PURPOSE: The purpose of this study was to compare the surface characteristics and healing patterns after implantation of implants treated with SLA and those treated with both SLA and femtosecond laser. MATERIALS AND METHODS: A total of 10 male New Zealand white rabbits were used to compare recovery levels between implants treated with SLA (SLA group) and those treated with both SLA and femtosecond laser (SF group). The implants’ surface characteristics were determined through topographic evaluation, element analysis, surface roughness, and wettability evaluation. In total, 4 implants were placed in each rabbit (2 in each tibia), with 20 implants per treatment group. Using the implant stability quotient (ISQ), marginal bone volume, and histological analysis (bone-to-implant contact (BIC), bone volume/tissue volume (BV/TV)), and post implantation outcomes were assessed. Outcome data were analyzed using independent t-tests, Mann-Whitney U tests, Wilcoxon signed-rank tests, and one-way ANOVA (α = 0.05). RESULTS: No significant differences were noted between SLA and SF groups in terms of ISQ, marginal bone volume, BIC, and BV/TV (P > .05). However, significant differences in ISQ were observed within each group over time (P < .05). Furthermore, significant differences were noted in the marginal bone volume of the SF group (P < .05) and the BV/TV of the SLA group between weeks 4 and 6 (P < .05). CONCLUSION Surface treatment via SLA and femtosecond laser is feasible compared with SLA treatment alone in terms of ISQ, marginal bone volume, BIC, and BV/TV. However, further clinical research is warranted.

Purpose: This study aimed to develop a magnetic resonance imaging (MRI)–based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space, and poorly differentiated patterns. Materials and Methods: As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography–computed tomography (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, maximum standardized uptake value on FDG PET/CT, and the mean apparent diffusion coefficient value on diffusion-weighted image, were considered together to build prediction models for high-risk pathologic features. Results: Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The magnetic resonance (MR)–eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p < 0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p < 0.001), worse 4-year disease-free survival (p < 0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC, 0.860 and 0.907, respectively). Conclusion Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.

PURPOSE: The purpose of this study was to compare the surface characteristics and healing patterns after implantation of implants treated with SLA and those treated with both SLA and femtosecond laser. MATERIALS AND METHODS: A total of 10 male New Zealand white rabbits were used to compare recovery levels between implants treated with SLA (SLA group) and those treated with both SLA and femtosecond laser (SF group). The implants’ surface characteristics were determined through topographic evaluation, element analysis, surface roughness, and wettability evaluation. In total, 4 implants were placed in each rabbit (2 in each tibia), with 20 implants per treatment group. Using the implant stability quotient (ISQ), marginal bone volume, and histological analysis (bone-to-implant contact (BIC), bone volume/tissue volume (BV/TV)), and post implantation outcomes were assessed. Outcome data were analyzed using independent t-tests, Mann-Whitney U tests, Wilcoxon signed-rank tests, and one-way ANOVA (α = 0.05). RESULTS: No significant differences were noted between SLA and SF groups in terms of ISQ, marginal bone volume, BIC, and BV/TV (P > .05). However, significant differences in ISQ were observed within each group over time (P < .05). Furthermore, significant differences were noted in the marginal bone volume of the SF group (P < .05) and the BV/TV of the SLA group between weeks 4 and 6 (P < .05). CONCLUSION Surface treatment via SLA and femtosecond laser is feasible compared with SLA treatment alone in terms of ISQ, marginal bone volume, BIC, and BV/TV. However, further clinical research is warranted.

