Schwabe Maria, Spiridonov Stanislav, Yanik Elizabeth L, Jennings Jack W, Hillen Travis, Ponisio Maria, McDonald Douglas J, Dehdashti Farrokh, Cipriano Cara A
Washington University School of Medicine in St. Louis, 660 South Euclid Avenue, St. Louis, MO 63110, USA.
Sarcoma. 2019 Jul 1;2019:4627521. doi: 10.1155/2019/4627521. eCollection 2019.
Distinguishing between benign and malignant peripheral nerve sheath tumors (MPNSTs) in neurofibromatosis 1 (NF1) patients prior to excision can be challenging. How can MPNST be most accurately diagnosed using clinical symptoms, magnetic resonance imaging (MRI) findings (tumor size, depth, and necrosis), positron emission tomography (PET) measures (SUV, SUV, SUV/SUV, and qualitative scale), and combinations of the above? . All NF1 patients who underwent PET imaging at our institution (January 1, 2007-December 31, 2016) were included. Medical records were reviewed for clinical findings; MR images and PET images were interpreted by two fellowship-trained musculoskeletal and nuclear medicine radiologists, respectively. Receiver operating characteristic (ROC) curves were created for each PET measurement; the area under the curve (AUC) and thresholds for diagnosing malignancy were calculated. Logistic regression determined significant predictors of malignancy.
Our population of 41 patients contained 34 benign and 36 malignant tumors. Clinical findings did not reliably predict MPNST. Tumor depth below fascia was highly sensitive; larger tumors were more likely to be malignant but without a useful cutoff for diagnosis. Necrosis on MRI was highly accurate and was the only significant variable in the regression model. PET measures were highly accurate, with AUCs comparable and cutoff points consistent with prior studies. A diagnostic algorithm was created using MRI and PET findings.
MRI and PET were more effective at diagnosing MPNST than clinical features. We created an algorithm for preoperative evaluation of peripheral nerve sheath tumors in NF1 patients, for which additional validation will be indicated.
在切除神经纤维瘤病1型（NF1）患者的良性和恶性周围神经鞘瘤（MPNST）之前进行区分可能具有挑战性。如何使用临床症状、磁共振成像（MRI）结果（肿瘤大小、深度和坏死情况）、正电子发射断层扫描（PET）测量值（SUV、SUV、SUV/SUV和定性量表）以及上述各项的组合来最准确地诊断MPNST？纳入了在我们机构（2007年1月1日至2016年12月31日）接受PET成像的所有NF1患者。查阅病历以获取临床发现；MR图像和PET图像分别由两名接受过专科培训的肌肉骨骼和核医学放射科医生解读。为每个PET测量值绘制受试者操作特征（ROC）曲线；计算曲线下面积（AUC）和诊断恶性肿瘤的阈值。逻辑回归确定恶性肿瘤的显著预测因素。
我们的41例患者群体中包含34个良性肿瘤和36个恶性肿瘤。临床发现不能可靠地预测MPNST。筋膜以下的肿瘤深度具有高度敏感性；较大的肿瘤更可能是恶性的，但没有用于诊断的有效临界值。MRI上的坏死情况具有高度准确性，并且是回归模型中唯一的显著变量。PET测量值具有高度准确性，AUC相当，截断点与先前研究一致。利用MRI和PET结果创建了一种诊断算法。
MRI和PET在诊断MPNST方面比临床特征更有效。我们创建了一种用于NF1患者周围神经鞘瘤术前评估的算法，对此还需要进行额外的验证。
