T2-weighted imaging-based radiomic-clinical machine learning model for predicting the differentiation of colorectal adenocarcinoma

BACKGROUND The study on predicting the differentiation grade of colorectal cancer(CRC)based on magnetic resonance imaging(MRI)has not been reported yet.Developing a non-invasive model to predict the differentiation grade of CRC is of great value.AIM To develop and validate machine learning-based models for predicting the differ-entiation grade of CRC based on T2-weighted images(T2WI).METHODS We retrospectively collected the preoperative imaging and clinical data of 315 patients with CRC who underwent surgery from March 2018 to July 2023.Patients were randomly assigned to a training cohort(n=220)or a validation cohort(n=95)at a 7:3 ratio.Lesions were delineated layer by layer on high-resolution T2WI.Least absolute shrinkage and selection operator regression was applied to screen for radiomic features.Radiomics and clinical models were constructed using the multilayer perceptron(MLP)algorithm.These radiomic features and clinically relevant variables(selected based on a significance level of P<0.05 in the training set)were used to construct radiomics-clinical models.The performance of the three models(clinical,radiomic,and radiomic-clinical model)were evaluated using the area under the curve(AUC),calibration curve and decision curve analysis(DCA).RESULTS After feature selection,eight radiomic features were retained from the initial 1781 features to construct the radiomic model.Eight different classifiers,including logistic regression,support vector machine,k-nearest neighbours,random forest,extreme trees,extreme gradient boosting,light gradient boosting machine,and MLP,were used to construct the model,with MLP demonstrating the best diagnostic performance.The AUC of the radiomic-clinical model was 0.862(95%CI:0.796-0.927)in the training cohort and 0.761(95%CI:0.635-0.887)in the validation cohort.The AUC for the radiomic model was 0.796(95%CI:0.723-0.869)in the training cohort and 0.735(95%CI:0.604-0.866)in the validation cohort.The clinical model achieved an AUC of 0.751(95%CI:0.661-0.842)in the training cohort and 0.676(95%CI:0.525-0.827)in the validation cohort.All three models demonstrated good accuracy.In the training cohort,the AUC of the radiomic-clinical model was significantly greater than that of the clinical model(P=0.005)and the radiomic model(P=0.016).DCA confirmed the clinical practicality of incorporating radiomic features into the diagnostic process.CONCLUSION In this study,we successfully developed and validated a T2WI-based machine learning model as an auxiliary tool for the preoperative differentiation between well/moderately and poorly differentiated CRC.This novel approach may assist clinicians in personalizing treatment strategies for patients and improving treatment efficacy.

Asymmetrically hypointense veins on T2~*w imaging and susceptibility-weighted imaging in ischemic stroke

AIM:To review the literature on the assessment of venous vessels to estimate the penumbra on T2*w imaging and susceptibility-weighted imaging (SWI). METHODS:Literature that reported on the assessment of penumbra by T2*w imaging or SWI and used a validation method was included. PubMed and relevant stroke and magnetic resonance imaging (MRI) related conference abstracts were searched. Abstracts that had overlapping content with full text articles were excluded. The retrieved literature was scanned for further relevant references. Only clinical literature published in English was considered, patients with Moya-Moya syndrome were disregarded. Data is given as cumulative absolute and relative values, ranges are given where appropriate. RESULTS:Forty-three publications including 1145 patients could be identified. T2*w imaging was used in 16 publications (627 patients), SWI in 26 publications (453 patients). Only one publication used both (65 patients). The cumulative presence of hypointense vessel sign was 54% (range 32%-100%) for T2* (668 patients) and 81% (range 34%-100%) for SWI (334 patients). There was rare mentioning of interrater agreement (6 publications, 210 patients) and reliability (1 publication, 20 patients) but the numbers reported ranged from good to excellent. In most publications (n = 22) perfusion MRI was used as a validation method (617 patients). More patients were scanned in the subacute than in the acute phase (596 patients vs 320 patients). Clinical outcome was reported in 13 publications (521 patients) but was not consistent. CONCLUSION:The low presence of vessels signs on T2*w imaging makes SWI much more promising. More research is needed to obtain formal validation and quantification.

