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Background To compare the quality of free-text reports (FTR) and structured reports (SR) of brain magnetic resonance imaging (MRI) examinations in patients following mechanical thrombectomy for acute stroke treatment. Methods A template for SR of brain MRI examinations based on decision trees was designed and developed in house and applied to twenty patients with acute ischemic stroke in addition to FTR. Two experienced stroke neurologists independently evaluated the quality of FTR and SR regarding clarity, content, presence of key features, information extraction, and overall report quality. The statistical analysis for the differences between FTR and SR was performed using the Mann–Whitney U-test or the Chi-squared test. Results Clarity (p < 0.001), comprehensibility (p < 0.001), inclusion of relevant findings (p = 0.016), structure (p = 0.005), and satisfaction with the content of the report for immediate patient management (p < 0.001) were evaluated significantly superior for the SR by both neurologist raters. One rater additionally found the explanation of the patient’s clinical symptoms (p = 0.003), completeness (p < 0.009) and length (p < 0.001) of SR to be significantly superior compared to FTR and stated that there remained no open questions, requiring further consultation of the radiologist (p < 0.001). Both neurologists preferred SR over FTR. Conclusions The use of SR for brain magnetic resonance imaging may increase the report quality and satisfaction of the referring physicians in acute ischemic stroke patients following mechanical thrombectomy. Trial registration Retrospectively registered.

ObjectivesTo update the 2012 ESGAR consensus guidelines on the acquisition, interpretation and reporting of magnetic resonance imaging (MRI) for clinical staging and restaging of rectal cancer.MethodsFourteen abdominal imaging experts from the European Society of Gastrointestinal and Abdominal Radiology (ESGAR) participated in a consensus meeting, organised according to an adaptation of the RAND-UCLA Appropriateness Method. Two independent (non-voting) Chairs facilitated the meeting. 246 items were scored (comprising 229 items from the previous 2012 consensus and 17 additional items) and classified as ‘appropriate’ or ‘inappropriate’ (defined by ≥ 80 % consensus) or uncertain (defined by < 80 % consensus).ResultsConsensus was reached for 226 (92 %) of items. From these recommendations regarding hardware, patient preparation, imaging sequences and acquisition, criteria for MR imaging evaluation and reporting structure were constructed. The main additions to the 2012 consensus include recommendations regarding use of diffusion-weighted imaging, criteria for nodal staging and a recommended structured report template.ConclusionsThese updated expert consensus recommendations should be used as clinical guidelines for primary staging and restaging of rectal cancer using MRI.Key Points• These guidelines present recommendations for staging and reporting of rectal cancer.• The guidelines were constructed through consensus amongst 14 pelvic imaging experts.• Consensus was reached by the experts for 92 % of the 246 items discussed.• Practical guidelines for nodal staging are proposed.• A structured reporting template is presented.

Structured reporting is advocated as a means of improving reporting in radiology to the ultimate benefit of both radiological and clinical practice. Several large initiatives are currently evaluating its potential. However, with numerous characterizations of the term in circulation, “structured reporting” has become ambiguous and is often confused with “standardization,” which may hamper proper evaluation and implementation in clinical practice. This paper provides an overview of interpretations of structured reporting and proposes a clear definition that differentiates structured reporting from standardization. Only a clear uniform definition facilitates evidence-based implementation, enables evaluation of its separate components, and supports (meta-)analyses of literature reports.

Synoptic reporting increases completeness and standardization of surgical pathology reports and thereby contributes to an increased quality of clinical cancer care. Nevertheless, its widespread practical implementation remains a challenge, which is in part related to the effort required for setup and maintenance of database structures. This prompted us to assess the effect of a simple template-based, database-free system for synoptic reporting on completeness of surgical pathology reports. For this purpose, we analyzed 200 synoptic reports (100 colon and 100 lung cancer resections each) for completeness as required by the pertinent College of American Pathologists (CAP) protocols and compared these to a control dataset of 200 narrative reports. Introduction of template-based synoptic reporting resulted in improved completeness (98% of mandatory data elements) as compared to narrative reports (77%). Narrative reports showed a high degree of completeness for data elements covered by previously existing dictation templates. In conclusion, template-based synoptic reporting without underlying database structure can be a useful transitory phase in the implementation of synoptic reporting. It can result in a similar degree of completeness as reported in the literature for database solutions and provides other benefits of synoptic reporting while facilitating its implementation.

