Clinicopathological Characteristics of Oral Squamous Cell Carcinoma at the Central Referral and Teaching Hospital in West Java, Indonesia.

Purpose: This study aimed to investigate the clinicopathological characteristics of oral squamous cell carcinoma (OSCC) patients and analyze the relationship between the degree of differentiation and factors including age, sex, stage, and tumor location in West Java, Indonesia. Patients and Methods: A retrospective cross-sectional study was conducted at the Central Referral and Teaching Hospital in West Java, Indonesia. The data were collected by reviewing medical records with International Classification of Diseases (ICD) codes C00-C06 from 2016 to 2023. Descriptive statistics were employed to summarize the clinicopathological characteristics of OSCC patients. Chi-square, rank Spearman tests, and contingency correlation coefficients were used to analyze the relationship between the degree of differentiation and various factors, such as age, sex, stage, and tumor location of OSCC. Results: Out of the 627 oral cancer patients, 70.49% were diagnosed with OSCC with a gender distribution of 45.7% males and 54.3% females, predominantly within the age range of 30-49 (37.2%). Most OSCC cases were stage IV (37.7%), with the tongue identified as the most common site (68.8%). A consistent trend of higher well-differentiated and moderately differentiated OSCC by age and gender was observed. Statistical analysis revealed no significant correlation between age, gender, tumor location, and the degree of OSCC differentiation (p>0.05). However, a statistically significant correlation was identified between the degree of OSCC differentiation and stage (p<0.001, r=0.460). Conclusion: There is a correlation between the degree of differentiation of OSCC and stage, suggesting significant prognostic implications that can aid in treatment planning and outcome prediction. However, further studies are needed due to the lack of comprehensive data on risk factors and survival rates of oral cancer patients, which is essential for enhancing prevention and treatment strategies for OSCC.

[Gastroenteropancreatic neuroendocrine neoplasms-Surgery in a multimodal concept]. / Gastroenteropankreatische neuroendokrine Neoplasien ­ Chirurgie im multimodalen Konzept.

Gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN) are mainly found in the small intestine and pancreas. The course of the disease in patients is highly variable and depends on the degree of differentiation (G1-G3) of the neoplasm. The potential for metastasis formation of GEP-NEN is high even with good differentiation (G1). Lymph node metastases and, in many cases, liver metastases are also often found. Less common are bone metastases or peritoneal carcinomas. The treatment of these GEP-NENs is surgical, whenever possible. If an R0 resection with removal of all lymph node and liver metastases is successful, the prognosis of the patients is excellent. Patients with diffuse liver or bone metastases can no longer be cured by surgery alone. The long-term survival of these patients is nowadays possible due to the availability of drugs (e.g., somatostatin analogues, tyrosine kinase inhibitors), peptide receptor radionuclide therapy (PRRT) and liver-directed procedures, with a good quality of life.

Intravoxel Incoherent Motion Diffusion-weighted Magnetic Resonance Imaging combined with Texture Analysis in Predicting the Histological Grades of Rectal Adenocarcinoma.

PURPOSE: To evaluate the predictive value of 3.0T MRI Intravoxel Incoherent motion diffusion-weighted magnetic resonance imaging (IVIM-DWI) combined with texture analysis (TA) in the histological grade of rectal adenocarcinoma. METHODS: Seventy-one patients with rectal adenocarcinoma confirmed by pathology after surgical resection were collected retrospectively. According to pathology, they were divided into a poorly differentiated group (n=23) and a moderately differentiated group (n=48). The IVIM-DWI parameters and TA characteristics of the two groups were compared, and a prediction model was constructed by multivariate logistic regression analysis. ROC curves were plotted for each individual and combined parameter. RESULTS: There were statistically significant differences in D and D* values between the two groups (P < 0.05). The three texture parameters SmallAreaEmphasis, Median, and Maximum had statistically significant differences between groups (P = 0.01, 0.004, 0.009, respectively). The logistic regression prediction model showed that D*, the median, and the maximum value were significant independent predictors, and the AUC of the regression prediction model was 0.860, which was significantly higher than other single parameters. CONCLUSION: 3.0T MRI IVIM-DWI parameters combined with TA can provide valuable information for predicting the histological grades of rectal adenocarcinoma one week before the operation.

