Purpose. To assess the efficacy of MRI and MSCT in measuring the depth of invasion of tongue squamous cell carcinoma.

Materials and methods. A total of 53 patients (100%) with primary diagnosed and histologically confirmed squamous cell carcinoma (SCC) of the tongue were examined. All patients underwent contrast-enhanced MSCT and MRI. The correlation between the data obtained from MRI and MSCT and the clinical-histological data of SCC of the tongue was assessed in evaluating the depth of invasion.

Results. The results of MRI and MSCT in evaluating the depth of invasion of SCC of the tongue were analyzed for 53 patients, including 32 (60.4%) men and 21 (39.6%) women with a mean age of 52 ± 6 years. Contrast-enhanced MSCT showed a lesser depth of invasion compared to postoperative pathological examination (Me–9.7 mm and 10.5 mm, respectively, with an interquartile range (Q1–Q3) of 6.75–13 mm and 8.2–13.1 mm, respectively, p < 0.001), while MRI showed a greater depth of invasion compared to postoperative pathological examination (Me–11,9 mm and 10,5 mm, respectively, with an interquartile range (Q1–Q3) of 9.3–15.1 mm and 8.2–13.1 mm, respectively, p < 0.001). The correlation between the data from radiation methods and pathological examination was higher for MRI (r = 0.9749) compared to contrast-enhanced MSCT (r = 0.9341).

Discussion. A comparative analysis of the MSCT and MRI results revealed their significance in determining the depth of invasion of SCC of the tongue compared to postoperative histological examination data. Our study results demonstrated differences from those obtained by other authors, who primarily focused on contrast-enhanced MSCT as the preferred diagnostic method for this category of patients. Although the correlation coefficient for MSCT in our study was also high (r = 0.9341, p < 0.001), MRI showed higher diagnostic value in determining the extent of tumor spread (r = 0.9749, p < 0.001) compared to contrast-enhanced MSCT. MRI in evaluating the depth of invasion in SCC of the tongue demonstrated a higher result, complementing information about the extent of the tumor process and clarifying the stage of the disease, which is crucial for selecting the optimal treatment strategy.

Conclusion. Thus, in measuring the depth of invasion in SCC of the tongue, the sensitivity and specificity for MSCT were 85.7% and 90.9%, respectively, while for MRI, the sensitivity and specificity made up 93.3% and 88.9%, respectively, confirming the high efficacy of MRI in examination of the oropharyngeal area. 

Purpose of the study: to improve the reliability of prediction of lymphovascular invasion (LVI) by hybrid morpho-radiomic naive Bayesian models in patients with malignant breast cancer (MBC) by elucidating the role of morphologic magnetic resonance (m-MR) features.

Materials and Methods. Data from 191 patients with MBC were analyzed in the form of 13 m-MR features, 6194 radiomic MR (r-MR) indicators of the whole tumor volume, and the target feature, LVI. Among the m-MR features, predictors of LVI were selected using crosstabulation, multivariate logistic regression, and Entropy-MDL discretization. Among 6194 r-MR indicators, predictors of LVI were selected by Entropy-MDL discretization. The selected indicators were used in training the naive Bayes algorithm. The performance of LVI predictors was compared.

Results. According to multivariate logistic regression, the odds of LVI increased when tumor rim feature was detected on DWI image 4.05-fold (OR 4.05, 95%CI: 1.63–10.47, p = 0.003), peritumoral edema 5.66-fold (OR 5.66, 95%CI: 2.27–14.94, p < 0.001). 3 hybrid models with high discriminatory abilities were obtained: 1 model with DWI rim and radiomic signature from 4 p-MR indicators (AUC = 0.886, sensitivity – 89.5%, specificity – 79.1%, classification correctness – 89.5%, correctness of prediction of LVI – 73.3% and its absence – 95.2%), 2 model with peritumoral edema and radiomic signature from 6 p-MR indicators (AUC = 0.879, sensitivity – 82.5%, specificity – 80,9%, classification correctness – 82.5%, correctness in predicting LVI – 80.0% and its absence – 83.3%) and 3 models with peritumoral edema, rim DWI sign and radiomic signature from 8 p-MR indicators (AUS = 0.957, sensitivity – 96.5%, specificity – 90.2%, classification correctness – 96.5%, correctness in predicting LVI – 86.7% and its absence – 100%). Removing the DWI rim feature from 1 model worsens its discriminatory power (AUC-ROC, 0.801 ± 0.074 vs 0.886 ± 0.059, p = 0.001) and correctness of LVI prediction (40 vs 73%, p = 0.066). Similar but less pronounced, non-statistically significant changes were observed after removal of the peritumoral edema feature from the 2 models (AUC-ROC, 0.843 ± 0.067 vs 0.879 ± 0.060, p = 0.190; LVI prediction correctness, 60 vs 80%, p = 0.232). Removing 2 m-MR features from the 3 model worsens its discriminatory power (AUC-ROC, 0.957 ± 0.038 vs 0.901 ± 0.055, p = 0.024) and correctness of LVI prediction (80 vs 86.7%, p = 0.624).

Conclusion. The use of hybrid models combining m-MR traits and r-MR indices improve the discriminatory power of prediction compared to models using only intratumoral r-MR indices.