Magnetic resonance imaging-based lymph node radiomics for predicting the metastasis of evaluable lymph nodes in rectal cancer

BACKGROUND Lymph node(LN)staging in rectal cancer(RC)affects treatment decisions and patient prognosis.For radiologists,the traditional preoperative assessment of LN metastasis(LNM)using magnetic resonance imaging(MRI)poses a challenge.AIM To explore the value of a nomogram model that combines Conventional MRI and radiomics features from the LNs of RC in assessing the preoperative metastasis of evaluable LNs.METHODS In this retrospective study,270 LNs(158 nonmetastatic,112 metastatic)were randomly split into training(n=189)and validation sets(n=81).LNs were classified based on pathology-MRI matching.Conventional MRI features[size,shape,margin,T2-weighted imaging(T2WI)appearance,and CE-T1-weighted imaging(T1WI)enhancement]were evaluated.Three radiomics models used 3D features from T1WI and T2WI images.Additionally,a nomogram model combining conventional MRI and radiomics features was developed.The model used univariate analysis and multivariable logistic regression.Evaluation employed the receiver operating characteristic curve,with DeLong test for comparing diagnostic performance.Nomogram performance was assessed using calibration and decision curve analysis.RESULTS The nomogram model outperformed conventional MRI and single radiomics models in evaluating LNM.In the training set,the nomogram model achieved an area under the curve(AUC)of 0.92,which was significantly higher than the AUCs of 0.82(P<0.001)and 0.89(P<0.001)of the conventional MRI and radiomics models,respectively.In the validation set,the nomogram model achieved an AUC of 0.91,significantly surpassing 0.80(P<0.001)and 0.86(P<0.001),respectively.CONCLUSION The nomogram model showed the best performance in predicting metastasis of evaluable LNs.

Diagnostic Power of Diffusion-weighted Magnetic Resonance Imaging for the Presence of Lymph Node Metastasis:A Meta-analysis

Present work was designed to quantitatively evaluate the performance of diffusion-weighted magnetic resonance imaging（DWI） in the diagnosis of the presence of metastasis in lymph nodes（LNs）. Eligible studies were identified from systematical Pub Med and EMBASE searches. Data were extracted. Meta-analyses were performed to generate pooled sensitivity and specificity on the basis of per-node, per-lesion and per-patient, respectively. Fourteen publications（2458 LNs, 404 lesions and 334 patients） were eligible. Per-node basis demonstrated the pooled sensitivity and specificity was 0.82（P〈0.0001） and 0.90（P〈0.0001）, respectively. Per-lesion basis illustrated the pooled sensitivity and specificity was 0.73（P=0.0036） and 0.85（P〈0.0001）, respectively. Per-patient basis indicated the pooled sensitivity and specificity was 0.67（P=0.0909） and 0.86（P〈0.0001）, respectively. In conclusion, DWI has rather a negative predictive value for the diagnosis of LN metastasis presence. The difference of the mean apparent diffusion coefficients between benign and malignant LNs is not yet stable. Therefore, the DWI technique has to be further improved.

Nomogram based on multimodal magnetic resonance combined with B7-H3mRNA for preoperative lymph node prediction in esophagus cancer

Accurate preoperative prediction of lymph node metastasis(LNM)in esophageal cancer(EC)patients is of crucial clinical significance for treatment planning and prognosis.AIM To develop a clinical radiomics nomogram that can predict the preoperative lymph node(LN)status in EC patients.METHODS A total of 32 EC patients confirmed by clinical pathology(who underwent surgical treatment)were included.Real-time fluorescent quantitative reverse transcription-polymerase chain reaction was used to detect the expression of B7-H3 mRNA in EC tissue obtained during preoperative gastroscopy,and its correlation with LNM was analyzed.Radiomics features were extracted from multi-modal magnetic resonance imaging of EC using Pyradiomics in Python.Feature extraction,data dimensionality reduction,and feature selection were performed using XGBoost model and leave-one-out cross-validation.Multivariable logistic regression analysis was used to establish the prediction model,which included radiomics features,LN status from computed tomography(CT)reports,and B7-H3 mRNA expression,represented by a radiomics nomogram.Receiver operating characteristic area under the curve(AUC)and decision curve analysis(DCA)were used to evaluate the predictive performance and clinical application value of the model.RESULTS The relative expression of B7-H3 mRNA in EC patients with LNM was higher than in those without metastasis,and the difference was statistically significant(P<0.05).The AUC value in the receiver operating characteristic(ROC)curve was 0.718(95%CI:0.528-0.907),with a sensitivity of 0.733 and specificity of 0.706,indicating good diagnostic performance.The individualized clinical prediction nomogram included radiomics features,LN status from CT reports,and B7-H3 mRNA expression.The ROC curve demonstrated good diagnostic value,with an AUC value of 0.765(95%CI:0.598-0.931),sensitivity of 0.800,and specificity of 0.706.DCA indicated the practical value of the radiomics nomogram in clinical practice.CONCLUSION This study developed a radiomics nomogram that includes radiomics features,LN status from CT reports,and B7-H3 mRNA expression,enabling convenient preoperative individualized prediction of LNM in EC patients.