MR imaging characteristics of different pathologic subtypes of esophageal carcinoma.

OBJECTIVES: To describe the specific MRI characteristics of different pathologic subtypes of esophageal carcinoma (EC) METHODS: This prospective study included EC patients who underwent esophageal MRI and esophagectomy between April 2015 and October 2021. Pathomorphological characteristics of EC such as localized type (LT), ulcerative type (UT), protruding type (PT), and infiltrative type (IT) were assessed by two radiologists relying on the imaging characteristics of tumor, especially the specific imaging findings on the continuity of the mucosa overlying the tumor, the opposing mucosa, mucosa linear thickening, and transmural growth pattern. Intraclass correlation coefficients (ICC) were calculated for the consistency between two readers. The associations of imaging characteristics with different pathologic subtypes were assessed using multilogistic regression model (MLR). RESULTS: A total of 201 patients were identified on histopathology with a high inter-reader agreement (ICC = 0.991). LT showed intact mucosa overlying the tumor. IT showed transmural growth pattern extending from the mucosa to the adventitia and a "sandwich" appearance. The remaining normal mucosa on the opposing side was linear and nodular in UT. PT showed correlation with T1 staging and grade 1; IT showed correlation with T3 staging and grades 2-3. Four MLR models showed high predictive performance on the test set with AUCs of 0.94 (LT), 0.87 (PT), 0.96 (IT), and 0.97 (UT), respectively, and the predictors that contributed most to the models matched the four specific characteristics. CONCLUSIONS: Different pathologic subtypes of EC displayed specific MR imaging characteristics, which could help predict T staging and the degree of pathological differentiation. CLINICAL RELEVANCE STATEMENT: Different pathologic subtypes of esophageal carcinoma displayed specific MR imaging characteristics, which correspond to differences in the degree of differentiation, T staging, and sensitivity to radiotherapy, and could also be one of the predictive factors of cause-specific survival and local progression-free rates. KEY POINTS: Different types of EC had different characteristics on MR images. A total of 91/95 (96%) LTEC showed intact mucosa over the tumor, while masses or nodules are specific to PTEC; 21/27 (78%) ITEC showed a "sandwich" sign; and 33/35 (60%) UTEC showed linear and nodular opposing mucosa. In the association of tumor type with degree of differentiation and T staging, PTEC was predominantly associated with T1 and grade 1, and ITEC was associated with T3 and grades 2-3, while LTEC and UECT were likewise primarily linked with T2-3 and grades 2-3.

Correlation analysis of contrast-enhanced ultrasound Liver Imaging Reporting and Data System classification with hepatocellular carcinoma differentiation and Ki-67 index / 中华超声影像学杂志

Objective:To investigate the correlation of hepatocellular carcinoma (HCC) classified by contrast-enhanced ultrasound (CEUS) Liver Imaging Data and Report System (LI-RADS) with differentiation degree and Ki-67 index.Methods:A multicenter, retrospective study was conducted.The clinical and CEUS imaging data of 208 patients with 208 HCC lesions from December 2017 to December 2020 in China CEUS database were included and analyzed. According to the CEUS LI-RADS version 2017 proposed by the American College of Radiology, the HCC was classified. The diagnosis and pathological information of all lesions were confirmed by pathology. The differentiation degree of HCC and the distribution of Ki-67 index in different LI-RADS categories were evaluated, and their correlation was analyzed.Results:The degree of differentiation and Ki-67 index among HCC of different CEUS LI-RADS were statistically significant ( P<0.001, P=0.009). LI-RADS M HCC was more likely to be poorly differentiated and showed a higher Ki-67 index. The category of LI-RADS was positively correlated with the degree of tumor differentiation (tau-b=-0.250, P<0.001) and the Ki-67 index (tau-b=0.178, P=0.002), that is, the higher the category of LI-RADS, the lower differentiation degree and the higher the Ki-67. Conclusions:The CEUS LI-RADS classification of HCC is correlating with the degree of differentiation and Ki-67 index.

