Primary tumor regression speed after radiotherapy and its prognostic significance in nasopharyngeal carcinoma: a retrospective study.

BACKGROUND: To observe the primary tumor (PT) regression speed after radiotherapy (RT) in nasopharyngeal carcinoma (NPC) and evaluate its prognostic significance. METHODS: One hundred and eighty-eight consecutive newly diagnosed NPC patients were reviewed retrospectively. All patients underwent magnetic resonance imaging and fiberscope examination of the nasopharynx before RT, during RT when the accumulated dose was 46-50 Gy, at the end of RT, and 3-4 months after RT. RESULTS: Of 188 patients, 40.4% had complete response of PT (CRPT), 44.7% had partial response of PT (PRPT), and 14.9% had stable disease of PT (SDPT) at the end of RT. The 5-year overall survival (OS) rates for patients with CRPT, PRPT, and SDPT at the end of RT were 84.0%, 70.7%, and 44.3%, respectively (P < 0.001, hazard ratio [HR] = 2.177, 95% confidence interval [CI] = 1.480-3.202). The 5-year failure-free survival (FFS) and distant metastasis-free survival (DMFS) rates also differed significantly (87.8% vs. 74.3% vs. 52.7%, P = 0.001, HR = 2.148, 95% CI, 1.384-3.333; 91.7% vs. 84.7% vs. 66.1%, P = 0.004, HR = 2.252, 95% CI = 1.296-3.912). The 5-year local relapse-free survival (LRFS) rates were not significantly different (95.8% vs. 86.0% vs. 81.8%, P = 0.137, HR = 1.975, 95% CI, 0.976-3.995). By multivariate analyses, the PT regression speed at the end of RT was the only independent prognostic factor of OS, FFS, and DMFS (P < 0.001, P = 0.001, and P = 0.004, respectively). The 5-year FFS rates for patients with CRPT during RT and CRPT only at the end of RT were 80.2% and 97.1%, respectively (P = 0.033). For patients with persistent PT at the end of RT, the 5-year LRFS rates of patients without and with boost irradiation were 87.1% and 84.6%, respectively (P = 0.812). CONCLUSIONS: PT regression speed at the end of RT was an independent prognostic factor of OS, FFS, and DMFS in NPC patients. Immediate strengthening treatment may be provided to patients with poor tumor regression at the end of RT.

Novel deep learning radiomics nomogram-based multiparametric MRI for predicting the lymph node metastasis in rectal cancer: A dual-center study.

PURPOSE: To develop and evaluate a nomogram that integrates clinical parameters with deep learning radiomics (DLR) extracted from Magnetic Resonance Imaging (MRI) data to enhance the predictive accuracy for preoperative lymph node (LN) metastasis in rectal cancer. METHODS: A retrospective analysis was conducted on 356 patients diagnosed with rectal cancer. Of these, 286 patients were allocated to the training set, and 70 patients comprised the external validation cohort. Preprocessed T2-weighted and diffusion-weighted imaging performed preoperatively facilitated the extraction of DLR features. Five machine learning algorithms-k-nearest neighbor, light gradient boosting machine, logistic regression, random forest, and support vector machine-were utilized to develop DLR models. The most effective algorithm was identified and used to establish a clinical DLR (CDLR) nomogram specifically designed to predict LN metastasis in rectal cancer. The performance of the nomogram was evaluated using receiver operating characteristic curve analysis. RESULTS: The logistic regression classifier demonstrated significant predictive accuracy using the DLR signature, achieving an Area Under the Curve (AUC) of 0.919 in the training cohort and 0.778 in the external validation cohort. The integrated CDLR nomogram exhibited robust predictive performance across both datasets, with AUC values of 0.921 in the training cohort and 0.818 in the external validation cohort. Notably, it outperformed both the clinical model, which had AUC values of 0.770 and 0.723 in the training and external validation cohorts, respectively, and the stand-alone DLR model. CONCLUSION: The nomogram derived from multiparametric MRI data, referred to as the CDLR model, demonstrates strong predictive efficacy in forecasting LN metastasis in rectal cancer.

