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临床研究
ADC最小值联合临床及影像特征预测HIFU治疗子宫肌瘤疗效研究
刘姿延 黄小华 刘子熠 王渊 万夕瑶 蒋雨

Cite this article as: LIU Z Y, HUANG X H, LIU Z Y, et al. Study of ADC minimum in combination with clinical and imaging features for prediction of HIFU efficacy in treatment of uterine fibroids[J]. Chin J Magn Reson Imaging, 2024, 15(9): 101-106.本文引用格式:刘姿延, 黄小华, 刘子熠, 等. ADC最小值联合临床及影像特征预测HIFU治疗子宫肌瘤疗效研究[J]. 磁共振成像, 2024, 15(9): 101-106. DOI:10.12015/issn.1674-8034.2024.09.017.


[摘要] 目的 探讨基于表观扩散系数(apparent diffusion coefficient, ADC)最小值(ADCmin)及临床和影像特征构建模型预测高强度聚焦超声(high intensity focused ultrasound, HIFU)治疗子宫肌瘤的临床疗效。材料与方法 回顾性收集2021年9月至2023年12月行子宫肌瘤HIFU治疗并符合纳排标准的153例患者临床及影像资料,共153枚肌瘤纳入研究(单病例存在多个肌瘤取其肌瘤最大枚)。超声评估HIFU治疗3个月后肌瘤体积缩小率,并将其分为疗效显著组(≥50%体积缩小,n=62)和非显效组(<50%体积缩小,n=91)。测量子宫肌瘤ADCmin和ADC平均值(ADCmean),采用单因素分析和多因素logistic回归对临床和影像资料进行筛选后建立临床影像模型。通过受试者工作特征(receiver operating characteristic, ROC)曲线比较子宫肌瘤ADCmin和ADCmean的预测效能,选择子宫肌瘤ADC具有较高预测效能的量化指标与临床及影像特征结合构建联合模型。ROC评估ADCmin、临床影像模型及联合模型的预测效能,DeLong检验比较不同模型间ROC曲线下面积(area under the curve, AUC)的差异。结果 共筛出血红蛋白、身体质量指数(body mass index, BMI)、T1WI增强信号程度三个因素建立临床影像特征模型。ROC曲线显示ADCmin、ADCmean的AUC值分别为0.753 [95%置信区间(confidence interval, CI):0.677~0.828]、0.658(95% CI:0.570~0.746),DeLong检验结果表明ADCmin的预测效能高于ADCmean(P<0.05)。临床影像模型及ADCmin与临床影像特征联合模型的AUC值分别为0.711(95% CI:0.627~0.796)、0.816(95% CI:0.748~0.884),DeLong检验显示ADCmin的预测效能与临床影像模型的AUC差异无统计学意义(P>0.05)。ADCmin与临床及影像特征联合模型的预测效能优于ADCmin值(P<0.05)及临床影像特征模型(P<0.05)。结论 ADCmin与临床及影像特征构建的联合模型可有效预测HIFU治疗子宫肌瘤的临床疗效,并能为临床治疗方案的制订提供一定参考依据。
[Abstract] Objective Construct a model to predict the clinical efficacy of high intensity focused ultrasound (HIFU) in treating uterine fibroids based on the apparent diffusion coefficient minimum (ADCmin) and clinical and imaging features.Materials and Methods Clinical and imaging data of 153 patients who underwent HIFU treatment for uterine fibroids from September 2021 to December 2023 and met the criteria for inclusion were retrospectively collected, and a total of 153 fibroids were included in the study (choosing the largest in cases with multiple). Ultrasound assessed the fibroids' volume reduction rate three months after HIFU treatment, categorizing them into a significantly effective group (≥50% volume reduction, n=62) and a non-effective group (<50% volume reduction, n=91). Measurements were taken for the uterine fibroids' ADCmin and apparent diffusion coefficient mean (ADCmean). Univariate and multivariate logistic regression analyses were performed on clinical and imaging data, identifying factors to establish a clinical imaging feature model. Receiver operating characteristic (ROC) curves compared the predictive performance of uterine fibroids' ADCmin and ADCmean. A combined model was constructed by integrating the quantifiable indicator with high predictive efficiency, ADCmin, and the clinical imaging feature model. ROC evaluation and DeLong test compared the area under the curve (AUC) differences between ADCmin, the clinical imaging feature model, and the combined model.Results Hemoglobin, body mass index (BMI), and T1WI enhancement signal intensity were identified as factors to establish a clinical imaging feature model. The ROC curve demonstrates that the AUC values for ADCmin and ADCmean were 0.753 [95% confidence interval (CI): 0.677-0.828] and 0.658 (95% CI: 0.570-0.746), respectively. The DeLong test results show that ADCmin demonstrates higher predictive performance than ADCmean (P<0.05). The AUC values for the clinical imaging feature model and the combined ADCmin and clinical imaging feature model were 0.711 (95% CI: 0.627-0.796) and 0.816 (95% CI: 0.748-0.884), respectively. DeLong test indicates that the difference in AUC between ADCmin and the clinical imaging model is not statistically significant (P>0.05). The predictive efficacy of the combined model of ADCmin and clinical imaging features surpasses that of ADCmin alone (P<0.05) and the clinical imaging feature model (P<0.05).Conclusions The combined model constructed by ADCmin and clinical and imaging features can effectively predict the clinical efficacy of HIFU in the treatment of uterine fibroids, and can offer valuable insights for formulating clinical treatment strategies.
[关键词] 子宫肌瘤;高强度聚焦超声;磁共振成像;表观扩散系数;预测
[Keywords] uterine fibroids;high intensity focused ultrasound;magnetic resonance imaging;apparent diffusion coefficient;prediction

