Objective: Automated breast ultrasound (ABUS) is a relevant imaging technique for early breast cancer diagnosis and is increasingly being used as a supplementary tool for mammography. This study compared the performance of ABUS and handheld ultrasound (HHUS) in detecting and characterizing the axillary lymph nodes (LNs) in patients with breast cancer. Materials and Methods: We retrospectively reviewed the medical records of women with recently diagnosed early breast cancer (≤ T2) who underwent both ABUS and HHUS examinations for axilla (September 2017–May 2018). ABUS and HHUS findings were compared using pathological outcomes as reference standards. Diagnostic performance in predicting any axillary LN metastasis and heavy nodal-burden metastases (i.e., ≥ 3 LNs) was evaluated. The ABUS-HHUS agreement for visibility and US findings was calculated. Results: The study included 377 women (53.1 ± 11.1 years). Among 385 breast cancers in 377 patients, 101 had axillary LN metastases and 30 had heavy nodal burden metastases. ABUS identified benign-looking or suspicious axillary LNs (average, 1.4 ± 0.8) in 246 axillae (63.9%, 246/385). According to the per-breast analysis, the sensitivity, specificity, positive and negative predictive values, and accuracy of ABUS in predicting axillary LN metastases were 43.6% (44/101), 95.1% (270/284), 75.9% (44/58), 82.6% (270/327), and 81.6% (314/385), respectively. The corresponding results for HHUS were 41.6% (42/101), 95.1% (270/284), 75.0% (42/56), 82.1% (270/329), and 81.0% (312/385), respectively, which were not significantly different from those of ABUS (P ≥ 0.53). The performance results for heavy nodal-burden metastases were 70.0% (21/30), 89.6% (318/355), 36.2% (21/58), 97.3% (318/327), and 88.1% (339/385), respectively, for ABUS and 66.7% (20/30), 89.9% (319/355), 35.7% (20/56), 97.0% (319/329), and 88.1% (339/385), respectively, for HHUS, also not showing significant difference (P ≥ 0.57). The ABUS–HHUS agreement was 95.9% (236/246; Cohen’s kappa = 0.883). Conclusion Although ABUS showed limited sensitivity in diagnosing axillary LN metastasis in early breast cancer, it was still useful as the performance was comparable to that of HHUS.

Objective: To prospectively investigate the influence of the menstrual cycle on the background parenchymal signal (BPS) and apparent diffusion coefficient (ADC) of the breast on diffusion-weighted MRI (DW-MRI) in healthy premenopausal women. Materials and Methods: Seven healthy premenopausal women (median age, 37 years; range, 33–49 years) with regular menstrual cycles participated in this study. DW-MRI was performed during each of the four phases of the menstrual cycle (four examinations in total). Three radiologists independently assessed the BPS visual grade on images with b-values of 800 sec/mm2 (b800), 1200 sec/mm2 (b1200), and a synthetic 1500 sec/mm2 (sb1500). Additionally, one radiologist conducted a quantitative analysis to measure the BPS volume (%) and ADC values of the BPS (ADCBPS) and fibroglandular tissue (ADCFGT). Changes in the visual grade, BPS volume (%), ADCBPS, and ADCFGT during the menstrual cycle were descriptively analyzed. Results: The visual grade of BPS in seven women varied from mild to marked on b800 and from minimal to moderate on b1200 and sb1500. As the b-value increased, the visual grade of BPS decreased. On b800 and sb1500, two of the seven volunteers showed the highest visual grade in the early follicular phase (EFP). On b1200, three of the seven volunteers showed the highest visual grades in EFP. The BPS volume (%) on b800 and b1200 showed the highest value in three of the six volunteers with dense breasts in EFP. Three of the seven volunteers showed the lowest ADCBPS in the EFP. Four of the seven volunteers showed the highest ADCBPS in the early luteal phase (ELP) and the lowest ADCFGT in the late follicular phase (LFP). Conclusion Most volunteers did not exhibit specific BPS patterns during their menstrual cycles. However, the highest BPS and lowest ADCBPS were more frequently observed in EFP than in the other menstrual cycle phases, whereas the highest ADCBPS was more common in ELP. The lowest ADCFGT was more frequent in LFP.

