北京生物醫(yī)學(xué)工程

基于經(jīng)驗(yàn)?zāi)B(tài)分解的超聲零差K成像評(píng)估肝纖維化研究

Ultrasonic evaluation of hepatic fibrosis with homodyned K imaging based on empirical mode decomposition

作者：張奇宇吳水才崔博翔周著黃

單位：北京工業(yè)大學(xué)環(huán)境與生命學(xué)部（北京 100124） 臺(tái)灣長庚大學(xué)醫(yī)學(xué)院(中國臺(tái)灣桃園  33302) 通信作者：周著黃。副研究員。E-mail: [email protected]

關(guān)鍵詞：肝纖維化；超聲；背散射；經(jīng)驗(yàn)?zāi)B(tài)分解；零差K分布

分類號(hào)：R318.04

出版年·卷·期（頁碼）：2022·41·2（125-133）

摘要：

目的為提高超聲零差K成像評(píng)估肝纖維化的性能，提出基于經(jīng)驗(yàn)?zāi)B(tài)分解的超聲背散射零差K成像評(píng)估肝纖維化方法，利用經(jīng)驗(yàn)?zāi)B(tài)分解技術(shù)，消除肝實(shí)質(zhì)等噪聲信號(hào)對(duì)肝纖維化信號(hào)的影響。方法首先，將采集到的43例臨床肝纖維化的超聲背散射信號(hào)(F0 = 14, F1 = 10, F2 = 6, F3 = 2, F4 = 11）進(jìn)行經(jīng)驗(yàn)?zāi)B(tài)分解，然后分別將分解后的第一本征模態(tài)函數(shù)和第二本征模態(tài)函數(shù)經(jīng)包絡(luò)檢測(cè)、滑動(dòng)窗口、零差K模型參數(shù)估算等處理，計(jì)算得到感興趣區(qū)域內(nèi)的零差K模型參數(shù)k和α矩陣，通過掃描變換得到零差K參數(shù)圖像，最后采用參數(shù)k和α對(duì)肝纖維化進(jìn)行評(píng)估。結(jié)果采用經(jīng)驗(yàn)?zāi)B(tài)分解技術(shù)提高了超聲零差K成像診斷肝纖維化的性能。參數(shù)k在診斷肝纖維化≥F1即有無肝纖維化時(shí)提高較為明顯，平均受試者工作特征曲線下面積提高至0.68，參數(shù)α在診斷肝纖維化程度≥F1時(shí)，平均受試者工作特征曲線下面積提高至0.82。結(jié)論經(jīng)驗(yàn)?zāi)B(tài)分解技術(shù)有效減少了肝實(shí)質(zhì)等非目標(biāo)背散射信號(hào)對(duì)肝纖維信號(hào)的影響，提高了超聲零差K成像檢測(cè)肝纖維化的性能，并且在判別有無肝纖維化時(shí)性能最佳；在肝纖維化評(píng)估效果方面，參數(shù)α優(yōu)于參數(shù)k。

Objective To improve the performance of ultrasound homodyned K imaging in the evaluation of liver fibrosis, in this study, ultrasonic backscattering homodyned K imaging based on empirical mode decomposition was proposed for assessment of liver fibrosis. The empirical mode decomposition technique was used to eliminate the influence of noise signals such as liver parenchyma on hepatic fibrosis signals. The effect of liver fibrosis assessment before and after empirical mode decomposition was compared. Methods The ultrasonic backscattering signals collected from 43 cases of clinical liver fibrosis (F0 = 14, F1 = 10, F2 = 6, F3 = 2, F4 = 11) were decomposed by empirical mode decomposition. Then, the decomposed first intrinsic mode function and second intrinsic mode function signals were processed by envelope detection, sliding window, and homodyned K model parameter estimation. Thus, the homodyned K model parameters k and α matrices were estimated within the regions of interest. Finally, the homodyned K parametric image was obtained by digital scan conversion, Finally, parameters k and α were used for evaluation of liver fibrosis. Results The results showed that the performance of ultrasonic homodyned K imaging in the diagnosis of liver fibrosis was improved by using the empirical mode decomposition technique. Parameter k significantly increased the performance when diagnosing liver fibrosis ≥ F1, and the average area under the receiver operating characteristic curve increased to 0.68. Parameter α yielded an average AUC of 0.82 when diagnosing liver fibrosis ≥ F1. Conclusions The empirical mode decomposition technique effectively reduced the influence of non-target backscattering signals such as liver parenchyma on liver fiber signals. It improved the performance of ultrasonic homodyned K imaging in detecting liver fibrosis, and had the best performance in determining whether there is liver fibrosis. Parameter α was better than parameter k in the ultrasonic evaluation of liver fibrosis.

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