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Objective:To investigate predictive value of model based on pre-surgical 18F-FDG PET/CT metabolic parameters for mediastinal lymph node metastasis (LNM) in lung adenocarcinoma. Methods:A total of 288 patients with lung adenocarcinoma (135 males, 153 females, age (61.6±8.5) years) who diagnosed and treated in the Fourth Hospital of Hebei Medical University from January 2016 to February 2021 were enrolled retrospectively. All patients underwent 18F-FDG PET/CT examination within 1 month before operation, and underwent complete resection of primary lung tumor and standard lymph node dissection. PET/CT parameters were extracted (PET metabolic parameters: minimum SUV(SUV min), SUV max, SUV mean, SUV standard deviation (SUV std), metabolic tumor volume (MTV) and total lesion glycolysis (TLG); CT parameters: minimum CT value (HU min), maximum CT value (HU max), mean CT value (HU mean), CT value standard deviation (HU std)). Multivariate logistic regression analysis was used for screening parameters and establishing model to predict LNM. ROC curves analyses were used to evaluate the predictive performance of models. Results:Among 288 patients, 90 had LNM, and 361 metastatic lymph nodes (N1: 186, N2: 175) were reported by pathology. SUV min (odds ratio ( OR)=1.859, 95% CI: 1.074-3.220, P=0.027), SUV max ( OR=2.255, 95% CI: 1.306-3.893, P=0.004), SUV mean ( OR=0.277, 95% CI: 0.115-0.665, P=0.004) were predictors of LNM. The AUC of PET/CT model was 0.849 (95% CI: 0.804-0.893), and the sensitivity, specificity, accuracy, and positive and negative predictive values were 87.8%(79/90), 72.2%(143/198), 77.1%(222/288), 59.0%(79/134) and 92.9%(143/154), respectively. Conclusion:The model based on 18F-FDG PET/CT metabolic parameters can improve the accuracy of pre-surgical N-staging in patients with lung adenocarcinoma.
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Objective:To investigate the value of pre-therapy 18F-FDG PET/CT radiomic models in differentiating epidermal growth factor receptor (EGFR) exon 19 deletion from exon 21 L858R missense in patients with non-small cell lung cancer (NSCLC). Methods:A total of 172 patients with EGFR mutant NSCLC (54 males, 118 females, age: (56.2±12.5) years) in the Fourth Hospital of Hebei Medical University between January 2015 and November 2019 were retrospectively included. Exon 19 mutation was found in 75 patients and exon 21 mutation was identified in 97 patients. The patients were divided into training set ( n=121) and validation set ( n=51) in a 7∶3 ratio by using random number table. The LIFEx 4.00 package was used to extract texture features of PET/CT images of lesions. The least absolute shrinkage and selection operator (LASSO) algorithm was used for feature screening. Three machine learning models, namely logistic regression (LR), random forest (RF), and support vector machine (SVM) models, were constructed based on the selected optimal feature subsets. The ROC curve analysis was performed to assess the predictive performance of those models. Finally, decision curve analysis (DCA) was used to evaluate the clinical value of the models. Results:Nine radiomics features, including 6 PET features (histogram (HISTO)_Kurtosis, SHAPE_Sphericity, gray level run length matrix (GLRLM)_ low gray-level run emphasis (LGRE), GLRLM_ run length non-uniformity (RLNU), neighborhood grey level different matrix (NGLDM)_Contrast, gray level zone length matrix (GLZLM)_ short-zone low gray-level emphasis (SZLGE)), and 3 CT features (gray level co-occurrence matrix (GLCM)_Correlation, GLRLM_ run percentage (RP), NGLDM_Contrast), were screened by LASSO algorithm. Three machine learning models had similar predictive performance in the training and validation sets: AUCs for the RF model were 0.79, 0.77, and those for the SVM model were 0.76, 0.75, for the LR model were 0.77, 0.75. The DCA showed that the 3 machine learning models had good net benefits and clinical values in predicting EGFR mutation subtypes.Conclusion:18F-FDG PET/CT radiomics provide a non-invasive method for the identification of EGFR exon 19 deletion and exon 21 L858R missense mutations in patients with NSCLC, which may help the clinical decision-making and the formulation of individualized treatment plan.
