T2-weighted Features Research Articles

Prognostic Value of Hybrid PET/MR Imaging in Patients with Differentiated Thyroid Cancer.

Simple SummaryHybrid positron emission tomography (PET)/magnetic resonance (MR) is an emerging imaging modality with great potential to provide complementary data acquired at the same time, under the same physiological conditions. We evaluated the prognostic value of hybrid 18F-fluorodeoxyglucose (FDG) PET/MR in patients with differentiated thyroid cancer (DTC) who underwent total thyroidectomy and radioactive iodine therapy for suspicion of disease relapse. Our findings suggest that hybrid PET/MR imaging may have the potential to improve the information content of one modality with the other and would offer new opportunities in patients with DTC. However, there is need of more clinical studies to understand the additional value of 18F-FDG PET/MR in patients with DTC.Background: Hybrid positron emission tomography (PET)/magnetic resonance (MR) is an emerging imaging modality with great potential to provide complementary data acquired at the same time, under the same physiological conditions. The aim of this study was to evaluate the prognostic value of hybrid 18F-fluorodeoxyglucose (FDG) PET/MR in patients with differentiated thyroid cancer (DTC) who underwent total thyroidectomy and radioactive iodine therapy for suspicion of disease relapse. Methods: Between November 2015 and February 2017, 55 patients underwent hybrid 18F-FDG PET/MR. Assessment of positive MR was made considering all sequences in terms of malignancy based on the morphological T2-weighted features and the presence of restricted diffusivity on diffusion-weighted imaging images and both needed to be positive on the same lesion. Both foci with abnormal 18F-FDG uptake, which corresponded to tissue abnormalities on the MR, and tracer accumulation, which did not correspond to normal morphological structures, were considered positive. Results: During follow-up (mean 42 ± 27 months), 29 patients (53%) had disease recurrence. In the Cox univariate regression analysis age, serum Tg level ≥ 2 ng/mL, positive short tau inversion recovery (STIR), and positive PET were significant predictors of DTC recurrence. Kaplan–Meier survival analyses showed that patients with Tg ≥ 2 ng/mL had poorer outcomes compared to those with serum Tg level < 2 ng/mL (p < 0.05). Similarly, patients with positive STIR and positive PET had a worst outcome compared to those with negative STIR (p < 0.05) and negative PET (p < 0.005). Survival analysis performed in the subgroup of 36 subjects with Tg level ≥ 2 ng/mL revealed that patients with positive PET had a worst outcome compared to those with negative PET (p < 0.05). Conclusions: Age, serum Tg level ≥ 2 ng/mL, positive STIR, and positive 18F-FDG PET were significant predictors of DTC recurrence. However, the serum Tg level was the only independent predictor of DTC. Hybrid PET/MR imaging may have the potential to improve the information content of one modality with the other and would offer new opportunities in patients with DTC. Thus, further studies in a larger patient population are needed to understand the additional value of 18F-FDG PET/MR in patients with DTC.

Enhancement patterns of adrenal nodules on magnetic resonance imaging.

ABSTRACTObjective:To compare enhancement patterns of typical adrenal adenomas, lipid-poor adenomas, and non-adenomas on magnetic resonance imaging (MRI).Materials and Methods:Evaluation of adrenal nodules larger than 1.0 cm, with at least 2-year follow-up, evaluated on MRI in January 2007 and December 2016. Two different protocols were included - upper abdomen MRI (delayed phase after 3 minutes) and abdomen and pelvis MRI (delayed phase after 7 minutes) – and nodules were divided in typical adenomas (characterized on out-of-phase MRI sequence), lipid-poor adenomas (based on follow-up imaging stability) and non-adenomas (based on pathological finding or follow-up imaging). T2-weighted and enhancement features were analyzed (absolute and relative washout and enhancement curve pattern), similarly to classic computed tomography equations.Results:Final cohort was composed of 123 nodules in 116 patients (mean diameter of 1.8 cm and mean follow up time of 4 years and 3 months). Of them, 98 (79%) nodules had features of typical adenomas by quantitative chemical shift imaging, and demonstrated type 3 curve pattern in 77%, mean absolute and relative washout of 29% and 16%, respectively. Size, oncologic history and T2-weighted features showed statistically significant differences among groups. Also, a threshold greater than 11.75% for absolute washout on MRI achieved sensitivity of 71.4% and specificity of 70.0%, in differentiating typical adenomas from non-adenomas.Conclusion:Calculating absolute washout of adrenal nodules on MRI may help identifying proportion of non-adenomas.

Thin-Slice Magnetic Resonance Imaging-Based Radiomics Signature Predicts Chromosomal 1p/19q Co-deletion Status in Grade II and III Gliomas.

