OBJECTIVES:This study aimed to compare image quality and diagnostic performance between artificial intelligence-assisted compressed sensing (ACS) images reconstructed using deep learning reconstruction (ACS-DLR) and conventional parallel imaging (PI) images in rectal cancer MRI. METHODS:107 patients with biopsy-proven rectal cancer were included. MRI included conventional PI and ACS acquisitions, with the ACS raw data reconstructed at three deep learning reconstruction strength levels (ACS-L, ACS-M, and ACS-H). Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were compared across four image sets using the Friedman test. Subjective image quality was assessed using a 5-point Likert scale for overall image quality, noise, artefact, and edge sharpness. Interobserver agreement for objective metrics was measured by ICC, and for subjective metrics by Cohen's kappa. Diagnostic performance was evaluated using postoperative histopathology, including T stage, N stage, extramural venous invasion (EMVI), and mesorectal fascia (MRF) involvement. RESULTS:ACS reduced acquisition time by 50 % (from 3 min 20 s to 1 min 40 s). Lesion SNR did not differ significantly among the four image sets (P > 0.05), but ACS-H showed the highest muscle SNR. CNR showed significant differences in selected pairwise comparisons. ACS-H achieved the highest subjective scores for overall image quality, noise reduction, and lesion edge sharpness. In the surgical subcohort, ACS-H improved T staging accuracy (P = 0.010; P = 0.018), MRF involvement assessment (P = 0.004; P = 0.012), and EMVI sensitivity (P = 0.039; P = 0.041). N staging accuracy was not significantly different (P = 0.521; P = 0.841). CONCLUSION:ACS reduced acquisition time, while ACS-DLR improved subjective image quality. ACS-H improved T-stage and MRF assessment and increased EMVI sensitivity, whereas N-stage accuracy did not improve significantly.

To explore the added value of the combination of radiomics and visual features based on contrasted enhanced computed tomography (CECT) images for predicting the invasiveness of pure ground-glass nodules (pGGNs). The clinical and imaging data of 123 patients with 143 pGGNs confirmed by surgical pathology were retrospectively analyzed. The lesions-based dataset was randomly divided with a ratio of 7:3 into training set and test set. Radiomics models and visual features model were constructed independently using logistic regression. Two combined model of 2D + and 3D + were also established. The performance of the five models was evaluated via receiver operating characteristic (ROC) curve analysis and the clinical validity was assessed by using the model’s integrated discrimination improvement (IDI) indices. The 3D + model and 2D + model performed better with higher AUC (training: 0.839/0.793; test: 0.829/0.794) than three independent models alone (all P < 0.05) and the DCA showed the IDI of 3D + model had a significant improvement in the test set than 2D + model, 3D radiomics model and visual features model (9.96

OBJECTIVES:Prostate cancer significantly impacts men's health, highlighting the necessity for precise diagnosis. This study evaluates combining Magnetic Resonance Image Compilation (MAGiC) parameters with Prostate Imaging Reporting and Data System (PI-RADS) scores to enhance diagnostic accuracy among radiologists with varied experience. METHODS:In this retrospective study, 174 patients with suspected prostate cancer were recruited from February 2023 to May 2024. Synthetic MRI-derived T1, T2, and proton density (PD) maps were generated, and synthetic T2-weighted imaging (T2WI) was reconstructed. Two radiologists of varying experience independently assessed lesions using PI-RADS based on both synthetic and conventional T2WI. Image quality was evaluated using the prostate imaging quality (PI-QUAL) scoring v2 system, and diagnostic performance was analyzed using receiver operating characteristic (ROC) curve analysis. RESULTS:Synthetic T2WI exhibited comparable image quality to conventional T2WI (P = 0.065). After excluding low-quality images, 99 lesions were analyzed. In the peripheral zone, higher T1 values were significantly linked to non-cancerous lesions (R1: OR = 0.989, P = 0.009; R2: OR = 0.990, P = 0.004). The integration of T1 values with PI-RADS scores improved diagnostic performance, achieving area under the curve (AUC) values of 0.960 for R1 and 0.944 for R2. CONCLUSION:The integration of MAGiC parameters, particularly T1 values, with PI-RADS scores significantly enhances diagnostic accuracy for clinically significant prostate cancer, especially benefitting less experienced radiologists. Additionally, synthetic T2WI demonstrates comparable image quality to conventional T2WI, supporting the clinical implementation of MAGiC parameters in prostate MRI assessments.

