Fantini Lorenzo, Belli Maria Luisa, Azzali Irene, Loi Emiliano, Bettinelli Andrea, Feliciani Giacomo, Mezzenga Emilio, Fedeli Anna, Asioli Silvia, Paganelli Giovanni, Sarnelli Anna, Matteucci Federica
Nuclear Medicine Unit, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori," Meldola, Italy.
Medical Physics Unit, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori," Meldola, Italy.
Front Oncol. 2021 Jun 24;11:601053. doi: 10.3389/fonc.2021.601053. eCollection 2021.
The objective of this study was to evaluate a set of radiomics-based advanced textural features extracted from F-FLT-PET/CT images to predict tumor response to neoadjuvant chemotherapy (NCT) in patients with locally advanced breast cancer (BC).
Patients with operable (T2-T3, N0-N2, M0) or locally advanced (T4, N0-N2, M0) BC were enrolled. All patients underwent chemotherapy (six cycles every 3 weeks). Surgery was performed within 4 weeks of the end of NCT. The MD Anderson Residual Cancer Burden calculator was used to evaluate the pathological response. F-FLT-PET/CT was performed 2 weeks before the start of NCT and approximately 3 weeks after the first cycle. The evaluation of PET response was based on EORTC criteria. Standard uptake value (SUV) statistics (SUV, SUV, SUV), together with 148 textural features, were extracted from each lesion. Indices that are robust against contour variability (ICC test) were used as independent variables to logistically model tumor response. LASSO analysis was used for variable selection.
Twenty patients were included in the study. Lesions from 15 patients were evaluable and analyzed: 9 with pathological complete response (pCR) and 6 with pathological partial response (pPR). Concordance between PET response and histological examination was found in 13/15 patients. LASSO logistic modelling identified a combination of SUV and the textural feature index IVH_VolumeIntFract_90 as the most useful to classify PET response, and a combination of PET response, ID range, and ID_Coefficient of Variation as the most useful to classify pathological response.
Our study suggests the potential usefulness of FLT-PET for early monitoring of response to NCT. A model based on PET radiomic characteristics could have good discriminatory capacity of early response before the end of treatment.
本研究的目的是评估从F-FLT-PET/CT图像中提取的一组基于放射组学的高级纹理特征，以预测局部晚期乳腺癌（BC）患者对新辅助化疗（NCT）的肿瘤反应。
纳入可手术（T2-T3，N0-N2，M0）或局部晚期（T4，N0-N2，M0）BC患者。所有患者均接受化疗（每3周6个周期）。在NCT结束后4周内进行手术。使用MD安德森残余癌负担计算器评估病理反应。在NCT开始前2周和第一个周期后约3周进行F-FLT-PET/CT检查。PET反应的评估基于欧洲癌症研究与治疗组织（EORTC）标准。从每个病变中提取标准摄取值（SUV）统计数据（SUV、SUV、SUV）以及148个纹理特征。对轮廓变异性具有稳健性的指标（ICC检验）用作逻辑模型肿瘤反应的自变量。使用套索分析进行变量选择。
20名患者纳入研究。对15名患者的病变进行了评估和分析：9例病理完全缓解（pCR），6例病理部分缓解（pPR）。13/15例患者的PET反应与组织学检查结果一致。套索逻辑模型确定SUV与纹理特征指数IVH_VolumeIntFract_90的组合对分类PET反应最有用，而PET反应、ID范围和ID变异系数的组合对分类病理反应最有用。
我们的研究表明FLT-PET在早期监测NCT反应方面具有潜在的有用性。基于PET放射组学特征的模型在治疗结束前对早期反应可能具有良好的鉴别能力。