刘姿延    黄小华 *   刘子熠    王渊    万夕瑶    蒋雨   

川北医学院附属医院放射科,南充 637000

通信作者:黄小华,E-mail: 15082797553@163.com

作者贡献声明::黄小华参与设计本研究的方案,对稿件重要内容进行了修改,获得了南充市市校合作项目的资助;刘姿延参与了研究方案的设计,起草和撰写稿件,获取、分析并解释本研究的数据;刘子熠、王渊、万夕瑶、蒋雨获取、分析或解释本研究的数据,对稿件的部分内容进行了修改。全体作者都同意发表最后的修改稿,同意对本研究的所有方面负责,确保本研究的准确性和诚信。


基金项目: 南充市市校合作项目 19SXHZ0429
收稿日期:2024-04-15
接受日期:2024-08-09
中图分类号:R445.2  R737.33 
文献标识码:A
DOI: 10.12015/issn.1674-8034.2024.09.017
本文引用格式:刘姿延, 黄小华, 刘子熠, 等. ADC最小值联合临床及影像特征预测HIFU治疗子宫肌瘤疗效研究[J]. 磁共振成像, 2024, 15(9): 101-106. DOI:10.12015/issn.1674-8034.2024.09.017.

0 引言

       子宫肌瘤是女性盆腔中最常见的良性肿瘤,发病率约为70%[1]。部分患者可出现较严重的临床症状,包括异常出血、月经过多、贫血和痛经等,需要及时干预[2, 3]。干预方法主要包括药物疗法、手术、子宫动脉栓塞术(uterine artery embolization, UAE)及高强度聚焦超声(high intensity focused ultrasound, HIFU)[4]。HIFU具有并发症较少、保留生育能力和恢复快的优点,现已被广泛用于临床实践中[5, 6, 7]。由于HIFU治疗子宫肌瘤患者的临床疗效存在差异,并非所有肌瘤都适合HIFU治疗,因此精准的术前评估至关重要[8, 9]。MRI是评估子宫肌瘤较为精确的检查方法[10, 11],扩散加权成像(diffusion weighted imaging, DWI)是其最常用的技术之一,能无创地对活体组织细胞密度变化和微循环状态提供半定量信息[12],但易受T2穿透效应的影响[13]。利用DWI图像测算出的表观扩散系数可有效避免T2权重的影响,并能真正地反映子宫肌瘤组织细胞水分子扩散受限程度。既往研究评估HIFU治疗子宫肌瘤疗效大多集中在表观扩散系数(apparent diffusion coefficient, ADC)平均值(ADCmean)及其MRI序列的选择上[14, 15, 16, 17]。ADCmean代表组织细胞水分子扩散受限程度的整体水平,而ADC最小值(ADCmin)则凸显了水分子扩散受限范围最严重的部分[18],在实际测量中更方便易行,并且目前还未见相关研究报告。因此本研究基于肌瘤HIFU治疗3个月后超声评估体积缩小率作为分组指标,拟构建ADCmin及临床影像特征的联合模型预测HIFU治疗子宫肌瘤的临床疗效,有望为临床治疗方案的制订提供一定的参考依据。

1 材料与方法

1.1 一般资料

       回顾性收集2021年9月至2023年12月在本院行子宫肌瘤HIFU治疗患者的临床及影像资料。纳入标准:(1)临床及影像检查诊断为子宫肌瘤;(2)绝经前或围绝经期女性;(3)肌瘤直径介于3~10 cm之间;(4)无相关外科手术或药物治疗史;(5)手术前、后三天内均完成MRI检查;(6)具备完整DWI图像,可用于ADC值测量;(7)临床随访资料完备。排除标准:(1)哺乳或怀孕女性;(2)存在其他子宫或附件疾病的患者;(3)疑似恶变肌瘤;(4)合并心、肝、肾等脏器功能衰竭。最终,纳入了153例患者的153枚肌瘤。本研究遵守《赫尔辛基宣言》,经川北医学院附属医院伦理委员会批准,免除受试者知情同意,批准文号:2024ER96-1。