Background: Structured reporting (SR) in oncologic imaging is becoming necessary and has recently been recognized by major scientific societies. The aim of this study was to build MRI-based structured reports for rectal cancer (RC) staging and restaging in order to provide clinicians all critical tumor information. Materials and Methods: A panel of radiologist experts in abdominal imaging, called the members of the Italian Society of Medical and Interventional Radiology, was established. The modified Delphi process was used to build the SR and to assess the level of agreement in all sections. The Cronbach’s alpha (Cα) correlation coefficient was used to assess the internal consistency of each section and to measure the quality analysis according to the average inter-item correlation. The intraclass correlation coefficient (ICC) was also evaluated. Results: After the second Delphi round of the SR RC staging, the panelists’ single scores and sum of scores were 3.8 (range 2–4) and 169, and the SR RC restaging panelists’ single scores and sum of scores were 3.7 (range 2–4) and 148, respectively. The Cα correlation coefficient was 0.79 for SR staging and 0.81 for SR restaging. The ICCs for the SR RC staging and restaging were 0.78 (p < 0.01) and 0.82 (p < 0.01), respectively. The final SR version was built and included 53 items for RC staging and 50 items for RC restaging. Conclusions: The final version of the structured reports of MRI-based RC staging and restaging should be a helpful and promising tool for clinicians in managing cancer patients properly. Structured reports collect all Patient Clinical Data, Clinical Evaluations and relevant key findings of Rectal Cancer, both in staging and restaging, and can facilitate clinical decision-making.

Objectives To assess the opinion on structured reporting (SR) and its usage by radiologist members of the Italian Society of Medical Radiology (SIRM) via an online survey. Methods All members received an email invitation to join the survey as an initiative by the SIRM Imaging Informatics Chapter. The survey included 10 questions about demographic information, definition of radiological SR, its usage in everyday practice, perceived advantages and disadvantages over conventional reporting and overall opinion about SR. Results 1159 SIRM members participated in the survey. 40.3 % of respondents gave a correct definition of radiological SR, but as many as 56 % of them never used it at work. Compared with conventional reporting, the most appreciated advantages of SR were higher reproducibility (70.5 %), better interaction with referring clinicians (58.3 %) and the option to link metadata (36.7 %). Risk of excessive simplification (59.8 %), template rigidity (56.1 %) and poor user compliance (42.1 %) were the most significant disadvantages. Overall, most respondents (87.0 %) were in favour of the adoption of radiological SR. Conclusions Most radiologists were interested in radiological SR and in favour of its adoption. However, concerns about semantic, technical and professional issues limited its diffusion in real working life, encouraging efforts towards improved SR standardisation and engineering. Key Points • Despite radiologists’ awareness, radiological SR is little used in working practice. • Perceived SR advantages are reproducibility, better clinico-radiological interaction and link to metadata. • Perceived SR disadvantages are excessive simplification, template rigidity and poor user compliance. • Improved standardisation and engineering may be helpful to boost SR diffusion.

Rectal MR is the key diagnostic exam at initial presentation for rectal cancer patients. It is the primary determinant in establishing clinical stage for the patient and greatly impacts the clinical decision-making process. Consequently, structured reporting for MR is critically important to ensure that all required information is provided to the clinical care team. The SAR initial staging reporting template has been constructed to address these important items, including locoregional extent and factors impacting the surgical approach and management of the patient. Potential outputs to each item are defined, requiring the radiologist to commit to a result. This provides essential information to the surgeon or oncologist to make specific treatment deisions for the patient. The SAR Initial Staging MR reporting template has now been officially adopted by the NAPRC (National Accreditation Program for Rectal Cancer) under the American College of Surgery. With the recent revisions to the reporting template, this user guide has been revamped to improve its practicality and support to the radiologist to complete the structured report. Each line item of the report is supplemented with clinical perspectives, images, and illustrations to help the radiologist understand the potential implications for a given finding. Common errors and pitfalls to avoid are highlighted. Ideally, rectal MR interpretation should not occur in a vacuum but in the context of a multi-disciplinary tumor board to ensure that healthcare providers use common terminology and share a solid understanding of the strengths and weaknesses of MR.