Utility of diffusion-weighted imaging in the diagnosis of inguinal lymph node metastasis with malignant melanoma

Malignant melanoma is a malignancy of pigmentproducing cells(melanocytes) located predominantly in the skin. Nodal metastases are an adverse prognostic factor compromising long term patient survival. Therefore, accurate detection of regional nodal metastases is required for optimization of treatment. Computed tomography(CT) and magnetic resonance imaging(MRI) remain the primary imaging modalities for regional staging of malignant melanoma. However, both modalities rely on size-related and morphological criteria to differentiate between benign and malignant lymph nodes, decreasing the sensitivity for detection of small metastases. Surgery is the primary mode of therapy for localized cutaneous melanoma. Patients should be followed up for metastases after surgical removal. We report here a case of inguinal lymph node enlargement with a genital vesicular lesion with a history of surgery for malignant melanoma on her thigh two years ago. CT and diffusion weighted-MRI(DW-MRI) were applied for the lymph node identification. DW-MRI revealed malignant lymph nodes due to malignant melanoma metastases correlation with pathological findings.

SPIO-enhanced magnetic resonance imaging for differentiating metastatic from hyperplastic lymph nodes: A study in rabbits

Objective: To investigate the potential of superparamagnetic iron oxide particles (SPIO) in MR imaging for the differentiation between hyperplastic and metastatic lymph node. Methods: Animal models of malignant lymph node metastasis were established in 6 New-Zealand rabbits by a unilateral intra-muscular injection of VX2 carcinoma cells, and models of hyperplastic lymph nodes were induced in another 6 rabbits by a unilateral intra-muscular injection of egg yolk emulsion. MR images of the lymph nodes were obtained before and 12 h after interstitial injection of SPIO. Image results were analyzed and compared with pathological findings. Results: On unenhanced images, the signal intensity of hyperplastic and metastatic lymph nodes did not differ significantly. After administration of SPIO, the signal intensity of both hyperplastic and metastatic lymph nodes remained unchanged on T1-weighted SE images. On T2-weighted SE images, the signal intensity of hyperplastic lymph nodes decreased heterogeneously, while that of all metastatic ones remained unchanged. On T2-weighted GRE images, the signal intensity of hyperplastic lymph nodes decreased significantly and homogeneously, while that of 4 metastatic ones remained unchanged and that of the rest 2 decreased heterogeneously. Conclusion: SPIO-enhanced MR imaging may enable the differentiation between the hyperplastic and metastatic lymph nodes.

Malignant proliferative ependymoma of the neck with lymph node metastasis:A case report

