A novel model based on liver/spleen volumes and portal vein diameter on MRI to predict variceal bleeding in HBV cirrhosis.

OBJECTIVE: To develop a novel logistic regression model based on liver/spleen volumes and portal vein diameter measured on magnetic resonance imaging (MRI) for predicting oesophagogastric variceal bleeding (OVB) secondary to HBV cirrhosis. METHODS: One hundred eighty-five consecutive cirrhotic patients with hepatitis B undergoing abdominal contrast-enhanced MRI were randomly divided into training cohort (n = 130) and validation cohort (n = 55). Spleen volume, total liver volume, four liver lobe volumes, and diameters of portal venous system were measured on MRI. Ratios of spleen volume to total liver and to individual liver lobe volumes were calculated. In training cohort, univariate analyses and binary logistic regression analyses were to determine independent predictors. Performance of the model for predicting OVB constructed based on independent predictors from training cohort was evaluated by receiver operating characteristic (ROC) analysis, and was validated by Kappa test in validation cohort. RESULTS: OVB occurred in 42 and 18 individuals in training and validation cohorts during the 2 years' follow-up, respectively. An OVB prediction model was constructed based on the independent predictors including right liver lobe volume (RV), left gastric vein diameter (LGVD) and portal vein diameter (PVD) (odds ratio = 0.993, 2.202 and 1.613, respectively; p-values < 0.001 for all). The logistic regression model equation (-0.007 × RV + 0.79 × LGVD + 0.478 × PVD-6.73) for predicting OVB obtained excellent performance with an area under ROC curve of 0.907. The excellent performance was confirmed by Kappa test with K-value of 0.802 in validation cohort. CONCLUSION: The novel logistic regression model can be reliable for predicting OVB. KEY POINTS: • Patients with oesophagogastric variceal bleeding are mainly characterized by decreased right lobe volume, and increased spleen volume and diameters of portal vein system. • The right liver lobe volume, left gastric vein diameter and portal vein diameter are the independent predictors of oesophagogastric variceal bleeding. • The novel model developed based on the independent predictors performed well in predicting oesophagogastric variceal bleeding with an area under the receiver operating characteristic curve of 0.907.

Refined tumescent liposuction-curettage with pruning in small incisions for treatment of axillary bromhidrosis.

Axillary bromhidrosis is a widespread social problem in our society. Various modalities have been developed for the destruction or removal of the apocrine sweat glands to eliminate underarm odor. However, conventional surgical treatments often result in a high complication rate and frequent recurrence. In this study, we aimed to evaluate the effect of refined tumescent liposuction-curettage with pruning in small incisions as treatment for axillary bromhidrosis. Between July 2013 and April 2019, 110 patients (75 women and 35 men) with axillary bromhidrosis underwent refined tumescent liposuction-curettage with pruning. The results of eliminating underarm odor were evaluated by both the patients and doctors and rated as very satisfied (excellent), satisfied (good), slightly satisfied (fair), and not satisfied (poor). Postoperative complications, such as dehiscence, infection, wound contracture, cyst, subcutaneous hydrops, hematoma, or seroma, were also evaluated. Preoperative and postoperative histological examinations of axillary tissues were performed in two patients. In the subjective evaluation of 110 patients, 33 (30.0%) were very satisfied with the results, 70 (63.6%) were satisfied, and seven (6.4%) were slightly satisfied. The objective evaluation showed that 43 (39.1%) patients graded the results as excellent, whereas others graded the results as good. No serious complications occurred, except three patients with slight local subcutaneous hydrops and hematoma. Histologic examinations showed that the apocrine glands were significantly decreased or destroyed after the surgery. Refined tumescent liposuction-curettage with pruning in small incisions is an effective method for the treatment of axillary bromhidrosis.

Diameters of left gastric vein and its originating vein on magnetic resonance imaging in liver cirrhosis patients with hepatitis B: Association with endoscopic grades of esophageal varices.

AIM: To determine whether diameters of the left gastric vein (LGV) and its originating vein are associated with endoscopic grades of esophageal varices. METHODS: Ninety-eight liver cirrhotic patients with hepatitis B undergoing magnetic resonance (MR) portography, and upper gastrointestinal endoscopy for grading esophageal varices were enrolled. Diameters of the LGV and its originating vein - the splenic vein (SV) or portal vein (PV) - were measured on MR imaging. Statistical analyses were performed to identify the association of the diameters with the endoscopic grades. RESULTS: Univariate analysis showed that the SV was predominantly the originating vein of the LGV, and diameters of the LGV and SV were associated with grades of esophageal varices. Diameters of the LGV (P = 0.023, odds ratio [OR] = 1.583) and SV (P = 0.012, OR = 2.126) were independent risk factors of presence of the varices. Cut-off LGV diameters of 5.1 mm, 5.9 mm, 6.6 mm, 7.1 mm, 7.8 mm and 5.8 mm; or cut-off SV diameters of 7.3 mm, 7.9 mm, 8.4 mm, 9.5 mm, 10.7 mm and 8.3 mm, could discriminate grades 0 from 1, 0 from 2, 0 from 3, 1 from 3, 2 from 3, and 0-1 from 2-3, respectively. CONCLUSION: Diameters of the LGV and SV are associated with endoscopic grades of esophageal varices.

