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- Can we use 3D volume of lymph nodes to predict oral melanoma metastasis
Can we use 3D volume of lymph nodes to predict oral melanoma metastasis
VRU 2023 - 64(4): 694-705
Timothy L. Menghini, Tobias Schwarz, Sumari Dancer, Calum Gray, Tom MacGillivray, Kelly L. Bowlt Blacklock
Background: Oral melanoma (OM) is a common and aggressive tumor in dogs that often metastasizes to regional lymph nodes (LNs). Accurate detection of LN metastasis is essential for staging and prognosis of OM. This study aimed to evaluate contrast-enhanced CT 3D measurements of LN volume and attenuation as predictors of LN metastasis in dogs with OM.
Study: This was a retrospective observational study that included 33 dogs: 12 with nodal metastatic OM, 10 with non-metastatic OM, and 11 healthy controls. CT images of the mandibular and retropharyngeal lymphocenters (LCs) were analyzed using commercial software to generate regions of interest (ROIs) and calculate voxel, area, volume, and degree of attenuation (HU) for each LC. These parameters were compared between groups and correlated with histopathology or cytology results of the LNs.
Methods: The authors used a linear mixed-effects model with Tukey HSD post hoc test to identify significant differences in CT measurements between groups. They also generated ROC curves to assess the diagnostic accuracy of volume and volume/weight ratio as predictors of metastatic status. They used Bland-Altman plots and one-sample t-test to evaluate intra- and inter-observer agreement for ROI measurements.
Results: The authors found that LC volume was significantly larger in dogs with metastatic OM than in dogs with non-metastatic OM or controls. However, the area under the curve (AUC) for volume as a predictor of metastasis was only 0.754, indicating moderate discrimination. There was no significant difference in voxel number or HU between groups. There was good intra- and inter-observer agreement for all CT measurements.
Limitations: The study had some limitations due to its retrospective nature, such as variability in CT protocols, slice thickness, and voxel size. The sample size was small and the number of positive LNs was low. The authors only included LCs with known histopathology or cytology results, which may have introduced selection bias. They also assumed that all LNs within a LC had the same metastatic status, which may not be true. They did not evaluate other CT features such as LN shape or texture, which may have improved the diagnostic accuracy.
Conclusions: The study demonstrated that 3D CT volume measurement of LCs can predict nodal metastasis in dogs with OM, but the accuracy is not high enough for clinical use. Further studies are needed to optimize CT protocols, increase sample size, and explore other CT parameters for LN assessment in dogs with OM.
Transverse contrast-enhanced head CT images and 3D volume renderings of mandibular lymphocenters (MLC) and retropharyngeal lymphocenters (RLC) [soft tissue algorithm, 120 kVp, 200 mAs, 1.0 s/rotation, 1.0 mm slice thickness, window width = 350, window level = 60]. Patient's right is in left of image. Top, Normal MLC (A), RLC (B), and 3D volume rendering of all four lymphocenters (C, front view) in a control dog. Bottom, enlarged metastatic right MLC (D), negative RLC (E) and 3D volume rendering of all 4 lymphocenters (F, front view) in a positive dog (Case #6). Note the extremely large left MLC compared to others, indicating macrometastasis. Circled areas indicate regions of interest (ROI). Red = right MLC(s); yellow = left MLC(s); green = right RLC and blue = left RLC. White arrowheads indicate MLCs; White stars indicate RLCs. [Correction added on June 19, 2023, after first online publication: In the Figure 1 legend
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