Classification of multi-differentiated liver cancer pathological images based on deep learning attention mechanism.

PURPOSE: Liver cancer is one of the most common malignant tumors in the world, ranking fifth in malignant tumors. The degree of differentiation can reflect the degree of malignancy. The degree of malignancy of liver cancer can be divided into three types: poorly differentiated, moderately differentiated, and well differentiated. Diagnosis and treatment of different levels of differentiation are crucial to the survival rate and survival time of patients. As the gold standard for liver cancer diagnosis, histopathological images can accurately distinguish liver cancers of different levels of differentiation. Therefore, the study of intelligent classification of histopathological images is of great significance to patients with liver cancer. At present, the classification of histopathological images of liver cancer with different degrees of differentiation has disadvantages such as time-consuming, labor-intensive, and large manual investment. In this context, the importance of intelligent classification of histopathological images is obvious. METHODS: Based on the development of a complete data acquisition scheme, this paper applies the SENet deep learning model to the intelligent classification of all types of differentiated liver cancer histopathological images for the first time, and compares it with the four deep learning models of VGG16, ResNet50, ResNet_CBAM, and SKNet. The evaluation indexes adopted in this paper include confusion matrix, Precision, recall, F1 Score, etc. These evaluation indexes can be used to evaluate the model in a very comprehensive and accurate way. RESULTS: Five different deep learning classification models are applied to collect the data set and evaluate model. The experimental results show that the SENet model has achieved the best classification effect with an accuracy of 95.27%. The model also has good reliability and generalization ability. The experiment proves that the SENet deep learning model has a good application prospect in the intelligent classification of histopathological images. CONCLUSIONS: This study also proves that deep learning has great application value in solving the time-consuming and laborious problems existing in traditional manual film reading, and it has certain practical significance for the intelligent classification research of other cancer histopathological images.

Classification and Grading Systems in Gastric Adenocarcinomas.

Gastric adenocarcinomas are lesions that raise important issues in clinical practice, due to their incidence and biological behavior. Over time, various systems have been used for classifying and grading of gastric adenocarcinomas, in the hope of increasing the diagnostic accuracy. In this study we statistically analyzed 112 cases of gastric adenocarcinomas in relation to different classification and grading systems, in order to identify their efficacy and concordance in the histopathological diagnosis. The results indicated a significant association of the Lauren and World Health Organization 2019 classifications and also between these and the three-tier and two-tier grading systems, which supports their practical utility in establishing the diagnosis and assessment of the tumor aggressiveness, for the differentiated therapy.

Quantitative analysis of the post-vascular phase of contrast-enhanced ultrasound in evaluating the differentiation of hepatocellular carcinoma / 中华超声影像学杂志

Objective:To investigate the diagnostic value of the post-vascular phase of contrast-enhanced ultrasound in the differentiation of hepatocellular carcinoma (HCC).Methods:The contrast-enhanced ultrasound data of 115 patients who were admitted to Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology for liver space-occupying lesions from September 2020 to September 2021 were retrospectively analyzed. All patients underwent contrast-enhanced ultrasound with perfluorobutane microspheres for injection within 1 week before operation and were confirmed to be HCC by postoperative pathology. According to the pathological results, the lesions were divided into two groups—a well differentiated group and a poorly differentiated group. The time intensity curves of the regions of interest were drawn to obtain the quantitative parameters of arterial phase and the post-vascular phase. The diagnostic performance of each quantitative parameter in differentiating the two groups of lesions was evaluated and the cut-off value was calculated.Results:117 lesions from 115 patients were finally included in the study, including 70 lesions in the well differentiated group and 47 lesions in the poorly differentiated group. There were no significant differences in the initial growth time, peak time, rise time and the absolute value of peak intensity of lesions between the two groups in the arterial phase (all P>0.05). In the post-vascular phase(12 min), the absolute value of enhancement intensity, intensity ratio and intensity difference of the well differentiated group were lower than those in the poorly differentiated group, and the difference was statistically significant (all P<0.01). The sensitivity and specificity of the absolute value of enhancement intensity<56.117 dB, intensity ratio<1.212, intensity difference<9.184 dB to distinguish the HCC lesions as well-differentiated group were 48.9% and 80.0%, 87.2% and 77.1%, 89.4% and 75.7%, respectively. Conclusions:The quantitative analysis of the post-vascular phase of contrast-enhanced ultrasound is helpful to identify the differentiation degree of HCC and has certain clinical application value.

