Background: This study assessed the comparative effectiveness of sextant and extended 12-core systematic biopsy within combined biopsy for the detection of prostate cancer. Methods: Patients who underwent combined biopsy targeting lesions with a Prostate Imaging Reporting and Data System (PI-RADS) score of 3–5 were assessed. Two specialists performed all combined cognitive biopsies. Both specialists performed target biopsies with five or more cores. One performed sextant systematic biopsies, and the other performed extended 12-core systematic biopsies. A total of 550 patients were analyzed. Results: Cases requiring systematic biopsy in combined biopsy exhibited a significant association with age ≥ 65 years (odds ratio [OR], 2.32; 95% confidence interval [CI], 1.25– 4.32; P = 0.008), PI-RADS score (OR, 2.32; 95% CI, 1.25–4.32; P = 0.008), and the number of systematic biopsy cores (OR, 3.69; 95% CI, 2.11–6.44; P < 0.001). In patients with an index lesion of PI-RADS 4, an extended 12-core systematic biopsy was required (target-negative/ systematic-positive or a greater Gleason score in the systematic biopsy than in the targeted biopsy) (P < 0.001). Conclusion During combined biopsy for prostate cancer in patients with PI-RADS 3 or 5, sextant systematic biopsy should be recommended over extended 12-core systematic biopsy when an effective targeted biopsy is performed.

A 62-year-old man with multiple myeloma visited our clinic with multiple painful erythematous to purpuric nodules on his whole body. He received a skin biopsy which showed septal and lobular inflammation with vasculitis, and multiple amoebic organisms were found.Polymerase chain reaction and culture were performed and an Acanthamoeba triangularis infection was diagnosed. This is the first report on cutaneous acanthamoebiasis caused by A. triangularis, suggesting that A. triangularis should be regarded as a clinical pathogen that can cause ocular as well as disseminated infection.

Purpose: We aimed to investigate the risk factors and patterns of locoregional recurrence (LRR) after radical nephrectomy (RN) in patients with locally advanced renal cell carcinoma (RCC). Materials and Methods: We retrospectively analyzed 245 patients who underwent RN for non-metastatic pT3-4 RCC from January 2006 to January 2016. We analyzed the risk factors associated with poor locoregional control using Cox regression. Anatomical mapping was performed on reference computed tomography scans showing intact kidneys. Results: The median follow-up duration was 56 months (range, 1 to 128 months). Tumor extension to renal vessels or the inferior vena cava (IVC) and Fuhrman’s nuclear grade IV were identified as independent risk factors of LRR. The 5-year actuarial LRR rates in groups with no risk factor, one risk factor, and two risk factors were 2.3%, 19.8%, and 30.8%, respectively (p < 0.001). The locations of LRR were distributed as follows: aortocaval area (n=2), paraaortic area (n=4), retrocaval area (n=5), and tumor bed (n=11). No LRR was observed above the celiac axis (CA) or under the inferior mesenteric artery (IMA). Conclusion Tumor extension to renal vessels or the IVC and Fuhrman’s nuclear grade IV were the independent risk factors associated with LRR after RN for pT3-4 RCC. The locations of LRR after RN for RCC were distributed in the tumor bed and regional lymphatic area from the bifurcation of the CA to that of the IMA.

Objective: Studies have been conducted to identify brain structural alterations related to high impulsivity in psychiatric populations. However, research on healthy subjects is relatively less extensive. Therefore, we aimed to investigate the correlation between the cortical thickness of whole brain regions and the impulsivity level in a healthy population. Methods: We included 100 healthy participants aged 19–65 years. Their T1-weighted magnetic resonance images and the 23-item Barratt Impulsiveness Scale (BIS) score were obtained. The patients were divided into high and low impulsivity groups according to the 75th percentile score of the BIS in the sample. The thickness of each cortical region was calculated using the FreeSurfer, and the difference in cortical thickness of the whole brain between the high and low impulsivity groups was analyzed using one-way analysis of covariance including age, sex, education level, and total intracranial cavity volume as covariates. Results: The high impulsivity group showed significant cortical thinning in the left pars opercularis. The cortical thickness of the left pars opercularis significantly correlated negatively with the total, attention, and motor scores of the BIS scale. Conclusion Our findings suggest that prefrontal cortex thinning may play an important role in the development of high impulsivity in healthy adults.

