Misdiagnosed as a perianal abscess: case report of perianal endometriosis.

Perianal endometriosis represents a rare form of endometriosis occurring outside the pelvic cavity. Owing to its infrequency in clinical practice, this condition is highly susceptible to misdiagnosis and inappropriate treatment. This case report details a young female patient who was erroneously diagnosed with a perianal abscess. We conducted a para-anal mass resection under spinal anesthesia, and subsequent histopathological examination definitively confirmed the diagnosis of perianal endometriosis.

Enhancement of gemcitabine sensitivity in intrahepatic cholangiocarcinoma through Saikosaponin-a mediated modulation of the p-AKT/BCL-6/ABCA1 axis.

BACKGROUND: Intrahepatic cholangiocarcinoma (ICC) remains a significant challenge in cancer therapy, especially due to its resistance to established treatments like Gemcitabine, necessitating novel therapeutic approaches. METHODS: This study utilized Gemcitabine-resistant cell lines, patient-derived organotypic tumor spheroids (PDOTs), and patient-derived xenografts (PDX) to evaluate the effects of Saikosaponin-a (SSA) on ICC cellular proliferation, migration, apoptosis, and its potential synergistic interaction with Gemcitabine. Techniques such as transcriptome sequencing, Luciferase reporter assays, and molecular docking were employed to unravel the molecular mechanisms. RESULTS: SSA exhibited antitumor effects in both in vitro and PDX models, indicating its considerable potential for ICC treatment. SSA markedly inhibited ICC progression by reducing cellular proliferation, enhancing apoptosis, and decreasing migration and invasion. Crucially, it augmented Gemcitabine's efficacy by targeting the p-AKT/BCL6/ABCA1 signaling pathway. This modulation led to the downregulation of p-AKT and suppression of BCL6 transcriptional activity, ultimately reducing ABCA1 expression and enhancing chemosensitivity to Gemcitabine. Additionally, ABCA1 was validated as a predictive biomarker for drug resistance, with a direct correlation between ABCA1 expression levels and the IC50 values of various small molecule drugs in ICC gene profiles. CONCLUSION: This study highlights the synergistic potential of SSA combined with Gemcitabine in enhancing therapeutic efficacy against ICC and identifies ABCA1 as a key biomarker for drug responsiveness. Furthermore, the introduction of the novel PDOTs microfluidic model provides enhanced insights into ICC research. This combination strategy may provide a novel approach to overcoming treatment challenges in ICC.

An XGBoost Machine Learning Based Model for Predicting Ki-67 Value ≥ 15% in T2NXM0 Stage Primary Breast Cancer Receiving Neoadjuvant Chemotherapy Using Clinical Data and Delta-Radiomic Features on Ultrasound Images and Overall Survival Analysis: A 5-Year Postoperative Follow-Up Study.

Objective: To establish a model based on clinical and delta-radiomic features within ultrasound images using XGBoost machine learning to predict proliferation-associated nuclear antigen Ki-67 value ≥ 15% in T2NXM0 stage primary breast cancer (BC). Method: Data were collected from 228 randomly selected BC patients who received ultrasound screening and postoperative pathologic assessment from April 2015 to September 2018. The patients were classified into the study group (n = 80) and control group (n = 148), and the data were apportioned into the training set and test set at a 7:3 ratio based on time intervals. In the training set, crucial factors were identified from clinical features and grayscale and delta-radiomic features within ultrasound images, by using the chi-square test, t-test, and rank-sum test. The clinical model, imaging model, and combined model were built using multivariate logistic regression, respectively. The model's predictive performance and clinical net benefit were assessed using DeLong's method and decision curve analysis. Meanwhile, an XGBoost algorithm is used to establish a prediction model to verify the above results. Results: The crucial factors affecting Ki-67 value ≥ 15% included BMI, lymph node metastases, BC volume, CA153, pathology type, tumor boundaries, tumor morphology, elastography score, and delta-radscore. The predictive performance of the combined model [AUC 0.857, OR 0.0290, 95% CI 0.793-0.908] was considerably improved on the training set than the clinical model [AUC 0.724, OR 0.0422, 95% CI 0.648-0.792] and the imaging model [AUC 0.798, OR 0.0355, 95% CI 0.727-0.857]. The decision curve analysis also confirmed that the combined model delivered a higher clinical net benefit, and the verification on the test set yielded similar results. The nomogram and the calibration curve plotted based on the combined model achieved satisfactory clinical effects. The SHAP value of the XGBoost algorithm also confirmed that lymph node metastasis, BC volume, elastography score, and delta-radscore are the best independent factors for predicting BC Ki-67 value ≥ 15%. Conclusion: The XGBoost machine learning-based combined model integrating clinical features and delta-radiomic features on ultrasound images was able to predict the Ki-67 value ≥ 15% in an efficient and noninvasive manner, providing important clues for clinical decision-making and follow-up in BC.