Clinical value of contrast-enhanced computed tomography (CECT) combined with contrast-enhanced ultrasound (CEUS) for characterization and diagnosis of small nodular lesions in liver.

OBJECTIVES: To explore the clinical value of contrast-enhanced computed tomography (CECT) combined with contrast-enhanced ultrasound (CEUS) for characterization and diagnosis of small nodular lesions in the liver and investigate the association between such small nodular lesions and the degree of tumor differentiation. METHODS: Combined imaging modalities were performed on 120 patients who were admitted by Linyi Maternal and Child Health hospital from December 2018 to December 2020 and diagnosed with hepatic nodular lesions. The CT scans were interpreted by two senior imageologists while the ultrasound scans were analyzed by two senior sonographers. A comparative analysis was carried out on different scan modes and the postoperative or post-puncture pathological results using the t-test, the χ2 test, and the Pearson's correlation analysis. RESULTS: Compared to the pathological results, definite diagnoses of 55 malignant cases were made using CECT alone, with the coincidence rate of 78.6%; CECT combined with CEUS formed correct diagnoses in 64 cases, and the coincidence rate was up to 91.4%. The difference between the two scan modes was statistically significant (p= 0.03). Based on pathological diagnosis, seventy out of the 120 cases of small nodular lesions were identified as malignant, while the other 50 cases were benign. The single imaging modality diagnosed 63 malignant and 57 benign nodules, whereas the combined modalities identified 68 malignancies and 52 benign conditions. Compared to CECT as a single imaging modality, the combined modalities showed a higher degree of sensitivity and accuracy, and the difference was statistically significant (sensitivity: p= 0.03; accuracy: p= 0.02); in the malignant cases, the magnitudes of contrast enhancement of CT and ultrasound imaging decreased with an increase in the degree of differentiation, indicating a negative correlation between these factors. CONCLUSIONS: CECT combined with CEUS has a higher coincidence rate, greater sensitivity, and better diagnostic accuracy when being used for characterization and diagnosis of small nodular lesions in the liver. A higher degree of tumor differentiation means a decreased magnitude of contrast enhancement and a blurrier boundary, which indicates that CECT and CEUS are complementary to each other in classifying malignant liver nodules. The use of the combined imaging modalities shows clinical value for characterizing small liver nodules and predicting the degree of malignancy.

Traditional in vitro strategies for sustainable production of bioactive compounds and manipulation of metabolomic profile in medicinal, aromatic and ornamental plants.

MAIN CONCLUSION: Precursor feeding, elicitation and culture medium parameters are traditional in vitro strategies to enhance bioactive compounds of medicinal, aromatic, and ornamental plants (MAOPs). Machine learning can help researchers find the best combination of these strategies to increase the secondary metabolites content of MAOPs. Many requirements for human life, from food, pharmaceuticals and cosmetics to clothes, fuel and building materials depend on plant-derived natural products. Essential oils, methanolic and ethanolic extracts of in vitro undifferentiated callus and organogenic cultures of medicinal, aromatic, and ornamental plants (MAOPs) contain bioactive compounds that have several applications for various industries, including food and pharmaceutical. In vitro culture systems provide opportunities to manipulate the metabolomic profile of MAOPs. Precursors feeding, elicitation and culture media optimization are the traditional strategies to enhance in vitro accumulation of favorable bioactive compounds. The stimulation of plant defense mechanisms through biotic and abiotic elicitors is a simple way to increase the production of secondary metabolites in different in vitro culture systems. Different elicitors have been applied to stimulate defense machinery and change the metabolomic profile of MAOPs in in vitro cultures. Plant growth regulators (PGRs), stress hormones, chitosan, microbial extracts and physical stresses are the most applied elicitors in this regard. Many other chemical tolerance-enhancer additives, such as melatonin and proline, have been applied along with stress response-inducing elicitors. The use of stress-inducing materials such as PEG and NaCl activates stress tolerance elicitors with the potential of increasing secondary metabolites content of MAOPs. The present study reviewed the state-of-the-art traditional in vitro strategies to manipulate bioactive compounds of MAOPs. The objective is to provide insights to researchers involved in in vitro production of plant-derived natural compounds. The present review provided a wide range of traditional strategies to increase the accumulation of valuable bioactive compounds of MAOPs in different in vitro systems. Traditional strategies are faster, simpler, and cost-effective than other biotechnology-based breeding methods such as genetic transformation, genome editing, metabolic pathways engineering, and synthetic biology. The integrate application of precursors and elicitors along with culture media optimization and the interpretation of their interactions through machine learning algorithms could provide an excellent opportunity for large-scale in vitro production of pharmaceutical bioactive compounds.

