OBJECTIVE: To determine if measurement of the diameter of the solid component in subsolid nodules (SSNs) on low-dose unenhanced chest computed tomography (CT) is as accurate as on standard-dose enhanced CT in prediction of pathological size of invasive component of lung adenocarcinoma. MATERIALS AND METHODS: From February 2012 to October 2015, 114 SSNs were identified in 105 patients that underwent low-dose unenhanced and standard-dose enhanced CT pre-operatively. Three radiologists independently measured the largest diameter of the solid component. Intraclass correlation coefficients (ICCs) were used to assess inter-reader agreement. We estimated measurement differences between the size of solid component and that of invasive component. We measured diagnostic accuracy of the prediction of invasive adenocarcinoma using a size criterion of a solid component ≥ 6 mm, and compared them using a generalized linear mixed model. RESULTS: Inter-reader agreement was excellent (ICC, 0.84.0.89). The mean ± standard deviation of absolute measurement differences between the solid component and invasive component was 4 ± 4 mm in low-dose unenhanced CT and 5 ± 4 mm in standard-dose enhanced CT. Diagnostic accuracy was 81.3% (95% confidence interval, 76.7.85.3%) in low-dose unenhanced CT and 76.6% (71.8.81.0%) in standard-dose enhanced CT, with no statistically significant difference (p = 0.130). CONCLUSION: Measurement of the diameter of the solid component of SSNs on low-dose unenhanced chest CT was as accurate as on standard-dose enhanced CT for predicting the invasive component. Thus, low-dose unenhanced CT may be used safely in the evaluation of patients with SSNs.
Adenocarcinoma* ; Humans ; Lung* ; Thorax* ; Tomography, X-Ray Computed

Large language models (LLMs) such as ChatGPT have garnered considerable interest for their potential to aid non-native English-speaking researchers. These models can function as personal, round-the-clock English tutors, akin to how Prometheus in Greek mythology bestowed fire upon humans for their advancement. LLMs can be particularly helpful for non-native researchers in writing the Introduction and Discussion sections of manuscripts, where they often encounter challenges.However, using LLMs to generate text for research manuscripts entails concerns such as hallucination, plagiarism, and privacy issues; to mitigate these risks, authors should verify the accuracy of generated content, employ text similarity detectors, and avoid inputting sensitive information into their prompts. Consequently, it may be more prudent to utilize LLMs for editing and refining text rather than generating large portions of text. Journal policies concerning the use of LLMs vary, but transparency in disclosing artificial intelligence tool usage is emphasized. This paper aims to summarize how LLMs can lower the barrier to academic writing in English, enabling researchers to concentrate on domain-specific research, provided they are used responsibly and cautiously.

Although the causes of hypertension are usually unknown, about 10% of the cases occur secondary to specific etiologies, which are often treatable. Common categories of secondary hypertension include renal parenchymal disease, renovascular stenosis, vascular and endocrinologic disorders. For diseases involving the renal parenchyma and adrenal glands, ultrasonography (US), computed tomography (CT) or magnetic resonance (MR) imaging is recommended. For renovascular stenosis and vascular disorders, Doppler US, conventional or noninvasive (CT or MR) angiography is an appropriate modality. Nuclear imaging can be useful in the differential diagnosis of endocrine causes. Radiologists should understand the role of each imaging modality and its typical findings in various causes of secondary hypertension. This article focuses on appropriate imaging approaches in accordance with the categorized etiologies leading to hypertension.
Adrenal Glands ; Angiography ; Constriction, Pathologic ; Diagnosis, Differential ; Diagnostic Imaging ; Humans ; Hypertension* ; Magnetic Resonance Imaging ; Ultrasonography