Data set for the reporting of lung cancer: recommendations from the International Collaboration on Cancer Reporting (ICCR).

Lung cancer is the leading cause of cancer related deaths worldwide, although some patients with early-stage disease can be cured with surgical resection. Standardised reporting of all clinically relevant pathological parameters is essential for best patient care and is also important for ongoing data collection and refinement of important pathological features that impact patient prognosis, staging and clinical care. Using the established International Collaboration on Cancer Reporting (ICCR) procedure, a representative international expert panel of nine lung pathologists as well as an oncologist was convened. Essential core elements and suggested non-core elements were identified for inclusion in the resected lung cancer pathology data set based on predetermined levels of evidence as well as consensus expert opinion. A lung cancer histopathology reporting guide was developed that includes relevant clinical, macroscopic, microscopic and ancillary testing. Critical review and discussion of current evidence was incorporated into the new data set including changes from the 2021 World Health Organisation (WHO) Classification of Thoracic Tumours, fifth edition, new requirements for grading invasive non-mucinous adenocarcinomas, assessment of response to neoadjuvant therapy and requirements for molecular testing in early-stage resected lung carcinomas. This ICCR data set represents incorporation of all relevant parameters for histology reporting of lung cancer resection specimens. Routine use of this data set is recommended for all pathology reporting of resected lung cancer and it is freely available worldwide on the ICCR website (https://www.iccr-cancer.org/datasets/published-datasets/). Widespread implementation will help to ensure consistent and comprehensive pathology reporting and data collection essential for lung cancer patient care, clinical trials and other research.

"3 + X D" structured report in radiology standardized resident training: Can it meet high-level teaching objectives?

PURPOSE: To evaluate the impact of the innovative "3 + X D" structured report (SR) designed based on Bloom's taxonomy on the learning outcomes of radiology residents during standardized training. METHODS: This is a prospective study that recruited 120 radiology residents from our hospital between 2020 and 2022. Randomly selected 60 residents from the 2020 grade to constituted the control group, and randomly selected 60 residents from the 2021 grade to formed the experimental group. The former group was trained utilizing the Free-text Reports (FTR) template, while the latter group received training with the "3 + X D" structured reports (SR) template. The learning outcomes of both groups was evaluated utilizing both objective and subjective measures. Objective assessments encompassed examinations of theoretical knowledge, diagnostic skills, and total scores, aligning with the cognitive domains of remembering, understanding, applying, and analyzing as outlined by Bloom's Taxonomy. Subjective assessments, on the other hand, comprised survey questionnaires administered to residents and feedback from clinical instructors, which correlated with the higher-order cognitive level of analyzing, evaluating, and creating within Bloom's Taxonomy. RESULTS: On 60 residents (mean age, 24.15 years ± 2.11[SD]; 25 male) from control group, and 60 residents (mean age, 24.58 years ± 1.88 [SD]; 27 male) from experimental group. Following the training, significant improvements were observed in the theoretical knowledge, diagnostic skills, and total scores for both groups (p < 0.001). Furthermore, the experimental group demonstrated significantly higher diagnostic skills and total scores compared to the control group (p < 0.001). However, no significant difference was observed in the theoretical knowledge exam between the two groups (p = 0.236). The questionnaire used for subjective assessments had good reliability (Cronbach α was 0.826) and acceptable validity (The KMO was 0.692). Additionally, the survey questionnaires indicated that the experimental group rated higher than the control group in terms of cultivating imaging thinking ability, diagnostic confidence, diagnostic speed, and the convenience of the templates (p < 0.001). Clinicians' feedback scores for the experimental group markedly surpassed those for the control group (p < 0.05). CONCLUSIONS: Utilizing the "3 + X D" SR template grounded in Bloom's taxonomy for training, the professional competency of radiology residents, particularly their diagnostic skills, saw a marked enhancement, successfully meeting the higher-level educational objectives. Consequently, the "3 + X D" SR template is highly recommended for the standardized training of radiology residents.