RATIONALE AND OBJECTIVES:To evaluate the diagnostic performance of diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), mean apparent propagator (MAP), neurite orientation dispersion and density imaging (NODDI), and the Vesical Imaging-Reporting and Data System (VI-RADS) in discriminating the pathological grade of bladder urothelial carcinoma (UCB). MATERIALS AND METHODS:This prospective study enrolled patients with pathologically confirmed UCB between May 2023 and December 2023. Preoperative MRI protocols included spin-echo echo-planner imaging (SE-EPI) and conventional DWI. Quantitative parameters from SE-EPI (DTI, DKI, MAP, NODDI) and apparent diffusion coefficient (ADC) values were measured. Group comparisons between low-grade and high-grade UCB were performed using t-tests or Mann-Whitney U tests. Receiver operating characteristic (ROC) analysis and DeLong's test were used to evaluate diagnostic performance. RESULTS:A total of 50 patients with UCB (low-grade/ high-grade = 16/34) were included. VI-RADS score and mean kurtosis (MK) derived from DKI emerged as independent predictors for differentiating low-grade and high-grade UCB (area under the curve (AUC): 0.692 and 0.865, respectively). The combination of VI-RADS and DKI-MK achieved superior diagnostic performance (AUC: 0.915, sensitivity: 0.941) compared to VI-RADS alone (AUC: 0.692, sensitivity: 0.471; p < 0.001) or ADC alone (AUC: 0.787, sensitivity: 0.813; p < 0.05). CONCLUSION:Integrating VI-RADS with DKI-MK significantly enhances preoperative assessment of UCB pathological grading, demonstrating higher accuracy and sensitivity than VI-RADS or ADC alone. This approach improves diagnostic objectivity by combining qualitative imaging criteria with quantitative diffusion metrics, offering potential clinical utility for treatment stratification.

To investigate the prognostic value of apparent diffusion coefficient (ADC) metrics, MRI characteristics, and clinicopathological parameters in predicting non-muscle-invasive bladder urothelial carcinoma (UCB) recurrence, and to develop a novel multiparametric risk stratification framework. This retrospective single-center study (n = 135) with histologically confirmed non-muscle-invasive UCB diagnosed between January 2015 and March 2023. ADC values, vesical imaging reporting and data system (VI-RADS) scores, and clinicopathological variables were analyzed with recurrence-free survival (RFS) as the primary endpoint. Prognostic determinants were identified using univariate and multivariate Cox proportional hazard regression models. An advanced risk stratification system was developed using independent predictors and validated against the European Association of Urology (EAU) risk classification using concordance index (C-index). Multivariate analysis identified three independent predictors: ADC values (HR = 0.104, 95

