Purpose: Predicting improvements in voiding symptoms following deobstructive surgery for male lower urinary tract symptoms/benign prostatic hyperplasia (LUTS/BPH) is challenging when detrusor contractility is impaired. This study aimed to develop an artificial intelligence model that predicts symptom improvement after holmium laser enucleation of the prostate (HoLEP), focusing on changes in maximum flow rate (MFR) and voiding efficiency (VE) 1-month postsurgery. Methods: We reviewed 1,933 patients who underwent HoLEP at Samsung Medical Center from July 2008 to January 2024. The study employed a deep neural network (DNN) for multiclass classification to predict changes in MFR and VE, each divided into 3 categories. For comparison, additional machine learning (ML) models such as extreme gradient boosting, random forest classification, and support vector machine were utilized. To address class imbalance, we applied the least squares method and multitask learning. Results: A total of 1,142 patients with complete data were included in the study, with 992 allocated for model training and 150 for external validation. In predicting MFR, the DNN achieved a microaverage area under the receiver operating characteristic curve (AUC) of 0.884±0.006, sensitivity of 0.783±0.020, and specificity of 0.891±0.010. For VE prediction, the microaverage AUC was 0.817±0.007, with sensitivity and specificity values of 0.660±0.014 and 0.830±0.007, respectively. These results indicate that the DNN's predictive performance was superior to that of other ML models. Conclusions The DNN model provides detailed and accurate predictions for recovery after HoLEP, providing valuable insights for clinicians managing patients with LUTS/BPH.

Purpose: Predicting improvements in voiding symptoms following deobstructive surgery for male lower urinary tract symptoms/benign prostatic hyperplasia (LUTS/BPH) is challenging when detrusor contractility is impaired. This study aimed to develop an artificial intelligence model that predicts symptom improvement after holmium laser enucleation of the prostate (HoLEP), focusing on changes in maximum flow rate (MFR) and voiding efficiency (VE) 1-month postsurgery. Methods: We reviewed 1,933 patients who underwent HoLEP at Samsung Medical Center from July 2008 to January 2024. The study employed a deep neural network (DNN) for multiclass classification to predict changes in MFR and VE, each divided into 3 categories. For comparison, additional machine learning (ML) models such as extreme gradient boosting, random forest classification, and support vector machine were utilized. To address class imbalance, we applied the least squares method and multitask learning. Results: A total of 1,142 patients with complete data were included in the study, with 992 allocated for model training and 150 for external validation. In predicting MFR, the DNN achieved a microaverage area under the receiver operating characteristic curve (AUC) of 0.884±0.006, sensitivity of 0.783±0.020, and specificity of 0.891±0.010. For VE prediction, the microaverage AUC was 0.817±0.007, with sensitivity and specificity values of 0.660±0.014 and 0.830±0.007, respectively. These results indicate that the DNN's predictive performance was superior to that of other ML models. Conclusions The DNN model provides detailed and accurate predictions for recovery after HoLEP, providing valuable insights for clinicians managing patients with LUTS/BPH.

Purpose: Predicting improvements in voiding symptoms following deobstructive surgery for male lower urinary tract symptoms/benign prostatic hyperplasia (LUTS/BPH) is challenging when detrusor contractility is impaired. This study aimed to develop an artificial intelligence model that predicts symptom improvement after holmium laser enucleation of the prostate (HoLEP), focusing on changes in maximum flow rate (MFR) and voiding efficiency (VE) 1-month postsurgery. Methods: We reviewed 1,933 patients who underwent HoLEP at Samsung Medical Center from July 2008 to January 2024. The study employed a deep neural network (DNN) for multiclass classification to predict changes in MFR and VE, each divided into 3 categories. For comparison, additional machine learning (ML) models such as extreme gradient boosting, random forest classification, and support vector machine were utilized. To address class imbalance, we applied the least squares method and multitask learning. Results: A total of 1,142 patients with complete data were included in the study, with 992 allocated for model training and 150 for external validation. In predicting MFR, the DNN achieved a microaverage area under the receiver operating characteristic curve (AUC) of 0.884±0.006, sensitivity of 0.783±0.020, and specificity of 0.891±0.010. For VE prediction, the microaverage AUC was 0.817±0.007, with sensitivity and specificity values of 0.660±0.014 and 0.830±0.007, respectively. These results indicate that the DNN's predictive performance was superior to that of other ML models. Conclusions The DNN model provides detailed and accurate predictions for recovery after HoLEP, providing valuable insights for clinicians managing patients with LUTS/BPH.

