分析乳腺超声报告的主要质量问题及主要原因，识别影响报告质量的关键环节，并探讨各项质量控制指标对乳腺影像报告与数据系统（BI-RADS）分类诊断准确率的影响。

本研究为多中心横断面调查，回顾性收集2024年1月1日至6月30日期间进行乳腺超声检查的乳腺超声报告。以病理结果为金标准判定诊断准确率。纳入来自13个省、自治区、直辖市1237家医疗机构的16 434份乳腺超声报告。从报告完整、存图合格、描述-结论匹配、图文匹配4个维度对报告进行系统评价。采用χ²检验和多因素Logistic回归分析各质控指标与BI-RADS分类诊断准确率的关系，采用柏拉图分析法识别其主要原因。

16 434份报告中，报告完整率为64.0%，存图合格率为75.3%，描述-结论匹配率为91.0%，图文匹配率为99.7%，BI-RADS分类准确率为75.9%。多因素回归分析显示，报告完整（OR=1.081，95%CI：1.002~1.165，P=0.044）、存图合格（OR=1.116，95%CI：1.027~1.212，P=0.010）、描述-结论匹配（OR=1.212，95%CI：1.074~1.367，P=0.002）是BI-RADS分类诊断准确率的独立影响因素，而图文匹配未显示出显著影响（P=0.452）。柏拉图分析显示，报告不完整的主要原因为病灶后方回声（21.49%）、方向（21.03%）、钙化（19.56%）、位置（16.54%）、形状（9.44%）描述缺失；存图不合格的主要原因为无体标（53.80%）、无彩色多普勒成像图像（19.03%）、可疑恶性征象存图不全（9.21%）；描述-结论不匹配的主要原因为描述中存在矛盾或歧义（84.03%）。

乳腺超声报告的完整性、存图规范性及描述-结论的匹配度是BI-RADS分类诊断准确率的独立影响因素。临床可针对病灶关键声像图特征（后方回声、方向、钙化）描述缺失、体标缺失等核心缺陷进行质量改进，以提升我国乳腺超声的整体诊断效能。

To analyze the major quality issues and their underlying causes in breast ultrasound reports in China, identify key factors affecting report quality, and investigate the association between various quality control indicators and the diagnostic accuracy of breast imaging reporting and data system (BI-RADS) classification, so as to provide evidence-based support for improving ultrasound report quality.

This multicenter cross-sectional study retrospectively collected breast ultrasound reports from patients who underwent breast ultrasound between January 1, 2024 and June 30, 2024. Pathological results served as the gold standard for diagnostic accuracy. A total of 16434 breast ultrasound reports from 1237 medical institutions across 13 provinces were included. Reports were systematically evaluated from four dimensions: report completeness, image acquisition adequacy, description-conclusion consistency, and image-text consistency. Chi-square tests and multivariate logistic regression were used to analyze the association between each quality control indicator and the diagnostic accuracy of BI-RADS classification. Pareto analysis was applied to identify the primary causes of problems.

Among the 16434 reports, the rate of report completeness was 64.0%, image acquisition adequacy was 75.3%, description-conclusion consistency was 91.0%, image-text consistency was 99.7%, and BI-RADS classification accuracy was 75.9%. Multivariate logistic regression showed that report completeness (OR=1.081, 95%CI: 1.002 – 1.165, P=0.044), image acquisition adequacy (OR=1.116, 95%CI: 1.027 – 1.212, P=0.010), and description-conclusion consistency (OR=1.212, 95%CI: 1.074 – 1.367, P=0.002) were independent influencing factors for the diagnostic accuracy of BI-RADS classification, whereas image-text consistency had no significant effect (P=0.452). Pareto analysis identified the main causes of report incompleteness as missing descriptions of posterior features (21.49%), orientation (21.03%), calcifications (19.56%), location (16.54%), and shape (9.44%). The primary causes of inadequate image acquisition were the lack of body markers (53.80%), absence of CDFI images (19.03%), and incomplete storage of suspicious malignant signs (9.21%). The main cause of description-conclusion inconsistency was contradictions or ambiguities in descriptions (84.03%).

The completeness of breast ultrasound reports, adequacy of image acquisition, and consistency between descriptions and conclusions directly influence the diagnostic accuracy of BI-RADS classification. To address the core defects, particularly missing descriptions of key sonographic features such as posterior features, orientation, and calcifications, as well as the lack of body markers, future efforts should focus on strengthening relevant quality control measures to improve the overall diagnostic efficacy of breast ultrasound in China.