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Objective:To investigate the value of preoperative prediction of Ki-67 expression status in breast cancer based on multi-phase enhanced MRI combined with clinical imaging characteristics prediction model.Methods:This study was retrospective. A total of 213 breast cancer patients who underwent surgical treatment at Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College between June 2016 and May 2017 were enrolled. All patients were female, aged 24-78 (51±10) years, and underwent routine breast MRI within 2 weeks prior to surgery. According to the different Ki-67 expression of postoperative pathological results, patients were divided into high expression group (Ki-67≥20%, 153 cases) and low expression group (Ki-67<20%, 60 cases). The radiomic features of breast cancer lesions were extracted from phase 2 (CE-2) and phase 7 (CE-7) images of dynamic contrast enhanced (DCE)-MRI, and all cases were divided into training and test sets according to the ratio of 7∶3. The radiomic features were first selected using ANOVA and Wilcoxon signed-rank test, followed by the least absolute shrinkage and selection operator method regression model. The same method of parameters selection was applied to clinical information and conventional imaging features [including gland classification, degree of background parenchymal enhancement, multifocal/multicentric, lesion location, lesion morphology, lesion long diameter, lesion short diameter, T 2WI signal characteristics, diffusion-weighted imaging (DWI) signal characteristics, apparent diffusion coefficient (ADC) values, time-signal intensity curve type, and axillary lymph nodes larger than 1 cm in short axis]. Support vector machine (SVM) was then used to construct prediction models for Ki-67 high and low expression states. The predictive performance of the models were evaluated using receiver operating characteristic (ROC) curves and area under cueve(AUC). Results:Totally 1 029 radiomic features were extracted from CE-2 and CE-7 images, respectively, and 9 and 7 best features were obtained after selection, respectively. And combining the two sets of features for a total of 16 features constituted the CE-2+CE-7 image best features. Five valuable parameters including lesion location, lesion short diameter, DWI signal characteristics, ADC values, and axillary lymph nodes larger than 1 cm in short axis, were selected from all clinical image features. The SVM prediction models obtained from the radiomic features of CE-2 and CE-7 images had a high AUC in predicting Ki-67 expression status (>0.70) in both the training set and the test set. The models were constructed by combining the CE-2, CE-7, and CE-2+CE-7 radiomic features with clinical imaging features, respectively, and the corresponding model performance in predicting Ki-67 expression status was improved compared with the models obtained by using the CE-2, CE-7, and CE-2+CE-7 radiomic features alone. The SVM prediction model obtained from CE-2+CE-7 radiomic features combined with clinical imaging features had the best prediction performance, with AUC of 0.895, accuracy of 84.6%, sensitivity of 87.9%, and specificity of 76.2% for predicting Ki-67 expression status in the training set and AUC of 0.822, accuracy of 70.3%, sensitivity of 76.1%, and specificity of 55.6% in test sets.Conclusion:The SVM prediction model based on DCE-MRI radiomic features can effectively predict Ki-67 expression status, and the combination of radiomic features and clinical imaging features can further improve the model prediction performance.
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Objective:To investigate the relationship between 18F-FDG PET/CT Lugano lymphoma response evaluation criteria and prognosis of patients with diffuse large B-cell lymphoma (DLBCL) at the end of chemotherapy. Methods:A total of 131 patients with DLBCL (63 males, 68 females, age (50.3±17.0) years) who underwent 18F-FDG PET/CT at the end of chemotherapy in the Fourth Hospital of Hebei Medical University from July 2013 to January 2021 were analyzed retrospectively. 18F-FDG PET/CT Lugano lymphoma response evaluation criteria was used to evaluate the response (complete remission (CR), partial remission (PR), stable disease (SD) and progressive disease (PD)). Progression-free survival (PFS) and overall survival (OS) were followed up. Kaplan-Meier survival analysis was used for univariate analysis of clinical parameters and imaging parameters, and Cox proportional hazards regression model was used for multivariate analysis to explore related factors affecting the prognosis of patients with DLBCL. Results:The median follow-up time was 35.47 months for 131 patients with DLBCL. The 5-year PFS rate was 57.3%(75/131), and the 5-year OS rate was 84.0%(110/131). There were 74 cases of CR, 37 cases of PR and 20 cases of PD. Univariate analysis showed that the Lugano lymphoma response evaluation criteria was the influencing factor of PFS and OS (PFS, χ2=72.25, P<0.001; OS, χ2=11.97, P=0.003). Deauville score (DS) of patients with DLBCL was also the influencing factor for PFS ( χ2=62.46, P<0.001) and OS ( χ2=19.95, P<0.001). Ann Arbor stage, Eastern Cooperative Oncology Group physical state (ECOG PS) score and international prognostic index (IPI) were the influencing factors for PFS ( χ2 values: 10.31-15.80, all P<0.05). Ann Arbor stage, ECOG PS score, number of extranodal organ involved, β 2 microglobulin, and IPI were the influencing factors for OS ( χ2 values: 4.97-30.57, all P<0.05). Cox multivariate analysis showed that Lugano lymphoma response evaluation criteria, Ann Arbor stage and ECOG PS score were independent prognostic factors for PFS (relative risk ( RR) and 95% CI: 8.841(4.764-16.405), 1.434(1.111-1.852), 2.125(1.205-3.746), P values: <0.001, 0.006, 0.009) and OS ( RR(95% CI): 3.276(1.304-8.235), 9.728(2.216-42.669), 2.506(1.040-6.039), P values: 0.012, 0.003, 0.041). Conclusion:18F-FDG PET/CT Lugano lymphoma response evaluation criteria can precisely evaluate the prognosis of patients with DLBCL at the end of chemotherapy.