A case misdiagnosed as hyperthyroid heart disease: Surgical repair of unroofed coronary sinus syndrome with severe tricuspid regurgitation.

Unroofed coronary sinus syndrome (URCS), also known as coronary sinus septal defect, is a rare congenital heart disease. Because of its special anatomy and the lack of typical clinical symptoms, the disease is easily missed and misdiagnosed. This case report particularly describes a middle-aged male patient with URCS misdiagnosed for more than 19 years, covered by hyperthyroid heart disease, who subsequently developed uncontrollable symptoms such as chest tightness and shortness of breath and came to our hospital. After a clear diagnosis in our hospital, the patient was successfully cured after treatment with coronary sinus repair and tricuspid valvuloplasty under extracorporeal circulation.

The use of modified TI-RADS using contrast-enhanced ultrasound features for classification purposes in the differential diagnosis of benign and malignant thyroid nodules: A prospective and multi-center study.

Objectives: To evaluate the diagnostic efficacy of a modified thyroid imaging reporting and data system (TI-RADS) in combination with contrast-enhanced ultrasound (CEUS) for differentiating between benign and malignant thyroid nodules and to assess inter-observer concordance between different observers. Methods: This study included 3353 patients who underwent thyroid ultrasound (US) and CEUS in ten multi-centers between September 2018 and March 2020. Based on a modified TI-RADS classification using the CEUS enhancement pattern of thyroid lesions, ten radiologists analyzed all US and CEUS examinations independently and assigned a TI-RADS category to each thyroid nodule. Pathology was the reference standard for determining the diagnostic performance (accuracy (ACC), sensitivity (SEN), specificity (SPN), positive predictive value (PPV), and negative predictive value (NPV)) of the modified TI-RADS for predicting malignant thyroid nodules. The risk of malignancy was stratified for each TI-RADS category-based on the total number of benign and malignant lesions in that category. ROC curve was used to determine the cut-off value and the area under the curve (AUC). Cohen's Kappa statistic was applied to assess the inter-observer agreement of each sonological feature and TI-RADS category for thyroid nodules. Results: The calculated malignancy risk in the modified TI-RADS categories 5, 4b, 4a, 3 and 2 nodules was 95.4%, 86.0%, 12.0%, 4.1% and 0%, respectively. The malignancy risk for the five categories was in agreement with the suggested malignancy risk. The ROC curve showed that the AUC under the ROC curve was 0.936, and the cutoff value of the modified TI-RADS classification was >TI-RADS 4a, whose SEN, ACC, PPV, NPV and SPN were 93.6%, 91.9%, 90.4%, 93.7% and 88.5% respectively. The Kappa value for taller than wide, microcalcification, marked hypoechoic, solid composition, irregular margins and enhancement pattern of CEUS was 0.94, 0.93, 0.75, 0.89, 0.86 and 0.81, respectively. There was also good agreement between the observers with regards to the modified TI-RADS classification, the Kappa value was 0.80. Conclusions: The actual risk of malignancy according to the modified TI-RADS concurred with the suggested risk of malignancy. Inter-observer agreement for the modified TI-RADS category was good, thus suggesting that this classification was very suitable for clinical application.