Decision Maker Profiling Using Their Mental Behavior Pattern.

This study describes a method to assist the task of predicting the result of the decision-making process of an individual based on psychological and emotional aspects and using artificial intelligence (AI) techniques. This study presents indicators created for profile identification, which are organized in primary and circumstantial categories. These indicators are merged according to the ultimate purpose of profile identification, including the expected behavioral pattern for a person who performs a decision-making process. The person behavior hypothesis was successfully tested and can be approximated by an indicator such as mental functioning pattern, and the mental functioning pattern hypothesis can signal the most likely decisions of an individual. Four debtor decision variables were assessed in a debt negotiation process, in order to validate the method, which is applicable to other decision-making domains. The best signaling of the most likely decision of the debtor was seven times greater than that of a random prediction, while the gain of the worst decision signaling variable was 20%.

Development and Validation of the Predictive Model for Esophageal Squamous Cell Carcinoma Differentiation Degree.

The diagnosis of the degree of differentiation of tumor cells can help physicians to make timely detection and take appropriate treatment for the patient's condition. In this study, the original dataset is clustered into two independent types by the Kohonen clustering algorithm. One type is used as the development sets to find correlation indicators and establish predictive models of differentiation, while the other type is used as the validation sets to test the correlation indicators and models. In the development sets, thirteen indicators significantly associated with the degree of differentiation of esophageal squamous cell carcinoma are found by the Kohonen clustering algorithm. Thirteen relevant indicators are used as input features and the degree of tumor differentiations is used as output. Ten classification algorithms are used to predict the differentiation of esophageal squamous cell carcinoma. Artificial bee colony-support vector machine (ABC-SVM) predicts better than the other nine algorithms, with an average accuracy of 81.5% for the 10-fold cross-validation. Based on logistic regression and ReliefF algorithm, five models with the greater merit for the degree of differentiation are found in the development sets. The AUC values of the five models are 0.672, 0.628, 0.630, 0.628, and 0.608 (P < 0.05). The AUC values of the five models in the validation sets are 0.753, 0.728, 0.744, 0.776, and 0.868 (P < 0.0001). The predicted values of the five models are constructed as the input features of ABC-SVM. The accuracy of the 10-fold cross-validation reached 82.0 and 86.5% in the development sets and the validation sets, respectively.

Prognostic Value of Neutrophil-Lymphocyte Ratio and Platelet-Lymphocyte Ratio in Head and Neck Malignancies.

To study the prognostic significance of neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) in head and neck cancers. The study included 170 cases of histopathologically diagnosed head and neck cancer patients and 80 control subjects. NLR and PLR of patients with head and neck cancers were compared to the control group. The correlation between NLR and PLR values and factors such as age, gender, duration of symptoms, site of tumour, histological type, histological grading, T-category, N-category and TNM stages in cancer patients were analysed. NLR and PLR were statistically higher in cancer patients compared to control. There was a non-significant increase in both NLR and PLR with advancing degree of differentiation and TNM Stages of the cancer patients. A significant increase in NLR and PLR with increasing T Categories and increasing N Categories of head and neck cancer patients was obtained. NLR and PLR can be used to estimate tumour prognosis in head and neck cancers. Increased NLR and PLR values can be used as a marker for poor prognosis. However further studies with larger study groups including treatment response and surveillance should be carried out to corroborate these results.

