• Journal of Chest Surgery
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• v.57 no.2
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• pp.128-135
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• 2024

Background: This retrospective study aimed to determine the treatment patterns and the surgical and oncologic outcomes after completion lobectomy (CL) in patients with locoregionally recurrent stage I non-small cell lung cancer (NSCLC) who previously underwent sublobar resection. Methods: Data from 36 patients who initially underwent sublobar resection for clinical, pathological stage IA NSCLC and experienced locoregional recurrence between 2008 and 2016 were analyzed. Results: Thirty-six (3.6%) of 1,003 patients who underwent sublobar resection for NSCLC experienced locoregional recurrence. The patients' median age was 66.5 (range, 44-77) years at the initial operation, and 28 (77.8%) patients were men. Six (16.7%) patients underwent segmentectomy and 30 (83.3%) underwent wedge resection as the initial operation. The median follow-up from the initial operation was 56 (range, 9-150) months. Ten (27.8%) patients underwent CL, 22 (61.1%) underwent non-surgical treatments (chemotherapy, radiation, concurrent chemoradiation therapy), and 4 (11.1%) did not receive treatment or were lost to follow-up after recurrence. Patients who underwent CL experienced no significant complications or deaths. The median follow-up time after CL was 64.5 (range, 19-93) months. The 5-year overall survival (OS) and post-recurrence survival (PRS) were higher in the surgical group than in the non-surgical (p<0.001) and no-treatment groups (p<0.001). Conclusion: CL is a technically demanding but safe procedure for locoregionally recurrent stage I NSCLC after sublobar resection. Patients who underwent CL had better OS and PRS than patients who underwent non-surgical treatments or no treatments; however, a larger cohort study and long-term surveillance are necessary.

• Korean Journal of Radiology
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• v.25 no.3
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• pp.243-256
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• 2024

Objective: We aimed to investigate whether 2-[¹⁸F]fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (2-[¹⁸F]FDG PET/CT) can aid in evaluating the risk of malignancy in ampullary tumors detected by endoscopy. Materials and Methods: This single-center retrospective cohort study analyzed 155 patients (79 male, 76 female; mean age, 65.7 ± 12.7 years) receiving 2-[¹⁸F]FDG PET/CT for endoscopy-detected ampullary tumors 5-87 days (median, 7 days) after the diagnostic endoscopy between June 2007 and December 2020. The final diagnosis was made based on histopathological findings. The PET imaging parameters were compared with clinical data and endoscopic features. A model to predict the risk of malignancy, based on PET, endoscopy, and clinical findings, was generated and validated using multivariable logistic regression analysis and an additional bootstrapping method. The final model was compared with standard endoscopy for the diagnosis of ampullary cancer using the DeLong test. Results: The mean tumor size was 17.1 ± 7.7 mm. Sixty-four (41.3%) tumors were benign, and 91 (58.7%) were malignant. Univariable analysis found that ampullary neoplasms with a blood-pool corrected peak standardized uptake value in earlyphase scan (SUVe) ≥ 1.7 were more likely to be malignant (odds ratio [OR], 16.06; 95% confidence interval [CI], 7.13-36.18; P < 0.001). Multivariable analysis identified the presence of jaundice (adjusted OR [aOR], 4.89; 95% CI, 1.80-13.33; P = 0.002), malignant traits in endoscopy (aOR, 6.80; 95% CI, 2.41-19.20; P < 0.001), SUVe ≥ 1.7 in PET (aOR, 5.43; 95% CI, 2.00-14.72; P < 0.001), and PET-detected nodal disease (aOR, 5.03; 95% CI, 1.16-21.86; P = 0.041) as independent predictors of malignancy. The model combining these four factors predicted ampullary cancers better than endoscopic diagnosis alone (area under the curve [AUC] and 95% CI: 0.925 [0.874-0.956] vs. 0.815 [0.732-0.873], P < 0.001). The model demonstrated an AUC of 0.921 (95% CI, 0.816-0.967) in candidates for endoscopic papillectomy. Conclusion: Adding 2-[¹⁸F]FDG PET/CT to endoscopy can improve the diagnosis of ampullary cancer and may help refine therapeutic decision-making, particularly when contemplating endoscopic papillectomy.

