Perfusion measurement in brain gliomas using velocity-selective arterial spin labeling: comparison with pseudo-continuous arterial spin labeling and dynamic susceptibility contrast MRI.

OBJECTIVES: To evaluate the performance of velocity-selective (VS) ASL among patients with untreated gliomas by comparing with both pseudo-continuous (PC) ASL and dynamic susceptibility contrast-enhanced perfusion-weighted imaging (DSC-PWI). METHODS: Forty-four consecutive patients with newly diagnosed glioma who underwent preoperative perfusion MRI including VSASL, PCASL, and DSC-PWI between 2017 and 2019 were retrospectively evaluated. Visual inspection was performed to evaluate the tumor signal intensity relative to gray matter based on 1-5 score criteria and weighted kappa was used to evaluate the pair-wise concordance between VSASL or PCASL and DSC-PWI. The relative tumor blood flow (rTBF) was measured from sampling intra-tumoral areas of hot-spot on the blood flow map and normalized against the contralateral normal gray matter blood flow. Linear regression and Bland-Altman analyses were performed to evaluate the correlation and agreement of rTBF measurements between ASL methods and DSC-PWI. The ROC analysis was constructed to determine the diagnostic performance of three perfusion methods for grading gliomas. RESULTS: TBF maps derived from VSASL were more comparable with DSC-PWI than PCASL on visual inspection (weighted kappa of 0.90 vs 0.68). In quantitative analysis, VSASL-rTBF yielded higher correlation with the values from DSC-PWI than PCASL-rTBF (R2 = 80% vs 47%, p < 0.001 for both). Both ASL and DSC-derived rTBF showed good distinction between low-grade and high-grade gliomas (p < 0.001). Compared to PCASL, VSASL yielded superior diagnostic sensitivity, specificity, and accuracy in glioma grading. CONCLUSIONS: VSASL showed great promise for accurate quantification of TBF and could potentially improve the diagnostic performance of ASL in preoperative grading of gliomas. KEY POINTS: • VSASL demonstrated a greater agreement with DSC-PWI than with PCASL on visual inspection and perfusion quantification. • VSASL showed a higher diagnostic sensitivity, negative predictive value, and accuracy than PCASL for glioma grading. • With the advantages of insensitivity to transit delay and no need of prescribing a labeling plane, VSASL could potentially improve the diagnostic performance of ASL for a more accurate, noninvasive quantification of TBF in patients with glioma.

Imaging features of sentinel lymph node mapped by multidetector-row computed tomography lymphography in predicting axillary lymph node metastasis.

INTRODUCTION: Accurately assessing axillary lymph node (ALN) status in breast cancer is vital for clinical decision making and prognosis. The purpose of this study was to evaluate the predictive value of sentinel lymph node (SLN) mapped by multidetector-row computed tomography lymphography (MDCT-LG) for ALN metastasis in breast cancer patients. METHODS: 112 patients with breast cancer who underwent preoperative MDCT-LG examination were included in the study. Long-axis diameter, short-axis diameter, ratio of long-/short-axis and cortical thickness were measured. Logistic regression analysis was performed to evaluate independent predictors associated with ALN metastasis. The prediction of ALN metastasis was determined with related variables of SLN using receiver operating characteristic (ROC) curve analysis. RESULTS: Among the 112 cases, 35 (30.8%) cases had ALN metastasis. The cortical thickness in metastatic ALN group was significantly thicker than that in non-metastatic ALN group (4.0 ± 1.2 mm vs. 2.4 ± 0.7 mm, P < 0.001). Multi-logistic regression analysis indicated that cortical thickness of > 3.3 mm (OR 24.53, 95% CI 6.58-91.48, P < 0.001) had higher risk for ALN metastasis. The best sensitivity, specificity, negative predictive value(NPV) and AUC of MDCT-LG for ALN metastasis prediction based on the single variable of cortical thickness were 76.2%, 88.5%, 90.2% and 0.872 (95% CI 0.773-0.939, P < 0.001), respectively. CONCLUSION: ALN status can be predicted using the imaging features of SLN which was mapped on MDCT-LG in breast cancer patients. Besides, it may be helpful to select true negative lymph nodes in patients with early breast cancer, and SLN biopsy can be avoided in clinically and radiographically negative axilla.