[Development of Dose Calculation Application for Computed Tomography Dose Management When Facility Protocols Differ from Diagnostic Reference Level (DRL)].

PURPOSE: In this study, we aimed to develop an application that computes dose values resembling diagnostic reference level (DRL) conditions when disparity prevents direct dose comparisons between the national diagnostic reference levels in Japan 2020 (Japan DRLs_2020) and facility-specific computed tomography (CT) protocols. METHODS: We developed an application using the R programming language and RStudio software that computes dose values and median values based on Japan DRLs_2020 imaging conditions following extraction of necessary information for dose calculations from the Radiation Dose Structured Report (RDSR) and Digital Imaging and Communications in Medicine (DICOM) tags. To ensure a user-friendly experience, we used the Shiny package to develop a graphical user interface that enables the application to operate seamlessly in web browsers. RESULTS: The developed application successfully facilitated the calculation of dose and median values that aligned with the Japan DRLs_2020 for protocols whose imaging range and acquisition timing differed from those of the Japan DRLs_2020. CONCLUSION: By calculating dose values that align with DRL conditions, our application contributes to the implementation and optimization of dose management in CT for facilities that use diverse imaging protocols.

Standardised and structured reporting in fetal magnetic resonance imaging: recommendations from the Fetal Task Force of the European Society of Paediatric Radiology.

Over the last decades, magnetic resonance imaging (MRI) has emerged as a valuable adjunct to prenatal ultrasound for evaluating fetal malformations. Several radiological societies advocate for standardised and structured reporting practices to enhance the uniformity of imaging language. Compared to narrative formats, standardised and structured reports offer enhanced content quality, minimise reader variability, have the potential to save reporting time, and streamline the communication between specialists by employing a shared lexicon. Structured reporting holds promise for mitigating medico-legal liability, while also facilitating rigorous scientific data analyses and the development of standardised databases. While structured reporting templates for fetal MRI are already in use in some centres, specific recommendations and/or guidelines from international societies are scarce in the literature. The purpose of this paper is to propose a standardised and structured reporting template for fetal MRI to assist radiologists, particularly those with less experience, in delivering systematic reports. Additionally, the paper aims to offer an overview of the anatomical structures that necessitate reporting and the prevalent normative values for fetal biometrics found in current literature.

The importance and future of prostate MRI report templates: improving oncological care.

The radiologist's report is crucial for guiding care post-imaging, with ongoing advancements in report construction. Recent studies across various modalities and organ systems demonstrate enhanced clarity and communication through structured reports. This article will explain the benefits of disease-state specific reporting templates using prostate MRI as the model system. We identify key reporting components for prostate cancer detection and staging as well as imaging in active surveillance and following therapy. We discuss relevant reporting systems including PI-QUAL, PI-RADS, PRECISE, PI-RR and PI-FAB systems. Additionally, we examine optimal reporting structure including disruptive technologies such as graphical reporting and using artificial intelligence to improve report clarity and applicability.

Dataset for reporting of the invasive carcinoma of the breast: recommendations from the International Collaboration on Cancer Reporting (ICCR).

BACKGROUND AND OBJECTIVES: Current national or regional guidelines for the pathology reporting on invasive breast cancer differ in certain aspects, resulting in divergent reporting practice and a lack of comparability of data. Here we report on a new international dataset for the pathology reporting of resection specimens with invasive cancer of the breast. The dataset was produced under the auspices of the International Collaboration on Cancer Reporting (ICCR), a global alliance of major (inter-)national pathology and cancer organizations. METHODS AND RESULTS: The established ICCR process for dataset development was followed. An international expert panel consisting of breast pathologists, a surgeon, and an oncologist prepared a draft set of core and noncore data items based on a critical review and discussion of current evidence. Commentary was provided for each data item to explain the rationale for selecting it as a core or noncore element, its clinical relevance, and to highlight potential areas of disagreement or lack of evidence, in which case a consensus position was formulated. Following international public consultation, the document was finalized and ratified, and the dataset, which includes a synoptic reporting guide, was published on the ICCR website. CONCLUSIONS: This first international dataset for invasive cancer of the breast is intended to promote high-quality, standardized pathology reporting. Its widespread adoption will improve consistency of reporting, facilitate multidisciplinary communication, and enhance comparability of data, all of which will help to improve the management of invasive breast cancer patients.