Purpose: We evaluated the change in patient quality of life after the use of a hydrophilic-coated catheter (SpeediCath) in adults requiring intermittent catheterization (IC). Methods: This was a multicenter, open-label, observational study using the Patient Perception of Intermittent Catheterization (PPIC) questionnaire and the Intermittent Self-Catheterization questionnaire (ISC-Q) and safety at 12 and 24 weeks in adult patients who had already used other type of catheters prior to switching to SpeediCath or in patients undergoing self-IC for the first time for any reason. Results: Among a total of 360 subjects, 215 (59.7%) were women, and the mean age was 62.0±13.2 years. At 24 weeks, the satisfaction rate after using SpeediCath was 84.1%, and 80% of patients responded that they could easily perform IC. In total, 81.6% of patients were willing to continue using SpeediCath. The mean ISC-Q score was 54.90±18.65 at 24 weeks. Men found less interference in their daily life by performing IC than women and found it easier to handle the catheter before it was inserted into the urethra. At week 12, the mean change in ISC-Q was significantly greater in patients <65 years (20.24±23.55) than in those ≥65 years (7.57±27.70, P=0.049), but there was no difference at 24 weeks. The most common adverse events were urinary tract infection in 9.72%, gross hematuria in 2.78%, and urethral pain in 1.39%. Conclusions The use of a SpeediCath provided good quality of life for patients who needed self-IC regardless of age or sex.

Purpose: In this trial, we investigated the efficacy and safety of adjuvant letrozole for hormone receptor (HR)-positive breast cancer. Here, we report the clinical outcome in postmenopausal women with HR-positive breast cancer treated with adjuvant letrozole according to estrogen receptor (ER) expression levels. Methods: In this multi-institutional, open-label, observational study, postmenopausal patients with HR-positive breast cancer received adjuvant letrozole (2.5 mg/daily) for 5 years unless they experienced disease progression or unacceptable toxicity or withdrew their consent. The patients were stratified into the following 3 groups according to ER expression levels using a modified Allred score (AS): low, intermediate, and high (AS 3–4, 5–6, and 7–8, respectively). ER expression was centrally reviewed. The primary objective was the 5-year disease-free survival (DFS) rate. Results: Between April 25, 2010, and February 5, 2014, 440 patients were enrolled. With a median follow-up of 62.0 months, the 5-year DFS rate in all patients was 94.2% (95% confidence interval [CI], 91.8–96.6). The 5-year DFS and recurrence-free survival (RFS) rates did not differ according to ER expression; the 5-year DFS rates were 94.3% and 94.1%in the low-to-intermediate and high expression groups, respectively (p = 0.6), and the corresponding 5-year RFS rates were 95.7% and 95.4%, respectively (p = 0.7). Furthermore, 25 patients discontinued letrozole because of drug toxicity. Conclusion Treatment with adjuvant letrozole showed very favorable treatment outcomes and good tolerability among Korean postmenopausal women with ER-positive breast cancer, independent of ER expression.

Objective: To evaluate the reliability of CT measurements of muscle quantity and quality using variable CT parameters. Materials and Methods: A phantom, simulating the L2–4 vertebral levels, was used for this study. CT images were repeatedly acquired with modulation of tube voltage, tube current, slice thickness, and the image reconstruction algorithm. Reference standard muscle compartments were obtained from the reference maps of the phantom. Cross-sectional area based on the Hounsfield unit (HU) thresholds of muscle and its components, and the mean density of the reference standard muscle compartment, were used to measure the muscle quantity and quality using different CT protocols. Signal-to-noise ratios (SNRs) were calculated in the images acquired with different settings. Results: The skeletal muscle area (threshold, -29 to 150 HU) was constant, regardless of the protocol, occupying at least 91.7% of the reference standard muscle compartment. Conversely, normal attenuation muscle area (30–150 HU) was not constant in the different protocols, varying between 59.7% and 81.7% of the reference standard muscle compartment. The mean density was lower than the target density stated by the manufacturer (45 HU) in all cases (range, 39.0–44.9 HU). The SNR decreased with low tube voltage, low tube current, and in sections with thin slices, whereas it increased when the iterative reconstruction algorithm was used. Conclusion Measurement of muscle quantity using HU threshold was reliable, regardless of the CT protocol used. Conversely, the measurement of muscle quality using the mean density and narrow HU thresholds were inconsistent and inaccurate across different CT protocols. Therefore, further studies are warranted in future to determine the optimal CT protocols for reliable measurements of muscle quality.