1.2 MRI检查

       使用中国联影uMR660 1.5 T和uMR790 3.0 T超导型磁共振扫描仪,12通道体部相控阵列线圈。扫描序列和参数如下(表1表2)。两台磁共振b值均设定为50、800 s/mm2。使用高压注射器以2 mL/s的速率注射对比剂钆双胺注射液(通用电气药业上海有限公司),注射剂量为0.1 mmol/kg,分别在注射对比剂后的15、30和45 s分别采集动脉早期、中期及晚期图像。

表1  uMR790 3.0 T各序列主要参数
Tab. 1  uMR790 3.0 T main parameters of each sequence
表2  uMR660 1.5 T各序列参数
Tab. 2  uMR660 1.5 T main parameters of each sequence

1.3 分组方法

       采用多普勒超声诊断仪,分别于HIFU治疗前、治疗3个月后进行阴道超声检查,并计算子宫肌瘤的体积和体积缩小率,体积(cm3)=左右径(cm)×前后径(cm)×长径(cm)×0.523[19],体积缩小率=(治疗前肌瘤体积-治疗3个月后肌瘤体积)/治疗前肌瘤体积×100%。依据治疗3个月后子宫肌瘤体积缩小率≥50%分为疗效显著组,<50%为非显效组[20, 21]。由两位具有十年诊断经验的中级职称放射医师读取子宫肌瘤患者的影像资料,意见不统一时协商达成一致。影像资料包含以下内容:腹壁的厚度、子宫肌瘤腹侧至皮肤的距离、子宫肌瘤中心到骶骨的水平距离、子宫位置、子宫肌瘤位置、肌瘤的类型、T1WI增强信号强度(轻度强化:强化程度低于子宫肌层;中度强化:与子宫肌层相当;明显强化:高于子宫肌层)、T1WI增强信号均匀度(均匀:呈均匀强化;非均匀:呈非均匀强化)、T2WI肌瘤的信号强度(低信号:信号强度低于或等于骨骼肌信号强度;等信号:高于骨骼肌但低于子宫肌层信号强度;高信号:等于或高于子宫肌层信号强度)、T2WI的信号均匀度(均匀:子宫肌瘤内部信号较均匀;非均匀:内部信号不均匀)、彩色多普勒血流成像(color doppler flow imaging, CDFI)的信号[分为少量(Adler Ⅰ级:可看到1~2个短棒状或点状血流信号)、稍丰富(Adler Ⅱ级:可看到1个较长血管或3~4个点状血管,长血管长度超过或接近肿块半径)和丰富(Adler Ⅲ级:可看到2个较长血管或5个以上点状血管)][22]。在动脉晚期图像上获得T1WI增强信号强度、T1WI增强信号均匀度,其余特征在T2WI矢状位图像上获得[23]。其他临床特征在病历系统上获得,包括年龄、身体质量指数(body mass index, BMI)、白细胞、红细胞、外周血小板和血红蛋白。

1.4 图像分析

       单病例存在多个肌瘤时,取其最大枚。由两名具有十年诊断经验的中级职称放射医师采用双盲法在联影后处理工作站上进行ADC值测量,意见不统一时协商达成一致。避开出血、坏死、囊性区选取感兴趣区(region of interest, ROI),ROI面积>50 mm2图1[24]。在五个连续层面上分别测量ADCmean和ADCmin,每一个层面选取一个ROI,最后以这五个层面的平均值作为该子宫肌瘤的ADCmean。记录每一层面的ADCmin,再从五个层面中取最小值作为该子宫肌瘤的ADCmin。

图1  ROI勾画示意图。1A:女,46岁,HIFU消融疗效不显著,ADC序列图像,ADCmin为1.010×10-3 mm2•s-1,ROI为52.2 mm2(箭);1B:女,51岁,HIFU消融疗效显著,ADC序列图像,ADCmin为0.668×10-3 mm2•s-1,ROI为52.1 mm2(箭)。ROI:感兴趣区;HIFU:高强度聚焦超声;ADC:表观扩散系数;ADCmin:ADC最小值。
Fig. 1  ROI delineation diagram. 1A: Female, 46 years old, non-significant HIFU ablation efficacy, ADC sequence image, ADCmin of 1.010×10-3 mm2•s-1, ROI of 52.2 mm2 (arrow); 1B: Female, 51 years old, significant HIFU ablation efficacy, ADC sequence image, ADCmin of 0.668×10-3 mm2•s-1, ROI of 52.1 mm2 (arrow). ROI: region of interest; HIFU: high intensity focused ultrasound; ADC: apparent diffusion coefficient; ADCmin: ADC minimum.