Purpose: External ear reconstruction has been a challenging subject for plastic surgeons for decades. Popular methods using autologous costal cartilage or polyethylene still have their drawbacks. With the advance of three-dimensional (3D) printing technique, bioscaffold engineering using synthetic polymer draws attention as an alternative. This is a clinical trial of ear reconstruction using 3D printed scaffold, presented with clinical results after 1 year. Materials and Methods: From 2021 to 2022, five adult patients with unilateral microtia underwent two-staged total ear reconstruction using 3D printed implants. For each patient, a patient-specific 3D printed scaffold was designed and produced with polycaprolactone (PCL) based on computed tomography images, using fused deposition modeling. Computed tomography scan was obtained preoperatively, within 2 weeks following the surgery and after 1 year, to compare the volume of the normal side and the reconstructed ear. At 1-year visit, clinical photo was taken for scoring by two surgeons and patients themselves. Results: All five patients had completely healed reconstructed ear at 1-year follow-up. On average, the volume of reconstructed ear was 161.54% of that of the normal side ear. In a range of 0 to 10, objective assessors gave scores 3 to 6, whereas patients gave scores 8 to 10. Conclusion External ear reconstruction using 3D printed PCL implant showed durable, safe results reflected by excellent volume restoration and patient satisfaction at 1 year postoperatively. Further clinical follow-up with more cases and refinement of scaffold with advancing bioprinting technique is anticipated. The study’s plan and results have been registered with the Clinical Research Information Service (CRIS No. 3-2019-0306) and the Ministry of Food and Drug Safety (MFDS No.1182).

Purpose: Several predictive models have been developed to predict the pathological complete response (pCR) after neoadjuvant chemotherapy (NAC); however, few are broadly applicable owing to radiologic complexity and institution-specific clinical variables, and none have been externally validated. This study aimed to develop and externally validate a machine learning model that predicts pCR after NAC in patients with breast cancer using routinely collected clinical and demographic variables. Methods: The electronic medical records of patients with advanced breast cancer who underwent NAC before surgical resection between January 2017 and December 2020 were reviewed. Patient data from Seoul National University Bundang Hospital were divided into training and internal validation cohorts. Five machine learning techniques, including gradient boosting machine (GBM), support vector machine, random forest, decision tree, and neural network, were used to build predictive models, and the area under the receiver operating characteristic curve (AUC) was compared to select the best model. Finally, the model was validated using an independent cohort from Seoul National University Hospital. Results: A total of 1,003 patients were included in the study: 287, 71, and 645 in the training, internal validation, and external validation cohorts, respectively. Overall, 36.3% of the patients achieved pCR. Among the five machine learning models, the GBM showed the highest AUC for pCR prediction (AUC, 0.903; 95% confidence interval [CI], 0.833–0.972).External validation confirmed an AUC of 0.833 (95% CI, 0.800–0.865). Conclusion Commonly available clinical and demographic variables were used to develop a machine learning model for predicting pCR following NAC. External validation of the model demonstrated good discrimination power, indicating that routinely collected variables were sufficient to build a good prediction model.

Purpose: Estrogen receptor (ER) expression in breast cancer plays an essential role in carcinogenesis and disease progression. Recently, tumors with low level (1%-10%) of ER expression have been separately defined as ER low positive (ERlow). It is suggested that ERlow tumors might be morphologically and behaviorally different from tumors with high ER expression (ERhigh). Materials and Methods: Retrospective analysis of a prospective cohort database was performed. Patients who underwent curative surgery for early breast cancer and had available medical records were included for analysis. Difference in clinicopathological characteristics, endocrine responsiveness and five-year recurrence-free survival was evaluated between different ER subgroups (ERhigh, ERlow, and ER-negative [ER–]). Results: A total of 2,162 breast cancer patients were included in the analysis, Tis and T1 stage. Among them, 1,654 (76.5%) were ERhigh, 54 (2.5%) were ERlow, and 454 (21.0%) were ER- patients. ERlow cases were associated with smaller size, higher histologic grade, positive human epidermal growth factor receptor 2, negative progesterone receptor, and higher Ki-67 expression. Recurrence rate was highest in ER– tumors and was inversely proportional to ER expression. Recurrence-free survival was not affected by hormonal therapy in the ERlow group (p=0.418). Conclusion ERlow breast cancer showed distinct clinicopathological features. ERlow tumors seemed to have higher recurrence rates compared to ERhigh tumors, and they showed no significant benefit from hormonal therapy. Future large scale prospective studies are necessary to validate the treatment options for ERlow breast cancer.