BACKGROUND Malignant proliferating trichilemmal tumor(MPTT)is an infrequent malignant neoplasm originating from cutaneous appendages,with only a handful of documented cases.This report delineates a unique instance of MPTT situated in the neck,accompanied by lymph node metastasis.A comprehensive exposition of its clinical trajectory and imaging manifestation is presented,aiming to enhance comprehension and management of this atypical ailment.CASE SUMMARY Patient concerns:A 79-year-old male presented with a longstanding right neck mass persisting for over six decades,exhibiting recent enlargement over the past year.Diagnoses:Enhanced magnetic resonance imaging of the neck unveiled an elliptical mass on the right neck side,characterized by an ill-defined border and a heterogeneous signal pattern.The mass exhibited subdued signal intensity on T1-weighted imaging(T1WI)and a heterogeneous high signal on T2-weighted imaging(T2WI),interspersed with a lengthy T1 and T2 cystic signal motif.Close anatomical association with the submandibular gland joint was noted,and intravenous gadolinium diethylene triamine pentaacetic acid administration facilitated conspicuous enhancement.Substantial enhancement of the solid segment prompted an initial preoperative diagnosis of malignant nerve sheath tumor.However,post-surgery histopathological and immunohistochemical analysis conclusively confirmed the diagnosis as malignant hyperplastic external hair root sheath tumor.Intervention:Complete excision of the tumor was successfully executed.Outcomes:The patient experienced a favorable postoperative recovery.CONCLUSION Malignant proliferative trichilemmal tumor external hair root sheath tumor is a cystic-solid lesion,appearing as low signal on T1WI images or high signal on T2WI with enhancement of the solid component.Suspicions of malignancy are heightened when the tumor border is indistinct,tissue planes are breached,or when linear or patchy high signals are observed in the subcutaneous tissue on T1 liver acquisition with volume acceleration enhanced images along with intermediate signal on T2WI and restricted diffusion on diffusion-weighted imaging images.Strong consideration for malignancy should arise if there are signs of compromised adjacent tissue relationships or direct invasion evident on imaging.We have incorporated the above-mentioned content into the entire manuscript.

Comparison of DWI and PET/CT in evaluation of lymph node metastasis in uterine cancer

AIM: To investigate diffusion-weighted imaging (DWI) and positron emission tomography and computed tomography (PET/CT) with Ⅳ contrast for the preoperative evaluation of pelvic lymph node (LN) metastasis in uterine cancer. METHODS: Twenty-five patients with endometrial or cervical cancer who underwent both DWI and PET/CT before pelvic lymphadenectomy were included in this study. For area specific analysis, LNs were divided into eight regions: both common iliac, external iliac, internal iliac areas, and obturator areas. The classification for malignancy on DWI was a focally abnormal signal intensity in a location that corresponded to the LN chains on the T1WI and T2WI. The criterion for malignancy on PET/CT images was increased tracer uptake by the LN.RESULTS: A total of 36 pathologically positive LN areas were found in 9 patients. With DWI, the sensitivity, specificity, positive predictive value, negative predictive value and accuracy for detecting metastatic LNs on an LN area-by-area analysis were 83.3%, 51.2%, 27.3%, 93.3% and 57.0%, respectively, while the corresponding values for PET/CT were 38.9%, 96.3%, 70.0%, 87.8% and 86.0%. Differences in sensitivity, specificity and accuracy were significant (P < 0.0005). CONCLUSION: DWI showed higher sensitivity and lower specificity than PET/CT. Neither DWI nor PET/CT were sufficiently accurate to replace lymphadenectomy.

Computed tomography and magnetic resonance imaging evaluation of pelvic lymph node metastasis in bladder cancer

Background:Accurate evaluation of lymph node metastasis in bladder cancer(BCa)is important for disease staging,treatment selection,and prognosis prediction.In this study,we aimed to evaluate the diagnostic accuracy of com-puted tomography(CT)and magnetic resonance imaging(MRI)for metastatic lymph nodes in BCa and establish criteria of imaging diagnosis.Methods:We retrospectively assessed the imaging characteristics of 191 BCa patients who underwent radical cys-tectomy.The data regarding size,shape,density,and diffusion of the lymph nodes on CT and/or MRI were obtained and analyzed using Kruskal-Wallis test and χ^(2) test.The optimal cutoff value for the size of metastatic node was deter-mined using the receiver operating characteristic(ROC)curve analysis.Results:A total of 184 out of 3317 resected lymph nodes were diagnosed as metastatic lymph nodes.Among 82 imaging-detectable lymph nodes,51 were confirmed to be positive for metastasis.The detection rate of metastatic nodes increased along with more advanced tumor stage(P<0.001).Once the ratio of short-to long-axis diameter≤0.4 or fatty hilum was observed in lymph nodes on imaging,it indicated non-metastases.Besides,lymph nodes with spiculate or obscure margin or necrosis indicated metastases.Furthermore,the short diameter of 6.8 mm was the optimal threshold to diagnose metastatic lymph node,with the area under ROC curve of 0.815.Conclusions:The probability of metastatic nodes significantly increased with more advanced T stages.Once lymph nodes are detected on imaging,the characteristic signs should be paid attention to.The short diameter>6.8 mm may indicate metastatic lymph nodes in BCa.

