Rigiroli Francesca, Hoye Jocelyn, Lerebours Reginald, Lyu Peijie, Lafata Kyle J, Zhang Anru R, Erkanli Alaattin, Mettu Niharika B, Morgan Desiree E, Samei Ehsan, Marin Daniele
Department of Radiology, Duke University Health System, 2301 Erwin Road, Box 3808, Durham, NC, 27710, USA.
Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, 1 Deaconess Road, Boston, MA, 02215, USA.
Eur Radiol. 2023 Aug;33(8):5779-5791. doi: 10.1007/s00330-023-09532-0. Epub 2023 Mar 10.
To develop and evaluate task-based radiomic features extracted from the mesenteric-portal axis for prediction of survival and response to neoadjuvant therapy in patients with pancreatic ductal adenocarcinoma (PDAC).
Consecutive patients with PDAC who underwent surgery after neoadjuvant therapy from two academic hospitals between December 2012 and June 2018 were retrospectively included. Two radiologists performed a volumetric segmentation of PDAC and mesenteric-portal axis (MPA) using a segmentation software on CT scans before (CTtp0) and after (CTtp1) neoadjuvant therapy. Segmentation masks were resampled into uniform 0.625-mm voxels to develop task-based morphologic features (n = 57). These features aimed to assess MPA shape, MPA narrowing, changes in shape and diameter between CTtp0 and CTtp1, and length of MPA segment affected by the tumor. A Kaplan-Meier curve was generated to estimate the survival function. To identify reliable radiomic features associated with survival, a Cox proportional hazards model was used. Features with an ICC ≥ 0.80 were used as candidate variables, with clinical features included a priori.
In total, 107 patients (60 men) were included. The median survival time was 895 days (95% CI: 717, 1061). Three task-based shape radiomic features (Eccentricity mean tp0, Area minimum value tp1, and Ratio 2 minor tp1) were selected. The model showed an integrated AUC of 0.72 for prediction of survival. The hazard ratio for the Area minimum value tp1 feature was 1.78 (p = 0.02) and 0.48 for the Ratio 2 minor tp1 feature (p = 0.002).
Preliminary results suggest that task-based shape radiomic features can predict survival in PDAC patients.
• In a retrospective study of 107 patients who underwent neoadjuvant therapy followed by surgery for PDAC, task-based shape radiomic features were extracted and analyzed from the mesenteric-portal axis. • A Cox proportional hazards model that included three selected radiomic features plus clinical information showed an integrated AUC of 0.72 for prediction of survival, and a better fit compared to the model with only clinical information.
开发并评估从肠系膜-门静脉轴提取的基于任务的放射组学特征，以预测胰腺导管腺癌（PDAC）患者的生存率及对新辅助治疗的反应。
回顾性纳入2012年12月至2018年6月期间在两家学术医院接受新辅助治疗后行手术的连续性PDAC患者。两名放射科医生使用分割软件在新辅助治疗前（CTtp0）和治疗后（CTtp1）的CT扫描上对PDAC和肠系膜-门静脉轴（MPA）进行容积分割。分割掩码被重新采样为均匀的0.625毫米体素，以开发基于任务的形态学特征（n = 57）。这些特征旨在评估MPA形状、MPA变窄、CTtp0和CTtp1之间形状和直径的变化以及受肿瘤影响的MPA节段长度。生成Kaplan-Meier曲线以估计生存函数。为了识别与生存相关的可靠放射组学特征，使用了Cox比例风险模型。组内相关系数（ICC）≥0.80的特征被用作候选变量，临床特征预先纳入。
共纳入107例患者（60例男性）。中位生存时间为895天（95%CI：717，1061）。选择了三个基于任务的形状放射组学特征（平均偏心度tp0、面积最小值tp1和比值2次要tp1）。该模型预测生存率的综合曲线下面积（AUC）为0.72。面积最小值tp1特征的风险比为1.78（p = 0.02），比值2次要tp1特征的风险比为0.48（p = 0.002）。
初步结果表明，基于任务的形状放射组学特征可预测PDAC患者的生存率。
• 在一项对107例接受新辅助治疗后行PDAC手术患者的回顾性研究中，从肠系膜-门静脉轴提取并分析了基于任务的形状放射组学特征。• 一个包含三个选定放射组学特征加临床信息的Cox比例风险模型预测生存率的综合AUC为0.72，与仅包含临床信息的模型相比拟合度更好。