Background: Myasthenia gravis (MG) is an autoimmune disease, and early thymectomy is recommended. Since the introduction of video-assisted thoracoscopic surgery, the safety and effectiveness of carbon dioxide insufflation in the thoracic cavity (capnothorax) has been controversial. This study aimed to compare the safety and effectiveness of ventilation methods in bilateral video-assisted thoracoscopic extended thymectomy (BVET) with capnothorax. Methods: We retrospectively investigated the medical records of patients with MG who underwent BVET between August 2016 and January 2018. Patients were divided into two groups: group D (n = 26) for one-lung ventilation and group S (n = 28) for two-lung ventilation. We set nine anesthesia time points (T0–T8) and collected respiratory and hemodynamic variables, including arterial O2 index (PaO2/FiO2). Results: SpO2 at T1–T3 and T8 was significantly lower in group D than in group S. The FiO2 in group S was lower than that in group D at all time points. The number of PaO2/FiO2 ≤ 300 and PaO2/FiO2 ≤ 200 events was significantly higher in group D than in group S. Hemodynamic variables were not significantly different between the two groups at any time point. The duration of surgery and anesthesia was shorter in group S than in group D. Conclusions This retrospective study suggests that anesthesia using two-lung ventilation during BVET with capnothorax is a safe and effective method to improve lung oxygenation and reduce anesthesia time.

Objective: The optimal imaging approach for evaluating pathological nipple discharge remains unclear. We investigated the value of adding ductography to ultrasound (US) for evaluating pathologic nipple discharge in patients with negative mammography findings. Materials and Methods: From July 2003 to December 2018, 101 women (mean age, 46.3 ± 12.2 years; range, 23–75 years) with pathologic nipple discharge were evaluated using pre-ductography (initial) US, ductography, and post-ductography US. The imaging findings were reviewed retrospectively. The standard reference was surgery (70 patients) or > 2 years of followup with US (31 patients). The diagnostic performances of initial US, ductography, and post-ductography US for detecting malignancy were compared using the McNemar’s test or a generalized estimating equation. Results: In total, 47 papillomas, 30 other benign lesions, seven high-risk lesions, and 17 malignant lesions were identified as underlying causes of pathologic nipple discharge. Only eight of the 17 malignancies were detected on the initial US, while the remaining nine malignancies were detected by ductography. Among the nine malignancies detected by ductography, eight were detected on post-ductography US and could be localized for US-guided intervention. The sensitivities of ductography (94.1% [16/17]) and post-ductography US (94.1% [16/17]) were significantly higher than those of initial US (47.1% [8/17]; p = 0.027 and 0.013, respectively). The negative predictive value of post-ductography US (96.9% [31/32]) was significantly higher than that of the initial US (83.3% [45/54]; p = 0.006). Specificity was significantly higher for initial US than for ductography and post-ductography US (p = 0.001 for all). Conclusion The combined use of ductography and US has a high sensitivity for detecting malignancy in patients with pathologic nipple discharge and negative mammography. Ductography findings enable lesion localization on second-look post-ductography US, thus facilitating the selection of optimal treatment plans.