Determination of Metastatic Axillary Lymph Node in Breast Cancer: Differentiation with Dynamic MRI Examination by Signal Intensity-Time Curves

Purpose: We aimed to evaluate the role of dynamic magnetic resonance imaging (MRI) in the detection of axillary lymph node metastasis based on the signal intensity-time curves. Materials and Methods: The data of 120 patients (benign patients, n = 91;malignant patients, n = 29) who underwent dynamic breast MRI were reviewed. The lymph nodes with the strongest criteria for malignancy (morphological-dynamic properties) were included in the analysis. Signal intensity-time curves were plotted by the software. Results: Of 29 patients with breast cancer, axillary lymph nodes were involved in 21 and not involved in the remaining 8. There was no significant difference between benign and malignant cases in terms of the distributions of Type Ia, Type Ib and Type IV curves (p = 0.12), whereas a significant difference was found between benign and malignant cases in terms of the distributions of Type II and III curves (p Conclusion: On dynamic MRI studies, benign and metastatic lymph nodes display different signal intensity-time curves.

基于深度学习的宫颈癌淋巴结转移预测

目的:基于深度学习,利用T_(2)加权成像(T_(2)WI)序列的高分辨特性获得宫颈癌淋巴结的结构信息,并预测淋巴结是否转移;利用弥散加权成像(DWI)序列的功能特性,获取淋巴结区域,并预测淋巴结是否转移;综合多模态MRI数据,预测淋巴结是否转移。方法:收集2021年6月至2022年5月年新疆维吾尔自治区人民医院收治的52例宫颈癌患者的多参数MRI影像数据以及病理检查数据作为训练集,另收集2022年6月至2023年5月新疆维吾尔自治区人民医院收治的150例宫颈癌患者多参数MRI影像数据以及病理检查数据作为验证集。训练集52例宫颈癌患者均接受MRI扫描,扫描序列包括T_(2)WI和DWI序列。对训练集52例宫颈癌患者的多参数MRI影像学图像进行非均匀性校正和标准化的预处理后,通过渐进演化空洞卷积对T_(2)WI图像进行分割,在扩大感受野的同时,有效降低空洞对图像丢失的影响;通过基于注意力网络机制的深度学习模型引导网络在预测时更关注淋巴结区域,并为预测结果提供一定程度的解释性;通过多模态协同学习模型实现T_(2)WI和DWI序列在淋巴结性质预测任务之间的经验共享。采用验证集患者的图像资料对基于多模态协同学习模型的淋巴结转移预测模型进行验证。结果:验证集150例患者中良性淋巴结585枚,恶性淋巴结65枚,其良恶性淋巴结在大小(长径、短径)和边界上存在差异,差异有统计学意义(x^(2)=8.437、143.100、104.608,P<0.05)。验证集150例患者中48例患者出现淋巴结转移,基于多模态协同学习模型的淋巴结性质预测模型准确预测出46例患者出现淋巴结转移,准确预测出99例患者未发生淋巴结转移,预测准确率为96.67%。结论:渐进演化空洞卷积结合U-Net框架完成了对T_(2)WI宫颈癌影像的多目标自动分割任务,基于注意力网络机制的深度学习模型完成了动态关注淋巴结区域的任务,多模态协同学习模型有效地避免了特征层融合之后特征空间分布的改变。

