Hyun Jung Yoon

신윤경, et al. J Korean Soc Radiol. 2026 ;87:e7. https://doi.org/10.3348/jksr.2024.0103

임정수, et al. J Korean Soc Radiol. 2025 Mar;86(2):291-297. https://doi.org/10.3348/jksr.2024.0078

Background: Fluoroscopy-guided PTNB for fluoroscopy-identifiable lung lesions has been suggested as a useful method for the pathological diagnosis of lung lesions; however, it is lacking in accuracy and safety compared to CT-guided PTNB. Thus, we aimed to investigate the diagnostic accuracy and complications of fluoroscopy-guided percutaneous transthoracic needle biopsy (PTNB) with the aid of pre-procedural planning cone-beam computed tomography (CBCT) in order to take advantage of their respective strengths. Methods: A total of 255 fluoroscopy-guided PTNBs with the aid of planning CBCT were performed. Pre-procedural planning CBCT was conducted to calculate the shortest length from the skin puncture site to the margin of the target lesion for the needle trajectory. No intra-procedural CBCT was performed. The diagnostic performance of fluoroscopy-guided PTNB with the aid of planning CBCT was calculated. The prognostic factors for diagnostic failures and complications were evaluated using logistic regression analysis. Results: The accuracy, sensitivity, specificity, PPV, and NPV were 97.3%, 88.0%, 90.9%, 100%, and 62.5%, respectively. There were 29 diagnostic failures (11.8%), and the multivariable analysis showed that a longer lesion depth on CBCT and a shorter specimen length were each associated with diagnostic failure (p = 0.010 and 0.012, respectively). Complications occurred in 34 PTNBs (13.3%). The multivariable analysis showed that an increased total number of biopsies per lesion, a longer length of lung aeration via needle insertion, a smaller lesion size on CT imaging (≤20 mm), and the presence of an air bronchogram were associated with the occurrence of complications (p = 0.027, <0.001, 0.003, and 0.020, respectively). Conclusions: Excellent diagnostic accuracy was obtained by fluoroscopy-guided PTNB with the aid of planning CBCT. Compared to that of CT- or CBCT-guided PTNB, the procedure-related complication rate was acceptably low, but the radiation dose to patients could be potentially reduced.

여성희, et al. J Korean Soc Radiol. 2024 Mar;85(2):394-408. https://doi.org/10.3348/jksr.2023.0011

송재은, et al. J Korean Soc Radiol. 2023 Sep;84(5):1123-1133. https://doi.org/10.3348/jksr.2022.0152

원희수, et al. J Korean Soc Radiol. 2021 Sep;82:e131. https://doi.org/10.3348/jksr.2021.0084

Kim JH, et al. Korean J Radiol. 2021 Jan;22(1):131-138. https://doi.org/10.3348/kjr.2020.0116

Background: Because shape or irregularity along the tumor perimeter can result from interactions between the tumor and the surrounding parenchyma, there could be a difference in tumor growth rate according to tumor margin or shape. However, no attempt has been made to evaluate the correlation between margin or shape features and tumor growth.Methods: We evaluated 52 lung adenocarcinoma (ADC) patients who had at least two computed tomographic (CT) examinations before curative resection. Volume‐based doubling times (DTs) were calculated based on CT scans, and patients were divided into two groups according to the growth pattern (GP) of their ADCs (gradually growing tumors [GP I] vs. growing tumors with a temporary decrease in DT [GP II]). CT radiomic features reflecting margin characteristics were extracted, and radiomic features reflective of tumor DT were selected.Results: Among the 52 patients, 41 (78.8%) were assigned to GP I and 11 (21.2%) to GP II. Of the 94 radiomic features extracted, eccentricity, surface‐to‐volume ratio, LoG uniformity (σ = 3.5), and LoG skewness (σ = 0.5) were ultimately selected for tumor DT prediction. Selected radiomic features in GP I were surface‐to‐volume ratio, contrast, LoG uniformity (σ = 3.5), and LoG skewness (σ = 0.5), similar to those for total subjects, whereas the radiomic features in GP II were solidity, energy, and busyness.Conclusions: This study demonstrated the potential of margin‐related radiomic features to predict tumor DT in lung ADCs.Key points: Significant findings of the study: We found a relationship between margin‐related radiomic features and tumor doubling time.What this study adds: Margin‐related radiomic features can potentially be used as noninvasive biomarkers to predict tumor doubling time in lung adenocarcinoma and inform treatment strategies.

김주희, et al. J Korean Soc Radiol. 2020 May;81(3):746-752. https://doi.org/10.3348/jksr.2020.81.3.746