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This study explored the feasibility of dual-energy computed tomography (DECT) for the diagnosis of mediastinal lymph node (LN) metastasis in patients with lung cancer.

Forty-two consecutive patients with lung cancer, who underwent DECT, were included in this retrospective study. The attenuation value (Hounsfield unit) in virtual monochromatic images and the iodine concentration in the iodine map were measured at mediastinal LNs. The slope of the spectral attenuation curve (K) and normalized iodine concentration (in thoracic aorta) were calculated. The measurement results were statistically compared using 2 independent samples t test. Receiver operating characteristic curve analysis, net reclassification improvement, and integrated discrimination improvement were used to evaluate the diagnostic performance of DECT for mediastinal LN metastasis.

A total of 74 mediastinal LNs were obtained, including 33 metastatic LNs and 41 nonmetastatic LNs. The attenuation value at the lower energy levels of virtual monochromatic images (40-90 keV), K, and normalized iodine concentration demonstrated a significant difference between metastatic LNs and nonmetastatic LNs. The attenuation value at 40 keV was the most favorable biomarker for the diagnosis of mediastinal LN metastasis (area under curve, 0.91; sensitivity, 0.94; specificity, 0.81), which showed a much better performance than the LN diameter-based evaluation method (area under curve, 0.72; sensitivity, 0.66; specificity, 0.82; net reclassification improvement, 0.359; integrated discrimination improvement, 0.330).

Dual-energy computed tomography is a promising diagnostic approach for the diagnosis of mediastinal LN metastasis in patients with lung cancer, which may help clinicians implement personalized treatment strategies.
Dual-energy computed tomography is a promising diagnostic approach for the diagnosis of mediastinal LN metastasis in patients with lung cancer, which may help clinicians implement personalized treatment strategies.
The objective of this study was to determine the diagnostic value of quantitative border irregularity assessment and apparent diffusion coefficient (ADC) in patients with squamous cell carcinoma of the tongue (SCCT).

Cervical lymph nodes (n = 192) from 63 patients with SCCT were examined preoperatively by magnetic resonance imaging, including routine head and neck sequences, dynamic contrast-enhanced magnetic resonance imaging, diffusion-weighted imaging, ADC, surface regularity (SR), and visually assessed variables, and evaluated pathologically after surgery.

Necrosis, lymphatic hilum, unclear margin, higher SR, long to short axis ratio, and ADC were associated with metastasis in cervical lymph nodes (M-cLNs) and extranodal extension (ENE), and thickened nodal rim with ENE alone. Apparent diffusion coefficient, SR, unclear margin, and visible necrosis were strongly associated with M-cLN, whereas SR, unclear margin, and visible necrosis were associated with ENE status on logistic regression analysis.

Quantitative SR and ADC data greatly improved diagnosis of M-cLNs and ENE, relative to visible variables alone in patients with SCCT.
Quantitative SR and ADC data greatly improved diagnosis of M-cLNs and ENE, relative to visible variables alone in patients with SCCT.
This study aimed to assess computed tomography (CT) imaging findings for predicting the histological subtypes and clinical outcomes in patients with head and neck nodal involvement of diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL).

This retrospective study included 64 patients with histologically confirmed head and neck nodal lymphoma (43 with DLBCL and 21 with FL) who underwent pretreatment CT examinations. The CT imaging findings were retrospectively assessed and compared according to the 2 pathologies and their clinical outcomes.

Multiplicity (86% vs 57%, P < 0.05), necrosis (44% vs 5%, P < 0.01), ill-demarcated margin (33% vs 0%, P < 0.01), and surrounding fat stranding (56% vs 14%, P < 0.01) were significantly more frequent in DLBCLs than in FLs. Multivariate logistic regression analysis revealed that necrosis was a significant factor for predicting the diagnosis of DLBCL (P < 0.01). Multiplicity (100% vs 67%, P < 0.01), bilaterality (44% vs 13%, P < 0.05), and surrounding fat stranding (69% vs 28%, P < 0.01) were significantly more frequent in the poor outcome group than in the good outcome group. Multivariate logistic regression analysis revealed that bilaterality and surrounding fat stranding were significant factors for predicting poor outcomes (P < 0.05).

In patients with head and neck nodal lymphoma, necrosis was useful for predicting the diagnosis of DLBCL, whereas bilaterality and surrounding fat stranding were useful for predicting poor outcomes.
In patients with head and neck nodal lymphoma, necrosis was useful for predicting the diagnosis of DLBCL, whereas bilaterality and surrounding fat stranding were useful for predicting poor outcomes.
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