Transforming free-text radiology reports into structured reports using ChatGPT: A study on thyroid ultrasonography.

PURPOSE: The importance of structured radiology reports has been fully recognized, as they facilitate efficient data extraction and promote collaboration among healthcare professionals. Our purpose is to assess the accuracy and reproducibility of ChatGPT, a large language model, in generating structured thyroid ultrasound reports. METHODS: This is a retrospective study that includes 184 nodules in 136 thyroid ultrasound reports from 136 patients. ChatGPT-3.5 and ChatGPT-4.0 were used to structure the reports based on ACR-TIRADS guidelines. Two radiologists evaluated the responses for quality, nodule categorization accuracy, and management recommendations. Each text was submitted twice to assess the consistency of the nodule classification and management recommendations. RESULTS: On 136 ultrasound reports from 136 patients (mean age, 52 years ± 12 [SD]; 61 male), ChatGPT-3.5 generated 202 satisfactory structured reports, while ChatGPT-4.0 only produced 69 satisfactory structured reports (74.3 % vs. 25.4 %, odds ratio (OR) = 8.490, 95 %CI: 5.775-12.481, p < 0.001). ChatGPT-4.0 outperformed ChatGPT-3.5 in categorizing thyroid nodules, with an accuracy of 69.3 % compared to 34.5 % (OR = 4.282, 95 %CI: 3.145-5.831, p < 0.001). ChatGPT-4.0 also provided more comprehensive or correct management recommendations than ChatGPT-3.5 (OR = 1.791, 95 %CI: 1.297-2.473, p < 0.001). Finally, ChatGPT-4.0 exhibits higher consistency in categorizing nodules compared to ChatGPT-3.5 (ICC = 0.732 vs. ICC = 0.429), and both exhibited moderate consistency in management recommendations (ICC = 0.549 vs ICC = 0.575). CONCLUSIONS: Our study demonstrates the potential of ChatGPT in transforming free-text thyroid ultrasound reports into structured formats. ChatGPT-3.5 excels in generating structured reports, while ChatGPT-4.0 shows superior accuracy in nodule categorization and management recommendations.

Using GPT-4 for LI-RADS feature extraction and categorization with multilingual free-text reports.

BACKGROUND AND AIMS: The Liver Imaging Reporting and Data System (LI-RADS) offers a standardized approach for imaging hepatocellular carcinoma. However, the diverse styles and structures of radiology reports complicate automatic data extraction. Large language models hold the potential for structured data extraction from free-text reports. Our objective was to evaluate the performance of Generative Pre-trained Transformer (GPT)-4 in extracting LI-RADS features and categories from free-text liver magnetic resonance imaging (MRI) reports. METHODS: Three radiologists generated 160 fictitious free-text liver MRI reports written in Korean and English, simulating real-world practice. Of these, 20 were used for prompt engineering, and 140 formed the internal test cohort. Seventy-two genuine reports, authored by 17 radiologists were collected and de-identified for the external test cohort. LI-RADS features were extracted using GPT-4, with a Python script calculating categories. Accuracies in each test cohort were compared. RESULTS: On the external test, the accuracy for the extraction of major LI-RADS features, which encompass size, nonrim arterial phase hyperenhancement, nonperipheral 'washout', enhancing 'capsule' and threshold growth, ranged from .92 to .99. For the rest of the LI-RADS features, the accuracy ranged from .86 to .97. For the LI-RADS category, the model showed an accuracy of .85 (95% CI: .76, .93). CONCLUSIONS: GPT-4 shows promise in extracting LI-RADS features, yet further refinement of its prompting strategy and advancements in its neural network architecture are crucial for reliable use in processing complex real-world MRI reports.