多参数MRI影像组学在术前预测胰腺导管腺癌淋巴结转移中的价值

目的联合常规MRI及表观扩散系数(apparent diffusion coefficient,ADC)图的影像组学特征构建多参数MRI影像组学模型术前预测胰腺导管腺癌(pancreatic ductal adenocarcinoma,PDAC)淋巴结转移(lymph node metastasis,LNM),并与建立的常规MRI影像组学模型和临床模型比较预测效能,探索基于ADC图影像组学的附加价值。材料与方法218例PDAC按照7∶3的比例随机分为训练集和验证集。纳入临床及常规影像特征构建临床影像学模型。提取常规MRI图像(T1WI、T2WI、动脉期图像及门静脉期图像)及ADC图的影像组学特征。在训练集中采用最小绝对收缩和选择算子筛选出与LNM最相关的特征用于模型构建。构建基于常规MRI影像组学模型(影像组学模型1)和联合常规MRI和ADC图的影像组学模型(影像组学模型2)。使用受试者工作特征曲线下面积(area under the curve,AUC)评估模型预测效能。采用DeLong检验比较模型间的AUC值的差异是否有统计学意义。校准曲线评估模型的准确性。决策曲线分析评估模型的临床价值。结果临床影像学模型、影像组学模型1、影像组学模型2术前预测LNM的AUC值在训练集和验证集中分别是0.741和0.674、0.818和0.702、0.854和0.839。影像组学模型2术前预测LNM的AUC值高于临床影像学模型(训练集P=0.009,验证集P=0.023)及影像组学模型1(训练集P=0.044,验证集P=0.041),差异均具有统计学意义。影像组学模型1的预测效能与临床影像学模型相比,差异不具有统计学意义(训练集P=0.095,验证集P=0.759)。三个模型的校准曲线均显示预测值与实际值具有较好的一致性。决策曲线显示影像组学模型2比影像组学模型1和临床影像学模型具有更高的净效益。结论联合常规MRI及ADC图构建的多参数MRI影像组学模型具有术前预测PDAC患者LNM的潜能,且其效能优于常规MRI影像组学模型及临床影像学模型。

磁共振成像对直肠癌盆腔侧方淋巴结转移的诊断价值分析

目的:分析磁共振成像(MRI)对直肠癌盆腔侧方淋巴结转移(PLLNM)的诊断价值。方法:选取2020年3月—2022年2月新乡医学院第三附属医院收治的80例直肠癌患者作为研究对象,所有患者术前均接受MRI检查及病理活检确诊,均行直肠癌切除及盆腔淋巴结清扫术。以病理结果为金标准,计算MRI对直肠癌PLLNM的准确度、敏感度、特异度及一致性,比较不同性质淋巴结的MRI图像特征。采用Pearson检验分析MRI图像特征与直肠癌PLLNM的相关性,采用多因素logistic回归分析模型分析影响PLLNM的独立危险因素。结果:80例直肠癌患者经病理诊断共检出PLLNM 29例,未转移51例;MRI诊断共检出PLLNM 35例,未转移45例,两者的诊断一致性良好(Kappa=0.845)。PLLNM患者的边缘模糊及型号不均匀占比显著高于未转移者,淋巴结短径显著长于未转移者,差异有统计学意义(χ^(2)=12.342、8.136;t=13.857,P<0.01)。Pearson相关性分析结果显示,直肠癌PLLNM检出率与淋巴结短径、边缘模糊及信号不均匀具有正相关性(r>0,P<0.001)。多因素logistic回归分析结果显示,淋巴结信号是影响直肠癌PLLNM的独立危险因素。结论:MRI对直肠癌PLLNM的诊断效能较高,不同性质淋巴结的MRI图像特征存在明显差异,其中淋巴结短径、边缘模糊及信号不均匀与PLL-NM密切相关,淋巴结信号是影响直肠癌PLLNM的独立危险因素。用MRI测量淋巴结短径是诊断直肠癌PLLNM的可靠参数,对PLLNM的早期预测具有积极作用。

