Park Ji Yeon
Department of Radiology, Inje University Ilsan Paik Hospital, Goyang 10380, Korea.
J Clin Med. 2022 Feb 22;11(5):1172. doi: 10.3390/jcm11051172.
Purpose: This study aimed to evaluate cancer size measurement by computer-aided diagnosis (CAD) and radiologist on breast magnetic resonance imaging (MRI) relative to histopathology and to determine clinicopathologic and MRI factors that may affect measurements. Methods: Preoperative MRI of 208 breast cancers taken between January 2017 and March 2021 were included. We evaluated correlation between CAD-generated size and pathologic size as well as that between radiologist-measured size and pathologic size. We classified size discrepancies into accurate and inaccurate groups. For both CAD and radiologist, clinicopathologic and imaging factors were compared between accurate and inaccurate groups. Results: The mean sizes as predicted by CAD, radiologist and pathology were 2.66 ± 1.68 cm, 2.54 ± 1.68 cm, and 2.30 ± 1.61 cm, with significant difference (p < 0.001). Correlation coefficients of cancer size measurement by radiologist and CAD in reference to pathology were 0.898 and 0.823. Radiologist’s measurement was more accurate than CAD, with statistical significance (p < 0.001). CAD-generated measurement was significantly more inaccurate for cancers of larger pathologic size (>2 cm), in the presence of an extensive intraductal component (EIC), with positive progesterone receptor (PR), and of non-mass enhancement (p = 0.045, 0.045, 0.03 and 0.002). Radiologist-measured size was significantly more inaccurate for cancers in presence of an in situ component, EIC, positive human epidermal growth factor receptor 2 (HER2), and non-mass enhancement (p = 0.017, 0.008, 0.003 and <0.001). Conclusion: Breast cancer size measurement showed a very strong correlation between CAD and pathology and radiologist and pathology. Radiologist-measured size was significantly more accurate than CAD size. Cancer size measurement by CAD and radiologist can both be inaccurate for cancers with EIC or non-mass enhancement.
本研究旨在评估计算机辅助诊断（CAD）和放射科医生在乳腺磁共振成像（MRI）上对癌症大小的测量相对于组织病理学的情况，并确定可能影响测量的临床病理和MRI因素。方法：纳入2017年1月至2021年3月期间拍摄的208例乳腺癌的术前MRI。我们评估了CAD生成的大小与病理大小之间的相关性以及放射科医生测量的大小与病理大小之间的相关性。我们将大小差异分为准确组和不准确组。对于CAD和放射科医生，比较了准确组和不准确组之间的临床病理和影像因素。结果：CAD、放射科医生和病理学预测的平均大小分别为2.66±1.68cm、2.54±1.68cm和2.30±1.61cm，差异有统计学意义（p<0.001）。放射科医生和CAD测量癌症大小相对于病理学的相关系数分别为0.898和0.823。放射科医生的测量比CAD更准确，具有统计学意义（p<0.001）。对于病理大小较大（>2cm）、存在广泛导管内成分（EIC）、孕激素受体（PR）阳性以及非肿块强化的癌症，CAD生成的测量明显更不准确（p=0.045、0.045、0.03和0.002）。对于存在原位成分、EIC、人表皮生长因子受体2（HER2）阳性以及非肿块强化的癌症，放射科医生测量的大小明显更不准确（p=0.017、0.008、0.003和<0.001）。结论：乳腺癌大小测量显示CAD与病理学、放射科医生与病理学之间具有非常强的相关性。放射科医生测量的大小明显比CAD大小更准确。对于具有EIC或非肿块强化的癌症，CAD和放射科医生测量的癌症大小都可能不准确。
