Evidence map›Paper›PMID 40790177›Full record

ArticleBMC medical imaging2025

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

Sina Wang, Zeyuan Xu, Bowen Zheng, Hui Zeng, Derun Pan, Mengwei Ma, Weiguo Chen, Genggeng Qin

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Article in BMC medical imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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8 authors.

Sina Wang *Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, PR China.ORCID 0000-0002-2159-7921
Zeyuan Xu *Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, PR China.ORCID 0000-0002-9899-778X
Bowen ZhengDepartment of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, PR China.ORCID 0000-0001-8653-8060
Hui ZengDepartment of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, PR China.ORCID 0000-0002-3715-8317
Derun PanDepartment of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, PR China.ORCID 0000-0001-7147-3970
Mengwei MaDepartment of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, PR China.ORCID 0000-0002-7261-0372
Weiguo ChenDepartment of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, PR China. chen1999@smu.edu.cn.ORCID 0000-0003-1552-0511
Genggeng QinDepartment of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, PR China. zealotq@smu.edu.cn.ORCID 0000-0002-7563-3924

Funding

Clinical Research Program of Nanfang Hospital, Southern Medical University 2019CR003President's Fund of Nanfang Hospital, Southern Medical University 2023B049Science and Technology Program of Guangdong Province, China 2024A1111120015the National Natural Science Foundation of China 82171929Wu Jieping Medical Foundation 320.6750.2021-06-36
6 · The paper itself

Abstract

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

methodsA 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.

resultsOverall, 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.

conclusionThe 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.

Indexed as

Breast NeoplasmsMammographyRadiographic Image Interpretation, Computer-AssistedAgedFemaleHumansMiddle AgedRetrospective StudiesBreastCraniocaudalImage matchingMammographyMediolateral oblique

Identifiers

PMID40790177
PMCPMC12337522

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