1.5 资料分析

       测量子宫肌瘤ADCmin和ADCmean,采用单因素分析和多因素logistic回归对临床和影像资料进行筛选建立临床影像模型。通过ROC比较子宫肌瘤ADCmin和ADCmean的预测效能,选择子宫肌瘤ADC具有较高预测效能的量化指标与临床影像特征结合构建联合模型。

1.6 统计学分析

       应用SPSS(V27.0,IBM,美国)和R语言(V4.3.2,R Foundation for Statistical Computing,奥地利维也纳,https://www.r-project.org/)对数据进行分析,具体使用R语言包包括:rms,ggplot2和rmda。采用Shapiro-Wilk方法对计量资料进行正态性检验。符合正态分布的计量资料,采用独立样本t检验比较,数据用均数±标准差(x¯±s)表示。不符合正态分布则采用非参数秩和检验(Mann-Whitney U检验)比较,数据用中位数四分位距MQ25Q75)表示。计数资料采用χ2检验比较,数据用例数或构成比表示。对于单因素分析筛选出的数据,采用多因素logistic回归中的二元逻辑回归(进入法)来分析。受试者工作特征(receiver operating characteristic, ROC)曲线评估模型的预测效能,DeLong检验比较不同模型间曲线下面积(area under the curve, AUC)差异。使用校正曲线评价模型的拟合优度,决策曲线评价模型的临床获益。P<0.05为差异有统计学意义。

2 结果

2.1 临床、影像特征及ADC表现

       依据纳排标准,共纳入153例患者,其中疗效显著组62例,非显效组91例。单因素分析结果显示,BMI、血红蛋白、T1WI增强信号强度在疗效显著组与非显效组间差异有统计学意义(P<0.05;表3表4)。疗效显著组的ADCmean与ADCmin均小于非显效组,两组间的差异均具有统计学意义(P<0.05;表5)。

表3  不同临床疗效组的临床特征比较
Tab. 3  Comparison of clinical characteristics in different clinical efficacy groups
表4  不同临床疗效组的影像特征比较
Tab. 4  Comparison of imaging features in different clinical efficacy groups
表5  不同临床疗效组ADCmean与ADCmin的比较
Tab. 5  Comparison of ADCmean and ADCmin in different clinical efficacy groups

2.2 特征筛选及模型构建

       单因素分析筛选出的特征通过二元logistic回归进一步分析,最终保留了血红蛋白、BMI和T1WI增强信号强度这三个差异有统计学意义的特征(表6),将其结合起来构建临床影像模型。ROC曲线显示ADCmean和ADCmin的AUC分别为0.658 [95%置信区间(confidence interval, CI):0.570~0.746]和0.753(95% CI:0.677~0.828)(图2),DeLong检验显示ADCmin的预测效能高于ADCmean(Z=-2.050,P=0.040)。因此选择ADCmin与临床影像特征结合构建联合模型。

图2  ADCmean与ADCmin ROC曲线图。
图3  ADCmin、临床影像模型及两者联合模型ROC曲线图。ADCmean:表观扩散系数平均值;ADCmin:表观扩散系数最小值;ROC:受试者工作特征。
Fig. 2  The ROC curves for ADCmean and ADCmin.
Fig. 3  The ROC curves for ADCmin, clinical imaging model and combined model. ADCmin: apparent diffusion coefficient minimum; ADCmean:apparent diffusion coefficient mean; ROC: receiver operating characteristic.
表6  临床和影像学特征的二元logistic回归分析
Tab. 6  Binary logistic regression analysis of clinical and imaging characteristics

2.3 模型效能评估

       运用ROC曲线对ADCmin、临床影像模型及两者联合模型的预测效能进行评估(图3,表7)。结果显示ADCmin的AUC值为0.753(95% CI:0.677~0.828),敏感度为64.5%,特异度为75.8%;临床影像模型的AUC值为0.711(95% CI:0.627~0.796),敏感度51.6%,特异度83.5%;联合模型的AUC值为0.816(95% CI:0.748~0.884),敏感度72.6%,特异度为80.2%。DeLong检验显示联合模型的预测效能优于ADCmin(Z=-2.189,P=0.029)及临床影像模型(Z=-2.897,P=0.004),而ADCmin和临床影像模型的AUC值差异无统计学意义(Z=-0.708,P=0.479)。校正曲线显示(图4),联合模型的预测概率与实际观察概率之间拟合度良好。决策曲线显示(图5),在大部分阈值概率内,联合模型的临床净收益高于ADCmin和临床影像模型。

图4  模型校正曲线图。
图5  模型决策曲线图。ADCmin为表观扩散系数最小值。
Fig. 4  Calibration curve of the models.
Fig. 5  Decision curves of the models. ADCmin: apparent diffusion coefficient minimum.
表7  ROC曲线分析结果
Tab. 7  Results of ROC curve analysis

3 讨论

       本研究基于ADCmin结合临床及影像特征建立联合模型,用于预测子宫肌瘤患者HIFU治疗的临床疗效。ROC曲线显示ADCmin值、临床影像模型及联合模型的AUC分别为0.753、0.711和0.816,联合模型的预测效能优于ADCmin值(P<0.05)及临床影像模型(P<0.05),表明ADCmin结合临床及影像特征的联合模型在预测HIFU治疗效果方面具有更高的准确性。本研究创新性地利用ADCmin值结合临床影像特征预测HIFU疗效的有效性,为临床治疗方案的选择提供了新的参考依据,具有重要的临床价值。

