Suppr超能文献

使用参考方法校正的自然T值进行K值计算以诊断乳腺癌

K Calculation Using Reference Method Corrected Native T for Breast Cancer Diagnosis.

作者信息

Negi Pradeep Singh, Mehta Shashi Bhushan, Jena Amarnath, Rana Prerana

机构信息

PET Suite (Indraprastha Apollo Hospitals and House of Diagnostics), Department of Molecular Imaging and Nuclear Medicine, Indraprastha Apollo Hospitals, New Delhi, India.

Department of Physics, Vivekananda Global University, Jaipur, Rajasthan, India.

出版信息

J Med Phys. 2023 Jan-Mar;48(1):19-25. doi: 10.4103/jmp.jmp_90_22. Epub 2023 Apr 18.

Abstract

PURPOSE

The objective of the study is to use multiple tube phantoms to generate correction factor at different spatial locations for each breast coil cuff to correct the native T value in the corresponding spatial location of the breast lesion. The corrected T value was used to compute K and analyze its diagnostic accuracy in the classification of target condition, i.e., breast tumors into malignant and benign.

MATERIALS AND METHODS

Both phantom study (external reference) and patient's studies were acquired on simultaneous positron emission tomography/magnetic resonance imaging (PET/MRI) Biograph molecular magnetic resonance (mMR) system using 4 channel mMR breast coil. The spatial correction factors derived using multiple tube phantom were used for a retrospective analysis of dynamic contrast-enhanced (DCE) MRI data of 39 patients with a mean age of 50 years (31-77 years) having 51 enhancing breast lesions.

RESULTS

Corrected and non-corrected receiver operating characteristic (ROC) curve analysis revealed a mean K value of 0.64 min and 0.60 min, respectively. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy for non-corrected data were 86.21%, 81.82%, 86.20%, 81.81%, and 84.31%, respectively, and for corrected data were 93.10%, 86.36%, 90%, 90.47%, and 90.20% respectively. The area under curve (AUC) of corrected data was improved to 0.959 (95% confidence interval [CI] 0.862-0.994) from 0.824 (95% CI 0.694-0.918) of non-corrected data, and for NPV, it was improved to 90.47% from 81.81%, respectively.

CONCLUSION

T values were normalized using multiple tube phantom which was used for computation of K. We found significant improvement in the diagnostic accuracy of corrected K values that results in better characterization of breast lesions.

摘要

目的

本研究的目的是使用多管体模为每个乳腺线圈套在不同空间位置生成校正因子,以校正乳腺病变相应空间位置的原始T值。校正后的T值用于计算K值,并分析其在目标疾病(即乳腺肿瘤良恶性分类)诊断中的准确性。

材料与方法

体模研究(外部参考)和患者研究均在使用4通道mMR乳腺线圈的同时正电子发射断层扫描/磁共振成像(PET/MRI)Biograph分子磁共振(mMR)系统上进行。使用多管体模得出的空间校正因子用于对39例平均年龄50岁(31 - 77岁)、有51个强化乳腺病变的患者的动态对比增强(DCE)MRI数据进行回顾性分析。

结果

校正后和未校正的受试者操作特征(ROC)曲线分析显示,平均K值分别为0.64分钟和0.60分钟。未校正数据的敏感性、特异性、阳性预测值(PPV)、阴性预测值(NPV)和总体准确率分别为86.21%、81.82%、86.20%、81.81%和84.31%,校正后数据的相应值分别为93.10%、86.36%、90%、90.47%和90.20%。校正后数据的曲线下面积(AUC)从未校正数据的0.824(95%置信区间[CI] 0.694 - 0.918)提高到0.959(95% CI 0.862 - 0.994),NPV从81.81%提高到90.47%。

结论

使用多管体模对T值进行标准化,用于计算K值。我们发现校正后的K值在诊断准确性方面有显著提高,从而能更好地对乳腺病变进行特征描述。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e8a/10277302/b19e244c6775/JMP-48-19-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验