Electroacupuncture at Sensitized Acupoints Relieves Somatic Referred Pain in Colitis Rats by Inhibiting Sympathetic-Sensory Coupling to Interfere with 5-HT Signaling Pathway.

OBJECTIVE: To investigate whether electroacupuncture (EA) at sensitized acupoints could reduce sympathetic-sensory coupling (SSC) and neurogenic inflammatory response by interfering with 5-hydroxytryptamine (5-HT)ergic neural pathways to relieve colitis and somatic referred pain, and explore the underlying mechanisms. METHODS: Rats were treated with 5% dextran sodium sulfate (DSS) solution for 7 days to establish a colitis model. Twelve rats were randomly divided into the control and model groups according to a random number table (n=6). According to the "Research on Rat Acupoint Atlas", sensitized acupoints and non-sensitized acupoints were determined. Rats were randomly divided into the control, model, Zusanli-EA (ST 36), Dachangshu-EA (BL 25), and Xinshu (BL 15) groups (n=6), as well as the control, model, EA, and EA + GR113808 (a 5-HT inhibitor) groups (n=6). The rats in the control group received no treatment. Acupuncture was administered on 2 days after modeling using the stimulation pavameters: 1 mA, 2 Hz, for 30 min, with sparse and dense waves, for 14 consecutive days. GR113808 was injected into the tail vein at 5 mg/kg before EA for 10 min for 7 consecutive days. Mechanical sensitivity was assessed with von Frey filaments. Body weight and disease activity index (DAI) scores of rats were determined. Hematoxylin and eosin staining was performed to observe colon histopathology. SSC was analyzed by immunofluorescence staining. Immunohistochemical staining was performed to detect 5-HT and substance P (SP) expressions. The calcitonin gene-related peptide (CGRP) in skin tissue and tyrosine hydroxylase (TH) protein levels in DRG were detected by Western blot. The levels of hyaluronic acid (HA), bradykinin (BK), prostaglandin I2 (PGI2) in skin tissue, 5-HT, tryptophan hydroxylase 1 (TPH1), serotonin transporters (SERT), 5-HT 3 receptor (5-HT3R), and 5-HT 4 receptor (5-HT4R) in colon tissue were measured by enzyme-linked immunosorbent assay (ELISA). RESULTS: BL 25 and ST 36 acupoints were determined as sensitized acupoints, and BL 15 acupoint was used as a non-sensitized acupoint. EA at sensitized acupoints improved the DAI score, increased mechanical withdrawal thresholds, and alleviated colonic pathological damage of rats. EA at sensitized acupoints reduced SSC structures and decreased TH and CGRP expression levels (P<0.05). Furthermore, EA at sensitized acupoints reduced BK, PGI2, 5-HT, 5-HT3R and TPH1 levels, and increased HA, 5-HT4R and SERT levels in colitis rats (P<0.05). GR113808 treatment diminished the protective effect of EA at sensitized acupoints in colitis rats (P<0.05). CONCLUSION: EA at sensitized acupoints alleviated DSS-induced somatic referred pain in colitis rats by interfering with 5-HTergic neural pathway, and reducing SSC inflammatory response.

A Systematic Review and Meta-Analysis of MRI Radiomics for Predicting Microvascular Invasion in Patients with Hepatocellular Carcinoma.

BACKGROUND: The prediction power of MRI radiomics for microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC) remains uncertain. OBJECTIVE: To investigate the prediction performance of MRI radiomics for MVI in HCC. METHODS: Original studies focusing on preoperative prediction performance of MRI radiomics for MVI in HCC, were systematically searched from databases of PubMed, Embase, Web of Science and Cochrane Library. Radiomics quality score (RQS) and risk of bias of involved studies were evaluated. Meta-analysis was carried out to demonstrate the value of MRI radiomics for MVI prediction in HCC. Influencing factors of the prediction performance of MRI radiomics were identified by subgroup analyses. RESULTS: 13 studies classified as type 2a or above according to the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis statement were eligible for this systematic review and meta-analysis. The studies achieved an average RQS of 14 (ranging from 11 to 17), accounting for 38.9% of the total points. MRI radiomics achieved a pooled sensitivity of 0.82 (95%CI: 0.78 - 0.86), specificity of 0.79 (95%CI: 0.76 - 0.83) and area under the summary receiver operator characteristic curve (AUC) of 0.88 (95%CI: 0.84 - 0.91) to predict MVI in HCC. Radiomics models combined with clinical features achieved superior performances compared to models without the combination (AUC: 0.90 vs 0.85, P < 0.05). CONCLUSION: MRI radiomics has the potential for preoperative prediction of MVI in HCC. Further studies with high methodological quality should be designed to improve the reliability and reproducibility of the radiomics models for clinical application. The systematic review and meta-analysis was registered prospectively in the International Prospective Register of Systematic Reviews (No. CRD42022333822).