3.1 相关研究分析

       既往研究多采用非灌注体积比(non-perfused volume ratio, NPVR)来评价HIFU消融子宫肌瘤的疗效[22]。NPVR反映术后即刻的肌瘤非灌注情况,而体积缩小率则是随访期间肌瘤体积的变化。本研究结合术后3个月超声评估体积缩小率作为分组指标,有助于进一步了解HIFU治疗的长期效果。且目前临床随访主要基于超声评估[25, 26]。研究表明,NPVR与肌瘤收缩之间存在显著的统计学相关性,治疗后肌瘤体积缩小幅度可通过提高NPVR来实现[27]。因此,本研究依据子宫肌瘤HIFU治疗3个月后超声评估体积缩小率作为分组指标[21]

3.2 ADCmin值对比与分析

       目前已有研究运用DWI和ADC平均值评价HIFU治疗子宫肌瘤的临床疗效,并显示出良好的评估价值。刘蓉华等[28]发现低ADC值的肌瘤超声消融率较高。SAINIO等[15]发现ADC分类可用于预测磁共振引导聚焦超声治疗效果,并且优于Funaki分类。本研究发现疗效显著组的术前ADCmean小于非显效组,与以往研究一致[28, 29]。ROC曲线显示,ADCmin的预测效能高于ADCmean(0.753 vs. 0.658,P<0.05)。因此,选择ADCmin作为评估HIFU治疗子宫肌瘤临床疗效的指标。本研究显示疗效显著组的术前ADCmin值明显低于非显效组(P<0.05),分析原因可能与两组肌瘤的组织病理学变化有关。子宫平滑肌瘤是一种平滑肌细胞排列紊乱和聚集的肿瘤。体积缩小率大的肌瘤含水量较低,细胞外基质大量的胶原纤维限制了水分子的自由扩散,ADCmin反映了组织中水分子扩散受限最显著的区域[30],因此该组肌瘤ADCmin较低。体积缩小率较小的肌瘤含有更多水分和相对较少的间质,细胞外水分子可以相对自由地扩散,ADCmin较高[31]

3.3 临床影像特征研究分析

       本研究结果显示BMI、T1WI增强信号强度在疗效显著组与非显效组间的差异有统计学意义。这表明高BMI、T1WI增强明显强化的子宫肌瘤对HIFU治疗的临床疗效不利,这一发现与岳俊宏[8]的研究结果一致。BMI值增高可能导致患者腹部皮下脂肪增厚,在HIFU治疗过程中超声波需要穿透更多非目标组织,同时发生折射、反射、散射等现象,导致能量衰减增多[32, 33],不利于治疗。T1WI增强程度反映了肌瘤血供情况,血供丰富的肌瘤在HIFU治疗时血液带走部分能量,超声能量难以有效聚集,因此疗效不佳[34]。此外,本研究还发现血红蛋白水平影响着HIFU治疗子宫肌瘤的临床疗效,分析原因可能与富细胞型子宫肌瘤有关。王袁[35]发现超过1/3的富细胞型子宫肌瘤患者出现术前贫血,而该型子宫肌瘤的ADC值较低[36],临床疗效较好[29]

3.4 局限性

       本文存在以下局限性:(1)样本量偏小,未进行外部数据验证;(2)回顾性分析,是否出现选择偏倚有待进一步研究;(3)采集数据源于两种不同场强设备,可能对其鲁棒性有一定的影响;(4)ADC值的测量可能存在一定误差。