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Objective:To investigate the value of baseline 18F-fluorodeoxyglucose (FDG) PET/CT radiomics features in predicting the prognosis of non-small cell lung cancer (NSCLC) before treatment. Methods:From January 2016 to August 2018, a total of 300 patients with solitary NSCLC (189 males, 111 females, age (62.3±9.0) years) who underwent 18F-FDG PET/CT imaging before treatment in Fourth Hospital of Hebei Medical University were retrospectively analyzed. According to the ratio of 7∶3 (R language), 300 patients were randomly divided into training group ( n=210) and validation group ( n=90). LIFEx software package was used to extract the PET and CT radiomics features of primary focus in 300 NSCLC patients. The least absolute shrinkage and selection operator (LASSO) algorithm combined with Cox proportional hazard regression model were used to select radiomics features and clinical features for predicting overall survival (OS) and progression-free survival (PFS) in training group. Then radiomics model, clinical model and complex model which integrated the two were established and the radiomics score (Rad-score), clinical score and complex score of each patient were calculated. Data of validation group was used to validate each training model. Efficiencies of each model in predicting the prognosis of patients with NSCLC were further evaluated by the concordance index (C-index), and a nomogram was developed based on the best prediction model. Results:In training group, the C-indices of predicting OS and PFS in NSCLC patients of radiomics model were 0.762 and 0.724 respectively, which were 0.834 and 0.780 respectively in clinical model, and were 0.842 and 0.787 respectively in complex model. Cox multivariate analysis showed that both Rad-score and complex score were independent prognostic factors for OS (hazard ratio ( HR): 1.804, 9.996, 95% CI: 1.023-3.184, 4.582-21.808, both P<0.05) and PFS ( HR: 1.771, 5.627, 95% CI: 1.138-2.756, 3.429-9.234, both P<0.05). Conclusions:Pre-treatment 18F-FDG PET/CT radiomics can predict OS and PFS of NSCLC patients. The complex model based on the combination of radiomics and clinical model is effective in predicting the prognosis of NSCLC patients, and the nomogram of complex model is simple and convenient to assist clinical decision-making.
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Objective:To assess the predictive value of histogram parameters derived from synthetic MRI for extramural venous invasion (EMVI) of rectal cancer.Methods:Totally 76 patients with pathologically proven rectal adenocarcinoma were enrolled in this retrospective study from November 2018 to December 2019 in Cancer Hospital, Chinese Academy of Medical Sciences. All participants underwent preoperative rectal MRI examination including MAGiC within 4 weeks before surgery. The status of EMVI on MRI was independently assessed by one junior and one senior radiologist. Histogram parameters were extracted from T 1, T 2 and proton density (PD) mapping, including mean, variance, maximum, minimum, 10 th percentile, median, 90 th percentile, energy, kurtosis, entropy and skewness. With postoperative pathological result as the gold standard, the patients were divided into EMVI-positive group ( n=18) and EMVI-negative group ( n=58). The Mann-whitney U test was used to compare the differences in histogram parameters between the two groups. The ROC curves were used to explore the predictive performance for assessing EMVI. The logistic regression analysis was used to combine the assessment of radiologists with parameters whose area under the ROC curve (AUC)>0.7. The Delong test was used to analyze the differences of diagnostic efficacy between different methods in predicting EMVI. Results:Significant differences of the energy of T 1, T 2 and PD mapping and skewness of PD mapping were observed between the EMVI-positive and EMVI-negative group ( P<0.05), with the AUC of 0.744, 0.728, 0.708 and 0.652. The AUC of junior radiologist in evaluating EMVI was 0.711, and the AUC of the combination with energy of T 1, T 2 and PD mapping was 0.817, showing a statistically significant difference ( Z=2.281, P=0.023). The AUC of senior radiologist in evaluating EMVI was 0.837, and the AUC of the combination with energy was 0.856. There was a significant difference in AUC between junior and senior radiologists in assessing EMVI ( Z=2.587, P=0.010), while there was no significant difference between junior radiologist combined with energy and senior radiologist ( Z=0.578, P=0.563). Conclusion:The histogram parameters based on quantitative mapping of synthetic MRI were useful for predicting EMVI of rectal cancer.
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Objective@#To investigate the characteristics of magnetic resonance imaging (MRI) of minimal deviation adenocarcinoma (MDA) of cervix, and improve the diagnostic accuracy of MDA.@*Methods@#The imaging data of eight cases of MDA was retrospectively collected, including tumor size, tumor location, tumor components, signal characteristics, enhancement characteristics and invasive extent.@*Results@#The maximum diameter of tumor was (4.36±1.46) cm. Six tumors were mixed solid and cystic and two were predominantly solid. Six were diffusion limited on diffusion-weighted imaging, and two were not diffusion limited. On multi-phase dynamic contrast-enhanced scan, the enhancement curve of solid components of the tumor showed a plateau-like pattern in three cases and a slow-rising pattern in five cases. Tumors were confined to the cervical canal in three cases, infiltrated to cervical stroma > 1/2 depth in seven cases, and ≤ 1/2 depth in one case. There were four cases of uterine invasion, four cases of vaginal fornix invasion, four cases of bilateral ovarian metastasis and one case of lymph node metastasis.@*Conclusions@#Patients suffering from large amount of vaginal discharge had cervical lesions on MRI showing polycystic and solid component enhancement should be alert to MDA. Deep-seated cervical biopsy and even conization is conducive to early diagnosis, treatment and improvement of prognosis.