Even today, surgical reports are usually dictated in a free text form (FTR), leading to a wide range in report-quality. This study investigated the use of a fully structured panendoscopy report (SR) compared to FTRs. 64 panendoscopies were performed by three experienced head and neck surgeons. The surgical reports were created as both FTRs and SRs, which were examined regarding time to completion and content using a multilevel regression analysis. User satisfaction was evaluated using a questionnaire. There was no significant difference in time to complete the SRs compared to FTRs. The completeness ratings of SRs were significantly higher than for FTRs (81% vs. 66%, p  < 0.001), leading to increased report quality. Overall user satisfaction was higher for SRs than for conventional FTRs (VAS 8.1 vs. 3.5, p  < 0.001). The SRs proved to be fast to complete and more comprehensive with a higher completeness of content. Participating surgeons indicated that they preferred SRs over FTRs because of their advantages in terms of structure, guidance for inexperienced residents and non-native speakers. The data stratification also enables secondary data use to further develop deep learning algorithms in patient care and research.

BackgroundTo evaluate the implementation process of structured reporting (SR) in a tertiary care institution over a period of 7 years.MethodsWe analysed the content of our image database from January 2016 to December 2022 and compared the numbers of structured reports and free-text reports. For the ten most common SR templates, usage proportions were calculated on a quarterly basis. Annual modality-specific SR usage was calculated for ultrasound, CT, and MRI. During the implementation process, we surveyed radiologists and clinical referring physicians concerning their views on reporting in radiology.ResultsAs of December 2022, our reporting platform contained more than 22,000 structured reports. Use of the ten most common SR templates increased markedly since their implementation, leading to a mean SR usage of 77% in Q4 2022. The highest percentages of SR usage were shown for trauma CT, focussed assessment with ultrasound for trauma (FAST), and prostate MRI: 97%, 95%, and 92%, respectively, in 2022. Overall modality-specific SR usage was 17% for ultrasound, 13% for CT, and 6% for MRI in 2022. Both radiologists and referring physicians were more satisfied with structured reports and rated SR better than free-text reporting (FTR) on various attributes.ConclusionsThe increasing SR usage during the period under review and the positive attitude towards SR among both radiologists and clinical referrers show that SR can be successfully implemented. We therefore encourage others to take this step in order to benefit from the advantages of SR. Key pointsStructured reporting usage increased markedly since its implementation at our institution in 2016.Mean usage for the ten most popular structured reporting templates was 77% in 2022.Both radiologists and referring physicians preferred structured reports over free-text reports.Our data shows that structured reporting can be successfully implemented.We strongly encourage others to implement structured reporting at their institutions.

A significant volume of medical data remains unstructured. Natural language processing (NLP) and machine learning (ML) techniques have shown to successfully extract insights from radiology reports. However, the codependent effects of NLP and ML in this context have not been well-studied. Between April 1, 2015 and November 1, 2016, 9418 cross-sectional abdomen/pelvis CT and MR examinations containing our internal structured reporting element for cancer were separated into four categories: Progression, Stable Disease, Improvement, or No Cancer. We combined each of three NLP techniques with five ML algorithms to predict the assigned label using the unstructured report text and compared the performance of each combination. The three NLP algorithms included term frequency-inverse document frequency (TF-IDF), term frequency weighting (TF), and 16-bit feature hashing. The ML algorithms included logistic regression (LR), random decision forest (RDF), one-vs-all support vector machine (SVM), one-vs-all Bayes point machine (BPM), and fully connected neural network (NN). The best-performing NLP model consisted of tokenized unigrams and bigrams with TF-IDF. Increasing N-gram length yielded little to no added benefit for most ML algorithms. With all parameters optimized, SVM had the best performance on the test dataset, with 90.6 average accuracy and F score of 0.813. The interplay between ML and NLP algorithms and their effect on interpretation accuracy is complex. The best accuracy is achieved when both algorithms are optimized concurrently.