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PURPOSE: To evaluate the performance of Microsoft Bing with ChatGPT-4 technology in analyzing abdominal computed tomography (CT) and magnetic resonance images (MRI). METHODS: A comparative and descriptive analysis was conducted using the institutional picture archiving and communication systems. A total of 80 abdominal images (44 CT, 36 MRI) that showed various entities affecting the abdominal structures were included. Microsoft Bing's interpretations were compared with the impressions of radiologists in terms of recognition of the imaging modality, identification of the imaging planes (axial, coronal, and sagittal), sequences (in the case of MRI), contrast media administration, correct identification of the anatomical region depicted in the image, and detection of abnormalities. RESULTS: Microsoft Bing detected that the images were CT scans with 95.4% accuracy (42/44) and that the images were MRI scans with 86.1% accuracy (31/36). However, it failed to detect one CT image (2.3%) and misidentified another CT image as an MRI (2.3%). On the other hand, it also misidentified four MRI as CT images (11.1%) and one as an X-ray (2.7%). Bing achieved an 83.75% success rate in correctly identifying abdominal regions, with 90% accuracy for CT scans (40/44) and 77.7% for MRI scans (28/36). Concerning the identification of imaging planes, Bing achieved a success rate of 95.4% for CT images and 83.3% for MRI. Regarding the identification of MRI sequences (T1-weighted and T2-weighted), the success rate was 68.75%. In the identification of the use of contrast media for CT scans, the success rate was 64.2%. Bing detected abnormalities in 35% of the images but achieved a correct interpretation rate of 10.7% for the definite diagnosis. CONCLUSION: While Microsoft Bing, leveraging ChatGPT-4 technology, demonstrates proficiency in basic task identification on abdominal CT and MRI, its inability to reliably interpret abnormalities highlights the need for continued refinement to enhance its clinical applicability. CLINICAL SIGNIFICANCE: The contribution of large language models (LLMs) to the diagnostic process in radiology is still being explored. However, with a comprehensive understanding of their capabilities and limitations, LLMs can significantly support radiologists during diagnosis and improve the overall efficiency of abdominal radiology practices. Acknowledging the limitations of current studies related to ChatGPT in this field, our work provides a foundation for future clinical research, paving the way for more integrated and effective diagnostic tools.
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OBJECTIVES: This study aimed to investigate the correlation between testicular shear wave elastography (SWE) values and semen analysis results in men with infertility. METHODS: This was a retrospective case-control study. Patients were categorized as normal, abnormal, or azoospermic based on sperm analysis results. Testicular volume was measured using B-mode ultrasonography using the Lambert formula. Subsequently, 40-80 regions of interest measuring 1.5 × 1.5 mm were manually positioned in both testicles based on their size, and two-dimensional SWE was applied through virtual touch imaging quantification software. RESULTS: The patients had a mean age of 33.79 ± 6.3 years, with semen analysis revealing normal results in 15 patients (22.4%), pathological findings in 35 patients (52.2%), and azoospermia in 17 patients (25.4%). Right, left, total, and mean testicular volumes were significantly lower in patients with azoospermia compared to those in both normal and impaired semen parameters (P < .05). Conversely, testicular elastography scores were higher in patients with azoospermia than in the other groups (P < .05). The significant negative correlation between volume and elastographic findings remained independent of age (r = 0.4, P < .001). The accuracy rates for detecting impaired semen parameters and azoospermia were 94.3% and 94.1%, respectively, after considering factors such as age, testicular volume (right/left/total), and elastography (right/left/total). Notably, the total mean elastography score ranked first, with 100% in the independent normalized importance distribution of these variables. CONCLUSION: SWE can be used effectively alone or in combination with other diagnostic tools to evaluate histopathological changes in the testicles of male patients with infertility.