Expression of RUNX3 gene and miR-363 in colorectal cancer and the relationship with clinicopathological features.

Expression of RUNX3 gene and miR-363 in colorectal cancer was studied to explore its relationship with clinicopathological characteristics of colorectal cancer and to analyze the value of RUNX3 combined with miR-363 in the diagnosis of colorectal cancer. In total, 85 patients diagnosed with colorectal cancer in the First Peoples Hospital of Xiaoshan Hangzhou from March 2014 to July 2016 were the experiment group. Seventy healthy individuals who underwent physical examination were the control group. RT-qPCR was used to detect the expression levels of RUNX3 gene and miR-363 in peripheral blood of the two groups. The relationship between the expression of RUNX3 and miR-363 with its clinicopathological characteristics was analyzed as well. The expression of RUNX3 in the experiment group was significantly lower than that in the control group (P<0.05). The expression level of miR-363 was significantly lower than in the control group (P<0.05). However, there was a correlation with tumor size, degree of differentiation, lymph node metastasis, depth of invasion and clinical stages (P<0.05). RUNX3 and miR-363 were significantly positively correlated with the degree of differentiation (r=0.7381, r=0.5375; P<0.05); RUNX3 and miR-363 were significantly negatively correlated with clinical stages (r=-0.7167, -0.6700; P<0.05). The area under the ROC curve of the combined test was larger than the single test. The expression of RUNX3 gene and miR-363 in peripheral blood of patients with colorectal cancer was lower than in the normal controls. The low expression of RUNX3 and miR-363 was closely related to various biological behaviors of colorectal cancer. A potential reference is provided for the evaluation of patients with colorectal cancer and expected to have an important guiding effect in the treatment of colorectal cancer. Moreover, combined test of RUNX3 and miR-363 has important significance in the diagnosis and treatment evaluation of colorectal cancer.

Expression and correlation of miR-124 and miR-126 in breast cancer.

The expression of micro ribonucleic acid (miR)-124 and miR-126 in different stages of breast cancer (BC) and their correlation were investigated to analyze the role of miR-124 and miR-126 in the occurrence and development of BC. BC tissues of 83 BC patients treated in First Teaching Hospital of Tianjin University of Traditional Chinese Medicine from March 2016 to January 2018 were selected as the research group, while the corresponding para-carcinoma normal tissues were selected as the control group. The relative expression levels of miR-124 and miR-126 in both groups were detected via reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and the miR-124 and miR-126 expression asociated with clinicopathological parameters of patients and the correlation between miR-124 and miR-126 was analyzed. The relative expression levels of miR-124 and miR-126 in the research group were significantly lower than those in the control group (P<0.001). miR-124 and miR-126 in the research group were associated with clinicopathological parameters (clinical stage, degree of pathological differentiation and lymph node metastasis) of patients (P<0.001). According to Pearsons correlation analysis, there was a positive correlation between the relative expression levels of miR-124 and miR-126 in cancer tissues (r=0.497, P<0.001). The expression levels of miR-124 and miR-126 were downregulated in BC tissues, which were associated with clinicopathological parameters (clinical stage, degree of pathological differentiation and lymph node metastasis). There was a positive correlation between the expression levels of miR-124 and miR-126 in BC tissues. Thus, miR-124 and miR-126 may be involved in the occurrence, development, invasion and metastasis of BC, and both can be used as targeted biological indexes for treatment of BC.

Psychotherapy and Artificial Intelligence: A Proposal for Alignment.

Brief Psychotherapy assists patients to become aware and change their behavior when facing an immediate emotional conflict, and to implement a transformation process through actions of listening, observing, increasing awareness and making interventions. Therapeutic work employs tools and techniques to trigger a process of change, emphasizing cognitive and affective understanding. This article presents an approach that combines Psychology and Artificial Intelligence with the purpose of enhancing psychotherapy with computer-implemented tools. This approach highlights the intersection between these two knowledge areas and shows how machine intelligence can help to characterize affective areas, construct genograms, determine degree of differentiation of self, investigate cognitive interaction patterns, and achieve self-awareness and redefinition. The conceptual proposal was implemented by a web application, and a sample of computer-aided analysis is presented.