Discriminating atypical parotid carcinoma and pleomorphic adenoma utilizing extracellular volume fraction and arterial enhancement fraction derived from contrast-enhanced CT imaging: A multicenter study.

OBJECTIVES: To investigate the added value of extracellular volume fraction (ECV) and arterial enhancement fraction (AEF) derived from enhanced CT to conventional image and clinical features for differentiating between pleomorphic adenoma (PA) and atypical parotid adenocarcinoma (PCA) pre-operation. METHODS: From January 2010 to October 2023, a total of 187 cases of parotid tumors were recruited, and divided into training cohort (102 PAs and 51 PCAs) and testing cohort (24 PAs and 10 atypical PCAs). Clinical and CT image features of tumor were assessed. Both enhanced CT-derived ECV and AEF were calculated. Univariate analysis identified variables with statistically significant differences between the two subgroups in the training cohort. Multivariate logistic regression analysis with the forward variable selection method was used to build four models (clinical model, clinical model+ECV, clinical model+AEF, and combined model). Diagnostic performances were evaluated using receiver operating characteristic (ROC) curve analyses. Delong's test compared model differences, and calibration curve and decision curve analysis (DCA) assessed calibration and clinical application. RESULTS: Age and boundary were chosen to build clinical model, and to construct its ROC curve. Amalgamating the clinical model, ECV, and AEF to establish a combined model demonstrated superior diagnostic effectiveness compared to the clinical model in both the training and test cohorts (AUC = 0.888, 0.867). There was a significant statistical difference between the combined model and the clinical model in the training cohort (p = 0.0145). CONCLUSIONS: ECV and AEF are helpful in differentiating PA and atypical PCA, and integrating clinical and CT image features can further improve the diagnostic performance.

Prognostic significance of maximum primary tumor diameter in nasopharyngeal carcinoma.

BACKGROUND: To evaluate the prognostic value of maximum primary tumor diameter (MPTD) in nasopharyngeal carcinoma (NPC). METHODS: Three hundred and thirty-three consecutive, newly-diagnosed NPC patients were retrospectively reviewed. Kaplan-Meier analysis and the log-rank test were used to estimate overall survival (OS), failure-free survival (FFS), distant metastasis-free survival (DMFS) and local relapse-free survival (LRFS). Cox proportional hazards regression analysis was used to assess the prognostic value of MPTD. RESULTS: Median follow-up was 66 months (range, 2-82 months). Median MPTD in stage T1, T2, T3 and T4 was 27.9, 37.5, 45.0 and 61.3 mm, respectively. The proportion of T1 patients with a MPTD ≤ 30 mm was 62.3%; 72% and 62.9% of T2 and T3 patients had a MPTD > 30-50 mm, and 83.5% of T4 patients had a MPTD > 50 mm. For patients with a MPTD ≤ 30 mm, > 30-50 mm and > 50 mm, the 5-year OS, FFS, DMFS and LRFS rates were 85.2%, 74.2% and 56.3% (P < 0.001); 87%, 80.7% and 62.8% (P < 0.001); 88.7%, 86.4% and 72.5% (P = 0.003); and 98.2%, 93.2% and 86.3% (P = 0.012), respectively. In multivariate analysis, MPTD was a prognostic factor for OS, FFS and DMFS, and the only independent prognostic factor for LRFS. For T3-T4 patients with a MPTD ≤ 50 mm and > 50 mm, the 5-year OS, FFS and DMFS rates were 70.4% vs. 58.4% (P = 0.010), 77.5% vs. 65.2% (P = 0.013) and 83.6% vs. 73.6% (P = 0.047), respectively. In patients with a MPTD ≤ 30 mm, 5-year LRFS in T1, T2, T3 and T4 was 100%, 100%, 88.9% and 100% (P = 0.172). CONCLUSIONS: Our data suggest that MPTD is an independent prognostic factor in NPC, and incorporation of MPTD might lead to a further refinement of T staging.

U-Net-Based Medical Image Segmentation.

