From the Mathematical Oncology Laboratory, Instituto de Matemática Aplicada a la Ciencia y la Ingeniería, Universidad de Castilla-La Mancha, Avenida de Camilo Jose Cela 3, 13071 Ciudad Real, Spain (J.P., D.M., J.A.O., A.F., B.L., V.M.P.); Departments of Radiology and Neurosurgery, Hospital General de Ciudad Real, Ciudad Real, Spain (E. Arregui, M.C., J.M.B.); Departments of Pathology, Radiology, and Neurosurgery, Hospital Virgen de la Salud, Toledo, Spain (B.M., Á.R.d.L., R.M.d.l.P.); Department of Neurosurgery, Hospital Clínico San Carlos, Madrid, Spain (L.I.B., J.A.B.); Department of Neurosurgery, Hospital Marqués de Valdecilla, Santander, Spain (J.M., C.V.); Department of Radiology, Complejo Hospitalario Universitario de Granada, Granada, Spain (B.A.); Department of Radiology, Hospital Carlos Haya, Málaga, Spain (M.B., I.H.); Department of Radiology, Hospital de Manises, Valencia, Spain (A.R.); and Department of Radiology, Instituto Valenciano de Oncología, Valencia, Spain (E. Arana).
Radiology. 2018 Jul;288(1):218-225. doi: 10.1148/radiol.2018171051.
Purpose To evaluate the prognostic and predictive value of surface-derived imaging biomarkers obtained from contrast material-enhanced volumetric T1-weighted pretreatment magnetic resonance (MR) imaging sequences in patients with glioblastoma multiforme. Materials and Methods A discovery cohort from five local institutions (165 patients; mean age, 62 years ± 12 [standard deviation]; 43% women and 57% men) and an independent validation cohort (51 patients; mean age, 60 years ± 12; 39% women and 61% men) from The Cancer Imaging Archive with volumetric T1-weighted pretreatment contrast-enhanced MR imaging sequences were included in the study. Clinical variables such as age, treatment, and survival were collected. After tumor segmentation and image processing, tumor surface regularity, measuring how much the tumor surface deviates from a sphere of the same volume, was obtained. Kaplan-Meier, Cox proportional hazards, correlations, and concordance indexes were used to compare variables and patient subgroups. Results Surface regularity was a powerful predictor of survival in the discovery (P = .005, hazard ratio [HR] = 1.61) and validation groups (P = .05, HR = 1.84). Multivariate analysis selected age and surface regularity as significant variables in a combined prognostic model (P < .001, HR = 3.05). The model achieved concordance indexes of 0.76 and 0.74 for the discovery and validation cohorts, respectively. Tumor surface regularity was a predictor of survival for patients who underwent complete resection (P = .01, HR = 1.90). Tumors with irregular surfaces did not benefit from total over subtotal resections (P = .57, HR = 1.17), but those with regular surfaces did (P = .004, HR = 2.07). Conclusion The surface regularity obtained from high-resolution contrast-enhanced pretreatment volumetric T1-weighted MR images is a predictor of survival in patients with glioblastoma. It may help in classifying patients for surgery.
目的 评估对比增强容积 T1 加权预处理磁共振成像(MR)序列获得的表面衍生成像生物标志物在多形性胶质母细胞瘤患者中的预后和预测价值。
材料与方法 本研究纳入了来自五个本地机构的发现队列(165 例患者;平均年龄 62 岁±12[标准差];43%为女性,57%为男性)和来自癌症成像档案的独立验证队列(51 例患者;平均年龄 60 岁±12;39%为女性,61%为男性),均具有容积 T1 加权预处理对比增强 MR 成像序列。收集了年龄、治疗和生存等临床变量。在肿瘤分割和图像处理后,获得了肿瘤表面规则性,即测量肿瘤表面相对于相同体积球体的偏离程度。使用 Kaplan-Meier、Cox 比例风险、相关性和一致性指数来比较变量和患者亚组。
结果 在发现组(P=.005,风险比[HR] = 1.61)和验证组(P=.05,HR = 1.84)中,表面规则性是生存的有力预测指标。多变量分析选择年龄和表面规则性作为联合预后模型中的显著变量(P<.001,HR = 3.05)。该模型在发现队列和验证队列中的一致性指数分别为 0.76 和 0.74。对于接受完全切除的患者,肿瘤表面规则性是生存的预测指标(P=.01,HR = 1.90)。表面不规则的肿瘤不能从全切除中获益(P=.57,HR = 1.17),但表面规则的肿瘤可以(P=.004,HR = 2.07)。
结论 从高分辨率对比增强预处理容积 T1 加权 MR 图像获得的表面规则性是胶质母细胞瘤患者生存的预测指标。它可能有助于对患者进行分类,以进行手术。