BackgroundThis study aims to develop and validate a pretreatment MRI-based radiomics model to predict lymph node metastasis (LNM) following neoadjuvant chemotherapy (NACT) in patients with locally advanced cervical cancer (LACC).MethodsPatients with LACC who underwent NACT from two centers between 2013 and 2022 were enrolled retrospectively. Based on the lymph node (LN) status determined in the pathology reports after radical hysterectomy, patients were categorized as LN positive or negative. The patients from center 1 were assigned as the training set while those from center 2 formed the validation set. Radiomics features were extracted from pretreatment sagittal T2-weighted imaging (Sag-T2WI), axial diffusion-weighted imaging (Ax-DWI), and the delayed phase of dynamic contrast-enhanced sagittal T1-weighted imaging (Sag-T1C) for each patient. The K-best and least absolute shrinkage and selection operator (LASSO) methods were employed to reduce dimensionality, and the radiomics features strongly associated with LNM were selected and used to construct three single-sequence models. Furthermore, clinical variables were incorporated through multivariate regression analysis and fused with the selected radiomics features to construct the clinical-radiomics combined model. The diagnostic performance of the models was assessed using receiver operating characteristic (ROC) curve analysis. The clinical utility of the models was evaluated by the area under the ROC curve (AUC) and decision curve analysis (DCA).ResultsA total of 282 patients were included, comprising 171 patients in the training set, and 111 patients in the validation set. Compared to the Sag-T2WI model (AUC, 95%CI, training set, 0.797, 0.722-0.782; validation set, 0.648, 0.521-0.776) and the Sag-T1C model (AUC, 95%CI, training set, 0.802, 0.723-0.882; validation set, 0.630, 0.505-0.756), the Ax-DWI model exhibited the highest diagnostic performance with AUCs of 0.855 (95%CI, 0.791-0.919) in training set, and 0.753 (95%CI, 0.638-0.867) in validation set, respectively. The combined model, integrating selected features from three sequences and FIGO stage, surpassed predictive ability compared to the single-sequence models, with AUC of 0.889 (95%CI, 0.833-0.945) and 0.859 (95%CI, 0.781-0.936) in the training and validation sets, respectively.ConclusionsThe pretreatment MRI-based radiomics model, integrating radiomics features from three sequences and clinical variables, exhibited superior performance in predicting LNM following NACT in patients with LACC.

To investigate the prognostic value of lymph node status in patients with cervical cancer (CC) patients who underwent neoadjuvant chemotherapy (NACT) and followed hysterectomy. Patients in two referral centers were retrospectively analyzed. The baseline tumor size and radiological lymph node status (LNr) were evaluated on pre-NACT MRI. Tumor histology, differentiation and pathological lymph node status (LNp) were obtained from post-operative specimen. The log-rank test was used to compare survival between patient groups. Cox proportional hazards regression models were employed to estimate the hazard ratio (HR) of various factors with progression-free survival (PFS) and overall survival (OS). A total of 266 patients were included. Patients with 2018 FIGO IIIC showed worse PFS compared to those with FIGO IB-IIB (p < 0.001). The response rate in patients with LNp(−) was 64.1% (134/209), significantly higher than that of 45.6% (26/57) in patients with LNp( +) (p = 0.011). Multivariate Cox analysis identified the main independent predictors of PFS as LNp( +) (HR = 3.777; 95% CI 1.715–8.319), non-SCC (HR = 2.956; 95% CI 1.297–6.736), poor differentiation (HR = 2.370; 95% CI 1.130–4.970) and adjuvant radiation (HR = 3.266; 95% CI 1.183–9.019). The interaction between LNr and LNp regarding PFS were significant both for univariate and multivariate (P = 0.000171 and 1.5357e−7 respectively). In patients with LNr( +), a significant difference in PFS was observed between patients with LNp(−) and LNp( +) (p = 0.0027). CC patients with FIGO 2018 stage IIIC who underwent NACT and followed hysterectomy had worse PFS compared to those with IB-IIB. LNp( +), non-SCC, poor differentiation and adjuvant radiation were independent risk factors for PFS. The adverse prognostic value of LNp( +) was more significant in patients with LNr( +).

