Structured Reporting in Ultrasound

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.

[Standardized acquisition and documentation of cine loops on conventional thyroid ultrasound]

Ultrasound is the basic imaging method for the assessment of the thyroid gland. Due to the high prevalence of structural disease, the examination procedure is used very frequently in Germany, in many cases in the context of follow-up. The assessment of thyroid pathologies and their dynamics is subjected to relevant inter- and intraobserver variability. Findings that were not identified during live ultrasound cannot be assessed retrospectively. Applying an SOP for the acquisition and documentation of standardized video sequences of ultrasound images (so-called cine loops), allows for a secondary retrospective evaluation of the thyroid gland, taking into account previously acquired images analogous to other cross-sectional imaging methods such as CT or MRI. The cine loops can be acquired by non-physician personnel, stored to the local PACS and used for educational and research purposes.

Gynecologic Imaging and Reporting Data System for classifying adnexal masses

INTRODUCTION

To perform a systematic review and meta-analysis of the diagnostic performance of the so-called Gynecologic Imaging and Report Data System (GI-RADS) for classifying adnexal masses.

EVIDENCE ACQUISITION

A search for studies reporting about the use of GI-RADS system for classifying adnexal masses from January 2009 to December 2021 was performed in Medline (Pubmed), Google Scholar, Scopus, Cochrane, and Web of Science databases. Pooled sensitivity, specificity, positive and negative likelihood ratios and diagnostic odd ratio (DOR) were calculated. Studies' quality was evaluated using QUADAS-2.

EVIDENCE SYNTHESIS

We identified 510 citations. Ultimately, 26 studies comprising 7350 masses were included. Mean prevalence of ovarian malignancy was 26%. The risk of bias was high in eight studies for domain "patient selection" and low for "index test," "reference test" domains for all studies. Overall, pooled estimated sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio and DOR of GI-RADS system for classifying adnexal masses were 94% (95% confidence interval [CI]=91-96%), 90% (95% CI=87-92%), 9.1 (95% CI=7.0-11.9), and 0.07 (95% CI=0.05-0.11), and 132 (95% CI=78-221), respectively. Heterogeneity was high for both sensitivity and specificity. Meta-regression showed that multiple observers and study's design explained this heterogeneity among studies.

CONCLUSIONS

GI-RADS system has a good diagnostic performance for classifying adnexal masses.

Can We Apply Snyder's Arthroscopic Classification to Ultrasound for Evaluating Rotator Cuff Tears? A Comparative Study with MR Arthrography

We aimed to demonstrate the applicability of Snyder's arthroscopic classification of rotator cuff tears (RCT) in shoulder ultrasound (US) and to compare it with MR arthrography (MRA). Forty-six patients (34 males; mean age:34 ± 14 years) underwent shoulder US and MRA. Two radiologists (R1 = 25 years of experience; R2 = 2 years of experience) assigned A1-4, B1-4, or C1-4 values depending on the extent of RCT in both US and MRA. Inter-reader intra-modality and intra-reader inter-modality agreement were calculated using Cohen's kappa coefficient. US sensitivity and specificity of both readers were calculated using MRA as the gold standard. Patients were divided into intact cuff vs. tears, mild (A1/B1) vs. moderate (A2-3/B2-3) tears, mild-moderate (A2/B2) vs. high-moderate (A3/B3) cuff tears, moderate (A2-3/B2-3) vs. advanced (A4/B4) and full-thickness (C) tears. The highest agreement values in inter-reader US evaluation were observed for mild-moderate vs. high-moderate RCT (K = 0.745), in inter-reader MRA evaluation for mild vs. moderate RCT (K = 0.821), in R1 inter-modality (US-MRA) for mild-moderate vs. high-moderate and moderate vs. advanced/full-thickness RCT (K = 1.000), in R2 inter-modality (US-MRA) for moderate vs. advanced/full-thickness RCT (K = 1.000). US sensitivity ranged from 88.89%(R1)-84.62%(R2) to 100% (both readers), while specificity from 77.78%(R1)-90.00%(R2) to 100% (both readers). Snyder's classification can be used in US to ensure the correct detection and characterization of RCT.

Professional Standards in Medical Ultrasound - EFSUMB Position Paper (Short Version) - General Aspects

This first position paper of the European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB) on professional standards presents a common position across the different medical professions within EFSUMB regarding optimal standards for the performing and reporting of ultrasound examinations by any professional ultrasound operator. It describes general aspects of professionality that ensure procedure quality, effectiveness, efficiency, and sustainability in virtually all application fields of medical ultrasound. Recommendations are given related to safety and indication of ultrasound examinations, requirements for examination rooms, structured examination, systematic reporting of results, and management, communication and archiving of ultrasound data. The print version of this article is a short version. The long version is published online.

Professional Standards in Medical Ultrasound - EFSUMB Position Paper (Long Version) - General Aspects

This first position paper of the European Federation of Societies for Ultrasound in Medicine and Biology (EFSUMB) on professional standards presents a common position across the different medical professions within EFSUMB regarding optimal standards for the performing and reporting of ultrasound examinations by any professional ultrasound operator. It describes general aspects of professionality that ensure procedure quality, effectiveness, efficiency, and sustainability in virtually all application fields of medical ultrasound. Recommendations are given related to safety and indication of ultrasound examinations, requirements for examination rooms, structured examination, systematic reporting of results, and management, communication and archiving of ultrasound data. The print version of this article is a short version. The long version is published online.