Correlation of fine needle aspiration cytology with histopathological diagnosis in assessing breast lumps at a tertiary care hospital

George, Greeshma Ann; Antony, Philips

doi:10.18203/2320-6012.ijrms20184440

Cited by 2 publications

(1 citation statement)

References 8 publications

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“…In evaluating the application of fine-needle aspiration in diagnosing breast lumps, GPT-3.5 provided recommendations that were somewhat general and did not adequately reflect advancements in breast lump diagnostic strategies. In particular, in certain cases, subsequent treatment plans can be directly formulated based on radiological examinations rather than solely relying on fine-needle aspiration for a definitive diagnosis 18 . Moreover, with the advancement of medical technology, the utilization rate of Fine-Needle Aspiration Cytology (FNAC) in breast cancer diagnosis has declined 19 .…”

Section: Discussionmentioning

confidence: 99%

Evaluation of large language models in breast cancer clinical scenarios: a comparative analysis based on ChatGPT-3.5, ChatGPT-4.0, and Claude2

Deng,

Wang,

Yangzhang

et al. 2024

International Journal of Surgery

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Background Large language models (LLMs) have garnered significant attention in the AI domain owing to their exemplary context recognition and response capabilities. However, the potential of LLMs in specific clinical scenarios, particularly in breast cancer diagnosis, treatment, and care, has not been fully explored. This study aimed to compare the performances of three major LLMs in the clinical context of breast cancer. Methods In this study, clinical scenarios designed specifically for breast cancer were segmented into five pivotal domains (nine cases): assessment and diagnosis, treatment decision-making, post-operative care, psychosocial support, and prognosis and rehabilitation. The LLMs were used to generate feedback for various queries related to these domains. For each scenario, a panel of five breast cancer specialists, each with over a decade of experience, evaluated the feedback from LLMs. They assessed feedback concerning LLMs in terms of their quality, relevance, and applicability. Results There was a moderate level of agreement among the raters (Fleiss’ kappa=0.345, P<0.05). Comparing the performance of different models regarding response length, GPT-4.0 and GPT-3.5 provided relatively longer feedback than Claude2. Furthermore, across the nine case analyses, GPT-4.0 significantly outperformed the other two models in average quality, relevance, and applicability. Within the five clinical areas, GPT-4.0 markedly surpassed GPT-3.5 in the quality of the other four areas and scored higher than Claude2 in tasks related to psychosocial support and treatment decision-making. Conclusion This study revealed that in the realm of clinical applications for breast cancer, GPT-4.0 showcases not only superiority in terms of quality and relevance but also demonstrates exceptional capability in applicability, especially when compared to GPT-3.5. Relative to Claude2, GPT-4.0 holds advantages in specific domains. With the expanding use of LLMs in the clinical field, ongoing optimization and rigorous accuracy assessments are paramount.

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Section: Discussionmentioning

confidence: 99%

Evaluation of large language models in breast cancer clinical scenarios: a comparative analysis based on ChatGPT-3.5, ChatGPT-4.0, and Claude2

Deng,

Wang,

Yangzhang

et al. 2024

International Journal of Surgery

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Assessing the Accuracy of Ultrasonography and Biopsy Necessity in the Management of Breast Lumps in Women Less than 40 Years

Itanyi,

Chukwuegbo,

Okafor

et al. 2024

J West Afr Coll Surg

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Background: Following recommended guidelines, palpable breast lumps in young women should be subjected to clinical–radiologic evaluation and tissue diagnosis where necessary. However, in our local practice, most benign breast lumps are also subjected to excision biopsy. Ultrasonography is the modality of choice in the evaluation of palpable breast lumps in young women. Aim: This study aims to determine the accuracy of ultrasonography and the necessity of tissue biopsy in the management of palpable breast lumps in women less than 40 years of age and to determine lesions that can safely be managed conservatively based on histological diagnosis. Materials and Methods: This was a prospective cross-sectional study of 87 adult females who had breast US and biopsy for palpable breast lumps in a tertiary healthcare center over a period of 10 months (July 2020–May 2021). Results: The age range of the women was 18–39 years (mean 27.9 ± 7.09 years). Benign lesions were noted in 86.2% of patients. No malignancy was detected in women < 25 years. Ultrasonography had sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 100%, 93.4%, 70.6%, 100%, and 94.3%, respectively, in differentiating benign from malignant breast lumps following tissue diagnosis. Conclusion: Ultrasonography and tissue biopsy are vital in the evaluation of breast lumps in women less than 40 years of age. Most (86.2%) of the lumps were benign, and no malignancy was detected in women < 25 years. The high accuracy of ultrasonography in distinguishing benign from malignant lesions suggests the need for conservative management of benign lumps in young women.

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Correlation of fine needle aspiration cytology with histopathological diagnosis in assessing breast lumps at a tertiary care hospital

Cited by 2 publications

References 8 publications

Evaluation of large language models in breast cancer clinical scenarios: a comparative analysis based on ChatGPT-3.5, ChatGPT-4.0, and Claude2

Evaluation of large language models in breast cancer clinical scenarios: a comparative analysis based on ChatGPT-3.5, ChatGPT-4.0, and Claude2

Assessing the Accuracy of Ultrasonography and Biopsy Necessity in the Management of Breast Lumps in Women Less than 40 Years

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