Comparing the eighth and the seventh editions of the American Joint Committee on Cancer staging system and the Brigham and Women's Hospital alternative staging system for cutaneous squamous cell carcinoma: Implications for clinical practice.

BACKGROUND: The new eighth edition of the American Joint Committee on Cancer staging system (AJCC-8) incorporates changes regarding cutaneous squamous cell carcinoma (CSCC). OBJECTIVES: We aimed to compare the AJCC-8 staging system with the previous seventh edition of the AJCC staging system (AJCC-7) and the Brigham and Women's Hospital (BWH) alternative staging system to identify their usefulness and the utility of their risk factors in defining prognostic groups in CSCC. METHODS: A series of 186 CSCCs of the head and neck were retrospectively collected. All 3 staging systems were compared from the standpoint of their ability to predict poor prognosis. Binary logistic regression models were built to determine which risk factors were most relevant. RESULTS: Poor prognosis was mainly associated with stage T2 of the AJCC-7, with stages T2b/T3 of the BWH system, and with stage T3 of the AJCC-8. The AJCC-8 and the BWH staging systems displayed overlap with each another in predicting poor prognosis, and both were superior to the AJCC-7. The new risk factors incorporated into the AJCC-8 and the poor degree of differentiation were independently associated with poor outcome. LIMITATIONS: Retrospective study and few cases with bone invasion. CONCLUSIONS: The AJCC-8 is more distinctive, monotonous, and homogeneous than the AJCC-7 and shows some overlap with the BWH system in stratification of tumors.

The value of gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid enhanced T1 mapping in dysplastic nodule and hepatocellular carcinoma with different degrees of differentiation / 中华放射学杂志

Objective@#To explore the value of gadolinium-ethoxybenzyl-diethylenetriamine (Gd-EOB-DTPA) enhanced MRI T1 mapping in diagnosing and distinguishing dysplastic nodule (DN) and hepatocellular carcinoma (HCC) with different degrees of differentiation.@*Methods@#A retrospective study in the first affiliated Hospital of Guangxi Medical University from September 2015 to December 2017 was conducted. Seventy-one patients with HCC or DN (a total of 79 lesions) that confirmed by biopsy or surgical pathology findings. Seventy-nine lesions were divided into DN (n=10), well differentiated HCC (n=15), moderately differentiated HCC (n=36) and poorly differentiated HCC (n=18) according to histopathology. All the patients underwent plain MRI scan and Gd-EOB-DTPA-MRI T1 mapping before surgery or needle biopsy. The T1 values of each lesion and non-tumorous liver parenchyma were measured on 20 min hepatobiliary phase (HBP) T1 mapping after Gd-EOB-DTPA administration, respectively. The increment rate of T1 value in lesions relative to non-tumorous liver parenchyma were calculated. One-way ANOVA was used to compare the differences of T1 value and the increment rate of T1 value of DN and 3 groups of HCC with different degrees of differentiation. Spearman correlation was used to evaluate the correlation between T1 mapping parameters and the malignancy degree of DN and HCC. Area under the receiver operating characteristic (ROC) curves were used to evaluate the efficacy of T1 mapping parameters in the differential diagnosis of DN and HCC with different degree of differentiation.@*Results@#Significant differences were found in T1 value and increase rate of T1 value of DN and HCC with different degrees of differentiation (P< 0.05). The T1 value and increase rate of T1 value showed an increasing trend from DN to poorly differentiated HCC after enhancement. The T1 value and increase rate of T1 value were positively correlated with the malignancy of DN and HCC (r=0.418 and 0.634, P<0.01). There were significant differences in the increase rate of T1 value between well-differentiated HCC and moderately-differentiated, well-differentiated HCC and poorly-differentiated HCC, respectively (P<0.05). The area under ROC curve of T1 value and the increase rate of T1 value for differentiating DN from well-differentiated, moderately differentiated and poorly differentiated HCC was 0.933, 0.928, 0.939 and 0.867, 0.961, 0.961, respectively. The area under ROC curve of the increase rate of T1 value for differentiating well-differentiated HCC from moderately-differentiated, well-differentiated HCC from poorly-differentiated HCC was 0.770 and 0.844, respectively.@*Conclusions@#Gd-EOB-DTPA enhanced MRI combined with T1 mapping can provide valuable diagnostic information for identifying DN and HCC with different degrees of differentiation.