Novel computed tomography-based nomograms for the pretherapeutic prediction of response to neoadjuvant chemotherapy with S-1 and oxaliplatin with or without the addition of docetaxel in patients with advanced gastric cancer.

Background: Selecting the appropriate preoperative neoadjuvant chemotherapy (NACT) regimen for patients with advanced gastric cancer (GC) is critical to effective treatment. The aim of this study was to develop nomograms based on pretherapeutic computed tomography (CT) features to predict response to NACT with S-1 and oxaliplatin (SOX) or that with docetaxel and SOX (DOS) in patients with advanced GC. Methods: This study enrolled 311 consecutive patients with confirmed advanced GC undergoing contrast-enhanced CT before and after the three cycles of NACT with DOS (n=152) or SOX (n=159), who were randomized into a training cohort (TC) (NACT with DOS: n=111; NACT with SOX: n=120) and validation cohort (VC) (NACT with DOS: n=41; NACT with SOX: n=39). The objective response rate (ORR) was used to evaluate the response to NACT. In the TC, ORR was compared between the DOS and SOX regimens, and independent predictors including CT features and tumor differentiation were determined by univariate and binary logistic regression analyses. Individual nomograms were constructed for the SOX and DOS regimens in the TC, and the predictive accuracy was validated in the VC. Results: After NACT, the percentage of ORR was higher in patients receiving DOS than in those receiving SOX in TC (P value <0.05). The independent predictors after DOS and SOX were pretherapeutic cT stage [odds ratio (OR) =7.364; OR =8.848], cN stage (OR =1.027; OR =1.345), degree of differentiation (OR =7.127; OR =7.835), and gross tumor volume (OR =8.960; OR =8.161) (all P values <0.05). The concordance indexes of the individual nomograms developed using these predictors were 0.940 and 0.932 after DOS or SOX in the TC, respectively, which was validated by calibration plots with a slope close to 45° in the TC and VC. Conclusions: Despite there being a superior response to DOS compared with SOX, nomograms for predicting response to both NACT regimens were similar, with each demonstrating good predictive performance.

CT radiomics based on the peritumoral adipose region of gastric adenocarcinoma for preoperative prediction of lymph node metastasis.

PURPOSE: To construct and validate CT radiomics model based on the peritumoral adipose region of gastric adenocarcinoma to preoperatively predict lymph node metastasis (LNM). METHODS AND METHODS: 293 consecutive gastric adenocarcinoma patients receiving radical gastrectomy with lymph node dissection in two medical institutions were stratified into a development set (from Institution A, n = 237), and an external validation set (from Institution B, n = 56). Volume of interest of peritumoral adipose region was segmented on preoperative portal-phase CT images. The least absolute shrinkage and selection operator method and stepwise logistic regression were used to select features and build radiomics models. Manual classification was performed according to routine CT characteristics. A classifier incorporating the radiomics score and CT characteristics was developed for predicting LNM. Area under the receiver operating characteristic curve (AUC) was used to show discrimination between tumors with and without LNM, and the calibration curves and Brier score were used to evaluate the predictive accuracy. Violin plots were used to show the distribution of radiomics score. RESULTS: AUC values of radiomics model to predict LNM were 0.938, 0.905, and 0.872 in the training, internal test, and external validation sets, respectively, higher than that of manual classification (0.674, all P values < 0.01). The radiomics score of the positive LNM group were higher than that of the negative group in all sets (both P-values < 0.001). The classifier showed no improved predictive power compared with the radiomics signature alone with AUC values of 0.916 and 0.872 in the development and external validation sets, respectively. Multivariate analysis showed that radiomics score was an independent predictor. CONCLUSIONS: Radiomics model based on peritumoral adipose region could be a useful approach for preoperative LNM prediction in gastric adenocarcinoma.

A computed tomography-based nomogram for neoadjuvant chemotherapy plus immunotherapy response prediction in patients with advanced esophageal squamous cell carcinoma.