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Objective@#To evaluate the value of T2WI signal intensity related parameters that can be obtained by magnetic resonance imaging (MRI) for predicting pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanved rectal cancer (LARC).@*Methods@#Signal Intensity of Tumor (SIT) and Signal Intensity of Tumor/Muscle (SIT/M) of MR T2WI before and after neoadjuvant chemoradiotherapy of 101 patients with locally advanced rectal cancer were evaluated by two experienced readers independently. Signal Intensity of Tumor Reduction Rate (SITRR) and Signal Intensity of Tumor/Muscle Reduction Rate (SIT/MRR) were calculated. The difference of related parameters of T2WI tumor signal intensity between the pCR and the non-pCR group were analyzed. Receiver operating characteristic (ROC) analysis was used to assess the diagnostic performance for predicting pCR.@*Results@#Of the 101 patients, 18 were in pCR group and 83 were in non-pCR group. In all patients, the SITpre, SITpost, SITRR, SIT/Mpre, SIT/Mpost and SIT/MRR measured by reader 1 were 197.0 (133.0), 144.2 (69.7), 0.4% (0.5%), 2.6 (0.6), 3.0 (2.3) and 0.4 (0.2)% in pCR group, and 227.0 (99.0), 205 (95.4), 0.1% (0.6%), 2.6 (0.6), 2.6 (1) in non-pCR group, respectively. SITpre, SITpost, SITRR, SIT/Mpre, SIT/Mpost and SIT/MRR measured by reader 2 were 193.0 (135.0), 143.0 (69.8), 0.4% (0.2%), 2.6 (0.6), 1.5 (0.5) and 0.39% (0.2%) in pCR group, and 234.0(108.0), 203(96.5), 0.1% (0.3%), 2.6 (0.6%), 1.7 (0.7) and 0.25% (0.2%) in non-pCR group, respectively. Between the pCR and non-pCR group, there were significant differences in SITpost, SIT/Mpost and SIT/MRR measured by both readers (all P<0.01), but there was no significant differences in SITpre and SIT/Mpre (P>0.05). The difference of SITRR measured by reader 1 was not statistically significant (P=0.415), while the difference of SITRR measured by reader 2 was statistically significant (P=0.001). In patients with rectal non-mucinous adenocarcinoma, SITpost, SIT/Mpost, SITRR and SIT/MRR measured by two physicians were still statistically significant between the pCR and non-pCR group (all P<0.01), but SITpre and SIT/Mpre had no significant difference (P>0.05). ROC curve analysis showed that in all patients, the area under curve (AUC) of SITpost, SIT/Mpost and SIT/MRR for predicting pCR to neoadjuvant chemoradiotherapy in locally advanced rectal cancer was 0.694-0.762, the sensitivity was 68.2%-77.3%, and the specificity was 63.6%-77.3%. In rectal non-mucinous adenocarcinoma patients, the AUC, sensitivity and specificity was 0.704-0.764, 62.7%-78.9% and 66.2%-84.2%, respectively.@*Conclusions@#T2WI signal intensity related parameters are potential predictors for pCR in locally advanced rectal cancer after neoadjuvant chemoradiptherapy. The predictive value is higher in non-mucinous adenocarcinoma.
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Objective@#To investigate the imaging appearance of CT and MRI in retroperitoneal dedifferentiated liposarcoma (DDL) based on pathological findings.@*Methods@#Twelve patients with retroperitoneal DDL (13 lesions) who were surgically and pathologically confirmed were retrospectively collected in the Cancer Hospital of Chinese Academy of Medical Sciences. The correlation of CT and MRI features with histopathologic findings was analyzed.@*Results@#The CT and MRI images of retroperitoneal DDLs were large, heterogeneous soft-tissue masses, mostly lobulated (30.8%, 4/13) or multinodular (46.2%, 6/13), invading adjacent anatomic structures (46.2%, 6/13). The lesions contained different proportions of fatty and non-fatty components, and usually with clear boundaries. The CT images of dedifferentiated components showed non-fatty masses of soft tissue density or mixed density, among which ground-glass nodules may be related to mucinous components. Occasionally calcification or ossification was seen (45.5%, 5/11). The contrast-enhanced CT and MRI images of non-fatty components commonly showed intense heterogeneous enhancement (84.6%, 11/13), central cystic changes and necrosis (61.5%, 8/13), pathologically corresponding to multiple types of soft tissue sarcomas without significant specificity. The well-differentiated components were fatty masses with irregular fibrous septa or soft tissue nodules, which is pathologically corresponding to well differentiated liposarcoma. Lymph node or distant metastasis was rare.@*Conclusions@#The imaging manifestations of retroperitoneal DDLs are diverse and closely related to the proportion and distribution of different components. CT, MRI and contrast-enhanced imaging has a certain diagnostic value for retroperitoneal DDLs.
