亞實性肺結(jié)節(jié)CT閾值分割：實性成分識別與定量
發(fā)布時間：2018-11-23 12:58
【摘要】：背景與目的在胸部計算機斷層掃描(computed tomography,CT)圖像上肺內(nèi)亞實性結(jié)節(jié)(subsolid nodule,SSN)是指純磨玻璃結(jié)節(jié)和部分實性結(jié)節(jié)。SSN實性成分的識別與定量對鑒別診斷,預(yù)測病理和評估預(yù)后具有重要價值,但目前缺乏公認且客觀的標準。對亞實性結(jié)節(jié)內(nèi)實性成分做CT體積定量的研究報告尚少。本研究旨在探究CT閾值分割法判斷SSN類型并定量其實性成分體積的閾值。方法共納入102例SSN。由觀察者1和觀察者2分別獨立對結(jié)節(jié)內(nèi)有無實性成分,即結(jié)節(jié)的類型(部分實性或純磨玻璃)進行主觀判斷,結(jié)果不一致時采納觀察者3的意見,由此確定出所有結(jié)節(jié)的類型并以此作為評估閾值分割法判斷SSN類型效能的參照標準。被判定為部分實性的結(jié)節(jié)由觀察者1和觀察者2分別獨立對其實性成分進行體積測量,測量時借助Auto Contour軟件包并輔以手動調(diào)整。以兩位觀察者所得實性成分體積的平均值作為評估閾值分割法定量SSN實性成分體積的參照標準。由觀察者1對全部結(jié)節(jié)進行閾值分割,步驟為首先采用Auto Contour軟件包對結(jié)節(jié)進行整體提取并記錄結(jié)節(jié)的整體體積,然后使用3D-color-ROI工具計算所獲結(jié)節(jié)內(nèi)不同CT值區(qū)間的體素體積。共設(shè)9個CT值區(qū)間,下限值(閾值)分別設(shè)為-500 HU、-450 HU、-400HU、-350 HU、-300HU、-250 HU、-200 HU、-160 HU、-130 HU,上限值均設(shè)為2000 HU,假定上述CT值區(qū)間的體素均為實性成分。計算閾值分割所獲實性成分體積與結(jié)節(jié)整體體積的比率(%)。以觀察者確定的結(jié)節(jié)類型為狀態(tài)變量,以體積比率為檢驗變量,繪制不同CT值區(qū)間判斷結(jié)節(jié)類型的受試者工作特征(receiver operating characteristic,ROC)曲線,得到曲線下面積(area under curve,AUC)。應(yīng)用DeLong檢驗篩選CT閾值分割判斷SSN類型的閾值。通過最大Youden指數(shù)得到確認結(jié)節(jié)存在實性成分的體積比率界限值。對閾值分割所得體積與實性成分體積參照標準之間進行配對Wilcoxon檢驗,篩選可用于實性成分體積定量的閾值。結(jié)果閾值為-250 HU時判斷亞實性結(jié)節(jié)類型的準確度最高(AUC=0.982),對應(yīng)體積比率界限值為1.10%,此時敏感度、特異度分別為100.0%、89.7%;閾值為-300 HU時判斷亞實性結(jié)節(jié)類型的準確度次之(AUC=0.977),對應(yīng)體積比率界限值為6.14%,此時敏感度、特異度分別為90.5%、94.9%。然而閾值-250 HU與閾值-350 HU、-300 HU、-200 HU、-160 HU、-130 HU在判斷亞實性結(jié)節(jié)類型上差異不顯著(P均0.05)。閾值為-250 HU、-300 HU時所得實性成分體積202.7mm~3(598.2 mm~3)、247.1 mm~3(696.0 mm~3)與參照標準199.5 mm~3(743.1 mm~3)間無顯著差異(P=0.1251、0.0613),而其他閾值所得實性成分體積均與參照標準間存在顯著差異(P均0.05)。結(jié)論本研究表明,CT閾值分割能夠可靠地對SSN的類型進行判斷并對其實性成分體積進行定量評估;閾值可設(shè)為-250 HU或-300 HU。
[Abstract]:Background & objective on chest computed tomography (computed tomography,CT) images, subsolid pulmonary nodules (subsolid nodule,SSN) are pure ground glass nodules and partial solid nodules. It is important to predict pathology and evaluate prognosis, but there is a lack of accepted and objective criteria. There are few studies on CT volume quantification of solid components in subsolid nodules. The purpose of this study was to explore the threshold value of CT threshold segmentation to determine the SSN type and to quantify the volume of the actual component. Methods 102 cases of SSN. were included Observer 1 and Observer 2 made independent subjective judgments on whether there were solid components in the nodules, that is, the types of nodules (partially solid or pure ground glass). When the results were inconsistent, the opinion of Observer 3 was adopted. The types of all nodules are determined and used as a reference criterion for evaluating the effectiveness of SSN type by threshold segmentation method. The nodules determined to be partially solid were measured independently by Observer 1 and Observer 2, respectively, with the help of Auto Contour software package and manual adjustment. The mean value of real component volume obtained by two observers is used as the reference criterion for evaluating the volume of SSN real component by threshold segmentation method. The threshold value of all the nodules was segmented by observer 1. The steps were as follows: firstly, the whole nodules were extracted by Auto Contour software package and the whole volume of the nodules was recorded. Then the volume of voxel in different CT values of the nodules was calculated by using the 3D-color-ROI tool. There are 9 CT ranges, and the lower limit (threshold) is -500 HU,-450 HU,-400HU,-350 HU,-300HU,-250 HU,-200 HU,-160 HU,-130 HU, and the upper limit is 2000 HU,. It is assumed that the voxels in the above CT interval are real components. Calculate the ratio of the solid component volume to the whole nodule volume obtained by threshold segmentation (%). Taking the nodular type determined by the observer as the state variable and the volume ratio as the test variable, the (receiver operating characteristic,ROC curves with different CT values to judge the nodule type were drawn, and the area under the curve (area under curve,AUC) was obtained. DeLong test was used to select the threshold value of CT to judge the threshold of SSN type. By using the maximum Youden exponent, the boundary value of the volume ratio is obtained to confirm the existence of solid components in the nodules. The matched Wilcoxon test was performed between the volume of real component and the reference standard of real component volume, and the threshold value for quantitative quantification of real component volume was screened. Results when the threshold was -250 HU, the accuracy (AUC=0.982) of subsolid nodules was the highest, and the threshold value of the corresponding volume ratio was 1.10. The sensitivity and specificity were 100.0 and 89.7, respectively. When the threshold was -300 HU, the accuracy (AUC=0.977) of subsolid nodules was the second, and the corresponding threshold value of volume ratio was 6.14. At this time, the sensitivity and specificity were 90.5 and 94.9, respectively. However, there was no significant difference between the threshold of-250 HU and the threshold of-350 HU,-300 HU,-200 HU,-160 HU,-130 HU in the classification of subsolid nodules. There was no significant difference between 202.7mm~3 (598.2 mm~3), 247.1 mm~3 (696.0 mm~3) and 199.5 mm~3 (743.1 mm~3) when the threshold was -250 HU,-300 HU. However, the volume of solid components obtained from other thresholds was significantly different from that of reference standard (P 0.05). Conclusion this study shows that CT threshold segmentation can reliably judge the type of SSN and quantitatively evaluate the volume of actual components, and the threshold can be set to -250 HU or -300 HU..
