Detection of axillary lymph node metastasis in breast cancer using dual-layer spectral computed tomography

PurposeTo investigate the value of contrast-enhanced dual-layer spectral computed tomography (DLCT) in the detection of axillary lymph node (ALN) metastasis in breast cancer. Materials and MethodsIn this prospective study, 31 females with breast cancer underwent contrast-enhanced DLCT from August 2019 to June 2020. All ALNs were confirmed by postoperative histology. Spectral quantitative parameters, including lambda(HU) (in Hounsfield units per kiloelectron-volt), nIC (normalized iodine concentration), and Z(eff) (Z-effective value) in both arterial and delay phases, were calculated and contrasted between metastatic and nonmetastatic ALNs using the McNemar test. Discriminating performance from metastatic and nonmetastatic ALNs was analyzed using receiver operating characteristic curves. ResultsIn total, 132 ALNs (52 metastatic and 80 nonmetastatic) were successfully matched between surgical labels and preoperative labels on DLCT images. All spectral quantitative parameters (lambda(Hu), nIC, and Z(eff)) derived from both arterial and delayed phases were greater in metastatic ALNs than in nonmetastatic SLNs (all p < 0.001). Logistic regression analyses showed that lambda(Hu) in the delayed phase was the best single parameter for the detection of metastatic ALNs on a per-lymph node basis, with an area under the curve of 0.93, accuracy of 86.4% (114/132), sensitivity of 92.3% (48/52), and specificity of 87.5% (70/80). ConclusionThe spectral quantitative parameters derived from contrast-enhanced DLCT, such as lambda(Hu), can be applied for the preoperative detection of ALN metastasis in breast cancer.