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Objective@#To evaluate Magnetic Resonance Imaging (MRI) at 3.0T in differential diagnosis of the origin of adenocarcinoma at the junction of the lower uterine segment and endocervix.@*Methods@#71 patients with adenocarcinoma at the junction of the lower uterine segment and endocervix were retrospectively collected. Pelvic MR examinations, including diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) sequences, were performed within 2 weeks before surgery. MR images were analyzed and measured by two radiologists, including the location of the tumor center, the enhancement pattern, the anterior and posterior diameters, the left and right diameters, the upper and lower diameters, and the apparent diffusion coefficient (ADC) of the tumor. Immunohistochemical method was used as gold standard in distinguishing cervical adenocarcinoma and uterine adenocarcinoma.@*Results@#The upper and lower diameters of uterine adenocarcinoma were [(5.80±2.31) cm], significantly larger than those of cervical adenocarcinoma [(4.16±2.17) cm, P=0.009]. Using 4.5cm as the best cutoff point value, the sensitivity and specificity in distinguishing uterine adenocarcinoma and cervical adenocarcinoma were 68.4% and 65.4%, respectively. According to the location of tumor center, the sensitivity and specificity were 84.2% and 73.1%, respectively. Using tumor enhancement pattern as the criterion, the sensitivity and specificity of diagnosing uterine adenocarcinoma and cervical adenocarcinoma were 68.4% and 80.8% respectively.@*Conclusions@#MRI has certain clinical value in evaluating the origin of adenocarcinoma at the junction of the lower uterine segment and endocervix. The lesions can be diagnosed according to the main location, the characteristics of dynamic enhancement and the growth pattern of the tumor.
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Objective@#To compare the diagnostic value of T2 weighted imaging (T2WI), diffusion-weighted imaging (DWI), and T2WI+ DWI magnetic resonance imaging (MRI) for staging of rectal cancers for improving the accuracy of tumor staging.@*Methods@#From January 2011 to December 2013, 120 cases of rectal cancers proved by colonoscopy without receiving any anti-tumor treatment were enrolled retrospectively. The MRI data for these patients were divided into three groups, ie., T2WI, DWI and T2WI+ DWI, for evaluating the tumor stages. The results were compared with histopathologic findings. The sensitivity and specificity were calculated and compared with chi-square test. The nodal staging was predicted by using T2WI+ DWI.@*Results@#The accuracy for prediction of tumor staging was 83.3%, 65.0% and 92.5% for T2WI, DWI, and T2WI+ DWI respectively. The specificity for evaluating T1 and T2 stage, and the sensitivity for evaluating T3 by DWI was significantly lower than those using T2WI and T2WI+ DWI in rectal cancers. The sensitivity for evaluation of T2 by DWI was lower than that using T2WI+ DWI (63.0% vs. 88.9%). The sensitivity for evaluation T2 and specificity for T3 by T2WI+ DWI was higher than thouse using T2WI only (88.9% vs. 51.9%, 94.0% vs. 72.0%). The accuracy for prediction of nodal staging by using T2WI+ DWI was 62.1% (72/116).@*Conclusions@#T2WI is the key sequence for staging of rectal cancers. Although the diagnostic accuracy was not good by using DWI alone, the combination of T2WI and DWI can improve the accuracy significantly for tumor staging in rectal cancers, whereas the nodal staging was still a hard task for radiologists.
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Objective To compare the predictive value of radiomics signature extracted from MRI plain and enhancement sequence for the disease-free survival (DFS) of rectal cancer. Methods We retrospectively analyzed fifty-one patients with rectal adenocarcinoma confirmed by biopsy from October 2010 to December 2013 in Cancer Hospital Chinese Academy of Medical Sciences.All patients underwent neoadjuvant chemotherapy(nCRT)followed total mesorectal excision(TME),and MRI scans were performed before nCRT.Follow-up time for the survival patients were more than 3 years.The image segmentation was performed on the T2WI sequence of the small FOV and the multi-phase enhancement sequence venous phase,respectively.Least absolute shrinkage and selection operator(LASSO)Cox regression was applied to extract radiomics features and the imaging signature was constructed. According to the radiomics score of each patient,the patients were divided into the high risk group with shorter DFS and the low risk group with longer DFS. A 3-year DFS was calculated for radiomics signature using the Kaplan-Meier product limit method with univariate log-rank analysis testing for differences in the training and validation cohort, respectively. And the predictive ability of the model was evaluated by concordance index (C-index). Results The training set and the validation set were 36 and 15 cases, respectively. During follow-up 32 patients experienced relapse(26 distant,3 local and 3 both),and 19 cases were censored.Twelve features were extracted in the enhanced sequence.The radiomics signatures were significant for DFS in the training set and the validation set(P=0.000 2 and 0.009 1,respectively).The C-index of the model were 0.904 and 0.700 in the training set and the validation set, respectively. The model has the better ability to predict survival.Two features were extracted in the plain sequence.The radiomic signature was significant for DFS in the training set(P=0.005 0),while the radiomics signature was not significant for DFS in the validation set (P=0.767 0). The C-index of the model were 0.711 and 0.500 in the training set and the validation set, respectively.Conclusions Radiomics signature extracted from MRI venous phase enhancement sequence superior to plain sequence for predicting the DFS of rectal cancer before nCRT.