Rationale and Objectives: To evaluate the potential of Synthetic Magnetic Resonance Imaging (SynMRI) in identifying muscular invasion in bladder cancer (BCa), and explore whether there is additional value in combination with the Vesical Imaging-Reporting and Data System (VI-RADS). Methods: In this prospective single-center study, pathologically-confirmed BCa were enrolled between May 2023 and November 2023. All participants underwent preoperative multiparametric MRI, including T1/T2 weighted, SynMRI and diffusion-weighted imaging. T1/T2/PD values and apparent diffusion coefficient (ADC) values were compared between muscle invasive (MIBC) and non-invasive (NMIBC) groups. Receiver operating characteristic (ROC) analysis with the variables and their combination was performed to explore the performance of distinguishing the MIBC from NMIBC, and the ROC curves were compared using DeLong's test. Results: A total of 54 BCa patients were enrolled (38 males; NMIBC/MIBC = 37/19) and all assessed with VI-RADS without dynamic enhanced imaging (DCE). Compared to NMIBC group, MIBC group had significantly larger diameter, higher VI-RADS score, lower T2 and ADC values (P < 0.05). VI-RADS score and T2 showed independent predictive value in differentiating NMIBC and MIBC. The combined model (T2 + VI-RADS + Diameter) resulted in significantly improved specificity (0.842), sensitivity (0.914), and AUC (0.943), in comparison to VI-RADS or ADC alone (P < 0.05). Conclusion: T2 relaxation time can be easily obtained from SynMRI in routine clinical protocol and assist VI-RADS score system without DCE to improve differentiation performance in identifying NMIBC and MIBC.

目的:探讨MRI在G1/G2胰腺神经内分泌肿瘤(pNENs)病理分级及临床分期中的价值,寻找同时与G1/G2 pNENs病理分级及临床分期相关的MRI征象.方法:回顾性分析62例经手术病理证实为pNENs患者的临床及MRI资料,采用独立样本t检验、秩和检验、卡方检验、Fisher's精确概率法等对pNENs不同病理分级及临床分期的临床表现及MRI征象进行比较.结果:边界是否清晰、肿瘤直径、有无周围组织浸润、增强后强化均匀与否、ADC比值在不同pNENs病理分级及临床分期间的差异均有统计学意义(P值均<0.05).DWI信号及静脉期、延迟期MRI信号在不同病理分级间的差异均有统计学意义(P值均<0.05);性别、pNENs病灶呈囊实性、淋巴结转移及肝转移情况在不同临床分期间的差异均有统计学意义(P值均<0.05).结论:边界不清、强化不均、周围组织浸润、较大的肿瘤直径、较低的ADC比值同时与pNENs较高的病理分级及临床分期相关,MRI检查有助于术前准确且全面评估pENEs的异质性,辅助患者的个性化治疗.

目的 评价动态对比增强MRI(DCE-MRI)放射状采集容积内插屏气检查(Radial-VIBE)序列定量参数预测膀胱癌病理学分级的价值.方法 前瞻性纳入60例经术后病理证实为膀胱尿路上皮癌的膀胱癌患者,将其分为低级别组(n=36)和高级别组(n=24).比较组间DCE-MRI参数,包括容积转运常数(Ktrans)、速率常数(Kep)、血管外细胞外间隙容积(Ve)及对比剂浓度-时间曲线下初始面积(IAUC)的差异;采用组内相关系数(ICC)评价观察者间测量结果的一致性.采用Spearman秩相关分析评价各参数与膀胱癌病理分级的相关性.绘制受试者工作特征(ROC)曲线,计算曲线下面积(AUC),评价各参数预测高级别膀胱癌的效能.结果 观察者间测量定量参数Ktrans、Kep、Ve及IAUC结果的一致性良好(ICC=0.82、0.83、0.83、0.85,P均<0.05).高级别组Ktrans、Kep及IAUC均显著高于低级别组(P均<0.05),Ve显著低于低级别组(P<0.05).Ktrans、Kep及IAUC均与病理分级呈正相关(r=0.61、0.54、0.29,P均<0.05),Ve与病理分级呈负相关(r=-0.36,P<0.05).Ktrans、Kep及IAUC预测高级别尿路上皮癌的AUC分别为0.86、0.82及0.67.结论 DCE-MRI Radial-VIBE序列定量参数Ktrans、Kep、Ve及IAUC可辅助预测膀胱癌病理学分级.