PURPOSE: The purpose of this study was to compare the surface characteristics and healing patterns after implantation of implants treated with SLA and those treated with both SLA and femtosecond laser. MATERIALS AND METHODS: A total of 10 male New Zealand white rabbits were used to compare recovery levels between implants treated with SLA (SLA group) and those treated with both SLA and femtosecond laser (SF group). The implants’ surface characteristics were determined through topographic evaluation, element analysis, surface roughness, and wettability evaluation. In total, 4 implants were placed in each rabbit (2 in each tibia), with 20 implants per treatment group. Using the implant stability quotient (ISQ), marginal bone volume, and histological analysis (bone-to-implant contact (BIC), bone volume/tissue volume (BV/TV)), and post implantation outcomes were assessed. Outcome data were analyzed using independent t-tests, Mann-Whitney U tests, Wilcoxon signed-rank tests, and one-way ANOVA (α = 0.05). RESULTS: No significant differences were noted between SLA and SF groups in terms of ISQ, marginal bone volume, BIC, and BV/TV (P > .05). However, significant differences in ISQ were observed within each group over time (P < .05). Furthermore, significant differences were noted in the marginal bone volume of the SF group (P < .05) and the BV/TV of the SLA group between weeks 4 and 6 (P < .05). CONCLUSION Surface treatment via SLA and femtosecond laser is feasible compared with SLA treatment alone in terms of ISQ, marginal bone volume, BIC, and BV/TV. However, further clinical research is warranted.

Background: Differentiating between asymptomatic bacteriuria (ASB) and urinary tract infection (UTI) is difficult in patients who have difficulty communicating their symptoms.This study aimed to evaluate the diagnostic accuracy of urine leukocytes in distinguishing between UTI and ASB, and the clinical outcomes of patients with UTI according to the degree of pyuria. Methods: This retrospective cohort study included patients with positive urine cultures between July 2022 and June 2023 at two hospitals. UTI and ASB were diagnosed through a comprehensive review of medical records. We evaluated the differences in urine leukocyte counts between patients with UTI and ASB. The diagnostic performance of urine leukocytes to differentiate between UTI and ASB was evaluated. To investigate the clinical outcomes based on the degree of pyuria, we classified patients with upper UTI according to their urine leukocyte counts. Results: Of the 1,793 eligible patients with bacteriuria included, 1,464 had UTI and 329 had ASB. Patients with UTI had higher urinary leukocytes than patients with ASB did (490.4 vs.123.5 cells/µL; P < 0.001). The area under the receiver operating characteristic curve was 0.702 for discriminating between ASB and UTI. The optimal urine leukocyte cutoff was 195.35 cells/µL, with a sensitivity and specificity of 0.70 and 0.60, respectively. A sequential rise in secondary bacteremia rate was observed according to an increase in urine leukocytes in patients with upper UTI, whereas in-hospital mortality showed no corresponding trend. Conclusion Urine leukocyte counts could be used to predict UTI occurrence and bacteremia secondary to UTI. Higher degrees of pyuria were associated with bacteremia but not with mortality. Urine leukocyte counts can provide additive information for patients with bacteriuria with vague symptoms.

Background: Differentiating between asymptomatic bacteriuria (ASB) and urinary tract infection (UTI) is difficult in patients who have difficulty communicating their symptoms.This study aimed to evaluate the diagnostic accuracy of urine leukocytes in distinguishing between UTI and ASB, and the clinical outcomes of patients with UTI according to the degree of pyuria. Methods: This retrospective cohort study included patients with positive urine cultures between July 2022 and June 2023 at two hospitals. UTI and ASB were diagnosed through a comprehensive review of medical records. We evaluated the differences in urine leukocyte counts between patients with UTI and ASB. The diagnostic performance of urine leukocytes to differentiate between UTI and ASB was evaluated. To investigate the clinical outcomes based on the degree of pyuria, we classified patients with upper UTI according to their urine leukocyte counts. Results: Of the 1,793 eligible patients with bacteriuria included, 1,464 had UTI and 329 had ASB. Patients with UTI had higher urinary leukocytes than patients with ASB did (490.4 vs.123.5 cells/µL; P < 0.001). The area under the receiver operating characteristic curve was 0.702 for discriminating between ASB and UTI. The optimal urine leukocyte cutoff was 195.35 cells/µL, with a sensitivity and specificity of 0.70 and 0.60, respectively. A sequential rise in secondary bacteremia rate was observed according to an increase in urine leukocytes in patients with upper UTI, whereas in-hospital mortality showed no corresponding trend. Conclusion Urine leukocyte counts could be used to predict UTI occurrence and bacteremia secondary to UTI. Higher degrees of pyuria were associated with bacteremia but not with mortality. Urine leukocyte counts can provide additive information for patients with bacteriuria with vague symptoms.

