Application of PDSA cycle-based O-RADS classification in quality control of ultrasonic diagnosis of ovarian tumors

doi:10.3877/cma.j.issn.1672-6448.2025.05.005

Abstract

Abstract:

Objective

To assess the clinical utility of the Ovarian-Adnexal Reporting and Data System (O-RADS) in ultrasound diagnosis of ovarian tumors and its impact on core quality metrics using the Plan-Do-Study-Act (PDSA) cycle framework.

Methods

We retrospectively analyzed 1790 ovarian tumor cases from Chongqing Maternal and Child Health Hospital (2021-2024), comparing pre-implementation(2021-2022, n=858) and post-implementation (2023-2024, n=932) cohorts following O-RADS adoption.The PDSA intervention addressed three baseline deficiencies: inconsistent terminology (28.79%),missing key imaging planes (27.04%), and diagnostic uncertainty (13.98%), with targets set for ＞95%achievement in standardization, completeness, and diagnostic clarity.Implementation involved O-RADSaligned terminology, standardized imaging protocols, and structured reporting templates.Post-intervention quality metrics were statistically compared using χ² tests.

Results

Standardized ultrasound diagnosis for ovarian tumors significantly improved quality control metrics, with reporting rates, image completeness,and diagnostic certainty reaching 95.06%, 97.5%, and 95.17%, respectively—all exceeding improvement targets.These values represent statistically significant increases of 23.85%, 24.54%, and 9.15% compared to baseline measurements (χ²=185.66, 220.79, and 44.77, respectively, P＜0.001 for all comparisons).

Conclusion

The systematic application of PDSA cycle management combined with O-RADS classification significantly improves the standardization of ultrasound diagnosis for ovarian tumors, validating the model’s efficacy in single-disease ultrasound quality control.

Key words: PDSA cycle, Single disease, Ultrasound, Quality control

Chenchen Xie, Jing Tang, Yanli Hu, Qian Ran, Chunmei Xiao, Suzhen Ran. Application of PDSA cycle-based O-RADS classification in quality control of ultrasonic diagnosis of ovarian tumors[J]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2025, 22(05): 408-413.

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URL: https://chaosheng.cma-cmc.com.cn/EN/10.3877/cma.j.issn.1672-6448.2025.05.005

https://chaosheng.cma-cmc.com.cn/EN/Y2025/V22/I05/408

Figures/Tables 4

References 19

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主要问题	病例数	占比（%）
描述性术语差异	247	28.79
血流分型不规范（未标注 “0 型 / Ⅰ 型 / Ⅱ 型” 血流分布）	129	15.03
未使用标准形态学术语（如将 “多房囊性” 错误描述为 “混合性包块”）	86	10.02
未描述关键特征（如 “壁立结节征”“云雾状低回声” 等）	32	3.73
关键切面缺失	232	27.04
未记录肿瘤内部结构切面（如分隔厚度、实性区范围、乳头状突起）	172	20.05
遗漏血流信号切面（未保存多普勒血流图像）	43	5.01
未联合经腹与经阴道 / 直肠扫查（肿瘤全貌显示不全）	17	1.98
诊断模糊性	120	13.98
未明确分类（如未标注肿瘤类型或 “良性 / 交界性 / 恶性”）	74	8.62
使用非确定性词汇（如 “性质待查”“不除外恶性”）	30	3.50
未结合临床信息（如未标注绝经状态）	16	1.86

主要问题	病例数	占比（%）
描述性术语差异	247	28.79
血流分型不规范（未标注 “0 型 / Ⅰ 型 / Ⅱ 型” 血流分布）	129	15.03
未使用标准形态学术语（如将 “多房囊性” 错误描述为 “混合性包块”）	86	10.02
未描述关键特征（如 “壁立结节征”“云雾状低回声” 等）	32	3.73
关键切面缺失	232	27.04
未记录肿瘤内部结构切面（如分隔厚度、实性区范围、乳头状突起）	172	20.05
遗漏血流信号切面（未保存多普勒血流图像）	43	5.01
未联合经腹与经阴道 / 直肠扫查（肿瘤全貌显示不全）	17	1.98
诊断模糊性	120	13.98
未明确分类（如未标注肿瘤类型或 “良性 / 交界性 / 恶性”）	74	8.62
使用非确定性词汇（如 “性质待查”“不除外恶性”）	30	3.50
未结合临床信息（如未标注绝经状态）	16	1.86

组别	例数	报告标准率	图像完整率	诊断确定性
基线组	858	71.21	72.96	86.02
优化组	932	95.06	97.50	95.17
χ² 值		185.66	220.79	44.77
P 值		<0.001	<0.001	<0.001

组别	例数	报告标准率	图像完整率	诊断确定性
基线组	858	71.21	72.96	86.02
优化组	932	95.06	97.50	95.17
χ² 值		185.66	220.79	44.77
P 值		<0.001	<0.001	<0.001

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