Three-dimensional time-of-flight magnetic resonance angiography combined with high resolution T2-weighted imaging in preoperative evaluation of microvascular decompression

BACKGROUND Neurovascular compression(NVC) is the main cause of primary trigeminal neuralgia(TN) and hemifacial spasm(HFS). Microvascular decompression(MVD) is an effective surgical method for the treatment of TN and HFS caused by NVC. The judgement of NVC is a critical step in the preoperative evaluation of MVD, which is related to the effect of MVD treatment. Magnetic resonance imaging(MRI) technology has been used to detect NVC prior to MVD for several years. Among many MRI sequences, three-dimensional time-of-flight magnetic resonance angiography(3D TOF MRA) is the most widely used. However, 3D TOF MRA has some shortcomings in detecting NVC. Therefore, 3D TOF MRA combined with high resolution T2-weighted imaging(HR T2WI) is considered to be a more effective method to detect NVC.AIM To determine the value of 3D TOF MRA combined with HR T2WI in the judgment of NVC, and thus to assess its value in the preoperative evaluation of MVD.METHODS Related studies published from inception to September 2022 based on PubMed, Embase, Web of Science, and the Cochrane Library were retrieved. Studies that investigated 3D TOF MRA combined with HR T2WI to judge NVC in patients with TN or HFS were included according to the inclusion criteria. Studies without complete data or not relevant to the research topics were excluded. The Quality Assessment of Diagnostic Accuracy Studies checklist was used to assess the quality of included studies. The publication bias of the included literature was examined by Deeks’ test. An exact binomial rendition of the bivariate mixed-effects regression model was used to synthesize data. Data analysis was performed using the MIDAS module of statistical software Stata 16.0. Two independent investigators extracted patient and study characteristics, and discrepancies were resolved by consensus. Individual and pooled sensitivities and specificities were calculated. The I_(2) statistic and Q test were used to test heterogeneity. The study was registered on the website of PROSERO(registration No. CRD42022357158).RESULTS Our search identified 595 articles, of which 12(including 855 patients) fulfilled the inclusion criteria. Bivariate analysis showed that the pooled sensitivity and specificity of 3D TOF MRA combined with HR T2WI for detecting NVC were 0.96 [95% confidence interval(CI): 0.92-0.98] and 0.92(95%CI: 0.74-0.98), respectively. The pooled positive likelihood ratio was 12.4(95%CI: 3.2-47.8), pooled negative likelihood ratio was 0.04(95%CI: 0.02-0.09), and pooled diagnostic odds ratio was 283(95%CI: 50-1620). The area under the receiver operating characteristic curve was 0.98(95%CI: 0.97-0.99). The studies showed no substantial heterogeneity(I2 = 0, Q = 0.001 P = 0.50).CONCLUSION Our results suggest that 3D TOF MRA combined with HR T2WI has excellent sensitivity and specificity for judging NVC in patients with TN or HFS. This method can be used as an effective tool for preoperative evaluation of MVD.

Comparison of Diagnostic Effects of T2-Weighted Imaging,DWI,SWI,and DTI in Acute Cerebral Infarction

Objective:To achieve precision medicine,the use of imaging methods to help the clinical detection of cerebral infarction is conducive to the clinical development of a treatment plan and increase of the cure rate and improvement of the prognosis of patients.Methods:In this work,T2-weighted imaging(T2WI),diffusion-weighted imaging(DWI),susceptibility-weighted imaging(SWI),and diffusion tensor imaging(DTI)examinations were performed on 34 patients with clinically diagnosed cerebral infarction to measure the difference in signal intensity between the lesion and its mirror area and make a comparative analysis by means of the Student-Newman-Keuls method.Results:The detection rate of T2WI was 79%(27/34),the detection rate of DWI was 97%(33/34),the detection rate of SWI was 88%(30/34),and the detection rate of DTI was 94%(32/34).Conclusion:The imaging performance was in the order DWI>DTI>SWI>T2WI for the diagnosis of cerebral infarction,and combined imaging is better than single imaging.