Tumor suppressor candidate 3 as a novel predictor for lymph node metastasis in lung cancer patients.

Tumor suppressor candidate 3 (TUSC3) was recently identified as a potential tumor suppressor gene in several cancer types. However, no data are currently available regarding the expression of TUSC3 in lung cancer. The present study investigated the expression of TUSC3 in patients with lung cancer and determined its association with the clinicopathological parameters of the disease. Cytoplasmic TUSC3 expression was evaluated by immunohistochemistry on tissue microarray slides, which included 35 small cell lung cancer (SCLC) specimens, 80 squamous cell lung cancer specimens (SCC), 80 adenocarcinoma lung cancer (ADC) specimens and 37 normal lung tissue specimens. Analysis showed significantly reduced TUSC3 expression in the SCLC patients, but not in the ADC and SCC patients, as compared with the normal controls. Additionally, TUSC3 expression in the patients with a degree of differentiation of 1-2 (well-moderately differentiated) was significantly higher than that in patients with a differentiation degree of 3-4 (poorly differentiated-undifferentiated). Further analysis showed that TUSC3 expression levels were negatively correlated with the degree of differentiation in the ADC and SCC patients. Notably, a marked decrease in TUSC3 expression was identified in the patients who were lymph node metastasis-positive (LNM+) compared with patients who were LNM-. Further analysis showed that significant differences in TUSC3 expression were identified among the different N stages (LNM status) in the SCLC, ADC and SCC patients. Correlation analysis also identified a negative correlation between TUSC3 expression and LNM in all three pathological types of lung cancer tested. Overall, these results indicated that a reduction in TUSC3 may be associated with a poorly-differentiated grade of lung cancer. Importantly, TUSC3 expression may be a useful predictor of LNM in lung cancer patients. A combined analysis of TUSC3 expression and the clinical variables will aid in predicting the incidence of LNM.

Role of diffusion-weighted magnetic resonance imaging and apparent diffusion coefficient values in the detection of gastric carcinoma.

OBJECTIVE: The study evaluated the applicability of diffusion-weighted magnetic resonance imaging (DW-MRI) and apparent diffusion coefficient (ADC) values in the diagnosis and staging of gastric carcinoma (GC). METHODS: From December, 2013 to December, 2014, 35 GC patients were selected from the Department of Oncology. Carcinomatous gastric tissues were collected as the case group, and normal gastric tissues were collected as the control group. The DW-MRI examination was performed on a 3.0-T GE Signa Excite MRI scanner. The ADC values of carcinomatous and normal gastric tissues were measured. A statistical meta-analysis was further performed. RESULTS: DW-MRI identified 75.0% (3/4) patients with T1, 75.0% (6/8) patients with T2, 86.4% (19/22) patients with T3, and 100.0% (1/1) patient with T4, showing an accuracy for T staging of 82.9% (29/35); identified 92.9% (13/14) patients of N0, 58.3% (7/12) patents of N1, 62.5% (5/8) patents of N2, and 100.0% (1/1) patients of N3, showing an accuracy for N staging of 74.3% (26/35). The average ADC value in the case group was apparently lower than the control group (P < 0.001); in the poorly differentiated group was lower than the moderately and well differentiated groups (F = 111.1, P < 0.001). Pairwise comparison of the average ADC value between the poorly, moderately and well differentiated groups showed statistical significance (all P < 0.05). Meta-analysis further confirmed a higher average ADC value in the case group than the control group (SMD = -4.136, 95% CI = -5.344~-2.928, P < 0.001). CONCLUSION: DW-MRI is proved to be an attractive, noninvasive, quantitative and useful technique in the diagnosis and staging of GC.