Phyllodes tumors are rare biphasic fibroepithelial breast neoplasms classified as benign, borderline, or malignant. Despite their rarity, malignant variants carry higher risks of recurrence and metastasis. This review synthesizes current evidence on their clinical, histopathological, and molecular characteristics, including treatment strategies and prognostic factors, emphasizing tailored management. We performed a comprehensive literature review to summarize knowledge on clinical presentation, imaging, histopathological features, surgical treatment, adjuvant therapy, and outcomes. Recent genomic and molecular research was also evaluated to identify future directions. Persistent challenges include a lack of consensus on optimal surgical margins, adjuvant radiotherapy, and follow-up protocols, highlighting the need for larger, high-quality studies. Advances in molecular profiling suggest potential for targeted therapies, especially in aggressive or metastatic cases. Due to clinical heterogeneity and the limited accuracy of core biopsies, definitive grading based on surgical histopathology remains essential for treatment planning. This review offers an updated perspective on phyllodes tumor management, identifies critical gaps, and suggests priorities for future research.

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: 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: 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.

Morules, or morule-like features, can be identified in benign and malignant lesions in various organs. Morular features are unusual in pulmonary adenocarcinoma cases with only 26 cases reported to date. Here, we describe two cases of pulmonary adenocarcinoma with morule-like features in Korean women. One patient had a non-mucinous-type adenocarcinoma in situ and the other had an acinarpredominant adenocarcinoma with a micropapillary component. Both patients showed multiple intra-alveolar, nodular, whorled proliferative foci composed of atypical spindle cells with eosinophilic cytoplasm. Targeted next-generation sequencing was performed on DNA extracted from formalin-fixed paraffin-embedded samples of the tumors. Results showed unusual epidermal growth factor receptor (EGFR) mutations, which are associated with drug resistance to EGFR tyrosine kinase inhibitors, revealing the importance of identifying morule-like features in pulmonary adenocarcinoma and the need for additional study, since there are few reported cases.

A 46-year old man visited our outpatient clinic with complaint of foreign body sensation in throat after consuming raw freshwater fish 5 days ago. Laryngoscopic examination revealed a motile worm attached on posterior pharyngeal wall. The worm was removed using biopsy forceps under transnasal endoscopy and evidently identified as Clinostomum complanatum after microscopic examination. Patient’s subjective foreign body sensation of throat and hyperemia of laryngeal mucosa remained for approximately 2 weeks post-removal, which were eventually resolved after administration of non-steroidal anti-inflammatory drug and anti-refluxant drug for 2 weeks. Treatment was ended at three weeks since the first visit. C. complanatum infections in humans are rare, and only four cases have been reported in Korea. Symptoms resembling pharyngitis or laryngitis occurs by consumption of raw, infected freshwater fish and treatment is done by mechanically removing the parasite.
Ambulatory Care Facilities ; Biopsy ; Endoscopy ; Foreign Bodies ; Fresh Water ; Humans ; Hyperemia ; Korea ; Laryngeal Mucosa ; Laryngitis ; Parasites ; Pharyngitis ; Pharynx ; Sensation ; Surgical Instruments

No abstract available.
Humans ; Recurrence

No abstract available.
Adenocarcinoma ; Thymoma