DCE-MRI联合IVIM-DWI预测早期宫颈癌盆腔淋巴结转移的价值

目的探讨动态对比增强MRI(dynamic contrast-enhanced MRI,DCE-MRI)联合体素内不相干运动扩散加权成像(intravoxel incoherent motion diffusion-weighted imaging,IVIM-DWI)预测早期宫颈癌盆腔淋巴结转移(pelvic lymph node metastasis,PLNM)的价值。材料与方法回顾性分析124例经病理证实为国际妇产科联盟(International Federation of Gynecology and Obstetrics,FIGO)ⅠB~ⅡA期宫颈癌患者的临床及影像资料,比较PLNM组与无PLNM组原发肿瘤DCE-MRI及IVIM-DWI定量参数的差异,采用多因素logistic回归分析确定独立危险因素,绘制受试者工作特征(receiver operating characteristic,ROC)曲线评估各参数诊断效能。结果PLNM组容积转运常数(volume transfer constant,K^(trans);t=6.203,P<0.001)、灌注分数(perfusion fraction,f;t=3.944,P<0.001)、表观扩散系数(apparent diffusion coefficient,ADC;Z=4.393,P<0.001)、细胞外血管外间隙容积比(extravascular extracellular volume fraction,V_(e);Z=2.312,P=0.021)低于无PLNM组,差异均有统计学意义,多因素logistic回归分析示K^(trans)(P<0.001)、f(P=0.003)、ADC(P=0.031)是宫颈癌PLNM的独立危险因素,ROC曲线示K^(trans)、f、ADC预测PLNM的曲线下面积(area under the curve,AUC)分别为0.808、0.707、0.745;与单一参数相比,三者联合预测PLNM的诊断效能最高,AUC为0.893,敏感度和特异度分别为82.4%、86.8%。结论早期宫颈癌原发肿瘤DCE-MRI的K^(trans)、V_(e)及IVIM-DWI的f、ADC有助于鉴别PLNM。独立危险因素K^(trans)、f、ADC具有较高的预测价值,三者联合应用可进一步提高诊断效能。

基于ZOOM-mDixon的T2^(*)/R2^(*)成像术前预测胰腺导管腺癌淋巴结转移的价值

目的 探讨ZOOM-mDixon序列衍生的定量T2^(*)/R2^(*)值在术前评价胰腺导管腺癌淋巴结转移的可行性。材料与方法 回顾性分析经病理证实的59例胰腺导管腺癌患者临床及影像资料,其中淋巴结转移(lymphatic metastasis, LNM)31例,非淋巴结转移(non-lymph node metastases, nLNM)28例。术前均行包括ZOOM-mDixon序列的MRI扫描,分析两组的临床基本资料(年龄、术前CA19-9水平等)、常规影像学特征(部位、形态等)和T2^(*)/R2^(*)值。使用组内相关系数(intra-class correlation coefficient, ICC)评价其可重复性,采用U检验、t检验或χ^(2)检验比较两组间各参数的差异,绘制受试者工作特征(receiving operator characteristic, ROC)曲线,利用曲线下面积(area under the curve, AUC)评价相关指标的诊断性能。结果 T2^(*)/R2^(*)值的组间和组内ICC值均在0.83~0.97之间。两组间的年龄、肿块形态、肿块短径、肿块部位、术前糖类抗原(carbohydrate antigen,CA)19-9、CA125、癌胚抗原(carcinoma embryonic antigen, CEA)水平等差异无统计学意义,而性别、病灶长径和病灶边界差异有统计学意义(P值分别为0.023、0.048、0.040)。两组间的T2^(*)值和R2^(*)值差异有统计学意义(P值均<0.05)。与nLNM组相比,LNM组的R2^(*)值较小[17.63(15.10, 22.50)/s vs. 24.00(20.00, 28.30)/s];T2^(*)值更高[(63.77±13.95)ms vs.(49.71±12.67)ms]。T2^(*)/R2^(*)值预测胰腺癌淋巴结转移的AUC分别为0.775和0.766。结论 ZOOM-mDixon序列衍生的T2^(*)/R2^(*)成像量化值可术前预测胰腺导管腺癌的淋巴结转移,为临床治疗提供参考。

高清与传统扩散加权成像在评价宫颈癌盆腔淋巴结转移中的对比研究

目的:基于复合灵敏度编码的高清扩散加权成像(MUSE DWI)与传统DWI在评价宫颈癌盆腔淋巴结转移中的对比研究。方法:收集行手术治疗的54例宫颈癌患者的病例资料,所有患者术前行磁共振检查,包含传统DWI序列和MUSE DWI序列。分析比较两组DWI序列在宫颈癌盆腔淋巴结中的整体图像质量、矫正几何失真程度和病变显示程度及信噪比(SNR)、对比噪声比(CNR)和平均表观扩散系数(ADC)。采用独立样本t检验分析两组ADC值在盆腔转移性淋巴结和非转移性淋巴结之间的差异,并用受试者操作特征(ROC)曲线评价两组ADC值鉴别宫颈癌盆腔淋巴结转移的诊断效能,采用Delong检验比较两种序列诊断效能的差异。结果:MUSE DWI的整体图像质量、矫正几何失真程度、病变显示程度、SNR和CNR均显著高于传统DWI(P均<0.001)。MUSE DWI和传统DWI的ADC值差异有统计学意义(P<0.001)。在MUSE DWI和传统DWI中,转移组的ADC值均显著低于非转移组(P<0.001)。MUSE DWI和传统DWI的鉴别诊断宫颈癌盆腔淋巴结转移能力的ROC曲线下面积分别为0.718和0.646,两种序列间差异没有统计学意义(P=0.094)。结论:MUSE DWI序列的图像质量、SNR和CNR均优于传统DWI,ADC值差异有统计学意义。MUSE DWI和传统DWI都可以鉴别宫颈癌盆腔淋巴结转移,两者的诊断效能无显著差异。