目的 对比基于逐层匀场技术弥散加权成像(iShim-DWI)与常规弥散加权成像(DWI)图像质量,评估iShim-DWI对膀胱癌的应用价值.方法 回顾性分析70例经手术病理证实的膀胱癌患者,依据TNM分期将其分为肌层浸润性膀胱癌(MIBC)组(n=34)和非肌层浸润性膀胱癌(NMIBC)组(n=36),根据术后病理分级分为低级别尿路上皮癌组(n=38)和高级别尿路上皮癌组(n=32).观察常规DWI和iShim-DWI图像质量的差异.测量iShim-DWI病灶表观弥散系数(ADC),比较NMIBC组与MIBC组、高、低级别尿路上皮癌组ADC差异.以受试者工作特征(ROC)曲线评估ADC鉴别膀胱癌肌层浸润及高、低级别膀胱癌和T2WI、传统DWI及iShim-DWI诊断膀胱癌肌层浸润的效能.结果 2名医师对 iShim-DWI 图像的主观评分均高于传统 DWI(P 均＜0.01).NMIBC 组 ADC[1.12(1.06,1.18)×10-3 mm2/s]大于MIBC 组[0.81(0.75,0.83)×10-3 mm2/s,Z=-6.79,P＜0.01],ADC 鉴别 MIBC 与 NMIBC 的 AUC 为0.97;低级别尿路上皮癌组 ADC[1.13(1.06,1.17)×10-3 mm2/s]大于高级别尿路上皮癌组[0.80(0.74,0.82)×10-3 mm2/s,Z=-6.79,P＜0.01],AUC为0.99.基于T2WI+常规DWI诊断膀胱癌肌层浸润的AUC均低于T2WI+iShim-DWI(P均＜0.05).结论 iShim-DWI有助于评估膀胱癌病理分级及肌层浸润,且图像质量优于常规DWI.

Depth of invasion (DOI) can be calculated preoperatively by MRI, and whether MRI-determined DOI can predict prognosis as well as whether it can be used as an indicator of neck dissection in cT1N0 tongue squamous cell carcinoma (SCC) remains unknown. The main goal of the current study was to answer these unknowns. A total of 151 patients with surgically treated cT1N0 tongue SCC were retrospectively enrolled, and MRI-determined DOI was measured based on T1-weighted layers with a 3.0T scan. The Chi-square test was used to evaluate the association between clinical pathologic variables and neck lymph node metastasis, and the factors that were significant in the Chi-square test were then analyzed in a multivariate logistic regression analysis model to determine the independent predictors. The main study endpoints were locoregional control (LRC) and disease-specific survival (DSS), and the Kaplan-Meier method (log-rank test) was used to calculate the LRC and DSS rates. The factors that were significant in univariate analysis were then analyzed in the Cox model to determine the independent prognostic factors. A value of p < 0.05 was considered significant, and all statistical analyses were performed with SPSS 20.0. Occult neck lymph node metastasis was noted in 26 (17.2%) patients, and the ROC curve indicated that the optimal cutoff value of MRI-determined DOI was 7.5 mm for predicting neck lymph node metastasis, with a sensitivity of 86.9%. The factors of lymphovascular invasion, MRI-determined DOI, pathologic DOI, and pathologic tumor grade were significantly associated with the presence of neck lymph node metastasis in univariate analysis, and further logistic regression analysis confirmed the independence of lymphovascular invasion, MRI-determined DOI, and pathologic DOI in predicting neck lymph node metastasis. The 5-year LRC and DSS rates were 84% and 90%, respectively. Cox model analysis suggested the MRI-determined DOI was an independent prognostic factor for both LRC and DSS. Therefore, elective neck dissection is suggested if MRI-determined DOI is greater than 7.5 mm in cT1N0 tongue SCC, and MRI-determined DOI ≥ 7.5 mm indicates additional risk for disease recurrence and cancer-related death.