Deep learning has been extensively applied to segmentation in medical imaging. U-Net proposed in 2015 shows the advantages of accurate segmentation of small targets and its scalable network architecture. With the increasing requirements for the performance of segmentation in medical imaging in recent years, U-Net has been cited academically more than 2500 times. Many scholars have been constantly developing the U-Net architecture. This paper summarizes the medical image segmentation technologies based on the U-Net structure variants concerning their structure, innovation, efficiency, etc.; reviews and categorizes the related methodology; and introduces the loss functions, evaluation parameters, and modules commonly applied to segmentation in medical imaging, which will provide a good reference for the future research.

Research on DCE-MRI Images Based on Deep Transfer Learning in Breast Cancer Adjuvant Curative Effect Prediction.

Breast cancer is a serious threat to women's physical and mental health. In recent years, its incidence has been on the rise and it has become the top female malignant tumor in China. At present, adjuvant chemotherapy for breast cancer has become the standard mode of breast cancer treatment, but the response results usually need to be completed after the implementation of adjuvant chemotherapy, and the optimization of the treatment plan and the implementation of breast-conserving therapy need to be based on accurate estimation of the pathological response. Therefore, to predict the efficacy of adjuvant chemotherapy for breast cancer patients is to find a predictive method that is conducive to individualized choice of chemotherapy regimens. This article introduces the research of DCE-MRI images based on deep transfer learning in breast cancer adjuvant curative effect prediction. Deep transfer learning algorithms are used to process images, and then, the features of breast cancer after adjuvant chemotherapy are collected through image feature collection. Predictions are made, and the research results show that the accuracy of the prediction reaches 70%.

Multivariable Models Based on Baseline Imaging Features and Clinicopathological Characteristics to Predict Breast Pathologic Response after Neoadjuvant Chemotherapy in Patients with Breast Cancer.

Introduction: Currently, the accurate evaluation and prediction of response to neoadjuvant chemotherapy (NAC) remains a great challenge. We developed several multivariate models based on baseline imaging features and clinicopathological characteristics to predict the breast pathologic complete response (pCR). Methods: We retrospectively collected clinicopathological and imaging data of patients who received NAC and subsequent surgery for breast cancer at our hospital from June 2014 till September 2020. We used mammography, ultrasound, and magnetic resonance imaging (MRI) to investigate the breast tumors at baseline. Results: A total of 308 patients were included and 111 patients achieved pCR. The HER-2 status and Ki-67 index were significant factors for pCR on univariate analysis and in all multivariate models. Among the prediction models in this study, the ultrasound plus MRI model performed best, producing an area under curve of 0.801 (95% CI 0.749-0.852), a sensitivity of 0.797, and a specificity of 0.676. Conclusion: Among the multivariable models constructed in this study, the ultrasound plus MRI model performed best in predicting the probability of pCR after NAC. Further validation is required before it is generalized.

Isolation, identification, and characterization of small bioactive peptides from Lactobacillus GG conditional media that exert both anti-Gram-negative and Gram-positive bactericidal activity.

OBJECTIVES: Diarrheal diseases remain a major human plague that still claim millions of lives every year. Probiotics, including Lactobacillus GG (LGG), are known to have a beneficial effect on diarrheal diseases, but their mechanism of action has not yet been completely established. Therefore, the main objective of this work was to identify and characterize moieties elaborated by LGG that exert antibacterial activity. MATERIALS AND METHODS: Lactobacillus GG conditional media was subjected to liquid chromatography/mass spectrometry. The identified peptides were synthesized by Symphony peptide synthesizer and purified by HPLC using Dynamax reverse-phase C18 column. Using A600 measurement and tested for their antibacterial activity. RESULTS: We identified 7 small peptides from LGG cultured media, 2 of which are NPSRQERR and PDENK, retained the antibacterial activity detected with LGG conditional media. The antibacterial activity was exerted against both Gram-negative (Escherichia coli EAEC 042 and Salmonella typhi) and, with less potency, Gram-positive (Staphylococcus aureus) bacteria. CONCLUSIONS: Lactobacillus GG elaborates small peptides showing various degrees of antibacterial activity. NPSRQERR showed the most potent antibacterial effect that was detected both in Gram-negative and Gram-positive microorganisms. These synthetic peptides may represent novel tools for the treatment of bacterial infectious diseases.