Objective: To develop a CT-based nomogram to predict the response of advanced esophageal squamous cell carcinoma (ESCC) to neoadjuvant chemotherapy plus immunotherapy. Methods: In this retrospective study, 158 consecutive patients with advanced ESCC receiving contrast-enhanced CT before neoadjuvant chemotherapy plus immunotherapy were randomized to a training cohort (TC, n = 121) and a validation cohort (VC, n = 37). Response to treatment was assessed with response evaluation criteria in solid tumors. Patients in the TC were divided into the responder (n = 69) and non-responder (n = 52) groups. For the TC, univariate analyses were performed to confirm factors associated with response prediction, and binary analyses were performed to identify independent variables to develop a nomogram. In both the TC and VC, the nomogram performance was assessed by area under the receiver operating characteristic curve (AUC), calibration slope, and decision curve analysis (DCA). Results: In the TC, univariate analysis showed that cT stage, cN stage, gross tumor volume, gross volume of all enlarged lymph nodes, and tumor length were associated with the response (all P < 0.05). Binary analysis demonstrated that cT stage, cN stage, and tumor length were independent predictors. The independent factors were imported into the R software to construct a nomogram, showing the discriminatory ability with an AUC of 0.813 (95% confidence interval: 0.735-0.890), and the calibration curve and DCA showed that the predictive ability of the nomogram was in good agreement with the actual observation. Conclusion: This study provides an accurate nomogram to predict the response of advanced ESCC to neoadjuvant chemotherapy plus immunotherapy.

Baseline CT radiomics features to predict pathological complete response of advanced esophageal squamous cell carcinoma treated with neoadjuvant chemotherapy using paclitaxel and cisplatin.

PURPOSE: To develop a CT radiomics model to predict pathological complete response (pCR) of advanced esophageal squamous cell carcinoma (ESCC) toneoadjuvant chemotherapy using paclitaxel and cisplatin. MATERIALS AND METHODS: 326 consecutive patients with advanced ESCC from two hospitals undergoing baseline contrast-enhanced CT followed by neoadjuvant chemotherapy using paclitaxel and cisplatin were enrolled, including 115 patients achieving pCR and 211 patients without pCR. Of the 271 cases from 1st hospital, 188 and 83 cases were randomly allocated to the training and test cohorts, respectively. The 55 patients from a second hospital were assigned as an external validation cohort. Region of interest was segmented on the baseline thoracic contrast-enhanced CT. Useful radiomics features were generated by dimension reduction using least absolute shrinkage and selection operator. The optimal radiomics features were chosen using support vector machine (SVM). Discriminating performance was assessed with area under the receiver operating characteristic curve (ROC) and F-1score. The calibration curves and Brier score were used to evaluate the predictive accuracy. RESULTS: Eight radiomics features were selected to create radiomics models related to pCR of advanced ESCC (P-values < 0.01 for both the training and test cohorts). SVM model showed the best performance (AUCs = 0.929, 0.868 and 0.866, F-1scores = 0.857, 0.847 and 0.737 in the training, test and external validation cohorts, respectively). The calibration curves and Brier scores indicated goodness-of-fit and its great predictive accuracy. CONCLUSION: CT radiomics models could well help predict pCR of advanced ESCC, and SVM model could be a suitable predictive model.

Contrast-enhanced CT radiomics features to preoperatively identify differences between tumor and proximal tumor-adjacent and tumor-distant tissues of resectable esophageal squamous cell carcinoma.

BACKGROUND: Esophagectomy is the main treatment for esophageal squamous cell carcinoma (ESCC), and patients with histopathologically negative margins still have a relatively higher recurrence rate. Contrast-enhanced CT (CECT) radiomics might noninvasively obtain potential information about the internal heterogeneity of ESCC and its adjacent tissues. This study aimed to develop CECT radiomics models to preoperatively identify the differences between tumor and proximal tumor-adjacent and tumor-distant tissues in ESCC to potentially reduce tumor recurrence. METHODS: A total of 529 consecutive patients with ESCC from Centers A (n = 447) and B (n = 82) undergoing preoperative CECT were retrospectively enrolled in this study. Radiomics features of the tumor, proximal tumor-adjacent (PTA) and proximal tumor-distant (PTD) tissues were individually extracted by delineating the corresponding region of interest (ROI) on CECT and applying the 3D-Slicer radiomics module. Patients with pairwise tissues (ESCC vs. PTA, ESCC vs. PTD, and PTA vs. PTD) from Center A were randomly assigned to the training cohort (TC, n = 313) and internal validation cohort (IVC, n = 134). Univariate analysis and the least absolute shrinkage and selection operator were used to select the core radiomics features, and logistic regression was performed to develop radiomics models to differentiate individual pairwise tissues in TC, validated in IVC and the external validation cohort (EVC) from Center B. Diagnostic performance was assessed using area under the receiver operating characteristics curve (AUC) and accuracy. RESULTS: With the chosen 20, 19 and 5 core radiomics features in TC, 3 individual radiomics models were developed, which exhibited excellent ability to differentiate the tumor from PTA tissue (AUC: 0.965; accuracy: 0.965), the tumor from PTD tissue (AUC: 0.991; accuracy: 0.958), and PTA from PTD tissue (AUC: 0.870; accuracy: 0.848), respectively. In IVC and EVC, the models also showed good performance in differentiating the tumor from PTA tissue (AUCs: 0.956 and 0.962; accuracy: 0.956 and 0.937), the tumor from PTD tissue (AUCs: 0.990 and 0.974; accuracy: 0.952 and 0.970), and PTA from PTD tissue (AUCs: 0.806 and 0.786; accuracy: 0.760 and 0.786), respectively. CONCLUSION: CECT radiomics models could differentiate the tumor from PTA tissue, the tumor from PTD tissue, and PTA from PTD tissue in ESCC.

