Breast cancer detection from ultrasound computed tomography imaging using radiomic analysis: in silico trial

IF 3.2 2区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

Medical physics Pub Date : 2025-02-28 DOI:10.1002/mp.17710

Andres Vargas, Nicole Hernandez, Ana B. Ramirez, Said Pertuz

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引用次数: 0

Abstract

Background

Ultrasound computed tomography (USCT) is an imaging modality currently under development for its clinical use in breast imaging. In order to justify clinical trials on imaging prototypes, further research is required to investigate uses and limitations of USCT.

Purpose

We investigate the potential of USCT for the detection of breast lesions through the computerized analysis of speed-of-sound (SOS) images of the breast.

Methods

We conducted an in silico study with a set of 116 virtual breast phantoms (VBPs). We simulated US acquisition and reconstructed 2D SOS slices of the breast via the full waveform inversion (FWI) technique. Subsequently, we conducted breast lesion detection based on computerized texture features (i.e., radiomic features) of the SOS slices. We compare the performance in cancer detection against radiomic analysis of mammograms in terms of the area under the curve (AUC) of the receiver operating characteristic (ROC) curve with 95% confidence intervals estimated using five-fold cross-validation. Statistical analysis involved the Wilcoxon rank-sum test to evaluate significant differences in detection scores, with a significance level of $p < 0.05$ . AUCs were compared using DeLong's test, and the significance level was adjusted with Bonferroni's correction to account for multiple comparisons.

Results

The AUC for lesion detection from reconstructed SOS images and mammography were 0.87 (95% CI: 0.81-0.94) and 0.77 (95% CI: 0.68-0.86), respectively. Detection of breast lesions using the multimodal approach combining SOS images and mammograms, yielded an AUC of 0.89 (95% CI: 0.83-0.95), with statistically significant differences with respect to the use of mammograms alone (p = 0.0112).

Conclusions

Our in silico experimental results demonstrate the feasibility of using USCT for breast lesion detection using fully automatic analysis of reconstructed SOS images. The multimodal approach, that combines radio-density and acoustic properties of the breast, outperforms the analysis using a single modality.

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利用放射学分析从超声计算机断层成像检测乳腺癌：计算机试验。

背景：超声计算机断层扫描（USCT）是一种目前正在发展的用于临床乳腺成像的成像方式。为了证明对成像原型进行临床试验是合理的，需要进一步研究USCT的用途和局限性。目的：我们通过对乳房声速（SOS）图像的计算机分析，探讨超声ct检测乳房病变的潜力。方法：我们对116个虚拟乳房幻影（VBPs）进行了一项计算机研究。我们模拟了美国采集，并通过全波形反演（FWI）技术重建了乳房的二维SOS切片。随后，我们基于SOS切片的计算机化纹理特征（即放射学特征）进行乳腺病变检测。我们根据受试者工作特征（ROC）曲线下面积（AUC）比较了癌症检测与乳房x线照片放射学分析的性能，并使用五倍交叉验证估计了95%的置信区间。统计学分析采用Wilcoxon秩和检验评价检测得分的显著性差异，显著性水平为p 0.05 $p。auc的比较采用DeLong检验，显著性水平采用Bonferroni校正进行调整，以考虑多重比较。结果：重建SOS图像和乳房x线检查病变的AUC分别为0.87 （95% CI: 0.81 ~ 0.94）和0.77 （95% CI: 0.68 ~ 0.86）。使用多模态方法结合SOS图像和乳房x线照片检测乳房病变，AUC为0.89 (95% CI: 0.83-0.95)，与单独使用乳房x线照片相比具有统计学意义（p = 0.0112）。结论：我们的计算机实验结果表明，通过对重建的SOS图像进行全自动分析，使用USCT进行乳房病变检测是可行的。多模态方法结合了乳房的无线电密度和声学特性，优于使用单一模态的分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Medical physics 医学-核医学

CiteScore

6.80

自引率

15.80%

发文量

660

审稿时长

1.7 months

期刊介绍： Medical Physics publishes original, high impact physics, imaging science, and engineering research that advances patient diagnosis and therapy through contributions in 1) Basic science developments with high potential for clinical translation 2) Clinical applications of cutting edge engineering and physics innovations 3) Broadly applicable and innovative clinical physics developments Medical Physics is a journal of global scope and reach. By publishing in Medical Physics your research will reach an international, multidisciplinary audience including practicing medical physicists as well as physics- and engineering based translational scientists. We work closely with authors of promising articles to improve their quality.