Purpose: The purpose of this study was to measure the cancer detection rate of computer-aided detection (CAD) software in preoperative automated breast ultrasonography (ABUS) of breast cancer patients and to determine the characteristics associated with false-negative outcomes. Methods: A total of 129 index lesions (median size, 1.7 cm; interquartile range, 1.2 to 2.4 cm) from 129 consecutive patients (mean age±standard deviation, 53.4±11.8 years) who underwent preoperative ABUS from December 2017 to February 2018 were assessed. An index lesion was defined as a breast cancer confirmed by ultrasonography (US)-guided core needle biopsy. The detection rate of the index lesions, positive predictive value (PPV), and false-positive rate (FPR) of the CAD software were measured. Subgroup analysis was performed to identify clinical and US findings associated with false-negative outcomes. Results: The detection rate of the CAD software was 0.84 (109 of 129; 95% confidence interval, 0.77 to 0.90). The PPV and FPR were 0.41 (221 of 544; 95% CI, 0.36 to 0.45) and 0.45 (174 of 387; 95% CI, 0.40 to 0.50), respectively. False-negative outcomes were more frequent in asymptomatic patients (P<0.001) and were associated with the following US findings: smaller size (P=0.001), depth in the posterior third (P=0.002), angular or indistinct margin (P<0.001), and absence of architectural distortion (P<0.001). Conclusion The CAD software showed a promising detection rate of breast cancer. However, radiologists should judge whether CAD software-marked lesions are true- or false-positive lesions, considering its low PPV and high FPR. Moreover, it would be helpful for radiologists to consider the characteristics associated with false-negative outcomes when reading ABUS with CAD.

Purpose: This study aimed to predict a heavy nodal burden (≥3 metastatic axillary lymph nodes [LNs]) using axillary ultrasonography (US) and US-guided fine-needle aspiration biopsy (FNAB) in patients with early-stage breast cancer. Methods: We retrospectively reviewed the medical records of 403 women (404 cancers) who underwent US-guided FNAB for axillary LN staging from January 2006 to December 2015. US findings and US-guided FNAB results were reviewed and compared using pathology results as the reference. Diagnostic performance was analyzed, and clinicopathological and radiological findings were compared between patients with <3 metastatic LNs and ≥3 metastatic LNs. Results: The final pathology results revealed that 20.5% of cancers had heavy nodal metastases. US-guided FNAB showed significantly higher sensitivity (79.0% vs. 63.0%, P=0.009) and specificity (84.8% vs. 79.3%, P=0.036) in predicting heavy nodal metastases than did US. The presence of a larger number of suspicious LNs (two or more) on axillary US and positive FNAB results were significantly correlated with a heavy nodal burden in the multivariate analysis. The odds ratios were 4.20 (95% confidence interval [CI], 1.90 to 9.39) for two suspicious LNs, 9.40 (95% CI, 2.99 to 29.54) for three or more suspicious LNs, and 14.22 (95% CI, 6.78 to 29.82) for positive FNAB results. Conclusion The number of suspicious LNs detected on axillary US and FNAB results can help predict a heavy axillary nodal burden in patients with early-stage breast cancer.

Purpose: : This study aimed to present the incidence of pressure ulcers and identify different associated factors according to the time of occurrence of pressure ulcers in intensive care unit (ICU) patients. Methods: : The participants were 313 patients who reported pressure ulcers among 2,908 patients in ICUs at a large tertiary hospital in Gyeonggi-do. Among them, 220 patients (70.3%) had a pressure ulcer before admission, and 93 patients (29.7%) reported newly developed pressure ulcers after admission to the ICU. Data were collected between August 2018 and April 2019. Along with the time of occurrence and characteristics of pressure ulcers, diverse associated factors were gathered through electronic medical records. Data were analyzed using descriptive statistics, independent t-tests, and χ2-tests. Results: : Different risk factors associated with pressure ulcers in ICU patients according to the time of occurrence were main diagnosis, score of acute physiology and chronic health evaluation, score of Richmond agitation sedation scale, level of consciousness, administered sedatives, use of a ventilator, insertion of a feeding tube, and the duration of fasting period. Conclusion : Based on the results of this study, healthcare providers, especially ICU nurses, should try to detect early signs and symptoms of pressure ulcers, taking into account the derived factors associated with pressure ulcers in ICU patients. Practical intervention programs and strategies considering the factors associated with pressure ulcers must be developed to prevent and alleviate such ulcers in ICU patients in the future.