Computed tomography-based nomogram of Siewert type II/III adenocarcinoma of esophagogastric junction to predict response to docetaxel, oxaliplatin and S-1.

BACKGROUND: Neoadjuvant chemotherapy (NAC) has become the standard care for advanced adenocarcinoma of esophagogastric junction (AEG), although a part of the patients cannot benefit from NAC. There are no models based on baseline computed tomography (CT) to predict response of Siewert type II or III AEG to NAC with docetaxel, oxaliplatin and S-1 (DOS). AIM: To develop a CT-based nomogram to predict response of Siewert type II/III AEG to NAC with DOS. METHODS: One hundred and twenty-eight consecutive patients with confirmed Siewert type II/III AEG underwent CT before and after three cycles of NAC with DOS, and were randomly and consecutively assigned to the training cohort (TC) (n = 94) and the validation cohort (VC) (n = 34). Therapeutic effect was assessed by disease-control rate and progressive disease according to the Response Evaluation Criteria in Solid Tumors (version 1.1) criteria. Possible prognostic factors associated with responses after DOS treatment including Siewert classification, gross tumor volume (GTV), and cT and cN stages were evaluated using pretherapeutic CT data in addition to sex and age. Univariate and multivariate analyses of CT and clinical features in the TC were performed to determine independent factors associated with response to DOS. A nomogram was established based on independent factors to predict the response. The predictive performance of the nomogram was evaluated by Concordance index (C-index), calibration and receiver operating characteristics curve in the TC and VC. RESULTS: Univariate analysis showed that Siewert type (52/55 vs 29/39, P = 0.005), pretherapeutic cT stage (57/62 vs 24/32, P = 0.028), GTV (47.3 ± 27.4 vs 73.2 ± 54.3, P = 0.040) were significantly associated with response to DOS in the TC. Multivariate analysis of the TC also showed that the pretherapeutic cT stage, GTV and Siewert type were independent predictive factors related to response to DOS (odds ratio = 4.631, 1.027 and 7.639, respectively; all P < 0.05). The nomogram developed with these independent factors showed an excellent performance to predict response to DOS in the TC and VC (C-index: 0.838 and 0.824), with area under the receiver operating characteristic curve of 0.838 and 0.824, respectively. The calibration curves showed that the practical and predicted response to DOS effectively coincided. CONCLUSION: A novel nomogram developed with pretherapeutic cT stage, GTV and Siewert type predicted the response of Siewert type II/III AEG to NAC with DOS.

A CT-based novel model to predict pathological complete response of locally advanced esophageal squamous cell carcinoma to neoadjuvant PD-1 blockade in combination with chemotherapy.

PURPOSE: To develop a novel CT-based model to predict pathological complete response (pCR) of locally advanced esophageal squamous cell carcinoma (ESCC) to neoadjuvant PD-1 blockade in combination with chemotherapy. METHODS: 117 consecutive patients with locally advanced ESCC were stratified into training cohort (n = 82) and validation cohort (n = 35). All patients underwent non-contrast and contrast-enhanced thoracic and upper abdominal CT before neoadjuvant PD-1 blockade in combination with chemotherapy (CTpre), and after two cycles of the therapy before esophagectomy (CTpost), respectively. Univariate analyses and binary logistic regression analyses of ESCC quantitative and qualitative CT features were performed to determine independent predictors of pCR. Prediction performance of the model developed with independent predictors from training cohort was evaluated by receiver operating characteristic (ROC) analysis, and validated by Kappa test in validation cohort. RESULTS: In training cohort, the difference in CT attenuation between tumor and background normal esophageal wall obtained from CTpre (ΔTNpre), tumoral increased CT attenuation after contrast-enhanced scan from CTpost images (ΔTpost) and gross tumor volume (GTV) from CTpre were independent predictors of pCR (odds ratio = 1.128 (95% confidence interval (CI): 0.997-1.277), 1.113 (95%CI: 0.965-1.239) and 1.133 (95%CI: 1.043-1.231), respectively, all P-values < 0.05). Logistic regression model equation (0.121 × ΔTNpre + 0.107 × ΔTpost + 0.125 × GTV - 9.856) to predict pCR showed the best performance with an area under the ROC of 0.876, compared with each independent predictor. The good performance was confirmed by the Kappa test (K-value = 0.796) in validation cohort. CONCLUSIONS: This novel model can be reliable to predict pCR to neoadjuvant PD-1 blockade in combination with chemotherapy in locally advanced ESCC.