目的 评估两种平扫T1 mapping 的成像方法(自由呼吸Look-locker序列和屏气B1-corrected VFA variable-flipangle(VFA)序列)在上腹部组织(脾脏、胰腺、双肾皮质及髓质、腹直肌及竖脊肌)所得T1值的定量特征,并评价其变异度.方法 对66名患者行Look-locker序列和B1-corrected VFA序列;测量两种序列在上腹部组织所得T1值,并比较所得T1值的差异,以P＜0.05为差异有统计学意义,应用变异系数(coefficient of variation,CV)来评价两种成像方法的变异度,采用Bland-Altman法对两名医师间的测量结果进行对比.结果 2名阅片者采用两种序列所得T1值得相关系数分别为0.973、0.924,P值＜0.001.两种序列在双肾皮质、髓质所得T1值比较,差异无统计学意义(P＞0.05).同侧肾皮、髓质之间所得T1值存在差异(t=10.27、13.45、12.44、17.24;P＜0.05).脾脏、胰腺、双肾皮髓质、腹直肌及竖脊肌所得T1值之间差异有统计学意义(P＜0.05).Look-locker序列在腹部组织所得T1值的变异系数低于B1-corrected VFA序列.Bland-Altman散点图显示Look-locker序列测定的f值分布相对更集中.结论 对腹部各组织采用Look-locker序列和B1-correctedVFA序列所得T1值是不同的,采用Look-locker序列测量的T1值一致性评估变异度小,稳定性高,临床实用价值更高.

Objective To explore whether CT perfusion imaging (CTPI)parameters can early predict the curative effect of anlotinib hydrochloride and their predictive accuracy for the treatment in lung cancer patients.Methods 2 6 patients with advanced nonGsmall cell lung cancer (NSCLC)were treated with anlotinib hydrochloride and underwent CTPI scanning before chemotherapy,after the first and second treatment cycle respectively.The average values of perfusion value (PV),peak enhancement image (PEI),time to peak (TTP),blood volume (BV)and the change rate of these parameters after one treatment cycle every time were measured and recorded. According to the response evaluation criteria in solid tumors 1.1 (RECIST1.1),the maximum diameter of the target tumor was measured and the tumor regression rate after two treatment cycles was calculated.Then a correlation analysis was conducted between the change rate of perfusion parameters (PV%,PEI%,TTP%,BV%)after one treatment cycle and the tumor regression rate (D%)after two treatment cycles. The ROC curve was performed to evaluate the accuracy of those parameters.Results PV after one treatment cycle was significantly lower than that before treatment,and PV% showed a statistical difference (P＝0.00).The PV% after one treatment cycle was positively correlated with D% after two treatment cycles (r＝0.56).In addition,the AUC of PV% and BV% were 0.99 and 0.88 respectively, and specificity were both 100%,with sensitivity respectively 75.7% and 82.6%.Conclusion CTPI can early reflect the curative effect of anlotinib hydrochloride for advanced NSCLC and provide more options for clinical evaluation.

目的 探讨DWI及ADC值在宫颈癌同步放化疗后随访中的应用价值.方法 回顾性分析宫颈癌放化疗后局部复发(20例)和非复发患者(30例)MRI资料.2名阅片者共同观察治疗前、治疗结束后6个月、12个月DWI表现,测量并比较各时间点ADC值.采用组内相关系数(ICC)值验证阅片者一致性.采用ROC曲线判断ADC值预测宫颈癌复发效能和诊断阈值.结果 复发组与非复发组治疗前病灶ADC值差异无统计学意义(t=0.913,P=0.367);复发组复发灶ADC值与原发灶ADC值差异无意义(t=0.423,P=0.675);治疗结束后6个月、1 2个月复发组ADC值均低于非复发组(t=2.865,4.001;P =0.006,0.000);分别以治疗后6个月、1 2个月ADC=1.105×10-3 mm2/s、1.215×10-3mm2/s为阈值预测肿瘤复发,其敏感度、特异度和AUC分别为90.0％,73.3％,0.853;95.0％,96.7％,0.961.结论 DWI可用于宫颈癌同步放化疗后的定期随访,测量宫颈癌病灶放化疗后ADC值有助于预测局部复发.