4 结论

       总之,ADCmin联合临床及影像特征构建的联合模型可有效预测HIFU治疗子宫肌瘤的临床疗效,有助于子宫肌瘤患者最佳治疗方案的选择。

[1]
QIN S Z, LIN Z Y, LIU N, et al. Prediction of postoperative reintervention risk for uterine fibroids using clinical-imaging features and T2WI radiomics before high-intensity focused ultrasound ablation[J/OL]. Int J Hyperthermia, 2023, 40(1): 2226847 [2024-04-14]. https://pubmed.ncbi.nlm.nih.gov/37394476/. DOI: 10.1080/02656736.2023.2226847.
[2]
DE LA CRUZ M S D, BUCHANAN E M. Uterine fibroids: diagnosis and treatment[J]. Am Fam Physician, 2017, 95(2): 100-107.
[3]
GIULIANI E, AS-SANIE S, MARSH E E. Epidemiology and management of uterine fibroids[J]. Int J Gynaecol Obstet, 2020, 149(1): 3-9. DOI: 10.1002/ijgo.13102.
[4]
韦超. 基于常规MRI和T_2WI-影像组学对子宫肌瘤病理分型、HIFU消融难度和即刻消融率的预测研究[D]. 合肥: 安徽医科大学, 2021. DOI: 10.26921/d.cnki.ganyu.2021.000015.
WEI C. Prediction of pathological classification, HIFU ablation difficulty and immediate ablation rate of hysteromyoma based on conventional MRI and T_2WI- imaging[D].Hefei: Anhui Medical University, 2021. DOI: 10.26921/d.cnki.ganyu.2021.000015.
[5]
LIU L, WANG T F, LEI B Y. High-intensity focused ultrasound (HIFU) ablation versus surgical interventions for the treatment of symptomatic uterine fibroids: a meta-analysis[J]. Eur Radiol, 2022, 32(2): 1195-1204. DOI: 10.1007/s00330-021-08156-6.
[6]
LYON P C, RAI V, PRICE N, et al. Ultrasound-guided high intensity focused ultrasound ablation for symptomatic uterine fibroids: preliminary clinical experience[J]. Ultraschall Med, 2020, 41(5): 550-556. DOI: 10.1055/a-0891-0729.
[7]
LIU D, ZHANG X Y, GONG X, et al. Learning curve of USgHIFU ablation for uterine fibroids: a multi-center prospective study[J]. J Ultrasound Med, 2022, 41(12): 3051-3059. DOI: 10.1002/jum.16056.
[8]
岳俊宏. 高强度聚焦超声治疗子宫肌瘤的疗效评价及其疗效预测模型的建立[D]. 广州: 南方医科大学, 2021. DOI: 10.27003/d.cnki.gojyu.2021.000632.
YUE J H. Evaluation of therapeutic effect of high intensity focused ultrasound on hysteromyoma and establishment of its therapeutic effect prediction model[D].Guangzhou: Southern Medical University, 2021. DOI: 10.27003/d.cnki.gojyu.2021.000632.
[9]
MARINOVA M, GHAEI S, RECKER F, et al. Efficacy of ultrasound-guided high-intensity focused ultrasound (USgHIFU) for uterine fibroids: an observational single-center study[J]. Int J Hyperthermia, 2021, 38(2): 30-38. DOI: 10.1080/02656736.2021.1939444.
[10]
TESTA A C, DI LEGGE A, BONATTI M, et al. Imaging techniques for evaluation of uterine myomas[J]. Best Pract Res Clin Obstet Gynaecol, 2016, 34: 37-53. DOI: 10.1016/j.bpobgyn.2015.11.014.
[11]
LI C W, HE Z M, LV F J, et al. An interpretable MRI-based radiomics model predicting the prognosis of high-intensity focused ultrasound ablation of uterine fibroids[J/OL]. Insights Imaging, 2023, 14(1): 129 [2024-04-14]. https://pubmed.ncbi.nlm.nih.gov/37466728/. DOI: 10.1186/s13244-023-01445-2.
[12]
GIBBONS M, SIMKO J P, CARROLL P R, et al. Prostate cancer lesion detection, volume quantification and high-grade cancer differentiation using cancer risk maps derived from multiparametric MRI with histopathology as the reference standard[J]. Magn Reson Imaging, 2023, 99: 48-57. DOI: 10.1016/j.mri.2023.01.006.
[13]
BONDE A, LAGO E A D, FOSTER B, et al. Utility of the diffusion weighted sequence in gynecological imaging: review article[J/OL]. Cancers, 2022, 14(18): 4468 [2024-04-14]. https://pubmed.ncbi.nlm.nih.gov/36139628/. DOI: 10.3390/cancers14184468.
[14]
曾雪伟, 周守国, 黄耀渠, 等. 表观弥散系数对磁共振引导聚焦超声术治疗子宫肌瘤效果的评估[J]. 中山大学学报(医学科学版), 2023, 44(5): 863-869. DOI: 10.13471/j.cnki.j.sun.yat-sen.univ(med.sci).2023.0520.
ZENG X W, ZHOU S G, HUANG Y Q, et al. Efficacy evaluation of apparent diffusion coefficient in the treatment of uterine fibroid by magnetic resonance guided focused ultrasound surgery[J]. J Sun Yat Sen Univ Med Sci, 2023, 44(5): 863-869. DOI: 10.13471/j.cnki.j.sun.yat-sen.univ(med.sci).2023.0520.