CT radiomics for prediction of microvascular invasion in hepatocellular carcinoma: A systematic review and meta-analysis.

The power of computed tomography (CT) radiomics for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) demonstrated in current research is variable. This systematic review and meta-analysis aim to evaluate the value of CT radiomics for MVI prediction in HCC, and to investigate the methodologic quality in the workflow of radiomics research. Databases of PubMed, Embase, Web of Science, and Cochrane Library were systematically searched. The methodologic quality of included studies was assessed. Validation data from studies with Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) statement type 2a or above were extracted for meta-analysis. Eleven studies were included, among which nine were eligible for meta-analysis. Radiomics quality scores of the enrolled eleven studies varied from 6 to 17, accounting for 16.7%-47.2% of the total points, with an average score of 14. Pooled sensitivity, specificity, and Area Under the summary receiver operator Characteristic Curve (AUC) were 0.82 (95% CI 0.77-0.86), 0.79 (95% CI 0.75-0.83), and 0.87 (95% CI 0.84-0.91) for the predictive performance of CT radiomics, respectively. Meta-regression and subgroup analyses showed radiomics model based on 3D tumor segmentation, and deep learning model achieved superior performances compared to 2D segmentation and non-deep learning model, respectively (AUC: 0.93 vs. 0.83, and 0.97 vs. 0.83, respectively). This study proves that CT radiomics could predict MVI in HCC. The heterogeneity of the included studies precludes a definition of the role of CT radiomics in predicting MVI, but methodology warrants uniformization in the radiology community regarding radiomics in HCC.

A novel quantitative model based on gross tumor volume corresponding to anatomical distribution measured with multidetector computed tomography to determine the resectability of non­distant metastatic esophageal squamous cell carcinoma.

It is important to accurately determine the resectability of thoracic esophageal squamous cell carcinoma (ESCC) for treatment decision-making. Previous studies have revealed that the CT-derived gross tumor volume (GTV) is associated with the staging of ESCC. The present study aimed to explore whether the anatomical distribution-based GTV of non-distant metastatic thoracic ESCC measured using multidetector computed tomography (MDCT) could quantitatively determine the resectability. For this purpose, 473 consecutive patients with biopsy-confirmed non-distant metastatic thoracic ESCC who underwent contrast-enhanced CT were randomly divided into a training cohort (TC; 376 patients) and validation cohort (VC; 97 patients). GTV was retrospectively measured using MDCT. Univariate and multivariate analyses were performed to identify the determinants of the resectability of ESCC in the TC. Receiver operating characteristic (ROC) analysis was performed to clarify whether anatomical distribution-based GTV could help quantitatively determinate resectability. Unweighted Cohen's Kappa tests in VC were used to assess the performance of the previous models. Univariate analysis demonstrated that sex, anatomic distribution, cT stage, cN stage and GTV were related to the resectability of ESCC in the TC (all P<0.05). Multivariate analysis revealed that GTV [P<0.001; odds ratio (OR) 1.158] and anatomic distribution (P=0.027; OR, 1.924) were independent determinants of resectability. ROC analysis revealed that the GTV cut-offs for the determination of the resectability of the upper, middle and lower thoracic portions were 23.57, 22.89 and 22.58 cm3, respectively, with areas under the ROC curves of >0.9. Unweighted Cohen's Kappa tests revealed an excellent performance of the ROC models in the upper, middle and lower thoracic portions with Cohen k-values of 0.913, 0.879 and 0.871, respectively. On the whole, the present study demonstrated that GTV and the anatomic distribution of non-distant metastatic thoracic ESCC may be independent determinants of resectability, and anatomical distribution-based GTV can effectively be used to quantitatively determine resectability.

Whole-tumor histogram analysis of apparent diffusion coefficients for predicting lymphovascular space invasion in stage IB-IIA cervical cancer.

