Abstract：
OBJECTIVE: The aim of our study was to evaluate the contribution of 18Fluorine-Fluorodeoxyglucose Positron Emission Tomography (18F-FDG PET) radiomic data obtained from both the tumoral and peritumoral area in predicting pathological complete response (pCR) in patients with locally advanced breast cancer receiving neoadjuvant chemotherapy (NAC).
METHODS: Female patients with a diagnosis of invasive ductal carcinoma who received NAC were evaluated retrospectively. The volume of interest (VOI) of the primary tumor (VOI-T) was manually segmented, then a voxel-thick VOI was added around VOI-T to define the peritumoral area (VOI-PT). Morphological, intensity-based, histogram and texture parameters were obtained from VOIs. The patients were divided into two groups as pCR and non-complete pathological response (npCR). A \"radiomic model\" was created with only radiomic features, and a \"patho-radiomic model\" was created using radiomic features and immunohistochemical data.
RESULTS: Of the 66 patients included in the study, 21 were in the pCR group. The only statistically significant feature from the primary tumor among patients with pCR and npCR was Morphological_Compacity-T (AUC: 0.666). Between response groups, a significant difference was detected in 2 morphological, 1 intensity, 4 texture features from VOI-PT; no correlation was found between Morphological_Compacity-PT and NGTDM_contrast-PT. The obtained radiomic model\'s sensitivity and accuracy values were calculated as 61.9% and 75.8%, respectively (AUC: 0.786). When HER2 status was added, sensitivity and accuracy values of the patho-radiomic model increased to 85.7% and 81.8%, respectively (AUC: 0.903).
CONCLUSIONS: Evaluation of PET peritumoral radiomic features together with the primary tumor, rather than just the primary tumor, provides a better prediction of the pCR to NAC in patients with breast cancer.
METHODS: Female patients with a diagnosis of invasive ductal carcinoma who received NAC were evaluated retrospectively. The volume of interest (VOI) of the primary tumor (VOI-T) was manually segmented, then a voxel-thick VOI was added around VOI-T to define the peritumoral area (VOI-PT). Morphological, intensity-based, histogram and texture parameters were obtained from VOIs. The patients were divided into two groups as pCR and non-complete pathological response (npCR). A \"radiomic model\" was created with only radiomic features, and a \"patho-radiomic model\" was created using radiomic features and immunohistochemical data.
RESULTS: Of the 66 patients included in the study, 21 were in the pCR group. The only statistically significant feature from the primary tumor among patients with pCR and npCR was Morphological_Compacity-T (AUC: 0.666). Between response groups, a significant difference was detected in 2 morphological, 1 intensity, 4 texture features from VOI-PT; no correlation was found between Morphological_Compacity-PT and NGTDM_contrast-PT. The obtained radiomic model\'s sensitivity and accuracy values were calculated as 61.9% and 75.8%, respectively (AUC: 0.786). When HER2 status was added, sensitivity and accuracy values of the patho-radiomic model increased to 85.7% and 81.8%, respectively (AUC: 0.903).
CONCLUSIONS: Evaluation of PET peritumoral radiomic features together with the primary tumor, rather than just the primary tumor, provides a better prediction of the pCR to NAC in patients with breast cancer.
摘要：
目的：我们的研究目的是评估从肿瘤和肿瘤周围区域获得的18氟-氟脱氧葡萄糖正电子发射断层扫描（18F-FDGPET）放射组学数据在预测接受新辅助化疗（NAC）的局部晚期乳腺癌患者的病理完全缓解（pCR）中的作用。
方法：对诊断为浸润性导管癌并接受NAC的女性患者进行回顾性评估。对原发肿瘤(VOI-T)的感兴趣体积(VOI)进行手动分割,然后在VOI-T周围添加体素厚的VOI以定义肿瘤周围区域(VOI-PT)。形态学,基于强度，直方图和纹理参数是从VOI获得的。将患者分为pCR和非完全病理反应（npCR）两组。创建了一个只有放射学特征的“放射学模型”，并使用放射学特征和免疫组织化学数据创建了“病理放射学模型”。
结果：纳入研究的66例患者中，pCR组中有21例。在具有pCR和npCR的患者中,原发性肿瘤的唯一统计学上显著的特征是形态学-Compacity-T(AUC:0.666)。在响应组之间，在2个形态学上检测到显著差异，1强度,来自VOI-PT的4个纹理特征；在形态学_Compacity-PT和NGTDM_contrast-PT之间没有发现相关性。计算得到的影像组学模型的灵敏度和准确度分别为61.9%和75.8%,分别（AUC：0.786）。当添加HER2状态时，病理影像模型的灵敏度和准确度分别提高到85.7%和81.8%，分别（AUC：0.903）。
结论：评估PET肿瘤周围影像组学特征以及原发肿瘤，而不仅仅是原发性肿瘤，为乳腺癌患者的pCR对NAC提供了更好的预测。
方法：对诊断为浸润性导管癌并接受NAC的女性患者进行回顾性评估。对原发肿瘤(VOI-T)的感兴趣体积(VOI)进行手动分割,然后在VOI-T周围添加体素厚的VOI以定义肿瘤周围区域(VOI-PT)。形态学,基于强度，直方图和纹理参数是从VOI获得的。将患者分为pCR和非完全病理反应（npCR）两组。创建了一个只有放射学特征的“放射学模型”，并使用放射学特征和免疫组织化学数据创建了“病理放射学模型”。
结果：纳入研究的66例患者中，pCR组中有21例。在具有pCR和npCR的患者中,原发性肿瘤的唯一统计学上显著的特征是形态学-Compacity-T(AUC:0.666)。在响应组之间，在2个形态学上检测到显著差异，1强度,来自VOI-PT的4个纹理特征；在形态学_Compacity-PT和NGTDM_contrast-PT之间没有发现相关性。计算得到的影像组学模型的灵敏度和准确度分别为61.9%和75.8%,分别（AUC：0.786）。当添加HER2状态时，病理影像模型的灵敏度和准确度分别提高到85.7%和81.8%，分别（AUC：0.903）。
结论：评估PET肿瘤周围影像组学特征以及原发肿瘤，而不仅仅是原发性肿瘤，为乳腺癌患者的pCR对NAC提供了更好的预测。
