Phosphaturic mesenchymal tumor-mixed connective tissue (PMT-MCT) is rare and usually benign and slow-growing. The majority of these tumors is associated with sporadic tumor-induced osteomalacia (TIO) or rickets, affect middle-aged individuals and are located in the extremities. Previous imaging studies often focused on seeking the causative tumors of TIO, not on the radiological features of these tumors, especially magnetic resonance imaging (MRI) features. PMT-MCT remains a largely misdiagnosed, ignored or unknown entity by most radiologists and clinicians. In the present case report, a review of the known literature of PMT-MCT was conducted and the CT and MRI findings from three patient cases were described for diagnosing the small subcutaneous tumor. Typical MRI appearances of PMT-MCT were isointense relative to the muscles on T1-weighted imaging, and markedly hyperintense on T2-weighted imaging containing variably flow voids, with markedly heterogeneous/homogenous enhancement on post contrast T1-weighted fat-suppression imaging. Short time inversion recovery was demonstrated to be the optimal sequence in localizing the tumor.
Abstract. Patients with renal medullary carcinoma (RMC) have a poor prognosis, usually due to late diagnosis. Computed tomography (CT) analysis may aid the differentiation between RMC and other types of renal cell carcinoma, in order to establish an accurate early diagnosis. There is a limited number of reports in the literature focusing on clinical and multi-slice CT (MSCT) imaging findings of RMC. Consequently, the present study aimed to characterize the clinical and MSCT imaging features of RMC. For this purpose, the MSCT imaging findings of 6 patients with RMC were retrospectively studied. The patients were subjected to MSCT in order to investigate the characteristics of the tumors, including location, size, density, calcification, cystic or solid appearance, capsule sign, enhancement pattern and presence of retroperitoneal lymph node metastasis. The tumors in the current study presented a mean diameter of 7.48±3.25 cm, and were observed to be solitary and heterogeneous with necrotic components. The majority of the tumors did not contain calcifications (5/6); displayed an ill-defined margin (4/6); were centered in the medulla; extended into the renal pelvis or peripelvic tissues (6/6); and did not exhibit a fibrous capsule. Localized caliectasis was observed in 3 of the 6 cases. The attenuation of the solid region of the RMC on unenhanced CT was equal to that of the renal cortex or medulla (42.3±2.7 vs. 40.7±3.6 and 41.2±3.9 Hounsfield units, respectively; P>0.05) while, on enhanced CT, the enhancement of the tumor was lower than that of the normal renal cortex and medulla during all phases (cortical phase, 52.6±4.8 vs. l99.5±9.7 and 72.7±6.4; medullary phase, 58.6±5.7 vs. 184.6±10.8 and 93.5±7.8; delayed phase, 56.8±6.1 vs. 175.7±8.5 and 96.5±7.9, respectively; P<0.05).In conclusion, RMC tends to be an infiltrative, ill-defined heterogeneous mass with intratumoral necrosis, which arises from the renal medulla, and displays lower enhancement than the renal cortex and medulla during all phases on enhanced CT. Despite its rarity in adults, RMC should be included in a differential diagnosis when CT imaging reveals these features.
BackgroundPatients with small hepatocellular carcinoma (HCC) (≤3 cm) still have a poor prognosis. The purpose of this study was to develop a radiomics nomogram to preoperatively predict early recurrence (ER) (≤2 years) of small HCC.MethodsThe study population included 111 patients with small HCC who underwent surgical resection (SR) or radiofrequency ablation (RFA) between September 2015 and September 2018 and were followed for at least 2 years. Radiomic features were extracted from the entire tumor by using the MaZda software. The least absolute shrinkage and selection operator (LASS0) method was applied for feature selection, and radiomics signature construction. A rad-score was then calculated. Multivariable logistic regression analysis was used to establish a prediction model including independent clinical risk factors, radiologic features and rad-score, which was ultimately presented as a radiomics nomogram. The predictive ability of the nomogram was evaluated using the area under the receiver operating characteristic (ROC) curve and internal validation was performed via bootstrap resampling and 5-fold cross-validation method.ResultsA total of 53 (53/111, 47.7%) patients had confirmed ER according to the final clinical outcomes. In univariate logistic regression analysis, cirrhosis and hepatitis B infection (P=0.015 and 0.083, respectively), hepatobiliary phase hypointensity (P=0.089), Child-Pugh score (P=0.083), the preoperative platelet count (P=0.003), and rad-score (P<0.001) were correlated with ER. However, after multivariate logistic regression analysis, only the preoperative platelet count and rad-score were included as predictors in the final model. The area under ROC curve (AUC) of the radiomics nomogram to predict ER of small HCC was 0.981 (95% CI: 0.957, 1.00), while the AUC verified by bootstrap is 0.980 (95% CI: 0.962, 1.00), indicating the goodness-of-fit of the final model.ConclusionsThe radiomics nomogram containing the clinical risk factors and rad-score can be used as a quantitative tool to preoperatively predict individual probability of ER of small HCC.
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