Objective: To evaluate the reliability of CT measurements of muscle quantity and quality using variable CT parameters. Materials and Methods: A phantom, simulating the L2–4 vertebral levels, was used for this study. CT images were repeatedly acquired with modulation of tube voltage, tube current, slice thickness, and the image reconstruction algorithm. Reference standard muscle compartments were obtained from the reference maps of the phantom. Cross-sectional area based on the Hounsfield unit (HU) thresholds of muscle and its components, and the mean density of the reference standard muscle compartment, were used to measure the muscle quantity and quality using different CT protocols. Signal-to-noise ratios (SNRs) were calculated in the images acquired with different settings. Results: The skeletal muscle area (threshold, -29 to 150 HU) was constant, regardless of the protocol, occupying at least 91.7% of the reference standard muscle compartment. Conversely, normal attenuation muscle area (30–150 HU) was not constant in the different protocols, varying between 59.7% and 81.7% of the reference standard muscle compartment. The mean density was lower than the target density stated by the manufacturer (45 HU) in all cases (range, 39.0–44.9 HU). The SNR decreased with low tube voltage, low tube current, and in sections with thin slices, whereas it increased when the iterative reconstruction algorithm was used. Conclusion Measurement of muscle quantity using HU threshold was reliable, regardless of the CT protocol used. Conversely, the measurement of muscle quality using the mean density and narrow HU thresholds were inconsistent and inaccurate across different CT protocols. Therefore, further studies are warranted in future to determine the optimal CT protocols for reliable measurements of muscle quality.

Purpose: In this trial, we investigated the efficacy and safety of adjuvant letrozole for hormone receptor (HR)-positive breast cancer. Here, we report the clinical outcome in postmenopausal women with HR-positive breast cancer treated with adjuvant letrozole according to estrogen receptor (ER) expression levels. Methods: In this multi-institutional, open-label, observational study, postmenopausal patients with HR-positive breast cancer received adjuvant letrozole (2.5 mg/daily) for 5 years unless they experienced disease progression or unacceptable toxicity or withdrew their consent. The patients were stratified into the following 3 groups according to ER expression levels using a modified Allred score (AS): low, intermediate, and high (AS 3–4, 5–6, and 7–8, respectively). ER expression was centrally reviewed. The primary objective was the 5-year disease-free survival (DFS) rate. Results: Between April 25, 2010, and February 5, 2014, 440 patients were enrolled. With a median follow-up of 62.0 months, the 5-year DFS rate in all patients was 94.2% (95% confidence interval [CI], 91.8–96.6). The 5-year DFS and recurrence-free survival (RFS) rates did not differ according to ER expression; the 5-year DFS rates were 94.3% and 94.1%in the low-to-intermediate and high expression groups, respectively (p = 0.6), and the corresponding 5-year RFS rates were 95.7% and 95.4%, respectively (p = 0.7). Furthermore, 25 patients discontinued letrozole because of drug toxicity. Conclusion Treatment with adjuvant letrozole showed very favorable treatment outcomes and good tolerability among Korean postmenopausal women with ER-positive breast cancer, independent of ER expression.

Leucine-rich repeat-containing G-protein coupled receptor 5 (LGR5) has been reported to play critical roles in the proliferation of various cancer cells. However, the roles of LGR5 in brain tumors and the specific intracellular signaling proteins directly associated with it remain unknown. Expression of LGR5 was first measured in normal brain tissue, meningioma, and pituitary adenoma of humans. To identify the downstream signaling pathways of LGR5, siRNA-mediated knockdown of LGR5 was performed in SH-SY5Y neuroblastoma cells followed by proteomics analysis with 2-dimensional polyacrylamide gel electrophoresis (2D-PAGE). In addition, the expression of LGR5-associated proteins was evaluated in LGR5-inhibited neuroblastoma cells and in human normal brain, meningioma, and pituitary adenoma tissue. Proteomics analysis showed 12 protein spots were significantly different in expression level (more than two-fold change) and subsequently identified by peptide mass fingerprinting. A protein association network was constructed from the 12 identified proteins altered by LGR5 knockdown. Direct and indirect interactions were identified among the 12 proteins. HSP 90-beta was one of the proteins whose expression was altered by LGR5 knockdown. Likewise, we observed decreased expression of proteins in the hnRNP subfamily following LGR5 knockdown. In addition, we have for the first time identified significantly higher hnRNP family expression in meningioma and pituitary adenoma compared to normal brain tissue. Taken together, LGR5 and its downstream signaling play critical roles in neuroblastoma and brain tumors such as meningioma and pituitary adenoma.
Brain ; Brain Neoplasms ; Cell Proliferation ; Dermatoglyphics ; Electrophoresis, Polyacrylamide Gel ; GTP-Binding Proteins ; Heterogeneous-Nuclear Ribonucleoproteins ; Humans ; Intracellular Signaling Peptides and Proteins ; Meningioma ; Neuroblastoma ; Pituitary Neoplasms ; Proteomics