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Objective To investigate the prognostic value of the texture analysis contrast-enhanced MR imaging (DCE-MRI) in predicting microvascular invasion in hepatocellular carcinoma (HCC) before operation. Methods Sixty patients with HCC confirmed by pathology in the Chinese Academy Medical Sciences from January 2014 to December 2016,were enrolled in our study retrospectively.According to the post-operative pathology, the patients were divided into positive microvascular invation[MVI(+)]group including 30 patients, and negative MVI[MVI(-)] group including 30 patients. All patients underwent normal MR and DCE-MRI before surgery.Sixty seven texture features were extracted from the original data of arterial phase (AP) and portal venous phase (PVP) of DCE-MRI. All data were calculated by using Omni-Kinetics(OK)software of the United States.The difference between MVI(+)group and MVI(-)group was statistically significant using the independent sample t test. The identified methods of the DCE-MR texture features in predicting MVI adopted the principal component analysis (PCA) and the establishing prediction model including dimensionality reduction, modeling, prediction and verification. The model was established by logistic regression method. According to the histopathology, 80% data of AP and PVP were used as training group[48 cases,MVI(+)and MVI(-)group 24 cases respectively],20% as validation group [12 cases, MVI(+) and MVI(-) group 6 cases respectively]. The DCE-MRI images of AP and PVP were modeled and cross-referenced respectively, and the diagnostic efficiency of ROC evaluation model was adopted. Results There were 15 significant different texture features of the AP and three significant different texture features of the PVP between MVI(+) group and MVI(-) group respectively. The PCA method extracted the important DCE-MRI texture features and analyzed the 15 features of AP.The UPP and energy showed a good correlation(r>0.90),therefore the UPP were removed.Fourteen texture features were analyzed using the PCA method.There were four important texture features including the GLCM Correlation, Hara Variance, GLCM sum Variance and GLCM sum Entropy in the AP. Moreover, there were three important texture features including GLCM difference Entropy, Long Run Low Grey Level Emphasis and GLCM difference Variance in the PVP.Through the prediction model was established and crossly validated. There were three significant different texture features in the AP of DCE-MRI,including GLCM Correlation, GLCM Contrast and GLCM sum Entropy.And there were two significant different texture features in the PVP of DCE-MRI,including GLCM difference Variance and Long Run Low Grey Level Emphasis.In the training and validation group,the areas under the ROC of the AP model and PVP model were 0.774,0.681,0.889 and 0.611 respectively.The diagnosed accuracy rate of the AP model(83.30%,10/12)was higher than that of the PVP model(42.00%,5/12).Conclusion The DCE-MRI texture analysis technique could predict the MVI of HCC before operation,and the predictive accuracy of the AP texture feature was higher.
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Objective@#To investigate the prognostic value of quantitative parameters of dynamic contrast-enhangced MR (DCE-MR) on short-term efficacy of transcatheter arterial chemoembolization (TACE) on hepatocellular carcinoma(HCC).@*Methods@#79 patients with HCC underwent non-enhanced MR imaging and DCE on a 3.0T MR scanner before and one month after TACE. The quantitative parameters were measured on the maximal tumor region, including maximal tumor diameter(MTD), ADC, Ktrans, Kep and Ve value before and after TACE. All patients were divided into stable group (36 patients) and progressive group (43 patients) based on follow-up. The quantitative data of the two groups before and after TACE was collected for analysis.@*Results@#Among the 79 lesions in 79 patients, 21 were located in the left lobe of the liver, 53 in the right lobe of the liver and 5 in the junction area of the hepatic lobe. The maximum tumor diameter (MTD) was 2.2-9.9 cm, the median MTD was 5.1 cm. There were significant differences between progressive group and the stable group in MTD, Ktrans, Kep values of the tumor before TACE (P<0.05). One month after TACE, the MTD, Ktrans, Kep,ΔMTD, ΔKtrans and ΔKep values of the tumor in progressive group were statistically different with the stable group (P<0.05, respectively). For all the patients, the pre-TACE MTD, AFP, Ktrans and Kep values of tumors were statistically different with the post-TACE values (P<0.05).@*Conclusion@#The quantitative parameters (Ktrans, Kep,ΔKtrans and ΔKep values) of the DCE-MR could predict and evaluate the short-term efficacy of TACE on HCC.