Update on imaging recommendations in paediatric uroradiology: the European Society of Paediatric Radiology workgroup session on voiding cystourethrography.

Voiding cystourethrography (VCUG) is a fluoroscopic technique that allows the assessment of the urinary tract, including the urethra, bladder, and-if vesicoureteral reflux (VUR) is present-the ureters and the pelvicalyceal systems. The technique also allows for the assessment of bladder filling and emptying, providing information on anatomical and functional aspects. VCUG is, together with contrast-enhanced voiding urosonography (VUS), still the gold standard test to diagnose VUR and it is one of the most performed fluoroscopic examinations in pediatric radiology departments. VCUG is also considered a follow-up examination after urinary tract surgery, and one of the most sensitive techniques for studying anatomy of the lower genitourinary tract in suspected anatomical malformations. The international reflux study in 1985 published the first reflux-protocol and graded VUR into five classes; over the following years, other papers have been published on this topic. In 2008, the European Society of Paediatric Radiology (ESPR) Uroradiology Task Force published the first proposed VCUG Guidelines with internal scientific society agreement. The purpose of our work is to create a detailed overview of VCUG indications, procedural recommendations, and to provide a structured final report, with the aim of updating the 2008 VCUG paper proposed by the European Society of Paediatric Radiology (ESPR). We have also compared VCUG with contrast-enhanced VUS as an emergent alternative. As a result of this work, the ESPR Urogenital Task Force strongly recommends the use of contrast-enhanced VUS as a non-radiating imaging technique whenever indicated and possible.

A dedicated structured data set for reporting of invasive carcinoma of the breast in the setting of neoadjuvant therapy: recommendations from the International Collaboration on Cancer Reporting (ICCR).

AIMS: The International Collaboration on Cancer Reporting (ICCR), a global alliance of major (inter-)national pathology and cancer organisations, is an initiative aimed at providing a unified international approach to reporting cancer. ICCR recently published new data sets for the reporting of invasive breast carcinoma, surgically removed lymph nodes for breast tumours and ductal carcinoma in situ, variants of lobular carcinoma in situ and low-grade lesions. The data set in this paper addresses the neoadjuvant setting. The aim is to promote high-quality, standardised reporting of tumour response and residual disease after neoadjuvant treatment that can be used for subsequent management decisions for each patient. METHODS: The ICCR convened expert panels of breast pathologists with a representative surgeon and oncologist to critically review and discuss current evidence. Feedback from the international public consultation was critical in the development of this data set. RESULTS: The expert panel concluded that a dedicated data set was required for reporting of breast specimens post-neoadjuvant therapy with inclusion of data elements specific to the neoadjuvant setting as core or non-core elements. This data set proposes a practical approach for handling and reporting breast resection specimens following neoadjuvant therapy. The comments for each data element clarify terminology, discuss available evidence and highlight areas with limited evidence that need further study. This data set overlaps with, and should be used in conjunction with, the data sets for the reporting of invasive breast carcinoma and surgically removed lymph nodes from patients with breast tumours, as appropriate. Key issues specific to the neoadjuvant setting are included in this paper. The entire data set is freely available on the ICCR website. CONCLUSIONS: High-quality, standardised reporting of tumour response and residual disease after neoadjuvant treatment are critical for subsequent management decisions for each patient.

Structured Reporting of Computed Tomography Enterography in Crohn's Disease.

