Collaborative Enhancement of Consistency and Accuracy in US Diagnosis of Thyroid Nodules Using Large Language Models.

Background Large language models (LLMs) hold substantial promise for medical imaging interpretation. However, there is a lack of studies on their feasibility in handling reasoning questions associated with medical diagnosis. Purpose To investigate the viability of leveraging three publicly available LLMs to enhance consistency and diagnostic accuracy in medical imaging based on standardized reporting, with pathology as the reference standard. Materials and Methods US images of thyroid nodules with pathologic results were retrospectively collected from a tertiary referral hospital between July 2022 and December 2022 and used to evaluate malignancy diagnoses generated by three LLMs-OpenAI's ChatGPT 3.5, ChatGPT 4.0, and Google's Bard. Inter- and intra-LLM agreement of diagnosis were evaluated. Then, diagnostic performance, including accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC), was evaluated and compared for the LLMs and three interactive approaches: human reader combined with LLMs, image-to-text model combined with LLMs, and an end-to-end convolutional neural network model. Results A total of 1161 US images of thyroid nodules (498 benign, 663 malignant) from 725 patients (mean age, 42.2 years ± 14.1 [SD]; 516 women) were evaluated. ChatGPT 4.0 and Bard displayed substantial to almost perfect intra-LLM agreement (κ range, 0.65-0.86 [95% CI: 0.64, 0.86]), while ChatGPT 3.5 showed fair to substantial agreement (κ range, 0.36-0.68 [95% CI: 0.36, 0.68]). ChatGPT 4.0 had an accuracy of 78%-86% (95% CI: 76%, 88%) and sensitivity of 86%-95% (95% CI: 83%, 96%), compared with 74%-86% (95% CI: 71%, 88%) and 74%-91% (95% CI: 71%, 93%), respectively, for Bard. Moreover, with ChatGPT 4.0, the image-to-text-LLM strategy exhibited an AUC (0.83 [95% CI: 0.80, 0.85]) and accuracy (84% [95% CI: 82%, 86%]) comparable to those of the human-LLM interaction strategy with two senior readers and one junior reader and exceeding those of the human-LLM interaction strategy with one junior reader. Conclusion LLMs, particularly integrated with image-to-text approaches, show potential in enhancing diagnostic medical imaging. ChatGPT 4.0 was optimal for consistency and diagnostic accuracy when compared with Bard and ChatGPT 3.5. © RSNA, 2024 Supplemental material is available for this article.

Outcomes after hepatectomy of patients with positive HBcAb Non-B Non-C hepatocellular carcinoma compared to overt hepatitis B virus hepatocellular carcinoma.

PURPOSE: Hepatitis B core antibody (HBcAb) positivity is regarded as a sensitive marker for occult and prior hepatitis B virus (HBV) infection. However, the prognosis of patients with HBcAb-positive in non-B, non-C hepatocellular carcinoma (NBNC-HCC) remains unclear. The study aimed to compare the clinicopathological characteristics of patients with HBcAb-positive NBNC-HCC to those with overt HBV (hepatitis B surface antigen positive) HCC. METHODS: 306 HCC patients underwent hepatectomy were divided into two groups: an overt HBV-HCC group and HBcAb-positive NBNC-HCC group. Then patients were analyzed using propensity score matching (PSM) to reduce selection bias. Clinicopathological characteristics and survival outcomes were compared between the two groups. Univariate and multivariate analysis for risk factors were also evaluated. RESULTS: HBcAb-positive NBNC-HCC group showed comparable survival outcomes to the overt HBV-HCC group (3-year overall survival rates 66% vs 62%, 69% vs 53%; 3-year recurrence-free survival rates 49% vs 40%, 47% vs 37%; P > 0.05) before and after PSM. Patients with HBcAb-positive NBNC-HCC were older, had more complications, higher proportions of vascular invasion, and larger tumor sizes but lower proportions of cirrhosis, elevated alanine aminotransferase and prothrombin time. CONCLUSIONS: HBcAb-positive NBNC-HCC group had more advanced tumors, but their prognosis was relatively comparable to that of the other group. Therefore, we believe that screening is also necessary in HBcAb-positive patients for early detection of HCC, especially in the elderly.