• Korean Journal of Radiology
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• v.25 no.1
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• pp.43-54
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• 2024

Objective: To evaluate the added value of diffusion-weighted imaging (DWI)-based quantitative parameters to distinguish uterine sarcomas from atypical leiomyomas on preoperative magnetic resonance imaging (MRI). Materials and Methods: A total of 138 patients (age, 43.7 ± 10.3 years) with uterine sarcoma (n = 44) and atypical leiomyoma (n = 94) were retrospectively collected from four institutions. The cohort was randomly divided into training (84/138, 60.0%) and validation (54/138, 40.0%) sets. Two independent readers evaluated six qualitative MRI features and two DWI-based quantitative parameters for each index tumor. Multivariable logistic regression was used to identify the relevant qualitative MRI features. Diagnostic classifiers based on qualitative MRI features alone and in combination with DWI-based quantitative parameters were developed using a logistic regression algorithm. The diagnostic performance of the classifiers was evaluated using a cross-table analysis and calculation of the area under the receiver operating characteristic curve (AUC). Results: Mean apparent diffusion coefficient value of uterine sarcoma was lower than that of atypical leiomyoma (mean ± standard deviation, 0.94 ± 0.30 10^-3 mm²/s vs. 1.23 ± 0.25 10^-3 mm²/s; P < 0.001), and the relative contrast ratio was higher in the uterine sarcoma (8.16 ± 2.94 vs. 4.19 ± 2.66; P < 0.001). Selected qualitative MRI features included ill-defined margin (adjusted odds ratio [aOR], 17.9; 95% confidence interval [CI], 1.41-503, P = 0.040), intratumoral hemorrhage (aOR, 27.3; 95% CI, 3.74-596, P = 0.006), and absence of T2 dark area (aOR, 83.5; 95% CI, 12.4-1916, P < 0.001). The classifier that combined qualitative MRI features and DWI-based quantitative parameters showed significantly better performance than without DWI-based parameters in the validation set (AUC, 0.92 vs. 0.78; P < 0.001). Conclusion: The addition of DWI-based quantitative parameters to qualitative MRI features improved the diagnostic performance of the logistic regression classifier in differentiating uterine sarcomas from atypical leiomyomas on preoperative MRI.

• Korean Journal of Radiology
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• v.23 no.10
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• pp.1009-1018
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• 2022

Objective: This study aimed to investigate the feasibility of using artificial intelligence (AI) to identify normal chest radiography (CXR) from the worklist of radiologists in a health-screening environment. Materials and Methods: This retrospective simulation study was conducted using the CXRs of 5887 adults (mean age ± standard deviation, 55.4 ± 11.8 years; male, 4329) from three health screening centers in South Korea using a commercial AI (Lunit INSIGHT CXR3, version 3.5.8.8). Three board-certified thoracic radiologists reviewed CXR images for referable thoracic abnormalities and grouped the images into those with visible referable abnormalities (identified as abnormal by at least one reader) and those with clearly visible referable abnormalities (identified as abnormal by at least two readers). With AI-based simulated exclusion of normal CXR images, the percentages of normal images sorted and abnormal images erroneously removed were analyzed. Additionally, in a random subsample of 480 patients, the ability to identify visible referable abnormalities was compared among AI-unassisted reading (i.e., all images read by human readers without AI), AI-assisted reading (i.e., all images read by human readers with AI assistance as concurrent readers), and reading with AI triage (i.e., human reading of only those rendered abnormal by AI). Results: Of 5887 CXR images, 405 (6.9%) and 227 (3.9%) contained visible and clearly visible abnormalities, respectively. With AI-based triage, 42.9% (2354/5482) of normal CXR images were removed at the cost of erroneous removal of 3.5% (14/405) and 1.8% (4/227) of CXR images with visible and clearly visible abnormalities, respectively. In the diagnostic performance study, AI triage removed 41.6% (188/452) of normal images from the worklist without missing visible abnormalities and increased the specificity for some readers without decreasing sensitivity. Conclusion: This study suggests the feasibility of sorting and removing normal CXRs using AI with a tailored cut-off to increase efficiency and reduce the workload of radiologists.

• Korean Journal of Radiology
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• v.24 no.9
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• pp.827-837
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• 2023

Objective: To investigate the predictive value of radiomics features based on cardiac magnetic resonance (CMR) cine images for left ventricular adverse remodeling (LVAR) after acute ST-segment elevation myocardial infarction (STEMI). Materials and Methods: We conducted a retrospective, single-center, cohort study involving 244 patients (random-split into 170 and 74 for training and testing, respectively) having an acute STEMI (88.5% males, 57.0 ± 10.3 years of age) who underwent CMR examination at one week and six months after percutaneous coronary intervention. LVAR was defined as a 20% increase in left ventricular end-diastolic volume 6 months after acute STEMI. Radiomics features were extracted from the oneweek CMR cine images using the least absolute shrinkage and selection operator regression (LASSO) analysis. The predictive performance of the selected features was evaluated using receiver operating characteristic curve analysis and the area under the curve (AUC). Results: Nine radiomics features with non-zero coefficients were included in the LASSO regression of the radiomics score (RAD score). Infarct size (odds ratio [OR]: 1.04 (1.00-1.07); P = 0.031) and RAD score (OR: 3.43 (2.34-5.28); P < 0.001) were independent predictors of LVAR. The RAD score predicted LVAR, with an AUC (95% confidence interval [CI]) of 0.82 (0.75-0.89) in the training set and 0.75 (0.62-0.89) in the testing set. Combining the RAD score with infarct size yielded favorable performance in predicting LVAR, with an AUC of 0.84 (0.72-0.95). Moreover, the addition of the RAD score to the left ventricular ejection fraction (LVEF) significantly increased the AUC from 0.68 (0.52-0.84) to 0.82 (0.70-0.93) (P = 0.018), which was also comparable to the prediction provided by the combined microvascular obstruction, infarct size, and LVEF with an AUC of 0.79 (0.65-0.94) (P = 0.727). Conclusion: Radiomics analysis using non-contrast cine CMR can predict LVAR after STEMI independently and incrementally to LVEF and may provide an alternative to traditional CMR parameters.

