Decoding medical jargon: The use of AI language models (ChatGPT-4, BARD, microsoft copilot) in radiology reports.

OBJECTIVE: Evaluate Artificial Intelligence (AI) language models (ChatGPT-4, BARD, Microsoft Copilot) in simplifying radiology reports, assessing readability, understandability, actionability, and urgency classification. METHODS: This study evaluated the effectiveness of these AI models in translating radiology reports into patient-friendly language and providing understandable and actionable suggestions and urgency classifications. Thirty radiology reports were processed using AI tools, and their outputs were assessed for readability (Flesch Reading Ease, Flesch-Kincaid Grade Level), understandability (PEMAT), and the accuracy of urgency classification. ANOVA and Chi-Square tests were performed to compare the models' performances. RESULTS: All three AI models successfully transformed medical jargon into more accessible language, with BARD showing superior readability scores. In terms of understandability, all models achieved scores above 70%, with ChatGPT-4 and BARD leading (p < 0.001, both). However, the AI models varied in accuracy of urgency recommendations, with no significant statistical difference (p = 0.284). CONCLUSION: AI language models have proven effective in simplifying radiology reports, thereby potentially improving patient comprehension and engagement in their health decisions. However, their accuracy in assessing the urgency of medical conditions based on radiology reports suggests a need for further refinement. PRACTICE IMPLICATIONS: Incorporating AI in radiology communication can empower patients, but further development is crucial for comprehensive and actionable patient support.

Assessing the Responses of Large Language Models (ChatGPT-4, Gemini, and Microsoft Copilot) to Frequently Asked Questions in Breast Imaging: A Study on Readability and Accuracy.

Background Large language models (LLMs), such as ChatGPT-4, Gemini, and Microsoft Copilot, have been instrumental in various domains, including healthcare, where they enhance health literacy and aid in patient decision-making. Given the complexities involved in breast imaging procedures, accurate and comprehensible information is vital for patient engagement and compliance. This study aims to evaluate the readability and accuracy of the information provided by three prominent LLMs, ChatGPT-4, Gemini, and Microsoft Copilot, in response to frequently asked questions in breast imaging, assessing their potential to improve patient understanding and facilitate healthcare communication. Methodology We collected the most common questions on breast imaging from clinical practice and posed them to LLMs. We then evaluated the responses in terms of readability and accuracy. Responses from LLMs were analyzed for readability using the Flesch Reading Ease and Flesch-Kincaid Grade Level tests and for accuracy through a radiologist-developed Likert-type scale. Results The study found significant variations among LLMs. Gemini and Microsoft Copilot scored higher on readability scales (p < 0.001), indicating their responses were easier to understand. In contrast, ChatGPT-4 demonstrated greater accuracy in its responses (p < 0.001). Conclusions While LLMs such as ChatGPT-4 show promise in providing accurate responses, readability issues may limit their utility in patient education. Conversely, Gemini and Microsoft Copilot, despite being less accurate, are more accessible to a broader patient audience. Ongoing adjustments and evaluations of these models are essential to ensure they meet the diverse needs of patients, emphasizing the need for continuous improvement and oversight in the deployment of artificial intelligence technologies in healthcare.

Evaluation of the relationship between end-tidal carbon dioxide level and heart failure classification.

OBJECTIVE: Heart failure is a disease with cardiac dysfunction, and its morbidity and mortality are associated with the degree of dysfunction. The New York Heart Association classifies the heart failure stages based on the severity of symptoms and physical activity. End-tidal carbon dioxide refers to the level of carbon dioxide that a person exhales with each breath. End-tidal carbon dioxide levels can be used in many clinical conditions such as heart failure, asthma, and chronic obstructive pulmonary disease. The aim of the study was to reveal the relationship between end-tidal carbon dioxide levels and the New York Heart Association classification of heart failure stages. METHODS: This study was conducted at Kahramanmaras Sütçü Imam University Faculty of Medicine Adult Emergency Department between 01/03/2019 and 01/09/2019. A total of 80 patients who presented to the emergency department with a history of heart failure or were diagnosed with heart failure during admission were grouped according to the New York Heart Association classification of heart failure stages. The laboratory parameters, ejection fraction values, and end-tidal carbon dioxide levels of the patients were measured and recorded in the study forms. RESULTS: End-tidal carbon dioxide levels and ejection fraction values were found to be significantly lower in the stage 4 group compared to the other groups. Furthermore, pro-B-type natriuretic peptide (BNP) values were found to be significantly higher in stage 4 group compared to the other groups. CONCLUSION: It was concluded that end-tidal carbon dioxide levels could be used together with pro-BNP and ejection fraction values in determining the severity of heart failure.