Purpose: This study aimed to develop a magnetic resonance imaging (MRI)–based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space, and poorly differentiated patterns. Materials and Methods: As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography–computed tomography (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, maximum standardized uptake value on FDG PET/CT, and the mean apparent diffusion coefficient value on diffusion-weighted image, were considered together to build prediction models for high-risk pathologic features. Results: Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The magnetic resonance (MR)–eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p < 0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p < 0.001), worse 4-year disease-free survival (p < 0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC, 0.860 and 0.907, respectively). Conclusion Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.

Background: Differentiating between asymptomatic bacteriuria (ASB) and urinary tract infection (UTI) is difficult in patients who have difficulty communicating their symptoms.This study aimed to evaluate the diagnostic accuracy of urine leukocytes in distinguishing between UTI and ASB, and the clinical outcomes of patients with UTI according to the degree of pyuria. Methods: This retrospective cohort study included patients with positive urine cultures between July 2022 and June 2023 at two hospitals. UTI and ASB were diagnosed through a comprehensive review of medical records. We evaluated the differences in urine leukocyte counts between patients with UTI and ASB. The diagnostic performance of urine leukocytes to differentiate between UTI and ASB was evaluated. To investigate the clinical outcomes based on the degree of pyuria, we classified patients with upper UTI according to their urine leukocyte counts. Results: Of the 1,793 eligible patients with bacteriuria included, 1,464 had UTI and 329 had ASB. Patients with UTI had higher urinary leukocytes than patients with ASB did (490.4 vs.123.5 cells/µL; P < 0.001). The area under the receiver operating characteristic curve was 0.702 for discriminating between ASB and UTI. The optimal urine leukocyte cutoff was 195.35 cells/µL, with a sensitivity and specificity of 0.70 and 0.60, respectively. A sequential rise in secondary bacteremia rate was observed according to an increase in urine leukocytes in patients with upper UTI, whereas in-hospital mortality showed no corresponding trend. Conclusion Urine leukocyte counts could be used to predict UTI occurrence and bacteremia secondary to UTI. Higher degrees of pyuria were associated with bacteremia but not with mortality. Urine leukocyte counts can provide additive information for patients with bacteriuria with vague symptoms.

PURPOSE: The purpose of this study was to compare the surface characteristics and healing patterns after implantation of implants treated with SLA and those treated with both SLA and femtosecond laser. MATERIALS AND METHODS: A total of 10 male New Zealand white rabbits were used to compare recovery levels between implants treated with SLA (SLA group) and those treated with both SLA and femtosecond laser (SF group). The implants’ surface characteristics were determined through topographic evaluation, element analysis, surface roughness, and wettability evaluation. In total, 4 implants were placed in each rabbit (2 in each tibia), with 20 implants per treatment group. Using the implant stability quotient (ISQ), marginal bone volume, and histological analysis (bone-to-implant contact (BIC), bone volume/tissue volume (BV/TV)), and post implantation outcomes were assessed. Outcome data were analyzed using independent t-tests, Mann-Whitney U tests, Wilcoxon signed-rank tests, and one-way ANOVA (α = 0.05). RESULTS: No significant differences were noted between SLA and SF groups in terms of ISQ, marginal bone volume, BIC, and BV/TV (P > .05). However, significant differences in ISQ were observed within each group over time (P < .05). Furthermore, significant differences were noted in the marginal bone volume of the SF group (P < .05) and the BV/TV of the SLA group between weeks 4 and 6 (P < .05). CONCLUSION Surface treatment via SLA and femtosecond laser is feasible compared with SLA treatment alone in terms of ISQ, marginal bone volume, BIC, and BV/TV. However, further clinical research is warranted.

Purpose: This study aimed to develop a magnetic resonance imaging (MRI)–based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space, and poorly differentiated patterns. Materials and Methods: As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography–computed tomography (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, maximum standardized uptake value on FDG PET/CT, and the mean apparent diffusion coefficient value on diffusion-weighted image, were considered together to build prediction models for high-risk pathologic features. Results: Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The magnetic resonance (MR)–eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p < 0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p < 0.001), worse 4-year disease-free survival (p < 0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC, 0.860 and 0.907, respectively). Conclusion Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.