目的 评估3.0T MRI DWI的ADC值及其比值术前诊断肌层浸润性膀胱癌的应用价值.方法 收集经术后病理证实的84例膀胱癌患者的资料,所有患者术前均行包括DWI序列的3.0T MRI检查.以膀胱壁正常肌层作为参照,测量病灶相邻膀胱壁肌层ADC值及正常肌层的ADC值,计算二者的比值,绘制ROC曲线分析膀胱癌病灶相邻肌层的ADC值及其比值与诊断肌层浸润性膀胱癌的关系.结果 测量肌层浸润性膀胱癌病灶相邻肌层的ADC值为(1.36±0.15)×10-3 mm2/s,ADC比值约为0.69±0.11.绘制ROC曲线分析,当ADC值的阈值为1.52×10-3 mm2/s时,诊断肌层浸润性膀胱癌的敏感性、特异性均高,分别为92.9％、85.2％;当ADC比值为0.74时,诊断肌层浸润性膀胱癌的敏感性特异性较高,分别为93.5％、89.8％.结论 膀胱癌病灶相邻肌层的ADC值及其比值诊断肌层浸润性膀胱癌有较高的敏感性和特异性,以ADC值1.52×10-3 mm2/s及ADC比值0.74为阈值诊断肌层浸润性膀胱癌具有较大的应用价值,此阈值可作为术前诊断肌层浸润性膀胱癌的指标,有一定的临床指导意义.

Abstracts Background Depth of invasion (DOI) could be calculated by MRI preoperatively, whether MRI-determined DOI could predict the prognosis and whether it could be used as an indicator for neck dissection for cT1N0 tongue squamous cell carcinoma (SCC) remain unknown, the main goal of the current study aimed to answer the questions. Methods Patients with surgically treated cT1N0 tongue SCC were retrospectively enrolled, MRI-determined DOI was measured based on T1-weigthed layers by a 1.5T scan. A multivariate logistic regression analysis model was used to determine the independent predictors for occult neck lymph node metastasis. The main study endpoints were locoregional control survival (LRC) and disease specific survival (DSS), the Cox model was used to determine the independent prognostic factors for the LRC and DSS. Results Occult neck lymph node metastasis was noted in 26 (17.2%) patients, ROC curve indicated the optimal cutoff value of MRI-determined DOI was 7.5mm for predicting neck lymph node metastasis with sensitivity of 86.9%. The factors of lymphovascular invasion, MRI-determined DOI, pathologic DOI, and pathologic tumor grade were significantly associated with the presence of neck lymph node metastasis in univariate analysis, further logistic regression analysis confirmed the independence of lymphovascular invasion, MRI-determined DOI, and pathologic DOI in predicting the neck lymph node metastasis. The 5-year LRC and DSS rates were 84% and 90%, respectively. Cox model analysis suggested the MRI-determined DOI was an independent prognostic factor for both the LRC and DSS. Conclusions Elective neck dissection is suggested if MRI-determined DOI is greater than 7.5mm in cT1N0 tongue SCC, and MRI-determined DOI ≥7.5mm indicates more risk for disease recurrence and cancer caused death.

