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不同经验水平的放射科医生在解读胎盘植入谱系疾病 MRI 中的诊断性能。

Diagnostic performance of radiologists with different levels of experience in the interpretation of MRI of the placenta accreta spectrum disorder.

机构信息

Department of Radiology, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, Brazil.

Department of Radiology, Hospital Moinhos de Vento, Porto Alegre, Brazil.

出版信息

Br J Radiol. 2021 Dec;94(1128):20210827. doi: 10.1259/bjr.20210827. Epub 2021 Sep 24.

Abstract

OBJECTIVES

There have been no investigations on the association between previous abdominopelvic MRI experience without placental MRI experience and diagnostic accuracy of placenta accreta spectrum (PAS). To evaluate the diagnostic performance of radiologists with different experience levels in interpreting PAS-related MRI findings.

METHODS

This retrospective study included 60 women who underwent MRI for placental assessment between 2016 and 2020. MR images were reviewed by four radiologists who were blinded to the clinical outcomes and had different experience levels in interpreting PAS-related MRI findings. The radiologists' diagnostic performance was evaluated according to the pathologic and surgical outcomes. Simple κ statistics were calculated to determine agreement among the radiologists.

RESULTS

Of 60 women, 46 were diagnosed with PAS. The maternal age mean ± SD was 33.0 years ± 5.0 for the PAS absent group and 36.0 ± 4.3 for the PAS present group ( = 0.013). Overall, the most experienced radiologist had the highest sensitivity (100%, 95% confidence interval (CI): 92.3-100%) and NPV (100%, 95% CI: 63.1-100%) in PAS diagnoses. However, the PPV and specificity were independent of experience. The most experienced radiologist had the highest diagnostic accuracy in PAS (90%, 95% CI: 79.5-96.2%) and placenta percreta (95%, 95% CI: 86.1-99.0%). There was a strong association between definitive PAS diagnoses and the highest experience level. The κ values for the interobserver agreement regarding PAS diagnoses were 0.67 for the most experienced radiologist ( < 0.001) and 0.38, 0.40, and 0.43 for the other radiologists ( = 0.001) and regarding placenta percreta diagnoses were 0.87 for the senior radiologist ( < 0.001) and 0.63, 0.57, and 0.62 for the other radiologists ( < 0.001).

CONCLUSION

Previous experience in interpreting PAS-related MRI findings plays a significant role in accurately interpreting such imaging findings. Previous abdominopelvic MRI experience without specific placental MRI experience did not improve diagnostic performance.

ADVANCES IN KNOWLEDGE

We believe that our study makes a significant contribution to the literature and that this paper will be of interest to the readership of your journal because to the best of our knowledge, this study is the first in which the correlation between previous experience in abdominopelvic MRI with no specific experience in PAS-related MRI and diagnostic accuracy of radiologists has been explored. Our results could aid in setting up specialized multidisciplinary teams to assist women with PAS disorders.

摘要

目的

目前尚无研究探讨缺乏胎盘 MRI 经验的既往腹盆腔 MRI 经验与胎盘植入谱系疾病(PAS)诊断准确性之间的关系。本研究旨在评估不同经验水平的放射科医生在解读 PAS 相关 MRI 表现方面的诊断表现。

方法

本回顾性研究纳入了 2016 年至 2020 年间因胎盘评估而行 MRI 检查的 60 名女性。4 名放射科医生对 MRI 图像进行了盲法评估,他们对 PAS 相关 MRI 表现的解读经验水平不同。根据病理和手术结果评估放射科医生的诊断表现。采用简单 κ 统计量评估放射科医生之间的一致性。

结果

60 名女性中,46 名被诊断为 PAS。PAS 阴性组的产妇年龄平均值 ± 标准差为 33.0 岁 ± 5.0 岁,PAS 阳性组为 36.0 岁 ± 4.3 岁( = 0.013)。总体而言,最有经验的放射科医生在 PAS 诊断中的灵敏度(100%,95%置信区间(CI):92.3-100%)和阴性预测值(100%,95%CI:63.1-100%)最高。然而,阳性预测值和特异性与经验无关。最有经验的放射科医生在 PAS(90%,95%CI:79.5-96.2%)和胎盘植入(95%,95%CI:86.1-99.0%)的诊断准确性最高。明确的 PAS 诊断与最高经验水平之间存在很强的关联。最有经验的放射科医生在 PAS 诊断方面的观察者间一致性 κ 值为 0.67(<0.001),其他放射科医生的 κ 值为 0.38、0.40 和 0.43( = 0.001);在胎盘植入的诊断方面,资深放射科医生的 κ 值为 0.87(<0.001),其他放射科医生的 κ 值为 0.63、0.57 和 0.62(<0.001)。

结论

既往解读 PAS 相关 MRI 表现的经验在准确解读此类影像学表现方面发挥着重要作用。缺乏特定 PAS 相关 MRI 经验的既往腹盆腔 MRI 经验并未提高诊断表现。

知识的进步

我们认为,我们的研究对文献做出了重要贡献,并且本文将引起您的期刊读者的兴趣,因为据我们所知,这是首次探讨既往腹盆腔 MRI 经验与 PAS 相关 MRI 经验之间的关系以及放射科医生诊断准确性之间的关系。我们的研究结果可能有助于建立专门的多学科团队,以帮助患有 PAS 疾病的女性。

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本文引用的文献

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Magnetic Resonance Imaging of Placenta Accreta Spectrum: A Step-by-Step Approach.
Korean J Radiol. 2021 Feb;22(2):198-212. doi: 10.3348/kjr.2020.0580. Epub 2020 Dec 28.
2
Placenta Accreta Spectrum: Correlation of MRI Parameters With Pathologic and Surgical Outcomes of High-Risk Pregnancies.
AJR Am J Roentgenol. 2020 Jun;214(6):1417-1423. doi: 10.2214/AJR.19.21705. Epub 2020 Mar 24.
4
Interobserver agreement in MRI assessment of severity of placenta accreta spectrum disorders.
Ultrasound Obstet Gynecol. 2020 Apr;55(4):467-473. doi: 10.1002/uog.20381.
6
Magnetic resonance imaging is often misleading when used as an adjunct to ultrasound in the management of placenta accreta spectrum disorders.
Am J Obstet Gynecol. 2018 Jun;218(6):618.e1-618.e7. doi: 10.1016/j.ajog.2018.03.013. Epub 2018 Mar 20.
7
FIGO consensus guidelines on placenta accreta spectrum disorders: Epidemiology.
Int J Gynaecol Obstet. 2018 Mar;140(3):265-273. doi: 10.1002/ijgo.12407.
8
FIGO consensus guidelines on placenta accreta spectrum disorders: Nonconservative surgical management.
Int J Gynaecol Obstet. 2018 Mar;140(3):281-290. doi: 10.1002/ijgo.12409.
10
MRI of Placenta Accreta, Placenta Increta, and Placenta Percreta: Pearls and Pitfalls.
AJR Am J Roentgenol. 2017 Jan;208(1):214-221. doi: 10.2214/AJR.16.16281. Epub 2016 Oct 20.

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