The Potential Role of Peritumoral Apparent Diffusion Coefficient Evaluation in Differentiating Glioblastoma and Solitary Metastatic Lesions of the Brain.

OBJECTIVE: Differentiating glioblastoma (GBM) and solitary metastasis is not always possible using conventional magnetic resonance imaging (MRI) techniques. In conventional brain MRI, GBM and brain metastases are lesions with mostly similar imaging findings. In this study, we investigated whether apparent diffusion coefficient (ADC) ratios, ADC gradients, and minimum ADC values in the peritumoral edema tissue can be used to discriminate between these two tumors. METHODS: This retrospective study was approved by the local institutional review board with a waiver of written informed consent. Prior to surgical and medical treatment, conventional brain MRI and diffusion-weighted MRI (b = 0 and b = 1000) images were taken from 43 patients (12 GBM and 31 solitary metastasis cases). Quantitative ADC measurements were performed on the peritumoral tissue from the nearest segment to the tumor (ADC1), the middle segment (ADC2), and the most distant segment (ADC3). The ratios of these three values were determined proportionally to calculate the peritumoral ADC ratios. In addition, these three values were subtracted from each other to obtain the peritumoral ADC gradients. Lastly, the minimum peritumoral and tumoral ADC values, and the quantitative ADC values from the normal-appearing ipsilateral white matter, contralateral white matter, and ADC values from cerebrospinal fluid (CSF) were recorded. RESULTS: For the differentiation of GBM and solitary metastasis, ADC3 / ADC1 was the most powerful parameter with a sensitivity of 91.7% and specificity of 87.1% at the cut-off value of 1.105 (p < 0.001), followed by ADC3 / ADC2 with a cut-off value of 1.025 (p = 0.001), sensitivity of 91.7%, and specificity of 74.2%. The cut-off, sensitivity and specificity of ADC2 / ADC1 were 1.055 (p = 0.002), 83.3%, and 67.7%, respectively. For ADC3 - ADC1, the cut-off value, sensitivity, and specificity were calculated as 150 (p < 0.001), 91.7%, and 83.9%, respectively. ADC3 - ADC2 had a cutoff value of 55 (p = 0.001), sensitivity of 91.7%, and specificity of 77.4, whereas ADC2 - ADC1 had a cut-off value of 75 (p = 0.003), sensitivity of 91.7%, and specificity of 61.3%. Among the remaining parameters, only the ADC3 value successfully differentiated between GBM and metastasis (GBM 1802.50 ± 189.74 vs. metastasis 1634.52 ± 212.65, p = 0.022). CONCLUSION: The integration of the evaluation of peritumoral ADC ratio and ADC gradient into conventional MR imaging may provide valuable information for differentiating GBM from solitary metastatic lesions.

Comparison Between the Maximum Standard Uptake Value and the Ratio of Lymph Node to Primary Tumor Attenuation in Head and Neck Cancers: A Prospective Study.

OBJECTIVE: The study aimed to investigate the relationship between the ratio of lymph node attenuation to primary lesion attenuation on contrast-enhanced CT and the PET/CT standard uptake value (SUVmax) in head and neck squamous cell cancer (HNSCC). METHODS: Volunteers with advanced-stage, histopathologically proven HNSCC, indicated to have radiotherapy/chemoradiotherapy, were evaluated for CT and PET/CT for radiotherapy planning. The attenuation and SUVmax of the primary lesion and the largest, possibly metastatic lymph node, and the round index and volume of the lymph node were calculated. The relationship between lymph node/primary lesion attenuation and SUVmax ratios was investigated. The differences in CT findings between the SUVmax < and ≥3 groups were examined. RESULTS: Thirty-two cases with adequate diagnostic quality were studied. There was a very strong positive correlation between the primary lesion and lymph node attenuation (r=0.817, p<0.001), a strong correlation between the lymph node volume and SUVmax (r=0.681, p<0.001), and a moderate negative correlation between lymph node/primary lesion SUVmax and attenuation (r=-0.503, p=0.004). In patients with ≥3 SUVmax, lymph node volume and lymph node/primary lesion SUVmax were significantly higher, and the attenuation ratio was close to 1 (PPV 94.1, 86.3%, respectively). CONCLUSION: In HNSCC, the lymph node/primary lesion attenuation ratio can be used instead of SUVmax if supported by other conventional CT findings. Metastasis should be considered if lymph node attenuation is similar to primary mass attenuation and excluded if higher. CT attenuation rate can be used as a supportive finding if PET/CT cannot be performed or lymph node SUVmax is close to the acceptable cut-off for metastasis.

