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使用自动骨减法软件对乳腺癌患者骨盆骨进行纵向计算机断层扫描监测。

Longitudinal Computed Tomography Monitoring of Pelvic Bones in Patients With Breast Cancer Using Automated Bone Subtraction Software.

作者信息

Horger Marius, Thaiss Wolfgang Maximilian, Wiesinger Benjamin, Ditt Hendrik, Fritz Jan, Nikolaou Konstantin, Kloth Christopher

机构信息

From the *Department of Diagnostic and Interventional Radiology, Eberhard-Karls-University, Tübingen; †Siemens AG, Healthcare Sector Imaging and Therapy Division, Forchheim, Germany; and ‡Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD.

出版信息

Invest Radiol. 2017 Feb;52(2):288-294. doi: 10.1097/RLI.0000000000000343.

Abstract

OBJECTIVE

The aim of this study was to optimize computed tomography (CT) surveillance of skeletal metastases in patients with breast cancer through the use of osseous subtraction maps between baseline and follow-up examinations created by a novel software algorithm. The new postprocessing algorithm segments the original bone followed by image intensity-based rigid alignment creating gray-shaded maps that highlight focal or diffuse loss or increase in bone attenuation.

MATERIALS AND METHODS

Institutional review board was obtained for this retrospective data evaluation. A total of 33 consecutive patients (31 female; 2 male; mean age, 59.13 ± 12.68 years; range, 32-81 years) with breast cancer were included, who underwent 143 standardized baseline and follow-up CT examinations between February 2014 and June 2016. We classified bone metastases into lytic, sclerotic, and mixed osseous lesions. Any new osteolysis inside a known sclerotic lesion and enlargement of pre-existing sclerotic lesions were considered to represent progressive disease (PD), whereas no change was classified as stable disease (SD). Results were compared additionally with the course of the disease considering the entire skeleton and other involved organs. Software-created automated bone subtraction maps were compared with conventional CT interpretations of axial 5-mm and coronal 1-mm reformatted images. Region of interest measurements were used to quantify new lesions. Results were validated by clinical and CT follow-up. Reading time was evaluated.

RESULTS

Skeletal metastases were present in 17/33 (51%) patients (9 sclerotic, 2 lytic, 6 mixed) at baseline. The use of bone subtraction maps resulted in an overall change of response classification into PD in 9/33 (8.1%) patients. Compared with conventional CT evaluation, the bone subtraction maps disclosed 123 new or enlarging sclerotic and 32 new lytic metastases in 23/33 (30.9%) examinations. Mean attenuation of new bone lesions (sclerotic or lytic) significantly increased or decreased (P < 0.01) in all patients. Bone attenuation in pelvic areas without evident metastatic disease significantly increased in patients with PD (P = 0.019), whereas there was no change in SD (P = 0.076). Lesion-based sensitivity, specificity, accuracy, positive predictive values, and negative predictive values were 98.7%, 79.5%, 94.5%, 95.1%, and 94.5%, respectively. Interobserver agreement was good (κ = 0.80; P = 0.077). Reading time was significantly faster for the bone subtraction maps versus 5-mm axial images (P < 0.001).

CONCLUSIONS

Longitudinal bone subtraction maps increase the accuracy and efficiency of CT diagnosis of skeletal metastases in patients with breast cancer.

摘要

目的

本研究旨在通过使用一种新型软件算法生成的基线和随访检查之间的骨减法图,优化乳腺癌患者骨骼转移瘤的计算机断层扫描(CT)监测。新的后处理算法先分割原始骨骼,然后基于图像强度进行刚性配准,生成突出显示骨密度局灶性或弥漫性降低或增加的灰度图。

材料与方法

本回顾性数据评估获得了机构审查委员会的批准。纳入了33例连续的乳腺癌患者(31例女性;2例男性;平均年龄59.13±12.68岁;范围32 - 81岁),这些患者在2014年2月至2016年6月期间接受了143次标准化的基线和随访CT检查。我们将骨转移瘤分为溶骨性、硬化性和混合性骨病变。已知硬化性病变内的任何新骨溶解以及先前存在的硬化性病变增大均被视为疾病进展(PD),而无变化则分类为疾病稳定(SD)。此外,将结果与考虑整个骨骼和其他受累器官的疾病进程进行比较。将软件生成的自动骨减法图与轴向5毫米和冠状1毫米重组图像的传统CT解读进行比较。使用感兴趣区域测量来量化新病变。结果通过临床和CT随访进行验证。评估了阅片时间。

结果

基线时,17/33(51%)的患者存在骨骼转移瘤(9例硬化性、2例溶骨性、6例混合性)。使用骨减法图导致9/33(8.1%)的患者反应分类总体变为PD。与传统CT评估相比,骨减法图在23/33(30.9%)的检查中发现了123个新的或增大的硬化性转移瘤和32个新的溶骨性转移瘤。所有患者中新骨病变(硬化性或溶骨性)的平均衰减显著增加或降低(P < 0.01)。PD患者中无明显转移瘤的盆腔区域骨密度显著增加(P = 0.019),而SD患者中无变化(P = 0.076)。基于病变的敏感性、特异性、准确性、阳性预测值和阴性预测值分别为98.7%、79.5%、94.5%、95.1%和94.5%。观察者间一致性良好(κ = 0.80;P = 0.077)。与5毫米轴向图像相比,骨减法图的阅片时间显著更快(P < 0.001)。

结论

纵向骨减法图提高了乳腺癌患者骨骼转移瘤CT诊断的准确性和效率。

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