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Objective@#To study the measurement reproducibility of parameters derived from introvoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI)-MRI of rectal cancer between- and within- radiologists.@*Methods@#Clinical data of 34 patients with rectal cancer were prospective analyzed. Conventional MRI sequences, IVIM DWI-MRI with sixteen b values and dynamic contrast enhancement (DCE)-MRI sequences of rectum were acquired by GE 3.0-T MRI imager. The IVIM sequence images with b value=1000 sec/mm2 were selected to measure the maximum axial section of tumor by a radiologist with 15 year-experiences in gastrointestinal cancer imaging.Two radiologists (radiologist 1 and radiologist 2 with 2 and 10 years of experience in gastrointestinal cancer imaging, respectively) independently draw a freehand region of interest (ROI) that contained the largest available tumor area on the selected section. Monoexponential apparent diffusion coefficient (ADC) and biexponential IVIM metrics maps and IVIM parameters were generated automatically by the software. The repeated measurement was performed at an interval of one week. The average values of each measurement were used for statistical analysis. ADC values and IVIM parameters obtained between- and within- radiologists were analyzed by Wilcoxon signed-rank test. Intraclass correlation coefficients (ICC) and Bland-Altaman plots were used to analyze the parameter reproducibility of two measurements between- and within- radiologists.@*Results@#The first and second measured ADC (×10-3mm2/s), true diffusivity (D, ×10-3mm2/s), false diffusivity (D*, mm2/s) and perfusion fraction (f, %) by radiologist 1 were 0.997, 0.692, 0.043, 34.6 and 0.993, 0.691, 0.038, 32.8, respectively. The first and second measured ADC (×10-3mm2/s), D (×10-3mm2/s), D* (mm2/s), f (%) by radiologist 2 were 0.987, 0.651, 0.046, 32.8 and 0.996, 0.689、0.041, 32.7, respectively. No statistically significant differences were observed in ADC and IVIM parameters obtained between- and within- radiologists (P>0.05). The ADC values and the f values of two times were significantly correlated between- and within- radiologists. The D values were significantly correlated within a radiologist, and the correlation of D* values within a radiologist was significantly higher than that between radiologists. The 95% limits of agreement (LoA) of ADC values and f values were smaller than those of D values and D* values between- and within- radiologists. The 95% LoA of ADC values was the least, while that of D* values varied most.The 95% LoA of f values and D values kept steady within a radiologist, and 95% LoA of f values was slightly smaller than that of D values. The 95% LoA of IVIM parameters (ADC, D, f, D* values) within radiologists 2 were better than those within radiologist 1.@*Conclusions@#The reproducibilities of ADC and f values are the best, while the reproducibility of D* values is relatively poorer in rectal cancer. Measurement reproducibility of parameters derived from IVIM may be improved by increasing radiologists’ experiences in drawing ROI.
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Objective To explore the effect of the procedural nursing management on nursing quality of hospitalized patients in department of rheumatology. Methods About 267 inpatients were divided into control group (n=125) and experiment group (n=142). The control group received routine medication nursing and the experiment patients were treated with procedural nursing management including implementing medication services and analyzing the factors influencing precise medication and the countermeasures . Result The rate of precise medication in the experiment group was significantly higher than that of the control group ( P<0 . 05 ) . Conclusions The procedural nursing management can promote patient's precise medication so as to ensure the therapeutic effect by medication . It does good for the promotion of medication scientizeation and professionalization .
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Objective To analyze the CT and MRI features of pancreatic serous micro-cystic cystadenoma (SMCA).Methods CT and MRI data of 17 patients with SMCA confirmed by pathology were analyzed retrospectively.Tumor's location,diameter,septation,contrast-enhancement features,calcification,central scar, and the extent of pancreaticobiliary duct dilatation were recorded.Results Seventeen patients were enrolled.10 underwent CT,6 underwent MR(2 patients also underwent MRCP), and 1 underwent both CT and MR.Tumors were located at pancreatic head in 2 cases,neck in 2 cases,and body/tail in 13 cases.Lesion size ranged from 1.7 cm to 14 cm with an average of 5.2 cm.Septation was seen in 16 cases.Central scar was seen in 9 cases Septation and scar were enhanced and cystic component was not enhanced on contrast enhancement.6 patients presented the main pancreaticduct dilation.Conclusion Pancreas SMCA has certain imaging features.It is always manifested as lobulated mass with multiple small capsules(<2 cm) and fiber separations.The fiber separation enhance significantly,but lower than normal pancreatic tissue.Central scar is the characteristic manifestation of SMCA, and it manifests iso or slightly lower signal on T1WI and T2WI.Typical SMCA can be diagnosed according to the CT and MR imaging manifestations.
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Objective To explore the value of pelvic MRI combined with clinical information in diagnosis of endometrial cancer (EC) with ovarian malignant tumor (OMT) using decision tree analysis.Methods The clinical information and pelvic MRI characteristics of 58 cases with ovarian malignant tumor (EC-OMT group) and 743 cases without ovarian malignant tumor (EC group) were reviewed and compared.The diagnostic efficacy of pelvic MRI was evaluated.Decision tree analysis was used in determining the performance on the diagnosis.Results In EC-OMT group,the depth of myometrial invasion,the frequency of cervical and cornua uteri involvement,adnexal mass,pelvic or para-aortic lymph nodes involvement and peritoneum metastasis were higher than those in EC group (all P＜0.01).Para-uterine involvement showed no significant difference between two groups (1.72％ vs 0.40％,P=0.26).In diagnosis of EC with OMT,the sensitivity and specificity value of MRI was 51.72％ (30/58) and 99.87％ (742/743),respectively.Cornua uteri involvement,adnexal mass and CA125 level were screened as helpful indicators for pre-operation diagnosis by decision tree,and the sensitivity was 89.66％ (52/58).Conclusion The diagnosis model of pelvic MRI combined with clinical information by using decision tree analysis can promote sensitivity in diagnosis of EC with OMT.