Assessment the Optimal Effect of Time of Repetition: Extrinsic Pulse Parameter on Gd-DTPA Enhanced, Spin-Echo T1-Weighted MR Images under Low Magnetic Field Strength

The contrast agent concentration, the time of repetition (TR) and magnetic field strength are significant parameters that influence for the accurate signal intensity (SI) in quantitative Magnetic Resonance Imaging (MRI). Therefore, this study was conducted to investigate and refine the dependence and the optimal effect of Time of Repetition (TR) on the relationship between signal intensity and Gd-DTPA (Gadolinium-diethylene-triaminepenta-acetic acid) concentration, after applying two-dimensional (2D) Spin Echo (SE) pulse sequence under low-field MRI. In addition to that, the optimal concentration of Gd-DTPA at given sequence parameters at low-field MRI was also evaluated. A water-filled phantom was constructed for a range of Gd-DTPA concentrations (0 - 6 mmol/L) and the mean signal intensities (SIs) were assessed in the defined region of interest on T1-weighted images with different TR values (40 - 2000 ms). The generated signal-concentration curves for Gd-DTPA revealed that increasing TR was associated with the increase of the overall SIs and the maximum relationship between SI to concentration. Moreover, the required Gd-DTPA concentration to produce the maximum SI was associated to decrease with the increase of TR. In addition to this, the application of beyond 100 ms TR values in this study with relatively higher concentrations (beyond 1 - 2 mmol/L) has resulted predominantly non-linear patterns in the signal-concentration curves and it appears the saturation or decay of the SIs due to T2 effect. From these results, it can be suggested that the selection of relatively lower Gd-DTPA concentration ( mmol/L) with less than 800 ms (<800 ms) TR values can produce a better linear relationship between the concertation and SIs in T1-weighted SE low field contrast-enhanced MRI. Furthermore, this study also outlined the significance and necessity of the optimization of TR in SE sequence in low field MRI prior to a particular examination.

MRI T_2 star mapping、T_1 images与3D DESS融合图在隐匿性膝关节软骨损伤中的应用

目的探讨T_2 star mapping、T_1 images与3D DESS融合伪彩图在关节软骨损伤中的诊断价值。方法对26例关节软骨损伤患者行T_2 star mapping、T_1 images和3D DESS扫描,并将T_1 images、T_2 star mapping与3D DESS图像融合,评价患者股骨、胫骨、髌骨关节软骨损伤程度并与关节镜结果对比,计算融合伪彩图诊断软骨损伤的特异性、敏感性及与关节镜诊断结果一致性。结果 T_1 images-3D DESS融合伪彩图诊断关节软骨损伤的敏感度、特异度及Kappa值分别为92.8%、93.0%、0.769,T_2 star mapping-3D DESS融合伪彩图诊断关节软骨损伤的敏感度、特异度及Kappa值分别为91.4%、94.2%、0.787。结论 T_2 star mapping、T_1 images与3D DESS融合伪彩图在关节软骨早期损伤评价上优于关节镜。

Early brainstem hemorrhage progression:multi-sequence magnetic resonance imaging and histopathology

According to clinical statistics,the mortality of patients with early brainstem hemorrhage is high.In this study,we established rat models of brainstem hemorrhage by injecting type Ⅶ collagenase into the right basotegmental pontine and investigated the pathological changes of early brainstem hemorrhage using multi-sequence magnetic resonance imaging and histopathological methods.We found that brainstem hematoma gradually formed in the injured rats over the first 3 days and then reduced after 7 days.The edema that occurred was mainly of the vasogenic type.No complete myelin sheath structure was found around the focus of the brainstem hemorrhage.The integrity and continuity of nerve fibers gradually deteriorated over the first 7 days.Neuronal degeneration was mild in the first 3 days and then obviously aggravated on the 7^(th)day.Inflammatory cytokines,interleukin-1β,and tumor necrosis factorαappeared on the 1st day after intracerebral hemorrhage,reached peak levels on the 3^(rd)day,and decreased from the 7^(th)day.Our findings show the characteristics of the progression of early brainstem hemorrhage.

