Breast cancer is the most common cancer in women worldwide, and its early detection is critical for improving survival outcomes. As a diagnostic and screening tool, mammography can be less effective owing to the masking effect of fibroglandular tissue, but breast US has good sensitivity even in dense breasts. However, breast US is highly operator dependent, highlighting the need for artificial intelligence (AI)-driven solutions. Unlike other modalities, US is performed using a handheld device that produces a continuous real-time video stream, yielding 12000–48000 frames per examination. This can be significantly challenging for AI development and requires real-time AI inference capabilities. In this review, we classified AI solutions as computer-aided diagnosis and computer-aided detection to facilitate a functional understanding and review commercial software supported by clinical evidence.In addition, to bridge healthcare gaps and enhance patient outcomes in geographically under resourced areas, we propose a novel framework by reviewing the existing AI-based triage workflows including mobile ultrasound.

Breast cancer is the most common cancer in women worldwide, and its early detection is critical for improving survival outcomes. As a diagnostic and screening tool, mammography can be less effective owing to the masking effect of fibroglandular tissue, but breast US has good sensitivity even in dense breasts. However, breast US is highly operator dependent, highlighting the need for artificial intelligence (AI)-driven solutions. Unlike other modalities, US is performed using a handheld device that produces a continuous real-time video stream, yielding 12000–48000 frames per examination. This can be significantly challenging for AI development and requires real-time AI inference capabilities. In this review, we classified AI solutions as computer-aided diagnosis and computer-aided detection to facilitate a functional understanding and review commercial software supported by clinical evidence.In addition, to bridge healthcare gaps and enhance patient outcomes in geographically under resourced areas, we propose a novel framework by reviewing the existing AI-based triage workflows including mobile ultrasound.

Breast cancer is the most common cancer in women worldwide, and its early detection is critical for improving survival outcomes. As a diagnostic and screening tool, mammography can be less effective owing to the masking effect of fibroglandular tissue, but breast US has good sensitivity even in dense breasts. However, breast US is highly operator dependent, highlighting the need for artificial intelligence (AI)-driven solutions. Unlike other modalities, US is performed using a handheld device that produces a continuous real-time video stream, yielding 12000–48000 frames per examination. This can be significantly challenging for AI development and requires real-time AI inference capabilities. In this review, we classified AI solutions as computer-aided diagnosis and computer-aided detection to facilitate a functional understanding and review commercial software supported by clinical evidence.In addition, to bridge healthcare gaps and enhance patient outcomes in geographically under resourced areas, we propose a novel framework by reviewing the existing AI-based triage workflows including mobile ultrasound.

Ectopic breast tissue can develop along the mammary ridge from the axilla to the groin, and the most common site is the axillae. Primary carcinoma of ectopic breast tissue is extremely rare. We report a rare case of a 61-year-old woman with a palpable mass in her left axilla who had a history of surgical excision of accessory breast tissue in the same area. Mammography (MMG), including axillary tail view, ultrasound (US), and breast MRI were performed. We evaluated the extent and characteristics of the microcalcifications in the axillary tail view. A US-guided biopsy was done, and histopathology revealed an invasive ductal carcinoma. Enhanced abdominal CT revealed multiple hepatic masses consistent with metastases, and the patient received palliative chemotherapy. Herein, we present a rare case of breast cancer arising from accessory breast tissue in the axilla, best appreciated on the axillary tail view of the patient’s MMG.

Objective: The aim of this study was to identify high- and low-risk subgroups of patients with lymph node (LN) metastasis in presumed early-stage endometrioid endometrial cancer (EC) patients. Methods: Clinicopathologic data of presumed early-stage endometrioid EC patients (n=361) treated with lymphadenectomy between March 2000 and July 2022 were analyzed. None of the patient had definite evidence of LN metastasis in a preoperative magnetic resonance imaging (MRI). A received operating characteristic curve analysis was conducted to define the sensitivity and specificity for the combined preoperative risk factors for LN metastasis, which was determined by multivariate analysis. Results: Nineteen patients (5.3%) had LN metastasis. Multivariate analysis identified cervical stromal invasion on MRI (odds ratio [OR]=4.386; 95% confidence interval [CI]=1.020–18.852;p=0.047), cornual location of tumor on MRI (OR=36.208; 95% CI=7.902–165.913; p<0.001), and lower uterine segment/isthmic location of tumor on MRI (OR=8.454; 95% CI=1.567–45.610;p=0.013) as independent prognostic factors associated with LN metastasis. Patients were categorized into low- and high-risk groups according to risk criteria. Significant differences in the rates of LN metastasis were observed between the two groups (0.4% vs. 22.2%, p<0.001). Conclusion Approximately 95% of presumed early-stage endometrioid EC patients did not have LN metastasis. A model using tumor location was significantly correlated with the risk of LN metastasis. Even in presumed early-stage endometrioid EC patients, therefore, tumor location should be investigated to determine whether to perform LN assessment.

