Steiner Dylan, Park Ju Ae, Singh Sarah, Potter Austin, Scalera Jonathan, Beane Jennifer, Suzuki Kei, Lenburg Marc E, Burks Eric J
Department of Medicine, Section of Computational Biomedicine, Boston University Chobanian and Avedisian School of Medicine, Boston, USA.
Thoracic Surgery, Inova Schar Cancer Institute, Fairfax, VA, USA.
Cancer Biomark. 2024 May 22:CBM230456. doi: 10.3233/CBM-230456.
Histologic grading of lung adenocarcinoma (LUAD) is predictive of outcome but is only possible after surgical resection. A radiomic biomarker predictive of grade has the potential to improve preoperative management of early-stage LUAD.
Validate a prognostic radiomic score indicative of lung cancer aggression (SILA) in surgically resected stage I LUAD ( 161) histologically graded as indolent low malignant potential (LMP), intermediate, or aggressive vascular invasive (VI) subtypes.
The SILA scores were generated from preoperative CT-scans using the previously validated Computer-Aided Nodule Assessment and Risk Yield (CANARY) software.
Cox proportional regression showed significant association between the SILA and 7-year recurrence-free survival (RFS) in a univariate ( 0.05) and multivariate ( 0.05) model incorporating age, gender, smoking status, pack years, and extent of resection. The SILA was positively correlated with invasive size (spearman 0.54, 8.0 10 ) and negatively correlated with percentage of lepidic histology (spearman 0.46, 7.1 10 ). The SILA predicted indolent LMP with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.74 and aggressive VI with an AUC of 0.71, the latter remaining significant when invasive size was included as a covariate in a logistic regression model ( 0.01).
The SILA scoring of preoperative CT scans was prognostic and predictive of resected pathologic grade.
肺腺癌(LUAD)的组织学分级可预测预后,但仅在手术切除后才能进行。一种可预测分级的放射组学生物标志物有潜力改善早期LUAD的术前管理。
验证一种在手术切除的I期LUAD(n = 161)中指示肺癌侵袭性的预后放射组学评分(SILA),这些病例的组织学分级为惰性低恶性潜能(LMP)、中等或侵袭性血管浸润(VI)亚型。
使用先前验证的计算机辅助结节评估和风险收益(CANARY)软件,从术前CT扫描生成SILA评分。
Cox比例回归显示,在纳入年龄、性别、吸烟状态、吸烟包年数和切除范围的单变量(P < .05)和多变量(P < .05)模型中,SILA与7年无复发生存率(RFS)之间存在显著关联。SILA与侵袭大小呈正相关(Spearman ρ = 0.54,P = 8.0 × 10⁻⁸),与鳞屑状组织学百分比呈负相关(Spearman ρ = 0.46,P = 7.1 × 10⁻⁷)。SILA预测惰性LMP的受试者工作特征(ROC)曲线下面积(AUC)为0.74,预测侵袭性VI的AUC为0.71,当在逻辑回归模型中将侵袭大小作为协变量纳入时,后者仍然显著(P < .01)。
术前CT扫描的SILA评分具有预后价值,并可预测切除后的病理分级。