Prevalence of elastofibroma dorsi on CT: Is it really an uncommon entity?

OBJECTIVE: The aim of this study was to determine the prevalence, demographic data of elastofibroma dorsi (ED) in adult population who had undergone chest CT examination and to discuss clinical, and radiological presentations, and treatment options of ED. METHODS: We retrospectively reviewed 4074 chest CT examinations for ED from July 2014 to April 2015. Lesion size, side, and patient demographics were analyzed for positive cases of ED. The initial radiology reports of patients with ED were also reviewed. RESULTS: Of the 4074 patients, 111 patients (2.73%) (77 women and 34 men; mean age: 68.2 years; range: 35-91 years) had a total of 168 ED. The females had a 1.96 -fold higher prevalence of ED than the males (OR, 1.96; 95% CI, 1.481-2.59). The mean lesion thickness was found to be significantly greater in the female patients compared with the male patients (p = 0.001). The prevalence of the disease was estimated to be 4.98 times higher in patients aged 65 years or older (CI 95%, 3.25-7.36). In 111 ED patients, the lesions were only noted in 9 patients' initial radiology report. CONCLUSION: Here, we present a prevalence study with the largest population in the literature concerning ED. Our study shows that ED is not as uncommon as previously thought and should be especially suspected in females and older age groups. LEVEL OF EVIDENCE: Level IV, Diagnostic Study.

A Rare Cause of Acute Abdomen: Diagnosis and Management of Adult Colonic Intussusception.

Intussusception in adults is very rarely seen, and this cause acute abdomen. A computed tomography (CT) scan, clinical suspicion, history, and a physical examination are important for the diagnosis. We present two cases of colonic intussusceptions induced by lipoma. The cases had similar locations, diagnoses, and management. Both lipomas were located close to the cecum in the ascending colon, and a right segmental colon resection was performed in both cases. The follow-up of both cases was uneventful. Although benign lesions can cause colonic intussusception, the high incidence of malignancy in colonic lesions should always be considered. Therefore, oncologic surgical procedures should be applied. The definitive diagnosis can be made by histopathology. HOW TO CITE THIS ARTICLE: Sertkaya M, Emre A, Pircanoglu EM, Yazar FM, Tepe M, Cengiz E, Isler A, Vicdan H. A Rare cause of Acute Abdomen: Diagnosis and Management of Adult Colonic Intussusception. Euroasian J Hepato-Gastroenterol 2016;6(2):179-182.

Variations in the popliteal artery branching in 342 patients studied with peripheral CT angiography using 64-MDCT.

PURPOSE: The objective of this study was to assess the utility of peripheral computed tomography angiography (CTA) using 64-multidetector computed tomography (64-MDCT) in the detection of variations in branching patterns of the popliteal artery. MATERIALS AND METHODS: The peripheral CTAs of 742 limbs in 342 patients who underwent peripheral CTA using 64-MDCT of the lower extremity due to various reasons were retrospectively reviewed. The anatomical variations in popliteal artery branching were assessed in 636 limbs from the same cohort of patients. RESULTS: Five hundred fifty-three (87 %) limbs had the usual branching pattern (type IA). Variations in the branching pattern of the popliteal artery were seen in 83 (13 %) limbs. The most common anatomical variation was trifurcation of the popliteal artery in 27 (4.2 %) limbs, with anterior tibial, posterior tibial, and peroneal arteries arising together with no true tibioperoneal trunk (type IB). CONCLUSION: The presence of variations in the anatomy of the popliteal artery could be of radiological and surgical importance in orthopedic interventions and various vascular surgery procedures. Peripheral CTA using MDCT is a suitable imaging modality for noninvasive evaluation of lower extremity arteries, and it may become the preferred method for evaluating variations in popliteal artery branching.