Objective: Chromosomal 1p/19q co-deletion is recognized as a diagnostic, prognostic, and predictive biomarker in lower grade glioma (LGG). This study aims to construct a radiomics signature to non-invasively predict the 1p/19q co-deletion status in LGG.Methods: Ninety-six patients with pathology-confirmed LGG were retrospectively included and randomly assigned into training (n = 78) and validation (n = 18) dataset. Three-dimensional contrast-enhanced T1 (3D-CE-T1)-weighted magnetic resonance (MR) images and T2-weighted MR images were acquired, and simulated-conventional contrast-enhanced T1 (SC-CE-T1)-weighted images were generated. One hundred and seven shape, first-order, and texture radiomics features were extracted from each imaging modality and selected using the least absolute shrinkage and selection operator on the training dataset. A 3D-radiomics signature based on 3D-CE-T1 and T2-weighted features and a simulated-conventional (SC) radiomics signature based on SC-CE-T1 and T2-weighted features were established using random forest. The radiomics signatures were validated independently and evaluated using receiver operating characteristic (ROC) curves. Tumors with IDH mutations were also separately assessed.Results: Four radiomics features were selected to construct the 3D-radiomics signature and displayed accuracies of 0.897 and 0.833, areas under the ROC curves (AUCs) of 0.940 and 0.889 in the training and validation datasets, respectively. The SC-radiomics signature was constructed with 4 features, but the AUC values were lower than that of the 3D signature. In the IDH-mutated subgroup, the 3D-radiomics signature presented AUCs of 0.950–1.000.Conclusions: The MRI-based radiomics signature can differentiate 1p/19q co-deletion status in LGG with or without predetermined IDH status. 3D-CE-T1-weighted radiomics features are more favorable than SC-CE-T1-weighted features in the establishment of radiomics signatures.

Differentiation of transitional zone prostate cancer from benign hyperplasia nodules: Evaluation of discriminant criteria at multiparametric MRI

To assess topographical and magnetic resonance imaging (MRI) features in characterizing prostate transitional zone (TZ) nodules. Two radiologists evaluated all TZ nodules visible at multiparametric MRI in 52 consecutive patients who underwent radical prostatectomy. The radiologists assessed topographical (anteroposterior and superior-inferior location, crossing of the sagittal midline) and T2-weighted (shape, presence and distinctness of capsule, distinctness of contours, presence of cysts) features, the apparent diffusion coefficient (ADC), and eight semi-quantitative and quantitative enhancement parameters derived from dynamic contrast-enhanced (DCE) imaging. The nature of the nodules was assessed using prostatectomy specimens. Five statistical methods taking into account multiple testing were used. One hundred and thirty-seven nodules (117 benign, 20 malignant) were evaluated. Mean ADC, all topographical, and all T2-weighted features were significant predictors of malignancy according to at least four out of the five statistical methods. Particularly, 20/20 and 18/20 cancers involved the anterior and apical third of the TZ, respectively. None of the enhancement parameters was significantly different between cancers and benign nodules. By assessing the presence of cysts, the nodules' capsule, and their anteroposterior and superior-inferior location, 111/117 benign nodules were correctly diagnosed, without misclassifying any cancer. Topographical, T2-weighted, and diffusion-weighted features can be used to characterize TZ nodules. DCE imaging does not seem to provide additional information.

Combined use of T2‐weighted MRI and T1‐weighted dynamic contrast–enhanced MRI in the automated analysis of breast lesions

A multiparametric computer-aided diagnosis scheme that combines information from T1-weighted dynamic contrast-enhanced (DCE)-MRI and T2-weighted MRI was investigated using a database of 110 malignant and 86 benign breast lesions. Automatic lesion segmentation was performed, and three categories of lesion features (geometric, T1-weighted DCE, and T2-weighted) were automatically extracted. Stepwise feature selection was performed considering only geometric features, only T1-weighted DCE features, only T2-weighted features, and all features. Features were merged with Bayesian artificial neural networks, and diagnostic performance was evaluated by ROC analysis. With leave-one-lesion-out cross-validation, an area under the ROC curve value of 0.77±0.03 was achieved with T2-weighted-only features, indicating high diagnostic value of information in T2-weighted images. Area under the ROC curve values of 0.79±0.03 and 0.80 ± 0.03 were obtained for geometric-only features and T1-weighted DCE-only features, respectively. When all features were considered, an area under the ROC curve value of 0.85±0.03 was achieved. We observed P values of 0.006, 0.023, and 0.0014 between the geometric-only, T1-weighted DCE-only, and T2-weighted-only features and all features conditions, respectively. When ranked, the P values satisfied the Holm-Bonferroni multiple-comparison test; thus, the improvement of multiparametric computer-aided diagnosis was statistically significant. A computer-aided diagnosis scheme that combines information from T1-weighted DCE and T2-weighted MRI may be advantageous over conventional T1-weighted DCE-MRI computer-aided diagnosis.