Koopman Daniëlle, van Dalen Jorn A, Arkies Hester, Oostdijk Ad H J, Francken Anne Brecht, Bart Jos, Slump Cornelis H, Knollema Siert, Jager Pieter L
Department of Nuclear Medicine, Isala, Zwolle, the Netherlands.
MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, the Netherlands.
EJNMMI Res. 2018 Jan 16;8(1):3. doi: 10.1186/s13550-018-0359-7.
We evaluated the diagnostic implications of a small-voxel reconstruction for lymph node characterization in breast cancer patients, using state-of-the-art FDG-PET/CT. We included 69 FDG-PET/CT scans from breast cancer patients. PET data were reconstructed using standard 4 × 4 × 4 mm and small 2 × 2 × 2 mm voxels. Two hundred thirty loco-regional lymph nodes were included, of which 209 nodes were visualised on PET/CT. All nodes were visually scored as benign or malignant, and SUV and TB(=SUV/SUV) were measured. Final diagnosis was based on histological or imaging information. We determined the accuracy, sensitivity and specificity for both reconstruction methods and calculated optimal cut-off values to distinguish benign from malignant nodes.
Sixty-one benign and 169 malignant lymph nodes were included. Visual evaluation accuracy was 73% (sensitivity 67%, specificity 89%) on standard-voxel images and 77% (sensitivity 78%, specificity 74%) on small-voxel images (p = 0.13). Across malignant nodes visualised on PET/CT, the small-voxel score was more often correct compared with the standard-voxel score (89 vs. 76%, p < 0.001). In benign nodes, the standard-voxel score was more often correct (89 vs. 74%, p = 0.04). Quantitative data were based on the 61 benign and 148 malignant lymph nodes visualised on PET/CT. SUVs and TB were on average 3.0 and 1.6 times higher in malignant nodes compared to those in benign nodes (p < 0.001), on standard- and small-voxel PET images respectively. Small-voxel PET showed average increases in SUV and TB of typically 40% over standard-voxel PET. The optimal SUV cut-off using standard-voxels was 1.8 (sensitivity 81%, specificity 95%, accuracy 85%) while for small-voxels, the optimal SUV cut-off was 2.6 (sensitivity 78%, specificity 98%, accuracy 84%). Differences in accuracy were non-significant.
Small-voxel PET/CT improves the sensitivity of visual lymph node characterization and provides a higher detection rate of malignant lymph nodes. However, small-voxel PET/CT also introduced more false-positive results in benign nodes. Across all nodes, differences in accuracy were non-significant. Quantitatively, small-voxel images require higher cut-off values. Readers have to adapt their reference standards.
我们使用最先进的氟代脱氧葡萄糖正电子发射断层显像/计算机断层扫描（FDG-PET/CT）评估了小体素重建对乳腺癌患者淋巴结特征的诊断意义。我们纳入了69例乳腺癌患者的FDG-PET/CT扫描图像。PET数据采用标准的4×4×4mm体素和较小的2×2×2mm体素进行重建。共纳入230个局部区域淋巴结，其中209个淋巴结在PET/CT上可见。所有淋巴结均通过视觉评分判定为良性或恶性，并测量了标准化摄取值（SUV）和TB（=SUV/平均本底SUV）。最终诊断基于组织学或影像学信息。我们确定了两种重建方法的准确性、敏感性和特异性，并计算了区分良性和恶性淋巴结的最佳截断值。
共纳入61个良性和169个恶性淋巴结。在标准体素图像上，视觉评估的准确性为73%（敏感性67%，特异性89%），在小体素图像上为77%（敏感性78%，特异性74%）（p = 0.13）。在PET/CT上可见的恶性淋巴结中，与标准体素评分相比，小体素评分更常正确（89%对76%，p < 0.001）。在良性淋巴结中，标准体素评分更常正确（89%对74%，p = 0.04）。定量数据基于PET/CT上可见的61个良性和148个恶性淋巴结。在标准体素和小体素PET图像上，恶性淋巴结的SUV和TB平均分别比良性淋巴结高3.0倍和1.6倍（p < 0.001）。小体素PET显示，与标准体素PET相比，SUV和TB平均通常增加40%。使用标准体素时的最佳SUV截断值为1.8（敏感性81%，特异性95%，准确性85%），而对于小体素，最佳SUV截断值为2.6（敏感性78%，特异性98%，准确性84%）。准确性差异无统计学意义。
小体素PET/CT提高了视觉淋巴结特征的敏感性，并提供了更高的恶性淋巴结检出率。然而，小体素PET/CT也在良性淋巴结中引入了更多假阳性结果。在所有淋巴结中，准确性差异无统计学意义。在定量方面，小体素图像需要更高的截断值。读者必须调整他们的参考标准。
