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Radiomics model and clinical scale for the preoperative diagnosis of silent corticotroph adenomas

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机构: [1]Chinese Acad Med Sci & Peking Union Med Coll, Peking Union Med Coll Hosp, Dept Neurosurg, 1 Shuai Fu Yuan, Beijing 100730, Peoples R China [2]Chinese Acad Med Sci & Peking Union Med Coll Hosp, Peking Union Med Coll Hosp, Dept Plast Surg, Beijing, Peoples R China [3]Capital Med Univ, Beijing Tiantan Hosp, Beijing Neurosurg Inst, Dept Neurosurg, Beijing, Peoples R China [4]Chinese Acad Med Sci & Peking Union Med Coll Hosp, Peking Union Med Coll Hosp, Dept Endocrinol, Beijing, Peoples R China [5]Chinese Acad Med Sci & Peking Union Med Coll Hosp, Peking Union Med Coll Hosp, Dept Radiol, Beijing, Peoples R China [6]Capital Med Univ, Xuanwu Hosp, China Int Neurosci Inst, Neurospine Ctr,Dept Neurosurg, Beijing, Peoples R China [7]Peking Univ First Hosp, Dept Thorac Surg, Beijing, Peoples R China
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关键词: Silent corticotroph adenoma Radiomics Machine learning Scale

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ObjectiveSilent corticotroph adenomas (SCAs) are a subtype of nonfunctioning pituitary adenomas that exhibit more aggressive behavior. However, rapid and accurate preoperative diagnostic methods are currently lacking.DesignThe purpose of this study was to examine the differences between SCA and non-SCA features and to establish radiomics models and a clinical scale for rapid and accurate prediction.MethodsA total of 260 patients (72 SCAs vs. 188 NSCAs) with nonfunctioning adenomas from Peking Union Medical College Hospital were enrolled in the study as the internal dataset. Thirty-five patients (6 SCAs vs. 29 NSCAs) from Fuzhou General Hospital were enrolled as the external dataset. Radiomics models and an SCA scale to preoperatively diagnose SCAs were established based on MR images and clinical features.ResultsThere were more female patients (internal dataset: p < 0.001; external dataset: p = 0.028) and more multiple microcystic changes (internal dataset: p < 0.001; external dataset: p = 0.012) in the SCA group. MRI showed more invasiveness (higher Knosp grades, p <= 0.001). The radiomics model achieved AUCs of 0.931 and 0.937 in the internal and external datasets, respectively. The clinical scale achieved an AUC of 0.877 and a sensitivity of 0.952 in the internal dataset and an AUC of 0.899 and a sensitivity of 1.0 in the external dataset.ConclusionsBased on clinical information and imaging characteristics, the constructed radiomics model achieved high preoperative diagnostic ability. The SCA scale achieved the purpose of rapidity and practicality while ensuring sensitivity, which is conducive to simplifying clinical work.

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出版当年[2022]版:
大类 | 3 区 医学
小类 | 3 区 内分泌学与代谢
最新[2023]版:
大类 | 2 区 医学
小类 | 2 区 内分泌学与代谢
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出版当年[2021]版:
Q2 ENDOCRINOLOGY & METABOLISM
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Q2 ENDOCRINOLOGY & METABOLISM

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第一作者机构: [1]Chinese Acad Med Sci & Peking Union Med Coll, Peking Union Med Coll Hosp, Dept Neurosurg, 1 Shuai Fu Yuan, Beijing 100730, Peoples R China [6]Capital Med Univ, Xuanwu Hosp, China Int Neurosci Inst, Neurospine Ctr,Dept Neurosurg, Beijing, Peoples R China
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