BACKGROUND: To compare the integrity, clarity, conciseness, etc., of the structured report (SR) versus free-text report (FTR) for computed tomography enterography of Crohn's disease (CD). METHODS: FTRs and SRs were generated for 30 patients with CD. The integrity, clarity, conciseness etc., of SRs versus FTRs, were compared. In this study, an evidence-based medicine practice model was utilized on 92 CD patients based on SR in order to evaluate its clinical value. Then, the life quality of the patients in two groups was evaluated before and after three months of intervention using an Inflammatory Bowel Disease Questionnaire (IBDQ). RESULTS: SRs received higher ratings for satisfaction with integrity (median rating 4.27 vs. 3.75, P=0.008), clarity (median rating 4.20 vs. 3.43, P=0.003), conciseness (median rating 4.23 vs. 3.20, P=0.003), the possibility of contacting a radiologist to interpret (median rating 4.17 vs. 3.20, P<0.001), and overall clinical impact (median rating 4.23 vs. 3.27, P<0.001) than FTRs. Besides, research group had higher score of IBDQ intestinal symptom dimension (median score 61.13 vs. 58.02, P=0.003), IBDQ systemic symptom dimension (median score 24.48 vs. 20.67, P<0.001), IBDQ emotional capacity dimension (median score 65.65 vs. 61.74, P<0.001), IBDQ social ability dimension (median score 26.80 vs. 22.37, P<0.001), and total IBDQ score (median score 178.07 vs. 162.80, P<0.001) than control group. CONCLUSION: The SR of CTE in CD patients was conducive to improving the quality and readability of the report, and CD patients' life quality could significantly improve after the intervention of an evidence-based medicine model based on SR.

Design of HL7 FHIR Profiles for Pathology Reports Integrated with Pathology Images.

This paper describes the development of Health Level Seven Fast Healthcare Interoperability Resource (FHIR) profiles for pathology reports integrated with whole slide images and clinical data to create a pathology research database. A report template was designed to collect structured reports, enabling pathologists to select structured terms based on a checklist, allowing for the standardization of terms used to describe tumor features. We gathered and analyzed 190 non-small-cell lung cancer pathology reports in free text format, which were then structured by mapping the itemized vocabulary to FHIR observation resources, using international standard terminologies, such as the International Classification of Diseases, LOINC, and SNOMED CT. The resulting FHIR profiles were published as an implementation guide, which includes 25 profiles for essential data elements, value sets, and structured definitions for integrating clinical data and pathology images associated with the pathology report. These profiles enable the exchange of structured data between systems and facilitate the integration of pathology data into electronic health records, which can improve the quality of care for patients with cancer.

Mesothelioma in the pleura, pericardium and peritoneum: Recommendations from the International Collaboration on Cancer Reporting (ICCR).

AIMS: Mesothelioma is a rare malignancy of the serosal membranes that is commonly related to exposure to asbestos. Despite extensive research and clinical trials, prognosis to date remains poor. Consistent, comprehensive and reproducible pathology reporting form the basis of all future interventions for an individual patient, but also ensures that meaningful data are collected to identify predictive and prognostic markers. METHODS AND RESULTS: This article details the International Collaboration on Cancer Reporting (ICCR) process and the development of the international consensus mesothelioma reporting data set. It describes the 'core' and 'non-core' elements to be included in pathology reports for mesothelioma of all sites, inclusive of clinical, macroscopic, microscopic and ancillary testing considerations. An international expert panel consisting of pathologists and a medical oncologist produced a set of data items for biopsy and resection specimens based on a critical review and discussion of current evidence, and in light of the changes in the 2021 WHO Classification of Tumours. The commentary focuses particularly upon new entities such as mesothelioma in situ and provides background on relevant and essential ancillary testing as well as implementation of the new requirement for tumour grading. CONCLUSION: We recommend widespread and consistent implementation of this data set, which will facilitate accurate reporting and enhance the consistency of data collection, improve the comparison of epidemiological data, support retrospective research and ultimately help to improve clinical outcomes. To this end, all data sets are freely available worldwide on the ICCR website (www.iccr-cancer.org/data-sets).

Acute Colonic Diverticulitis: CT Findings, Classifications, and a Proposal of a Structured Reporting Template.