Rectal Cancer Stages T2 and T3 Identification Based on Asymptotic Hybrid Feature Maps

Many existing intelligent recognition technologies require huge datasets for model learning.However,it is not easy to collect rectal cancer images,so the performance is usually low with limited training samples.In addition,traditional rectal cancer staging is time-consuming,error-prone,and susceptible to physicians’subjective awareness as well as professional expertise.To settle these deficiencies,we propose a novel deep-learning model to classify the rectal cancer stages of T2 and T3.First,a novel deep learning model(RectalNet)is constructed based on residual learning,which combines the squeeze-excitation with the asymptotic output layer and new cross-convolution layer links in the residual block group.Furthermore,a two-stage data augmentation is designed to increase the number of images and reduce deep learning’s dependence on the volume of data.The experiment results demonstrate that the proposed method is superior to many existing ones,with an overall accuracy of 0.8583.Oppositely,other traditional techniques,such as VGG16,DenseNet121,EL,and DERNet,have an average accuracy of 0.6981,0.7032,0.7500,and 0.7685,respectively.

Fluorescence life-time imaging microscopy(FLIM)monitors tumor cell death triggered by photothermal therapy with MoS_(2) nanosheets

Recently,photothermal therapy(PTT)has been proved to have great potential in tumor therapy.In the last several years,MoS_(2),as one novel member of nanomaterials,has been applied into PTT due to its excellent photothermal conversion efficacy.In this work,we applied fuorescence lifetime imaging microscopy(FLIM)techniques into monitoring the PPT-triggered cell death under MoS_(2) nanosheet treatment.Two types of MoS_(2) nanosheets(single layer nanosheets and few layer nanosheets)were obtained,both of which exhibited presentable photothermal conversion fficacy,leading to high cell death rates of 4T1 cells(mouse breast cancer cells)under PTT.Next,live cell images of 4T1 cells were obtained via directly labeling the mitochondria with Rodamine123,which were then continuously observed with FLIM technique.FLIM data showed that the fuorescence lifetimes of mitochondria targeting dye in cells treated with each type of MoS_(2) nanosheets significantly increased during PTT treatment.By contrast,the fuorescence lifetime of the same dye in control cells(without nanomaterials)remained constant after laser irradiation.These findings suggest that FLIM can be of great value in monitoring cell death process during PTT of cancer cells,which could provide dynamic data of the cellular microenvironment at single cell level in multiple biomedical applications.

Linear-fitting-based similarity coefficient map for tissue dissimilarity analysis in T2^＊-w magnetic resonance imaging

Similarity coefficient mapping（SCM） aims to improve the morphological evaluation of T＊2weighted magnetic resonance imaging（T＊2-w MRI）. However, how to interpret the generated SCM map is still pending. Moreover, is it probable to extract tissue dissimilarity messages based on the theory behind SCM？ The primary purpose of this paper is to address these two questions. First, the theory of SCM was interpreted from the perspective of linear fitting. Then, a term was embedded for tissue dissimilarity information. Finally, our method was validated with sixteen human brain image series from multiecho T＊2-w MRI. Generated maps were investigated from signal-to-noise ratio（SNR） and perceived visual quality, and then interpreted from intra- and inter-tissue intensity. Experimental results show that both perceptibility of anatomical structures and tissue contrast are improved. More importantly, tissue similarity or dissimilarity can be quantified and cross-validated from pixel intensity analysis. This method benefits image enhancement, tissue classification, malformation detection and morphological evaluation.

Assessment of structural brain changes in patients with type 2 diabetes mellitus using the MRI-based brain atrophy and lesion index