Objective: Studies have been conducted to identify brain structural alterations related to high impulsivity in psychiatric populations. However, research on healthy subjects is relatively less extensive. Therefore, we aimed to investigate the correlation between the cortical thickness of whole brain regions and the impulsivity level in a healthy population. Methods: We included 100 healthy participants aged 19–65 years. Their T1-weighted magnetic resonance images and the 23-item Barratt Impulsiveness Scale (BIS) score were obtained. The patients were divided into high and low impulsivity groups according to the 75th percentile score of the BIS in the sample. The thickness of each cortical region was calculated using the FreeSurfer, and the difference in cortical thickness of the whole brain between the high and low impulsivity groups was analyzed using one-way analysis of covariance including age, sex, education level, and total intracranial cavity volume as covariates. Results: The high impulsivity group showed significant cortical thinning in the left pars opercularis. The cortical thickness of the left pars opercularis significantly correlated negatively with the total, attention, and motor scores of the BIS scale. Conclusion Our findings suggest that prefrontal cortex thinning may play an important role in the development of high impulsivity in healthy adults.

Background/Aims: Intrahepatic cholangiocarcinoma (ICC) is the second-most common primary liver malignancy, arising from the peripheral intrahepatic bile duct epithelium. Hepatitis B virus (HBV) or hepatitis C virus (HCV) may be involved in the development of ICC. We explored the prognostic value of hepatitis virus infection, as well as other prognostic factors affecting survival in patients with ICC. Methods: A retrospective chart review was performed for patients diagnosed with ICC between August 2005 and December 2018 at Konkuk University Medical Center. We identified a total of 131 patients with ICC. Overall survival rates of patients with and without hepatitis were determined. Univariate and multivariate analyses were used to estimate factors influencing survival outcomes. Results: A total of 17.6% (23/131) of patients were positive for HBV or HCV. Hepatitis B positive ICC patients were significantly younger with higher albumin and higher α-fetoprotein than those without hepatitis viral infections. The median survival of hepatitis-positive and hepatitis-negative groups was 280 and 213 days, respectively. Survival rates were not significantly different between the two groups (p = 0.279). Multivariate analyses indicated that lower serum carbohydrate antigen 19-9 (CA 19-9) (p < 0.001), lower T stage (p = 0.042), the absence of lymph-node metastasis (p = 0.043), and receiving curative surgery (p = 0.033) were independent predictors of better outcomes. Conclusions While hepatitis influenced a number of clinical features in ICC patients, it did not affect survival rate. Prognostic factors influencing survival outcomes with ICC were CA 19-9 level, T stage, the presence of lymph node metastasis, and curative surgery.

PURPOSE: To compare biopsy performance of 2 approaches for multiparametric magnetic resonance imaging (MRI) guided biopsy and transrectal ultrasonography (TRUS)-guided biopsy with 2nd and 3rd repeat biopsy patients in prostate cancer detection. MATERIALS AND METHODS: This retrospective study reviewed 2,868 patients who was performed prostate biopsy between September 2013 to March 2017 at Samsung Medical Center, Seoul, Korea with TRUS-guided random biopsy and MRI fusion, MRI cognitive, and MRI-guided biopsy as 2nd and 3rd repeat biopsy and propensity matching was applied to reduce bias. Detection rate of each study was compared with 1:1 matching. RESULTS: Among 265 patients who performed TRUS 2nd biopsy, positivity rate for prostate cancer (PCa) was 18.49% (n=49/265) while 54.72% (n=145/265) for MRI-guided biopsy. In 3rd biopsy, positivity rate for PCa of TRUS biopsy was 17.74% (n=11/62) while 56.45% (n=35/62) for MRI guided biopsy. There was no significant difference in the detection rate for the patient with Gleason score 8 or more. CONCLUSIONS: MRI-guided biopsy was associated with a higher detection rate of prostate cancer with especially in patients with prior negative biopsy.
Bias (Epidemiology) ; Biopsy ; Cohort Studies ; Humans ; Korea ; Magnetic Resonance Imaging ; Neoplasm Grading ; Passive Cutaneous Anaphylaxis ; Propensity Score ; Prostate ; Prostatic Neoplasms ; Retrospective Studies ; Seoul ; Ultrasonography