[15]
SAINIO T, SAUNAVAARA J, KOMAR G, et al. Feasibility of apparent diffusion coefficient in predicting the technical outcome of MR-guided high-intensity focused ultrasound treatment of uterine fibroids-a comparison with the Funaki classification[J]. Int J Hyperthermia, 2021, 38(1): 85-94. DOI: 10.1080/02656736.2021.1874545.
[16]
JIANG Y, QIN S Z, WANG Y L, et al. Intravoxel incoherent motion diffusion-weighted MRI for predicting the efficacy of high-intensity focused ultrasound ablation for uterine fibroids[J/OL]. Front Oncol, 2023, 13: 1178649 [2024-04-14].https://pubmed.ncbi.nlm.nih.gov/37427113/. DOI: 10.3389/fonc.2023.1178649.
[17]
ZHENG Y N, CHEN L P, LIU M Q, et al. Prediction of clinical outcome for high-intensity focused ultrasound ablation of uterine leiomyomas using multiparametric MRI radiomics-based machine leaning model[J/OL]. Front Oncol, 2021, 11: 618604 [2024-04-14]. https://pubmed.ncbi.nlm.nih.gov/34567999/. DOI: 10.3389/fonc.2021.618604.
[18]
KANG Y, CHOI S H, KIM Y J, et al. Gliomas: Histogram analysis of apparent diffusion coefficient maps with standard- or high-b-value diffusion-weighted MR imaging: correlation with tumor grade[J]. Radiology, 2011, 261(3): 882-890. DOI: 10.1148/radiol.11110686.
[19]
金琳, 石琴, 封岚, 等. CEUS定量参数及增强形态与高强度聚焦超声治疗子宫肌瘤疗效的关系[J]. 中国介入影像与治疗学, 2018, 15(3): 152-155. DOI: 10.13929/j.1672-8475.201709002.
JIN L, SHI Q, FENG L, et al. Relationship of CEUS quantitative parameters and enhance patterns with therapeutic effect of high-intensity focused ultrasound for hysteromyoma[J]. Chin J Interv Imag Ther, 2018, 15(3): 152-155. DOI: 10.13929/j.1672-8475.201709002.
[20]
刘玛丽, 袁媛, 李明东, 等. MRI影像组学及临床特征联合模型预测高强度聚焦超声治疗子宫肌瘤效果[J]. 中国介入影像与治疗学, 2023, 20(7): 390-394. DOI: 10.13929/j.issn.1672-8475.2023.07.002.
LIU M L, YUAN Y, LI M D, et al. MRI radiomics and clinical features combined models for prdicting effect of high-intensity focused ultrasound in treatment of uterine fibroids[J]. Chin J Interv Imag Ther, 2023, 20(7): 390-394. DOI: 10.13929/j.issn.1672-8475.2023.07.002.
[21]
中国医学装备协会磁共振应用专业委员会微创治疗学组. MR引导聚焦超声治疗子宫肌瘤中国专家共识[J]. 协和医学杂志, 2020, 11(5): 571-579. DOI: 10.3969/j.issn.1674-9081.2020.05.012.
China Consensus on MR-guided Focused Ultrasound for Uterine Fibroids. China consensus on MR-guided focused ultrasound for uterine fibroids[J]. Med J Peking Union Med Coll Hosp, 2020, 11(5): 571-579. DOI: 10.3969/j.issn.1674-9081.2020.05.012.
[22]
蒋雨, 黄小华, 秦石泽, 等. 基于增强MRI影像组学模型预测HIFU消融子宫肌瘤疗效的价值研究[J]. 临床放射学杂志, 2022, 41(11): 2095-2100. DOI: 10.13437/j.cnki.jcr.2022.11.008.
JIANG Y, HUANG X H, QIN S Z, et al. Study on the value of predicting the therapeutic effect of HIFU ablation of uterus myoma based on enhanced MRI radiomics model[J]. J Clin Radiol, 2022, 41(11): 2095-2100. DOI: 10.13437/j.cnki.jcr.2022.11.008.
[23]
曾朝强, 王晶, 张小明, 等. 基于多参数MRI对子宫肌瘤HIFU术后再干预风险预测模型的构建与评价[J]. 磁共振成像, 2022, 13(7): 68-74, 111. DOI: 10.12015/issn.1674-8034.2022.07.012.
ZENG C Q, WANG J, ZHANG X M, et al. Development and assessment of a novel nomogram based on multiple parameters MRI for predicting the risk of reintervention after high intensity focused ultrasound treatment of uterine leiomyoma[J]. Chin J Magn Reson Imag, 2022, 13(7): 68-74, 111. DOI: 10.12015/issn.1674-8034.2022.07.012.
[24]
肖杨, 廖凯兵, 施欣园, 等. ADC平均值及最小值在鉴别良、恶性四肢软组织肿瘤中的价值[J]. 放射学实践, 2021, 36(01): 112-116. DOI: 10.13609/j.cnki.1000-0313.2021.01.022.
XIAO Y, LIAO K B, SHI X Y, et al. Value of mean ADC and minimum ADC in identifying benign and malignant soft tissue tumors of extremities [J]. Radiol Pract, 2021, 36(01): 112-116. DOI: 10.13609/j.cnki.1000-0313.2021.01.022.