Acute colonic diverticulitis (ACD) is the most common complication of diverticular disease and represents an abdominal emergency. It includes a variety of conditions, extending from localized diverticular inflammation to fecal peritonitis, hence the importance of an accurate diagnosis. Contrast-enhanced computed tomography (CE-CT) plays a pivotal role in the diagnosis due to its high sensitivity, specificity, accuracy, and interobserver agreement. In fact, CE-CT allows alternative diagnoses to be excluded, the inflamed diverticulum to be localized, and complications to be identified. Imaging findings have been reviewed, dividing them into bowel and extra-intestinal wall findings. Moreover, CE-CT allows staging of the disease; the most used classifications of ACD severity are Hinchey's modified and WSES classifications. Differential diagnoses include colon carcinoma, epiploic appendagitis, ischemic colitis, appendicitis, infectious enterocolitis, and inflammatory bowel disease. We propose a structured reporting template to standardize the terminology and improve communication between specialists involved in patient care.

Advancements in Standardizing Radiological Reports: A Comprehensive Review.

Standardized radiological reports stimulate debate in the medical imaging field. This review paper explores the advantages and challenges of standardized reporting. Standardized reporting can offer improved clarity and efficiency of communication among radiologists and the multidisciplinary team. However, challenges include limited flexibility, initially increased time and effort, and potential user experience issues. The efforts toward standardization are examined, encompassing the establishment of reporting templates, use of common imaging lexicons, and integration of clinical decision support tools. Recent technological advancements, including multimedia-enhanced reporting and AI-driven solutions, are discussed for their potential to improve the standardization process. Organizations such as the ACR, ESUR, RSNA, and ESR have developed standardized reporting systems, templates, and platforms to promote uniformity and collaboration. However, challenges remain in terms of workflow adjustments, language and format variability, and the need for validation. The review concludes by presenting a set of ten essential rules for creating standardized radiology reports, emphasizing clarity, consistency, and adherence to structured formats.

Dataset for reporting of thymic epithelial tumours: recommendations from the International Collaboration on Cancer Reporting (ICCR).

AIMS: Thymic epithelial tumours (TET), including thymomas and thymic carcinomas and thymic neuroendocrine neoplasms, are malignant neoplasms that can be associated with morbidity and mortality. Recently, an updated version of the World Health Organization (WHO) Classification of Thoracic Tumours 5th Edition, 2021 has been released, which included various changes to the classification of these neoplasms. In addition, in 2017 the Union for International Cancer Control (UICC) / American Joint Committee on Cancer (AJCC) published the 8th Edition Staging Manual which, for the first time, includes a TNM staging that is applicable to thymomas, thymic carcinomas, and thymic neuroendocrine neoplasms. METHODS AND RESULTS: To standardize reporting of resected TET and thymic neuroendocrine neoplasms the accrediting bodies updated their reporting protocols. The International Collaboration on Cancer Reporting (ICCR), which represents a collaboration between various National Associations of Pathology, updated its 2017 histopathology reporting guide on TET and thymic neuroendocrine neoplasms accordingly. This report will highlight important changes in the reporting of TET and thymic neuroendocrine neoplasms based on the 2021 WHO, emphasize the 2017 TNM staging, and also comment on the rigour and various uncertainties for the pathologist when trying to follow that staging. CONCLUSION: The ICCR dataset provides a comprehensive, standardized template for reporting of resected TET and thymic neuroendocrine neoplasms.

Neuropathy Score Reporting and Data System (NS-RADS): A Practical Review of MRI-Based Peripheral Neuropathy Assessment.

The Neuropathy Score Reporting and Data System (NS-RADS) is a newly developed MR imaging-based classification that standardizes reporting and multidisciplinary communication for MR imaging diagnosis and follow-up of peripheral neuropathies. NS-RADS classification has shown to be accurate and reliable across different centers, readers' experience levels, and degrees of peripheral neuropathies, which include nerve injury, entrapment, neoplasm, diffuse neuropathy, post-interventional status, and temporal changes in muscle denervation. This article brings a practical review of NS-RADS classification, representative MR cases, and a step-by-step tutorial on how to approach this staging system. Readers can gain knowledge and apply it in their practice, aiming to standardize the communications between specialties and improve patient management.

