Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

ObjectiveThis study aimed to analyze the difference in setup error before and after correction of systematic error. To determine the most appropriate image-guided strategy during HT treatment， we use different scanning ranges and image-guidance frequencies in patients with nasopharyngeal carcinoma （NPC） treated with helical tomotherapy （HT）. MethodsFifteen patients with NPC who received HT treatment in Sun Yat-sen University Cancer Center from October 2019 to February 2020 were selected. Megavoltage computed tomography （MVCT） scanning was performed before each treatment. After five times of radiotherapy， system-error correction was performed to adjust the setup center. The setup errors before and after the correction of systematic errors， as well as the setup errors of different scanning ranges and different scanning frequencies， were collected for analysis and comparison. ResultsWhen comparing the setup errors before and after the correction of systematic error， the differences in setup errors in the left–right （LR）， superior–inferior （SI）， and anterior–posterior （AP） directions were statistically significant （P<0.05）.The different scanning ranges of "nasopharynx + neck" and "nasopharynx" were compared， and a statistically significant difference was found in yaw rotational errors （P<0.05）. In the comparison of daily and weekly scan frequency after system-error correction， a significant difference was found in AP direction （P<0.05）. ConclusionDuring radiotherapy for NPC， the systematic error can be corrected according to the first five setup errors， and then small-scale scanning was selected for image-guided radiotherapy every day.

Humans ; Child ; Lymphoma, Large B-Cell, Diffuse/pathology*

ObjectivePeriprosthetic joint infections （PJI） are currently the most calamitous complication after arthroplasty. Although achievements have been made in many markers for the diagnosis of PJI， the lack of a gold standard remains a great obstacle for early diagnosis. This study aimed to investigate the association between coagulation markers and the development of PJI in patients undergoing revision total joint arthroplasty （TJA）. MethodsWe conducted a retrospective cohort study with a total of 2 517 patients who underwent hip or knee arthroplasties from January 2011 to January 2022 （2 394 with primary TJA， 87 with aseptic revision and 36 with PJI）. We applied univariate analysis and multivariate logistic regression to analyze differences of coagulation factors between primary TJA and aseptic revision or PJI group. Receiver operating characteristic （ROC） curve and area under the curve （AUC） were used to measure the diagnostic value of coagulation factors in predicting PJI. ResultsCoagulation factors and their ratios including plasma fibrinogen （FBG）， prothrombin time （PT）， thrombin time （TT）， activated partial thromboplastin time （APTT）， platelet （PLT）， mean platelet volume （MPV）， platelet distribution width （PDW）， plateletcrit （PCT）， PLT / MPV， PLT / PDW and PLT / PCT were included in this study. High FGB level was strongly correlated with the risk of PJI compared to other coagulation factors. The optimal threshold value of FBG was 4.53 g/L with a sensitivity of 47.22%， a specificity of 93.07% （Primary TJA group vs. PJI group）. Similarly， the optimal threshold value of FBG was 4.44 g/L with a sensitivity of 47.22%， a specificity of 95.40% between the other two groups （Aseptic revision group vs. PJI group）. ROC curve analysis demonstrated moderate diagnostic performance of FBG （AUC value）， indicating a potential to be a diagnostic marker for PJI. ConclusionsFBG is significantly correlated with PJI and it can be used as a potential non-invasive marker for early detection. It may serve as a safe and cost-effective tool for assessing PJI in clinical work.

In this study, we investigated the anti-osteoporotic activity and mechanism of action of extract of Panax quiquefolium L. based on zebrafish model combined with metabolomics technology. A zebrafish model of prednisolone-induced osteoporosis was used to compare the anti-osteoporotic activity of Panax quiquefolium L., and the expression of osteoblast-associated genes and osteoclast-associated genes in zebrafish was detected by quantitative real-time PCR (qRT-PCR), using bone fluorescence area and fluorescence density as evaluation indexes. Metabolomics based on ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS) was used to explore the change patterns of biomarkers and the metabolic pathways affected. The results showed that the 50% ethanol extracts of Panax quiquefolium L. from Jilin, Canada, Wenden and the United States can significantly improve the bone fluorescence area of zebrafish compared with model group. Furthermore, four sources 50% ethanol extracts of Panax quiquefolium L. except United States also can significantly improve the bone fluorescence density of zebrafish. In addition, PCR showed that extract of Panax quiquefolium L. can significantly up-regulated the expression of vitamin D receptor b (vdrb), collagen type I α2 (col1a2) and cysteine-rich acidic secreted protein (sparc) genes, and down-regulated the expression of matrix metalloproteinase 9 (mmp9), anti-tartrase acid phosphatase (trap) and cathepsin K (ctsk) genes. Metabolomic analysis identified 24 key differential metabolites. Furthermore, pathway analysis showed that Panax quiquefolium L. could regulate the levels of 10 key biomarkers by participating in purine metabolism, tricarboxylic acid cycle and pentose phosphate metabolism and improve the osteoporosis status of zebrafish. This study preliminically revealed the anti-osteoporosis mechanism of 50% ethanol extract from Panax quiquefolium L. through multi-component, multi-target and multi-pathway and also provides theoretical basis for clinical development and utilization of anti-osteoporosis products of Panax quiquefolium L. This experiment was approved by the Experimental Animal Welfare Ethics Committee of the Institute of Biology, Shandong Academy of Sciences (approval number: SWS20181002).

Humans ; Child ; Lymphoma, Large-Cell, Anaplastic ; Neoplasm Recurrence, Local ; Prognosis ; Hodgkin Disease