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扩散加权成像用于提高乳腺磁共振成像筛查的诊断性能:表观扩散系数定量方法及临界值的影响

Diffusion weighted imaging for improving the diagnostic performance of screening breast MRI: impact of apparent diffusion coefficient quantitation methods and cutoffs.

作者信息

Biswas Debosmita, Hippe Daniel S, Winter Andrea M, Li Isabella, Rahbar Habib, Partridge Savannah C

机构信息

Department of Radiology, School of Medicine, University of Washington, Seattle, WA, United States.

Department of Bioengineering, College of Engineering, University of Washington, Seattle, WA, United States.

出版信息

Front Oncol. 2024 Dec 20;14:1437506. doi: 10.3389/fonc.2024.1437506. eCollection 2024.

DOI:10.3389/fonc.2024.1437506
PMID:39759131
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11695236/
Abstract

INTRODUCTION

Diffusion weighted MRI (DWI) has emerged as a promising adjunct to reduce unnecessary biopsies prompted by breast MRI through use of apparent diffusion coefficient (ADC) measures. The purpose of this study was to investigate the effects of different lesion ADC measurement approaches and ADC cutoffs on the diagnostic performance of breast DWI in a high-risk MRI screening cohort to identify the optimal approach for clinical incorporation.

METHODS

Consecutive screening breast MRI examinations (August 2014-Dec 2018) that prompted a biopsy for a suspicious breast lesion (BI-RADS 4 or 5) were retrospectively evaluated. On DWI, ADC (b=0/100/600/800s/mm) measures were calculated with three different techniques for defining lesion region-of-interest (ROI; single slice('2D'), whole volume('3D') and lowest ADC region('hotspot')). An optimal data-derived ADC cutoff for each technique was retrospectively identified to reduce benign biopsies while avoiding any false negatives, inherently producing cutoffs with 100% sensitivity in this particular cohort. Further, diagnostic performance of these measures was validated using two prespecified ADC cutoffs: 1.53x10mm/s from the ECOG-ACRIN A6702 trial and 1.30x10mm/s from the international EUSOBI group. Diagnostic performance was compared between ADC maps generated with 2(0/800s/mm) and 4(0/100/600/800s/mm) b-values. Benign biopsy reduction rate was calculated (number of benign lesions with ADC >cutoff)/(total number of benign lesions).

RESULTS

137 suspicious lesions (in 121 women, median age 44 years [range, 20-75yrs]) were detected on contrast-enhanced screening breast MRI and recommended for biopsy. Of those, 30(21.9%) were malignant and 107(78.1%) were benign. Hotspot ADC measures were significantly lower (p<0.001) than ADCs from both 2D and 3D ROI techniques. Applying the optimal data-derived ADC cutoffs resulted in comparable reduction in benign biopsies across ROI techniques (range:16.8% -17.8%). Applying the prespecified A6702 and EUSOBI cutoffs resulted in benign biopsy reduction rates of 11.2-19.6%(with 90.0-100% sensitivity) and 36.4-51.4%(with 70.0-83.3% sensitivity), respectively, across ROI techniques. ADC measures and benign biopsy reduction rates were similar when calculated with only 2 b-values (0,800 s/mm) versus all 4 b-values.

DISCUSSION

Our findings demonstrate that with appropriate ADC thresholds, comparable reduction in benign biopsies can be achieved using lesion ADC measurements computed from a variety of approaches. Choice of ADC cutoff depends on ROI approach and preferred performance tradeoffs (biopsy reduction vs sensitivity).

摘要

引言

扩散加权磁共振成像(DWI)已成为一种有前景的辅助手段,可通过使用表观扩散系数(ADC)测量来减少乳腺MRI引发的不必要活检。本研究的目的是在高危MRI筛查队列中,研究不同病变ADC测量方法和ADC临界值对乳腺DWI诊断性能的影响,以确定临床应用的最佳方法。

方法

回顾性评估2014年8月至2018年12月期间因可疑乳腺病变(BI-RADS 4或5)而进行活检的连续乳腺MRI筛查检查。在DWI上,使用三种不同技术计算ADC(b=0/100/600/800s/mm²)测量值,以定义病变感兴趣区(ROI;单层(“2D”)、全容积(“3D”)和最低ADC区域(“热点”))。回顾性确定每种技术的最佳数据衍生ADC临界值,以减少良性活检,同时避免任何假阴性,在此特定队列中固有地产生具有100%敏感性的临界值。此外,使用两个预先指定的ADC临界值验证这些测量的诊断性能:ECOG-ACRIN A6702试验中的1.53×10⁻³mm²/s和国际EUSOBI组中的1.30×10⁻³mm²/s。比较使用2个(0/800s/mm²)和4个(0/100/600/800s/mm²)b值生成的ADC图之间的诊断性能。计算良性活检减少率(ADC>临界值的良性病变数量)/(良性病变总数)。

结果

在对比增强乳腺MRI筛查中检测到137个可疑病变(121名女性,中位年龄44岁[范围,20-75岁])并建议进行活检。其中,30个(21.9%)为恶性,107个(78.1%)为良性。热点ADC测量值显著低于2D和3D ROI技术的ADC值(p<0.001)。应用最佳数据衍生ADC临界值导致各ROI技术的良性活检减少程度相当(范围:16.8%-17.8%)。应用预先指定的A6702和EUSOBI临界值导致各ROI技术的良性活检减少率分别为11.2%-19.6%(敏感性为90.0%-100%)和36.4%-51.4%(敏感性为70.0%-83.3%)。仅使用2个b值(0,800 s/mm²)与使用所有4个b值计算时,ADC测量值和良性活检减少率相似。

讨论

我们的研究结果表明,使用适当的ADC阈值,通过各种方法计算的病变ADC测量值可实现相当程度的良性活检减少。ADC临界值的选择取决于ROI方法和首选的性能权衡(活检减少与敏感性)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5ca/11695236/b238c6e97c9a/fonc-14-1437506-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5ca/11695236/7bcc4b2745ab/fonc-14-1437506-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5ca/11695236/4757436df55a/fonc-14-1437506-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5ca/11695236/6528cdc680cc/fonc-14-1437506-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5ca/11695236/b238c6e97c9a/fonc-14-1437506-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5ca/11695236/7bcc4b2745ab/fonc-14-1437506-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5ca/11695236/4757436df55a/fonc-14-1437506-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5ca/11695236/6528cdc680cc/fonc-14-1437506-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5ca/11695236/b238c6e97c9a/fonc-14-1437506-g004.jpg

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