【學(xué)位授予單位】：天津醫(yī)科大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：R734.2;R730.44
本文編號：2351704
[Abstract]:Background & objective on chest computed tomography (computed tomography,CT) images, subsolid pulmonary nodules (subsolid nodule,SSN) are pure ground glass nodules and partial solid nodules. It is important to predict pathology and evaluate prognosis, but there is a lack of accepted and objective criteria. There are few studies on CT volume quantification of solid components in subsolid nodules. The purpose of this study was to explore the threshold value of CT threshold segmentation to determine the SSN type and to quantify the volume of the actual component. Methods 102 cases of SSN. were included Observer 1 and Observer 2 made independent subjective judgments on whether there were solid components in the nodules, that is, the types of nodules (partially solid or pure ground glass). When the results were inconsistent, the opinion of Observer 3 was adopted. The types of all nodules are determined and used as a reference criterion for evaluating the effectiveness of SSN type by threshold segmentation method. The nodules determined to be partially solid were measured independently by Observer 1 and Observer 2, respectively, with the help of Auto Contour software package and manual adjustment. The mean value of real component volume obtained by two observers is used as the reference criterion for evaluating the volume of SSN real component by threshold segmentation method. The threshold value of all the nodules was segmented by observer 1. The steps were as follows: firstly, the whole nodules were extracted by Auto Contour software package and the whole volume of the nodules was recorded. Then the volume of voxel in different CT values of the nodules was calculated by using the 3D-color-ROI tool. There are 9 CT ranges, and the lower limit (threshold) is -500 HU,-450 HU,-400HU,-350 HU,-300HU,-250 HU,-200 HU,-160 HU,-130 HU, and the upper limit is 2000 HU,. It is assumed that the voxels in the above CT interval are real components. Calculate the ratio of the solid component volume to the whole nodule volume obtained by threshold segmentation (%). Taking the nodular type determined by the observer as the state variable and the volume ratio as the test variable, the (receiver operating characteristic,ROC curves with different CT values to judge the nodule type were drawn, and the area under the curve (area under curve,AUC) was obtained. DeLong test was used to select the threshold value of CT to judge the threshold of SSN type. By using the maximum Youden exponent, the boundary value of the volume ratio is obtained to confirm the existence of solid components in the nodules. The matched Wilcoxon test was performed between the volume of real component and the reference standard of real component volume, and the threshold value for quantitative quantification of real component volume was screened. Results when the threshold was -250 HU, the accuracy (AUC=0.982) of subsolid nodules was the highest, and the threshold value of the corresponding volume ratio was 1.10. The sensitivity and specificity were 100.0 and 89.7, respectively. When the threshold was -300 HU, the accuracy (AUC=0.977) of subsolid nodules was the second, and the corresponding threshold value of volume ratio was 6.14. At this time, the sensitivity and specificity were 90.5 and 94.9, respectively. However, there was no significant difference between the threshold of-250 HU and the threshold of-350 HU,-300 HU,-200 HU,-160 HU,-130 HU in the classification of subsolid nodules. There was no significant difference between 202.7mm~3 (598.2 mm~3), 247.1 mm~3 (696.0 mm~3) and 199.5 mm~3 (743.1 mm~3) when the threshold was -250 HU,-300 HU. However, the volume of solid components obtained from other thresholds was significantly different from that of reference standard (P 0.05). Conclusion this study shows that CT threshold segmentation can reliably judge the type of SSN and quantitatively evaluate the volume of actual components, and the threshold can be set to -250 HU or -300 HU..
【學(xué)位授予單位】：天津醫(yī)科大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：R734.2;R730.44
【參考文獻】
相關(guān)期刊論文 前1條
1 王群;蔣偉;奚俊杰;;肺部多發(fā)磨玻璃影的外科治療[J];中國肺癌雜志;2016年06期
，本文編號：2351704
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