MRI of endometriosis in correlation with the #Enzian classification: applicability and structured report.

Endometriosis represents one of the most common causes of life-impacting chronic pelvic pain and female infertility. Magnetic resonance imaging (MRI) plays an increasing role in the diagnosis and mapping of endometriosis, while diagnostic laparoscopy currently tends to be reserved for the patients with negative imaging results. The #Enzian, published in 2021, proposes a new comprehensive classification system of endometriosis, combining a complete staging of deep infiltrative endometriosis with the evaluation of peritoneal/ovarian/tubal localizations and the presence of adenomyosis. This article addresses in detail the applicability of the #Enzian classification, primarily based on surgical findings, to the MRI evaluation of the endometriosis. Overall, there is a significant matching between MRI features and the #Enzian classification criteria, two different perspectives of endometriosis mapping, with different goals and levels of detail. The main discrepancy lies in the evaluation of tubo-ovarian condition, which is not fully assessable by MRI. Furthermore, as endometriosis is a complex disease, usually multifocal, that can present with a myriad of imaging findings, MRI reporting should be clear and well organized. The authors group, both radiologists and gynecologists, propose a structured MRI report of endometriosis in correlation with the #Enzian classification, merging the detailed anatomical and pre-operative information provided by the MRI with the benefits of a comprehensive classification system of endometriosis in the clinical practice and research field.Critical relevance statement This article addresses in detail the applicability of the #Enzian classification, primarily based on surgical findings, to the MRI evaluation of the endometriosis and proposes a #Enzian-based structured MRI report.

Large language models for structured reporting in radiology: performance of GPT-4, ChatGPT-3.5, Perplexity and Bing.

Structured reporting may improve the radiological workflow and communication among physicians. Artificial intelligence applications in medicine are growing fast. Large language models (LLMs) are recently gaining importance as valuable tools in radiology and are currently being tested for the critical task of structured reporting. We compared four LLMs models in terms of knowledge on structured reporting and templates proposal. LLMs hold a great potential for generating structured reports in radiology but additional formal validations are needed on this topic.

Impact of a structured reporting template on the quality of HRCT radiology reports for interstitial lung disease.

PURPOSE: This QI study compared the completeness of HRCT radiology reports before and after the implementation of a disease-specific structured reporting template for suspected cases of interstitial lung disease (ILD). MATERIALS AND METHODS: A pre-post study of radiology reports for HRCT of the thorax at a multicenter health system was performed. Data was collected in 6-month period intervals before (June 2019-November 2019) and after (January 2021-June 2021) the implementation of a disease-specific template. The use of the template was voluntary. The primary outcome measure was the completeness of HRCT reports graded based on the documentation of ten descriptors. The secondary outcome measure assessed which descriptor(s) improved after the intervention. RESULTS: 521 HRCT reports before and 557 HRCT reports after the intervention were reviewed. Of the 557 reports, 118 reports (21%) were created using the structured reporting template. The mean completeness score of the pre-intervention group was 9.20 (SD = 1.08) and the post-intervention group was 9.36 (SD = 1.03) with a difference of -0.155, 95% CI [-0.2822, -0.0285, p < 0.0001]. Within the post-intervention group, the mean completeness score of the unstructured reports was 9.25 (SD = 1.07) and the template reports was 9.93 (SD = 0.25) with a difference of -0.677, 95% CI [-0.7871, -0.5671, p < 0.0001]. After the intervention, the use of two descriptors improved significantly: presence of honeycombing from 78.3% to 85.1% (p < 0.0039) and technique from 90% to 96.6% (p < 0.0001). DISCUSSION: Shifting to disease-specific structured reporting for HRCT exams of suspected ILD is beneficial, as it improves the completeness of radiology reports. Further research on how to improve the voluntary uptake of a disease-specific template is needed to help increase the acceptance of structured reporting among radiologists.