Improvement in matching lesions in dual-view mammograms using a geometric model.

IF 3.2 3区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Sina Wang, Zeyuan Xu, Bowen Zheng, Hui Zeng, Derun Pan, Mengwei Ma, Weiguo Chen, Genggeng Qin
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引用次数: 0

Abstract

Objectives: To evaluate the effectiveness of a geometric model (GM) as an adjunctive tool for radiologists to match lesions between craniocaudal (CC) and mediolateral (MLO) views.

Methods: A retrospective study was conducted on 711 patients who underwent mammography from January 2016 to August 2018. Two senior radiologists used bounding boxes to delineate lesions as the reference standard, calculated the absolute error (the shortest distance from the lesion center to the predicted curve) of GM, and compared it with the annular band (AB) and straight strip (SS) methods. Four radiologists of varying seniority levels were tasked with localizing the corresponding lesion in MLO view using a bounding box, based on the given lesion in CC views, and recording reading time per case with or without GM assistance. The Dice coefficient was used to evaluate the overlap between the bounding box and the reference standard.

Results: Overall, 499 calcification and 212 mass pairs were evaluated. GM outperformed both AB and SS, yielding a median absolute error of 3.03 mm (IQR 1.45-5.55 mm) versus 5.78 mm (IQR 2.44-10.71 mm) for AB and 4.59 mm (IQR 1.91-8.19 mm) for SS (P < 0.001). With GM assistance, all four radiologists achieved improved Dice coefficients and reduced reading times (all P  < 0.001). Stratified analysis by lesion conspicuity demonstrated that GM assistance significantly enhanced Dice coefficients for all radiologists in the low-conspicuity group and improved matching consistency for junior radiologists.

Conclusion: The geometric model holds substantial promise as a valuable tool to assist radiologists in more effectively localizing lesions in ipsilateral mammograms, thereby potentially enhancing diagnostic accuracy and efficiency.

使用几何模型在双视图乳房x线照片中匹配病变的改进。
目的:评估几何模型(GM)作为放射科医生匹配颅侧(CC)和中外侧(MLO)视图之间病变的辅助工具的有效性。方法:对2016年1月至2018年8月711例乳腺x光检查患者进行回顾性研究。两位资深放射科医师以边界框法圈定病灶为参考标准,计算GM的绝对误差(病灶中心到预测曲线的最短距离),并与环形带法(AB)和直条法(SS)进行比较。四名不同资历级别的放射科医生的任务是根据CC视图中给定的病变,使用边界框在MLO视图中定位相应的病变,并记录每个病例在有或没有GM辅助的情况下的阅读时间。Dice系数用于评价边界框与参考标准之间的重叠程度。结果:总共评估了499个钙化和212个质量对。GM优于AB和SS,平均绝对误差为3.03 mm (IQR 1.45-5.55 mm),而AB为5.78 mm (IQR 2.44-10.71 mm), SS为4.59 mm (IQR 1.91-8.19 mm)。(P结论:几何模型作为一种有价值的工具,有望帮助放射科医生在同侧乳房x线照片中更有效地定位病变,从而潜在地提高诊断的准确性和效率。
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来源期刊
BMC Medical Imaging
BMC Medical Imaging RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
4.60
自引率
3.70%
发文量
198
审稿时长
27 weeks
期刊介绍: BMC Medical Imaging is an open access journal publishing original peer-reviewed research articles in the development, evaluation, and use of imaging techniques and image processing tools to diagnose and manage disease.
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