基于全病变MRI动态增强扫描直方图分析对小乳腺癌腋窝淋巴结转移的预测价值

目的:基于小乳腺癌全病变MRI动态增强扫描(DCE-MRI)直方图分析及临床特征预测腋窝淋巴结(ALN)转移。方法:回顾性分析93例小乳腺癌患者临床病理资料,其中30例发生ALN转移(转移组),63例ALN无转移(无转移组)。患者术前或治疗前均行MRI检查。采用FireVoxel软件勾画ROI并行直方图分析,采用t检验及Mann-WhitneyU检验分析比较2组的直方图参数。采用Pearson及Spearman相关检验分析ALN转移与直方图参数之间的相关性,采用二元logistic回归分析对筛选出ALN转移组和无转移组间差异有统计学意义的参数构建联合模型,并利用ROC曲线分析直方图参数对ALN状态的诊断效能。结果:年龄和绝经状态均与ALN转移存在相关性(均P<0.05)。直方图参数中最小值、第5百分位数、变异系数、体积均与ALN转移显著相关(均P<0.05)。在直方图参数中,体积预测ALN状态的AUC最大,为0.729,最佳阈值为1.765。最小值、第5百分位数、变异系数、体积和年龄构建的联合模型的AUC最高,为0.780。结论:基于全病变DCE-MRI直方图分析可用于预测小乳腺癌的ALN转移,且最小值、第5百分位数、变异系数和体积是预测ALN状态有价值的影像学指标。

多模态磁共振成像评估乳腺癌腋窝淋巴结转移

目的:分析多模态磁共振成像(MRI)在乳腺癌腋窝淋巴结转移(ALNM)评估效果以及可靠指标。方法:选取2020年1月至2021年11月在邯郸市第一医院确诊并接受手术治疗的152例女性乳腺癌患者,根据术后腋窝淋巴结病理结果将其分为ALNM组(45例)和非ALNM组(107例)。利用磁共振动态增强成像(DCE-MRI)、T2加权成像(T2WI)和弥散加权成像(DWI)技术对乳腺癌ALNM做出判定。结果:多模态MRI诊断灵敏度为82.22%,特异度为96.26%,阳性预测值为90.24%,阴性预测值为92.79%,诊断符合率为92.11%。logistic回归分析显示,肿瘤最大径、ADC值与淋巴结转移密切相关。受试者工作特征(ROC)曲线分析,肿瘤最大径ROC曲线下面积(AUC)为0.797(95%CI:0.694~0.842,P<0.01),在最佳截断值为1.96 cm下诊断的灵敏度为77.4%,特异度为60.7%;ADC值AUC为0.844(95%CI:0.808~0.915,P<0.01),在最佳截断值1.122×10^(-3)mm^(2)/s下诊断灵敏度为82.1%,特异度为71.2%。肿瘤最大径和AUC值联合诊断AUC为0.952(95%CI:0.904~0.991,P<0.01),最佳截断值下灵敏度为88.6%,特异度为81.4%。联合指标的AUC要高于肿瘤最大径(Z=3.982,P<0.05)和ADC值(Z=3.014,P<0.05)。结论:多模态MRI对乳腺癌ALNM诊断效果良好,其中肿瘤最大径和AUC值是重要的参考指标,两者联合应用能提高诊断效率。