• Korean Journal of Radiology
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• v.23 no.12
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• pp.1269-1280
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• 2022

Objective: This study aimed to evaluate the usefulness of quantitative indices obtained from deep learning analysis of gadoxetic acid-enhanced hepatobiliary phase (HBP) MRI and their longitudinal changes in predicting decompensation and death in patients with advanced chronic liver disease (ACLD). Materials and Methods: We included patients who underwent baseline and 1-year follow-up MRI from a prospective cohort that underwent gadoxetic acid-enhanced MRI for hepatocellular carcinoma surveillance between November 2011 and August 2012 at a tertiary medical center. Baseline liver condition was categorized as non-ACLD, compensated ACLD, and decompensated ACLD. The liver-to-spleen signal intensity ratio (LS-SIR) and liver-to-spleen volume ratio (LS-VR) were automatically measured on the HBP images using a deep learning algorithm, and their percentage changes at the 1-year follow-up (ΔLS-SIR and ΔLS-VR) were calculated. The associations of the MRI indices with hepatic decompensation and a composite endpoint of liver-related death or transplantation were evaluated using a competing risk analysis with multivariable Fine and Gray regression models, including baseline parameters alone and both baseline and follow-up parameters. Results: Our study included 280 patients (153 male; mean age ± standard deviation, 57 ± 7.95 years) with non-ACLD, compensated ACLD, and decompensated ACLD in 32, 186, and 62 patients, respectively. Patients were followed for 11-117 months (median, 104 months). In patients with compensated ACLD, baseline LS-SIR (sub-distribution hazard ratio [sHR], 0.81; p = 0.034) and LS-VR (sHR, 0.71; p = 0.01) were independently associated with hepatic decompensation. The ΔLS-VR (sHR, 0.54; p = 0.002) was predictive of hepatic decompensation after adjusting for baseline variables. ΔLS-VR was an independent predictor of liver-related death or transplantation in patients with compensated ACLD (sHR, 0.46; p = 0.026) and decompensated ACLD (sHR, 0.61; p = 0.023). Conclusion: MRI indices automatically derived from the deep learning analysis of gadoxetic acid-enhanced HBP MRI can be used as prognostic markers in patients with ACLD.

• Safety and Health at Work
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• v.15 no.1
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• pp.66-72
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• 2024

Background: This study examines the relationship between functional disability and work ability in workers affected by low back pain (LBP) through an analysis of correlations between the Oswestry Disability Index (ODI) and Work Ability Index (WAI). The role of personal and work factors on functional disability/work ability levels has also been studied. LBP is the most common musculoskeletal problem and a major disabling health problem worldwide. Its etiology is multifactorial. Multidisciplinary approaches may help reduce the burden of pain and disability and improve job continuity and reintegration at work. Methods: A cohort of 264 patients affected by LBP from an Italian outpatient clinic were included in a clinical diagnostic/therapeutic trial aiming at rehabilitation and return to work through an integrated investigation protocol. Data were collected during the first medical examination using anamnestic and clinical tools. The final sample is composed of 252 patients, 57.1% man, 44.0 % blue collars, 46.4% with the high school degree, 45.6% married. Results: WAI and ODI reported a negative and fair correlation (r = -0.454; p = .000). Workers with acute LBP symptoms have a higher probability of severe disability than those with chronic LBP symptoms. White collars without depressive symptoms reported higher work ability - even in chronic disability conditions-than those with depressive symptoms. Conclusion: The study found that ODI and WAI have a convergent validity and this suggests that the two tools measure capture distinctive aspects of disability related to personal, environmental, and occupational characteristics. The most important and modifiable prognostic factors found for ODI and WAI were depressive symptoms, workday absence, and intensity of back pain. The study also found a mild association between age and ODI. The study's findings highlight the importance of using a multidisciplinary approach to manage and prevent disability due to LBP.

