategy (definition of content and structure, standard terminologies, tools and protocols). A potential implementation strategy is outlined. Moving from conventional prose reports to structured reporting is endorsed as a positive development, and must be an international effort, with international design and adoption of structured reporting templates that can be translated and adapted in local environments as needed. Industry involvement is key to success, based on international data standards and guidelines.
Key Points
•
Standardisation of radiology report structure ensures completeness and comparability of reports.
•
Use of standardised language in reports minimises ambiguity.
•
Structured reporting facilitates automatic functions, integration with other clinical parameters and data sharing.
•
International and inter-society cooperation is key to developing successful structured report templates.
•
Integration with industry providers of radiology-reporting software is also crucial.
Journal Article
Chest CT manifestations of new coronavirus disease 2019 (COVID-19): a pictorial review
Coronavirus disease 2019 (COVID-19) outbreak, first reported in Wuhan, China, has rapidly swept around the world just within a month, causing global public health emergency. In diagnosis, chest computed tomography (CT) manifestations can supplement parts of limitations of real-time reverse transcription polymerase chain reaction (RT-PCR) assay. Based on a comprehensive literature review and the experience in the frontline, we aim to review the typical and relatively atypical CT manifestations with representative COVID-19 cases at our hospital, and hope to strengthen the recognition of these features with radiologists and help them make a quick and accurate diagnosis.
Key Points
• Ground glass opacities, consolidation, reticular pattern, and crazy paving pattern are typical CT manifestations of COVID-19.
• Emerging atypical CT manifestations, including airway changes, pleural changes, fibrosis, nodules, etc., were demonstrated in COVID-19 patients.
• CT manifestations may associate with the progression and prognosis of COVID-19.
Journal Article