基于术前MRI影像组学及临床特征的卵巢癌淋巴结转移预测模型构建及验证

目的探讨卵巢癌淋巴结转移的危险因素,并构建基于术前MRI影像组学及临床特征的卵巢癌淋巴结转移的列线图。方法选取2018年2月—2021年7月期间于安徽医科大学第一附属医院就诊的225例卵巢癌患者作为研究对象,根据淋巴结转移情况分为淋巴结转移组和无淋巴结转移组。应用Logistic回归分析筛选卵巢癌淋巴结转移的危险因素。利用LIFEx软件提取卵巢癌患者手术前的核磁共振(MRI)影像组学特征,将所选MRI影像组学与其对应非零系数乘积的线性组合确定其MRI影像组学评分。建立MRI影像组学、临床特征模型。通过整合优化的MRI影像组学及临床特征模型,采用R(R4.2.0)软件建立卵巢癌淋巴结转移的列线图,并对模型进行内部验证。结果225例卵巢癌中有95例患者出现淋巴结转移,淋巴结转移的发生率为42.22%(95/225)。Logsitc回归分析结果显示,临床分期、病灶位置、分化程度及糖尿病等是卵巢癌淋巴结转移的危险因素(P<0.05)。结合多因素结果及MRI影像组学参数提取构建了3组预测模型,其中包括临床模型1组,MRI影像组学模型1组,组合模型(临床-MRI影像组学模型)1组,其中临床-MRI影像组学模型的AUC(0.862)最高。构建的临床-MRI影像组学关于卵巢癌淋巴结转移的列线图模型的结果显示,校正曲线显示预测值和实际值具有良好的拟合度,模型的ROC曲线下面积为0.862(95%CI:0.790~0.934),决策曲线显示阈值概率为22%~80%时,列线图预测卵巢癌淋巴结转移的净获益值较高。结论基于术前MRI影像组学及临床特征的卵巢癌淋巴结转移的列线图模型具有较高的准确率和较好的临床应用价值,能够用于术前卵巢癌淋巴结转移的识别。

多模态MRI影像组学对非小细胞肺癌纵隔淋巴结转移的预测价值

目的建立基于常规MRI序列的影像组学模型,比较不同模型预测非小细胞肺癌(non-small cell lung cancer,NSCLC)纵隔淋巴结转移的效能。材料与方法回顾性分析2012年10月至2022年5月南通市第一人民医院90例NSCLC患者的术前MRI数据,根据手术病理结果分为淋巴结转移阳性组(52例)和阴性组(38例),采用完全随机法按照7∶3比例将患者分为训练集和测试集,盐城第一人民医院的31例患者数据作为外部验证(阳性9例,阴性22例),放射科医师半自动逐层勾画原发病灶,提取基于T1WI、T2WI、高b值弥散加权成像(diffusion weighted imaging,DWI)、表观扩散系数(apparent diffusion coefficient,ADC)图像的组学特征,由超参数搜索在单因素方差分析、L1正则化、树模型等特征筛选法中选择最佳方法用于降维,分别建立逻辑斯特回归(logistic regression,LR)、高斯朴素贝叶斯(Gaussian naive Bayes,Gaussian NB)、随机森林(random forest,RF)、支持向量机(support vector machine,SVM)、决策树(decision tree,DT)等11种模型,通过受试者工作特征(receiver operating characteristic,ROC)曲线来评估模型的性能。结果在不同序列中DT、LR、SVM模型的预测性能都表现良好,其中基于T2WI图像构建的SVM模型效能最佳,训练集、测试集及外部验证集曲线下面积(area under the curve,AUC)分别达0.98、0.98、0.72,准确度分别为96%、67%、61%、敏感度分别为88%、67%、55%、特异度分别为100%、67%、78%。结论MRI影像组学可帮助识别NSCLC患者纵隔淋巴结是否转移,以基于T2WI的SVM模型表现最优。

MRI在甲状腺肿瘤中的应用进展

甲状腺肿瘤是最常见的内分泌肿瘤,早期发现及精准诊断对于制定临床治疗方案和改善病人预后至关重要。随着甲状腺专用MR线圈及基于并行发射平台选择性激发成像技术(ZOOMit)等的开发,使得诸如扩散加权成像、动态增强MRI、体素内不相干运动成像、扩散峰度成像以及磁共振波谱成像等被逐渐应用于甲状腺肿瘤的良恶性鉴别、淋巴结转移评估、周围组织侵袭性预测及偶发瘤的检测中,为临床诊治甲状腺肿瘤提供了重要影像参考。就各种功能MRI技术在甲状腺肿瘤中的应用进展予以综述。