• IMMUNE NETWORK
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• v.21 no.6
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• pp.41.1-41.13
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• 2021

Correlation between vaccine reactogenicity and immunogenicity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is unclear. Thus, we investigated to determine whether the reactogenicity after coronavirus disease 2019 vaccination is associated with antibody (Ab) titers and T cell responses. This study was prospective cohort study done with 131 healthcare workers at tertiary center in Seoul, South Korea. The degrees of the local reactions after the 1st and 2nd doses of ChAdOx1 nCov-19 (ChAdOx1) vaccination were significantly associated with the S1-specific IgG Ab titers (p=0.003 and 0.01, respectively) and neutralizing Ab (p=0.04 and 0.10, respectively) in age- and sex-adjusted multivariate analysis, whereas those after the BNT162b2 vaccination did not show significant associations. T cell responses did not show significant associations with the degree of reactogenicity after the ChAdOx1 vaccination or the BNT162b2 vaccination. Thus, high degree of local reactogenicity after the ChAdOx1 vaccine may be used as an indicator of strong humoral immune responses against SARS-CoV-2.

• Annals of Occupational and Environmental Medicine
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• v.35
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• pp.38.1-38.10
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• 2023

Background: Hearing loss (HL) is linked to an elevated risk of cardiovascular diseases (CVDs). The pathogeneses of HL and CVD commonly involve inflammatory responses. Previous studies investigated elevated levels of inflammatory biomarkers in subjects with HL, however, their findings did not demonstrate statistical significance. In our cross-sectional and longitudinal study, we investigated the correlation between HL and increased high-sensitivity C-reactive protein (hsCRP) levels to determine how HL is associated with CVDs. Methods: We conducted a cross-sectional study with workers aged over 18 years who underwent health check-ups at our institution between 2012 and 2018 (n = 566,507), followed by conducting a longitudinal study of workers aged > 18 who underwent health checkups at least twice at our institution between 2012 and 2018 (n = 173,794). The definition of HL was as an average threshold of ≥ 20 dB in pure-tone air conduction at 0.5, 1.0, and 2.0 kHz in both ears. The incidence of increased hsCRP levels throughout the follow-up period was defined as a level exceeding 3 mg/L. Logistic regression and generalized estimating equations were performed to estimate the risk of increased hsCRP levels according to the occurrence of HL in groups stratified by age. Results: In the cross-sectional study, the multivariate-adjusted odds ratio (OR) was 1.17 (95% confidence interval [CI]: 1.02-1.34); the OR was 0.99 (95% CI: 0.80-1.22) in those under 40 and 1.28 (1.08-1.53) in those over 40. In the longitudinal study, the multivariable-adjusted OR was 1.05 (95% CI: 0.92-1.19); the OR was 1.10 (95% CI: 0.90-1.35) in those under 40 and 1.20 (1.01-1.43) in those over 40. Conclusions: This cross-sectional and longitudinal study identified an association between HL and increased hsCRP levels in workers aged over 40 years.

• Korean Journal of Radiology
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• v.20 no.8
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• pp.1300-1310
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• 2019

Objective: To measure the diagnostic accuracy of percutaneous transthoracic needle lung biopsies (PTNBs) on the basis of the intention-to-diagnose principle and identify risk factors for diagnostic failure of PTNBs in a multi-institutional setting. Materials and Methods: A total of 9384 initial PTNBs performed in 9239 patients (mean patient age, 65 years [range, 20-99 years]) from January 2010 to December 2014 were included. The accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of PTNBs for diagnosis of malignancy were measured. The proportion of diagnostic failures was measured, and their risk factors were identified. Results: The overall accuracy, sensitivity, specificity, PPV, and NPV were 91.1% (95% confidence interval [CI], 90.6-91.7%), 92.5% (95% CI, 91.9-93.1%), 86.5% (95% CI, 85.0-87.9%), 99.2% (95% CI, 99.0-99.4%), and 84.3% (95% CI, 82.7-85.8%), respectively. The proportion of diagnostic failures was 8.9% (831 of 9384; 95% CI, 8.3-9.4%). The independent risk factors for diagnostic failures were lesions ≤ 1 cm in size (adjusted odds ratio [AOR], 1.86; 95% CI, 1.23-2.81), lesion size 1.1-2 cm (1.75; 1.45-2.11), subsolid lesions (1.81; 1.32-2.49), use of fine needle aspiration only (2.43; 1.80-3.28), final diagnosis of benign lesions (2.18; 1.84-2.58), and final diagnosis of lymphomas (10.66; 6.21-18.30). Use of cone-beam CT (AOR, 0.31; 95% CI, 0.13-0.75) and conventional CT-guidance (0.55; 0.32-0.94) reduced diagnostic failures. Conclusion: The accuracy of PTNB for diagnosis of malignancy was fairly high in our large-scale multi-institutional cohort. The identified risk factors for diagnostic failure may help reduce diagnostic failure and interpret the biopsy results.