Patients with type 2 diabetes mellitus(T2 DM) often have cognitive impairment and structural brain abnormalities.The magnetic resonance imaging(MRI)-based brain atrophy and lesion index can be used to evaluate common brain changes and their correlation with cognitive function,and can therefore also be used to reflect whole-brain structural changes related to T2 DM.A total of 136 participants(64 men and 72 women,aged 55–86 years) were recruited for our study between January 2014 and December 2016.All participants underwent MRI and Mini-Mental State Examination assessment(including 42 healthy control,38 T2 DM without cognitive impairment,26 with cognitive impairment but without T2 DM,and 30 T2 DM with cognitive impairment participants).The total and sub-category brain atrophy and lesion index scores in patients with T2 DM with cognitive impairment were higher than those in healthy controls.Differences in the brain atrophy and lesion index of gray matter lesions and subcortical dilated perivascular spaces were found between non-T2 DM patients with cognitive impairment and patients with T2 DM and cognitive impairment.After adjusting for age,the brain atrophy and lesion index retained its capacity to identify patients with T2 DM with cognitive impairment.These findings suggest that the brain atrophy and lesion index,based on T1-weighted and T2-weighted imaging,is of clinical value for identifying patients with T2 DM and cognitive impairment.Gray matter lesions and subcortical dilated perivascular spaces may be potential diagnostic markers of T2 DM that is complicated by cognitive impairment.This study was approved by the Medical Ethics Committee of University of South China(approval No.USC20131109003) on November 9,2013,and was retrospectively registered with the Chinese Clinical Trial Registry(registration No.Chi CTR1900024150) on June 27,2019.

MRI梯度回波T_2加权序列对脑内海绵状血管瘤的诊断价值

目的 通过分析比较自旋回波 (SE)序列和梯度回波T2 WI(准T2 序列T 2 )序列对脑内海绵状血管瘤 (CA)的显示能力 ,以探讨T 2 技术对CA的诊断价值。方法 对 18例CA病人采用SE和T 2 序列进行MRI检查 ,观察两者对CA病灶的检测能力。结果 SE序列共检出 2 3个CA病灶。而T 2 序列则比前者多发现 2 0个CA病灶。T 2 序列能更准确识别邻近蛛网膜下腔的皮层下和缺血灶附近的小CA病灶。结论 CA病人MRI检查时 ,常规SE序列与T 2 相结合 ,能更全面准确地提供诊断信息。

MRI FSE T2和GRE T2^＊成像技术在脊椎转移瘤中的应用

目的 比较快速自旋回波T2 加权 (FSET2 WI)和梯度回波T2 加权 (GRET2 WI)在脊椎转移瘤中的应用效果。资料与方法 5 0例脊椎转移瘤患者进行FSET2 WI和GRET2 WI扫描。分别测得正常骨髓、异常骨髓和脊柱背面的信号强度。计算其对比度 /噪声比值 (C/Ns)、信噪比 (SNR)并进行t检验。还对FSET2 WI和GRET2 WI序列对转移灶边界的清晰度进行比较。结果 GRET2 WI所有病灶的C/Ns和SNR均高于FSET2 WI。脊椎转移灶在GRET2 WI上的C/Ns和SNR分别为 2 2 .2 2± 11.5 0和 2 6 .2 1± 15 .96 (平均值±标准差 ) ,在FSET2 图像上分别为4 .19± 5 .0 8和 17.2 3± 11.0 8,两者C/Ns具有显著差异 (t=10 .14 ,P <0 .0 0 1) ;SNR也有明显差异 (t =3.2 7,P <0 .0 1)。并且GRET2 WI对脊椎转移灶边界的显示比FSET2 WI更清晰 (P <0 .0 0 5 )。结论 GRET2 WI比FSET2 WI能更清晰地显示脊椎转移瘤。

MR T_2WI直方图分析在评价髓母细胞瘤复发风险中的应用

目的:探讨MR T_2WI直方图分析在髓母细胞瘤复发风险评估中的应用价值。方法:将32例经手术病理证实的后颅窝髓母细胞瘤患者纳入研究,所有患者术后随访36个月,未见复发者纳入无复发组,发现复发者纳入复发组。在T_2WI图像中选择肿瘤最大层面,应用MaZda软件在病灶内勾画ROI进行灰度直方图分析,获得灰度平均值、方差、偏度、峰度及第1、第10、第50、第90和第99百分位数共9个参数的测量值并进行统计学分析,对两组间差异有统计学意义的参数,采用ROC曲线分析来评价其对髓母细胞瘤复发的诊断效能。结果:直方图分析提取的9个参数中,复发组的灰度方差小于无复发组,组间差异有统计学意义(P<0.05),两组间其它各项参数值的差异均无统计学意义(P>0.05)。灰度方差的ROC曲线下面积为0.725,鉴别肿瘤复发风险的临界值为376.26,诊断敏感度和特异度分别为60.0%和99.9%。结论:MR T_2WI直方图分析可作为评估髓母细胞瘤复发风险的重要辅助手段。