Prognostic value of gross tumor regression and plasma Epstein Barr Virus DNA levels at the end of intensity-modulated radiation therapy in patients with nasopharyngeal carcinoma.

PURPOSE: To assess gross tumor regression and plasma Epstein-Barr virus (EBV)-DNA levels at the end of intensity-modulated radiation therapy (IMRT) and its prognostic impact on patients with nasopharyngeal carcinoma (NPC). PARTICIPANTS AND METHODS: In total, 397 patients with non-metastatic, histologically confirmed NPC were retrospectively examined. All patients underwent magnetic resonance imaging of the nasopharynx and neck, and plasma EBV DNA assays before treatment and at the end of IMRT. RESULTS: The estimated 5-year loco-regional, local and regional relapse-free survival rates for patients with complete response (CR) and non-CR of the total tumor, primary tumor and metastatic lymph nodes at the end of IMRT were 94.9% vs. 85.8%, 96.6% vs. 87.3%, and 98.7% vs. 89.8%, respectively (P < 0.05). The estimated 5-year loco-regional relapse-free survival (LRRFS) rates for patients with persistent tumor with and without boost irradiation were 95.3% vs. 83%, respectively (P = 0.034). The estimated 5-year overall survival (OS), failure-free survival (FFS) and distant metastasis-free survival (DMFS) rates for patients with negative and positive plasma EBV DNA at the end of IMRT were 83.1% vs. 50.3%, 81.5% vs. 49.3%, and 87.6% vs. 61.5%, respectively (P < 0.001). Multivariate analyses indicated that regression of the total tumor and boost irradiation was an independent predictor of LRRFS, and plasma EBV DNA levels were independent predictors of OS, FFS and DMFS. CONCLUSIONS: Gross tumor regression and plasma EBV DNA levels at the end of IMRT served as predictors of poor prognosis for patients with NPC. The patients with persistent tumor and/or positive plasma EBV DNA might require timely strengthening treatment.

Inflammatory myofibroblastic tumours of the spleen and liver.

Inflammatory myofibroblastic tumour (IMT) is a rare neoplasm. Generally, these lesions have a benign behaviour, but the possibility of malignant transformation exists. We report the rare case of a 43-year-old woman with metachronous IMTs in the spleen and the liver. The patient was treated with laparoscopic splenectomy and partial hepatectomy. The patient recovered uneventfully. This case emphasizes the difficulties in diagnosis and the possibility of a metachronous occurrence.

Zonula occludin toxin, a microtubule binding protein.

AIM:To investigate the interaction of Zot with microtubule.METHODS:Zot affinity column was applied to purify Zot-binding protein(s) from crude intestinal cell lysates. After incubation at room temperature, the column was washed and the proteins bound to the Zot affinity column were eluted by step gradient with NaCl (0.3molcenter dotL(-1) -0.5molcenter dotL(-1)). The fractions were subjected to 6.0%-15.0% (w/v) gradient SDS-PAGE and then transferred to PVDF membrane for N-terminal sequencing.Purified Zot and tau protein were blotted by using anti-Zot or anti tau antibodies. Finally, purified Zot was tested in an in vitro tubulin binding assay.RESULTS:Fractions from Zot affinity column yielded two protein bands with a M(r) of 60kU and 45kU respectively. The Nterminal sequence of the 60kU band resulted identical to beta-tubulin. Zot also crossreacts with antitau antibodies. In the in vitro tubulin binding assay, Zot coprecipitate with Mt, further suggesting that Zot possesses tubulin-binding properties.CONCLUSION:Taken together, these results suggest that Zot regulates the permeability of intestinal tight junctions by binding to intracellular Mt, with the subsequent activation of the intracellular signaling leading to the permeabilization of intercellular tight junctions.