[25]
汤蕊嘉, 赵卫, 范宏杰, 等. 高强度聚焦超声治疗子宫肌瘤患者的 妊娠结局分析[J]. 实用放射学杂志, 2020, 36(9): 1446-1449. DOI: 10.3969/j.issn.1002-1671.2020.09.023.
TANG R J, ZHAO W, FAN H J, et al. Analysis of pregnancy outcome in patients with uterine fibroids treated with HIFU[J]. J Pract Radiol, 2020, 36(9): 1446-1449. DOI: 10.3969/j.issn.1002-1671.2020.09.023.
[26]
洪澜, 陈旺生, 杨舒盈, 等. 子宫动脉栓塞治疗子宫肌瘤远期疗效随访评价[J]. 实用妇产科杂志, 2009, 25(8): 481-483. DOI: 10.3969/j.issn.1003-6946.2009.08.015.
HONG L, CHEN W S, YANG S Y, et al. Long-term effects of uterine artery. embolization of uterine myoma[J]. J Pract Obstet Gynecol, 2009, 25(8): 481-483. DOI: 10.3969/j.issn.1003-6946.2009.08.015.
[27]
LEBLANG S D, HOCTOR K, STEINBERG F L. Leiomyoma shrinkage after MRI-guided focused ultrasound treatment: report of 80 patients[J]. AJR Am J Roentgenol, 2010, 194(1): 274-280. DOI: 10.2214/AJR.09.2842.
[28]
刘蓉华, 刘忠华. ROC曲线评价MIR-T_2WI信号强度比值、信号值、ADC对聚焦超声治疗子宫肌瘤效果的评估价值[J]. 中国CT和MRI杂志, 2022, 20(7): 126-128. DOI: 10.3969/j.issn.1672-5131.2022.07.042.
LIU R H, LIU Z H. Evaluated vale of ROC curve evaluation of MIR-T2WI signal intensity ratio, signal value and ADC on high intensity focused ultrasound in the treatment of uterine fibroids[J]. Chin J CT MRI, 2022(7): 126-128. DOI: 10.3969/j.issn.1672-5131.2022.07.042.
[29]
LIAO L, XU Y H, BAI J, et al. MRI parameters for predicting the effect of ultrasound-guided high-intensity focused ultrasound in the ablation of uterine fibroids[J]. Clin Radiol, 2023, 78(1): 61-69. DOI: 10.1016/j.crad.2022.09.112.
[30]
方磊, 方慧, 金利, 等. ADC最小值对外周带早期前列腺癌与慢性前列腺炎的鉴别诊断价值[J]. 磁共振成像, 2023, 14(7): 93-97. DOI: 10.12015/issn.1674-8034.2023.07.016.
FANG L, FANG H, JIN L, et al. The value of apparent diffusion coefficient minimum in differential diagnosis of early prostate cancer and chronic prostatitis in peripheral zone[J]. Chin J Magn Reson Imag, 2023, 14(7): 93-97. DOI: 10.12015/issn.1674-8034.2023.07.016.
[31]
ZHAO W P, CHEN J Y, CHEN W Z. Effect of biological characteristics of different types of uterine fibroids, as assessed with T2-weighted magnetic resonance imaging, on ultrasound-guided high-intensity focused ultrasound ablation[J]. Ultrasound Med Biol, 2015, 41(2): 423-431. DOI: 10.1016/j.ultrasmedbio.2014.09.022.
[32]
ZHANG W Y, HE M, HUANG G H, et al. A comparison of ultrasound-guided high intensity focused ultrasound for the treatment of uterine fibroids in patients with an anteverted uterus and a retroverted uterus[J]. Int J Hyperthermia, 2016, 32(6): 623-629. DOI: 10.1080/02656736.2016.1191680.
[33]
GONG C M, YANG B, SHI Y R, et al. Factors influencing the ablative efficiency of high intensity focused ultrasound (HIFU) treatment for adenomyosis: a retrospective study[J]. Int J Hyperthermia, 2016, 32(5): 496-503. DOI: 10.3109/02656736.2016.1149232.
[34]
LIU Z Q, GONG C M, LIU Y C, et al. Establishment of a scoring system for predicting the difficulty level of high-intensity focussed ultrasound ablation of uterine fibroids[J]. Int J Hyperthermia, 2018, 34(1): 77-86. DOI: 10.1080/02656736.2017.1325015.
[35]
王袁. 富于细胞型子宫平滑肌瘤的临床特点及术后复发相关研究[D]. 广州: 南方医科大学, 2020. DOI: 10.27003/d.cnki.gojyu.2020.000547.
WANG Y. Clinical characteristics and postoperative recurrence of cellular uterine leiomyoma[D].Guangzhou: Southern Medical University, 2020. DOI: 10.27003/d.cnki.gojyu.2020.000547.
[36]
杨笛, 朱雅馨, 王雪, 等. 不同病理类型子宫肌瘤3.0T磁共振扩散加权成像观察[J]. 中华医学杂志, 2016, 96(15): 1155-1159. DOI: 10.3760/cma.j.issn.0376-2491.2016.15.002.
YANG D, ZHU Y X, WANG X, et al. Diffusion-weighted imaging characteristics of uterine leiomyomas with different pathological subtypes at 3.0 T[J]. Natl Med J China, 2016, 96(15): 1155-1159. DOI: 10.3760/cma.j.issn.0376-2491.2016.15.002.

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