超顺磁性氧化铁胶束体系的制备和T_2弛豫增强作用

制备了在负离子型胶束十二烷基硫酸钠 (SDS)、羧甲基纤维素钠 (CMC) ,正离子型胶束十六烷基三甲基溴化铵 (CTAB)和非离子型胶束TritonX 1 0 0、PEG 40 0中的氧化铁粒子(SPIO)溶胶分散体系 .测定了这些SPIO胶束体系水质子的横向弛豫时间T2 ,并讨论了不同胶束性质对T2 的影响 .对PEG 40 0分散SPIO溶胶体系进行了动物急性毒性测试和活体T2加权成像实验 .结果表明 :该溶胶体系无明显急性毒性 。

肾上腺肿瘤磁共振T_2加权像的定量分析及定性诊断

通过肉眼观测32个肾上腺肿瘤MRT_2加权像(T_2 Weightedimage,T_2WI)的信号强度并着重行T_2WI定量分析(测量肿瘤T_2值和计算信号强度比),结果表明:肾上腺腺瘤、恶性肿瘤和嗜铬细胞瘤的肉眼信号强度、T_2值、肿瘤/肝信号强度比(T/LSIR)及肿瘤/脂肪信号强度比(T/FSIR)均呈递增趋势。三类肿瘤的T/LSIR和T/FSIR差异最为显著(P<0.01)且数值范围重叠最小。尽管肉眼观测T_2WI肾上腺肿瘤信号强度能有效方便地行鉴别诊断,但计算信号强度比值对肾上腺肿瘤的定性及鉴别诊断更为准确。

磁共振PDWI和T_(2) Mapping在长爪沙鼠腰椎间盘退变中的价值比较

为了探讨7.0 T MRI质子密度加权像(PDWI)与T_(2) mapping在长爪沙鼠腰椎间盘退变中的价值和意义。将20只雄性沙鼠,按照3、6、9月龄和12月龄分为4组,每组5只。通过腰椎MRI PDWI和T_(2) mapping检查,测量4组沙鼠L_(1)/L 2~L_(7)/S 1共140个椎间盘信号强度/脂肪信号平均值(SS_(disc)/SS_(fat))和T_(2)值。结果显示:随着月龄的增加,SS_(disc)/SS_(fat)和T_(2)值均出现不同程度的下降,以3月龄为参照,SS_(disc)/SS_(fat)在12月龄时出现显著性差异(P<0.05),而T_(2)值在9月龄时即出现显著性差异(P<0.05),在12月龄时出现极显著性差异(P<0.01)。表明PDWI和T_(2) mapping均可评估沙鼠腰椎间盘退变,但T_(2) mapping能发现更早期的沙鼠腰椎间盘退变差异。

磁共振T2加权成像纹理特征分析在脑胶质母细胞瘤与脑原发性中枢神经系统淋巴瘤鉴别诊断中的价值（英文）

目的探讨脑胶质母细胞瘤与原发中枢神经系统淋巴瘤磁共振成像T2加权图像(T2 weighted imaging, T2WI)纹理特征及影像学特征的差异。方法选取中国人民解放军总医院及海南分院81例胶质母细胞瘤和28例原发性中枢神经系统淋巴瘤患者术前脑部MRI图像,观察其平扫及增强扫描影像学特征,同时采用ImagJ软件的纹理分析插件,分别对T2WI横轴位图像进行纹理特征分析(选取角二阶矩、对比度、自相关、逆差距、熵5个纹理特征参数)。采用独立样本t检验及Mann-Whitney U检验分析各组之间的纹理特征差异,同时进行二元Logistic回归分析法建立回归模型,并进行受试者工作特征曲线(ROC)分析影像学特征及其纹理特征的诊断效能。结果 MRI平扫及增强扫描结果显示:两种肿瘤在肿瘤内囊变坏死(P=0.000)、增强扫描"花环样"强化(P=0.000)及"缺口征"(P=0.635)方面的差异存在统计学意义,"火焰样"瘤周水肿的差异无统计学意义(P>0.05)。T2WI图像纹理特征参数中,角二阶矩(P=0.006)、对比度(P=0.000)、自相关(P=0.002)、逆差距(P=0.000)及熵(P=0.015)在两组之间的差异均存在统计学意义,以上参数的单变量ROC曲线下面积分别为0.671,0.752,0.695,0.000和0.646。进入Logistic回归模型联合变量(肿瘤内囊变坏死、"花环样"强化、"缺口征"及纹理特征对比度)的ROC曲线下面积为0.917。二元Logistic回归分析提示肿瘤内囊变坏死、"花环样"强化、"缺口征"及纹理特征对比度可以作为鉴别二者的变量。结论由磁共振T2WI图像的纹理特征及影像学特征构成的Logistic回归模型在脑胶质母细胞瘤与原发性中枢神经系统淋巴瘤的鉴别诊断方面具有一定价值。