Objective To investigate the correlation between CT manifestations of intramural vascular abnormalities and pathological subtypes,ground glass types in ground-glass opacity (GGO) lung adenocarcinoma.Methods CT data of 50 patients (55 lesions) with GGO lung adenocarcinoma confirmed by operative pathology were analyzed.The vascular morphology was observed.Correlation between vascular abnormalities (vascular thickening and hyperplasia) and pathological subtypes,ground glass types in GGO lung adenocarcinoma were analyzed.Results Among 55 GGO lung adenocarcinoma lesions,5 were pre-invasive lesions,no vascular thickening was observed,whereas vascular increasing was noticed in 1 lesion.Among 16 minimally invasive adenocarcinomas (MIA),vascular thickening and vascular increasing were observed in 11 and 16 lesions,respectively.All 34 invasive adenocarcinomas (IAC) were found with vascular thickening and increasing.The overall difference of vascular thickening and vascular increasing among pre-invasive lesions,MIA and IAC was statistically significant (x2 =27.67,20.08,both P＜0.05).There was positive correlation between pathological subtypes and vascular thickening and vascular increasing (r=0.61,0.66,P＜0.01).Significant differences of vascular thickening were found between pre-invasive lesions and MIA (x2=9.19,P=0.01),pre-invasive lesions and IAC (x2 =29.87,P＜0.01),as well as MIA and IAC (x2 =12.63,P＜0.01).There were significant differences of vascular increasing between pre-invasive lesions and MIA,pre-invasive lesions and IAC (x2 =15.45,20.79,both P＜0.01).Of all 55 GGO lung adenocarcinoma lesions,25 were pGGO,17 with vascular thickening and 21 vascular increasing;30 were mGGO,28 with vascular thickening and 30 vascular increasing.There were significant differences of vascular thickening and increasing in pGGO and mGGO (x2=6.12,6.69,both P＜0.05).Conclusion Vascular abnormalities in GGO lung adenocarcinoma suggest increasing of invasion.Vascular thickening and increasing can occur independently.

目的 探讨卵巢性索间质肿瘤(SCST)的 CT 和 MRI 表现,提高术前诊断正确率.方法 回顾性分析 46 例卵巢 SCST的CT和MRI表现.结果 1 1 例为颗粒细胞瘤(成年型8 例,幼年型3 例),卵泡膜细胞瘤1 1 例、纤维-卵泡膜细胞瘤1 0 例、纤维瘤1 4 例.颗粒细胞瘤常为单侧发生的囊性或囊实性肿块,囊性成分混杂,内常见出血,实性成分明显强化.纤维瘤与纤维-卵泡膜细胞瘤CT表现类似,平扫密度类似子宫,内可见有钙化.卵泡膜细胞瘤 CT 平扫密度稍低于子宫.于 MRI T2WI 上纤维瘤信号极低,其次为纤维-卵泡膜细胞瘤,呈低信号,内可见散在稍高信号区,卵泡膜细胞瘤呈稍低信号,内可见结节状及云絮状高信号.增强后,纤维瘤不强化,纤维-卵泡膜细胞瘤轻度延迟强化,而卵泡膜细胞瘤于 T2WI 上肿瘤内呈结节状及云絮状高信号区会明显强化,且T2WI信号越高,强化越明显.结论 卵巢SCST的T2WI信号及强化方式具有一定的特征性,其病理亚型不同,表现不同.颗粒细胞瘤常为囊性或囊实性肿块,实性成分明显强化.纤维瘤、纤维-卵泡膜细胞瘤、卵泡膜细胞瘤的T2WI信号及强化程度依次升高.

胰腺实性假乳头状瘤(solid pseudopapillary tumor,SPT)是一种少见的良性或低度恶性肿瘤,在所有胰腺外分泌肿瘤中占比不超过1％～2％,占全部胰腺囊性肿瘤的5％[1]. 这一类肿瘤有低度恶性潜能,手术可完全切除且预后良好[2] ,若肿瘤较大或囊变坏死明显容易误诊为胰腺恶性肿瘤. 本研究回顾性分析SPT的多层螺旋CT及3.0 T MRI影像学表现,探讨不同影像学检查的优势和局限性,指导临床合理应用影像学检查方法.