Objectives: To investigate the value of apparent diffusion coefficient (ADC) histogram analysis based on whole tumor volume for the preoperative prediction of lymphovascular space invasion (LVSI) in patients with stage IB-IIA cervical cancer. Methods: Fifty consecutive patients with stage IB-IIA cervical cancer were stratified into LVSI-positive (n = 24) and LVSI-negative (n = 26) groups according to the postoperative pathology. All patients underwent pelvic 3.0T diffusion-weighted imaging with b-values of 50 and 800 s/mm2 preoperatively. Whole-tumor ADC histogram analysis was performed. Differences in the clinical characteristics, conventional magnetic resonance imaging (MRI) features, and ADC histogram parameters between the two groups were analyzed. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of ADC histogram parameters in predicting LVSI. Results: ADCmax, ADCrange, ADC90, ADC95, and ADC99 were significantly lower in the LVSI-positive group than in the LVSI-negative group (all P-values < 0.05), whereas no significant differences were reported for the remaining ADC parameters, clinical characteristics, and conventional MRI features between the groups (all P-values > 0.05). For predicting LVSI in stage IB-IIA cervical cancer, a cutoff ADCmax of 1.75×10-3 mm2/s achieved the largest area under ROC curve (Az) of 0.750, followed by a cutoff ADCrange of 1.36×10-3 mm2/s and ADC99 of 1.75×10-3 mm2/s (Az = 0.748 and 0.729, respectively), and the cutoff ADC90 and ADC95 achieved an Az of <0.70. Conclusion: Whole-tumor ADC histogram analysis has potential value for preoperative prediction of LVSI in patients with stage IB-IIA cervical cancer. ADCmax, ADCrange, and ADC99 are promising prediction parameters.

Renal ectopic lipid deposition in rats with early-stage diabetic nephropathy evaluated by the MR mDixon-Quant technique: association with the expression of SREBP-1 and PPARα in renal tissue.

Background: Renal ectopic lipid deposition (ELD) plays a significant role in the development of diabetic nephropathy (DN). This study aimed to use the magnetic resonance (MR) mDixon-Quant technique to evaluate renal ELD and its association with the expression of sterol regulatory element binding protein 1 (SREBP-1) and peroxisome proliferator-activated receptor alpha (PPARα) in renal tissue. Methods: Seventy male Sprague-Dawley (SD) rats were randomly divided into experimental (n=50) and control groups (n=20). A high-fat diet combined with low-dose streptozotocin (STZ) was administered to the experimental group to establish a type 2 diabetes mellitus (T2DM) model. The rats received renal mDixon-Quant scans and blood lipid and histopathological examinations in batches after the T2DM model was established. According to the histopathological findings, the included rats were stratified into control and early DN groups. Renal fat fraction (FF), blood lipid level, the ratio of the integrated optical density of intracellular lipid droplets and the total area of all the cells (IOD/TAC), and the expression of SREBP-1 and PPARɑ in renal tissue were analyzed. Results: Compared to the controls, renal FF, IOD/TAC, the expression of SREBP-1 in renal tissue, and serum total cholesterol (TC), triglyceride (TG) and low-density lipoprotein (LDL) levels were higher in the early DN group, while the expression of PPARɑ in renal tissue and the high-density lipoprotein (HDL) level were lower (all P values <0.001). Renal FF gradually increased with the progression of disease [r=0.810 (95% CI: 0.675-0.928), P<0.001]. Positive correlations between renal FF and each of the following: TC, TG, LDL, IOD/TAC, and the expression of SREBP-1 [r=0.479 (95% CI: 0.353-0.640, P=0.012), 0.576 (95% CI: 0.283-0.842, P=0.002), 0.441 (95% CI: 0.305-0.606, P=0.021), 0.911 (95% CI: 0.809-0.964, P<0.001) and 0.800 (95% CI: 0.640-0.910, P<0.001), respectively] and negative correlations between renal FF and each of the following: HDL and the expression of PPARɑ [r=-0.611 (95% CI: -0.809 to -0.469, P=0.001) and -0.748 (95% CI: -0.886 to -0.585, P<0.001), respectively] were found. Conclusions: Renal lipid deposition evaluated by the MR mDixon-Quant technique is associated with the blood lipid level, histological fat quantification, and the expression of SREBP-1 and PPARɑ in renal tissue. The renal FF value might serve as a biomarker for better understanding of renal lipid metabolism in early-stage DN.

An improved model based on quantitative features of right liver lobe, maximum varices, and portal vein system measured on magnetic resonance imaging to predict oesophagogastric variceal haemorrhage secondary to hepatitis B-related cirrhosis.