基于T_2加权图像的纹理分析:不同转移部位间肾癌纹理特征的对比

目的:利用磁共振T_2加权图像纹理分析方法,探讨发生不同部位转移(肺、骨、区域淋巴结)的肾透明细胞癌(ccRCC)影像特征的差异。方法:回顾性分析25例经影像及病理证实发生单一部位转移的ccRCC患者的MRI资料,其中发生肺转移7例,发生骨转移9例,发生区域淋巴结转移9例。所有患者行肾脏3.0T MR扫描,利用软件工具在T_2加权图像上逐层对病灶进行ROI勾画并融合为感兴趣容积(VOI),获得93个纹理特征参数。使用非参数检验对3组ccRCC原发灶的特征参数进行统计学分析,确定有统计学差异的特征参数并进行ROC曲线分析。结果:基于T_2加权图像生成的93个肿瘤特征参数中,共有12个参数在3组间的差异具有统计学意义(P<0.05)。将3组病例分别划分为二分类变量后,有和无区域淋巴结转移组之间未发现有统计学差异的参数;而肺转移与非肺转移组之间有统计学差异的参数有19个,其中病灶表面积的ROC曲线下面积(AUC)最大,为0.881±0.080(95%CI为0.689~0.975);骨转移与非骨转移组之间有统计学差异的参数有14个,其中灰度不均匀性的AUC最大,为0.875±0.070(95%CI为0.682~0.972)。结论:发生不同部位转移(肺、骨、区域淋巴结)的ccRCC原发灶的影像组学特征存在差异,纹理分析或可作为一种预测ccRCC转移部位的有效诊断方法。

T_2-mapping评估成人腰椎骨髓含水量与年龄、性别的相关性

目的:探讨T_2-mapping技术在评估成人腰椎骨髓含水量与年龄、性别相关性中的应用价值。方法:采用3.0T MR对78例健康志愿者行腰椎多回波SE序列T_2-mapping检查。78例志愿者中男36例,女42例,按年龄分为20~29岁、30~39岁、40~49岁、≥50岁共4组,每个年龄段又按性别分为男、女2组,共8组。测量78例志愿者L1-L5各个椎体(共390个椎体)的T_2值。对相同性别、不同年龄段及相同年龄段、不同性别的腰椎T_2值进行组间比较,并进行统计学分析。结果:相同性别、不同年龄段的腰椎T_2值比较:男性中20~29岁年龄段的腰椎T_2值均高于其它年龄段,差异均有统计学意义(P值均<0.05),其它年龄段之间差异均无统计学意义(P值均>0.05);女性中≥50岁年龄段的腰椎T_2值均低于其它年龄段,差异均有统计学意义(P值均<0.05),其它年龄段之间差异均无统计学意义(P值均>0.05)。相同年龄段、不同性别的腰椎T_2值比较:各个年龄段上女性的腰椎T_2值均高于男性,差异均有统计学意义(P值均<0.05)。结论:T_2-mapping技术可用于评估成人腰椎骨髓含水量在年龄、性别上的差异。男性与女性腰椎骨髓含水量随年龄变化规律不同,女性腰椎骨髓含水量高于男性。