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Objective To evaluate the value of MRI texture analysis (TA) in prediction of treatment response neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer patients. Methods Fifty nine histopathologically-proven rectal adenocarcinoma patients through biopsy treated with nCRT before total mesorectal excision were enrolled in this retrospective study.The first MRI examination (pre-nCRT MRI)was performed before nCRT,and the second one(early nCRT MRI)was performed at the third week of nCRT. The texture parameters values were measured, including mean value, standard deviation, skewness, kurtosis, uniformity, energy, and entropy. Tumoral downstaging was determined by comparing the pre-nCRT clinical T stage(cT stage) with the ypT stage. The patients were divided into downstaging and non downstaging group based on postoperative T staging. Parameters were compared between pre-and early nCRT in terms of averages using Wilcoxon signed-rank test. Downstaging and non downstaging groups were analyzed using Mann-Whitney U test.Multivariate logistic regression analysis was performed using the statistically significant parameters between the two groups as independent variables. ROC analysis was performed on the new independent variables obtained by multi-parameter logistic regression analysis and the single parameter independent variables. The diagnostic efficiency of the parameters were evaluated. Results T-downstaging were found in 28 patients after nCRT. The stdDeviation, kurtosis, and uniformity were significantly different between pre-and early nCRT (P<0.05). There was no significant difference in mean value, skewness, energy, and entropy between pre-and early nCRT (P>0.05). The pre-nCRT, uniformity, energy, entropy and the early nCRT mean value, entropy were significantly different in patients with downstaging vs. non downstaging (P<0.05). For the pre-nCRT stdDeviation,uniformity,energy,entropy and the early nCRT mean value,entropy,ROC analysis showed an area under curve(AUC) of 0.69, 0.76, 0.68, 0.67 and 0.65, 0.68, respectively. The multivariate logistic regression analysis for the four pre-nCRT independent variables(stdDeviation,uniformity,energy,entropy) achieved logical variable 1,and the logical variable 1 achieved an AUC of 0.78 to discriminate patients with T-downstaging from patients with non downstaging.The multivariate logistic regression analysis for the two early nCRT independent variables(mean value,entropy)achieved logical variable 2,and the logical variable 2 achieved an AUC of 0.69 to predict T-downstaging.Conclusion Pre-and early nCRT MRI TA in rectal cancer have the efficacy to predict treatment response.
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Objective The aim of this study was to determine whether multi?parameters MRI of tongue carcinoma have the potential to predict cervical lymph node metastases. Methods A total of 46 patients with tongue carcinoma, who underwent MRI scan preoperatively, were investigated retrospectively and were divided into cervical lymph node (LN) metastases group (unilateral LN+, n=16;bilateral LN+, n=14) and no cervical lymph node metastases group (LN-, n=16) according to their pathological grading. Of the 40 patients with tongue carcinoma underwent plain and contrast MRI scan, 6 patients have plain MRI scan, and 32 have DWI examination.The ADC value, tumor length, tumor thickness, sublingual distance between tumor and sublingual space, and para?lingual distance between tumor and tongue midlinedetermined from MRI, were preoperatively estimated and compared with the pathological findings of cervical lymph nodes. A unpaired t test was used to analyze normal distributed continuous data, and a Mann?Whitney U test was used to analyze abnormally distributeddata. The ROC was used to evaluate the efficacy of MRI in predicting the metastasis of cervical lymph nodes. Results The indexes of ADC value, tumor length, tumor thickness, and para?lingual distance between tumor and tongue midline, which all showed significant difference between LN+group and LN-group (all P0.05). The index of ADC value showed significant difference between unilateral LN+group and bilateral LN+group (P0.05). The ROC curve analysis of the ADC value, tumor length, tumor thickness, and para?lingual distance between tumor and tongue midline of the neck lymph node metastasis were carried out, with the cutoff set as 1.13×10?3 mm2/s, 31.08 mm, 17.33 mm and-2.26 mm. The corresponding area under curve(AUC), sensitivity, and specificity were 0.878, 90.9%and 90.0%; 0.822, 83.3% and 81.3%; 0.834, 86.7% and 81.3%; 0.794, 86.7% and 75.0%, respectively. The ROC curve analysis of the ADC of the bilateral neck lymph node metastasis was also carried out, with the cutoff of ADC value set as 1.07×10?3 mm2/s, the corresponding AUC, sensitivity, and specificity were 0.806, 80.0%and 75.0%. Conclusion The ADC value, tumor length ,tumor thickness and para?lingual distance between tumor and tongue midline,determined from MR imaging, all can be used as independent factors in predicting cervical lymph node metastasis, where ADC value may be helpful to predict bilateral neck lymph node metastasis.