OBJECTIVE: Bone mineral density (BMD) is an important consideration during fusion surgery. Although dual X-ray absorptiometry is considered as the gold standard for assessing BMD, quantitative computed tomography (QCT) provides more accurate data in spine osteoporosis. However, QCT has the disadvantage of additional radiation hazard and cost. The present study was to demonstrate the utility of artificial intelligence and machine learning algorithm for assessing osteoporosis using Hounsfield units (HU) of preoperative lumbar CT coupling with data of QCT.METHODS: We reviewed 70 patients undergoing both QCT and conventional lumbar CT for spine surgery. The T-scores of 198 lumbar vertebra was assessed in QCT and the HU of vertebral body at the same level were measured in conventional CT by the picture archiving and communication system (PACS) system. A multiple regression algorithm was applied to predict the T-score using three independent variables (age, sex, and HU of vertebral body on conventional CT) coupling with T-score of QCT. Next, a logistic regression algorithm was applied to predict osteoporotic or non-osteoporotic vertebra. The Tensor flow and Python were used as the machine learning tools. The Tensor flow user interface developed in our institute was used for easy code generation.RESULTS: The predictive model with multiple regression algorithm estimated similar T-scores with data of QCT. HU demonstrates the similar results as QCT without the discordance in only one non-osteoporotic vertebra that indicated osteoporosis. From the training set, the predictive model classified the lumbar vertebra into two groups (osteoporotic vs. non-osteoporotic spine) with 88.0% accuracy. In a test set of 40 vertebrae, classification accuracy was 92.5% when the learning rate was 0.0001 (precision, 0.939; recall, 0.969; F1 score, 0.954; area under the curve, 0.900).CONCLUSION: This study is a simple machine learning model applicable in the spine research field. The machine learning model can predict the T-score and osteoporotic vertebrae solely by measuring the HU of conventional CT, and this would help spine surgeons not to under-estimate the osteoporotic spine preoperatively. If applied to a bigger data set, we believe the predictive accuracy of our model will further increase. We propose that machine learning is an important modality of the medical research field.
Absorptiometry, Photon ; Artificial Intelligence ; Boidae ; Bone Density ; Classification ; Dataset ; Humans ; Learning ; Logistic Models ; Machine Learning ; Osteoporosis ; Spine ; Surgeons

BACKGROUND AND PURPOSE: The pathophysiology of post-stroke depression (PSD) is complex and may differ according to an individual’s mood immediately after stroke. Here, we compared the therapeutic response and clinical characteristics of PSD at a later stage between patients with and without depression immediately after stroke. METHODS: This study involved a post hoc analysis of data from EMOTION (ClinicalTrials.gov NCT01278498), a placebo-controlled, double-blind trial that examined the efficacy of escitalopram (10 mg/day) on PSD and other emotional disturbances among 478 patients with acute stroke. Participants were classified into the Baseline-Blue (patients with baseline depression at the time of randomization, defined per the Montgomery-Asberg Depression Rating Scale [MADRS] ≥8) or the Baseline-Pink groups (patients without baseline depression). We compared the efficacy of escitalopram and predictors of 3-month PSD (MADRS ≥8) between these groups. RESULTS: There were 203 Baseline-Pink and 275 Baseline-Blue patients. The efficacy of escitalopram in reducing PSD risk was more pronounced in the Baseline-Pink than in the Baseline-Blue group (p for interaction=0.058). Several risk factors differentially affected PSD development based on the presence of baseline depression (p for interaction < 0.10). Cognitive dysfunction was an independent predictor of PSD in the Baseline-Blue, but not in the Baseline-Pink group, whereas the non-use of escitalopram and being female were more strongly associated with PSD in the Baseline-Pink group. CONCLUSIONS: Responses to escitalopram and predictors of PSD 3 months following stroke differed based on the presence of baseline depression. Our data suggest that PSD pathophysiology is heterogeneous; therefore, different therapeutic strategies may be needed to prevent PSD emergence following stroke.
Affective Symptoms ; Anger ; Citalopram ; Depression* ; Female ; Humans ; Random Allocation ; Risk Factors ; Stroke