Background: In patients with hepatitis B-related cirrhosis, it is important to predict those at high-risk of oesophagogastric variceal haemorrhage (OVH) to decide upon prophylactic treatment. Our published model developed with right liver lobe volume and diameters of portal vein system did not incorporate maximum variceal size as a factor. This study thus aimed to develop an improved model based on right liver lobe volume, diameters of maximum oesophagogastric varices (OV) and portal vein system obtained at magnetic resonance imaging (MRI) to predict OVH. Methods: Two hundred and thirty consecutive individuals with hepatitis B-related cirrhosis undergoing abdominal enhanced MRI were randomly grouped into training (n=160) and validation sets (n=70). OVH was confirmed in 51 and 23 participants in the training and validation sets during 2-year follow-up period, respectively. Spleen, total liver, right lobe, caudate lobe, left lateral lobe, and left medial lobe volumes, together with diameters of maximum OV and portal venous system were measured on MRI. In the training set, univariate analyses and binary logistic regression analyses were conducted to determine independent predictors. The performance of the model for predicting OVH constructed based on independent predictors from the training set was evaluated with receiver operating characteristic (ROC) analysis and validated in the validation set. Results: The model for predicting OVH was established based on right liver lobe volume and diameters of the maximum OV, left gastric vein, and portal vein [odds ratio (OR) =0.991, 2.462, 1.434, and 1.582, respectively; all P values <0.05]. The logistic regression model equation [-0.009 × right liver lobe volume + 0.901 × maximum OV diameter (MOVD) + 0.361 × left gastric vein diameter (LGVD) + 0.459 × portal vein diameter (PVD) - 7.842] with a cutoff value of -0.656 for predicting OVH obtained excellent performance with an area under ROC curve (AUC) of 0.924 [95% confidence interval (CI): 0.878-0.971]. The Delong test showed negative statistical difference in the model performance between the training and validation sets, with a P value >0.99. Conclusions: The model could help well screen those patients at high risk of OVH for timely intervention and avoiding the fatal complications.

Use of conventional MR imaging and diffusion-weighted imaging for evaluating the risk grade of gastrointestinal stromal tumors.

PURPOSE: To study the risk grade of gastrointestinal stromal tumors (GISTs) with conventional MR imaging and diffusion-weighted imaging (DWI). MATERIALS AND METHODS: The abdominal MR images with DWI of 23 patients with pathologically proven GISTs during January 2010 to May 2011 were retrospectively reviewed. The conventional MR imaging findings and apparent diffusion coefficient (ADC) values of the tumors related to the risk grade were analyzed. RESULTS: In the 23 patients, there were 13 patients with high-risk, 5 with medium-risk, 5 with low-risk, and 0 with very low-risk GISTs. Most of the conventional MR findings of the tumors did not correlate with the risk grade. The only exception to this was the correlation between risk grade and the enhancement degree of the tumor after Gd-DTPA. The ADC values were, respectively, (1.04 ± 0.13) × 10(-3) mm(2) ·s(-1) , (1.59 ± 0.06) × 10(-3) mm(2) ·s(-1) and (1.94 ± 0.08) × 10(-3) mm(2) ·s(-1) (P < 0.05) in the high-, medium-, and low-risk grade groups. The ADC values of GISTs decreased with the increase of the risk grade of the tumors (r = -0.957; P < 0.05). CONCLUSION: DWI can be used to assess the risk grade of GISTs, but conventional MR imaging is of limited use.

[Use of buccal swab as a source of genomic DNA for genetic screening in patients with age-related macular degeneration].

OBJECTIVE: The collection of buccal cells with swabs provides a noninvasive method for obtaining genomic DNA for genetic screening. We aimed to study the feasibility of using buccal swabs for genetic screening in patients with exudative age-related macular degeneration (AMD). METHODS: Blood and buccal swabs were collected for genetic analysis from 65 patients with exudative AMD. Genomic DNA was isolated from either blood or buccal swabs. The yield of genomic DNA from both sources was determined by spectrophotometer. Genotyping for CFH, LOC387715, and HTRA1 Polymorphisms was performed using a method of polymerase chain reaction (PCR) followed by restriction enzyme digestion. Results using genomic DNA from blood or buccal swabs were compared. RESULTS: Three swabs were obtained from each patient, 2 from each side of buccal mucosa, and 1 from both upper and inferior gingival mucosa. From swabs with genomic DNA extracted within a week after sample collection, an average of (3.17 ± 1.46) µg genomic DNA was obtained from swab collected from the left or right side buccal mucosa, and (3.94 ± 1.04) µg from swab collected from the upper and inferior gingival mucosa, with relatively higher yield of genomic DNA from the upper and inferior gingival mucosa (t = 6.79, P < 0.05). From swabs of the left or right side buccal mucosa after being stored at -20°C for 12 months, an average of (3.10 ± 1.17) µg genomic DNA was obtained, which showed no statistically significant difference as compared to the yield of genomic DNA extracted from newly collected swabs (t = 0.59, P > 0.05). In all 65 patients, genomic DNA isolated from either buccal swabs or blood samples showed exactly the same results regarding the genotypes of CFH, LOC387715, and HTRA1 Polymorphisms. CONCLUSIONS: Buccal swab is a simple, noninvasive, and reliable source for obtaining genomic DNA. Swabs stored for 12 months at -20°C provide similar amount of genomic DNA as the freshly collected swabs.