PDF(Pubmed)
Abstract：
UNASSIGNED: Immediate post-mastectomy breast reconstruction offers benefits; however, complications can compromise outcomes. Intraoperative indocyanine green fluorescence angiography (ICGFA) may mitigate perfusion-related complications (PRC); however, its interpretation remains subjective. Here, we examine and develop methods for ICGFA quantification, including machine learning (ML) algorithms for predicting complications.
UNASSIGNED: ICGFA video recordings of flap perfusion from a previous study of patients undergoing nipple-sparing mastectomy (NSM) with either immediate or staged immediate (delayed by a week due to perfusion insufficiency) reconstructions were analysed. Fluorescence intensity time series data were extracted, and perfusion parameters were interrogated for overall/regional associations with postoperative PRC. A naïve Bayes ML model was subsequently trained on a balanced data subset to predict PRC from the extracted meta-data.
UNASSIGNED: The analysable video dataset of 157 ICGFA featured females (average age 48 years) having oncological/risk-reducing NSM with either immediate (n=90) or staged immediate (n=26) reconstruction. For those delayed, peak brightness at initial ICGFA was lower (p<0.001) and significantly improved (both quicker-onset and brighter p=0.001) one week later. The overall PRC rate in reconstructed patients (n=116) was 11.2%, with such patients demonstrating significantly dimmer (overall, p=0.018, centrally, p=0.03, and medially, p=0.04) and slower-onset (p=0.039) fluorescent peaks with shallower slopes (p=0.012) than uncomplicated patients with ICGFA. Importantly, such relevant parameters were converted into a whole field of view heatmap potentially suitable for intraoperative display. ML predicted PRC with 84.6% sensitivity and 76.9% specificity.
UNASSIGNED: Whole breast quantitative ICGFA assessment reveals statistical associations with PRC that are potentially exploitable via ML.
UNASSIGNED: ICGFA video recordings of flap perfusion from a previous study of patients undergoing nipple-sparing mastectomy (NSM) with either immediate or staged immediate (delayed by a week due to perfusion insufficiency) reconstructions were analysed. Fluorescence intensity time series data were extracted, and perfusion parameters were interrogated for overall/regional associations with postoperative PRC. A naïve Bayes ML model was subsequently trained on a balanced data subset to predict PRC from the extracted meta-data.
UNASSIGNED: The analysable video dataset of 157 ICGFA featured females (average age 48 years) having oncological/risk-reducing NSM with either immediate (n=90) or staged immediate (n=26) reconstruction. For those delayed, peak brightness at initial ICGFA was lower (p<0.001) and significantly improved (both quicker-onset and brighter p=0.001) one week later. The overall PRC rate in reconstructed patients (n=116) was 11.2%, with such patients demonstrating significantly dimmer (overall, p=0.018, centrally, p=0.03, and medially, p=0.04) and slower-onset (p=0.039) fluorescent peaks with shallower slopes (p=0.012) than uncomplicated patients with ICGFA. Importantly, such relevant parameters were converted into a whole field of view heatmap potentially suitable for intraoperative display. ML predicted PRC with 84.6% sensitivity and 76.9% specificity.
UNASSIGNED: Whole breast quantitative ICGFA assessment reveals statistical associations with PRC that are potentially exploitable via ML.
摘要：
■乳房切除术后立即乳房重建有好处；然而，并发症会损害结果。术中吲哚菁绿荧光血管造影术(ICGFA)可减轻灌注相关并发症(PRC);然而,它的解释仍然是主观的。这里,我们检查和开发了ICGFA定量方法，包括用于预测并发症的机器学习(ML)算法。
■ICGFA视频记录分析了先前对接受保留乳头乳房切除术（NSM）并立即或分期（由于灌注不足而延迟一周）重建的患者的皮瓣灌注。提取荧光强度时间序列数据,和灌注参数被询问与术后PRC的整体/区域关联。随后在平衡数据子集上训练朴素贝叶斯ML模型以从提取的元数据预测PRC。
■157个ICGFA的可分析视频数据集以女性（平均年龄48岁）为特征，具有立即（n=90）或分阶段（n=26）重建的肿瘤/降低风险的NSM。对于那些延迟的人，初始ICGFA时的峰值亮度较低(p<0.001),一周后显著改善(起效更快和更亮,p=0.001).重建患者(n=116)的总体PRC率为11.2%，这些患者表现出明显变暗(总体而言，p=0.018，中央，p=0.03，中间，p=0.04）和起效较慢（p=0.039）的荧光峰的斜率较浅（p=0.012）。重要的是,这些相关参数被转换为可能适合术中显示的全视场热图.ML预测PRC的敏感性为84.6%，特异性为76.9%。
■全乳房定量ICGFA评估显示与PRC的统计关联，可通过ML利用。
■ICGFA视频记录分析了先前对接受保留乳头乳房切除术（NSM）并立即或分期（由于灌注不足而延迟一周）重建的患者的皮瓣灌注。提取荧光强度时间序列数据,和灌注参数被询问与术后PRC的整体/区域关联。随后在平衡数据子集上训练朴素贝叶斯ML模型以从提取的元数据预测PRC。
■157个ICGFA的可分析视频数据集以女性（平均年龄48岁）为特征，具有立即（n=90）或分阶段（n=26）重建的肿瘤/降低风险的NSM。对于那些延迟的人，初始ICGFA时的峰值亮度较低(p<0.001),一周后显著改善(起效更快和更亮,p=0.001).重建患者(n=116)的总体PRC率为11.2%，这些患者表现出明显变暗(总体而言，p=0.018，中央，p=0.03，中间，p=0.04）和起效较慢（p=0.039）的荧光峰的斜率较浅（p=0.012）。重要的是,这些相关参数被转换为可能适合术中显示的全视场热图.ML预测PRC的敏感性为84.6%，特异性为76.9%。
■全乳房定量ICGFA评估显示与PRC的统计关联，可通过ML利用。