Objective: The aim of this study was to identify high- and low-risk subgroups of patients with lymph node (LN) metastasis in presumed early-stage endometrioid endometrial cancer (EC) patients. Methods: Clinicopathologic data of presumed early-stage endometrioid EC patients (n=361) treated with lymphadenectomy between March 2000 and July 2022 were analyzed. None of the patient had definite evidence of LN metastasis in a preoperative magnetic resonance imaging (MRI). A received operating characteristic curve analysis was conducted to define the sensitivity and specificity for the combined preoperative risk factors for LN metastasis, which was determined by multivariate analysis. Results: Nineteen patients (5.3%) had LN metastasis. Multivariate analysis identified cervical stromal invasion on MRI (odds ratio [OR]=4.386; 95% confidence interval [CI]=1.020–18.852;p=0.047), cornual location of tumor on MRI (OR=36.208; 95% CI=7.902–165.913; p<0.001), and lower uterine segment/isthmic location of tumor on MRI (OR=8.454; 95% CI=1.567–45.610;p=0.013) as independent prognostic factors associated with LN metastasis. Patients were categorized into low- and high-risk groups according to risk criteria. Significant differences in the rates of LN metastasis were observed between the two groups (0.4% vs. 22.2%, p<0.001). Conclusion Approximately 95% of presumed early-stage endometrioid EC patients did not have LN metastasis. A model using tumor location was significantly correlated with the risk of LN metastasis. Even in presumed early-stage endometrioid EC patients, therefore, tumor location should be investigated to determine whether to perform LN assessment.

Ectopic breast tissue can develop along the mammary ridge from the axilla to the groin, and the most common site is the axillae. Primary carcinoma of ectopic breast tissue is extremely rare. We report a rare case of a 61-year-old woman with a palpable mass in her left axilla who had a history of surgical excision of accessory breast tissue in the same area. Mammography (MMG), including axillary tail view, ultrasound (US), and breast MRI were performed. We evaluated the extent and characteristics of the microcalcifications in the axillary tail view. A US-guided biopsy was done, and histopathology revealed an invasive ductal carcinoma. Enhanced abdominal CT revealed multiple hepatic masses consistent with metastases, and the patient received palliative chemotherapy. Herein, we present a rare case of breast cancer arising from accessory breast tissue in the axilla, best appreciated on the axillary tail view of the patient’s MMG.

Objective: The aim of this study was to identify high- and low-risk subgroups of patients with lymph node (LN) metastasis in presumed early-stage endometrioid endometrial cancer (EC) patients. Methods: Clinicopathologic data of presumed early-stage endometrioid EC patients (n=361) treated with lymphadenectomy between March 2000 and July 2022 were analyzed. None of the patient had definite evidence of LN metastasis in a preoperative magnetic resonance imaging (MRI). A received operating characteristic curve analysis was conducted to define the sensitivity and specificity for the combined preoperative risk factors for LN metastasis, which was determined by multivariate analysis. Results: Nineteen patients (5.3%) had LN metastasis. Multivariate analysis identified cervical stromal invasion on MRI (odds ratio [OR]=4.386; 95% confidence interval [CI]=1.020–18.852;p=0.047), cornual location of tumor on MRI (OR=36.208; 95% CI=7.902–165.913; p<0.001), and lower uterine segment/isthmic location of tumor on MRI (OR=8.454; 95% CI=1.567–45.610;p=0.013) as independent prognostic factors associated with LN metastasis. Patients were categorized into low- and high-risk groups according to risk criteria. Significant differences in the rates of LN metastasis were observed between the two groups (0.4% vs. 22.2%, p<0.001). Conclusion Approximately 95% of presumed early-stage endometrioid EC patients did not have LN metastasis. A model using tumor location was significantly correlated with the risk of LN metastasis. Even in presumed early-stage endometrioid EC patients, therefore, tumor location should be investigated to determine whether to perform LN assessment.

Ectopic breast tissue can develop along the mammary ridge from the axilla to the groin, and the most common site is the axillae. Primary carcinoma of ectopic breast tissue is extremely rare. We report a rare case of a 61-year-old woman with a palpable mass in her left axilla who had a history of surgical excision of accessory breast tissue in the same area. Mammography (MMG), including axillary tail view, ultrasound (US), and breast MRI were performed. We evaluated the extent and characteristics of the microcalcifications in the axillary tail view. A US-guided biopsy was done, and histopathology revealed an invasive ductal carcinoma. Enhanced abdominal CT revealed multiple hepatic masses consistent with metastases, and the patient received palliative chemotherapy. Herein, we present a rare case of breast cancer arising from accessory breast tissue in the axilla, best appreciated on the axillary tail view of the patient’s MMG.

Purpose: Endoscopic nipple-sparing mastectomy (E-NSM) is a minimally invasive surgical technique that shows good results in patients with breast cancer. The authors compared 3 different types of commercial energy devices to examine their efficacy and safety in E-NSM performed with breast reconstruction. Methods: A total of 36 cases of E-NSM were conducted with either Sonicision (S group, n = 11), Harmonic (H group, n = 6), or Thunderbeat (T group, n = 19). The clinicopathologic factors and postoperative complications, including nipple or skin necrosis and surgical site seroma volume, were evaluated for 3 months after surgery. Results: The surgical duration of E-NSM was significantly shorter in the S group than in the H group (P = 0.043) and T group (P = 0.037). However, the total surgical duration including E-NSM and breast reconstruction, and the total and daily drainage volume of postoperative seroma did not differ significantly among the 3 groups. Even when the energy devices were compared according to their working principle, i.e., ultrasonic (S and H) vs. hybrid (T), the total breast surgery duration and total and daily drainage volume of seroma showed no difference between the 2 groups. Although surgeon satisfaction did not significantly differ when using 3 devices for E-NSM (P = 0.428), surgeon’s fatigue was found to be lowest in the S group, though it was not significant (P = 0.064). Conclusion Any energy device can be safely used for E-NSM with breast reconstruction without causing any major complications. However, cordless ultrasonic energy devices allow greater mobility for the surgeon and, therefore, may shorten surgical time in breast surgery.